Sugarcane
ethanol
Contributions to climate change mitigation and the environment
edited by:
Peter Zuurbier
Jos van de Vooren
Wageningen Academic
P u b l i s h e r s
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ISBN 978-90-8686-090-6
First published, 2008
Wageningen Academic Publishers
The Netherlands, 2008
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Table of contents
Foreword
José Goldemberg, professor at the University of São Paulo, Brazil
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Executive summary
15
Chapter 1 Introduction to sugarcane ethanol contributions to climate change
mitigation and the environment
Peter Zuurbier and Jos van de Vooren
1. Introduction
2. Biofuels
3. Bioethanol
4. Production and use of bioethanol
5. Where does it come from: the feedstock for ethanol
6. Brazil as main exporter
7. What makes the ethanol attractive?
8. The core of the debate
9. Structure of the book
References
Chapter 2 Land use dynamics and sugarcane production
Günther Fischer, Edmar Teixeira, Eva Tothne Hizsnyik and Harrij van Velthuizen
1. Historical scale and dynamics of sugarcane production
2. Global potential for expansion of sugarcane production
References
Chapter 3 Prospects of the sugarcane expansion in Brazil: impacts on direct
and indirect land use changes
André Meloni Nassar, Bernardo F.T. Rudorff, Laura Barcellos Antoniazzi, Daniel
Alves de Aguiar, Miriam Rumenos Piedade Bacchi and Marcos Adami
1. Introduction
2. The dynamics of sugarcane expansion in Brazil
3. Methodology
4. Results and discussions
5. Conclusions and recommendations
References
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Chapter 4 Mitigation of GHG emissions using sugarcane bioethanol
Isaias C. Macedo and Joaquim E.A. Seabra
1. Introduction
2. Ethanol production in 2006 and two Scenarios for 2020
3. Energy flows and lifecycle GHG emissions/mitigation
4. Land use change: direct and indirect effects on GHG emissions
5. Conclusions
References
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102
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Chapter 5 Environmental sustainability of sugarcane ethanol in Brazil
Weber Antônio Neves do Amaral, João Paulo Marinho, Rudy Tarasantchi, Augusto
Beber and Eduardo Giuliani
1. Introduction
2. The Brazilian environmental legal framework regulating ethanol production
3. Environmental indicators
4. Initiatives towards ethanol certification and compliance
5. Future steps towards sustainable production of ethanol and the role of
innovation
References
113
Chapter 6 Demand for bioethanol for transport
Andre Faaij, Alfred Szwarc and Arnaldo Walter
1. Introduction
2. Development of the ethanol market
3. Drivers for ethanol demand
4. Future ethanol markets
5. Discussion and final remarks
References
139
Chapter 7 Biofuel conversion technologies
Andre Faaij
1. Introduction
2. Long term potential for biomass resources.
3. Technological developments in biofuel production
4. Energy and greenhouse gas balances of biofuels
5. Final remarks
References
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Sugarcane ethanol
Chapter 8 The global impacts of US and EU biofuels policies
Wallace E. Tyner
1. Introduction
2. Ethanol economics and policy
3. Impacts of US and EU policies on the rest of the world
4. Conclusions
Acknowledgements
References
Chapter 9 Impacts of sugarcane bioethanol towards the Millennium
Development Goals
Annie Dufey
1. Introduction
2. Opportunities for sugarcane bioethanol in achieving sustainable
development and the Millennium Development Goals
3. Risks and challenges
4. Conclusions
References
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Chapter 10 Why are current food prices so high?
Martin Banse, Peter Nowicki and Hans van Meijl
1. World agricultural prices in a historical perspective
2. Long run effects
3. What explains the recent increase in agricultural prices?
4. First quantitative results of the analysis of key driving factors
5. The future
6. Concluding remarks
Acknowledgements
References
227
Acknowledgements
Peter Zuurbier and Jos van de Vooren
249
Authors
251
Keyword index
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9
Foreword
José Goldemberg, professor at the University of São Paulo, Brazil
Ethanol, produced from biomass, has been considered as a suitable automobile fuel since
the beginning of the automotive industry one century ago, particularly for vehicles powered
with spark-ignition engines (technically referred as Otto cycle engines, but commonly
known as gasoline engines). However, the use of ethanol was dwarfed by gasoline refined
from abundant and cheap oil. The staggering amounts of gasoline in use today – more than
1 trillion litres per year – eliminated almost all the alternatives.
However environmental as well as security of supply concerns sparked, in the last decades,
renewed interest in ethanol. In many countries it is blended with gasoline in small amounts
to replace MTBE. In Brazil it has already replaced 50% of the gasoline thanks to the use of
flex-fuel engines or dedicated pure ethanol motors. Worldwide ethanol is replacing already
3% of the gasoline.
Maize (in the US) and sugarcane (in Brazil) account for 80% of all ethanol in use today. The
agricultural area used for that purpose amounts to 10 million hectares less than 1% of the
arable land in use in the world.
There are three main routes to produce ethanol from biomass:
• fermentation of sugar from sugarcane, sugar beet and sorghum;
• saccharification of starch from maize, wheat and manioc;
• hydrolysis of cellulosic materials, still in development.
There are important differences between the fermentation and saccharification routes. When
using sugarcane one does not need an ‘external’ source of energy for the industrial phase of
ethanol production since the bagasse supplies all the energy needed. The fossil fuel inputs
are small (in the form of fertilizers, pesticides, etc.) so basically this route converts solar
energy into ethanol. The final product is practically a renewable fuel contributing little to
greenhouse gas (GHG) emissions.
Ethanol from maize and other feed stocks requires considerable inputs of ‘external’ energy
most of it coming from fossil fuels reducing only marginally GHG emissions.
Sugarcane grows only in tropical areas and the Brazilian experience in this area led to ethanol
produced at very low cost and competitive with gasoline through gains in productivity and
economies of scale (Goldemberg, 2007). Ethanol produced from maize in the US cost almost
twice and from wheat, sugar beets, sorghum (mainly in Europe) four times (Worldwatch
Institute, 2006).
Sugarcane ethanol
11
Foreword
The use of biofuels as a substitute for gasoline has been recently criticized mainly for:
• sparking a competition between the use of land for fuel ‘versus’ land for food which is
causing famine in the world and
• leading to deforestation in the Amazonia.
The importance of these concerns was greatly exaggerated and is, generally speaking,
unwarranted.
The recent rise in prices of agricultural products – after several decades of declining real
prices – has given rise to the politically laden controversy of fuel ‘versus’ food. This problem
has been extensively analyzed in many reports, particularly the World Bank (World Bank,
2008), which pointed out that grain prices have risen due to a number of individual factors,
whose combined effect has led to an upward price spiral namely: high energy and fertilizer
prices, the continuing depreciation of the US dollar, drought in Australia, growing global
demand for grains (particularly in China), changes in import-export policies of some
countries and speculative activity on future commodities trading and regional problems
driven by policies subsidizing production of biofuels in the US and Europe (from maize,
sugar beets and wheat). The expansion of biofuels production particularly from maize
over areas covered by soybeans in the US contributed to price increases but was not the
dominant factor. The production of ethanol from sugarcane in Brazil has not influenced
the prize of sugar.
Despite that, the point has been made that other countries had to expand soybean production
to compensate for reductions in the US production possibly in the Amazonia, increasing thus
deforestation. Such speculative ‘domino effect’ is not borne out by the facts: the area used
for soybeans in Brazil (mainly in the Amazonia) has not increased since 2004 (Goldemberg
and Guardabassi, in press). The reality is that deforestation in the Amazonia has been going
on for a long time at a rate of approximately 1 million hectares per year and recent increases
are not due to soybean expansion but to cattle.
Emissions from land use changes resulting from massive deforestation would of course
release large amounts of CO2 but the expansion of the sugarcane plantations in Brazil is
taking place over degraded pastures very far from the Amazonia. Emissions from such land
use change have been shown to be small (Cerri et al., 2007).
The present area used of sugarcane for ethanol production in Brazil today is approximately
4 million hectares out of 20 million hectares used in the world by sugarcane in almost
100 countries. Increasing the areas used for of sugarcane for ethanol production in these
countries by 10 million hectares would result in enough ethanol to replace 10% of the
gasoline in the world leading to a reduction of approximately 50 million tons of carbon
per year. This would help significantly many OECD countries to meet the policy mandates
adopted for the use of biofuels.
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Sugarcane ethanol
Foreword
Such course of action would of course require a balanced weighting of the advantages of
replacing gasoline by a renewable fuel and impacts and land use and biodiversity.
This book analyzes all these aspects of the problem and will certainly be an important
instrument to clarify the issues, dispel some myths and evaluate the consequence of different
policy choices.
References
Cerri, C.E.P., M. Easter, K. Paustian, K. Killian, K. Coleman, M. Bernoux, P. Falloon, D.S. Powlson, N.H.
Batjes, E. Milne and C.C. Cerri, 2007. Predicted soil organic carbon stocks and changes in the Brazilian
Amazon between 2000 and 2030. Agriculture, Ecosystems and Environment 122: 58-72.
Goldemberg, J., 2007. Ethanol for a Sustainable Energy Future. Science 315: 808-810.
Goldemberg, J., S.T. Coelho and P. Guardabassi, 2008. The sustainablility of ethanol production from
sugarcane. Energy Policy 36: 2086-2097.
Worldwatch Institute, 2006. Biofuels for transport: Global Potential and Implications for Sustainable
Agriculture and Energy in 21st Century. ISBN 978-1-84407-422-8
World Bank, 2008. Double Jeopardy: Responding to high Food and Fuel Prices. G8 Hokkaido – Toyako
Summit. July 2, 2008.
Sugarcane ethanol
13
Executive summary
Do biofuels help to reduce greenhouse gas emissions and do they offer new sources of
income to farmers, by producing biomass? Are biofuels competing with food, animal feed
and contributing to higher food prices? And are biofuels directly or indirectly threatening
the environment, biodiversity, causing irreversible or undesirable changes in land use and
landscape?
This publication aims to set the stage for the discussion about both challenges and
concerns of sugarcane ethanol by providing the scientific context, the basic concepts and
the approach for understanding the debate on biofuel-related issues. This book largely
limits itself to sugarcane ethanol and its contribution to climate change mitigation and the
environment.
The main findings and conclusions are:
1. The dominance of Brazil in global sugarcane production and expansion – Brazil
accounted for 75 percent of sugarcane area increase in the period 2000 to 2007 and
two-thirds of global production increase in that period – derives from its experience
and capability to respond to thriving demand for transport fuels, which was recently
triggered by measures to mitigate greenhouse gas emissions of the rapidly growing
transport sector, concerns in developed countries to enhance energy security and lessen
dependence on petroleum, and not the least the need of many developing countries to
reduce import bills for fossil oil.
2. According to the IIASA/AEZ assessment, the most suitable climates for rain-fed
sugarcane production are found in south-eastern parts of South America, e.g. including
São Paulo State in Brazil, but also large areas in Central Africa as well as some areas in
Southeast Asia. The massive further expansion of sugarcane areas, e.g. as forecasted for
Brazil, is expected to cause the conversion of pastoral lands in the savannah region.
3. This study analyzes the land use changes (LUC) in Brazil caused by sugarcane expansion,
looking both at the past and expected future dynamics. Remote sensing images have
identified that in 2007 and 2008 Pasture and Agriculture classes together were responsible
for almost 99% of the total area displaced for sugarcane expansion which equals an
area of more than 2 million ha. Pasture was responsible for approximately 45% and
Agriculture was responsible for more than 50% of the displaced area for sugarcane.
About 1% of sugarcane expansion took place over the Citrus class and less than 1% over
the Reforestation and Forest classes together. Pasture displacement is more important
in São Paulo and Mato Grosso do Sul, while Agriculture is more important in the other
states analyzed.
4. The shift-share model using IBGE micro-regional data has analyzed sugarcane expansion
from 2002 to 2006 and has identified around 1 million ha in the ten Brazilian states
analyzed. From this total expansion, 773 thousand ha displaced pasture land and 103
thousands displaced other crops, while only 125 thousand ha were not able to be allocated
Sugarcane ethanol
15
Executive summary
over previous productive areas (meaning new land has been incorporated into agricultural
production, which might be attributed to the conversion of forest to agriculture or to
the use of previously idle areas). Total agricultural area growth – the sum of all crops,
including sugarcane, and pastures – in the period was around 3.3 million ha.
5. Projections indicate that harvested sugarcane area in Brazil will reach 11.7 million ha and
other crops 43.8 million ha in 2018, while pasture area will decrease around 3 million
ha. The total land area in Brazil is 851.196.500 ha.
6. The expansion of crops, except sugarcane, and pasture land is taking place despite of the
sugarcane expansion. This is important because it reinforces that, even recognizing that
sugarcane expansion contributes to the displacement of other crops and pasture, there
is no evidence that deforestation caused by indirect land use effect is a consequence of
sugarcane expansion.
7. Sugarcane ethanol from Brazil does comply with the targets of greenhouse gases (GHG)
reduction.
8. The GHG emissions and mitigation from fuel ethanol production/use in Brazil are
evaluated for the 2006/07 season, and for two scenarios for 2020: the 2020 Electricity
Scenario (already being implemented) aiming at increasing electricity surplus with
cane biomass residues; and the 2020 Ethanol Scenario using the residues for ethanol
production. Emissions are evaluated from cane production to ethanol end use; process
data was obtained from 40 mills in Brazilian Centre South. Energy ratios grow from 9.4
(2006) to 12.1 (2020, the two Scenarios); and the corresponding GHG mitigation increase
from 79% (2006) to 86% (2020) if only the ethanol is considered. With co-products
(electricity) it would be 120%. LUC derived GHG emissions were negative in the period
2002 – 2008, and very little impact (if any) is expected for 2008 – 2020, due mostly to the
large availability of land with poor carbon stocks. Although indirect land use changes
(ILUC) impacts cannot be adequately evaluated today, specific conditions in Brazil may
lead to significant increases in ethanol production without positive ILUC emissions.
9. Brazil has achieved very high levels of productivity (on average 7.000 litres of ethanol/ha
and 6,1 MWhr of energy/ha), despite its lower inputs of fertilizers and agrochemicals
compared with other biofuels, while reducing significantly the emissions of greenhouse
gases. The ending of sugarcane burning in 2014 is a good example of improving existing
practices.
10. Production of ethanol in Brazil, which has been rising fast, is expected to reach 70 billion
litres by the end of 2008. Approximately 80% of this volume will be used in the transport
sector while the rest will go into alcoholic beverages or will be either used for industrial
purposes (solvent, disinfectant, chemical feedstock, etc.).
11. When evaluating key drivers for ethanol demand, energy security and climate change
are considered to be the most important objectives reported by nearly all countries that
engage in bioenergy development activities. A next factor is the growth in demand for
transport fuels. A third factor is vehicle technologies that already enable large scale use
of ethanol.
16
Sugarcane ethanol
Executive summary
12. Projections of ethanol production for Brazil, the USA and the EU indicate that supply
of 165 billion litres by 2020 could be achieved with the use of a combination of first and
second generation ethanol production technologies.
13. Compared to current average vehicle performance, considerable improvements are
possible in drive chain technologies and their respective efficiencies and emission profiles.
IEA does project that in a timeframe towards 2030, increased vehicle efficiency will play
a significant role in slowing down the growth in demand for transport fuels. With further
technology refinements, which could include direct injection and regenerative breaking,
fuel ethanol economy of 24 km/litre may be possible. Such operating conditions, can
also deliver very low emissions.
14. Future ethanol markets could be characterized by a diverse set of supplying and producing
regions. From the current fairly concentrated supply (and demand) of ethanol, a future
international market could evolve into a truly global market, supplied by many producers,
resulting in stable and reliable biofuel sources. This balancing role of an open market and
trade is a crucial precondition for developing ethanol production capacities worldwide.
15. However, the combination of lignocellulosic resources (biomass residues on shorter
term and cultivated biomass on medium term) and second generation conversion
technology offers a very strong perspective. Also, the economic perspectives for such
second generation concepts are very strong, offering competitiveness with oil prices
equivalent to some 55 US$/barrel around 2020.
16. First generation biofuels in temperate regions (EU, North America) do not offer a
sustainable possibility in the long term: they remain expensive compared to gasoline and
diesel (even at high oil prices), are often inefficient in terms of net energy and GHG gains
and have a less desirable environmental impact. Furthermore, they can only be produced
on higher quality farmland in direct competition with food production. Sugarcane based
ethanol production and to a certain extent palm oil and Jatropha oilseeds are notable
exceptions to this, given their high production efficiencies and low(er) costs.
17. Especially promising are the production via advanced conversion concepts biomassderived fuels such as methanol, hydrogen, and ethanol from lignocellulosic biomass.
Ethanol produced from sugarcane is already a competitive biofuel in tropical regions
and further improvements are possible. Both hydrolysis-based ethanol production
and production of synthetic fuels via advanced gasification from biomass of around 2
Euro/GJ can deliver high quality fuels at a competitive price with oil down to US$55/
barrel. Net energy yields per unit of land surface are high and up to a 90% reduction in
GHG emissions can be achieved. This requires a development and commercialization
pathway of 10-20 years, depending very much on targeted and stable policy support and
frameworks.
18. Global land use changes induced by US and EU biofuels mandates show that when it
comes to the assessing the impacts of these mandates on third economies, the combined
policies have a much greater impact than just the US or just the EU policies alone, with
crop cover rising sharply in Latin America, Africa and Oceania as a result of the biofuel
Sugarcane ethanol
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Executive summary
mandates. These increases in crop cover come at the expense of pasturelands (first and
foremost) as well as commercial forests.
19. Sugarcane based ethanol can contribute to the achievement of several Millennium
Development Goals through a varied range of environmental, social and economic
advantages over fossil fuels. These include enhanced energy security both at national
and local level; improved trade balance by reducing oil imports; improved social wellbeing through better energy services especially among the poorest; promotion of rural
development and better livelihoods; product diversification leaving countries betteroff to deal with market fluctuations; the creation of new exports opportunities; the
potential to help tackling climate change through reduced emissions of greenhouse
gases as well as other air emissions; and opportunities for investment attraction through
the carbon finance markets. The highest impact on poverty reduction is likely to occur
where sugarcane ethanol production focuses on local consumption, involving the
participation and ownership of small farmers and where processing facilities are near
to the cultivation fields.
20. Development of oil prices is crucial for the development of biofuels. High feedstock
prices make biofuels less profitable. Hence, price hikes for commodities have a negative
impact on bioethanol prices. Other factors, like stock level, price speculation, expected
policy measures and natural disasters may add to price volatility as well.
The final conclusion is that sugarcane ethanol contributes to mitigation of climate change.
The environmental impacts of sugarcane ethanol production are overall positive within
certain conditions, as outlined in this publication, For advancing the sustainable sugarcane
ethanol production, it is of importance to enhance a process of dialogue in the market place
and between interested stakeholders in society.
18
Sugarcane ethanol
Chapter 1
Introduction to sugarcane ethanol contributions to climate
change mitigation and the environment
Peter Zuurbier and Jos van de Vooren
1. Introduction
Life is energy. Humankind depends on energy and produces and consumes large volumes of
energy. The total final energy consumption in industry, households, services and transport
in 2005 was 285 EJ (OECD/IEA, 2008). And the consumption is growing fast. The growth
of global final energy between 1990 and 2005 was 23%. Globally, energy consumption grew
most quickly in the transport and service sectors. Between 1990 and 2005, global final
energy use in transport increased by 37% to 75 EJ and according to the IEA study, road
transport contributes the most to the increase in overall transport energy consumption.
Between 1990 and 2005, road transport energy use increased by 41%. And with this growth,
CO2 emissions increased as well. These emissions grew during that same period with 25%
(IEA, 2008). The associated CO2 emissions increased to 5.3 Gt CO2. There is a widely shared
opinion that these emissions contribute to global warming and climate change. Reason
enough for making a change.
Another reason for making a change, are the fossil oil prices. Fact is that the price increased
from $20 in 2002 to a record high of more than $140 a barrel in July 2008. The price
volatility creates a lot of uncertainty in global markets. So, it is not surprising that the world
is looking for substitutes for petroleum-derived products. Securing a reliable, constant and
sustainable supply of energy demands a diversification of energy sources and an efficient
use of available energy.
One of the alternatives for fossil fuels is biofuels. And here we enter in to the heat of the
debate. Do biofuels help to reduce greenhouse gas emissions and offering new sources of
income to farmers, by producing biomass? Are biofuels competing with food, animal feed
and contributing to higher food prices? And are biofuels directly or indirectly threatening
the environment, biodiversity, causing irreversible or undesirable changes in land use and
landscape?
In this publication we aim to set the stage for the discussion about both challenges and
concerns of sugarcane ethanol by providing the scientific context, the basic concepts and
the approach for understanding the debate on biofuel-related issues. This book largely
limits itself to sugarcane ethanol and its contribution to climate change mitigation and
the environment.
Sugarcane ethanol
19
Chapter 1
2. Biofuels
Biofuels encompass a variety of feedstock, conversion technologies, and end uses. They are
used mostly for transport and producing electricity. Biofuels for transportation, like ethanol
and biodiesel, are one of the fastest-growing sources of alternative energy in the world
today. Global production of biofuels amounted to 62 billion litres or 36 million tonnes of
oil equivalent (Mt) in 2007 - equal to about 2 % of total global transport fuel consumption
in energy terms (OESO, 2008).
3. Bioethanol
Global bioethanol production tripled from its 2000 level and reached 52 billion litres
(28.6 Mt) in 2007 (OESO, 2008). Based on the origin of supply, Brazilian ethanol from
sugarcane and American ethanol from maize are by far leading the ethanol production. In
2007 Brazil and the United States together accounted for almost 90% of the world ethanol
production.
In Brazil production of ethanol, entirely based on sugarcane (Saccharum spp.), started in the
seventies and peaked in the 1980s, then declined as international fossil oil prices fell back,
but increased rapidly again since the beginning of the 21st century. Falling production costs,
higher oil prices and the introduction of vehicles that allow switching between ethanol and
conventional gasoline have led to this renewed surge in output.
In the crop season 2007/08 Brazil produced 22.24 billion litres of ethanol. Conab/AgraFNP
expects another jump for the crop season 2008/09 with an expected production of 26.7
billion litres (AgraFNP, 2008). This increase is mainly due to expansion of the sugarcane
area. In 2007/08 the area for sugarcane was 6.96 million hectare, and is estimated to grow
to 7.67 million hectare in 2008/09. The total sugarcane production will also increase from
549.902 Mt to 598.224 Mt.
A typical plant in Brazil crushes 2 million tonnes of sugarcane per year and produces
200 million litres of ethanol per year (1 million litres per day during 6 months – April to
November in the south-eastern region). The size of the planted area required to supply the
processing plant is on average 30,000 hectares. Due to process of degradation of the quality
of harvested cane the distance to the mill is up to 70 kilometres at the most.
United States (US) output of ethanol, mainly from maize (Zea mays ssp. mays L.), has
increased in recent years as a result of public policies and measures such as tax incentives and
mandates and a demand for ethanol as a replacement for methyl-tertiary-butyl-ether (MTBE)
a gasoline-blending component. Between 2001 and 2007, US fuel ethanol production capacity
grew 220 from 7.19 billion to 26.50 billion litres (OECD, 2008). The new Energy Bill expands
the mandate for biofuels, such as ethanol, to 56.8 billion litres in 2015.
20
Sugarcane ethanol
Introduction to sugarcane ethanol
Although the installed ethanol fuel capacity in the European Union (EU) amounts to 4.04
billion litres at the moment (OESO, 2008), Europe’s operational capacity is significantly
lower at 2.9-3.2 billion litres as some plants have suspended production. The bulk of EU
production, however, is biodiesel, which, in turn, accounts for almost two-thirds of world
biodiesel output.
Elsewhere, China with 1.8 billion litres of ethanol (Latner et al., 2007), Canada with 0.8
billion litres are relatively smaller producers.
4. Production and use of bioethanol
Ethanol is manufactured by microbial conversion of biomass materials through fermentation.
The production process consists of three main stages:
• conversion of biomass to fermentable sugars;
• fermentation of sugars to ethanol; and
• separation and purification of the ethanol (Figure 1).
Fermentation initially produces ethanol containing a substantial amount of water. Distillation
removes the major part of the water to yield about 95 percent pure ethanol. This mixture
of 95% ethanol and water is called hydrous ethanol. If the remaining water is removed, the
ethanol is called anhydrous ethanol and is suitable for blending with gasoline. Ethanol is
‘denatured’ prior to leaving the distillery to make it unfit for human consumption.
Feed stock preparation
washing/separation
C3 plants and starch
(Wheat, barley and beet)
C4 plants
(Sugar cane and corn)
Solid residues
Hydrolysis
Fermentation
Use of yeast
Distillation
CO2 and heat
Liquor
Dehydration
Figure 1. Production process of ethanol (Barriga, 2003).
Sugarcane ethanol
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Chapter 1
Traditional fermentation processes rely on yeasts that convert six-carbon sugars, such
as glucose, into ethanol. Ethanol is used primarily in spark-ignition engine vehicles. The
amount of ethanol in the fuel ranges from 100 percent to 5 percent or lower, blended with
gasoline. In Brazil the Flex-Fuel-Vehicles (FFV) are fit to use the whole range of blends of
ethanol, up to 100%. The attractiveness of FFV is shown by the fact that in 2008 of the new
cars sold 87.6% are FFV’s (Anfavea: www.anfavea.com.br/tabelas.html). In other countries,
such as Sweden, a maximum of 85% (E85) is used.
Anhydrous ethanol is used in a gasoline-ethanol blend. For example, of the total Brazilian
ethanol production in the crop-season 2007/08, 8.38 billion litres are anhydrous and the
rest, 13.86 billion litres hydrous ethanol (AgraFNP, 2008). Aside from FFV’s manufactured
to run on hydrous ethanol, non-FFV’s in Brazil run on a 25 % mixture of a gasoline-ethanol
blend and hydrous ethanol.
Another application of ethanol is as a feedstock to make ethers, most commonly ethyl
tertiary-butyl ether (ETBE), an oxygenate with high blending octane used in gasoline. ETBE
contains 44 percent ethanol. A last application, that we mention here, is the use of ethanol in
diesel engines. Take for example Scania: Scania’s compression-ignition (CI) ethanol engine is
a modified 9-liter diesel with a few modifications. Scania raised the compression ratio from
18:1 to 28:1, added larger fuel injection nozzles, and altered the injection timing. The fuel
system also needs different gaskets and filters, and a larger fuel tank since the engine burns
65% to 70% more ethanol than diesel. The thermal efficiency of the engine is comparable
to a diesel, 43% compared to 44% (http://gas2.org/2008/04/15).
5. Where does it come from: the feedstock for ethanol
The term feedstock refers to the raw material used in the conversion process. The main
types of feedstock for ethanol are described below.
1. Sugar and starch-based crops: As mentioned earlier bioethanol is mainly produced of
sugarcane and maize. Other major crops being used are wheat, sugar beet, sorghum and
cassava. Starch consists of long chains of glucose molecules. Hydrolysis, a reaction of
starch with water, breaks down the starch into fermentable sugars (see Figure 1).
The co-products include bagasse (the residual woody fibre of the cane obtained
after crushing cane), which can be used for heat and power generation in the case of
sugarcane; distiller’s dried grains sold as an animal feed supplement from maize in dry
mill processing plants; and high-fructose maize syrup, dextrose, glucose syrup, vitamins,
food and feed additives, maize gluten meal, maize gluten feed, maize germ meal and
maize oil in wet mill processing plants. In all cases, commercial carbon dioxide (CO2)
can be captured for sale.
2. Wastes, residues and cellulosic material: according to Kim and Dale (2005), there are
about 73.9 million tonnes of dry wasted crops and about 1.5 billion tonnes of dry
lignocellulosic biomass.
22
Sugarcane ethanol
Introduction to sugarcane ethanol
Cellulose is the substance that makes up the cell walls of plant matter along with
hemicellulose and lignin. Cellulose conversion technologies will allow the utilization of
nongrain parts of crops like maize stover, rice husk, straws, sorghum stalk, bagasse from
sugarcane and wood and wood residues. Among the cellulosic crops perennial grasses
like switchgrass (Panicum virgatum L.) and Miscanthus are two crops considered to hold
enormous potential for ethanol production. Perennial crops offer other advantages like
lower rates of soil erosion and higher soil carbon sequestration (Khanna et al., 2007;
Schuman et al, 2002) However, technologies for conversion of cellulose to ethanol are
just emerging and not yet technically or commercially mature.
Furthermore, lignin-rich fermentation residue, which is the co-product of ethanol
made from crop residues and sugarcane bagasse, can potentially generate electricity
and steam.
6. Brazil as main exporter
Brazil has been by far the largest exporter of ethanol in recent years. In the crop season
2007/08, its hydrated ethanol exports amounted to 3.7 billion litres, of the 5 billion litres
of ethanol traded globally (excl. intra-EU trade) (AgraFNP, 2008). The US imported more
than half the ethanol traded in 2006. Of the 2.7 billion litres imported by the US in 2006,
about 1.7 billion litres were imported directly from Brazil, while much of the remainder
was imported from countries which are members of the Caribbean Basin Initiative (CBI)
which enjoy preferential access to the US market and import (hydrated) ethanol from Brazil,
dehydrate it and re-export to the US.
China, too, has been a net exporter of ethanol over the last several years, though at
significantly lower levels than Brazil. Despite some exports to the US as well as to CBI
countries, most of the larger destinations for Chinese ethanol are within the Asian region,
in particular South Korea and Japan (OESO, 2008). The EU is also a net importer.
7. What makes the ethanol attractive?
One may observe a variety of reasons for the recent bioethanol interest. From the market
point of view, there is an increasing consensus about the end of cheap oil and the volatility
in world oil prices. Nowhere is the need for alternative to fossil oil felt more than in the
transport sector. Transport consumes 30% of the global energy, 98 % of which is supplied
by fossil oils (IEA, 2007).
From a policy point of view, other factors are mentioned, such as assuring energy security,
reducing greenhouse gas emissions, increase and diversification of incomes of farmers and
rural communities and rural development. And next there are arguments that ethanol is
replenishable, that the ethanol industry can create new jobs, and that feedstock for ethanol
can be made easily available considering already existing technologies.
Sugarcane ethanol
23
Chapter 1
However the debate on biofuels in general and bioethanol in particular shows a lot of
counterarguments. They include that production of feedstock for ethanol might have
negative environmental impacts on GHG, land use change, water consumption, biodiversity
and air quality; also indirect negative environmental impacts are mentioned as a result of
the interactions between different land uses. The development of biofuels, it is said, may
also have both direct and indirect negative social and socio-economic impacts.
A third point of view comes from developing countries being motivated to diversify energy
sources. Specifically net importing countries, may consider enhancing their energy security
by domestically produced ethanol. Quality of air might be another argument for countries
where the vehicle fleet is old, causing huge polluting emissions. However, also for these
countries the counterarguments are widely discussed. Will the bioethanol production
contribute to small farmers? And what will be the impact of production for bioethanol on
the food production in those countries. Next to possible environmental impacts, developing
countries might decide to take irreversible decisions that might, according to this point of
view, create more instead off less poverty (Oxfam, 2008).
8. The core of the debate
The debate on sugarcane ethanol contains several major issues. The first one is impact of
sugarcane production on land use change and climate. Here the assumption is made that
land use for sugarcane implies serious impacts on the carbon stock, GHG emissions, and
water and soil conditions. (Macedo et al., 2004). Also, the reallocation of land or land cleared
for ethanol may have unforeseen impacts on biodiversity. The main question here is, can
production of sugarcane ethanol be sustainable?
Second, the demand side of the sugarcane ethanol may have impacts on the automotive
industry, as happened in Brazil by the introduction of FFV’s. Here the assumption is that
demand will not so much be geared by balanced growth of the supply, but by the price and
attractiveness of new automotive solutions. And this may have unintended consequences
for sustainable production of sugarcane ethanol (Von Braun, 2006).
Third issue is the impact of new technologies on the efficiency of biomass for biofuels and the
conversion of biomass for ethanol. Here the assumption is that new technologies may provide
not only higher efficiency, but also the need for larger scale of operations, asking more land
to be cleared for ethanol with possible negative environmental effects (Faaij, 2006).
Fourth, the public policies may have positive effects on balanced growth of the ethanol
industry. However, these policies may also contribute to numerous distortions in trade,
consumption, supply and technology development and on the environment as well (Hertel
et al., 2008).
24
Sugarcane ethanol
Introduction to sugarcane ethanol
Fifth, the debate also addresses the impacts of biofuels on developing countries. These
societies may benefit greatly by diversifying the energy matrix. However, unbalanced growth
may have unintended consequences for the food security domestically and land use (Teixeira
Coelho, 2005; Kojima and Johnson, 2005; Dufey et al., 2007).
Sixth, the last issue deals with the food prices hike. How do biofuels rank as factor for
explaining the food prices in 2007-2008 and, possibly, the coming years (Banse, 2008; Maros
and Martin, 2008)? And how does ethanol fit into this explanation and projection?
The impact studies are conducted from a multidisciplinary point of view. Also, the impacts
are observed on different scale levels: global, regional and on value chain level. Hence, the
analysis focuses on land use dynamics, market demand, technology development and public
policies. These four main factors are assumed to contribute to the understanding of impacts
of sugarcane ethanol on climate change mitigation and the environment. The debate asks
understanding based on the latest science based insights (The Royal Society, 2008). This
book aims to contribute to present these insights.
9. Structure of the book
In Chapter 2 the debate on sugarcane ethanol focuses on land use from a global point of
view. There are many competing demands for land: to grow crops for food, feed, fibre and
fuel, for nature conservation, urban development and other functions. The objective of the
chapter is to analyze current and potential sugarcane production in the world and to provide
an assessment of land suitable for sugarcane production.
Considering the particular situation in Brazil, Chapter 3 discusses the prospects of the
sugarcane production, considering land use allocation and the land use dynamics. It shows
on an empirical basis the expected sugarcane land expansion. This expansion is supposed
to convert annual crops, permanent crops, pasture areas, natural vegetation and degraded
areas. The chapter presents substitution patterns based on a reference scenario for sugarcane
and ethanol production.
What are the impacts of sugarcane ethanol for the mitigation of GHG emissions? Chapter 4
goes into this debate. The chapter compares the ethanol production in 2006 with a scenario
for 2020. Next energy flows and a life cycle analysis is presented. Then the effects on land
use change on GHG emissions on global scale are discussed. Finally the chapter discusses
the indirect effects of land use change in the Brazil.
Chapter 5 addresses the question on environmental sustainability of the sugarcane ethanol
production in Brazil. Sustainable production is discussed worldwide. For bioethanol
sustainability criteria vary among countries and institutions. Criteria that are pertinent in the
debate are use of agricultural inputs, air quality and burning of sugarcane vs. mechanization,
Sugarcane ethanol
25
Chapter 1
use of water, soil, farm inputs such as fertilizer and the energy and carbon balance. The
chapter ends with the discussion on certification and compliance
Chapter 6 starts with the assessment of studies on the market potential of ethanol. The
demand predictions will be considered, taking into consideration technological development
and innovation. The study provides an overview of the main issues and challenges related
to the current and potential use of ethanol in the transport sector.
In Chapter 7 the technology developments for bioenergy will be analyzed. It gives a state of
the art overview of technologies for bioenergy production from biomass. Next the chapter
highlights some challenges in developing technologies from biomass. Further it sheds light
on some scenarios for technologies to be developed in the 10-15 years to come.
As described earlier, public policies play a major role in the biofuel industry. What are the
policies, what measures are implemented and what are the impacts? This Chapter 8 will
deal specifically with the policies originating from the United States of America and the
European Union. The chapter starts with an overview of policies and policy instruments of
both. Next, these policies will be evaluated from an economic point of view. Based on this
analysis, the impacts on the global biofuel industry will be considered.
There is much debate on the impacts of biofuels on developing countries. Just positive, only
negative? In Chapter 9 the impact will be discussed within the framework of the Millennium
Development Goals (MDG). The chapter will deal with the question: How can global biofuels industry support sustainable development and poverty reduction?
The book ends with the probably most heated debate: the impacts of bio fuels production
on food prices. Chapter 10 covers the following questions: what is the state of the art: what
are the relations between production of food and food prices and bio-fuels? Then the main
drivers for the hike in food prices are discussed. Based on quantitative model studies some
core findings will be presented. Finally, the chapter ends with the impacts of bioethanol on
food production and prices.
References
AgraFNP, 2008. June 24. Ethanol consumption and exports continue to increase.
Banse, M., P. Nowicki and H. van Meijl, 2008. Why are current world food prices so high? A memo. LEI
Wageningen UR, The Hague, the Netherlands.
Barriga, A., 2003. Energy System II. University of Calgary/OLADE, Quito.
Dufey, A., S. Vermeulen and B. Vorley, 2007. Biofuels: Strategic Choices for Commodity Dependent
Developing Countries. Common Fund for Commodities Amsterdam, the Netherlands.
Faaij, A., 2006. Modern Biomass Conversion Technologies. Mitigation and Adaptation Strategies for Global
Change 11: 335-367.
26
Sugarcane ethanol
Introduction to sugarcane ethanol
Hertel, T., W. W.E. Tyner and D.K. Birur, 2008. Biofuels for all? Understanding the Global Impacts of
Multinational. Center for Global Trade Analysis Department of Agricultural Economics, Purdue
University GTAP Working Paper No. 51, 2008.
IEA, 2007. Bioenergy Potential contribution of bioenergy to the world’s future energy demand, International
Energy Agency, Paris.
IEA, 2008. Worldwide Trends in Energy Use and Efficiency Key Insights from IEA Indicator Analysis,
Paris, France.
Khanna, M., H. Onal, B. Dhungana and M. Wander, 2007. Economics of Soil Carbon Sequestration Through
Biomass Crops. Association of Environmental and Resource Economists; Workshop Valuation and
Incentives for Ecosystem Services, June 7-9, 2007.
Kim, S. and B.E. Dale, 2005. Life cycle assessment of various cropping systems utilized for producing biofuels:
Bioethanol and biodiesel. Biomass and Bioenergy 29: 426-439.
Kojima, M. and T. Johnson, 2005. Potential for biofuels for transport in developing countries. ESMAP,
World Bank Copyright The International Bank for Reconstruction and Development/The World Bank,
Washington D.C., USA.
Latner, K., O. Wagner and J. Junyang, 2007. China, Peoples Republic of Bio-Fuels Annual 2007. GAIN Report
Number: CH7039. USDA Foreign Agricultural Service, January 2007.
Macedo, I.C., M.R.L.V. Leal and J.E.A.R. da Silva, 2004. Assessment of Greenhouse Gas Emissions in the
Production and Use of Fuel Ethanol in Brazil. Report to the Government of the State of São Paulo, 2004.
Maros, I. and W. Martin, 2008. Implications of Higher Global Food Prices for Poverty in Low-Income
Countries. The World Bank Development Research Group Trade Team April, Washington, USA.
OECD, 2008. Economic assessment of biofuel support policies. Paris, France.
OECD/IEA, 2008. Worldwide Trends in Energy Use and Efficiency Key Insights from IEA Indicator Analysis.
Paris, France.
OESO, 2008. Economic assessment of biofuel support policies. Paris, France.
Oxfam, 2008. Inconvenient Truth How biofuel policies are deepening poverty and accelerating climate
change Oxfam Briefing Paper, June 2008.
Schuman, G.E., H.H. Janzen and J.E. Herrick, 2002. Soil carbon dynamics and potential carbon sequestration
by rangelands. Environmental Pollution 116: 391-396.
Teixeira Coelho, S., 2005. Biofuels- advantages and trade barriers. UNCTAD/DITC/TED/2005/1.
The Royal Society, 2008. Sustainable biofuels: prospects and challenges. London, United Kingdom. ISBN
9780854036622.
Von Braun, J., 2006. When Food Makes Fuel: The Promises and Challenges of Biofuels. Ifpri. Washington, USA.
Sugarcane ethanol
27
Chapter 2
Land use dynamics and sugarcane production
Günther Fischer, Edmar Teixeira, Eva Tothne Hizsnyik and Harrij van Velthuizen
1. Historical scale and dynamics of sugarcane production
Sugarcane originates from tropical South- and Southeast Asia. Crystallized sugar, extracted
from the sucrose stored in the stems of sugarcane, was known 5000 years ago in India. In
the 7th century, the knowledge of growing sugarcane and producing sugar was transferred
to China. Around the 8th century sugarcane was introduced by the Arabs to Mesopotamia,
Egypt, North Africa and Spain, from where it was introduced to Central and South
America. Christopher Columbus brought sugarcane to the Caribbean islands, today’s
Haiti and Dominican Republic. Driven by the interests of major European colonial powers,
sugarcane production had a great influence on many tropical islands and colonies in the
Caribbean, South America, and the Pacific. In the 20th century, Cuba played a special role
as main supplier of sugar to the countries of the Former USSR. In the last 30 years, Brazil
wrote a new chapter in the history of sugarcane production, the first time not driven by
colonial powers and the consumption of sugar, but substantially driven by domestic policies
fostering bioethanol production to increase energy self-reliance and to reduce the import
bill for petroleum.
1.1. Regional distribution and dynamics of sugarcane production
World crop and livestock statistics collected and published by the Food and Agriculture
Organization (FAO) of the United Nation are available for years since 1950. According to
these data, world production of sugarcane at the mid of last century was about 260 million
tons produced on around 6.3 million hectares, i.e. an average yield of just over 40 tons per
hectare. Only 30 years later, in 1980, the global harvest of sugarcane had reached a level of
some 770 million tons cultivated on about 13.6 million hectares of land with an average yield
of 57 tons per hectare. Another nearly 30 years later, the estimates of sugarcane production
for 2007 indicate more than doubling of outputs to 1525 million tons from some 21.9 million
hectares harvested sugarcane. In summary, the global harvest of sugarcane had a nearly sixfold increase from 1950 to 2007 while harvested area increased 3.5 times. During the same
period average global sugarcane yield increased from 41.4 tons per hectare in 1950 to 69.6
tons per hectare in 2007, i.e. a sustained average yield increase per annum of nearly 1%.
Figure 1 shows the time development and broad regional distribution of sugarcane
production and area harvested.
Sugarcane ethanol
29
1400
1200
1000
800
600
400
200
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
0
C.America
Europe
Oceania
N.America
22
20
18
16
14
12
10
8
6
4
2
0
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
1600
Area harvested (million hectares)
Production (million tons)
Chapter 2
Asia
Africa
S.America
Caribbean
Figure 1. Global sugarcane production 1960-2007, by broad geographic region. a: production (million
tons); b: area harvested (million hectares). Source: FAOSTAT, online database at http://www.fao.org,
accessed July 2008.
Table 1 indicates the main global players in sugarcane production. The countries shown
are listed in decreasing order of their sugarcane production in 2007. The table includes all
those countries, which ranked at least once among the 10 largest global producers in past
decades since 1950, and shows their global production rank for each period.
Table 2 indicates for the same countries level of production for respectively 1950 (three-year
average for 1949-1951), 1960, etc., to 2000 (three-year average for 1999-2001), and for 2007.
Table 3 presents associated harvested sugarcane areas.
In 1950, and still in 1960, India and Cuba were the two largest sugarcane producers in the
world. India continued to dominate sugarcane production until 1980, when Brazil took
over the first rank both in terms of area harvested and sugarcane output. Cuba maintained
rank three among global sugarcane producers until 1991. Then, however, with the collapse
of the USSR, Cuba’s guaranteed sugar export market, the sugar industry in Cuba collapsed
rapidly as well. As a result, sugarcane production in 2007 was only about one-eighth of the
peak reached in 1990. Another example for the decline of Caribbean sugarcane industry
is Puerto Rico, the world’s seventh largest producer in 1950, where sugarcane cultivation
became uneconomical and was completely abandoned in recent years.
Though the FAO lists more than 100 countries where sugarcane is cultivated, Table 2 and 3
indicate that global sugarcane production is fairly concentrated in only a few countries. The
15 top countries listed in Table 1 account for about 85 percent of the harvested sugarcane
area in 2007, and for a similar level in 1950 and the other periods shown. The first three
30
Sugarcane ethanol
Land use dynamics and sugarcane production
Table 1. Rank of major producers of sugarcane, 1950-2007.
Brazil1
India3
China1
Thailand1
Pakistan1
Mexico3
Colombia3
Australia1
United States2
Philippines3
Indonesia1
South Africa3
Argentina2
Cuba2
Puerto Rico2
2007
1999-01
1989-91
1979-81
1969-71
1959-61
1949-51
1
2
3
4
5
6
7
8
9
10
11
12
13
17
>100
1
2
3
4
5
6
9
7
10
11
12
13
14
8
88
1
2
4
6
7
5
9
12
10
11
8
13
14
3
56
1
2
5
12
7
4
8
10
9
6
11
13
14
3
40
2
1
8
20
6
4
11
9
7
5
12
10
13
3
21
3
1
6
27
9
4
7
12
5
8
11
15
10
2
13
3
1
8
43
12
6
5
11
4
10
18
13
9
2
7
Source: FAOSTAT, online database at http://www.fao.org, accessed July 2008; FAO, 1987.
that have significantly improved their rank in global production during the last five
decades.
2 Countries that have lost global importance in sugarcane production.
3 Countries that occupied a rank in 2007 similar to their position in the 1950s.
1 Countries
countries – Brazil, India and China – produced more than 60 percent of the global sugarcane
harvest in 2007; Brazil alone contributed about one-third. Somewhat lower, but similar
ratios hold for sugarcane area harvested in 2007: the top three countries accounted for 58
percent of land harvested, Brazil for about 30%, which indicates that these countries enjoy
sugarcane yields above the world average.
The dominance of Brazil in global sugarcane production and expansion – Brazil accounted
for 75 percent of sugarcane area increases in the period 2000 to 2007 and two-thirds of
global production increases in that period – derives from its experience and capability to
respond to thriving international demand for transport fuels, which was recently triggered
by measures to mitigate greenhouse gas emissions of the rapidly growing transport sector,
concerns in developed countries to enhance energy security and lessen dependence on
petroleum, and not the least the need of many developing countries to reduce import bills
for fossil oil.
Sugarcane ethanol
31
Chapter 2
Table 2. Sugarcane production (million tons) of major producers, 1950-2007.
Brazil
India
China
Thailand
Pakistan
Mexico
Colombia
Australia
United States
Philippines
Indonesia
South Africa
Argentina
Cuba
Puerto Rico
Sum of above
World
2007
1999-01
1989-91
1979-81
1969-71
1959-61
1949-51
514.1
322.9
105.7
64.4
54.8
50.7
40.0
36.0
27.8
25.3
25.2
20.5
19.2
11.1
0.0
1,317.5
1,524.4
335.8
297.0
75.1
51.3
48.4
46.1
33.1
35.3
32.1
25.6
24.2
22.1
17.9
34.2
0.1
1,078.2
1,259.4
258.6
223.2
63.9
37.0
36.2
40.8
27.4
24.2
26.6
25.2
27.6
18.9
15.9
80.8
0.9
907.1
1,053.5
147.8
144.9
33.8
17.7
29.1
34.4
24.7
23.4
24.5
31.5
19.5
17.3
15.6
69.3
2.0
635.5
768.1
78.5
128.7
19.6
5.4
23.8
33.3
13.2
17.6
21.4
25.3
10.3
14.6
10.2
60.5
5.0
467.1
576.3
56.6
87.3
15.0
1.9
11.6
18.8
12.5
9.4
16.0
12.0
9.6
8.2
10.4
58.3
9.4
337.0
413.0
32.2
52.0
8.0
0.3
6.4
9.8
11.1
6.5
13.5
7.1
3.1
4.7
7.6
44.5
9.7
216.5
260.8
Source: FAOSTAT, online database at http://www.fao.org, accessed July 2008; FAO, 1987.
Tables 1 to 3 point to two main factors that underlie the dynamics of sugarcane cultivation
during the last four decades: a four-fold expansion of sugarcane acreage in South America
between 1960 and 2007, and a collapse of sugarcane cultivation in the Caribbean sugar
islands, especially important Cuba and Puerto Rico, which still held a substantial production
share until the late 1980s. Solid growth of production and about three-fold expansion of
sugarcane acreage since 1960 occurred in Asia mainly fuelled by rapid domestic demand
increases for sugar in China and India. Fuel ethanol production from sugarcane has
played a minor role in these dynamics with the exception of Brazil where it caused a large
expansion.
An additional factor promoting the global expansion of sugarcane cultivation is the plant’s
efficient agronomic performance and its comparative advantage relative to sugar beets.
While post-war self-reliance policies and protection of agriculture in developed countries
supported an expansion of sugar beet cultivation areas until the late 1970s, the last three
decades witnessed a gradual decline in harvested areas of sugar beet and increasingly a
substitution of temperate sugar beets as a raw material for sugar production with tropical
sugarcane (Figure 2). Regional changes of sugarcane cultivation are shown in Figure 3.
32
Sugarcane ethanol
Land use dynamics and sugarcane production
Table 3. Sugarcane area harvested (million hectares) in major producing countries, 1950-2007.
Brazil
India
China
Thailand
Pakistan
Mexico
Colombia
Australia
United States
Philippines
Indonesia
South Africa
Argentina
Cuba
Puerto Rico
Sum of above
World
2007
1999-01
1989-91
1979-81
1969-71
1959-61
1949-51
6,712
4,830
1,225
1,010
1,029
680
450
420
358
400
350
420
290
400
0
18,574
21,896
4,901
4,197
1,171
903
1,042
628
400
412
412
365
381
392
282
1,015
3
16,504
19,476
4,092
3,699
1,230
897
888
556
344
333
374
367
392
272
258
1,372
16
15,089
17,729
3,130
3,073
722
549
894
520
270
314
306
409
234
252
314
1,246
25
12,257
14,708
1,830
2,486
566
159
574
483
260
234
282
446
77
181
242
1,254
61
9,134
11,025
1,400
2,428
279
62
407
352
294
159
184
240
75
96
218
1,218
129
7,539
8,946
1,307
2,011
414
53
418
325
280
131
176
205
62
110
264
1,097
133
6,986
8,302
Source: FAOSTAT, online database at http://www.fao.org, accessed July 2008; FAO, 1987.
1.2. Global significance of ethanol production from sugarcane
As shown in the previous analysis, for most of the 20th century sugarcane production took
place in response to global demand for sugar, was largely conditioned by the heritage of
colonial structures, and was greatly influenced by policy and trade agreements. With the
launching of the PROALCOOL program in Brazil in the mid 1970s another important
demand factor entered the scene, initially of national importance only. As a consequence
of the program however Brazil became the largest sugarcane producer in the world and by
now the largest exporter of transport bioethanol.
Figure 4 shows the dynamics of area expansion for sugarcane cultivation in Brazil and
indicates the significant amount of land dedicated to ethanol production and the important
role of the ethanol program in this process. The figure illustrates three phases that characterize
the last three decades. In the first decade after launching the PROALCOOL program, i.e.
during 1975 to 1986, there was a sharp increase in Brazilian sugarcane area, which is entirely
due to the domestic feedstock demand of the ethanol program. Then, during 1986 to 2000,
the figure suggests a growth of sugar production but a phase of stagnation in ethanol
Sugarcane ethanol
33
10
5
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
0
Cane
Beet
40
30
20
10
0
60
15
50
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
70
60
19
Yields (tons per hectare)
25
80
19
30
19
Harvested area (million hectares)
Chapter 2
Cane
Beet
Figure 2. Harvested area and yields of sugarcane and sugar beet, 1960-2007. Source: FAOSTAT,
online database at http://www.fao.org, accessed July 2008.
production, which has been attributed to various national and international factors, not
the least a low price of petroleum. Finally, the most rapid expansion of sugarcane harvested
areas occurred after 2000 and in particular during 2005 to 2008. This time ethanol demand
to substitute for gasoline consumption became a driving force at the global level, with many
countries seeking ways to cut greenhouse gas emissions and reducing dependence of their
economies on imported fossil oil.
In recent years, biofuels have re-emerged as a possible option in response to climate change,
and also to concerns over energy security. At the same time, many concerns among experts
worldwide have been raised about the effectiveness to achieve these goals and the possible
negative impacts on the poor, in particular regarding food security (Scharlemann and
Laurance, 2008) and environmental consequences.
Recent sharp increases of agricultural prices have partly been blamed on rapid growth of
biofuel production, especially maize-based ethanol production in the United States, which
in 2007 absorbed more than a quarter of the US maize harvest. How important is sugarcane
in this respect, and what fraction of the global sugar harvest is currently used for ethanol
production?
Figure 5 shows world fuel ethanol production, which is dominated by two producers, the
USA and Brazil. In 2008 these two countries contribute nearly 90 percent of total fuel
ethanol production. Though detailed data on used feedstocks are difficult to obtain, it can
be concluded that 45-50% of the world fuel ethanol production is based on sugarcane,
requiring some 280 to 300 million tons of sugarcane from an estimated 3.75 million hectares
harvested area (Table 4).
34
Sugarcane ethanol
Land use dynamics and sugarcane production
7
2.5
5
4
3
2
2.0
1.5
1.0
60
19
80
19
85
19
90
19
95
20
00
20
05
19
19
19
19
19
75
0.0
70
0
65
0.5
60
1
19
6
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
million hectares
B 3.0
million hectares
A 8
Other
Argentina
Colombia
Brazil
Other
Guatemala
Cuba
Mexico
1.6
1.4
million hectares
D 1.8
9
8
7
6
5
4
3
2
1
0
1.0
0.8
0.6
0.4
0.2
Other
Indonesia
Thailand
Pakistan
China
India
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
60
19
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
19
65
19
19
1.2
0.0
60
million hectares
C 10
Northern
Western
Middle
Southern
Eastern
Figure 3. Change in sugarcane cultivation 1960-2007, by broad geographic region. a: South America
(million hectares); b: Central America & Caribbean; c: Asia (million hectares); d: Africa (million
hectares). Source: FAOSTAT, online database at http://www.fao.org, accessed July 2008.
Table 4 and 5 summarize the available data for two time points, 1969-71 and 2007. Apart
from basic sugarcane statistics, the regional land-use significance of sugarcane is shown in
terms of percentage of cultivated land used for sugarcane cultivation. For 1970, the region
of Central America & Caribbean had the highest share where an estimated 7 percent of
cultivated land was used for growing sugarcane. At that time, Brazil devoted 4.4 percent of
cultivated land to sugarcane. In comparison, in year 2007 just over 10 percent of cultivated
land were in use in Brazil to serve the sugar and ethanol industries. As a consequence, at the
regional scale South America shows the highest share in 2007, now allocating 6.6 percent
Sugarcane ethanol
35
Chapter 2
3:
Phase :3
rapid expansion driven by
domestic and intern. demand
8
7
Phase :1
1:
rapid expansion
driven by policy
million hectares
6
Phase :2
2:
stagnation of
ethanol program
5
Ethanol
Sugar
4
3
2
1
0
1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008
Figure 4. Use of Brazilian sugarcane land for ethanol and sugar production. Source: FAOSTAT, 2008;
Conab, 2008a; Licht, 2007, 2008; calculation by authors.
70
60
billion litres/year
50
Others
China
EU
USA
Brazil
40
30
20
10
0
1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008
Figure 5. World fuel ethanol production (billion liters/year). Source: Licht, 2007 and 2008.
of total cultivated land to sugarcane. In comparison, the countries holding rank two and
three in global production, India and China, devoted respectively 2.8 and 1.0 percent of
cultivated land to sugarcane. The estimate for the global level amounts to 1.4 percent, i.e.
36
Sugarcane ethanol
Sugarcane ethanol
Table 4. Global significance of sugarcane production in 2007.
Sugarcane
Harvested
million ha
Cultivated
land 1
Production
million tons
Yield
tons/ha
million ha
Sugarcane
% of total
cultivated
percent
Sugarcane
ethanol land
Ethanol
% of sugarcane
million ha
percent
0
0
0
<1
<1
1
45
0.4
< 0.1
0.5
9.6
1.6
1.8
8.0
28
<1
40
639
92
114
611
77.6
61.4
79.9
66.4
56.8
63.4
76.5
229.3
296.4
54.8
577.1
239.3
42.9
121.9
0.2
0.0
0.9
1.7
0.7
4.2
6.6
0
0
0
< 0.1
< 0.1
< 0.1
3.6
Developed
Developing
World
0.9
21.0
21.9
67
1457
1524
78.9
69.2
69.6
580.4
981.3
1561.7
0.1
2.1
1.4
0
3.8
3.8
6.7
4.8
1.4
1.0
1.0
514
323
106
64
55
76.6
72.6
86.2
63.7
53.2
66.6
169.7
140.0
17.8
22.1
10.1
2.8
1.0
5.7
4.7
3.5
< 0.1
< 0.2
< 0.1
0
Brazil
India
China
Thailand
Pakistan
Source: FAOSTAT, 2008; Licht, 2007, 2008; calculation by the authors.
1 Estimates of cultivated land refer to year 2005.
0
17.8
17.1
50
n.a.
n.a.
3
n.a.
37
Land use dynamics and sugarcane production
North America
Europe & Russia
Oceania & Polynesia
Asia
Africa
Centr. Am. & Carib.
South America
Chapter 2
Table 5. Global significance of sugarcane production in 1969-71.
Sugarcane
Cultivated
land
Sugarcane
% of total
cultivated
percent
Harvested
million ha
Production Yield
million tons tons/ha
North America
Europe & Russia
Oceania & Polynesia
Asia
Africa
Centr. Am. & Carib.
South America
0.2
< 0.1
0.3
4.6
0.7
2.5
2.5
21
<1
20
227
47
132
128
89.8
72.1
75.0
49.5
66.2
53.9
51.7
243.4
378.3
46.2
448.7
180.5
34.9
90.6
0.1
0.0
0.6
1.0
0.4
7.0
2.7
Developed
Developing
World
0.5
10.2
10.7
42
534
576
82.8
52.2
53.7
667.9
754.6
1422.6
0.1
1.4
0.8
1.8
2.5
0.6
0.1
0.6
78
129
20
5
24
45.9
48.9
41.3
44.5
39.9
41.3
164.7
102.5
13.7
19.3
4.4
1.5
0.6
0.4
3.0
Brazil
India
China
Thailand
Pakistan
million ha
Source: FAOSTAT, 2008.
sugarcane harvested was 22 million hectares out of 1562 million total cultivated land. In
comparison, the share of sugarcane in global cultivated land was 0.8 percent in 1970, which
means that nearly a doubling of the global significance of sugarcane has occurred in the
last three decades.
At first glance, the rather low percentage of global cultivated land occupied by sugarcane
suggests that sugarcane area expansion and associated land competition has had little
influence on food supply. Yet, this may be misleading for two reasons: (1) sugarcane is
cultivated either under irrigation (e.g. India and Pakistan) or in rain-fed tropical areas with
ample rainfall. Hence land productivity in areas suitable for rain-fed sugarcane production
is typically much higher than for cultivated land in cooler climates or arid sub-tropical and
tropical agriculture; and (2) large parts of the world cannot grow sugarcane for climatic
reasons and the impact in climatically suitable areas is therefore more significant, as shown
in Table 6.
38
Sugarcane ethanol
Land use dynamics and sugarcane production
Table 6. Global significance of sugarcane production in 2007 revisited.
Sugarcane
harvested
area
Cultivated land
Sugarcane harvested
Total
With
sugarcane
potential
% of total
cultivated
land
million ha
million ha
million ha
percent
North America
Europe & Russia
Oceania & Polynesia
Asia
Africa
Centr. Am. & Carib.
South America
0.4
< 0.1
0.5
9.6
1.6
1.8
8.0
229.3
296.4
54.8
577.1
239.3
42.9
121.9
17.6
0.8
2.5
213.3
81.6
28.0
90.2
0.2
0.0
0.9
1.7
0.7
4.2
6.6
2.0
0.1
19.5
4.5
2.0
6.4
8.9
Developed
Developing
World
0.9
21.0
21.9
580.4
981.3
1561.7
19.5
414.4
434.0
0.1
2.1
1.4
4.4
5.1
5.0
6.7
4.8
1.4
1.0
1.0
66.6
169.7
140.0
17.8
22.1
57.3
70.1
12.4
17.0
15.6
10.1
2.8
1.0
5.7
4.7
11.7
6.8
11.3
5.9
6.4
Brazil
India
China
Thailand
Pakistan
% of
cultivated
land with
sugarcane
potential
percent
Source: FAOSTAT, 2008; Fisher et al., 2008.
The global analysis clearly shows that the most significant and relevant land use change
dynamics related to sugarcane in the last decades have taken place in Brazil. In the following
we take a short look at the Brazilian development and some issues and questions this
development has raised.
1.3. Sugarcane and land use change dynamics in Brazil
Brazil has the largest area under sugarcane cultivation in the world, being responsible for
approximately one third of the global harvested area and production. For the year 2007,
6.7 million hectares were harvested with a production of 514 million tons of sugarcane
Sugarcane ethanol
39
Chapter 2
(FAOSTAT, 2008). The land use change into sugarcane production is part of the history of
the country, dating short after Portuguese colonization during the 16th century. Since then,
the crop has maintained its characteristic of a monoculture with high elasticity of supply,
expanding rapidly in response to market stimuli (Tercil et al., 2007). The first establishment
phase of the crop over native vegetation aimed to provide sugar to the growing European
market during colonial times, during this period plantations were established in the NorthEast and South-East of the country where agro-ecological conditions are highly favorable
for the growth of tropical grasses such as sugarcane (e.g. see Figure 2.10 in next section).
From 2000 to 2007, an impressive pace of approximately 300 thousand hectares of land was
converted into sugarcane every year (FAOSTAT, 2008). This already phenomenal rate of
conversion is being surpassed by recent projections for the 2007/08 harvest season, which
indicate an expansion of 650 thousand hectares in Brazil (Conab, 2008a). Most of the recent
expansion in sugarcane area has occurred in São Paulo state (Conab, 2008a). From 1995 to
2007, there was a 70% enlargement of the sugarcane area in São Paulo, from 2.26 million
ha to 3.90 million ha, which represents 58% of the Brazilian area under sugarcane (IEA,
2007). In response to a greater demand for ethanol, São Paulo is also the region where most
of the land use change into sugarcane plantation is expected to take place in the near future
(Goldemberg et al., 2008). The projected expansion of sugarcane for the 2007/08 harvest
season is 350 thousand hectares, i.e. 54% of the Brazilian total (Conab, 2008b). Therefore, we
further discuss the aspects of land use change in Brazil with special attention on São Paulo
as an example of intensive conversion of other land uses into sugarcane monocultures.
The basis for the success of the crop in the South-East of Brazil is the favorable environmental
conditions in terms of temperature, radiation, precipitation, soil characteristics and relief that
match the crop physiological requirements. The potential to achieve high yields, today an
average near 80 t/ha (Conab 2008b), has diluted fixed production costs and has established
Brazilian ethanol as one of the most competitive bio-fuel options with an estimated cost of
US$ 0.21/liter (Goldemberg, 2007).
1.4. What are the drivers for these changes in Brazil?
The main drivers for the recent expansion of sugarcane in Brazil, particularly São Paulo, were
market opportunities created by the international demand for sugar and ethanol in conjunction
with national policies that promoted ethanol production and commercialization. During
these periods, intense and initially heavily subsidized investments (e.g. PROALCOOL in mid
70’s) allowed the development of a solid industrial capacity and know-how (Goldemberg,
2006). The historical background of sugarcane as a traditional land use and the investments
in the ethanol production chain created ideal conditions for the development of indigenous
technologies on agronomical (e.g. plant nutrition, management and high yielding genetic
material) and industrial aspects of production. For example, the flexibility to shift between
sugar and ethanol production (mixed production units) mitigates fluctuations on the
40
Sugarcane ethanol
Land use dynamics and sugarcane production
demand side, which makes the business highly attractive as a land use option. Currently,
mixed production units process 85.4% of Brazil’s industrialized sugarcane (Conab, 2008b).
Another aspect that favors rapid expansion of sugarcane in Brazil is the current land tenure
structure in this agri-business. There is a large concentration of land in the hands of the
industry, 67% of Brazilian sugarcane producing areas (Conab, 2008b). The operation
of extensive sugarcane farms reduces the cost of production through economy of scale
(Goldemberg, 2006) contributing to the overall competitiveness of sugarcane production
in relation to other land uses options. Finally, the environmental conditions in vast areas
of Brazil’s arable land are adequate not only for achieving high sugarcane yields (see Figure
10) but also high sucrose concentrations, i.e. a cool and dry winter period in São Paulo
favors accumulation of sugar, which increases industrial efficiency (Conab, 2008b). In
combination, these favorable biophysical conditions and socio-economical historical aspects
produced a setting for effective response to political and market stimuli explaining the rapid
expansion of sugarcane monoculture in Brazil.
1.5. What have been the impacts on environmental parameters?
The recent boom of ethanol production has drawn international attention to the environmental
impacts of land conversion into sugarcane monocultures. Site-specific biophysical and socioeconomical aspects largely determine the impacts of land use change. The conversion of land
use, its susceptibility to land degradation and the choice of agronomic and agro-processing
technologies for sugarcane production and conversion determine the magnitude of impacts
on environmental quality at the local level. Major areas of concern include deforestation and
threats to biodiversity, environmental pollution and competition with food crops.
1.5.1. Deforestation and threats to biodiversity
The expansion of sugarcane could increase deforestation rates either ‘directly’ by intruding
in areas of native non-protected forest areas or ‘indirectly’ by forcing other land uses (e.g.
displaced livestock production and agricultural crops such as soybeans) to open up new
land. Past surges of sugarcane expansion in Brazil are not regarded as a major cause of
deforestation (Martinelli and Filoso, 2008). The current sugarcane area represents only
2.5% of the 264 million ha of agricultural land use in Brazil, of which nearly 200 million
ha are pastoral lands. The hotspots of deforestation in the Amazon region, however have
a low suitability for sugarcane production and are not directly threatened by the current
sugarcane expansion (Smeets et al., 2008). Amazon deforestation has been caused mainly by
conversion to pastoral lands for livestock production and, more recently, also for expansion
of soybean production (Fearnside, 2005).
From 1988 to 2007 the average rate of expansion of sugarcane was 0.14 million ha/year when
rates of Amazon deforestation ranged from ~1.1 to 2.9 million ha per year (Fearnside, 2005)
Sugarcane ethanol
41
Chapter 2
indicating that sugarcane expansion is by far insufficient to have forced ‘direct’ or the ‘indirect’
reallocation of pasture and soybeans northwards intruding into Amazon rainforests.
Currently, the savannah region (‘Cerrados’), considered a world bio-diversity hotspot (Myers
et al., 2000), is the ecosystem most threatened by sugarcane expansion in Brazil as it is
situated on the frontier of agricultural expansion and has at least partly excellent cultivation
potentials (Klink and Machado 2005; Smeets et al. 2008). The Cerrado is characterized by
high biodiversity (e.g. >6.5 thousand plants species from which 44% are endemic to the
biome) and has suffered rates of conversion to either cultivated pasture land or to crop
cultivation land that are higher than the deforestation rates in Amazon (Conservation
International, 2008; Klink and Machado, 2005). In 2002, nearly 40% of a total of about
205 million ha of Cerrado had already been converted (Table 7), mainly into pastures and
cash-crops such as soybeans (Machado et al., 2004; Sano et al., 2008).
From the early 1970s to 2000 around 0.36 million ha of Cerrado vegetation were lost in
São Paulo (Florestar, 2005). However, from 2001 to 2005, total native vegetation areas in
this state were maintained at about 3.15 million ha suggesting that more recent sugarcane
expansion was not a major lever of deforestation during this period. Nevertheless, specific
ecological systems such as riparian forests were highly affected in regions of intensive
sugarcane production to give way to cropping areas (Martinelli and Filoso, 2008). In major
watersheds in São Paulo State, where pastures and sugarcane are the main land uses, it is
Table 7. Land use shares of the Brazilian Cerrado region in 2002 (Adapted from Sano et al., 2008
and Ministério do Meio Ambiente, 2007).
Land use classes
Area (million ha)
Percent of total
Native areas
Native forest
Native non-forest 1
Anthropic areas
Cultivated pastures
Agriculture
Reforestation
Urbanized plus mining
Water
Total cerrado area
124
75
48
80
54
21
3
1
1
205
60%
37%
24%
39%
26%
10%
2%
<1%
1%
100%
1 The
48 million ha of non-forested areas are estimated to include 28 million ha of native pastures
(Ministério do Meio Ambiente, 2007).
42
Sugarcane ethanol
Land use dynamics and sugarcane production
shown that 75% of the riparian vegetation (a reservoir of biodiversity and a buffer against
sedimentation of water bodies) had disappeared (Silva et al., 2007).
1.5.2. Air, water and soil pollution and degradation
During the past surges of sugarcane expansion, cases of environmental pollution were
identified at different stages of production and industrialization. The impacts on air, water
and soil quality largely depend on the choices of technologies applied in agronomic and
agro-processing practices. Beyond carbon releases and biodiversity losses caused by land
conversion (discussed above), the main environmental effects concern air pollution from
pre-harvest sugarcane burning, water pollution from cultivation and processing of sugarcane,
and soil erosion and compaction as a consequence of sugarcane cultivation.
For example, air quality is highly compromised by the common practice of sugarcane
burning, a technique used before harvest to facilitate manual cutting. The emission of
pollutants during the dry months of the year, when harvest occurs in São Paulo, has direct
negative impacts on health (e.g. respiratory disorders mainly in children and elderly
citizens). It promotes erosion of topsoil, causes loss of nutrients and leads to soil compaction
(Tominaga et al., 2002; Cançado et al., 2006; Ribeiro, 2008).
Soil degradation through erosion and compaction are also considered a problem in sugarcane
fields, which are under intense mechanization during soil cultivation and harvesting
(Martinelli and Filoso, 2008). Soil compaction is a consequence of the traffic of heavy
machinery in conjunction with the lack of implementation of best management cultivation
practices (Naseri et al., 2007). Compaction exacerbates erosion problems because soil
porosity is reduced, which decreases water infiltration and increases runoff (Oliveira et al.,
1995; Martinelli and Filoso 2008). The main periods when soil remains bare and subjected to
erosive forces by rain and winds are (1) during the process of land conversion, (2) between
crop harvesting and subsequent canopy closure, and (3) during re-planting of sugarcane
fields every 5-6 years. The conversion of natural vegetation and extensive pastures (which
are less intensively managed) into sugarcane increases the risk soil degradation (Politano
and Pissarra, 2005). Erosion rates of 30 Mg of soil/ha.year were estimated for sugarcane
fields in the São Paulo State in comparison with less than 2 Mg/ha.year for pastures and
other natural vegetation (Sparovek and Schnug, 2001). Soil erosion in poorly managed
sugarcane areas also causes sediment deposition into water reservoirs, wetlands, streams
and rivers (Politano and Pissarra, 2005). This is aggravated by the transport of fertilizer and
agro-chemical residues that directly compromise water quality (Corbi et al., 2006).
Water pollution has been a severe environmental problem in sugarcane production regions
until early 80’s in Brazil when legislation was implemented to ban direct discharge of
vinasse (Martinelli and Filoso, 2008; Smeets et al., 2008). The main industrial sources of
pollutants of sugarcane industry are wastewater from washing of stems before processing
Sugarcane ethanol
43
Chapter 2
and vinasse produced during distillation. These by-products have a large potential of
water contamination due to a high concentration of organic matter, which increases the
biochemical oxygen demand (BOD5) of water bodies receiving such effluents (Gunkel et al.,
2007). While the Brazilian standards for wastewater emission are BOD5 of 60 mg/l, values
for wastewater from cane washing are up to 500 mg/l and > 1.000 mg/l for vinasse (Gunkel
et al., 2007; Smeets et al., 2008). In addition, agro-chemicals residues have been found as a
important component of water pollution in areas of intense sugarcane production (Corbi
et al., 2006; Silva et al., 2008).
1.5.3. Land use and competition with food crops
A major area of concern is the threat to food security (Goldemberg et al., 2008). Rapid
expansion of sugarcane areas could potentially reduce the availability of arable land for the
cultivation of food and feed crops causing a reduction in their supply and increase of food
prices. Fast rates of expansion of sugarcane in São Paulo state in the mid 70s at the expense
of maize and rice cropping areas seem to have had a short-term impact on regional food
supply and prices (Saint, 1982). However, the recent sugarcane expansion in São Paulo from
mid 90’s has not compromised food crop production as most of the expansion intruded in
pastoral lands (Figure 6).
For Brazil as a whole, in the 2006/07 season, nearly two thirds of sugarcane expansion
occurred at the expense of pastures (0.42 million ha) in comparison with one quarter coming
from land under crop cultivation (Conab, 2008b). This conversion of pastures into sugarcane
16
Area (million hectares)
14
12
10
Grain crops
Sugarcane
Pasture natural
Pasture cultivated
8
6
4
2
0
1983
1988
1993
1998
2003
Figure 6. Evolution of areas of sugarcane, pasture and grain crops in São Paulo State. Source: IEA,
2007; Conab, 2008c. Note: The total area of São Paulo State is 24.8 million ha.
44
Sugarcane ethanol
Land use dynamics and sugarcane production
areas is explained by their relative abundance (200 million ha) as well as occurrence adjacent
to existing sugarcane estates (Goldemberg et al., 2008).
The area of main grain crops has decreased by 0.9 million ha in the State of São Paulo from
early 80’s to 2005 (Conab, 2008c), while sugarcane area expanded nearly 1.7 million ha (IEA
2007), Figure 7. At the national level the magnitude of these regional land use changes is
diluted (Figure 8) as the total area of major crops, including sugarcane, is about 50 million
ha (Conab, 2008c). By far more important than sugarcane has been the rapid expansion
of soybeans in Brazil, from less than 10 million hectares in the early 1980s to around 23
million hectares, more than a third of all cropping land.
1.6. Lessons from Brazilian sugarcane land development dynamics
The learning experience with deploying sugarcane based ethanol production in Brazil
during the last 30 years has put the country in a unique position to respond to the current
wave of energy systems developments, particularly renewable transport fuels. As to land
use, the following conclusions can be summarized:
• There was a very rapid and large land use change into sugarcane production in Brazil in
the last 30 years, particularly in São Paulo State.
• Main drivers for the expansion of sugarcane areas were a combination of favorable
biophysical conditions, a historical foundation of logistical and technological conditions
to respond to market opportunities, national policies giving incentives to the sugarcane
Harvested area (million hectares)
6
5
sugarcane
wheat
cotton
rice
beans
maize
soybean
4
3
2
1
0
1983
1988
1993
1998
2003
2008
Figure 7. Area of selected crops in São Paulo. Source: Conab, 2008c.
Sugarcane ethanol
45
Chapter 2
50
Harvested area (million hectares)
45
40
35
30
25
20
15
sugarcane
wheat
cotton
rice
beans
maize
soybean
10
5
0
1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007
Figure 8. Area of selected crops in Brazil. Source: Conab, 2008c.
•
•
•
•
46
agri-business, and a growing demand for sugar and bioethanol, setting favorable
conditions to benefit from economies of scale.
The trend in sugarcane area expansion continues at record rates, now fostered by both
the domestic and international demand for ethanol.
The savannah ecosystem (Brazilian ‘Cerrados’) is the current frontier of sugarcane
expansion.
There are risks of environmental degradation in different stages of sugarcane production
and processing. Negative impacts have been caused by the lack of implementation of best
management practices and ineffective legislation and control. Examples from São Paulo
state indicate that environmental sustainability of sugarcane production and processing
has been substantially improved during the last three decades. Nevertheless, further
improvements are necessary.
While more effective and environmentally less harmful technologies are now available,
there is nevertheless a risk of affecting biodiverse ecosystems of the savannah region.
Strict regulation and enforcement are needed to safeguard against environmental losses,
for example by guaranteeing the protection and recuperation of specific biomes such as
the Cerrado and riparian forests.
Sugarcane ethanol
Land use dynamics and sugarcane production
2. Global potential for expansion of sugarcane production
2.1. Future land requirements for food and feed
Several inter-linked processes determine the dynamics of world food demand and supply.
Agro-climatic conditions, availability of land resources and their management are clearly key
aspects, but they are critically influenced by regional and global socio-economic pressures
including current and projected trends in population growth, availability and access to
technology, market demands and overall economic development.
While climate and farm management are key determinants of local food production, agroeconomics and world trade combine to significantly shape regional and global agricultural
land use. Catering to consumers and industries in OECD countries is an important driver
for agricultural activities in well-resourced developing countries. Computations of current
and future cultivated land were carried out by assessing land potential with the global Agroecological Zones model (GAEZ) and economic utilization with IIASA’s world food system
model (Fischer et al., 2002; Fischer et al., 2005). In 2000 about 1.5 billion hectares of arable
land were in use for food, fiber and fodder crop production, or roughly 10% of all available
land on earth. Of these, about 900 million hectares were in developing countries. By 2050,
under a IIASA designed plausible global socio-economic development scenario (Grübler et
al., 2006; Tubiello and Fischer, 2006; Fischer et al., 2006), for developed countries a slightly
lower level of cultivated land use was projected compared to 2000, i.e. a modest net decrease
in land under cultivation for food and feed crops was projected, while additional production
resulted from increased productivity and input use. In developing countries, by contrast,
cultivated land in 2050 was projected to increase by roughly 190 million ha (+21%) relative
to year 2000. In the scenario, most of this additional cropland is brought into use in Africa
(+85 million ha, or +42%) and Latin America (70 million ha, or +41%).
From a range of alternative scenario runs predicting world food system development
(Fischer et al., 2002; 2005) it can be concluded that global food and feed demand will require
some additional land to be used for cultivation, depending on socioeconomic scenario in
the range of 120-180 million hectares, notably in developing countries. Therefore, when
adopting a ‘food first’ paradigm, to realize a substantial contribution of agricultural biomass
to energy sources would necessitate (1) focused efforts of national and international R&D
institutions and extension services to enable sustainable agricultural production increases
on current agricultural land, which go beyond ‘business as usual’ trends and expectations,
in particular to mobilize undeveloped agricultural potentials on the African continent, and
(2) tapping into resources currently not or only extensively used for cultivation or livestock
production, e.g. certain grass, scrub and woodland areas where environmental and social
impacts might be regarded as acceptable. For this reason, we next look into the question as
to how much land, where and under what current uses, could be potentially available for
expanding global sugarcane production.
Sugarcane ethanol
47
Chapter 2
2.2. AEZ assessment of land suitable for sugarcane production
2.2.1. AEZ background
The range of uses that can be made of land for human needs is limited by environmental
factors including climate, topography and soil characteristics, and is to a large extent
determined by demographic and socioeconomic drivers, cultural practices, and political
factors, e.g. such as land tenure, markets, institutions, and agricultural policies.
The Food and Agriculture Organization of the United Nations (FAO) with the collaboration
of IIASA, has developed a system that enables rational land-use planning on the basis of
an inventory of land resources and evaluation of biophysical limitations and production
potentials of land. This is referred to as the Agro-ecological Zones (AEZ) methodology.
The AEZ methodology follows an environmental approach; it provides a standardized
framework for the characterization of climate, soil and terrain conditions relevant to
agricultural production. Crop modeling and environmental matching procedures are used
to identify crop-specific limitations of prevailing climate, soil and terrain resources, under
assumed levels of inputs and management conditions. This part of the AEZ methodology
provides maximum potential and agronomically attainable crop and biomass yields globally
at 5-minute latitude/longitude resolution grid-cells.
2.2.2. Land suitability for sugarcane
Sugarcane belongs to the crops with C4 photosynthetic pathway; it is adapted to operate
best under conditions of relatively high temperatures and, in comparison to C3 pathway
crops, has high rates of CO2 exchange and photosynthesis, in particular at higher light
intensities.
Sugarcane is a perennial with determinate growth habit; its yield is located in the stem as
sucrose and the yield formation period is about two-thirds to three quarters of its cultivated
life span. Climatic adaptability attributes of sugarcane qualify it as being most effective in
tropical lowland and warm subtropical climates; it does particularly well in somewhat drier
zones under irrigation, but is sensitive to frost. A short dry and moderately cool period at
the end of its cultivation cycle significantly increases sugar content at harvest.
Ecological requirements of sugarcane include warm, sunny conditions and adequate soil
moisture supply during most of its cultivation cycle. Sugarcane prefers deep, well drained,
well structured and aerated loamy to clayey fertile soils. Ideal pH ranges are between 5.5
and 7.5.
48
Sugarcane ethanol
Land use dynamics and sugarcane production
2.2.3. AEZ procedures applied for sugarcane
Box 1 summarizes the AEZ methodology and information flow as applied for the assessment
of global sugarcane potentials.
Box 1. AEZ procedures (see Figure 9).
Land Utilization Type (LUT): The AEZ procedures have been used to derive by grid-cell potential
biomass and yield estimates for rain-fed sugarcane production under high level inputs/
advanced management, which includes main socio-economic and agronomic/farm-management
components:
The farming system is (1) market oriented; (2) commercial production of sugar and bioethanol
are management objectives, and (3) production is based on currently available yielding cultivars,
is fully mechanized with low labor intensity, and assumes adequate applications of nutrients and
chemical pest, disease and weed control.
GIS Layers
Sugarcane
land utilization
definition
Soils
Climate database
CRU/GPC
Terrain slopes
Land use/land cover
Sugarcane
catalog
adaptability characteristics
biomass and yield parameters
partitioning coefficients,
ecological requirements
Climate analysis
Climatic and
edaphic
matching
procedures
Biomass and yield
calculation
Protected areas
Administrative areas
Land resources
database
Harmonized
world soil database
Biomass and yield
potentials
by grid-cell
Land use/land cover
shares
Conversion
sugarcane yields
to
bioethanol
(energy equivalent)
Agro-ecological
bio-ethanol production potential
(energy equivalent)
by grid-cell and
by land use/land cover class
Figure 9. AEZ methodology: information flow and integration.
Sugarcane ethanol
49
Chapter 2
The quantified description of sugarcane LUTs include characteristics such as vegetation period,
ratoon practices, photosynthetic pathway, photosynthesis in relation to temperature, maximum
leaf area index, partitioning coefficients, and parameters describing ecological requirements of
sugarcane produced under rain-fed conditions.
Climatic data: Climate data are from the Climate Research Unit (CRU CL 2.0 (New et al.,
2002, CRU TS 2.1; Mitchell and Jones, 2005), and precipitation data from VASClimO (Global
Precipitation Climatology Centre - GPCC). Average climate and historical databases were used
to quantify: (1) the length of growing period parameters, including year-to-year variability, and
(2) to estimate for each grid-cell by crop/LUT, average and individual years agro-climatically
attainable sugarcane yields.
Soils data: Spatial soil information and attributes data is used from the recently published
Harmonized World Soil Database (FAO, IIASA, ISRIC, ISSCAS & JRC, 2008)
Terrain data: Global terrain slopes are estimated on the bases of elevation data available from
the Shuttle Radar Topography Mission (SRTM) at 3 arc-second resolution
Land use/land cover: Potential yields, suitable areas and production were quantified for
different major current land cover categories (Fischer et al., 2008). The estimation procedures
for estimating seven major land-use and land cover categories are as follows: Cultivated land
shares in individual 5’ grid cells were estimated with data from several land cover datasets: (1)
the GLC2000 land cover regional and global classifications (http://www-gvm.jrc.it/glc2000), (2)
the global land cover categorization, compiled by IFPRI (IFPRI, 2002), based on a reinterpretation
of the Global Land Cover Characteristics Database (GLCC) ver. 2.0, EROS Data Centre (EDC,
2000) (3) the Forest Resources Assessment of FAO (FAO, 2001), and global 5’ inventories of
irrigated land (GMIA version 4.0; FAO/University of Frankfurt, 2006). Interpretations of these land
cover data sets at 30-arc-sec. were used to quantify shares of seven main land use/land cover,
consistent with land use estimates of published statistics. These shares are: cultivated land,
subdivided into (1) rain-fed and (2) irrigated land, (3) forest, (4) pasture and other vegetation,
(5) barren and very sparsely vegetated land, (6) water, and (7) urban land and land required for
housing and infrastructure.
Protected areas: The principal data source of protected areas is the World Database of Protected
Areas (WDPA) (http://www.unep-wcmc.org/wdpa/index.htm.) Two main categories of protected
areas are distinguished: (1) protected areas where restricted agricultural use is permitted, and
(2) strictly protected areas where agricultural use is not permitted.
Land resources database: Spatial data linked with attribute information from soils, terrain, land
use and land cover, and protected areas are combined with an administrative boundary GIS layer
in the land resources database
Climate analysis: Monthly reference evapotranspiration (ETo) has been calculated according to
Penman-Monteith. A water-balance model provides estimations of actual evapotranspiration (ETa)
and length of growing period (LGP). Temperature and elevation are used for the characterization of
thermal conditions, e.g. thermal climates, temperature growing periods (LGPt), and accumulated
temperatures. Temperature requirements of sugarcane were matched with temperature
profiles prevailing in individual grid-cells. For grid-cells with an optimum or sub-optimum match,
calculations of biomass and yields were performed.
50
Sugarcane ethanol
Land use dynamics and sugarcane production
Edaphic modifiers: The edaphic suitability assessment is based on matching of soil and terrain
requirements of the assumed sugarcane production systems with prevailing soil and terrain
conditions.
Land productivity for rain-fed sugarcane: The combination of climatic and edaphic suitability
classification provides by grid-cell potential biomass and yield estimates for assumed production
conditions
2.3. Agro-ecological suitability of sugarcane – risks and opportunities of expansion
Figure 10 presents a map of climatically attainable relative yields for rain-fed conditions,
normalized to a range of 0 (i.e. no yield possible) to 1 (i.e. geographical locations where
highest rain-fed yields would be obtained). According to the AEZ assessment, the most
suitable climates are found in the southeastern parts of South America, e.g. including
São Paulo State in Brazil, but also large areas in Central Africa as well as some regions in
Southeast Asia. Very wet areas with low temperature seasonality such as parts of the Amazon
basin1 produce substantially lower yields due to lower sugar content, high pest and disease
incidence combined with lower efficacy of control, and in extreme wet areas difficulties with
field operations and harvest. Note that in India and Pakistan, the world’s second and fifth
largest producers of sugarcane, irrigation is needed to exploit the thermal and radiation
resources in these countries for sugarcane cultivation.
1 Conditions in the equatorial parts of Africa differ substantially in wetness as compared to parts of the Amazon
basin and provide from climate viewpoint better sugar yields.
<0.75
0.50-0.75
0.35-0.50
0.15-0.35
>0.15
Figure 10. Normalized agro-climatically attainable yield of rain-fed sugarcane. Source: Fisher et al.,
2008, IIASA. Note: Maximum attainable yields in this global map are about 15 tons sugar per hectare.
Sugarcane ethanol
51
Chapter 2
Table 8 summarizes by region the current distribution of cultivated land, the land harvested
for sugarcane in 2007, and the area of current cultivated land assessed as very suitable (VS),
suitable (S) and moderately suitable (MS). Globally, the currently harvested 22 million
hectares of land for sugarcane compare to the potential of 28 million hectares VS-land
and 92 million hectares rain-fed S-land. In other words, of currently 1550 million hectares
cultivated land about 120 million hectares is very suitable or suitable for rain-fed sugarcane
cultivation, with the majority of this land located in developing countries of Africa (28
million hectares), Asia (34 million hectares) and South America (40 million hectares).
The Brazilian experience has shown that a major land source of sugarcane expansion
was from pastures. The assessment of sugarcane suitability in current grass, scrub, wood
land concluded that some 130 million hectares of this land would be very suitable or
suitable for rain-fed sugarcane production, of which 48 million hectares were found in
Sub-Saharan Africa and 69 million hectares in South America; Brazil accounts for nearly
half this potential (Table 9). There is only very little potential of this kind, about 7 million
hectares, in Asia as all the vast grasslands of Central Asia are too cold and too dry for rainfed sugarcane production.
The maps for South America and Africa shown in Figure 11 indicate the suitability of
climate, soil and terrain conditions for rain-fed sugarcane production. The respective
suitability class is shown for areas where 50 percent or more of a grid-cell of 5’ by 5’ latitude/
longitude is currently used as cultivated land and/or is covered by grass, scrub or woodland
ecosystems. Hence, it shows the suitability of land where a substantial fraction is nonforest ecosystems. This geographical filter was used to indicate the distribution of land for
potential sugarcane expansion, i.e. areas where further expansion of sugarcane would not
cause direct deforestation and, provided the biodiverse native Cerrado ecosystem can be
protected, would not create associated major risks for biodiversity and substantial carbon
debts as is the case with forest conversion.
The maps shown in Figure 12 indicate the suitability of climate, soil and terrain conditions
for rain-fed sugarcane production in areas where 50 percent or more of each grid-cell of
5’ by 5’ latitude/longitude is classified as forest or protected land, highlighting land at risk
of undesirable conversion ‘hot spots’ due to its suitability for sugarcane expansion. Unlike
the areas shown in Figure 11, conversion of these forest and protected areas would likely
be associated with high environmental impacts.
While legally protected areas, both forests and non-forest ecosystems, are less exposed
to conversion, unprotected forest areas with good suitability for rain-fed sugarcane
cultivation are of particular concern due to possible severe environmental impacts. The
AEZ methodology was therefore used to assess the magnitude and geographical distribution
of unprotected forest areas. A summary of results by region is provided in Table 10.
52
Sugarcane ethanol
Sugarcane ethanol
Table 8. Suitability of current cultivated land for rain-fed sugarcane production.
North America
Europe & Russia
Oceania & Polynesia
Asia
Africa
Centr. Am. & Carib.
South America
Brazil
India
China
Thailand
Pakistan
Land potentially suitable, of which
million ha
Very suitable (VS) Suitable (S)
million ha
million ha
Share of VS+S in Sugarcane
cultivated land
harvested (2007)
Moderately suitable
million ha
percent
million ha
230
305
53
559
244
43
129
2.7
0
0.4
5.7
6.8
3.1
9.7
4.6
0
0.6
28.6
20.6
7.3
30.3
7.7
0
0.6
70.6
27.0
5.7
30.6
3.1
0.0
1.9
6.1
11.2
24.1
31.0
0.4
0.0
0.5
9.6
1.6
1.8
8.0
591
972
1563
2.7
25.6
28.3
4.8
87.1
91.9
7.9
134.3
142.2
1.3
11.6
7.7
0.9
21.0
21.9
66
167
139
19
21
5.0
0.7
1.6
0.1
0.1
19.6
2.9
4.1
0.6
0.5
18.0
8.1
11.1
6.3
1.1
37.4
2.1
4.1
3.0
2.5
6.7
4.8
1.2
1.0
1.0
Source: Fisher et al., 2008, IIASA; FAOSTAT, 2008; calculation by the authors. Suitability classes are mutually exclusive, i.e. do not overlap.
53
Land use dynamics and sugarcane production
Developed
Developing
World
Cultivated land
Chapter 2
Table 9. Suitability of unprotected grass/scrub/wood land for rain-fed sugarcane production.
Unprotected Land potentially suitable, of which
grass/scrub/
wood land
Very suitable Suitable
Moderately
suitable
million ha
million ha
million ha
million ha
North America
Europe & Russia
Oceania & Polynesia
Asia
Africa
Centr. Am. & Carib.
South America
Developed
Developing
World
Brazil
India
China
Thailand
Pakistan
VS+S in grass
& wood land
percent
566
666
519
699
973
98
613
1.1
0
0.4
1.3
11.9
1.1
22.0
2.1
0
1.6
5.7
36.0
2.4
47.2
3.7
0.0
3.2
22.5
65.0
3.5
90.8
0.6
0.0
0.4
1.0
4.9
3.6
11.3
1741
2394
4135
1.2
36.6
37.8
2.5
92.5
95.0
4.5
184.2
188.7
0.2
5.4
3.2
260
26
268
12
14
7.7
0.0
0.7
0.0
0.0
26.5
0.1
1.4
0.1
0.0
49.9
0.2
2.9
1.2
0.0
13.2
0.3
0.8
0.6
0.0
Source: Fisher et al., 2008; calculation by authors. Suitability classes are mutually exclusive, i.e. do
not overlap.
In total, globally some 3.2 billion hectares of land are classified as unprotected forests, of
which 7.3 percent were regarded as very suitable (49 million hectares) or as suitable (some
185 million hectares; see Table 10) for rain-fed sugarcane cultivation. Of the suitable extents
in both of these prospective suitability classes, Africa and South America contribute about
85 percent of the total.
2.4. Sustainability of land use changes
Sugarcane is widely accepted as one of the most promising – economically and with regard
to greenhouse gas saving potential – bioenergy feedstock options currently available.
For instance, the fossil energy ratio (output biofuel energy per unit of fossil fuel input
energy) of sugarcane ethanol was 9.3 in 2006 and is projected to reach 11.6 by 2020 with
54
Sugarcane ethanol
Land use dynamics and sugarcane production
SI >75: high
SI 50-75: good
SI 20-50: moderate
SI 0-20: marginal
Not suitable, protected
and cultivated + grass <50%
Figure 11. Suitability of current cultivated land and grass, scrub, woodland areas for rain-fed sugarcane
production. Source: Fisher et al., 2008.
SI >75: high
SI 50-75: good
SI 20-50: moderate
SI 0-20: marginal
Not suitable, not protected
and forest <50%
Figure 12. Hot spots of suitability of forest land for rain-fed sugarcane production. Source: Fisher et
al., 2008; calculation by authors.
the implementation of commercial technologies already available (Macedo et al., 2008).
In comparison, as reviewed by Goldemberg (2007), fossil energy ratio is 10.0 for cellulose
ethanol in the United States, 2.1 for sugar beet in Europe and 1.4 for maize ethanol in the
United States. The energy and greenhouse gas balance of sugarcane compares very favorably
Sugarcane ethanol
55
Chapter 2
Table 10. Suitability of unprotected forest land for rain-fed sugarcane production.
Unprotected Land potentially suitable, of which
forest
Very suitable Suitable
Moderately
suitable
million ha
million ha
million ha
million ha
North America
Europe & Russia
Oceania & Polynesia
Asia
Africa
Centr. Am. & Carib.
South America
Developed
Developing
World
Brazil
India
China
Thailand
Pakistan
VS+S in
unprotected
forest
percent
496
910
121
476
444
81
694
3.1
0
0.8
1.7
28.0
1.9
13.1
8699
0
4.6
10.5
79.5
3.7
78.2
16.1
0.0
8.2
41.4
81.4
5.2
266.9
2.4
0.0
4.5
2.6
24.2
6.9
13.2
1516
1706
3222
3.5
45.2
48.7
10.2
175.0
185.2
18.0
401.2
419.2
0.9
12.9
7.3
414
61
158
9
2
4.4
0.3
0.5
0.0
0.0
45.0
0.6
1.2
0.1
0.0
174.8
2.0
2.7
1.3
0.1
11.9
1.4
1.1
0.6
0.8
Source: Fisher et al., 2008; calculation by authors. Suitability classes are mutually exclusive, i.e. do
not overlap.
with other first generation biofuels; as reviewed in several studies, bioethanol based on
sugarcane can achieve greenhouse gas reductions of more than 80% compared to fossil fuel
use (e.g. Macedo (2002); Macedo et al. (2004); De Oliveira et al. (2005)).
The rapid further expansion of sugarcane areas forecasted for Brazil is expected to continue
at the expense of current crop land and extensively managed pastoral land in the Cerrado
region. This expansion may directly or indirectly affect parts of the Cerrado area with native
vegetation and unprotected forest where biophysical, infrastructural and socio-economic
conditions are favorable for sugarcane cultivation. Most threatened are those lands adjacent
to current production areas. Environmental consequences of sugarcane expansion might
range from quite acceptable (conversion of crop land and managed pastures) to very negative
where sugarcane expands directly or indirectly in unprotected areas, which still have native
56
Sugarcane ethanol
Land use dynamics and sugarcane production
vegetation with high bio-diversity or into unprotected native forest areas. Apart from
the question, which land will be converted, environmental impacts will be molded by
agricultural and industrial technologies applied in newly converted areas.
Current concerns regarding sustainable expansion of the sugarcane industry in Brazil (see
Box 2) have been recently investigated (Goldemberg et al., 2008; Martinelli and Filoso,
2008; Smeets et al. 2008).
Pressure on native ecosystems and threats to biodiversity can be avoided by effective
environmental regulation and control and by implementation of agricultural policies
supporting intensification of production. Increasing demand for food and livestock
products will require replacement of the land converted to sugarcane, leading to substantial
shifts of crop land and pastures to other regions, causing pressure on the ecosystems there.
Such indirect land use changes would negatively affect the greenhouse gas efficiency of
sugarcane production.
So far sugarcane in Brazil has mostly intruded in the cultivated and pasture areas of São
Paulo State. For this state, the estimated remaining area of pastures, of which many are
bordering on the sugarcane production expansion front, is 7.6 million ha (IEA, 2007). In
the entire Cerrado region (205 million ha) there are currently about 54 million ha of these
pastures (Ministério do Meio Ambiente, 2007).
Assuming that cultivated pastures will continue to be converted into sugarcane and that on top
of this, demand for livestock products further increases, substantially higher stocking rates
will be required. This implies adoption of new technologies (Corsi, 2004) for intensification
of pastoral management (e.g. use of fertilizers, rotational grazing) with consequent increases
of agro-chemical inputs, production costs and greenhouse gas emissions. The remaining
124 million ha of Cerrado with native vegetation (see Table 7), which are susceptible to loss
Box 2. What are key concerns and environmental issues with sugarcane expansion?
• Deforestation and habitat loss.
• Land competition with food and feed production.
• Indirect effects of land conversion because of strong expansion of sugarcane production outcompeting other crop and livestock activities, which in turn encroach on natural habitats.
• Water pollution and eutrophication.
• Soil erosion and soil compaction (mainly during land preparation and early growth phases
when soil is barren combined with sub-optimal tillage methods and relative high rainfall and
the use of steep slopes).
• Air pollution (mainly through burning of sugarcane before harvest)
• Possible extensive use of transgenic sugarcane types
Sugarcane ethanol
57
Chapter 2
of bio-diversity and land degradation are an imminent target for sugarcane expansion and
needs therefore serious attention. Expansion of protected areas, zero deforestation policies
for native forest land as well as reforestation of already deforested areas are important
elements of a sustainable agricultural development (Machado et al., 2004; Durigan et al.,
2007). Currently, less than 6% of the Cerrado region is legally protected. A share of 20% of
natural vegetation is required as a ‘legal reserve’ by the Brazilian Forest Code in this region,
in comparison to 80% in the Amazon rainforest (Conservation International, 2008; Klink
and Machado, 2005).
The use of genetically modified sugarcane, with associated risks of impacting biodiversity or
becoming invasive in natural habitats, has been identified as an additional area of concern for
future expansion of sustainable sugarcane production (Smeets et al., 2008). The sequencing
of sugarcane genes and development of transgenic varieties has been pursued in Brazil as a
means of conferring disease resistance, stress tolerance and efficiency of nutrient use in the
plant, which could contribute to sustainable expansion in the future (Cardoso Costa et al.
2006). The country has a well-established research in the biotechnology field with reported
successes in developing disease and herbicide resistant agricultural and horticultural crops.
Although potential benefits are high, there is still a lack of understanding of the potential
impacts of genetically modified organisms on environmental parameters (Smeets et al.,
2008), which prompted the removal of permits for commercial trials with transgenic
sugarcane after public concerns.
Pollution problems require strict enforcement of legislation and inspection of agricultural
and industrial activities. Strict regulation and control of the disposal of nutrient-rich waste
from industrial processes (e.g. vinasse) is required to avoid deterioration of water quality
near production areas (Gunkel et al., 2007). Recycling of byproducts of sugarcane in the fields
reduces chemical fertilizers application rates; however, there is a risk of excess application
in particular at close distance to the processing plants (Smeets et al., 2008).
Various technologies have been identified for immediate increases in the efficiency and
sustainability of current and future sugarcane mills, e.g. reducing water consumption with
closure of water-processing circuits and the use of bagasse (fibrous residue left after cane
milling) to generate electricity, improving the energy balance of ethanol production; as well
as in production and harvesting processes. Air pollution caused by sugarcane burning can
be effectively avoided by the adoption of mechanized harvesting. In São Paulo, where more
than one third of the area of sugarcane is already harvested mechanically (Conab, 2008b),
a schedule of phasing out burning is in place. Targets are that by 2020 all land with slopes
<12% and by 2030 all the sugarcane land should harvested mechanically (Smeets et al.,
2008). These authors also indicate that high investment requirements and difficulties with
mechanization on, for example steep land, increase the risks of the full implementation of
mechanized harvest. An additional challenge are the social consequences of mechanical
harvesting because of the significant losses of jobs, i.e. currently 80 workers would be
58
Sugarcane ethanol
Land use dynamics and sugarcane production
replaced by one mechanical harvester (Conab, 2008a). In 2007, about three quarters of the
Brazilian sugarcane area was still manually harvested and some 300,000 workers depend
for their livelihood on manual cutting of cane. The pace of introduction of mechanized
harvesting will therefore be affected by the cost/benefit of substituting manual labor and
on suitable socio-economic conditions to reallocate the current contingent of sugarcanecutting workers.
Adequate know-how and well developed technology is available to achieve sustainable
sugarcane production and expansion (Goldemberg et al., 2008). However, the adoption of
new technologies requires a favorable economic and political environment that facilitates
investments in clean technologies. While Brazil has accumulated considerable experience
on sustainable sugarcane production through its PROALCOOL program, it will be critical
to share and transfer this knowledge and ensure application of new technologies and
of ‘best practices’ in other regions of the Americas, Asia and especially Africa, where
large expansion potentials may materialize quickly due to the current urgency to develop
bioenergy resources.
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Chapter 2
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62
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Chapter 3
Prospects of the sugarcane expansion in Brazil: impacts on
direct and indirect land use changes
André Meloni Nassar, Bernardo F.T. Rudorff, Laura Barcellos Antoniazzi, Daniel Alves de
Aguiar, Miriam Rumenos Piedade Bacchi and Marcos Adami
1. Introduction
Sugarcane has been an important crop since the initial colonization period of Brazil and
is nowadays expanding considerably its cultivated area, particularly due to strong ethanol
demand. Ethanol demand has been increasing in the internal market since 2003 - due to the
expansion of the flex-fuel car fleet - and is also facing good perspectives in the international
market. From 2000 to 2007 the cultivated sugarcane area increased by about 3 million ha,
reaching about 7.9 million ha based on information from IBGE (2008a). The South-Central
region was responsible for 95.7% of this total growth.
Sustainability of agricultural based biofuels has turned into a central question once the use
of biofuels with the aim to reduce greenhouses gases’ (GHG) emissions increases. The full
life cycle analysis of the production process of every feedstock, based on carbon equivalent
emissions, is the essential measure for assessing the sustainability of biofuels.
The agricultural component of the biofuel production is, therefore, a key variable for
determining the avoided carbon emissions. Agricultural products are, by its nature, large
land users. Crops - annual and permanent - and cattle - for dairy and beef - occupy about
77 and 172 million ha, respectively, in Brazil (IBGE, 2008b). Land use changes due to the
competition between crops and cattle may raise concerns in terms of GHG emissions and
it becomes even more important when land with natural vegetation (mainly forests and
Cerrado) is converted into cattle raising or agricultural production. There is no recognized
and unquestionable methodology to measure the amount of deforestation caused by
agricultural expansion. However, the amount of land allocated to pastures and crops in the
frontier are indicators that both processes are correlated.
Given that sustainability of Brazilian ethanol is intrinsically associated to the sugarcane
expansion’s effects on land use changes, this paper aims to analyze past and expected
sugarcane expansion in Brazil and to understand the land use change process. Competition
between food and biofuel increases the importance of this issue and has been adding
also social and economic concerns about land use change caused by biofuels’ expansion.
Different opinions from many international organizations, national governments, NGOs
and researchers are putting this debate in the centre of media and public opinion worldwide.
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Chapter 3
Considering that this debate has not yet been explored in depth in Brazil, this paper aims
to support these discussions with technical and scientific arguments.
Land use change, as a consequence of the expansion of agricultural production as well as
due to the competition for land among agricultural activities, is an issue under development
in Brazil in terms of economic analysis and modeling. With exception of the analysis
focused on land use changes related to deforestation in the Brazilian Amazon, which
is well monitored by Brazilian government agencies and environmentalists non-profit
organizations, there is not regular monitoring of the conversion of natural landscapes into
agricultural uses. Furthermore, there is a lack of economic models that are able to explain
and predict land allocation and land use change as a consequence of the dynamics of crops
and pasture land. This paper is a result of one of the initiatives under development in Brazil
in order to clarify this issue.
However, the complexity associated to measure land use change in the context of assessing
biofuel’s carbon life cycle is largely related to the extension of the concept. Two approaches
are under scrutiny: direct land use change (LUC); and indirect land use change (ILUC). The
objectives of the present study are to measure and evaluate direct changes of land use caused
by the sugarcane expansion over the last years as well as the consequences of future expected
expansion. Land use changes are measured in terms of crops and pasture directly displaced
by the sugarcane expansion. The study also aims to discuss indirect land use change related
to Brazilian sugarcane expansion. Information and data are presented in order to evaluate
effect-cause relationships between sugarcane and other agricultural expansion areas.
The measurement of land use changes as a consequence of agricultural production
expansion, looking to the past and forecasting the future, is a very dynamic and complex
process. This paper searches for support on different methodologies to understand this
process: (1) when measuring the past land use change, primary data based on remote sensing
images and environmental licensing reports as well as secondary data based on planted
and harvested area are used; (2) with respect of projections of land allocated to sugarcane,
a partial equilibrium model based on profitability and demand/supply responses to price
variations is developed.
The paper is organized as follows. Section two introduces the discussion of the dynamics of
the sugarcane expansion in Brazil and shows that the expansion is highly concentrated in the
South-Central region. Section three presents the different methodologies used in this study
to measure land use change due to past and future expansion of sugarcane. Section four is
also divided in two perspectives, past and future expansion, and presents the results of the
assessment of the sugarcane expansion and the consequent crop and pasture displacement.
Conclusions and recommendations are presented in section five.
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Prospects of the sugarcane expansion in Brazil
2. The dynamics of sugarcane expansion in Brazil
Before discussing land use changes caused by the sugarcane expansion, it is important to
know how the sugarcane crop is spatially distributed in Brazil. Almost all of the sugarcane
in Brazil is produced in the South-Central and Northeast regions. These two regions are
considered separately due to its different harvest seasons: the first is from April to October
and the second from November to March.
Based on data from the Canasat Project for the states of São Paulo, Minas Gerais, Paraná,
Mato Grosso, Mato Grosso do Sul and Goiás and from the IBGE (Brazilian Institute of
Geography and Statistics) for all other states, it is estimated that in 2008 the cultivated area
in the South-Central region was 7.4 million ha (85.0%) and in the Northeast region was
1.3 million ha (14.7%).
Figure 1 presents the evolution of sugarcane area for three regions: South-Central (comprising
its six most important states)2, Northeast and all the other states. According to the statistics
of IBGE the Northeast region has a relative steady sugarcane area, presenting a mean annual
growth rate of only 2%; while in the South-Central region the annual growth rate was 16%
over the last four years being responsible for 95.4% of the total sugarcane area expansion in
Brazil from 2005 to 2008. During this period the sugarcane area in Brazil expanded by an
annual rate of 13% (2.6 million ha) going from 6.1 to 8.7 million ha (Figure 1).
São Paulo is the most important state for sugarcane, representing 55.7% of the total sugarcane
area in Brazil in 2008. The four states with the largest sugarcane area are São Paulo, Paraná,
Minas Gerais and Goiás which are responsible for 75.2% of total sugarcane area in Brazil.
Coincidently, these states plus Mato Grosso and Mato Grosso do Sul have experienced
the greatest sugarcane expansion area over the last years. A new and promising region for
sugarcane is located in the states of Maranhão, Piauí and Tocantins, in the Cerrado biome,
commonly known in Brazil as the MAPITO region; however, in 2008 these states were
responsible for only 0.25% of the cultivated sugarcane area in Brazil.
South-Central, including MAPITO region, is here called Expanded South-Central and is
considered to be a relevant region for sugarcane expansion analysis. The sugarcane area
in the Expanded South-Central in 2008 was 7.5 million hectares (84% of total area) and
represents 97% of the total sugarcane expansion. In all other Brazilian states not included
in the Expanded South-Central and Northeast regions, which accounts for 3% of the total
sugarcane area, a reduction of 13.7 thousand hectares was observed from 2005 to 2008.
2 Although South-Central region is commonly defined as the states in South, Southeast and Centre-West political
regions, this paper refers to the South-Central as a region comprising São Paulo, Minas Gerais, Paraná, Goiás,
Mato Grosso do Sul and Mato Grosso. This definition is in line with the satellite images monitored by the Canasat
Project, due to the fact they are the most important states in terms of sugarcane expansion.
Sugarcane ethanol
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Chapter 3
9,000
8,000
1,000 ha
7,000
Annual growth rate (2005 to 2008)
South-Central
16% p.a.
Northeast
2% p.a.
Other
2% p.a.
Brazil
13% p.a.
6,000
5,000
4,000
3,000
2,000
1,000
0
2005
2006
South-Central (a)
2007
Northeast (b)
2008
Other (b)
Figure 1. Sugarcane area cultivated in Brazil according to production regions (2005 to 2008).
Sources: (a) Canasat/INPE, comprising São Paulo, Minas Gerais, Paraná, Goiás, Mato Grosso and
Mato Grosso do Sul; (b) PAM/IBGE (2005 and 2006) and LSPA/IBGE (2007 and 2008).
Therefore, for this work the evaluation of the conversion of land use and occupation for
sugarcane is restricted to a reduced South-Central region that comprises the states of São
Paulo, Minas Gerais, Goiás, Paraná, Mato Grosso do Sul and Mato Grosso (or South-Central
region minus the states of Rio de Janeiro, Espírito Santo, Santa Catarina and Rio Grande
do Sul)3 in Sections 3.1 and 4.1 and these states plus Maranhão, Piauí, Tocantins and Bahia
in Sections 3.2 and 4.2. As a means of illustration, a detailed visualization of the sugarcane
distribution in the South-Central region is presented in Figure 2.
3. Methodology
This papers divides the analysis of land use changes (LUC) caused by sugarcane expansion
basically in observed LUC (past trend) and projected LUC (future trend). Three different
methods were used to estimate past land use dynamics, and another one to project future
trend. For observed LUC and sugarcane expansion, we used the information extracted from
remote sensing images, secondary data by IBGE, and field research through environmental
licensing studies. The satellite image analysis was carried out for São Paulo, Minas Gerais,
Paraná, Goiás, Mato Grosso and Mato Grosso do Sul. Using IBGE data, all these states plus
Tocantins, Maranhão, Piauí and Bahia were analyzed due to their potentiality for future
expansion of agricultural area in Brazil. For the field research, the analyzed states were São
3 The states of Rio de Janeiro, Espírito Santo, Santa Catarina and Rio Grande do Sul are part of the South-Central
region but represent only 3.2% of the cultivated sugarcane area in 2008 and have not shown relevant sugarcane
expansion over the last years (Table 3).
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Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
Figure 2. Spatial distribution of sugarcane crop in 2007 in the South-Central region of Brazil. Source:
INPE (www.dsr.inpe.br/canasat/).
Paulo, Minas Gerais, Mato Grosso, Mato Grosso do Sul, Goiás and Tocantins, capturing
both past and near future trends. A deeper description of each method follows below.
It is important to clarify the available sources of data regarding sugarcane area inBrazil, since
different ones are used for different purposes here. The Brazilian Institute for Geography
and Statistics (IBGE) is the Brazilian official organization which provides data on crops
area, production, yield, and several others variables. For estimation of planted and harvested
sugarcane area, two IBGE databases can be used: one from the systematical survey on
agricultural production (LSPA – Levantamento Sistemático da Produção Agrícola) and
the other from the agricultural production by municipality (PAM – Produção Agrícola
Municipal). While the former includes all area occupied with sugarcane – which consists of
areas to be harvested and new areas, to be harvested only next year – the latter just includes
harvested area in a certain year4. PAM data is available for all geographic scales, from 1990
to 2006 while LSPA data are forecasts from previous and current years subjected to change.
4 Sugarcane crop is harvested yearly for 5 or 6 consecutive years. In general, after that period the sugarcane field is
renewed and generally rotated for soil improvement during one season with a crop from the Leguminosae family.
Planted area (or total land occupied by sugarcane), therefore, is the area available for harvest of sugarcane plus
the area of sugarcane that is being renewed.
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Chapter 3
Another source of data on sugarcane planted area is the National Food Supply Company
(CONAB). CONAB data, which are presented in a crop assessment reports, are not used
in this study.
Sugarcane planted area is also provided on the Canasat Project, coordinated by the National
Institute for Space Research (INPE). Canasat Project monitors the most important producing
states and estimates the planted area from remote sensing satellite images. A summary of
data available in Brazil is presented in the Table 1.
Table 1. Sugarcane area in Brazil (sources of data available).
Source
Data gathering
Period available
Data presented
Aggregation level
IBGE
LSPA survey
1990-2006
state (Brazil)
CONAB
INPE/Canasat
PAM survey
1990-2006
crop assessment 2005, 2007-2008
satellite images 2003/2005 - 2008
planted area and
harvested area
harvested area
planted area
planted area
municipality (Brazil)
state (Brazil)
municipality (SouthCentre)
3.1. Measuring the LUC using remote sensing images
Remote sensing satellite images from the Earth surface are an important source of information
to evaluate the fast land use changes observed by the dynamic agricultural activity. Brazil,
through its National Institute for Space Research (INPE), acquires remote sensing images
from both Landsat and CBERS satellites since 1973 and 1999, respectively. In 2003, INPE
started the Canasat Project together with UNICA (Sugarcane Industry Association), CEPEA
(Center for Advanced Studies on Applied Economics) and CTC (Center of Sugarcane
Technology) to map the cultivated sugarcane area in the South-Central region of Brazil
using remote sensing images (www.dsr.inpe.br/canasat/).
The mapping began in São Paulo State in 2003 and in 2005 it was extended to the states of
Minas Gerais, Goiás, Mato Grosso do Sul and Mato Grosso where sugarcane production
has been most intensified over the last years. In order to obtain an accurate thematic map,
multitemporal images were acquired at specific periods to correctly identify the sugarcane
fields and to clearly distinguishing them from other targets (Rudorff and Sugawara,
2007). The mapping procedure was mainly performed through visual interpretation on
the computer screen using the SPRING software (www.dpi.inpe.br/spring/), which is a
Geographic Information System (GIS) with digital image processing capabilities.
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Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
Results from the thematic maps of the Canasat Project presented in Section 4.1 refer to the
total cultivated sugarcane area which includes the fields being renewed with the 18 months
sugarcane plant, the fields planted in new areas (expansion) and the fields of sugarcane
ratoons (Sugawara et al., 2008). Prior land use identification for the expanded sugarcane
plantations in each year was carried out using remote sensing images acquired before the
land use change to sugarcane. This evaluation was accomplished in São Paulo for the years
of 2005 to 2008, and for the years of 2007 and 2008 for the States of Minas Gerais, Goiás,
Paraná, Mato Grosso do Sul and Mato Grosso.
Four classes of land use and occupation were defined, as follows: Agriculture, for cultivated
and bare soil fields; Pasture, for natural and anthropogenic pasture land; Reforestation, for
reforested areas with Pinus and Eucalyptus; and Forest, for riparian forests and other forests
no matter the stage of succession. In São Paulo State the Citrus class was also considered
due to its relevance in terms of land occupation and change to sugarcane. These five classes
were responsible for almost all of the changes to sugarcane. Figure 3 illustrates each of these
classes over some Landsat images acquired at two different dates prior to the change and
one date after the change to sugarcane. Figure 3a highlights a field classified as Agriculture.
On Date 1 (March of 2003), the field has the appearance of bare soil (medium-gray), and
on Date 2 (May of 2003), it is covered with a winter crop - probably maize. On Date 3 (April
of 2008), a well grown sugarcane field can be clearly identified (light-gray with well defined
pathways). An example for the Pasture class is illustrated in Figure 3b where it appears as
a mixture of different amounts of vegetation and soil (medium/light-gray). On Date 1, the
vegetation amount is dominant (end of rain season) whereas on Date 2 the soil becomes
dominant due to a reduction in the green vegetation amount in response to less available
water to the plant (mid dry season). On Date 3, a sugarcane field can be observed in
substitution to the pasture field. Figure 3c illustrates the Citrus class with its typical pattern
on Date 1 and 2, and a sugarcane field on Date 3. Figure 3d presents a typical field for the
Forest class (Dates 1 and 2) that was changed to sugarcane (Date 3). A field changed from
the Reforestation class to sugarcane is illustrated in Figure 3e.
It is worth to mention that Figure 3 only illustrates, in a simplified way, part of the whole
procedure used to identify the different land use classes that were displaced to sugarcane
in each year over the analyzed period. In several occasions a greater number of images
were necessary to clearly identify the classes that were changed to sugarcane. The SPRING
software allows coupling images acquired at different dates to alternate views of the same
area facilitating the visual interpretation resulting in a better extraction of the correct
information registered in the coloured multispectral satellite images.
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Chapter 3
Figure 3. Different land use classes over multispectral (bands 3, 4 and 5) black and white Landsat
images acquired in March of 2003 (date 1), May of 2003 (date 2), and April of 2008 (date 3).
3.2. Measuring the LUC using micro-regional secondary data
The objective of this method is to analyze the official secondary data about sugarcane and
other agricultural land uses in order to verify how substitution among these uses have taken
place over the last years, in different areas all over Brazil. Knowing how sugarcane expansion
has occurred and how other land uses have behaved is a first step to make considerations
about LUC and ILUC caused by ethanol production.
The analysis developed here was based on the Shift-share model adapted for the purposes of
this study. The Shift-share model looks at the mix of activities and whether they are shifting
towards or away from the area being studied (Oliveira et al., 2008).
The Shift-share model decomposes the growth area of an agriculture activity in a region
over a given period of time into two components: (1) growth effect, which is the part of the
change attributed to the growth rate of the agriculture as a whole; and (2) an agriculture
70
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
mix effect (substitution effect), which is the change in each crop share of the total cultivated
area. The sum of the two effects equals to the actual change in total sugarcane area within
a region over a time period.
We have used sugarcane and other crops harvested area data from IBGE, by ‘micro-region’,
which is an aggregated number of some closely located municipalities with geographic
similarities. The main advantage of using data by ‘micro-region’ is that it is a sufficient
small unit so that land substitution is captured in a more direct way, avoiding leakages.
Furthermore, the same method using data by municipality has presented some problems,
probably due to the fact that municipalities have correlated productive relations and
sometimes municipality data are not very accurate.
We have considered 2002 as the baseline year when the last significant sugarcane expansion
began and 2006 as the last year of available data from PAM-IBGE. Since expanded sugarcane
area, harvested in a certain year, was planted about 12 or 18 months before, the prior land
use needs to be observed still another year before. For example, 2006 sugarcane data regards
sugarcane harvested in 2006 and most likely planted in the beginning of 2005; therefore,
land use prior to the 2005 sugarcane plantation should be observed in the data from 2004.
Thus we have compared sugarcane expansion from 2002 to 2006 to other land occupation
from 2001 to 2005.
The three land use categories are: (a) sugarcane; (b) other crops (annual and permanent
crops, excluding sugarcane and second crops); and (c) pasture. Pasture land was estimated
by using cattle stocking rate because data on pasture area are available only on the IBGE
Agricultural Census of 1996 and 2006, while cattle herd data is available annually. Thus,
stocking rate for 1996 and 2006 were calculated and an annual average growth for this
period was considered. Pasture area for the analyzed years – 2001 to 2005 – were obtained
dividing herd by the stocking rate. Total agricultural area is the sum of these three categories,
and should represent agricultural dynamics in general. The data used for analysis was the
difference between the final period and the baseline, thus positive numbers mean that there
was an increase in the period while negative numbers mean that the area has decreased.
Following a logic tree of land use dynamics for the period, the ‘micro-regions’ were divided
in six categories (Figure 4). We have only considered for analysis those ‘micro-regions’ where
sugarcane area has increased, which means groups 2, 3 and 6. Thus expansion of sugarcane
was distributed proportionally through decreased areas of pasture land and crops. When
it was not possible to allocate sugarcane expansion over these land uses, it was considered
not allocated over previous productive areas, meaning whether already anthropized areas
not used, such as idle areas, or natural landscapes. Using shift-share terminology, sugarcane
expansion over pasture and crops is considered substitution effect, while those over not
productive areas are considered growth effect.
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Total used area
(sugarcane + pasture + crops)
Increased (+)
Decreased (-)
Sugarcane
+
Pasture land
and crops
+
Sugarcane
-
Pasture land
and crops
+
-
Pasture land
and crops
+
1-Pastureand
crops
expansion
2-Agricultural
expansion
+
Pasture land
and crops
-
-
6-Sugarcane
over other
activities
3-Sugarcane
expansion
4-Other activities
expansion
5-Declining
agriculture
Figure 4. Land use dynamics’ categories used for micro-regional secondary data analysis.
3.3. Case studies through environmental licensing reports (past and near future trend)
This third method is an empirical study which aims to collect field data from sugarcane mills
in six states where the crop is under strong expansion or is expected to be in near future:
São Paulo, Minas Gerais, Mato Grosso, Mato Grosso do Sul, Goiás and Tocantins5.
Environmental Impact Assessments presented in files of environmental licenses in
governmental bodies can be a useful source of information about many environmental,
social and economic impacts caused by any business venture. Environmental licensing is
an important instrument present in the Brazilian Environmental Policy and all sugarcane
mills are required to have this license to operate. Governmental agencies responsible for
issuing environmental licenses - state bodies in this case – define which type of study
will be necessary for the entrepreneur to present. The most complex type of study would
be the Environmental Impact Study (EIA, in Portuguese acronym) and the respective
Environmental Impact Report (RIMA, which is a synthesis of EIA in a non-technical
language). This study, made by the entrepreneur, contains a full characterization of the
business venture, a diagnosis of the surrounding area (here including information on land
use), and the impacts it will cause (natural vegetation suppression included). Even in the
less complex studies, this kind of information is generally available.
5 State of Paraná was excluded due to research restrictions imposed by the environmental authority of the state
government.
72
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
Through the environmental studies used to get this license, and through the governmental
agencies’ database, one can obtain the exact location of mills and the economically feasible
surrounding area where sugarcane is or will be cultivated. Knowing current land use in
these areas by the time of the study, one can know land use prior to sugarcane plantations,
as well as the type of original natural landscape when this is present.
Brazilian environmental licensing system is composed of three different phases, each of
them resulting in a different license. The environmental study required by the appropriate
governmental agency has to be submitted and approved to obtain the Previous License (LP,
in Portuguese). The LP certifies the environmental viability of the project at that specific
location, and it means the entrepreneur can ask for the Installation License (LI). Just with
the LI it is legal to start the construction of the mill plant, but to initiate operation and
production, the Operation License (LO) is required. The LP analysis generally takes long,
because the agency must analyze deep studies, such as EIA-RIMAs, while to issue the other
two licenses the approval periods are usually smaller.
By knowing which phase of the environmental licensing a mill project is ongoing or
when the LO was issued, one can know when the mill will start or has started production.
Furthermore, the environmental study specifies the business plan, which includes expected
date to start-up. Field research was conduced between May and June, 2008.
3.4. Projecting sugarcane expansion and changes in land use
The approach used for projecting land allocation for sugarcane is based on a partial
equilibrium model that is under development by the Institute for International Trade
Negotiations (ICONE). The model is based on demand response to price changes and
supply response to market returns (profitability) changes. National and regional prices are
calculated according to a basic assumption of microeconomics: they are achieved when
supply and demand prices for each coincide, generating a market equilibrium.
The model comprises 11 categories of products (sugarcane, soybean, maize, cotton, rice,
dry beans, milk, beef, chicken, eggs and pork) and 6 regions: South (states of Rio Grande
do Sul, Santa Catarina and Paraná), Southeast (states of São Paulo, Minas Gerais, Rio de
Janeiro and Espírito Santo), Central-West Cerrados (states of Goiás, Mato Grosso do Sul
and Mato Grosso under the Cerrados ecosystem), North-northeast Cerrados (states of
Tocantins, Bahia, Piauí and Maranhão under the Cerrado ecosystem), Amazon Biome
(states of Acre, Amazonas, Rondônia, Roraima, Amapá, Pará and Mato Grosso under the
Amazon ecosystem) and Northeast Coast (states of Ceará, Rio Grande do Norte, Paraíba,
Pernambuco, Alagoas and Sergipe). Estimated projections are performed on a yearly basis
over a period of 10 years.
Sugarcane ethanol
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Given that the model is under development, a reduced version, comprising only the land
allocation components, is used for projections presented here. Domestic demand and
expected net trade are calculated exogenously, using world prices contained in the Fapri’s
2008 Outlook (Fapri, 2008). Production is calculated in order to meet demand and net
trade needs.
Total national area allocated for grains and sugarcane is calculated according to yields trends.
In the case of pasture, total national area is the sum of regional areas. For each region, land
allocation equations were specified according to the competition among crops and cattle.
The allocation of land on the six regions and between product’s categories is calculated
on the model’s land use component. The amount of land to be allocated for each activity
is defined according to the required production to meet the domestic demand and net
trade projections and yields trends. Allocated land is calculated by region, and crops and
pasture compete according to the expected market returns per hectare. For each region and
activity, specific competition equations were defined and elasticities were calculated. Land
use change is measured comparing, in each region, the amount of land allocated for each
activity. Absolute annual variation indicates activities that are incorporating land and the
ones that are being displaced.
The competition matrix used for the specification of the land allocation regional models is
described in Table 2. The competition matrix was defined according to trends in harvested
area observed from 1997 to 2008 and comparing market returns per hectare. Activities
with higher market returns tend to have a lower number of competitors. Historical market
returns also indicate activities that are land taker and land releaser. Cattle, for example, is a
typical land releaser activity and, therefore, all crops compete with pasture.
It is important to mention that the regional area allocated to pastures is calculated
independently of the herd projections. Projections on regional herd and pasture must
be compared to evaluate whether they are compatible with stocking rate (number of
animals per hectare) trends. Although this is a limitation, because the stocking rate is
not endogenous on the model, the results presented in this study are in line with the past
trends in stocking rate.
Regional data, however, is too aggregate for the objective of evaluating direct land use
effect of sugarcane expansion. Regional projections are breakdown by micro-regional
level, in order to obtain the same level of disaggregation used in the section 3.3. Products
categories are aggregated in sugarcane, pastures and grains6. Projected land use for each
category is disaggregated according to the evolution of market share of each micro-region
in the region.
6 Grains, for the objective of the projections, comprise the following activities: soybean, maize, cotton, rice and
dry beans.
74
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
Table 2. Regional land competition matrix.
Region and competing product
sugarcane sugarcane
maize
soybean
Southeast
soybean
maize
sugarcane sugarcane
maize
soybean
cotton
cotton
sugarcane sugarcane
maize
soybean
cotton
cotton
maize
soybean
Centerwest
Cerrados
Amazon
biome
Northeast
coastal
Northnortheast
Cerrados
soybean
maize
soybean
maize
soybean
maize
cotton
maize
cotton
soybean
soybean
maize
rice
all crops
all crops
soybean
all crops
soybean
all crops
maize
soybean
maize
rice
dry beans
Cattle/pasture
soybean
maize
Dry beans
South
Rice
Maize
Soybean
Cotton
Sugarcane
Product (dependant variable)
soybean
maize
all crops
soybean
maize
rice
all crops
The calculation of the substitution of crops and pastures by sugarcane is executed following
a similar methodology of the Shift share model presented in the section 3.2. Given that the
projected period used was 2008 to 2018, sugarcane expansion is calculated as the absolute
variation from 2018 to 2008 and crops and pastures expansion is calculated using a one
year lag.
As well as the secondary data analysis for past expansion, the model is using harvested area
rather than planted area. Therefore, the total area occupied with sugarcane is necessarily
higher than the amount presented in the projections.
4. Results and discussions
The results are discussed following the same structure of the methodology section: (a) Subsection 4.1 presents the past expansion measured through remote sensing techniques; (b)
Sub-section 4.2 brings the results based on secondary data; (c) Sub-section 4.3 is devoted
Sugarcane ethanol
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Chapter 3
to the case studies; (d) Sub-section 4.4 presents the projections on land use for sugarcane;
and (e) Sub-section 4.5 discusses options for analyzing ILUC.
A summary of the results obtained from the three different methodologies used in this study
is presented in Table 3. Detailed results are discussed in the sub-sections.
Table 3. Land use classes converted to sugarcane: comparative results in the South-Central region
(1000 ha).
Period/measurement method
Sugarcane expansion
Agriculture
Pasture
Other
2002-2006
(harvested area)1
2007-2008
(planted area)2
2008-2018
(harvested area)3
1,030
122 (12%)
793 (77%)
114 (11%)
2,184
1,152 (53%)
991 (45%)
42 (2%)
3,848
1,455 (38%)
2,369 (62%)
24 (1%)
1
Source: secondary data from IBGE.
Source: satellite images.
3 Source: projection model.
2
4.1. LUC evaluation through remote sensing images
This sub-section analysis the expanded sugarcane area harvested for the first time and is
divided in three parts: (1) analysis comprising the years of 2007 and 2008 for the states of
Minas Gerais, Goiás, Paraná Mato Grosso do Sul and Mato Grosso; (2) analysis comprising
the period from 2005 to 2008 for the State of São Paulo; and (3) analysis comparing the years
of 2007 and 2008 for the reduced South-Central region3 (or South-Central region minus
the states of Rio de Janeiro, Espírito Santo, Santa Catarina and Rio Grande do Sul).
4.1.1. Analysis for the years of 2007 and 2008 in the states of Minas Gerais, Goiás,
Paraná, Mato Grosso do Sul and Mato Grosso
Figure 5 shows the results for the Pasture, Agriculture, Reforestation and Forest classes which
were displaced for the expansion of sugarcane crop harvested for the first time in 2007 and
2008. Most of the expansion of sugarcane area took place over the Agriculture and Pasture
classes. The Agriculture class registered the largest displaced area to sugarcane except for
76
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
739
1%
25,656
21%
Minas Gerais
Total expansion:
2007
120,306
2008
141,190
876
1%
48,284
34%
93,883
78%
91,959
65%
Goiás
Total expansion:
2007
85,559
2008
143,155
25,703
30%
59,442
70%
34,514
24%
108,072
76%
Paraná
Total expansion:
2007
107,350
2008
97,719
35,039
33%
42,336
43%
71,883
67%
1,119
2%
55,159
57%
Mato Grosso du Sul
Total expansion:
2007
46,446
2008
87,434
18,395
40%
48,465
55%
26,823
58%
1,892
8%
38,908
45%
2,385
Mato Grosso
8%
Total expansion:
2007
25,524
2008
30,735
8,440
33%
10,555
34%
15,134
59%
2007
forest
agriculture
pasture
17,761
58%
2008
Figure 5. Area in hectares and percentages of the land use classes converted to sugarcane in 2007
and 2008 in the states of Minas Gerais, Goiás, Paraná, Mato Grosso do Sul and Mato Grosso.
Sugarcane ethanol
77
Chapter 3
Mato Grosso do Sul in 2008 when the Pasture and Agriculture classes took place over 55.4
and 44.5% of the sugarcane expansion, respectively.
For the analyzed states in this section it was verified that the Agriculture class decreased
its contribution of displaced area for sugarcane expansion from 69.3% in 2007 to 62.2% in
2008. Conversely the Pasture class increased its contribution from 29.4% in 2007 to 37% in
2008 suggesting a trend of increasing sugarcane expansion over the Pasture class.
In Minas Gerais, Goiás and Paraná more than 99% of the sugarcane expansion was observed
over the classes of Agriculture and Pasture. In Mato Grosso do Sul, 2.41% (1,119 ha) of the
area of sugarcane expansion took place over the Forest class in 2007; while in 2008 it was
insignificant (61 ha). In the state of Mato Grosso the sugarcane expansion over the Forest
class was 7.4% (1,892 ha) in 2007 and 7.8% (2,385 ha) in 2008.
4.1.2. Analysis for the period from 2005 to 2008 in the state of São Paulo
Figure 6 shows the results for Pasture, Agriculture, Reforestation, Forest and Citrus classes
which were displaced for the expansion of the sugarcane crop harvested for the first time
from 2005 to 2008 in São Paulo State. During the analyzed period a sugarcane expansion
of 1,810 million ha was observed. Pasture (53%; 960,000 ha) and Agriculture (44.6%;
808,000 ha) were responsible for 97.7% (1,768 million ha) of the change. About 2% (36,900
ha) of sugarcane expansion took place over the Citrus class and 0.31% (5,500 ha) over the
Reforestation and Forest classes together. Based on the data shown in Figure 6 it is not
possible to conclude that the Pasture class tends to increase its contribution in displaced
area for sugarcane expansion in relation to the Agriculture class. Nevertheless in 2008 the
Pasture class contribution is the largest (56.1%) and the Agriculture class is the smallest
(40.6%) in the four analyzed years.
4.1.3. Analysis for the years of 2007 and 2008 in the South-Central region
Figure 7 shows the results that refer to the classes of land use that were displaced for sugarcane
expansion in the most relevant producing states of the South-Central region in 2007 and
2008. In both years, Pasture and Agriculture classes were together responsible for 98.1%
of the total area displaced for sugarcane expansion (2,184 thousand ha). The Pasture class
was responsible for 45.4% (0.991 million ha) and the Agriculture class was responsible for
52.7% (1,152 thousand ha) of the displaced area for sugarcane (Table 3). About 1.3% of
sugarcane expansion took place over the Citrus class (28,916 ha) and 0.58% (12,623 ha) over
the Reforestation and Forest classes together (others in Figure 7). Figure 7 shows that the
Agriculture class was more displaced than the Pasture class for sugarcane expansion; however,
78
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
6,523
2%
1,429
1%
107,352
52%
96,940
47%
2005
8,997
1%
160,540
53%
137,456
45%
citrus
agriculture
pasture
2006
19,919
3%
Total expansion:
304,625
48%
2005
2006
2007
2008
205,958
305,603
636,814
661,969
268,633
41%
371,262
56%
321,119
51%
2007
2008
Figure 6. Area in hectares and percentages of the classes of land use that were displaced for
sugarcane expansion in São Paulo State from 2005 to 2008.
8,997
1%
6,863
1%
434,330 571,810
42%
56%
2007
19,919
2%
5,760
0%
556,703
48%
others
citrus
agriculture
pasture
579,821
50%
2008
Total expansion:
2007
2008
1,022,000
1,162,203
Figure 7. Area in hectares and percentages of the classes of land use displaced for the expansion
of sugarcane in the most relevant sugarcane producing states in the South-Central region in 2007
and 2008.
Sugarcane ethanol
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Chapter 3
the Pasture class increased from 42.5 to 47.9% its relative contribution, while the Agriculture
class decreased its relative contribution from 55.9 to 49.9% from 2007 to 2008.7
Finally we can conclude that the remote sensing images obtained systematically by
the Landsat and CBERS satellites enabled an accurate identification of land use classes
defined in this work, which were displaced for the recent and most relevant sugarcane
expansion observed in Brazil. The visual interpretation of the remote sensing images on
a computer screen is hard-working, but it allows an accurate classification of the areas of
interest producing a reliable thematic classification through an objective and measurable
procedure.
4.2. Micro-regional secondary data
The dynamics of agricultural area and sugarcane in particular is presented in Table 4.
Sugarcane expansion from 2002 to 2006 in the ten states analyzed reached 1,077 thousand
ha, and more than half of this number occurred in São Paulo State. From this total expansion,
773 thousand ha displaced pasture land and 103 thousand ha displaced other crops, while
only 125 thousand ha were not able to be allocated over previous productive areas. Total
agricultural area growth – the sum of all crops, including sugarcane, and pastures – in the
period was 3,376 thousand ha.
By looking at Table 4 it is possible to state that sugarcane expansion is relatively small
comparing to total agricultural expansion in many states, particularly in Mato Grosso and
Tocantins (about 1% of total agricultural expansion) and Paraná and Mato Grosso do Sul
(about 16% of total agricultural expansion). Expansion of agriculture as a whole means
new areas are converted to productive uses, which were former natural landscapes (forests,
Cerrado savannah, natural pastureland, and so on) or idle areas. In those states where total
agricultural area decreased over the analyzed period (Minas Gerais, Goiás, Maranhão
and Piauí), there is no clear evidence that sugarcane expansion had taken place over non
anthropized areas.
It is also important to state the significant proportion of sugarcane expansion over pasture,
which represents 72% of total sugarcane expansion. By state level, also 72% of sugarcane
increased over pasture in São Paulo, while in Minas Gerais, Paraná and Goiás these numbers
were 51, 63, and 90%, respectively. This result is quite different from the one presented in
Section 4.1 and a possible reason to explain this distortion is presented in Section 4.3.
7 A recent study published by CONAB (2008), stated that the sugarcane expansion in the 2007 harvest in Brazil,
totaling 653,722 ha, has occurred mainly over pastureland, 64.7%, followed by maize and soybean, 21.8%. New
areas were responsible for 2.4% of area used for sugarcane expansion. These data were collected through 343
interviews with sugarcane mill managers.
80
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
Table 4. Area of crops and pasture displaced for sugarcane expansion by State, from 2002 to 2006
(1,000 hectares).
State
São Paulo
Minas Gerais
Paraná
Goiás
Mato Grosso do Sul
Mato Grosso
Bahia
Maranhão
Piauí
Tocantins
Total
1
Total agricultural
expansion
146
-1,251
535
-775
281
4,945
124
-655
-122
148
3,376
Sugarcane expansion
Total growth
Over pasture
Over other
crops
N.A.1
639
160
92
63
45
31
27
16
3
1
1,077
460
157
58
56
44
18
19
12
0.2
0.5
773
115
2
2
0.1
0.6
3
5
0
0
0
103
65
1
32
6
0.1
10
3
5
2
0.6
125
N.A. means not allocated over previous productive area.
It is important to note that the shift-share methodology is not sufficiently robust to explain the
re-allocation of land in regions that are subjected to expansions in all categories of products.
In those regions, new land has been incorporated into agricultural production, which might
be attributed to the conversion of forest to agriculture or to the use of previous idle areas.
However, the model is not able to identify this conversion since data on deforestation are
not necessarily available for the same period of time and for the same geographical unit.
Even if we could assume that 100 percent of the expanded area results in natural vegetation
conversion, it would not be possible to isolate the contribution of the sugarcane for this
process. One possible alternative to explain the not allocated area presented above would
be to assume a partial indirect effect at a micro-regional level. The indirect effect is partial
because the amount of not allocated area of sugarcane would be allocated in the amount
of new area proportionally of the share of sugarcane expansion to the total agriculture
expansion. The assumption that sugarcane is expanding in not anthropized area, however,
is not corroborated by satellite images as discussed in the previous section.
4.3. Environmental licensing reports
As a first result of this field research, it was possible to count and locate new mills projects in
six different states (Table 5). Goiás is the state that has more projects under analysis, which
Sugarcane ethanol
81
State
Goiás
Tocantins
Mato Grosso do Sul
Mato Grosso
Minas Gerais3
São Paulo3
1
Chapter 3
82
Table 5. Number of sugarcane mills in selected states and sampled mills information on land use change.
Number of mills
Mills sampled
Under analysis/ Sampled
total 1
Crushing
capacity
(1,000 ton/
year)
Sugarcane
area
(1,000 ha)
Previous land use (1,000 ha) 2
Pasture
Grains
Permanent
crops
Natural
vegetation
13,000
7,100
40,610
15,000
3,822
8,000
130
91
494
200
47
108
37.5
24
101
yes
yes
50.5
32.5
12
yes
32.5
yes
yes
no
no
no
no
no
yes
no
10
no
0.8
yes
no
53/72
2/4
36/47
4/14
22/52
37/205
4
4
13
8
2
3
Under analysis means the project mill is under environmental analysis.
The numbers refer to those studies which presented land use changes numbers, while ‘yes/no’ refer to those studies which did not quantified
land use.
3 Minas Gerais and São Paulo total mills are preliminary data.
2
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
means sugarcane is expanding significantly there. The projects under analysis correspond to
more than 70% of total projects, while in São Paulo, traditional producer state, it represents
about 18%.
Mato Grosso do Sul is another state where new mills are majority, and where sugarcane
expansion is very recent. Although the state production represents less than 3% of sugarcane
production in 2007, this share is expected to increase considerably over next years. Thirty six
new projects are under environmental analysis, while just eleven are already in operation,
and from the thirteen new projects’ Environmental Studies analyzed no forest is expected to
be suppressed. All new projects needs to present EIA-RIMA and public hearings take place
in the local town, where the environmental agency team helps to divulgate and motivate
community to participate.
Minas Gerais is currently the third biggest sugarcane producer right after Paraná State and
has a significant number of new mills that are being projected. The regions concentrating
the majority of new projects are mainly in the south and south-eastern – the later including
a traditional cattle raising region denominated Triângulo Mineiro. In spite of the fact that
sugar mills need environmental licenses, the state law doesn’t require EIA-RIMA, which
means that simpler studies are made in order to get the license. These studies don’t include
land use changes impacts and public hearings are not necessary.
In Mato Grosso State, expansion dynamics is different. During the 80’s, some sugarcane mills
were implemented in order to produce ethanol, as part of PROALCOOL Plan. After decline
in governmental supports and the crisis in the sector, some mills have been closed down
while others have started to produce sugar as well, and thus have kept business profitable.
Recently, two mills that used to be no longer in operation are requesting licenses to come
back to business. Nevertheless, sugarcane production is relatively small in this state, and
only two new mill projects are under analysis.
The State of Tocantins is not under important sugarcane expansion now, but it is expected to
be in near future if demand for land for this crop keeps increasing. The state Environmental
Agency estimates that after the implementation of North-South railway the regional
transportation problem will be solved and about 50 sugar mills will be constructed. Thus,
the state government wants to get ready for this huge demand over environmental licensing
and planning for this land use change.
São Paulo is the most important Brazilian state for sugarcane production and the most
industrialized, urbanized and occupied state. Many of existing mills are requesting licenses
to expand crushing capacity and some new mills projects are also under licenses analysis.
Some studies analyze the impact of this recent sugarcane expansion over other crops in this
state, resulting especially in reduction of pastures, citrus and maize areas (Coelho et al.,
2007). Camargo et al. (2008) state that land rental for sugarcane has increased by an average
Sugarcane ethanol
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of 12.6% from 2001 to 2006 in São Paulo, contributing to diminish expansion in São Paulo,
which in turn can boost sugarcane expansion in other states.
Two significant facts regarded to land use change caused by sugarcane were verified during
this field research. First, many of the projects which were considering to use pasture to
cultivate sugarcane mentioned the necessity of one or two years cultivating other crops, such
as soybean prior to the planting of sugarcane, in order to improve the soil quality of the low
productive pasture land (regarding structure and/or fertility). This fact may partially explain
the relative big proportion of sugarcane expansion over the Agriculture class detected in
the remote sensing image analyses (Section 4.1). Since data presented in this paper are not
able to verify this fact, deeper analysis are necessary to evaluate whether these crops were
cultivated just to prepare the soil under pasture for sugarcane, meaning that the Agriculture
class could possibly be overestimated (and therefore the Pasture class underestimated).
The other significant fact is the common use of crop rotation during sugarcane renovation
process. After a number of harvests – generally five to six – sugarcane yield decreases
and, therefore, the sugarcane field should be renovated. This is usually performed with
an ‘18 months’ sugarcane plant. In this case an annual food crop such as soybeans can be
cultivated during the summer season. Potentially, this means that about 15 to 20% of the
cultivated sugarcane area can be cultivated with an annual crop in order to improve soil
quality, prevent soil erosion and contribute to food production. Although this practice is
not used in all sugarcane fields, it has been disseminating fast and it is likely to be used in
the majority of areas all over Brazil.
4.4. Expected sugarcane expansion and implied land use changes
Projections developed for this study are indicating that harvested sugarcane area in Brazil
will reach 11.7 million ha in 2018, departing from 7.8 million ha in 2008. Area allocated for
crops (soybean, maize, cotton, rice and dry beans) is expected to grow from 37.8 million
ha to 43.8 million ha. Pasture area will move to the opposite direction, being reduced from
165 to 162 million ha.
Projections on regional level are presented in the Figure 8. The figure shows that the
South-Central region, comprising the regions South, Southeast and Center-west Cerrados,
will continue to be the most relevant and dynamic. North-northeast region is also very
important but, as described in the methodology section, it is not a dynamic region in terms
of growth.
Table 6 summarizes the expected growth in the South-Central region. Results show that
the expansion of grains and sugarcane are fully compensated by the reduction on pasture
area. Projections also confirm that cattle production is improving in terms of productivity
given that the herd is increasing despite of the reduction on pasture area.
84
Sugarcane ethanol
35,000
30,000
25,000
20,000
15,000
10,000
5,000
Pasture
Grains
Sugarcane
Figure 8. Projected evolution of sugarcane, grains and pasture area in agricultural regions (1,000 ha).
18(p)
16(p)
18(p)
16(p)
14(p)
12(p)
10(p)
0
08(e)
18(p)
16(p)
14(p)
12(p)
40,000
85
Prospects of the sugarcane expansion in Brazil
10(p)
18(p)
North-northeast Cerrados
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
08(e)
16(p)
18(p)
16(p)
14(p)
Amazon biome
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
14(p)
Southeast region
12(p)
08(e)
18(p)
16(p)
14(p)
0
12(p)
0
10(p)
10,000
08(e)
5,000
10(p)
20,000
10,000
14(p)
30,000
15,000
12(p)
40,000
20,000
12(p)
25,000
10(p)
50,000
Northeast coastal
08(e)
30,000
18,000
16,000
14,000
12,000
10,000
8,000
6,000
4,000
2,000
0
10(p)
Central-west Cerrados
60,000
08(e)
Sugarcane ethanol
South region
35,000
Chapter 3
Table 6. South-Centre: expected land allocation for sugarcane, grains and pastures (1,000 ha and
heads).
Sugarcane (ha)
Grains (ha)
Pasture (ha)
Total (ha)
Cattle herd (hd)
2008
2018
Net growth
6,359
26,332
92,328
125,018
119,399
9,654
29,529
86,215
125,398
125,501
3,295
3,198
-6,113
380
6,102
Detailed analysis on sugarcane, crops and pasture expansion was developed for the SouthCentral region, in order to standardize the producing regions with the past land use change
presented in the previous sections. Figure 9 shows the results obtained for São Paulo, Minas
Gerais, Paraná, Goiás, Mato Grosso do Sul and Mato Grosso. Sugarcane expansion will
follow trends in terms of land use change similar to the ones observed in the past.
The absolute variation shows that expansion will be larger in São Paulo, with 1.9 million
ha expansion. However, the relative variation shows that Minas Gerais (98 percent growth
in comparison to 2008), Paraná (98 percent expansion), Goiás (118 percent expansion)
and Mato Grosso do Sul (105 percent) are the states where sugarcane will present the most
dynamic expansion.
Apart from Minas Gerais, pasture is losing area in all states, while crops area is decreasing
only in São Paulo. Due to this strong reduction in pasture and simultaneous growth in
sugarcane and crops, the results indicate that both categories are displacing pasture. Microregional data in states such as Paraná and Goiás allow us to conclude that crops area displaced
by sugarcane is partially compensated over pastures areas. The reduction on pastures area,
as already shown in Table 6, is expected to be compensated by yields improvement. Even in
states where cattle herd tend to fall, such as São Paulo and Paraná, pasture area reduction
does not compromise beef and dairy production. In the Centre-West states, Goiás, Mato
Grosso do Sul and Mato Grosso, pastures areas are declining and projected cattle herd is
increasing, showing strong productivity gains.
It is also important to say that pasture area is expected to increase only in the Amazon Biome
region. However, this expansion is taken place independently of the other regions, because
cattle herd is increasing in the South-Central region, which is the sugarcane expansion
region. Projections also confirm results observed by satellite images: as soon as the sugarcane
increases its expansion, more pasture is displaced in comparison to grains. Pasture land
displacement is majority in Minas Gerais and Centre-West states. In Paraná sugarcane
expansion will push grains production to pastures area. We probably will see the same
86
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
14,611
3%
57,421
10%
910,312 1,027,675
53%
47%
9,051
2%
São Paulo
233,516
40%
331,232
58%
Paraná
499,969
87%
Minas Gerais
113,223
261,014
30%
70%
N.A.
crops
pasture
Goiás
2,842
1%
248,177
99%
Mato Grosso do Sul
40,269
29%
98,498
71%
Total expansion:
São Paulo
1,938,211
Minas Gerais
572,000
Paraná
573,799
Goiás
374,237
Mato Grosso do Sul 251,018
Mato Grosso
138,767
Mato Grosso
Figure 9. Projection of crops and pasture displacement due to sugarcane expansion, from 2008 to
2018 in selected Brazilian states (in ha).
Note: N.A. means not allocated over previous productive area.
process in São Paulo, although not only pasture but also grains are strongly releasing land
for sugarcane.
Grains are releasing 1.6 million ha for sugarcane but, as can be observed in the Table 6,
total area is expanding by 3.9 million ha, more than compensating the losses for sugarcane.
Pasture area will be reduced by 6.1 million ha and sugarcane is contributing with 2.4 million
ha of this total.
Sugarcane ethanol
87
Chapter 3
4.5. Options for approaching indirect effect
Indirect Land Use Change analysis is still under development, both in terms of proper
definitions and methods to measure it. Regarding to its definitions, Gnansounou et al. (2008)
classify four different sources of ILUC: spatial ILUC (displacement of prior production to
other location); temporal ILUC (shifting land-use in the same location); use ILUC (shifting
biomass use in the same location); and displaced activity/use ILUC (avoiding national landuse change by shifting previous activity to other country).
According to the authors, ILUC is market driven, global effect, spatial dependent and time
dependent. The first two items must be analyzed in a global scale, while the last two need
down-scaling analysis. Considering local analysis, although there is no consensual method
in specialized literature, it is possible to use available land use data to clarify some points.
Notwithstanding that the sources of ILUC can be formally defined from a theoretical
perspective, the difficulties associated to isolate and to separate the contribution of each
source to the indirect effect make empirical analysis much less promising than what it
appears to be. Thus, even though it is reasonable to state that the displacement of one
activity as a result of the expansion of other activity may lead to an indirect land use
change, as argued by Searchinger et al. (2008), such as deforestation, this incorporation
of additional land may be happening despite of the expansion of biofuel’s feedstocks
production. Additionally, when the expansion of biofuel’s feedstocks is taking place in
conjunction with the expansion of agricultural products for food production, it is hard to
prove effect-cause relations between biofuel’s expansion and deforestation. This is exactly
one of the fragilities of Searchinger’s paper.
It is beyond of the objectives of this paper to address ILUC in a worldwide perspective.
However, due to the fact that sugarcane is expanding in Brazil, it is necessary to search
for arguments and data supporting the idea that sugarcane expansion is leading to an
increase in the land productivity, rather than promoting incorporation of new land for food
production, as grains and pasture land are displaced. Both projections and observed data
give indication that this process is taking place in Brazil. As presented in Tables 6 and 7, the
strong increase in pasture productivity, measured by the stocking ratio, make the Brazilian
case a strong example of how hard it is to empirically prove the ILUC effect associated to
the expansion of sugarcane.
As discussed in previous sections, sugarcane expansion is taking place in anthropized areas.
Although this paper has no evidences regarding deforestation in Brazil, it is well known
that deforestation is observed in the agricultural frontier. Brazil has two most important
frontiers: the Amazon Biome region, where the Amazon Forest is located, and the Northnortheast Cerrados region (also called as MAPITO region), where the larger stock of
savannah land is located. Both past data and projections have shown that sugarcane is not
88
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
significantly expanding in these regions. Moreover, the expansion of pastures and grains
area in the Amazon Biome region, which one would argue that it is happening due to the
indirect effect, are lower than the area displaced by sugarcane in the South-Central region.
As presented in the Table 6, we project that pasture will lose 6 million ha for sugarcane
and grains in the South-Central region for the period of 2008 to 2018. Projections for the
Amazon Biome region indicate that pasture area will increase by 4 million ha for the same
period (Figure 8). Those numbers show that one unity of pasture land lost does not have to be
fully compensated in the frontier because productivity of the cattle production is increasing.
Results of this study, therefore, support the idea that both pasture land improvement and
increasing stocking rate can more than compensate land released for sugarcane and even for
other crops. Regional herd data presented in Table 7 reinforces even more this evidence.
In the states where sugarcane area increased from 2002 to 2006, other crops area have also
increased (exception for São Paulo), which means there is no clear reason to state that
sugarcane has displaced crops which in turn could occupy natural vegetation (Table 7). A
similar rational can be made for pasture land, but now including yield improvement. The
Table 7. Net growth of sugarcane, other crops, pasture land, total used area, and cattle herd from
2002 to 2006 in selected Brazilian states (1,000 ha and heads).
State
São Paulo
Minas Gerais
Paraná
Mato Grosso do Sul
Goiás
Bahia
Mato Grosso
Maranhão
Pará
Piauí
Rondônia
Tocantins
Acre
Total
Net growth 2002-06
Sugarcane
(ha)
Other crops
(ha)
Pasture land
(ha)
Total used
area (ha)
Cattle herd
(heads)
622
153
74
41
34
27
25
16
3
3
1
0.9
0.7
1,000
-224
390
850
734
576
492
1,634
298
115
206
124
238
13
5,446
-882
-625
-636
-985
-2,041
143
-1,437
-463
2,502
-112
-364
-595
109
-5,385
-484
-82
287
-210
-1,431
661
222
-148
2,620
97
-239
-355
123
1,061
-909
1,644
-284
558
545
912
3,881
1,835
5,311
34
3,444
778
635
18,383
Source: PAM/IBGE, Agricultural Census/IBGE and PPM/IBGE.
Sugarcane ethanol
89
Chapter 3
states that have lost pasture land have also increased cattle herd (exception for São Paulo and
Paraná), meaning there was an improvement in the cattle sector. Therefore, it is important
to state that biofuels produced from biomass grown on unused arable land or resulting from
yield improvements (as much of the pasture land displaced for sugarcane) have no indirect
effects according to the Roundtable on Sustainable Biofuels (2008).
Thus, yields improvements in crops can be considered as area’s release, meaning that the
same amount of cereals, for example, is produced on a smaller area, leaving area available for
other uses. Ceteris paribus, i.e. not considering other variables such as increase in demands,
yield improvements alleviate area for other purposes. Sugarcane cultivated over these areas
does not compete with land and has no indirect effects. For a total of about 1,390 thousand
ha of agricultural area displaced for sugarcane verified by satellite images in the six states
analyzed, 572 thousands ha were released by crops yields improvements (Table 8).
Grains, cereals and oilseeds area displaced, besides yields improvements, necessarily
have to be compensated in a non-sugarcane area, although food production would be
compromised. However, crops re-allocation could also take place in pastures areas, being
partially compensated by cattle yield improvements. Moreover, if the expansion of food
Table 8: Agricultural area displaced by sugarcane and agricultural area compensated by yield
improvement from 2005 to 2008 (São Paulo) and 2007 to 2008 for the other States.
State
Agricultural area
displaced by
sugarcane1
(1,000 ha)
Average annual
yield growth2
Agricultural area
compensated by
yield improvement3
(1,000 ha)
Minas Gerais
Goiás
Paraná
Mato Grosso do Sul
Mato Grosso
São Paulo
Total
186
168
127
66
33
808
1,387
4.4%
1.9%
4.8%
5.8%
9.5%
3.4%
118
46
231
30
44
103
572
1
Source: Figures 5 and 6.
Averages are calculated from CONAB data for soybeans, maize, rice, dry beans and cotton, for the
period of 1991 to 2008 (www.conab.gov.br).
3 The baseline agricultural area (2005 for São Paulo and 2007 for the remaining states) for the
selected crops were discounted by the area ‘saved’ due to those yield growth.
2
90
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
crops is larger than the amount of land displaced by sugarcane, indirect effect cannot be
quantified. This is also the situation taking place in Brazil.
For global scale considerations for ILUC, however, the analysis is much more complex. In
this case, it is even more difficult to determine the proper scale pertinent, considering that
many countries produce and trade different products that can be related to ILUC analysis.
Regarding to shifting biomass use, Brazilian sugar production has also increased from 2002
to 2006, from 22.5 to 29.6 million tons, according to UNICA (2008). Meats and all grains
production have also increased significantly in the period and in the last years. Therefore,
there was no need to convert land in other countries due to increase in ethanol production
in Brazil. Nevertheless, all ILUC considerations can be considered preliminary and subject
to improvements since the topic has been developing fast recently.
5. Conclusions and recommendations
This work was an effort to analyze land use changes due to sugarcane expansion in Brazil,
contributing to the global debate about social and especially environmental benefits of
ethanol. A careful look of the distribution of sugarcane shows that the crop is located and is
expanding in regions that are devoted to agricultural production since a long time. Projections
indicated that sugarcane expansion will continue to take place on these areas. This means
that there is no sugarcane expansion in the agricultural frontier, which is the place where
agricultural production has been converting natural landscapes. Thus, results are indicating
that sugarcane is not directly pressing natural vegetation in any region in Brazil.
The use of different methods gives consistency to the analysis, since each one has its
weakness and strengths. Remote sensing images can be considered the most reliable source
of information, however they focused only in areas where sugarcane expansion took place,
neglecting dynamics of other crops and pasture land. Secondary data from IBGE cover
all significant productive land uses, nevertheless the data is subject to accuracy problems,
especially those relating to areas dedicated to pasture. Case studies through environmental
licensing reports can offer profound analysis to understand the dynamics of the mill,
although they are limited in scope of coverage. The land use model projects future trends
of land substitution among crops, based on past trends, but it relies on many economic
assumptions.
Both remote sensing and secondary data analysis have generated similar results regarding
direct land use changes promoted by sugarcane expansion. Although results are different
in terms of crops and pasture land displacement, they both corroborate that sugarcane
expansion has taken place with no direct effect on natural vegetation land. Furthermore,
pasture is increasing its participation on the area displaced by sugarcane, and this pattern
is expected to continue or even become more relevant in the future.
Sugarcane ethanol
91
Chapter 3
It is important to contextualize the LUC caused by sugarcane within the entire Brazilian
debate regarding land use and occupation and other factors correlated, including agricultural
and environmental public policies, international commodity markets and technology
development. ILUC issues, in turn, are even more complex and correlated to many other
factors. Sugarcane is concentrated in the most densely occupied state, São Paulo, which has
been presented signals of saturation many years ago. In a lack of clear land use and occupation
policy, sugarcane, as well as many other agricultural activities, has been expanding around
close states according to local conditions, both agronomic and economic. This movement
presses land valorization and thus contributes to improvements on agricultural yields (crops
and pasture), as it is happening in almost all regions in Brazil.
This study concludes that the expansion of crops, except sugarcane, and pasture land is
taking place despite of the sugarcane expansion. This is important because it reinforces
that, even recognizing that sugarcane expansion contributes to the displacement of other
crops and pasture, there is no evidence that deforestation caused by indirect land use effect
is a consequence of sugarcane expansion. Results on past data and projections show that
increasing cattle herd stocking rate is able to offset pasture land reduction in regions where
competition for land is taking place. Increasing productivity on cattle production, therefore,
also reinforces that the expansion of pasture land on the Amazon Biome is not directly
promoted by the expansion of crops and sugarcane in the non-frontier regions.
It is strongly recommended that the analysis here presented continues on a regular base
in order to guarantee that sugarcane activity continues to respect natural landscapes. As
any other agricultural product, sugarcane also contributes to land use changes. However,
as discussed here, these changes do not undermine sugarcane’s environmental benefits as
a renewable agricultural-based biofuel.
References
Camargo, A.M.M.P., D.V. Caser, F.P. Camargo, M.P.A. Olivette, R.C.C. Sachs and S.A. Torquato, 2008.
Dinâmica e tendência da cana-de-acucar sobre as demais atividades agropecuárias, Estado de São Paulo,
2001-2006. Informações Econômicas 38: 47-66.
Coelho, S.T., P.M. Guardabassi, B.A. Lora, M.B.C.A. Monteiro and R. Gorren, 2007. A Sustentabilidade da
expansão da cultura canavieira. Centro de Referencia em Biomassa – CENBIO – USP. Cadernos Técnicos
da Associação Nacional de Transportes Públicos, v. 6.
Companhia Nacional de Abastecimento (CONAB), 2008. Perfil do Setor de Açúcar e Álcool no Brasil.
Brasília: CONAB.
Food and Agricultural Policy Research Institute (FAPRI), 2008. FAPRI 2008: U.S. and World Agricultural
Outlook. FAPRI Staff Report 08-FSR 1. Available at: www.fapri.org (accessed in October 4th, 2008).
Gnansounou, E., L. Panichelli, A. Dauriat and J.D. Villegas, 2008. Accounting for indirect land-use changes
in GHG balances of biofuels: review of current approaches. École Polytechnique Fédérale de Lausanne,
Working Paper 437.101, March 2008.
92
Sugarcane ethanol
Prospects of the sugarcane expansion in Brazil
Instituto Brasileiro de Geografia e Estatística (IBGE), 2008b. Censo Agropecuário de 2008. Available at:
www.sidra.ibge.gov.br (accessed in July 10th, 2008).
Instituto Brasileiro de Geografia e Estatística, (IBGE), 2008a. Levantamento Sistemático da Produção
Agrícola. Available at: www.sidra.ibge.gov.br (accessed in July 10th, 2008).
Oliveira, A.A., M.F.M. Gomes, J. Dos Santos, L. Rufino, A.G. Da Silva Júnior, and S.T. Gomes, 2008. Estrutura
e dinâmica da cafeicultura em Minas Gerais. Revista de Economia Agrícola 34: 121-142.
Roundtable on Sustainable Biofuels, 2008. Background paper (teleconference June 3rd, 2008) of the Expert
advisory group and working group on GHG. Available at: http://cgse.epfl.ch/page65660.html (accessed
in August 2nd, 2008).
Rudorff, B.F.T and L.M. Sugawara, 2007. Mapeamento da cana-de-açúcar na Região Centro-Sul via imagens
de satélites. Informe Agropecuário. Geotecnologias, Belo Horizonte, 241: 79-86.
Searchinger, T., R. Heimlich, R.A. Houghton, F. Dong, A., Elobeid, J. Fabiosa, S., Tokgoz, D., Hayes and T.
Yu, 2008. Land clearing and the biofuels carbon debt. Sciencexpress. Feb., 2008.
Sugawara, L.M.S., B.F.T. Rudorff, R.M.S.P., Vieira, A.G. Afonso, T.L.I.N. Aulicino, M.A. Moreira, V. Duarte
and W.F. Silva, 2008. Imagens de satélites na estimativa de área plantada com cana na safra 2005/2006
– Região Centro-Sul. São José dos Campos: INPE (15254-RPQ/815). 74 p.
União da Indústria de Cana-de-Açucar (ÚNICA), 2008. Estatísticas de produção de açúcar no Brasil.
Available at: www.unica.com.br (accessed in July 29th, 2008).
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Chapter 4
Mitigation of GHG emissions using sugarcane bioethanol
Isaias C. Macedo and Joaquim E.A. Seabra
1. Introduction
The implementation of the Brazilian sugarcane ethanol program always included a
continuous assessment of its sustainability. The possibilities for increasing production in
the next years must consider the exciting promises of new technologies (that may lead to
50% more commercial energy/ha, from sugarcane) as well as environmental restrictions.
The greenhouse gases emissions associated with the expansion are analyzed in the next
sections.
2. Ethanol production in 2006 and two Scenarios for 2020
After the initial growth with the Pro-Álcool program (~12 M m3, from 1975 to 1984)
ethanol production in Brazil stabilized at this level until 2002, when the implementation of
the Flex Fuel cars led to a new period of strong growth (from 12.5 M m3 in 2002 to ~24 M
m3 in 2008; internal demand scenarios point to 40 M m3 in 2020, with exportation in the
10-15 M m3 range) (Carvalho, 2007; CEPEA, 2007; MAPA, 2007; EPE, 2007). Environmental
legislation phasing out sugarcane burning practices, the internal demand for electricity
and the opportunity with the large number of new sugarcane mills (Carvalho, 2007) are
leading to a fast transition from the ‘energy self-sufficient’ industrial unit to a much better
use of cane biomass (bagasse and trash), turning the sugarcane industry into an important
electricity supplier.
The evaluation of the GHG emissions (and mitigation) from the sector in the last years
(2002-2008) and the expected changes in the expansion from 2008 to 2020 must consider
technology (the continuous evolution and selected more radical changes), both in cane
production as in cane processing. Two (alternative) technology paths were selected:
• The Electricity Scenario follows the technology trends today, with commercially available
technologies: the use of trash (40% recovery) and surplus bagasse (35%) to produce
surplus electricity in conventional high pressure co-generation systems (Seabra, 2008).
• The Ethanol Scenario considers advanced ethanol production with the hydrolysis of
lignocellulosic cane residues; ethanol would be produced from sucrose but also in an
annexed plant with the surpluses of bagasse and of the 40% trash recovered (Seabra,
2008). This condition would lead to a smaller area (29% smaller, for the same ethanol
production) than the Electricity Scenario; technologies may be commercial in the next
ten years.
Sugarcane ethanol
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Chapter 4
The 2006 results are based on 2005/2006 average conditions, with the best available and
comprehensive data for the Brazilian Center-South Region (Macedo et al., 2008). Note that
GHG emissions/mitigation are evaluated for each Scenario specific conditions; Scenario
implementation schedules are not presented (or needed) for the objective of this study.
However, it must be said that the Electricity Scenario implementation is occurring now
in all Greenfield operations, and already in some retrofit of existing units. The Ethanol
Scenario as proposed still depends on technological development of the biomass hydrolysis/
fermentation processes, and it would take longer to be implemented to a significant level in
the context of the Brazilian ethanol production (Seabra, 2008).
The essential parameters for 2006 and the two 2020 Scenarios are presented in Table 1 (Cane
production) and Table 2 (Cane processing). The data used for 2006 is for a sample of 44 mills
(100 M t cane/season), all in the Brazilian Center South. Data have been collected/processed
for the last 15 years, for agriculture and industry, for the CTC ‘mutual benchmarking’.
The ethanol transportation (sugar mill to gas station) energy needs are (Seabra, 2008):
2006: 100% road (trucks), 340 km (average), 0.024 l diesel/(m3.km) (energy consumption).
2020: 80% road, with average transport distance and diesel consumption as in 2006; 20%
pipeline, 1000 km (average), 130 kJ/(m3.km) (pipeline energy consumption).
The hydrolysis/fermentation parameters in the Ethanol Scenario correspond to a SSCF
process, expected to be commercial before 2020, as seen in Table 3.
3. Energy flows and lifecycle GHG emissions/mitigation
The systems boundaries considered for the energy flows and GHG emissions and mitigation
include the sugarcane production, cane transportation to the industrial conversion unit,
the industrial unit, ethanol transportation to the gas station, and the vehicle engine
(performance). Methodologies use data and experimental coefficients as indicated in the
tables, and in some cases IPCC (IPCC, 2006) defaults; details are presented in Macedo et al.
(2008), Seabra (2008) and Macedo (2008). The CO2 (and other GHG) related fluxes are:
• CO2 absorption (photosynthesis) in sugarcane; its release in trash and bagasse burning,
residues, sugar fermentation and ethanol end use. These fluxes are not directly measured
(not needed for the net GHG emissions).
• CO2 emissions from fuel use in agriculture and industry (including input materials); in
ethanol transportation; and in equipment/buildings production and maintenance.
• Other GHG fluxes (N2O and methane): trash burning, N2O soil emissions from Nfertilizer and residues (including stillage, filter cake, trash)
• GHG emissions mitigation: ethanol and surplus bagasse (or surplus electricity)
substitution for gasoline, fuel oil or conventional electricity.
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Mitigation of GHG emissions using sugarcane bioethanol
Table 1. Basic data: sugarcane production.
Item
Units
Sucrose content
Fiber content
Trash (db) e
Cane productivity
Fertilizer utilization f
P2O5
K2O
Nitrogen
Lime g
Herbicide h
Insecticide h
Filter cake application
Stillage application
Mechanical harvesting
Unburned cane harvesting
Diesel consumption
% cane stalks
% cane stalks
% cane stalks
t cane/ha
kg/(ha.year)
kg/(ha.year)
kg/(ha.year)
t/ha
kg/ha
kg/ha
t (db)/ha (% area) i
m³/ha (% area) j,k
% area
% area
L/ha
2006 a
14.22
12.73
14
87.1
25
37
60
1.9
2.2
0.16
5 (70%)
140 (77%)
50
31
230
2020 scenarios b
15.25 c
13.73 d
14
95.0
32
32
50
2.0
2.2
0.16
5 (70%)
140 (77%) l
100 m
100 m
314
a
CTC’s database (44 mills in Center-South of Brazil, equivalent to ~100 Mt cane/year) (CTC,
2006a).
b Author’s projections; Scenarios are Electricity and Ethanol.
c 2020: increasing 1 point (%) in 15 years (variety development and better allocation).
d Apparent fiber increasing with increase in green cane harvesting (trash).
e Hassuani et al. (2005).
f Total averages, including: fertilizer use in plant and ratoon cane, in areas with and without stillage;
full description in Macedo et al. (2008). For Scenario 2020 Ethanol averages are slightly lower (~4%)
due to larger stillage production/utilization.
g Utilized essentially at planting.
h Macedo (2005a).
i Reforming areas: areas where sugarcane is re-planted, after the 6 year cycle.
j Ratoon areas: areas where sugarcane is cut to grow again, without re-planting
k It is considered that all stillage is used only in the ‘ethanol cane area’, but keeping the suitable
level of application (~140 m³/ha). For 2020 Ethanol scenario, see Note l.
l In the 2020 Ethanol scenario more stillage would be produced, from the ethanol derived from
hydrolysis. Stillage application would reach larger ratoon areas.
m Considering the legislation and phase out schedules for cane trash burning in SãoPaulo.
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Chapter 4
Table 2. Basic data: sugarcane processing.
Item
Units
2006 a
2020
electricity b
2020
ethanol b
Advanced
cogeneration
30
0
135 e
40
0g
92.3 h
Biochemical
conversion
kWh/t cane
kWh/t cane
kWh/t cane
% total
% total
l/t cane
Low pressure
cogeneration
14.0
16.0
9.2 d
0
9.6
86.3
Bagasse use
Electricity demand
Mechanical drivers
Electricity surplus
Trash recovery
Bagasse surplus
Ethanol yield
c
0
44 f
40
0g
129
a
CTC information (CTC, 2006b).
Authors’ projections.
c 30 kWh/t cane + 130 kWh/t hydrolyzed biomass (dry basis).
d Cogen’s data; only 10% of the mills use higher pressure boilers, and the remaining 90% still use
21 bar/300°C, with very low electricity surplus.
e All mills operating at 65 bar/480°C, CEST systems; process steam consumption ~340 kg steam/t
cane, and using recovered trash (40%).
f A hypothetical mill operating at 65 bar/480°C, ‘pure’ cogeneration; using ~340 kg steam/t cane.
g All biomass (bagasse and 40% trash) is used for power generation or ethanol production.
h Only the increase in sucrose % cane was considered.
b
Table 3. Bioconversion parameters (SSCF process with dilute acid pretreatment)a.
Hydrolysis
Fermentation
Energy demand
Electricity
Steam
Pre-treatments (kg/kg db)
Distillation (kg/l et)
Concentration (kg/l et.)
a
95 % (cellulose); 90% (hemicellulose)
95% (glucose); 85% (other sugars)
130 kWh/t (db)
0.45 (13 bar); 0.25 (4.4 bar)
3.0 (2.5 bar); 0.05 (22 bar)
0.2 (1.7 bar)
Based on Aden et al. (2002); details in Seabra (2008).
98
Sugarcane ethanol
Mitigation of GHG emissions using sugarcane bioethanol
The GHG emissions associated with direct land use change (LUC) are estimated separately
in the next section, where the possible indirect impacts of land use change (ILUC) are also
discussed for the specific case of the expansion of ethanol production in Brazil. The energy
use/conversion for 2006 and for each 2020 Scenario is presented in Table 4.
The corresponding GHG emissions for are in Table 5. Note that the differences in total
emissions are strongly dependent on the co-products credits. The large difference between
2006 and the 2020 Electricity Scenario is due to an actual increase in the system energy
efficiency (much larger energy output). An analogous increase in energy output occurred
between 2006 and the 2020 Ethanol Scenario, but note that the change is an increase in
ethanol output (rather than in electricity) and also the emissions are presented in kg CO2
eq/m3 ethanol. In the 2020 Ethanol Scenario the volume of ethanol produced/unit area (or
ethanol/ t cane) is 1.4 times larger than in the 2020 Electricity Scenario.
It is important to remember that the 2006 data (and results) correspond to the average
values of the parameters; even for a homogeneous set of producers (Brazil Center South
region) differences in processes (agricultural and industrial) impact energy flows and
GHG emissions. For the sample used, the variation of main production parameters and the
Table 4. Energy balance in anhydrous ethanol production (MJ/t cane).
Energy input
Agriculture
Cane production
Fertilizers
Transportation
Industry
Inputs
Equip./buildings
Energy output
Ethanol a
Electricity surplus b
Bagasse surplus a
Energy ratio
2006
2020 electricity
2020 ethanol
235
211
109
65
37
24
19
5
2,198
1,926
96
176
9.4
262
238
142
51
45
24
20
4
3,171
2,060
1,111
0.0
12.1
268
238
143
50
45
31
25
6
3,248
2,880
368
0.0
12.1
a
Based on LHV (Low Heating Value).
Considering the substitution of biomass-electricity for natural gas-electricity, generated with 40%
(2006) and 50% (2020) efficiencies (LHV).
b
Sugarcane ethanol
99
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Table 5. Total emission in ethanol life cycle (kg CO2 eq/m3 anhydrous) a.
Cane production
Farming
Fertilizers
Cane transportation
Trash burning
Soil emissions
Ethanol production
Chemicals
Industrial facilities
Ethanol distribution
Credits
Electricity surplus b
Bagasse surplus c
Total
2006
2020 electricity
2020 ethanol
416.8
107.0
47.3
32.4
83.7
146.3
24.9
21.2
3.7
51.4
326.3
117.2
42.7
37.0
0.0
129.4
23.7
20.2
3.5
43.3
232.4
90.6
23.4
26.4
0.0
92.0
21.6
18.5
3.2
43.3
-74.2
-150.0
268.8
-802.7
0.0
-409.3
-190.0
0.0
107.3
a
Emissions for hydrous ethanol/m3 are about 5% less than values verified for anhydrous ethanol.
Considering the substitution of biomass-electricity for natural gas-electricity, generated with 40%
(2006) and 50% (2020) efficiencies (LHV).
c Considering the substitution of biomass fuelled boilers (efficiency = 79%; LHV) for oil fuelled boilers
(efficiency = 92%; LHV).
b
corresponding response to each single parameter variation in GHG emissions are shown
in Figure 1.
Note that the electricity surplus and the bagasse surplus show very large variation now,
when a few mills have started to export large amounts of electricity. The net GHG avoided
emissions, including the ethanol substitution for gasoline and considering the engines
performances in Brazil (based on the experience with the fleet of 23 M vehicles, in the last
30 years, with E-24, E-100 and Flex Fuel engines) is shown in Table 6.
The use of the allocation (energy) criterion for the co-products (with the whole GHG
emissions associated with cane and ethanol production being distributed among ethanol,
electricity and surplus bagasse according to their energy content, and with no co-product
credits considered in the net emission) is compared to the use of the substitution criterion
(with the mitigation derived from ethanol, electricity and surplus bagasse use being
considered as well as all emissions from cane and ethanol production) in Figure 2; the
substitution criterion results are detailed in Table 6.
100
Sugarcane ethanol
GHG emission (kg CO2 eq/m3 etOH)
Mitigation of GHG emissions using sugarcane bioethanol
500
400
300
200
100
0
-100
-200%
-100%
0%
100%
200%
300%
400%
500%
Parameter variation
N-fertilizer use
Average distance (cane)
Unburned cane
Ethanol yield
Electricity surplus
Average distance (ethanol)
Trucks' energy efficiency
Mechanical harvesting
Cane productivity
Bagasse surplus
Other diesel consumption
Figure 1. GHG emissions variation in response to single parameter variation; including co-product
credits (2006 only).
Table 6. Avoided emissions due to ethanol use (t CO2 eq/m3 hydrous or anhydrous; substitution
criterion for the co-products).
2006
2020 electricity
2020 ethanol
Ethanol use a
Avoided emission b
Net emission c
E100
E25
E100
FFV
E25
E100
FFV
E25
-2.0
-2.1
-2.0
-1.8
-2.1
-2.0
-1.8
-2.1
-1.7
-1.8
-2.4
-2.2
-2.5
-1.9
-1.7
-2.0
a
E100, or HDE: hydrous ethanol in dedicated engines; FFV: hydrous ethanol in flex-fuel engines;
E25: anhydrous ethanol (25% volume) and gasoline blend.
b Avoided emission (negative values) due to the substitution of ethanol for gasoline; fuel
equivalencies verified for each application in Brazil (Macedo et al., 2008).
c Net emission = (avoided emission due to ethanol use) + (ethanol life cycle emission). Co-products
credits are included.
Sugarcane ethanol
101
Chapter 4
2020 electricity
2006
HDE
E25
HDE
FFV
E25
2020 ethanol
HDE
FFV
E25
0%
-20%
-40%
-60%
-80%
-100%
-120%
-140%
Allocation
Co-products credits
Figure 2. GHG mitigation with respect to gasoline: allocation or co-products credits.
As expected from the energy balances, the use of ethanol from sugarcane substituting for
gasoline leads to a very important GHG emissions mitigation; this is due mostly to the
use of cane residues as the source of energy for processing sucrose to ethanol. However,
the much more efficient use of the cane residues is leading to entirely offset the gasoline
emissions, and beyond that, as shown in Figure 2 for the 2020 Electricity scenario. A separate
accounting of the gains with electricity and ethanol (with allocation of the emissions) still
shows gains in the 2020 Scenarios, due to increase efficiencies/productivity in both cane
production and processing.
4. Land use change: direct and indirect effects on GHG emissions
The variation in carbon stocks (both in soils and above ground) due to changes in the land
use is included in the national carbon inventories, and evaluation methodologies have been
established. The large number of parameters (culture type; soil; cultivation practices; local
climate) and the lack of sufficient and adequate information for many cases lead to large
error estimates for the default values, both for the basic soil type/climate carbon stocks for
native vegetation and for the relative (main parameters) stock change factors (IPCC, 2006).
The use of adequate local data is recommended.
Recently the so called indirect land use change (ILUC) impact in emissions is being discussed;
the debate shows that we do not have suitable tools (methodologies) or sufficient data to
reach acceptable, quantified conclusions about ILUC impacts on GHG emissions, globally.
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Mitigation of GHG emissions using sugarcane bioethanol
However, local conditions in Brazil indicate a good possibility of significant increases in
ethanol production without increasing ILUC emissions. Both LUC and ILUC impacts on
emissions for ethanol are considered below.
4.1. Land use change with the ethanol production in Brazil: past and trends
Brazil has 28.3% (~440 M ha) of all original forests in the world, over a total surface of 850
M ha. From the agricultural land, only 46.6 M ha are used for grain; 199 M ha correspond
to ‘pasture’; large fraction of this is somewhat degraded land (extensive grazing, not planted
pasture).
Sugarcane for ethanol today (2008) uses only 4 M ha, slightly more than 1% of the arable
land in Brazil. Ethanol production increased fast with the Pro-Alcool Program until 1985,
when it reached 11.8 M m3; stabilized at this level, and in 2002 the production was 12.5 M
m3. There was no land use change with cane for ethanol in the period from 1984 to 2002.
Ethanol production growth re-started only in 2002, to an expected value of 26 M m3 in
2008 (MAPA, 2007; CONAB, 2008). The expansion area (sugar and ethanol) from 2005 to
2008 was 2.2 M ha in the Center-South (Nassar, 2008); ethanol used 49% of the sugarcane
in 2002, and 55% in 2008.
The patterns of land use change, as well as the changes in cane culture procedures determine
the associated impacts on GHG emissions. For land use change, a recent analysis (Nassar
et al, 2008) uses satellite images (Landsat and CBERS) available since 2003 for State of São
Paulo, and 2005 for other States; and secondary data (based on IBGE data, for the whole
region, from 2002 to 2006) is also analyzed for each micro-region using a Shift Share model.
A comprehensive field survey was reported by CONAB (CONAB, 2008) for the LUC
involving sugarcane from 2007 to 2008. Data was also obtained from the Environmental
impact reports (EIA – RIMA) needed for licensing new increases in sugarcane area (Nassar
et al, 2008); they refer also to the next years expected LUC.
Some of the main conclusions for the changes from 2002 to 2008 are:
1. Sugarcane always substitutes for established crops, or pasture lands; for economic
reasons, and with the large availability of low productivity pasture lands associated to
some pasture area conversion to higher efficiency systems, very small advances in native
vegetation (forests, cerrados) areas are observed. In some cases degraded pasture lands
are cultivated for one or two years with soybeans, to improve soil conditions before using
for sugarcane. Intercropping (rotation of sugarcane every five or six years, before a new
planting, with other crops) is becoming a widespread practice. Satellite data for the last
two years (2007/08 and 2008/09) for the cane expansion areas in the six Center South
cane producer states (total 2.18 M ha) indicates their origin: 53% from Agriculture; 45%
from Pastures; 1.3% from Citrus plantations; and only 0.5% from Arboreal Vegetation
Sugarcane ethanol
103
Chapter 4
(native or anthropic), including wood plantations (eucalyptus or pinus). The CONAB
survey (CONAB, 2008) indicates for ‘new areas’ (not all related to native vegetation) only
1.5% of the expansion, in 2007/08. All studies indicate that Pasture lands utilization is
surpassing Agriculture land utilization (for cane) in the last years, in many areas.
2. The field survey (CONAB, 2008) indicates for 2007/08 LUC the largest Agriculture area
substituted was soybean, followed by maize. The use of Pasture lands is also related to
the conversion from low productivity pasture (both native and some planted pasture:
degradation from inadequate management, and no fertilizers) (Macedo, 2005b), to high
productivity pastures, liberating areas. Estimates indicate today 150 M ha of cultivated
pasture land, and 70 M ha of ‘natural’ pastures.
3. Most of the expansion (94%) for sugar from 1992 to 2003 occurred around the existing
sugar mills, in the Center South; now sugarcane moves to the West and North of the
region, in the States of Goiás, Mato Grosso, Minas Gerais and Mato Grosso do Sul. This
is the trend for the next decade.
The analysis (Nassar et al., 2008) included the projected patterns of land use change for the
sugarcane expansion to 2020, considering land availability, biomes and reserved areas; the
response to prices/costs, demand and competition in Brazil and outside.
4.2. Soil and above ground carbon stocks
A recent study (Amaral et al., 2008) on ethanol production sustainability included data
on below and above ground carbon stocks for sugarcane (both burned and green cane
harvesting conditions) in Brazil, as well as for the most important replaced crops and
vegetation. The data was obtained from more than 80 reports in the last 8 years; a selection
was made to yield comparable results (for soil types, soil depths, methodology, cultural
practices).
Table 7 shows some results for soil carbon from the survey, as well as the default values
calculated with the IPCC recommendations (IPCC, 2006). The IPCC based values
correspond to the specific soil types (High or Low activity clay, HAC or LAC), climate,
crop type and cultivation practices for each crop. The experimental data indicates the soil
types (HAC, LAC or Sandy) and some cultural practices, always for 20 cm depth. Selected
values were used to evaluate the soil carbon stock change with land use change, for each
specific case (last column).
Table 8 (Amaral et al., 2008) shows the experimental values for the sugarcane and the main
replaced crops/pasture above ground carbon.
104
Sugarcane ethanol
Mitigation of GHG emissions using sugarcane bioethanol
Table 7. Soil carbon content for different crops (t C/ha).
Crop
Degraded pasturelands
Natural pasturelands
Cultivated pasturelands
Soybean cropland
Maize cropland
Cotton cropland
Cerrado
Campo Limpo
Cerradão
Burned cane
Unburned cane
IPCC defaults a
Experimental b
LAC
HAC
HAC
Other
33
46
55
31
31
23
47
47
47
23
60
46
63
76
42
42
31
65
65
65
31
83
41
56
52
53
40
38
46
72
53
35-37
44-59
16 c
24 c
35 d
Selected
values
41
56
52
53
40
38
46
72
53
36
51
a
Based on IPCC parameters indicated, IPCC, 2006
Amaral et al., 2008 (all 0-20 cm).
c Sandy soils.
d LAC soils.
b
Table 8. Above ground carbon stocks (t C/ha)a.
Degraded pasturelands
Cultivated pasturelands
Soybean croplands
Maize croplands
Cotton croplands
Cerrado sensu strictu
Campo Limpo
Cerradão
Unburned cane
1.3
6.5b
1.8c
3.9
2.2d
25.5e
8.4f
33.5g
17.8
a
Amaral et al. (2008).
LAC soils.
c HAC soils.
d General value.
e Areas with more than 20 years without burning.
d Areas with 3 years without burning.
e Areas with 21 years without burning.
b
Sugarcane ethanol
105
Chapter 4
4.3. Estimated emissions from LUC
For the changes from 2002 to 2006 (areas closer to the existing mills) soil types were
frequently HAC, and some of the cane was burned; for the expansion now and in next
decade, soils will be closer to LAC (and for 2020, 100% green cane harvesting is assumed).
The trends for land use change until 2020 are discussed in the next sections.
It is assumed that at least 70% of the pasture land used for cane is not planted pasture,
with varying degrees of degradation. Using the values in Tables 7 and 8, and the areas
for each type of vegetation replaced with sugarcane, the total carbon stock change was
evaluated and divided by a 20 year period. For the above ground carbon stock, only the
values corresponding to perennial vegetation were considered. Results are in Table 9.
Note that in all Scenarios there is a net reduction in emissions (close to 100 kg CO2 eq/m3
ethanol); this was expected, since the expansion areas for sugarcane include a very small
fraction of native lands with high carbon stocks, and some degraded land. The specific
situation for land availability, the environmental restrictions and local economic conditions
(relative crop values and implementation costs), discussed in the section Ethanol in the
Table 9. Emissions associated with LUC to unburned cane.
Reference crop
Degraded pasturelands
Natural pasturelands
Cultivated pasturelands
Soybean cropland
Maize cropland
Cotton cropland
Cerrado
Campo Limpo
Cerradão
LUC emissionsb
Carbon stock
changea
(t C/ha)
10
-5
-1
-2
11
13
-21
-29
-36
Emissions (kg CO2 eq./m3)
2006
2020 electricity
2020 ethanol
-302
157
29
61
-317
-384
601
859
1,040
-118
-259
134
25
52
-272
-329
515
737
891
-109
-185
96
18
37
-195
-236
369
527
638
-78
a
Based on measured values for below and above ground (only for perennials) carbon stocks.
Considering the following LUC distribution – 2006: 50% pasturelands (70% degraded
pasturelands; 30% natural pasturelands), 50% croplands (65% soybean croplands; 35% other
croplands); 2020: 60% pasturelands (70% degraded pasturelands; 30% natural pasturelands); 40%
croplands (65% soybean croplands; 35% other croplands). Cerrados were always less than 1%.
b
106
Sugarcane ethanol
Mitigation of GHG emissions using sugarcane bioethanol
specific Brazilian context, indicate that LUC motivated GHG emissions will not impact
ethanol production growth in Brazil in the time frame considered (2020).
It must be noted that the above ground carbon in the sugarcane plant is relatively high, and
even with its annual harvesting the change from any of the other crop, or even a campo
limpo, to sugarcane will produce an additional carbon capture (corresponding to differences
in the ‘average’ above ground carbon in the plants). This was not included here, since it has
not been considered in the IPCC methodology.
4.4. Indirect land use change effects on GHG emissions of biofuels worldwide
For most land use changes anywhere some impacts (including in GHG emissions) may
happen; and in our increasingly globalized economy indirect LUC impacts may occur.
However some of the hypotheses and tools leading to the initial quantification of the
impacts of biofuels production (Gnansounou et al., 2008), as presented today, are clearly
not suitable:
• A key issue for the models is the correct description of the drivers to LUC, everywhere;
but many agricultural products are interchangeable, and (increasingly) traded globally;
and the drivers of LUC vary in time and regionally. ‘Equilibrium’ conditions are not
reached. Drivers are established by local culture, economics, environmental conditions,
land policies and development programs. The development of a range of methodologies
and the acquisition/selection of suitable data are needed to reach acceptable, quantified
conclusions on ILUC effects. The growing consensus over this problem is summarized in
the recent letter from 28 scientists to the CARB (M.D. Nichols, personal communication):
‘…a severe lack of hard empirical data’… (the need to) ‘further study highly controversial
and speculative indirect land use changes… (for the) necessary time over the next five
years… before incorporating any of these indirect impacts in (the LCFS) standard’.
Simplifying methodologies (looking to ‘regions’ in the world, therefore losing the global
implications; or relying on indexes for too large areas, to by-pass the lack of data; or
distributing the total ‘estimated’ ILUC emissions equally among all biofuels) would lead
to still less accurate results.
• The land used for agriculture today is ~1300 M ha, excluding pasture lands; biofuels use
less than 1.5% of that; and possibly less than 4% in 2030 (IEA, 2006). Today’s distribution
of production among regions/countries has never considered GHG emissions; it was
determined by the local/time dependent drivers (including subsidies and food security
considerations). The better knowledge of those drivers and their effects, and its use to
re-direct land use as possible over all the agricultural and pasture lands worldwide, would
be much more effective than just to work on the ‘marginal’ biofuels growth areas. We
should not simply take as ‘unchangeable’ the huge context of today’s agriculture.
• Increases in agricultural productivity, energy end-use efficiencies and the use of other
energy renewable resources in the next decades may be expected, changing energy
Sugarcane ethanol
107
Chapter 4
demand and required areas for energy production, and they can entirely change the
‘future’ ILUC impacts of biofuels.
4.5. ILUC effects from ethanol in the specific Brazilian context
In general, exceptions (biofuel sources with no LUC indirect GHG emissions) have been
considered: waste or residues; use of marginal or degraded land; unused or fallow arable
land; or improving yields in currently used land. Looking at the scenarios for ethanol
production in Brazil, and the land use in Brazil today (in the context of the available land)
we note that:
• Most scenarios (based on Internal Demand plus some hypotheses for Exports) indicate
a total of ~ 60 M m3 ethanol in 2020 (CEPEA, 2007; Carvalho, 2007; EPE, 2007),
corresponding to 36 M m3 more than in 2008. For the 2020 conditions, the additional
area needed will be only 4.9 M ha (Scenario Electricity) or 3.5 M ha (Scenario Ethanol).
Since the Scenario Ethanol would not be implemented (even if technically successful,
and competitive) in time, we may expect ~5.1 M ha of new cane area, until 2020.
• Agricultural production (crops) uses a small fraction of the total area, and only 18.5 %
of the arable land (Table 10). Pasture land (200 M ha) is nearly 60% of the arable land.
Sugarcane for ethanol uses only 1% of the arable land, and the Land Available (not
including the conversion of pasture lands) is twenty times larger. The new area needed
for sugarcane until 2020 (5.1 M ha) is only 8% of the total crop area today, or 2.5% of
the pasture area today.
• The conversion of low quality pasture land to higher efficiency productive pasture is
liberating areas for other crops. The average heads/ha in Brazil was 0.86 (1996); and
0.99 (2006), with nearly 50% planted pasture (IBGE, 2006). In the State of São Paulo the
average was 1.2-1.4 in the last years. The conversion of low grade pasture could release
~30 M ha for other uses.
• Sugarcane expansion is smaller than the expansion of pasture and crops; and in the
places where sugarcane expands the eventual competition products (crops and cattle)
also expand. The expansion for other agricultural crops and pasture is taking place
independently of sugarcane expansion. In the period from 2002 to 2008 the sugarcane
expansion displaced Pasture and Crops (CONAB, 2008; Nassar, 2008) as follows: crop
area displaced, 0.5% (but crop area increased 10%, and cereal + oilseeds production
increased 40%); pasture area displaced, 0.7%; total pasture area decreased 1.7% (but
beef production grew 15%).
Within its soil and climate limitations, the strict application of the environmental legislation
for the new units, and the relatively small areas needed, the expansion of sugarcane until
2020 is not expected to contribute to ILUC GHG emissions.
108
Sugarcane ethanol
Mitigation of GHG emissions using sugarcane bioethanol
Table 10. Land use in Brazil: selected uses (2006) (UNICA, 2008; Scolari, 2006; FAO, 2005; IBGE,
2005).
Land use
Area, M ha
% of arable land
% cultivated land
Total land
Forests
Arable land
Pasture land
Cultivated land (all crops)
Soybean
Maize
Sugarcane (total)
Sugarcane for ethanol
Available land
850
410
340 (40%)
200
63
22
13
7
3.5
77
100.0
58.8
18.5
6.5
3.8
2.1
1.0
22.6
100.0
34.9
20.6
11.1
5.6
122.2
5. Conclusions
The analyses of the GHG emissions (and mitigation) with ethanol from sugarcane in Brazil
in the last years (2002-2008) and the expected changes in the expansion from 2008 to 2020
show that:
• The large energy ratios (output renewable/input fossil) may still grow from the 9.4 value
(2006) to 12.1 (2020) in two Scenarios: the better use of cane biomass to generate surplus
electricity (2020 Electricity Scenario: already under implementation) or to produce more
ethanol (2020 Ethanol Scenario: depending on technology development). The Ethanol
Scenario, if fully implemented, would reduce the area needed by 29%.
• The corresponding GHG mitigation (with respect to gasoline), for ethanol use in Brazil,
would increase from the 79% (2006) to 86% (2020) if only the ethanol is considered
(with emissions allocation to co-products), or from 86% (2006) to 95% or 120% (2020:
Ethanol or Electricity Scenarios) if all co-products credits and emissions are considered
for ethanol (substitution criterion).
• LUC due to ethanol expansion started in 2002 (ethanol production was constant at the 12
M m3 level, since 1984). In the expansion, land availability, the environmental restrictions,
the relatively small area used for expansion and the local economic conditions (relative
crop values and implementation costs) led to very small use of native vegetation lands
(<1%), and large use of low productivity pasture lands and some crop areas: soy and
maize. LUC derived GHG emissions were actually negative in the period 2002-2008. The
growth scenarios for 2020 (~reaching 60 M m3 ethanol) indicate the need for relatively
small areas (~5 M ha) as compared to the availability (non used arable lands, or even
degraded pasture lands); the trend is the use of more pasture lands and less crop areas, in
the expansion. Again, very little impact (if any) on LUC GHG emissions are expected.
Sugarcane ethanol
109
Chapter 4
• Suitable evaluations (even estimates) of ILUC impact in emissions are far from possible
today, due to the lack of adequate methodologies and corresponding (global) data.
However local conditions in Brazil indicate a good possibility of significant increases
in ethanol production without increasing ILUC GHG emissions:
– The area needed for expansion (~5 M ha, until 2020) is very small when compared
with the areas liberated with increased cattle raising efficiency (30 M ha) and other
non used arable lands.
– Sugarcane expansion has been independent of (and much smaller than) the growth
of other agricultural crops, in the same areas. In all sugarcane expansion areas the
eventual competition products (crops and beef production) also expanded.
References
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Lukas, 2002. Lignocellulosic biomass to ethanol process design and economics utilizing co-current
dilute acid prehydrolysis and enzymatic hydrolysis for maize stover. Technical report TP-510-32438,
NREL, Golden, CO, USA.
Amaral, W.A.N., 2008. Environmental sustainability of sugarcane ethanol in Brazil. In: P. Zuurbier and J. van
de Vooren (eds.) Sugarcane ethanol, Wageningen Academic Publishers, Wageningen, the Netherlands,
pp. 113-138.
Carvalho, E.P., 2007. Etanol como Alternativa Energética. UNICA: presentation to the Casa Civil, Presidência
da República, Brasília, Brazil.
CEPEA, 2007. Cenários (oferta e demanda) para o setor de cana de açúcar. CEPEA (Internal Report), Esalq,
Piracicaba, Brazil.
CONAB, 2008. Acompanhamento da safra Brasileira: Cana de Açúcar. Companhia Nacional de
Abastecimento, MAPA, Brasilia, Brazil.
CTC, 2006a. Controle mútuo agrícola anual - safra 2005/2006. Centro de Tecnologia Canavieira, Piracicaba,
Brazil, 126 p. + anexos.
CTC, 2006b. Technical information provided by scientists and engineers to I Macedo and J Seabra. Piracicaba:
Sugarcane Technology Centre, Brazil.
EPE, 2007. Plano Nacional de Energia 2030. Empresa de Planejamento Energético, MME, Brazil.
FAO, 2005. Food and Agriculture Organization, U.N. Statistical Databases, Agriculture. http://www.fao.
org/faostat.
Gnansounou, E., L. Panichelli, A. Dauriat and J.D. Villegas, 2008. Accounting for indirect land-use changes
in GHG balances of biofuels: review of current approaches. École Polytechnique Fédérale de Lausanne,
Working Paper 437.101.
Hassuani, S.J., M.R.L.V. Leal and I.C. Macedo, 2005. Biomass power generation: sugarcane bagasse and trash.
Série Caminhos para Sustentabilidade. Piracicaba: PNUD-CTC, Brazil.
IBGE, 2005. Indicadores Agropecuários 2005. Instituto Brasileiro de Geografia e Estatistica. Available at:
http://www.ibge.org.br.
IBGE, 2006. Produção Agrícola Municipal, v. 33. Instituto Brasileiro de Geografia e Estatistica. Available
at: http://www.ibge.org.br.
110
Sugarcane ethanol
Mitigation of GHG emissions using sugarcane bioethanol
IEA, 2006. Alternative Energy Scenarios. World Energy Outlook 2006. International Energy Agency.
IPCC, 2006. IPCC guidelines for national greenhouse gas inventories, Prepared by the National Greenhouse
Gas Inventories Programme. In: H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara and K. Tanabe (eds.)
Japan: IGES.
Macedo, I.C. (ed.) 2005. Sugarcane’s Energy – Twelve studies on Brazilian sugarcane agribusiness and its
sustainability. São Paulo: Berlendis & Vertecchia: UNICA, Brazil.
Macedo, I.C., 2008. GHG mitigation and cost analyses for expanded production and use of fuel ethanol in
Brazil. Final Report, prepared for Center for Clean Air Policy – CCAP. Washington, USA.
Macedo, I.C., J.E.A. Seabra and J.E.A.R. Silva, 2008. Green house gases emissions in the production and
use of ethanol from sugarcane in Brazil: The 2005/2006 averages and a prediction for 2020. Biomass
and Bioenergy, 32: 582-595.
MAPA, 2007. Projeções do Agronegócio – Mundo e Brasil, 2006/07 a 2017/18. Ministério da Agricultura,
Pecuária e Abastecimento (MAPA), Assessoria de Gestão Estratégica, Brazil.
Nassar, 2008. Sustainability considerations for ethanol. Food, Fuel and Forests: A Seminar in Climate Change,
Agriculture and Trade. Bogor, Indonesia.
Nassar, A.M., B.F.T. Rudorff, L.B. Antoniazzi, D. Alves de Aguiar, M.R.P. Bacchi and M. Adami, 2008.
Prospects of the sugarcane expansion in Brazil: impacts on direct and indirect land use changes. In: P.
Zuurbier and J. van de Vooren (eds.) Sugarcane ethanol, Wageningen Academic Publishers, Wageningen,
the Netherlands, pp. 63-93.
Seabra, J.E.A., 2008. Avaliação técnico-econômica de opções para o aproveitamento integral da biomassa
de cana no Brasil. Campinas, Faculdade de Engenharia Mecânica, Universidade Estadual de Campinas,
PhD Thesis, 273 p.
Scolari, D., 2006. Produção Agricola Mundial: o potencial do Brasil. Embrapa (Empresa Brasileira de
Pesquisa Agopecuária), Brasilia, Brazil.
UNICA, 2008. Frequently asked questions about the Brazilian sugarcane industry. UNICA, S Paulo,
Brazil.
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111
Chapter 5
Environmental sustainability of sugarcane ethanol in Brazil
Weber Antônio Neves do Amaral, João Paulo Marinho, Rudy Tarasantchi, Augusto Beber and
Eduardo Giuliani
1. Introduction
Brazil’s economy is performing well during the last few year reaching international
investment grade levels, while at the same time providing quantifiable reductions of
greenhouse gases, specially through its renewable energy matrix and the large scale use
of ethanol in transportation. It is well-known that the quality of life in the world increases
with economic growth, which increases demand for energy (Figure 1). If one considers the
externalities created by burning fossil fuels, then economic growth becomes a major threat
to the global well being; reinforcing the need to explore alternatives to improve the efficiency
of energy use and diversification of energy sources, and especially from renewable ones.
Brazil’s commitment to sustainability in the agribusiness for example can be assessed by
concrete examples such as the development and implemental of stringent legal environmental
frameworks, agricultural zoning, massive investments in research and development and
rural social policies, being the ethanol business a good example from which best practices
could be disseminated.
The benefits of the production and use of ethanol in Brazil can also serve as a platform and
model for further acceptance and deployment of renewable sources of biomass as feedstock
for sustainable production of biofuels in the World. However there are several drivers that
currently affect the supply and demand for biofuels and their sustainable production: land
use changes, environmental concerns, competition with other sources of energy, food
security, agricultural subsidies, innovation and technological development, public policies,
oil prices, energy security policies, etc.
The Proalcool program (the Brazilian program for the production of ethanol) started in 1975,
33 years ago, is a good example of a pro-active public policy supporting the development of
biofuels with a focus on sugarcane ethanol. It made Brazil the second largest producer of
ethanol (expected production of 23 billion liters in 2008), with the lowest production costs
in the World (US$ 0.22/l – Table 1).
Sugarcane ethanol
113
+
Climate
change
+
-
Gasoline/diesel/
querosene
+
GHGs
Chapter 5
114
Global
awareness
Oil reserves
-
Hydraulic
+
+
-
Environmental
taxes and
policies
-
Energy
demand
Energy
supply
+
+
+
Consumption
-
+
Economic
growth
+
+ Reinforcing loop
-
Balanced loop
+
Quality of
life and
livelihoods
+
Nuclear
+
Wind
-
Land use
patterns
+
Hydrogen
-
+
+
+
+
+
+
Ethanol &
biodiesel
Jobs
+
Quality
of jobs
Roles and functions of
government, private
sector and ONGs
Diversity of jobs
Figure 1. Social-economical-environmental dynamic structure. Source: Venture Partners do Brasil.
-
+
Native
forests
+
Food
+
Food
security
+
Biodiversity
Sugarcane ethanol
Environmental sustainability of sugarcane ethanol in Brazil
Sugarcane
Sugar
beets
Molasses 3
Raw sugar 3
0.11
0.17
0.28
0.14
0.14
0.28
0.40
0.25
0.65
0.43
0.21
0.63
0.25
0.10
0.34
0.84
0.10
0.94
EU
Sugarbeets 4
Maize dry
milling
Feedstock2
Processing
Total
Brazil
Sugarcane 4
United States
Refined
sugar 3
Costs item
Maize wet
milling
Table 1. Production costs of different biofuels (US$/liter)1.
0.97
0.10
1.07
0.08
0.14
0.22
0.26
0.52
0.78
Source: USDA (2007).
1 Excludes capital costs.
2 Feedstock costs for US maize wet and dry milling are net feedstock costs; feedstock costs for US
sugarcane and sugar beets are gross feedstock costs.
3 Excludes transportation costs.
4 Average of published estimates.
The long track record of Brazilian sugarcane ethanol proved its economic sustainability
over time, while improving its social and environmental indicators, involving technology
transfer from Europe, US and other regions and developing several innovations at national
level. This program no longer exists, however it has contributed significantly to improve the
productivity of sugarcane and ethanol extraction rates (Figure 2).
Due to the increasing internal demands and the possibility of future exports, it is expected
that the Brazilian production might increase to 47 billion liters of ethanol by 2015, with an
estimated annual growth rate of 10-13% (Table 2).
Several steps will be necessary to achieve these production targets, including sustainable
planning of the sugarcane expansion into new areas, improving the logistics, the development
of global markets and continuously developing new technological innovations, while at
the same time improving the environmental performance of existing brown fields (areas
with already established sugarcane fields and industry either/or sugar mills/distilleries)
and especially from new green fields (new areas for expansion of sugarcane fields and
new industrial plants), which are being implemented using cutting edge technologies
in the agriculture and in the industry. With more than 360 mills in operation, there is a
gap between the best practices available and the average performance of Brazilian mills,
however due to recent developments in the ethanol business, with the consolidation of
economic groups, capacity building programs, companies going public, new investments
Sugarcane ethanol
115
80
70
70
60
60
productivity gain = 2.8% CA GR
50
50
03/04
01/02
99/00
97/98
95/96
93/94
91/92
89/90
87/88
85/86
83/84
30
81/82
30
79/80
40
77/78
40
Ton of cane/ha
80
75/76
Liter of ethanol/ton of cane
Chapter 5
liter of ethanol/ton of cane (LHS)
ton of cane/ha (LHS)
Figure 2. Evolution of productivity of Brazilian ethanol. Source: Itaú Corretora (2007).
Table 2. Future projections of ethanol production in Brazil.
Sugarcane Production (M-ton)
Area (M-ha)
Sugar (M-ton)
Internal
Export
Ethanol (B-liters)
Internal
Export
Bioelectricity (GW average)
2007/08
2015/16
2020/21
493
7.8
30.8
12.2
18.6
22.5
18.9
3.6
1.8
829
11.4
41.3
11.4
29.9
46.9
34.6
12.3
11.5
1,038
13.9
45
12.1
32.9
65.3
49.6
15.7
14.4
Source: Unica (2008).
in research and development the speed of this dissemination is increasing significantly
from previous decades.
This chapter addresses the following:
• the Brazilian environmental legal frameworks;
• key environmental indicators: carbon, water, soil, agrochemicals, biodiversity, air and
by-products;
• different biofuels certifications regimes and compliance;
• the future steps and the role of innovation.
116
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Environmental sustainability of sugarcane ethanol in Brazil
2. The Brazilian environmental legal framework regulating ethanol production
The Brazilian environmental legal framework is complex and one of the most stringent
and advanced in the World. As an agribusiness activity, the ethanol/sugar industry has
several environmental restrictions that require appropriate legislation or general policies
for its operation. Some of them are pioneers in the area which define principles in order to
maintain the welfare of living beings and to provide resources for future generations: the
first version of the Brazilian forest code dated from 1931, already addressed the need to
combine forest cover with quality of life and livelihoods.
Brazil has wide range of federal and state laws regarding environmental protection (Table 3),
aiming at combining the social economic development with environmental preservation,
which the ethanol business need to comply with for its proper operation.
They also involve frameworks such as the Environmental Impact Assessment and
Environmental Licensing, among others (Figure 3), especially for the implementation of
new project: i.e. new green field projects in Brazil are being stringently assessed (Nassar et
al., this book) using these frameworks.
Volunteer adherence to Environmental Protocols represents also a major breakthrough for
the sugar business. For example The ‘Protocolo Agroambiental do Setor Sucroalcooleiro’
(Agriculture and Environmental Protocol for the ethanol/sugar industry) signed by UNICA
and the Government of the State of São Paulo in June 2007 deals with issues such as:
conservation of soil and water resources, protection of forests, recovery of riparian corridors
and watersheds, reduction of greenhouse emissions and improve the use of agrochemicals
and fertilizers. But its main focus is anticipating the legal deadlines for ending sugarcane
burning by 2014 from previous deadline of 2021. In February 2008, the State Secretariat
of Environment reported that 141 industries of sugar and alcohol had already signed the
Protocol, receiving the ‘Certificado de Conformidade Agroambiental’ (Agricultural and
Environmental Certificate of Compliance). These adherences correspond for more than
90% of the total sugarcane production in São Paulo. A similar initiative is happening in the
State of Minas Gerais with the ‘Protocolo de Intenções de Eliminação da Queima da Cana
no Setor Sucroalcooleiro de Minas Gerais’ from August 2008.
Sugarcane ethanol
117
Law
Objective
P.S.
No. 4,771, September 15th, 1965
No. 997, May 31st, 1976
Portaria do Ministério do Interior No. 323,
November 29th, 1981
No. 6,938, August 31st, 1981
Forest Code
Environment Polution Control
It prohibits release of vinhoto in the water
Permanent preservation areas
Environmental Permission
Environment National Policy
Mechanisms and instruments (environmental
zoning, Environmental Impact Assessment)
For ‘industrial complex and units and agroindustrial’
General Guidelines for the Evaluation of
Environmental Impact
No. 6,171, July 04th, 1988
The use, conservation and preservation of
agricultural soil
No. 11,241, September 19th, 2002
Gradual elimination of burning the straw of
Elimination of the use of fire as a unstraw method
sugarcane
and facilitator of cutting the sugarcane
Use of water charge
No. 12183/05
Legal Reserve of landed property in the State of
Obligation of reserving an area equivalent to 20%
No. 50,889, June 16th, 2006
São Paulo
of each rural property
SMA deliberation 42, October 14th, 2006 Environmental prior license to distilleries of alcohol, It defines criteria and procedures
sugar plants and units of production of spirits
Deliberation No. 382, December 26th,
It sets the maximum emission of air pollutants to Annex III: Emission limits for air pollutants from
2006
sources.
processes of heat generation from the external
combustion of sugarcane’s mulch
Government of the State of São Paulo and UNICA
Agricultural and Environmental Protocol of Prominence to anticipate the legal period to the
sugar/ethanol industry
end of the harvest of sugarcane with the previous
use of fire in the areas cultivated by plants
Removal of burnt by 2014
SIAMIG/SINDAÇÚCAR-MG and Government of the
Elimination intentions of burning
State of Minas Gerais
sugarcane in the ethanol/sugar sector of
Minas Gerais protocol
CONAMA deliberation No.001/7986
Sugarcane ethanol
Source: Brazilian and State laws.
Chapter 5
118
Table 3. Summary of main environmental laws.
Sugarcane ethanol
Sugar and ethanol agribusiness undertaking
Activity 2:
planting, crop
treatments
Activity 1:
preliminary
Activity 3:
harvesting
Activity 4:
industrial
process
Activity 5:
support
Environment
Biological:
flora,
fauna
Anthropic:
jobs, economy, sociocultural
aspects
Changes
Impacts
Mitigating measures
Preventive
Corrective
Valorization
Compensatory
Figure 3. Environmental analysis structure for EIA/RIMA: sugarcane agribusiness. Source: Elia Neto (2008).
Monitoring
119
Environmental sustainability of sugarcane ethanol in Brazil
Physical:
atmosphere,
land, water
Chapter 5
3. Environmental indicators
The environmental sustainability is evaluated through indicators such as carbon, water, soil,
agrochemicals, biodiversity and by-products.
3.1. Greenhouse gases (GHG) balance
One of the goals of using biofuels is to contribute with net reduction of GHG emissions
and thus not affecting carbon stock negatively in different sub-systems of production,
below and above ground biomass (roots, branches and leaves) and in the soil (carbon fixed
in clay, silt, sand and organic matter). Figure 4 shows that ethanol from sugarcane reduces
86% of the GHG emissions when compared to gasoline. It has also a leading performance
when compared to other biofuels from other feedstocks. In addition the energy efficiency
difference is even greater: 9.3 against 1.4 to 2.0 of other biomasses (Figure 5).
Sugarbeet, EU
Sugarcane, Brazil
Wheat, EU
Corn, US
Rapeseed, EU
Second generation
0
20
40
60
80
100
Figure 4. GHG emissions avoided with ethanol or biodiesel replacing gasoline. Source: International
Energy Agency (IEA/OECD, 2006).
9.3
2.0
2.0
1.4
sugercane
wheat
sugarbeets
corn
Figure 5. Energy output per unit of fossil fuel consumption in the production process. Source: World
Watch Institute (2006) and Macedo et al. (2008).
120
Sugarcane ethanol
Environmental sustainability of sugarcane ethanol in Brazil
3.1.1. Carbon stocks
One of the main effects caused by land use changes is the variation in the amount of carbon
stocks under different subsystem, namely in the soil and in the above ground biomass in the
area. When analyzing the environmental effects caused by different land use regimes, the
balance of carbon should be taken into account. It is necessary to know how much carbon
would be fixed or released into the air under different land use regimes compared with the
previous baseline of use.
One limiting factor to perform an in depth analysis of these balances is the lack of long
term monitoring plots assessing precisely these dynamics through time. However the stock
and flows of carbon for major crops like soybean, maize, cotton and sugarcane have been
extensively studied, but in general using different methodologies. There are also other
factors that affect the results: crop productivity and management, soil physical and chemical
properties, climate and land use history for example.
In large countries such as Brazil, there are many different soils and climatic conditions. The
different characteristics of each region will influence the potential for carbon storage. A
clay soil, for example, has the ability to store more organic matter and consequently, more
carbon than a sandy soil, because of their physical properties. In hot and humid climates,
the rate of deposition and decomposition of organic matter is higher than in dry and cold
climates, facilitating the deposition of carbon in the soil.
The spatial distribution of crops in Brazil is edaphic-climatic (soil characteristics and climate
interactions) dependent for their profitability. These interactions influence carbon content
in the soil and in the biomass, which are also affected by soil management practices, such
as minimum tillage, which can significantly for example increase soil carbon content. The
land use history is also relevant when assessing and explaining current levels of carbon,
because when land use changes do occur; soil carbon stocks take several years to achieve a
new carbon balance. If carbon is measured in a newly cultivated system, the carbon present
in the soil is actually reflecting the carbon content from the formerly existing vegetation/
history and not a consequence of current land use. Table 4 presents the carbon stocks in
soil for some selected Brazilian crops and in the native vegetation.
For carbon stored in the biomass, crop productivity is of great importance as indicator
carbon stored in the above ground biomass per unit of area. The larger the quantity of
biomass above ground, the greater the stocks of carbon in biomass (Table 5), which is a
measure much easier to obtain and with a larger dataset from multiple management and
production systems in Brazil.
According to the National Supply Company (CONAB - Ministry of Agriculture and
Livestock, 2008) sugarcane area expanded 653,722 ha in the 2007/2008 period, occupying
Sugarcane ethanol
121
Chapter 5
Table 4. Carbon stock in soil for selected crops in native vegetation.
Biomass
Carbon stocks in soil (Mg/ha)
Campo Limpo – grassland savannah (a)
Sub-tropical forest (b)
Tropical forest (c)
Natural pasture (d)
Soybean (e)
Cerradão – woody savannah (a)
Managed pasture (f)
Cerrado – typical savannah (a)
Sugarcane without burn (g)
Degraded pasture (h)
Maize (h)
Cotton (i)
Sugarcane burned (g)
72
72
71
56
53
53
52
46
44
41
40
38
35
Sources: (a) Lardy et al. (2001); (b) Cerri et al. (1986); (c) Trumbore et al. (1993); (d) Jantalia et al.
(2005); (e) Campos (2006); (f) Rangel and Silva et al. (2007); (g) Estimated from Galdos (2007); (h)
d’Andréa et al. (2004); (i) Neves et al. (2005).
Table 5. Carbon stocks in the above biomass of selected crops and native vegetation.
Biomass
Carbon stocks in biomass (Mg/ha)
Tropical rain forest (a)
Cerradão – woody savannah (b)
Cerrado – typical savannah (b)
Sugarcane without burn (c)
Sugarcane burned (c)
Campo Limpo – grasland savannah (b)
Managed pasture (d)
Maize (e)
Cotton (f)
Soybean (g)
Degraded pasture (d)
200.0
33.5
25.5
17.5
17.0
8.4
6.5
3.9
2.2
1.8
1.3
Sources: (a) INPE; (b) Ottmar et al. (2001); (c) VPB Estimative; (d) Estimated from Szakács et al.
(2003); (e) Estimated from Titon et al. (2003); (f) Adapted from Fornasieri and Domingos et al.
(1978); (g) Adapted from Campos (2006).
122
Sugarcane ethanol
Environmental sustainability of sugarcane ethanol in Brazil
areas previously covered with pasture (67%), soybean (16.9%), maize (4.9%) and 2.4% of
these new areas expanded into native vegetation of cerrado (savannah-like vegetation). From
these numbers, it is possible to estimate the overall carbon balance resulting from land use
changes due to sugarcane expansion for this period (Table 6). Figure 6 shows the positive
carbon balance resulting from 91.2% in the area of expansion of sugarcane, corresponding
to the areas of pasture, maize, soybeans and native vegetation as replaced by not burned
sugarcane as 100% of these new green field are using mechanized harvesting practices.
It was considered for this assessment that the totality of pastures replaced was of planted
pastures and the native vegetation replaced as areas of Grassland Savannah (Campo Limpo).
However it is important to mention that there are other statistics of sugarcane expansion
(See Nassar et al. in this volume for details), which could affect this carbon balance.
Table 6. Carbon balance under different land uses replaced by sugarcane.
Biomass
Total carbon stocks
(Mg/ha)
Cotton (d)
40.1
Degraded pasture (b)
42.0
Maize (h)
44.1
Sugarcane burned (g)
52.1
Soybean (e)
54.9
Managed pasture (f)
58.5
Cerrado – typical savannah (a)
71.5
Campo Limpo – grassland savannah (a)
80.4
Cerrado – woody savannah (a)
86.5
Tropical forest (c)
271.0
Total carbon stocks in sugarcane net burned = 61.8 Mg/ha
Carbon balance
due to sugarcane
replacement (Mg/ha)
21.8
19.8
17.7
9.7
6.9
3.3
-9.7
-18.6
-24.7
-209.2
Sources: (a) Lardy et al. (2001)/Ottmar et al. (2001); (b) d`Andréa et al. (2004)/Estimated from
Szakács et al. (2003); (c) Trumbore et al. (1993)/INPE; (d) Neves et al. (2005)/Adapted from
Fornasieri and Domingos et al. (1978); (e) Campos (2006)/Adapted from Campos (2006); (f) Rangel
and Silva et al. (2007)/Estimated from Szakács et al. (2003); (g) Estimated from Galdos (2007)/
VPB Estimative; (h) d`Andréa et al. (2004)/Estimated from Titon et al. (2003).
Sugarcane ethanol
123
Chapter 5
Total carbon in the
biomass (ton C/ha)
Replaced areas
(ha)
Carbon balance *
(ton C)
Pasture
(~59)
423,120
+1,400,527
Soya
(~55)
110,447
+763,169
Corn
(~44)
32,211
+571,423
Native vegetation
(~80)
15,546
-384,453
Final balance
+ 2,350,687
* Carbon balance = total C in biomass - total C in sugar cane × replaced area (ha)
Figure 6. Carbon balance of sugarcane expansion in São Paulo State, 2007. Source: VPB analysis.
3.2. Water
Despite having the greatest water availability in the world, with 14 percent of the surface
waters and the equivalent of annual flow in underground aquifers, the use of crop irrigation
in Brazil is minimum (~3.3 Mha, compared to 227 Mha in the world). Practically all of the
sugarcane produced in São Paulo State is grown without irrigation (Donzelli, 2005).
The levels of water withdraw and release for industrial use have substantially decreased
over the past few years, from around 5 m3/ton sugarcane collected in 1990 and 1997 to
1.83 m3/ton sugarcane in 2004 (sampling in São Paulo). If we take 1.83 m3 of water/ton of
sugarcane, and exclude the mills having the highest specific consumption, the mean rate
for the mills that account for 92% of the total milling is 1.23 m3 of water/ton of sugarcane.
In addition the recycling rate has been increasing since 1990 (Figure 7). Mills with better
water management practice replace only 500 liters in the industrial system, with a recycling
rate of 96,67%.
Recent developments might lead to convert sugarcane mills from water consumers to water
exporters industry. Dedini the largest Brazilian manufacturer of sugar mills and equipment
suppliers has developed a new technology that allows the process of transforming sugarcane
in ethanol to be much more efficient, and in the end of this process, industrial mills will
be able to sell about 300 liters of water per ton of sugarcane (Figure 8). This would be
124
Sugarcane ethanol
Environmental sustainability of sugarcane ethanol in Brazil
87.8%
66.2%
62.7%
1990
1997
2005
Figure 7. Evolution of water recycling. Source: Elia Neto (2008).
5.7
5.0
2.5
0.7
0.7
1990
1997
0.3
0.4
Best practice
Export
Figure 8. Evolution of water consumption in industrial ethanol production from sugarcane (m3/ton of
sugarcane). Source: Dedini (2008).
possible because water represents approximately 70% of sugarcane’s composition. This new
technology will be available next year (2009). Current estimates from maize ethanol mills
on water consumption are of 4 liters of water per liter of ethanol produced (Commission
on Water Implications of Biofuels Productions in United States, 2008).
Sugarcane ethanol
125
Chapter 5
3.3. Soil and fertilizers8
The sustainability of the culture improves with the protection against soil erosion,
compacting and moisture losses and correct fertilization. In Brazil, there are soils that have
been producing sugarcane for more than 200 years, with ever-increasing yields and soil
carbon content. Soil erosion in sugarcane fields is lower than in soybean and maize (Macedo
et al., 2005) and other crops (Table 7). It is expected also that the growing harvesting of cane
without burning will further improve this condition, with the use of the remaining trash
in the soil. Recent sugarcane expansion in Brazil has happened mostly in low fertility soils
(pasture lands), and thus improving their organic matter and nutrient levels from previous
land use patterns. Sugarcane uses lower inputs of fertilizers: ten, six and four times lower
than maize respectively for nitrogen, phosphorous and potassium (Table 8). An important
characteristic of the Brazilian sugarcane ethanol is the full recycling of industrial waste to
the field.
Vinasse, a by-product of the distillation process, rich in nutrients (mainly potassium) and
organic matters is a good example, which is being used extensively as a source of fertiirrigation (nutrients associated with water). For each liter of alcohol, 10 to 15 liters of vinasse
8 This
text was adapted from Donzeli (2005) and Souza (2005).
Table 7. Losses of soil and water for selected crops.
Annual crop
Castor
Beans
Manioc
Peanut
Rice
Cotton
Soybean
English potato
Sugarcane
Maize
Maize + beans
Sweet potato
Losses
Soil (t/ha-year)
Water (% rain)
41.5
38.1
33.9
26.7
25.1
24.8
20.1
18.4
12.4
12.0
10.1
6.6
12.0
11.2
11.4
9.2
11.2
9.7
6.9
6.6
4.2
5.2
4.6
4.2
Source: Bertoni et al. (1998).
126
Sugarcane ethanol
Environmental sustainability of sugarcane ethanol in Brazil
Table 8. Agrochemical inputs consumption (per ha) and per ethanol production (m3).
Sugarcane
Cons./ha
Ethanol production (m3)
Quantity of N (kg)
Quantity of P (kg)
Quantity of K (kg)
Liming materials (kg)
Herbicide (liters)
Drying hormone (liters)
Insecticides (liters)
Formicide (kg)
Nematicide (liters)a
Total
8.1
25.0
37.0
60.0
600.0
2.6
0.4
0.1
1.2
726.2
Maize
Cons./m3
3.1
4.6
7.4
74.5
0.3
0.0
0.0
0.1
90.2
Cons./ha
Cons./m3
4.2
140.0
100.0
110.0
500.0
13.0
2.2
0.5
865.7
33.7
24.1
26.5
120.5
3.1
0.5
0.1
208.5
Sources: Agrianual (2008); Fancelli and Dourado Neto (2006).
a Product used to control microscopic multicellular worms called nematodes.
are produced. Generally the vinasse has a high organic matter and potassium content,
and relatively poor nitrogen, calcium, phosphorus and magnesium contents (Ferreira and
Monteiro 1987). Advantages of using vinasse include increased pH and cation exchange
capacity, improved soil structure, increased water retention, and development of the soil’s
micro flora and micro fauna. Many studies have been conducted involving specific aspects
pertaining to leaching and underground water contamination possibilities at variable
vinasse doses over periods of up to 15 years. The results obtained from tests so far indicate
that there are no damaging impacts on the soil at doses lower than 300 m3/ha, while higher
doses may damage the sugarcane or, in specific cases (sandy or shallow soil), contaminate
underground water (Souza, 2005).
Investments in infrastructure have enabled the use water from the industrial process and
the ashes from boilers. Filter cake (a by product of the yeast fermentation process) recycling
processes were also developed, thereby increasing the supply of nutrients to the field.
Sugarcane ethanol
127
Chapter 5
3.4. Management of diseases, insects and weeds9
Strategies for disease control involve the development of disease resistant varieties within
large genetic improvement programs. This approach kept the major disease outbreak
managed, i.e. the SCMV (sugarcane mosaic virus, 1920), the sugarcane smut, Ustilago
scitaminea, and rust Puccinia melanocephala (1980’s), and the SCYLV (sugarcane yellow
leaf virus, 1990’s) by replacing susceptible varieties.
The soil pest monitoring method in reform areas enabled a 70% reduction of chemical
control (data provided by CTC), thereby reducing costs and risks to operators and the
environment.
Sugarcane, as semi-permanent culture of annual cycle and vegetative propagation, forms a
crop planted with a certain variety that is reformed only after 4 to 5 years of commercial use.
These characteristics determine that the only economically feasible disease control option
is to use varieties genetically resistant to the main crop diseases.
Insecticide consumption in sugarcane crops is lower than in citrus, maize, coffee and soybean
crops; the use of insecticides is also low, and of fungicides is virtually null (Agrianual,
2008). Among the main sugarcane pests, the sugarcane beetle, Migdolus fryanus (the most
important pest) and the cigarrinha, Mahanarva fimbriolata, are biologically controlled. The
sugarcane beetle is the subject of the country’s largest biological control program. Ants,
beetles and termites are chemically controlled. It has been possible to substantially reduce
the use of pesticides through selective application.
The control or management of weeds encompasses specific methods or combinations of
mechanical, cultural, chemical and biological methods, making up an extremely dynamic
process that is often reviewed. In Brazil, sugarcane uses more herbicides than coffee and maize
crops, less herbicides than citrus and the same amount as soybean (Agrianual, 2008).
On these issues mentioned above related to use of agrochemicals, soil management and
water uses, UNICA’s (Brazilian Sugarcane Growers Association) associated mills are
developing a set of goals, aiming at improving agricultural sustainability in the next few
years (Table 9).
9 This
128
text was adapted from Arrigoni and Almeida (2005) and Ricci Junior (2005).
Sugarcane ethanol
Environmental sustainability of sugarcane ethanol in Brazil
Table 9. Sugarcane agricultural sustainability.
Sugarcane
Less agrochemicals
Low soil loss
Minimal water use
Low use of pesticides.
Brazilian sugarcane fields have Brazilian sugarcane fields
No use of fungicides
relatively low levels of soil loss, require practically no irrigation
Biological control to mitigate
thanks to the semi-perennial
because rainfall is abundant
pests.
nature of the sugarcane that is and reliable, particularly in the
Advanced genetic enhancement only replanted every 6 years.
main South Central production
programs that help idntify the The trend will be for current
region.
most resistant varieties of
losses, to decrease
Ferti-irrigation: applying vinasse
sugarcane.
significantly in coming years
(a water-based residue from
Use of vinasse and filter cake as through the use of sugarcane
sugar and ethanol production).
organic fertilizers.
straw, some of which is left on Water use during industrial
the fields as organic matters
processing has decreased
after mechanical harvesting
significantly over the years:
from 5 m3/t to 1 m3/t.
Source: Unica (2008).
3.5. Conservation of biodiversity
Brazil is a biodiversity hotspot and contains more than 40% of all tropical rain forest of the
World. Brazilian biodiversity conservation priorities were set mainly between 1995 and
2000, with the contribution of hundreds of experts; protected areas were established for
the six major biomes in the National Conservation Unit System.
Steps for the implementation of the Convention on Biological Diversity includes the
preparation of the biodiversity inventory and monitoring of important biodiversity
resources, the creation of reserves, the creation of seed, germoplasm and zoological banks,
and the conduct of Environmental Impact Assessments covering activities that could affect
the biodiversity.
The percentage of forest cover represents a good indicator of conservation of biodiversity
in agricultural landscapes. In São Paulo State for example the remaining forest covered is
11%, of which 8% being part of the original Atlantic Forest. Table 10 demonstrates that
while the sugarcane area increased from 7 to 19% of the State territory, native forests also
increased from 5 to 11%, showing that it is possible to recover biodiversity in intense
agricultural systems.
Sugarcane ethanol
129
Chapter 5
Year
Sugarcane
New lands (Kha)
Land in use (Kha)
Total area (Kha)
Production (Kton)
Productivity (ton/ha)
Woody-Cerradao
(Kha)
Shrubby-Cerrado/
savana (Kha)
Native forests (Kha)
Sugarcane area
Native forests area
Table 10. Sugarcane and vegetation area in São Paulo State.
Vegetation
% SP State
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
345
317
326
350
311
325
322
276
301
372
371
421
449
428
422
342
281
338
440
457
495
463
553
822
935
1,421
1,526
1,626
1,704
1,753
1,771
1,757
1,836
1,864
1,940
1,989
2,180
2,260
2,388
2,451
2,544
2,475
2,491
2,569
2,661
2,818
2,951
3,121
3,437
3,897
1,765
1,842
1,952
2,054
2,064
2,097
2,078
2,112
2,165
2,311
2,360
2,601
2,709
2,816
2,872
2,887
2,756
2,829
3,009
3,118
3,313
3,414
3,673
4,258
4,832
107,987
116,666
121,335
122,986
132,322
134,108
130,795
139,400
144,581
150,878
156,623
168,362
175,073
187,040
194,801
199,764
193,374
189,391
201,683
212,707
227,981
241,659
254,810
284,917
327,684
76.0
76.5
74.6
72.2
75.5
75.7
74.5
75.9
77.6
77.8
78.7
77.2
77.5
78.3
79.5
78.5
78.1
76.0
78.5
79.9
80.9
81.9
81,7
82,9
84,1
196
167
221
205
211
192
198
175
198
204
238
201
189
217
215
217
218
221
223
224
225
211
217
228
233
489
427
438
378
348
316
325
290
301
284
259
238
220
232
244
241
244
257
262
263
264
262
254
271
277
1,139
1,453
1,545
1,795
1,870
1,624
1,487
1,097
1,601
2,109
2,120
2,453
2,434
2,462
2,478
2,482
2,468
2,629
2,622
2,725
2,720
2,732
2,648
2,695
2,716
7%
7%
8%
8%
8%
8%
8%
9%
9%
9%
10%
10%
11%
11%
12%
12%
11%
11%
12%
13%
13%
14%
15%
17%
19%
5%
6%
6%
7%
8%
7%
6%
4%
6%
8%
9%
10%
10%
10%
10%
10%
10%
11%
11%
11%
11%
11%
11%
11%
11%
Source: IEA/CATI-SAAESP (Annual statistics from 1983-2007).
130
Sugarcane ethanol
Environmental sustainability of sugarcane ethanol in Brazil
3.6. Air quality
Burning sugarcane for harvesting is one of the most criticized issue of sugarcane production
system, causing local air pollution and affecting air quality, despite of the benefits of using
100% ethanol running engines instead of gasoline (Figure 9), which decreases air pollution
from 14 to 49%.
In order to eliminate gradually sugarcane burning, several attempts are being made. The
São Paulo Green Protocol is being considered the most important one, setting an example
for other regions and states in Brazil. Signed between the São Paulo state government (State
Environment Secretariat) and the Sugarcane Growers Association (UNICA) in June 04,
2007, the Green Protocol aimed at:
• The anticipation of the legal deadline for the elimination of the practice of sugarcane
straw burning to 2014.
• The protection of river side woods and recovering of those near water streams (permanent
protected areas - APPs).
• The implementation of technical plans for conservation of soil and water resources.
• The adoption of measures to reduce air pollution.
• The use of machines instead of fire to harvest new sugarcane fields.
Voluntarily 141 of the total of 170 sugar mills from the state of São Paulo signed this
Protocol, and recently 13 thousand sugarcane independent suppliers, members of the
Organization of Sugarcane Farmers of the Center-South Region (Orplana), signed also this
protocol. Therefore the entire production chain of sugar and ethanol of São Paulo participates
104
100
100
100
86
85
80
53
51
CO
Gasoline 0%
HC
E 22%
NOx
Ethanol 100%
Figure 9. Air pollution by different blends of ethanol. Source: ANFAVEA (2006).
Sugarcane ethanol
131
Chapter 5
in the implementation of the Protocol. Maintaining the 2007 levels of mechanization,
when 550 new harvest machines have begun to operate, it will be possible to complete the
mechanization even prior to the deadline (2014) set by the Protocol.
4. Initiatives towards ethanol certification and compliance
The discussion on sustainable production of biofuels has fulfilled the scientific literature
lately (see for example Hill et al., 2006; Van Dam et al., 2006; Goldemberg et al., 2006; Smeets
et al., 2008; Macedo et al., 2008). At the same time several initiatives are being developed in
Europe and in the United States related to certification, traceability and definition of criteria
and indicators for sustainable production of biofuels, mainly due to different supporting
policies. For example in May 2003, the European Commission launched its Biofuels Directive
2003/30/EC, establishing legal basis for blending biofuels and fossil fuels. The EU member
countries are urged to replace 2% of fossil fuels with biofuels by 2005 and 5.75% by 2010.
From 2003 to 2005 the group of 25 countries members enhanced biofuel’s market share of
0.6% to 1.4%. However, they have not yet achieved the first target yet. The EU Directive
2003/96/EC had also established tax incentives to encourage renewable energy use.
The government of Germany (GE), Netherlands (NL) and United Kingdom (UK) are
supporting different assessment studies, while another one initiative is taking place from
Switzerland, the Roundtable on Sustainable Biofuels (RTB), a multiple stakeholder initiative,
hosted by the Ecole Polytechnique Federale de Lausanne. The main environmental issues
addressed by these different initiatives are related to greenhouse gas reduction compared
with fossil fuels; competition with other land uses, especially food competition; impacts on
the biodiversity and on the environment (Table 11). Considering carbon and greenhouse
gases balance current agricultural and industrial practices sugarcane ethanol from Brazil
does comply with the targets of greenhouse reduction higher than 79% from existing brown
fields, and from new green fields, when not replacing large areas of native vegetation. On
food competition, there is no direct evidence that sugarcane is replacing the basic Brazilian
staple foods (Nassar et al., this book). On biodiversity conservation, data from São Paulo
State show that sugarcane expansion did not reduce forest cover, but on the contrary (IEA/
CATI – SAAESP). On the use of water, fertilizers and agrochemicals, sugarcane ethanol
does perform well above any other current biofuel in the market (in this chapter).
In the USA, the Environmental Protection Agency (EPA) under the Energy Independence
and Security Act of 2007 is responsible for revising and implementing regulations on the
use of biofuels blended with gasoline. The Renewable Fuel Standard program will increase
the volume of renewable fuel required to be blended into gasoline from 9 billion gallons in
2008 to 36 billion gallons by 2022. At the same time, EPA is conducting several studies on
the direct and indirect impacts of the expansion of biofuels production and their carbon
footprint and potential reduction of greenhouse gases.
132
Sugarcane ethanol
Environmental sustainability of sugarcane ethanol in Brazil
Table 11. Main issues related to sustainable production of biofuels being considered under different
certification regimes.
Criterion
NL
UK
GE
RTB
EU
1. Greenhouse gas balance
a1) Net emission reduction compared with a fossil fuel
reference is at least 50%. Variation in policy instruments
could benefit the best performances.
a2) Life cycle GHG balance reduction of 67% compared with
fossil fuels
a3) Processing of energy crops GHG reduction of 67%
compared with fossil fuels
a4) GHG emissions savings from the use of biofuels at least
35% compared with fossil fuels
a5) GHG emissions will be reduced when compared to fossil
fuels
b) Soil carbon and carbon sinks
c) Emissions of N2O from biofuels
2. Competition with other applications/ land use
a) Availability of biomass for food, local energy supply,
building materials or medicines should not decline
b) Use of less productive land for biofuels
c) Increasing maximum use of crops for both food and fuel
d) Avoiding negative impacts from bioenergy-driven changes
in land use
3. Biodiversity
a) No deterioration of protected area’s or high quality ecosystems.
b) Insight in the active protection of the local ecosystem.
c) Alteration of local habitats
d) Effect on local species
e) Pest and disease resistance
f) Intellectual property and usage rights
g) Social circumstances of the local residents
h) Integrity
i) Standard on income distribution and poverty-reduction
j) Avoiding human health impacts
4. Environment
a) No negative effects on the local environment
b) Waste management
c) Use of agro-chemicals, including artificial manure
✓
✓
✓
✓
✓
✓
Sugarcane ethanol
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
133
Chapter 5
Table 11. Continued.
Criterion
NL
UK
GE
RTB
4. Environment (continued)
d) Preventing erosion and deterioration of the soil to occur
and maintaining the fertility of the soil
e) Active improvement of quality and quantity of surface and
groundwater
f) Water use efficiency of crop and production chain
g) Emissions to the air
h) Use of genetically modified organisms
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
EU
✓
✓
✓
✓
✓
Source: adapted from Van Dam et al. (2006).
NL = the Netherlands; UK = United Kingdom; GE = Germany; RTB = Round table on sustainable
biofuels; EU = European Union.
While the above concerns are well-justified, some criticism of biofuels and their impacts are
motivated by protectionism and interest in agricultural subsidies and agribusiness production
chains in several developing countries, especially from EU countries. Certification schemes
suggested may become non-tariff barriers, rather than environmentally and socially sound
schemes.
Scientific and technological assessments comparing different kinds of biofuels are needed to
reduce the play of such interests and to establish the strengths of best potential of biofuels
along with their dangers and limitations.
The OECD’s latest report on biofuels illustrates how fears can be perpetuated without proper
scientific basis. Suggestively titled: (‘Biofuels: is the cure worse than the disease?’), the report
stated: ‘Even without taking into account carbon emissions through land-use change, among
current technologies only sugarcane-to-ethanol in Brazil, ethanol produced as a by-product
of cellulose production (as in Sweden and Switzerland), and manufacture of biodiesel from
animal fats and used cooking oil, can substantially reduce [greenhouse gases] compared with
gasoline and mineral diesel. The other conventional biofuel technologies typically deliver
[greenhouse gas] reductions of less than 40% compared with their fossil-fuel alternatives’.
This report also recognized that while still trade barriers would persist to the international
market, it will be difficult for the world to take advantage of the environmental qualities of
the use of some biofuels, mainly the ethanol form sugarcane and so forth as international
markets are not yet fully created for biofuels.
134
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Environmental sustainability of sugarcane ethanol in Brazil
5. Future steps towards sustainable production of ethanol and the role of
innovation
A huge challenge facing policy makers, businesses, scientists and societies as a whole is how
to responsibly establish sustainable production systems and biofuel supplies in sufficient
volume that meet current and future demands globally.
The examples and best practices found in Brazilian sugarcane ethanol provides a good
framework and baseline of sustainability compared with other current biofuels available
in large scale in the World, having the smallest impact on food inflation, high levels of
productivity (on average 7,000 liters of ethanol/ha and 6.1 MWhr of energy/ha), with
lower inputs of fertilizers and agrochemicals, while reducing significantly the emissions of
greenhouse gases. The ending of sugarcane burning in 2014 is a good example of improving
existing practices. The proper planning of sugarcane expansion into new areas will for
another important step towards sustainable production of ethanol
In addition new technologies and innovation are taking place in Brazil and elsewhere in
the world, aiming at optimizing the use of feedstocks: using lignocellulosic materials (the
second generation of biofuels); reducing waste; adding value to ethanol co-products and
moving towards ethanol chemistry and biorefinaries full deployment.
Different initiatives in Brazil from the State of São Paulo Research Foundation (FAPESP),
Ministry of Science and Education (MC&T – FINEP) and investments from the private
sector are contributing to the deployment of new opportunities provided by the sugarcane
biomass, at the same time improving the environmental performances at the agriculture
and at the industry.
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latossolo vermelho distroférrico sob diferentes sistemas de uso e manejo. Ciências Agrárias, Londrina
26: 17-26.
OECD, 2007. Biofuels: is the cure worse than the disease? Paris: September, 2007. Available at: www.oecd.
org/dataoecd/40/25/39266869.pdf.
Ottmar, R.D., R.E. Vihnanek, H.S. Miranda, M.N. Sato and S.M.A. Andrade, 2003. Séries de estéreofotografias para quantificar a biomassa da vegetação do cerrado no Brasil Central. Brasília: USDA,
USAID, UnB, 2001. In: Ciclagem de Carbono em Ecossistemas Terrestres – O caso do Cerrado Brasileiro.
Planaltina/,DF – Embrapa Cerrados, 2003. Available at: bbeletronica.cpac.embrapa.br/2003/doc/doc_
105.pdf.
Protocolo Agroambiental do Setor Sucroalcooleiro, 2008. Available at: www.unica.com.br/content/show.
asp?cntCode={BEE106FF-D0D5-4264-B1B3-7E0C7D4031D6}.
Rangel, O.J.P. and C.A. Silva, 2007. Estoque de carbono e nitrogênio e frações orgânicas de latossolo
submetido a diferentes sistemas de uso e manejo. Revista Brasileira de Ciência do Solo 31: 1609-1623.
Ricci Junior, A., 2005. Pesticides: herbicides. In: Macedo, Isaias de Carvalho; Several Authors, 2005.
Sugarcane’s Energy – Twelve studies on Brazilian sugarcane agribusiness and its sustainability. São
Paulo, pp 156-161.
São Paulo State Government. Decreto no. 50.889, de 16 de junho de 2006. Dispõe sobre a manutenção,
recomposição, condução da regeneração natural e compensação da área de Reserva Legal de imóveis
rurais no Estado de São Paulo e dá providências correlatas. São Paulo. Available at: www.cetesb.sp.gov.
br/licenciamentoo/legislacao/estadual/decretos/2006_Dec_Est_50889.pdf.
São Paulo State Government. Lei no. 997, de 31 de maio de 1976. Dispõe sobre o controle da poluição do meio
ambiente. São Paulo. Available at: www.ambiente.sp.gov.br/uploads/arquivos/legislacoesambientais/1976_
Lei_Est_997.pdf.
São Paulo State Government. Lei no. 6.171, de 04 de julho de 1988. Dispõe sobre o uso, conservação e
preservação do solo agrícola. São Paulo. Available at: sigam.ambiente.sp.gov.br/Sigam2/legisla%C3%A
7%C3%A3o%20ambiental/Lei%20Est%201988_06171.pdf.
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São Paulo State Government. Lei no. 11.241, de 19 de Setembro de 2002. Dispõe sobre a eliminação gradativa
da queima da palha da cana-deaçúcar e dá providências correlatas. São Paulo. Available at: sigam.
ambiente.sp.gov.br/sigam2/Legisla%C3%A7%C3%A3o%20Ambiental/Lei%20Est%202002_11241.pdf.
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utilização dos recursos hídricos do domínio do Estado de São Paulo, os procedimentos para fixação dos
seus limites, condicionantes e valores e dá outras providências. São Paulo. Available at: www.ana.gov.
br/cobrancauso/_ARQS-legal/Geral/Legislacoes%20Estaduais/SP/Lei-12183-05.pdf.
São Paulo State Government. Resolução SMA 42, de 14 de outubro de 2006. Licenciamento ambiental prévio
de destilarias de álcool, usinas de açúcar e unidades de fabricação de aguardente. São Paulo. Available
at: www.milare.adv.br/ementarios/legislacao2006.pdf. São Paulo State Government. Resolução no. 382,
de 26 de dezembro de 2006. Estabelece os limites máximos de emissão de poluentes atmosféricos para
fontes fixas. São Paulo. Available at: www.mp.rs.gov.br/areas/ambiente/arquivos/boletins/bola_leg01_07/
ib382.pdf.
Smeets, E., M. Junginger, A. Faaij, A. Walter, P. Dolzan and W. Turkenburg, 2008;The sustainability of
Brazilian ethanol – an assessment of the possibilities of certified production. Biomass and Bioenergy
32: 781-813.
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Szakács, G.G.J., 2003. Avaliação das potencialidades dos solos arenosos sob pastagens, Anhembi – Piracicaba/
SP. Piracicaba, 2003. Dissertação (mestrado) – Centro de Energia Nuclear na Agricultura.
Titon, M., C.O. Da Ros, C. Aita, S.J. Giacomini, E.B. Do Amaral and M.G. Marques, 2003. Produtividade
e acúmulo de nitrogênio no milho com diferentes épocas de aplicação de N-uréia em sucessão a aveia
preta. In: XXIX Congresso Brasileiro de Ciência do Solo, 2003, Ribeirão Preto – SP.
Trumbore, S. 1993. Comparison of carbon dynamics in tropical and temperate soils using radiocarbon
measurements. Global Biogeochemical Cycles, Washington, v.7, pp. 75-290. In: Silveira, A.M., Victoria,
R.L., Ballester, M.V., De Camargo, P.B., Martinelli, L.A. and Piccolo, M.C., 2000. Simulação dos efeitos das
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show.asp?cntCode={BEE106FF-D0D5-4264-B1B3-7E0C7D4031D6}.
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Van Dam, J., M. Junginger, A. Faaij. I. Jurgens, G. Best and U. Fritsche, 2006. Overview of recent developments
in sustainable biomass certification. IEA Bioenergy Task 40. 40 pp.
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14 pp.
World Watch Institute, 2006. Available at: www.worldwatch.org.
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Chapter 6
Demand for bioethanol for transport
Andre Faaij, Alfred Szwarc and Arnaldo Walter
1. Introduction
The utilization of ethanol either as a straight fuel or blended to gasoline (in various
proportions) has been fully proven in various countries and it is regarded as technically
feasible with existing internal combustion engine technologies. Because ethanol offers
immediate possibilities of partially substituting fossil fuels, it has become the most popular
transport biofuel in use. Production of ethanol, which has been rising fast, is expected to
reach 70 billion litres by the end of 2008. Approximately 80% of this volume will be used
in the transport sector while the rest will go into alcoholic beverages or will be either used
for industrial purposes (solvent, disinfectant, chemical feedstock, etc.).
Although a growing number of countries, including China and India, have been introducing
ethanol in the transport fuels market, it is in Brazil, in the USA and in Sweden where this
use has gained most relevance. In March 2008, consumption of ethanol surpassed that of
gasoline in Brazil, largely due to the success of the flex-fuel vehicles (FFVs) and resulting
steep increase in straight ethanol (E100) consumption. In the USA, in addition to a rising
utilization of FFVs and high ethanol content blends with up to 85% ethanol content (E85),
over 50% of the gasoline marketed now contains ethanol, mostly 10% (E10). Sweden has
been leading ethanol use in Europe with the 5% gasoline blend consumed nationwide (E5),
an upward demand of E85 and a fleet of 600 ethanol-fuelled buses.
The international interest on ethanol in the transport sector has been based on various
reasons including energy security, trade balance, rural development, urban pollution
and mitigation of global warming. The challenge for the near future is to achieve wide
acceptance of ethanol as a sustainable energy commodity and global growth of its demand.
In the transport sector this includes increased supply of ethanol produced from a variety
of renewable energy sources in an efficient, sustainable and cost-effective way. In many
countries, 2nd generation biofuels (including ethanol) produced from lignocellulosic biomass
instead of food crops, is thought to deliver such performance, but commercial technology to
convert biomass from residues, trees and grasses to liquid fuels is not yet available. On the
demand side, it comprises the optimisation of existing engine technologies and development
of new ones that could make the best possible use of ethanol and be introduced in the
market in a large scale. Ethanol is a well suited and high quality fuel for more efficient flex
fuel engines, ethanol-fuelled hybrid drive chains and dual-fuel combustion systems. Such
technologies can boost vehicle efficiency and increase demand for ethanol use in various
transport applications.
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2. Development of the ethanol market
2.1. Growth in demand and production
Liquid biofuels play so far a limited role in global energy supply, and represent only 10%
of total bioenergy, 1.38% of renewable energy and 0.18% of total world energy supply.
They are of significance mainly for the transport sector, but even here they supplied only
0.8% of total transport fuel consumption in 2005, up from 0.3% in 1990. In recent years,
liquid biofuels have shown rapid growth in terms of volumes and share of global demand
for transport energy. Ethanol production is rising rapidly in many parts of the world in
response to higher oil prices, which are making ethanol more competitive. In 2007 the
world fuel ethanol production was estimated as 50 billion litres, being the production in
USA (24.6 billion litres) and Brazil (19 billion litres) equivalent to 88% of the total; in EU
the production was almost 2.2 billion litres, in China 1.8 billion litres and in Canada 800
million litres (RFA, 2008, based on Licht, 2007).
Production of ethanol via fermentation of sugars is a classic conversion route, yet the
most popular, which is applied for sugarcane, maize and cereals on a large scale, especially
in Brazil, the United States and to a lesser extent the EU and China. Ethanol production
from food crops like maize and cereals has been linked to food price increase, although
estimates to what extent vary widely and many factors apart from biofuels play a role in
those price increases (FAO, 2008). In addition bioethanol from such feedstocks has only
been competitive to gasoline and diesel when supported by subsidies. Despite of some
advances in its production process, ethanol from food crops is not likely to achieve major
cost reduction in the short and medium terms.
In contrast, the impact of sugarcane based ethanol production (dominated by Brazil) on
food prices seems minimal, given reduced world sugar prices in recent years. It’s production
achieved competitive performance levels with fossil fuel prices without the need of subsidies
(Wall-Bake et al., 2008). Also it has been gaining an increasingly relevant position in other
countries in tropical regions (such as India, Thailand, Colombia and various countries in
Sub-Saharan Africa). Production costs of ethanol in Brazil have steadily declined over the
past few decades and have reached a point where ethanol is competitive with production
costs of gasoline (Rosillo-Calle and Cortez, 1998; Wall-Bake et al., 2008). As a result, ethanol
is no longer financially supported in Brazil and competes openly with gasoline (Goldemberg
et al., 2004).
Figure 1 shows the learning curves of sugarcane and ethanol from sugarcane in Brazil
since late 1970s. The estimated progress ratio (PR) of 0.68 in case of sugarcane imply that
its costs of production have reduced, on average, 32% each time its cumulative production
has doubled (19% in case of ethanol costs, excluding feedstock costs). The figure also shows
140
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Demand for bioethanol for transport
Production costs sugarcane [US$/tonne] and ethanol (US$/m3)
Cumulative ethanol production (106 m3)
10
20
40
80
160
320
640
1,280
800
PR = 0.81±0.02
400
200
2020
40
20
PR = 0.68±0.03
10
Sugarcane
Ethanol prod. cost (excl. feedstock)
Expected range of cane prod. costs in 2020
Expected range of ethanol prod. costs in 2020
1,000
2,000
4,000
8,000
2020
16,000
32,000
Cumulative sugarcane production (106 TC)
Figure 1. Learning curves and estimated future costs of sugarcane and ethanol production (excluding
feedstock costs) assuming 8% annual growth of sugarcane and ethanol production (Wall-Bake et
al., 2008).
estimated costs of sugarcane and ethanol production by 2020, supposing a certain growth
path of sugarcane and ethanol production.
Larger facilities, better use of bagasse and trash residues from sugarcane production, e.g.
with advanced power generation (gasification based) or hydrolysis techniques (see below),
and further improvements in cropping systems, offer further perspectives for sugarcane
based ethanol production (Damen, 2001; Hamelinck et al., 2005).
The growth in the use of ethanol has been facilitated by its ability to be blended with gasoline
in existing vehicles and be stored and transported using current facilities, equipment and
tanks. Blending anhydrous ethanol with gasoline at ratios that generally are limited to E10 has
been the fastest and most effective way of introducing ethanol in the fuel marketplace.
In Brazil fuel retailers are required to market high ethanol-content blends, with a percentage
that can vary from 20% to 25% by volume (E20 – E25). Vehicles are customized for these
Sugarcane ethanol
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Chapter 6
blends by car manufacturers or, in the case of imported cars (around 10% of the market),
at the origin or by the importers themselves.
FFVs in the USA, Sweden and elsewhere can operate within a range that varies from straight
gasoline to E85 blends, while in Brazil they are built to run in a range that varies from
E20–E25 blends to E100. Up to 2006 car manufacturers in Brazil used to market dedicated
E100 vehicles, which were later substituted by the FFVs.
Considering that current world’s gasoline demand stands in the order of 1.2 trillion litres
per year (information brochure produced by Hart Energy Consulting for CD Technologies,
2008) fuel ethanol supply will reach approximately 5% of this volume in 2008, which in
energy terms represents 3% of current gasoline demand.
Ethanol has the advantage that it lowers various noxious emissions (carbon monoxide,
hydrocarbons, sulphur oxides, nitrogen oxides and particulates) when compared to
straight gasoline. Nevertheless the extent of emission reduction depends on a number
of variables mainly engine characteristics, the way ethanol is used and emission control
system features.
With regard to GHG emissions it has been demonstrated that on a life-cycle basis sugarcane
ethanol produced in Brazil can reduce these emissions by 86% under current manufacturing
conditions and use when compared to gasoline (Macedo et al., 2008). Avoided emissions
due to the use of ethanol produced from maize (USA) and wheat (EU) are estimated as 2040% on life-cycle basis (IEA, 2004). In case of ethanol from sugarcane further reductions
of GHG emissions are possible in short to mid-term, with advances in the manufacturing
process (i.e. replacement of mineral diesel with biodiesel or ethanol in the tractors and
trucks, end of pre-harvest sugarcane burning and capture of fermentation-generated CO2)
(Macedo et al., 2008; Damen, 2001; Faaij, 2006).
2.2. International trade
The development of truly international markets for bioenergy has become an essential
driver to develop available biomass resources and bioenergy potentials, which are currently
underutilised in many world regions. This is true for both residues as well as for dedicated
biomass production (through energy crops or multifunctional systems, such as agroforestry). The possibilities to export biomass-derived commodities for the world’s energy
market can provide a stable and reliable demand for rural communities in many developing
countries, thus creating an important incentive and market access that is much needed in
many areas in the world. The same is true for biomass users and importers that rely on a
stable and reliable supply of biomass to enable often very large investments in infrastructure
and conversion capacity.
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Demand for bioethanol for transport
Figures 2 and 3 show the top ten ethanol importers and exporters in 2006, when the total
volume traded was estimated as 6.5 billion litres, i.e. almost 13% of the whole production
(Valdes, 2007). At that year more than 60 countries exported ethanol, but only ten surpassed
100 million litres traded and the most important 15 exporters covered 90% of the whole
trade. US have imported more than 2.5 billion litres in 2006, EU about 690 million litres
(Licht, 2007), while the imports of Japan were estimated as about 500 million litres. These
three economic blocks represented about 80% of the net imports of ethanol in 2006.
Clearly, Brazil stands out as the largest exporter, covering more than 50% of the total volume
traded. Except in 2006, when more than 50% was directly sold to US, ethanol exports from
Italy
France
Belgium
S.Korea
Sweden
UK
Netherlands
Germany
Japan
USA
0
500
1,000
1,500
2,000
2,500
3,000
Ethanol import (mln litres)
Figure 2. Top 10 ethanol importers in 2006 (Licht, 2007).
Italy
Pakistan
Ukraine
UK
Germany
Spain
USA
France
China
Brazil
0
500
1,000
1,500
2,000
2,500
3,000
3,500
Ethanol export (mln litres)
Figure 3. Top 10 ethanol exporters in 2006 (Licht, 2007).
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Chapter 6
Brazil have been roughly well distributed among 10-12 countries. On the other hand, due to
the Caribbean Basin Initiative (CBI) agreement10, most of the ethanol exported from Brazil
to Central America and Caribbean countries reaches US. US importers from Caribbean
and Central America countries have continuously grown since 2002.
Figure 4 shows Brazil’s ethanol trade since 1970. Traditionally, Brazilian exports of ethanol
have been oriented for beverage production and industrial purposes but, recently, trade
for fuel purposes has enlarged. Halfway the 90-ies, a shortage of ethanol occurred, even
requiring net imports. But after 2000 Brazilian exports of ethanol have risen steadily. In
2007 exports reached 3.5 billion litres and it is estimated that about 4 billion litres will be
exported in 2008. It is expected that Brazil will maintain such an important position in the
future. Outlooks on the future ethanol market are discussed in the next section.
10 CBI
is an agreement between US and Central American and Caribbean countries that allows that up to 7%
of the US ethanol demand may be imported duty-free, even if the production itself occurs in another country
(Zarilli, 2006).
5,000
Imports
Exports
Brazil's ethanol trade (million litres)
4,000
3,000
2,000
1,000
0
1970
1975
1980
1985
1990
1995
2000
2005
2010
-1,000
-2,000
-3,000
Figure 4. Trade in ethanol in Brazil 1970-2008 (estimates for 2008), including all end-uses (Brazil,
2008), (Kutas, 2008).
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Sugarcane ethanol
Demand for bioethanol for transport
3. Drivers for ethanol demand
3.1. Key drivers
When evaluating key drivers for ethanol demand, energy security and climate change are
considered to be the most important objectives reported by nearly all countries that engage
in bioenergy development activities. As illustrated in Table 1 no country highlights less
than three key objectives. This renders successful bioenergy development a challenge as it
tries to reach multiple goals, which are not always compatible. For instance, energy security
considerations favour domestic feedstock production (or at least diversified suppliers),
whereas climate change considerations and cost-effectiveness call for sourcing of feedstocks
with low emissions and costs. This implies that imports are likely to grow in importance for
various industrialized countries, but also a strong pressure on developing 2nd generation
biofuels that are to be produced from lignocellulosic biomass. Not surprisingly, the latter is
a key policy and RD&D priority in North America and the EU.
X
X
X
X
X
X
X
X
X
X
X
X
Sugarcane ethanol
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Cost
effectivenness
X
X
Technological
progress
X
X
Agricultural
development
Environment
Brazil
China
India
Mexico
South Africa
Canada
France
Germany
Italy
Japan
Russia
UK
US
EU
Rural
development
Objectives
Energy security
Country
Climate change
Table 1. Main objectives of bioenergy development of G8 +5 countries (GBEP, 2008).
X
X
X
X
X
X
X
X
X
X
X
X
X
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Chapter 6
Overall there are few differences between the policy objectives of G8 Countries and the +5
countries (Mexico, South Africa, Brazil, India, China). Rural development is more central to
the +5 countries’ focus on bioenergy development, and this is often aligned with a poverty
alleviation agenda. Bioenergy development is also seen as an opportunity to increase access to
modern energy, including electrification, in rural areas. The rural development objectives of
the wealthier G8 countries focus more on rural revitalization. Similarly, in the +5 countries,
agricultural objectives envisage new opportunities not just for high-end commercialised
energy crop production, but also for poorer small-scale suppliers. Very important is that
in many countries (both industrialized and developing) sustainability concerns, e.g. on
land-use, competition with food, net GHG balances, water use and social consequences,
has become an overriding issue. Development and implementation of sustainability criteria
is now seen in a variety of countries (including the EU) and for various commodities (such
as palm oil, sugar and soy) (Van Dam et al., 2008; Junginger et al., 2008).
3.2. Developments in vehicle technology
Transport predominantly relies on a single fossil resource, petroleum that supplies 95% of
the total energy used by world transport. In 2004, transport was responsible for 23% of world
energy-related GHG emissions with about three quarters coming from road vehicles. (see
also the breakdown of energy use of different modes of transport in Table 2). Over the past
decade, transport’s GHG emissions have increased at a faster rate than any other energyusing sector (Kahn Ribeiro et al., 2007).
Figures 5a and 5b provide projections for the growth in energy use per mode of transport
and per world region. Transport activity will continue to increase in the future as economic
growth fuels transport demand and the availability of transport drives development, by
Table 2. World transport energy use in 2000, by mode (Kahn Ribeiro et al., 2007, based on WBCSD,
2004b).
Mode
Energy use (EJ)
Share (%)
Light-duty vehicles
2-wheelers
Heavy freight trucks
Medium freight trucks
Buses
Rail
Air
Shipping
Total
34.2
1.2
12.48
6.77
4.76
1.19
8.95
7.32
76.87
44.5
1.6
16.2
8.8
6.2
1.5
11.6
9.5
100
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Sugarcane ethanol
Demand for bioethanol for transport
b
a
200
EJ
150
Rail
Water
Air
100
Buses
Freight trucks
50
Africa
Latin America
Middle East
India
Other Asia
China
Eastern Europe
EECCA
OECD Pacific
OECD Europe
2-3 wheelers
OECD N. America
LDVs
Bunker fuel
0
2000 2010 2020 2030 2040 2050 2000 2010 2020 2030 2040 2050
Figure 5. Projection of transport energy consumption by mode (a) and region (b) (WBCSD, 2004a).
facilitating specialization and trade. The majority of the world’s population still does not
have access to personal vehicles and many do not have access to any form of motorized
transport. However, this situation is rapidly changing.
Freight transport has been growing even more rapidly than passenger transport and is
expected to continue to do so in the future. Urban freight movements are predominantly
by truck, while international freight is dominated by ocean shipping.
Transport activity is expected to grow robustly over the next several decades. Unless there
is a major shift away from current patterns of energy use, world transport energy use is
projected to increase at the rate of about 2% per year, with the highest rates of growth in
the emerging economies. Total transport energy use and carbon emissions are projected to
be about 80% higher than current levels by 2030 (Kahn Ribeiro et al., 2007).
There is an ongoing debate about whether the world is nearing a peak in conventional oil
production that will require a significant and rapid transition to alternative energy resources.
There is no shortage of alternative energy sources that could be used in the transport
sector, including oil sands, shale oil, coal-to-liquids, gas-to-liquids, natural gas, biofuels,
electricity and hydrogen produced from fossil fuels or renewable energy sources. Among
these alternatives, unconventional fossil carbon resources could produce competitively
priced fuels most compatible with the existing transport infrastructure, but these will lead
to strongly increased carbon emissions (Kahn Ribeiro et al., 2007).
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3.2.1. The impact of existing technologies on fuel ethanol demand
In use vehicle technologies already enable large scale use of ethanol and therefore can be
considered a key driver for its worldwide use. For instance, if E10 were to become globally
used today, the global FFVs fleet (estimated at 15 million vehicles as of 2008) were to use the
maximum level of ethanol and 50,000 buses were equipped with dedicated ethanol engines,
fuel ethanol demand would jump from current 56 billion litres to 165 billion litres, almost
a 200% increase over existing demand (Szwarc, A. personal communication). The largest
consumption (75%) would come from ethanol blending with gasoline.
This estimate indicates the potential demand for ethanol without any technological
breakthrough and although it would not be feasible to be achieved overnight because it
requires a regulatory framework and ethanol logistics, it could be gradually developed
until 2020. Projections of ethanol production for Brazil, the USA and the EU indicate that
supply of 165 billion litres by 2020 could be achieved with the use of a combination of first
and second generation ethanol production technologies.
However, a scenario where sugarcane ethanol production in Asia, Africa, Latin America and
the Caribbean could fulfil these needs is also possible. Approximately 25 million hectares of
sugarcane would be needed to produce this volume worldwide using only first generation
technology. With cellulosic ethanol production technologies in place using sugarcane
bagasse and straw and combination of these technologies with first generation technology,
the need for land use would be reduced to 20 million hectares. A third scenario considering
extensive use of second generation ethanol production from various non-conventional
feedstocks, including industrial residues and municipal waste, could further reduce the
need of land for ethanol production further (Walter et al., 2008).
3.2.2. FFVs technology and the market
In 1992, the US market saw the first commercially produced FFVs. It was a concept that
would allow the gradual structuring of an ethanol market. Drivers would be allowed to run
on gasoline where ethanol would not be available, therefore resolving the question on ‘what
comes first: the car or the fuel infrastructure?’ that inhibited the ethanol market growth.
Pushed by alternative energy regulations and fiscal incentives, American car manufacturers
began producing FFVs that in most part ended up in government fleets. Because the number
of fuel stations marketing E85 is very limited, FFVs in the US have been fuelled with straight
gasoline most of the time. General Motors has been championing the FFV concept in the
USA and has recently engaged in the expansion of E85 sales locations. Other companies
like Ford, Chrysler and Nissan have also FFVs in their sales portfolio. By December 2008
approximately 8 million FFVs (2.8% of vehicle fleet in the US) will be on American roads
but still consuming mostly gasoline (Szwarc, A., personal communication).
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Sweden was the first country in Europe to start using FFVs in 1994. At first only a few
imported vehicles from the US composed a trial fleet, but in 2001 FFVs sales started. In
2005 local car manufacturers like Saab and Volvo developed E85 FFVs versions. In 2007, the
market share of new FFVs in Sweden was 12% and the total fleet reached 80,000 vehicles (2%
of the total vehicle fleet). Over 1,000 fuel stations are selling E85 in Sweden making possible
the use of E85 in FFVs. A variety of policy measures have been provided incentives for
FFVs in Sweden. These include exemption of biofuels from mineral oil tax, tax benefits for
companies and private car owners, free parking in 16 cities and mandatory alternative fuel
infrastructure and government vehicle purchases. This initiative is part of a set of measures
taken by Sweden in order to achieve its ambitious goal to be at the forefront of the world’s
‘green’ nations and achieve a completely oil-free economy by 2020.
E100-compatible FFVs were introduced in the Brazilian market in 2003 in a different context
than observed in the US or Sweden, in order to fulfil consumers’ desire to use a cheaper
fuel. FFVs have become a sales phenomenon and presently sales correspond to nearly 90%
of new light-duty vehicle sales. All car manufacturers in Brazil have developed FFVs that
are being offered as standard versions for the domestic market (over 60 models in 2008).
The success of FFVs can be explained by now excellent availability of E100 and E20/E25
(at more than 35,000 fuel stations nationwide), flexibility for consumers who can choose
the fuel they want depending on fuel costs and/or engine performance. Since fuel ethanol
has been in general less expensive than gasoline blends (straight gasoline is not available
for sale in Brazil) and gives better performance, it became the fuel of choice. Furhtermore
FFV’s have a ‘greener’ and more modern image and have higher resale value compared to
conventional cars.
In 2008, the Brazilian fleet of FFVs will reach 7 million vehicles (25% of vehicle fleet) and
in most cases the preferred fuel has been E100. The success of FFVs in Brazil has caught the
attention of manufacturers of two wheel vehicles (motorcycles, scooters and mopeds) who
are developing FFVs versions that are expected to reach the market soon.
3.2.3. The impact of new drive chain technologies
Compared to current average vehicle performance, considerable improvements are possible
in drive chain technologies and their respective efficiencies and emission profiles. IEA does
project that in a timeframe towards 2030, increased vehicle efficiency will play a significant
role in slowing down the growth in demand for transport fuels. Such steps can be achieved
with so-called hybrid vehicles which make use of combined power supply of internal
combustion engine and an electric motor. Current models on the market, if optimised
for ethanol use, could deliver a fuel economy of about 16 km/litre of fuel. With further
technology refinements, which could include direct injection and regenerative breaking,
fuel ethanol economy of 24 km/litre may be possible. Such operating conditions, can also
deliver very low concentration of emissions.
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The use of ethanol in heavy-duty diesel fuelled applications is not easy. But the well established
experience with ethanol-fuelled buses in Sweden, which started in the mid-nineties, and
recent research with dual-fuel use (diesel is used in combination with ethanol but each
fuel is injected individually in the combustion chamber according to a preset electronically
controlled engine map) indicate interesting possibilities with regard to reducing both diesel
use and emissions.
Drive chain technologies that may make a considerable inroad in the coming decades, such
as electric vehicles and serial hybrids, may however have a profound impact on vehicle
efficiency and, to some extent, a dampening effect on the growth of transport fuel demand.
Penetration of electric vehicles (cars, motorcycles and mopeds) or the use of plug-in hybrids
that could be connected to the grid is still uncertain. Developments in battery technology
are rapid though and electric storage capacity, charging time and power to weight ratios are
continuously improved. When such improved technology is especially deployed in hybrid
cars, the net effect will simply be a reduction of fuel demand. However, when deployed as
plug-in hybrid, part of the fuel demand can be replaced by electricity. This could reduce the
growth in demand for (liquid) transport fuels down more quickly than currently assumed
in various studies.
In case Fuel Cell Vehicles (FCVs) become commercially available, this may mean a boost for
the use hydrogen as fuel. Although the projected overall ‘well-to-wheel’ potential efficiency
of e.g. natural gas to hydrogen or biomass to hydrogen for use in a FCV is very good
(Hamelinck and Faaij, 2006), it is highly uncertain to what extent the required hydrogen
distribution infrastructure may be available in the coming decades. Important barriers are
the currently high costs of FCVs and the high investment costs of hydrogen infrastructure.
Most scenarios on the demand for transport fuels towards 2030 project only a marginal
role for hydrogen.
Nevertheless, the speed of penetration of such more advanced drive chains in the market
and the new infrastructure they require, is uncertain and the available projections for
demand of liquid transport fuels indicate that we may be looking at a doubling of demand
halfway this century. Also, the overall economic and environmental performance of the use
of electricity and hydrogen for transport depends heavily on the primary energy source and
overall chain efficiency.
Hybrid vehicles in the transport sector and urban services seem to be at present stage a
more viable alternative than FCV for the same applications. Not only is this technology more
advanced in terms of commercial use but also it has many practical advantages in terms of
cost and fuel infrastructure (Kruithof, 2007). Sweden has been leading the development
of hybrid buses and trucks equipped with electric motor and ethanol engine. Commercial
use of this type of vehicles could occur by 2010 setting a new benchmark for sustainable
ethanol use.
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4. Future ethanol markets
Future ethanol markets could be characterized by a diverse set of supplying and producing
regions. From the current fairly concentrated supply (and demand) of ethanol, a future
international market could evolve into a truly global market, supplied by many producers,
resulting in stable and reliable biofuel sources. This balancing role of an open market and
trade is a crucial precondition for developing ethanol production capacities worldwide.
Paramount to a solution is an orderly and defined schedule for elimination of subsidies,
tariffs, import quotas, export taxes and non-tariff barriers in parallel with the gradual
implementation of sustainable ethanol mandates. These measures will provide the
necessary conditions to reduce risks and to attract investment to develop and expand
sustainable production. Several different efforts to reach these goals are ongoing including
multilateral, regional, and bilateral negotiations, as well as unilateral action. Public and
private instruments such as standards, product specifications, certification and improved
distribution infrastructure are important for addressing technical and sustainability issues.
In addition, the development of a global scheme for sustainable production combined with
technical and financial support to facilitate compliance, could ensure that sustainability and
trade agendas are complementary (Best et al., 2008).
4.1. Outlook on 2nd generation biofuels
Projections that take explicitly second generation options into account are more rare, but
studies that do so come to rather different outlooks, especially in the timeframe exceeding
2020. Providing an assessment of studies that deal with both supply and demand of biomass
and bioenergy, IPCC highlights that biomass demand could lay between 70-130 EJ in total,
subdivided between 28-43 EJ biomass input for electricity and 45-85 EJ for biofuels (Barker
and Bashmakov, 2007). Heat and biomass demand for industry are excluded in these reviews.
It should also be noted that around that timeframe biomass use for electricity has become a
less attractive mitigation option due to the increased competitiveness of other renewables
(e.g. wind energy) and e.g. carbon capture and storage. (Barker and Bashmakov, 2007).
In de Vries et al. (2007) (based on the analyses of Hoogwijk et al. (2005, 2008), it is indicated
that the biofuel production potential around 2050 could lay between about 70 and 300 EJ
fuel production capacity depending strongly on the development scenario, i.e. equivalent to
3,100 to 9,300 billion litres of ethanol11. Around that time, biofuel production costs would
largely fall in the range up to 15 U$/GJ, competitive with equivalent oil prices around 50-60
U$/barrel (see also Hamelinck and Faaij, 2006). A recent assessment study confirms that
such shares in the global energy supply are possible, to a large extent by using perennial
11 Based
on the LHV of anhydrous ethanol (22.4 MJ/litre).
Sugarcane ethanol
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Chapter 6
cropping systems that produced lignocellulosic biomass, partly from non-agricultural lands
and the use of biomass residues and wastes. Large changes in land use and leakage effects
could be avoided by keeping expanding biomass production in balance with increased
productivity in agriculture and livestock management. Such a development would however
require much more sophisticated policies and effective safeguards and criteria in the global
market (Dornburg et al., 2008).
4.2. Scenario’s on ethanol demand and production
Walter et al. (2008) evaluated market perspectives of fuel ethanol up to 2030, considering
two alternative scenarios. The first scenario reflects constrains of ethanol production in
US and Europe due to the hypothesis that large-scale production from cellulosic materials
would be feasible only towards the end of the period. In this case world production would
reach 272,4 billion litres in 2030 (6 EJ), being only 8 billion litres of second generation
ethanol, amount that would displace almost 10% of the estimated demand of gasoline.
Scenario 2 is based on the ambitious targets of ethanol production defined by US government
by early 2007, i.e. consumption of about 132 billion litres by 2017. This target can only be
achieved if large-scale ethanol production from cellulosic materials becomes feasible in
short- to mid-term. In Scenario 2 the consumption of fuel ethanol reaches 566 billion litres
in 2030 (about 13 EJ), displacing more than 20% of the demand of gasoline; 203 billion litres
would be second generation ethanol.
Tables 3 summarizes results of the two scenarios for different regions/countries of the
world. In case of EU, the substitution of 28.5% of gasoline volume basis (Scenario 1)
would correspond to the displacement of 20% energy basis. By 2030, the estimated ethanol
consumption in EU (both scenarios) and US (scenario 2) would only be possible with FFVs
or even neat ethanol vehicles.
Table 3 also presents estimates of production capacity of first generation ethanol. Production
capacity by 2030 was evaluated by Walter et al. (2008) based on the capacity available in
2005 and on projections based on trends and plans. In some cases (e.g. EU) these results
were adjusted to the estimates done by the IEA (2004) as well as Moreira (2006) taking into
account constraints such as land availability. It is clear that without second generation ethanol
the relatively modest target to displace 10% of the gasoline demand in 2030 (Scenario 1), at
reasonable cost, can only be accomplished fostering fuel ethanol production in developing
countries. Second generation of ethanol would be vital if 20% of the gasoline demand is to
be replaced by biofuels in 2030 (Scenario 2), although a significant contribution would have
to come from conventional feedstocks mainly from developing countries.
However, the combination of lignocellulosic resources (biomass residues on shorter term
and cultivated biomass on medium term) and second generation conversion technology
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Demand for bioethanol for transport
Table 3. Ethanol consumption by 2030 in two different scenarios and production capacity based on
conventional technologies (billion litres).
Region/
country
Scenario 1
Scenario 2
Gasoline
displaced (%) 1
Production
Gasoline
displaced (%) 1 capacity
US
EU
Japan
China
Brazil
ROW 5
55.3
36.0
9.3
21.6
50.0
100.2
7.4
28.5
10.0
10.0
48.03
10.0
35.0
39.3
15.0
15.0
48.03
15.0
263.7
49.6
14.3
33.5
50.0
154.9
63.0
27.3
–2
18.2
62.0 4
n.c.6
1
Gasoline displaced in volume basis regarding the estimated gasoline consumption in 2030.
It was assumed that first generation ethanol would not be produced in Japan.
3 Estimates of gasoline displaced considering that the substitution ratio by 2030 would be 1 litre of
gasoline = 1.25 litre of ethanol. In case of Brazil there is only one scenario.
4 In this case production capacity is not the maximum, but the capacity that should be reached
considering a certain path of growth.
5 Rest of the World.
6 n.c. = not calculated.
2
offers a very strong perspective. Furthermore, sugarcane based ethanol has a key role
to play at present and that role can be considerably expanded by improving the current
operations further and by implementation cane based ethanol production to regions where
considerably opportunities exist, especially to parts of Sub-Saharan Africa. For example,
the efficient use bagasse and sugar can trash with advanced co-generation technology can
increase electricity output of sugar mills considerably in various countries and thus deliver
a significant contribution to (renewable) electricity production. Also, it seems realistic to
assume that sugarcane based ethanol can meet the new and stringent sustainability criteria
that are expected in the global market on short term (see e.g. Smeets et al., 2008).
5. Discussion and final remarks
5.1. Key issues for the future markets
Biofuels in 2008 is at a crossroad: the public perception and debate have to a considerable
amount pushed biofuels in a corner as being expensive, not effective as GHG mitigation
option, to have insignificant potential compared to global energy use, a threat for food
production and environmentally dangerous. But that basic rationale for the production
and use of biofuels still stands and is stronger than ever. Climate change is accepted as a
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Chapter 6
certainty, the supply of oil in relation to growing demand has developed into a strategic and
economic risk, with oil prices hoovering around 130 US$/barrel at the moment of writing.
Furthermore, the recent food crisis has made clear how important it is that investment and
capacity building reach the rural regions to improve food production capacity and make
this simultaneously more sustainable. Biofuels produced today in various OECD countries
have a mediocre economic and environmental performance and many objections raised
are understandable, be it overrated.
However, distinguishing those biofuels from sugarcane based ethanol production and the
possibilities offered by further improvement of that production system, as well as second
generation biofuels (including ethanol production from lignocellulosic resources produced
via hydrolysis) is very important. It is clear though, that future growth of the biofuel market
will take place with much more emphasis on meeting multiple goals, especially avoiding
conflicts on land-use, water, biodiversity and at the same time achieving good GHG
performance and socio-economic benefits (see e.g. Hunt et al., 2007).
5.2. Future outlook
Projections for the production and use of biofuels differ between various institutions.
Clearly, demand for transport fuels will continue to rise over the coming decades, also with
the introduction of new drive chain technology. In fact, there could be an important synergy
between new drive chains (such as serial hybrid technology) and high quality biofuels with
narrow specifications (such as ethanol), because such fuels allow for optimised performance
and further decreased emissions of dust and soot, sulphur dioxide and nitrous oxides.
Projections that highlight a possibly marginal role for biofuels in the future usually presume
that biomass resource availability is a key constraint and that biofuel production will remain
based on current technologies and crops and stay expensive (e.g. IEA, 2006, OECD/FAO,
2007). Clearly, the information compiled in this chapter shows that a combination of further
improved and new conversion technologies and conversion concepts (such as hydrolysis
for producing sugars of ligno cellulosic materials) and use of ligno cellulosic biomass offers
a different perspective: the biomass resource basis consisting of biomass residues from
forestry and agriculture, organic wastes, use of marginal and degraded lands and the possible
improvement in agricultural and livestock efficiency that can release lands for additional
biomass production could become large enough to cover up to one third of the global
energy demand, without conflicting with food production or additional use of agricultural
land. Also, the economic perspectives for such second generation concepts are very strong,
offering competitiveness with oil prices equivalent to some 55 US$/barrel around 2020.
Further improved ethanol production (i.e. with improved cane varieties, more efficient
factories and efficiently use of bagasse and trash for power generation or more ethanol using
hydrolysis processes) from sugarcane holds a similar strong position for the future.
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Demand for bioethanol for transport
5.3. Policy requirements and ways forward
It is very likely ethanol has a major role to play in the future worlds’ energy markets. There
are uncertainties though, such as dwindling public support for biofuels and possible failure
to commercialise second generation technologies on foreseeable term. In case biofuels
can be developed and managed to be the large and sustainable energy carriers they can in
principle become (which largely depends on the above mentioned governance issues). It is
also clear that sugarcane based ethanol production is one of the key systems now with a very
good future outlook. In addition, ethanol is a fuel that can easily absorbed by the market.
Key preconditions for achieving the sketched desirable future outlook are:
• To build on the success of current sugarcane based ethanol production and develop and
implement further optimised production chains.
• Remove market barriers to allow for open trade for biofuels across the globe, while at
the same time securing sustainable production by adoption of broad criteria.
• To enhance strong Research Development, Demonstration and Deployment efforts with
respect to advanced, second generation conversion technologies. This concerns new,
commercial stand-alone processes, but also improvements of existing infrastructure
and even combinations with fossil fuels (such as co-gasification of biomass with coal
for production of synfuel, combined with CO2 capture and storage).
• To develop and broaden the biomass resources base by expanding (commercial) experience
with production of woody and grassy crops. Also the enhanced use of agricultural and
forestry residues can play an important role, in particular on the shorter term.
• To further develop, demonstrate and implement the deployment of broad sustainability
criteria for biomass production, in general, and biofuels, in particular. This can be done
by means of certification. Global collaboration and linking efforts around the globe
is important now to avoid a ‘proliferation of standards’ and the creation of different,
possible conflicting schemes.
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Chapter 7
Biofuel conversion technologies
Andre Faaij
1. Introduction
In the current heated societal debate about the sustainability of biofuels, usually a distinction
is made between so-called ‘first’ and ‘second’ generation biofuels. A large number of options
to produce biomass from biofuel is used or are possible (a simplified overview of options is
given in Figure 1). Although definitions differ between publications, first generation biofuels
typically are produced from food crops as oilseeds (rapeseed, palm oil), starch crops (cereals,
maize) or sugar crops (sugar beet and sugarcane). Conversion technologies are commercial
and typically feedstock costs dominate the overall biofuel production costs. Furthermore,
Water gas shift
+ separation
Gasification
Hydrogen
(H2)
Methanol
(CH3OH)
Syngas
Catalysed
synthesis
DME
(CH3OCH3)
FT Diesel
(CxHy)
Lignocellulosic
biomass
Anaerobic
digestion
Biogas
Purification
SNG
(CH4)
Flash pyrolysis
Bio oil
Hydro treating
and refining
Biodiesel
(CxHy)
Sugar
Fermentation
Ethanol
(CH3CH2OH)
Esterification
Biodiesel
(alkyl esters)
Hydrothermal
liquefaction
Hydrolysis
Sugar/starch
crops
Milling and
hydrolysis
Oil plants
Pressing or
extraction
Vegetable oil
Bio oil
(vegetable oil)
Figure 1. different existing and possible biofuel production routes (Hamelinck and Faaij, 2006). This
is a simplified overview; other production chains are possible for example by combining conversion
pathways, e.g. combined ethanol and biogas production, ethanol production and gasification of
lignine for synfuels and integrated concepts with other industrial processes (pulp & paper plants) or
bio refineries.
Sugarcane ethanol
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in particular when food crops are used grown in temperate climates (i.e. the US and the
EU), costs are typically high due to high feedstock costs and the net overall avoided GHG
emissions range between 20-50% compared to conventional gasoline or diesel (Fulton, 2004,
Hunt et al., 2007). Another constraint is that such food crops need to be produced on better
quality land and increased demand directly competes with food markets. This has recently
led to a wide range of estimates on the presumed impact of biofuel production on food prices
(FAO, 2008), ranging between 3 up to 75%. However, sugarcane based ethanol production
is a notable exception to these key concerns. Overall production costs as achieved in Brazil
are competitive without subsidies, net GHG balance achieves 80-90% reduction and sugar
prices have remained constant or have decreased slightly over the past years, despite strong
increases in ethanol production from sugarcane.
Palm oil, in turn, although far less important as feedstock for biofuel production has been
at the centre of the sustainability debate, because it’s production is directly linked to loss
of rainforest and peat lands in South-East Asia. Nevertheless, palm oil is an efficient and
high yield crop to produce vegetal oil (Fulton, 2004). Recently, interest in Jatropha, a oil
crop that can be grown in semi-arid conditions is growing, but commercial experience is
very limited to date.
Second generation biofuels are not commercially produced at this stage, although in various
countries demonstration projects are ongoing. 2nd generation biofuels are to be produced
from lignocellulosic biomass. In lignocellulose, typically translated as biomass from woody
crops or grasses and residue materials such as straw, sugars are chemically bound in chains
and cannot be fermented by conventional micro-organisms used for production of ethanol
from sugars and the type of sugars are different than from starch or sugar crops. In addition,
woody biomass contains (variable) shares of lignine, that cannot be converted to sugars.
Thus, more complex conversion technology is needed for ethanol production. Typical
processes developed include advanced pre-treatment and enzymatic hydrolysis, to release
individual sugars. Also fermentation of C5 instead of C6 sugars is required. The other key
route being developed is gasification of lignocellulosic biomass, subsequent production of
clean syngas that can be used to produce a range of synthetic biofuels, including methanol.
DME and synthetic hydrocarbons (diesel). Because lignocellulosic biomass can origin from
residue streams and organic wastes (that do in principle not lead to extra land-use when
utilised), from trees and grasses that can also be grown on lower quality land (including
degraded and marginal lands), it is thought that the overall potential of such routes is
considerably larger on longer term than for 1st generation biofuels. Also, the inherently
more extensive cultivation methods lead to very good net GHG balances (around 90% net
avoided emissions) and ultimatly, they are thought to deliver competitive biofuels, due to
lower feedstock costs, high overall chain efficiency, net energy yield per hectare, assuming
large scale conversion.
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Biofuel conversion technologies
This chapter gives an overview of the options to produce fuels from biomass, addressing
current performance and the possible technologies and respective performance levels on
longer term. It focuses on the main currently deployed routes to produce biofuels and
on the key chains that are currently pursued for production of 2nd generation biofuels.
Furthermore, an outlook on future biomass supplies is described in section 2, including
a discussion of the impact of sustainability criteria and main determining factors and
uncertainties. The chapter is finalized with a discussion of projections of the possible longer
term role of biofuels on a global scale and the respective contribution of first and second
generation biofuels.
2. Long term potential for biomass resources.
This section discusses a integral long term outlook on the potential global biomass resource
base, including the recent sustainability debate and concerns. This assessment covered on
global biomass potential estimates, focusing on the various factors affecting these potentials,
such as food supplies, water use, biodiversity, energy demands and agro-economics
(Dornburg et al., 2008). The assessment focused on the relation between estimated biomass
potentials and the availability and demand of water, the production and demand of food,
the demand for energy and the influence on biodiversity and economic mechanisms.
The biomass potential, taken into account the various uncertainties as analysed in this study,
consists of three main categories of biomass:
1. Residues from forestry and agriculture and organic waste, which in total represent
between 40 - 170 EJ/yr, with a mean estimate of around 100 EJ/yr. This part of the
potential biomass supplies is relatively certain, although competing applications may
push the net availability for energy applications to the lower end of the range. The latter
needs to be better understood, e.g. by means of improved models including economics
of such applications.
2. Surplus forestry, i.e. apart from forestry residues an additional amount about 60-100
EJ/yr of surplus forest growth is likely to be available.
3. Biomass produced via cropping systems:
a. A lower estimate for energy crop production on possible surplus good quality
agricultural and pasture lands, including far reaching corrections for water scarcity,
land degradation and new land claims for nature reserves represents an estimated
120 EJ/yr (‘with exclusion of areas’ in Figure 2).
b. The potential contribution of water scarce, marginal and degraded lands for energy
crop production, could amount up to an additional 70 EJ/yr. This would comprise
a large area where water scarcity provides limitations and soil degradation is more
severe and excludes current nature protection areas from biomass production (‘no
exclusion’ in Figure 2).
c. Learning in agricultural technology would add some 140 EJ/yr to the above mentioned
potentials of energy cropping.
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The three categories added together lead to a biomass supply potential of up to about
500 EJ.
Energy demand models calculating the amount of biomass used if energy demands are
supplied cost-efficiently at different carbon tax regimes, estimate that in 2050 about 50-250
EJ/yr of biomass are used. At the same time, scenario analyses predict a global primary energy
use of about 600 – 1040 EJ/yr in 2050 (the two right columns of Figure 2). Keep in mind that
food demand of around 9 billion people in 2050 are basically met in those scenario’s.
1,600
'ultimate' technical potential
1,000
High
range
Range
WEA
EJ/year
800
Medium
range
600
400
Learning in
agricultural
technology
200
With exclusion
of areas
No exclusion
Low range
Surplus forestry
Range
studies
er
en
a
re ss p
vie o
w ten
st tia
ud ls
ie
Bi
s
an oma
al ss
ys p
is ot
th en
is ti
st als
ud
M
y
od
el
le
d
bi
o
de ene
m rg
an y
d
om
Bi
gy Tota
de l w
m or
an ld
ds
Residues
0
Figure 2. Comparison of biomass supply potentials in the review studies and in this study with the
modelled demand for biomass and the total world energy demand, all for 2050 (Dornburg et al.,
2008). EJ = Exajoule (current global energy use amounts about 470 EJ at present). The first bar from
the left represents the range of biomass energy potentials found in different studies, the second
presents the results generated in (Dornburg et al., 2008), taking a variety of sustainability criteria
into account (such as water availability, biodiversity protection and soil quality), the third bar shows
currently available estimates of biomass demand for energy from long term scenario studies and the
fourth bar shows the range of projections of total global energy use in 2050.
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In principle, biomass potentials are likely to be sufficient to allow biomass to play a significant
role in the global energy supply system. Current understanding of the potential contribution
of biomass to the future world energy supply is that the total technical biomass supplies
could range from about 100 EJ using only residues up to an ultimate technical potential of
1500 EJ/yr potential per year. The medium range of estimates is between 300 and 800 EJ/yr
(first column of Figure 2).
This study (Dornburg et al., 2008) has confirmed that annual food crops may not be suited
as a prime feedstock for bioenergy, both in size of potentials and in terms of meeting a wide
array of sustainability criteria, even though annual crops can be a good alternative under
certain circumstances. Perennial cropping systems, however, offer very different perspectives.
These cannot only be grown on (surplus) agricultural and pasture lands, but also on more
marginal and degraded lands, be it with lower productivity. At this stage there is still limited
(commercial) experience with such systems for energy production, especially considering the
more marginal and degraded lands and much more development, demonstration (supported
by research) is needed to develop feasible and sustainable systems suited for very different
settings around the globe. This is a prime priority for agricultural policy.
As summarized, the size of the biomass resource potentials and subsequent degree of
utilisation depend on numerous factors. Part of those factors are (largely) beyond policy
control. Examples are population growth and food demand. Factors that can be more
strongly influenced by policy are development and commercialization of key technologies
(e.g. conversion technology that makes production of fuels from lignocellulosic biomass and
perennial cropping systems more competitive), e.g. by means of targeted RD&D strategies.
Other areas are:
• Sustainability criteria, as currently defined by various governments and market
parties.
• Regimes for trade of biomass and biofuels and adoption of sustainability criteria (typically
to be addressed in the international arena, for example via the WTO).
• Infrastructure; investments in infrastructure (agriculture, transport and conversion) is
still an important factor in further deployment of bioenergy.
• Modernization of agriculture; in particular in Europe, the Common Agricultural Policy
and related subsidy instruments allow for targeted developments of both conventional
agriculture and second generation bioenergy production. Such sustainable developments
are however crucial for many developing countries and are a matter for national
governments, international collaboration and various UN bodies.
• Nature conservation; policies and targets for biodiversity protection do determine to what
extent nature reserves are protected and expanded and set standards for management
of other lands.
• Regeneration of degraded lands (and required preconditions), is generally not attractive
for market parties and requires government policies to be realized.
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Current insights provide clear leads for further steps for doing so. In the criteria framework
as defined currently by several governments, in roundtables and by NGO’s, it is highlighted
that a number of important criteria require further research and design of indicators and
verification procedures. This is in particular the case for to the so-called ‘macro-themes’
(land-use change, biodiversity, macro-economic impacts) and some of the more complex
environmental issues (such as water use and soil quality). Sustainability of biofuels and
ongoing development around defining criteria and deployment of certification is discussed
in Chapter 5 of this book by Neves do Amaral.
3. Technological developments in biofuel production
The previous section highlights the importance of lignocellulosic resources for achieving
good environmental performance and reducing the risks of competition for land and with
food production. This implies that different technologies are required to produce liquid
fuels, compared to the currently dominant use of annual crops as maize and rapeseed.
Sugarcane is however a notable exception given it’s very high productivity, low production
costs and good energy and GHG balance (Macedo et al., 2004; Smeets et al., 2008).
Three main routes can be distinguished to produce transportation fuels from biomass:
gasification can be used to produce syngas from lignocellulosic biomass that can be
converted to methanol, Fischer-Tropsch liquids, DiMethylEther (DME) and hydrogen.
Production of ethanol can take place via direct fermentation of sugar and starch rich
biomass, the most utilized route for production of biofuels to date, or this can be preceded
by hydrolysis processes to convert lignocellulosic biomass to sugars first. Finally, biofuels
can be produced via extraction from oil seeds (vegetal oil from e.g. rapeseed or palm oil),
which can be esterified to produce biodiesel.
Other conversion routes and fuels are possible (such as production of butanol from sugar or
starch crops) and production of biogas via fermentation. The above mentioned routes have
however so far received most attention in studies and Research and Demonstration efforts.
3.1. Methanol, hydrogen and hydrocarbons via gasification
Methanol (MeOH), hydrogen (H2) and Fischer Tropsch synthetic hydrocarbons (especially
diesel), DME (DiMethylEther) and SNG (Synthetic Natural Gas) can be produced from
biomass via gasification. All routes need very clean syngas before the secondary energy
carrier is produced via relatively conventional gas processing methods. Here, focus lays on
the first three fuels mentioned.
Several routes involving conventional, commercial, or advanced technologies under
development, are possible. Figure 3 pictures a generic conversion flowsheet for this category
of processes. A train of processes to convert biomass to required gas specifications precedes
164
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the methanol or FT reactor, or hydrogen separation. The gasifier produces syngas, a mixture
of CO and H2, and a few other compounds. The syngas then undergoes a series of chemical
reactions. The equipment downstream of the gasifier for conversion to H2, methanol or
FT diesel is the same as that used to make these products from natural gas, except for
the gas cleaning train. A gas turbine or boiler, and a steam turbine optionally employ the
unconverted gas fractions for electricity co-production (Hamelinck et al., 2004).
So far, commercial biofuels production via gasification does not take place, but interest
is on the rise and development and demonstration efforts are ongoing in several OECD
countries.
Overall energetic efficiencies of relatively ‘conventional’ production facilities, could be close to
60% (on a scale of about 400 MWth input). Deployment on large scale (e.g over 1000 MWth)
is required to benefit maximally from economies of scale, which are inherent to this type
of installations. Such capacities are typical for coal gasification. The use of coal gasifiers and
feeding of pre-treated biomass (e.g. via torrefaction or pyrolysis oils) could prove one of the
shorter term options to produce 2nd generation biofuels efficiently. This conversion route
has a strong position from both efficiency and economic perspective (Hamelinck et al., 2004;
Hamelinck and Faaij, 2002; Tijmensen et al, 2002; Williams et al., 1995). Generic performance
ranges resulting from various pre-engineering studies are reported in Figure 3.
The findings of the previously published papers can be summarised as follows: gasificationbased fuel production systems that apply pressurised gasifiers have higher joint fuel and
electricity energy conversion efficiencies than atmospheric gasifier-based systems. The total
efficiency is also higher for once-through configurations, than for recycling configurations
that aim at maximising fuel output. This effect is strongest for FT production, where (costly)
syngas recycling not only introduces temperature and pressure leaps, but also ‘material leaps’
by reforming part of the product back to syngas. For methanol and hydrogen, however,
Recycle
Biomass
Drying and
chipping
Gasification and
gas cleaning
Reforming, shifting,
CO2 separation
Catalysis,
separation
Methanol
Separation
Hydrogen
Catalysis,
separation
Refining
Gas turbine or boiler
FT diesel
Electricity
Steam turbine
Figure 3. Generic process scheme for production of synthetic biofuels via gasification (Hamelinck
and Faaij, 2006).
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maximised fuel production, with little or no electricity co-production, generally performs
economically somewhat better than once-through concepts.
Hot (dry) gas cleaning generally improves the total efficiency, but the economical effects are
ambivalent, since the investments also increase. Similarly, CO2 removal does increase the
total efficiency (and in the FT reaction also the selectivity), but due to the accompanying
increase in investment costs this does not decrease the product costs. The bulk of the capital
investment is in the gasification and oxygen production system, syngas processing and
power generation units. These parts of the investment especially profit from cost reductions
at larger scales. Also, combinations with enriched air gasification (eliminating the expensive
oxygen production assumed for some methanol and hydrogen concepts) may reduce costs
further.
Several technologies considered here are not yet fully proven or commercially available.
Pressurised (oxygen) gasifiers still need further development. At present, only a few
pressurised gasifiers, operating at relatively small scale, have proved to be reliable.
Consequently, the reliability of cost data for large-scale gasifiers is uncertain. A very critical
step in all thermal systems is gas cleaning. It still has to be proven whether the (hot) gas
cleaning section is able to meet the strict cleaning requirements for reforming, shift and
synthesis. Liquid phase reactors (methanol and FT) are likely to have better economies of
scale. The development of ceramic membrane technology is crucial to reach the projected
hydrogen cost level. For FT diesel production, high CO conversion, either once through
or after recycle of unconverted gas, and high C5+ selectivity are important for high overall
energy efficiencies. Several units may be realised with higher efficiencies than considered
in this paper: new catalysts and carrier liquids could improve liquid phase methanol single
pass efficiency. At larger scales, conversion and power systems (especially the combined
cycle) have higher efficiencies, further stressing the importance of achieving economies of
scale for such concepts.
3.2. Production of ethanol from sugarcane
Ethanol production from sugarcane has established a strong position in Brazil and increasingly
in other countries in tropical regions (such as India, China and various countries in SubSaharan Africa). Production costs of ethanol in Brazil have steadily declined over the past
few decades and have reached a point where ethanol is competitive with production costs of
gasoline (Wall-Bake et al., 2008). As a result, bioethanol is no longer financially supported
in Brazil and competes openly with gasoline.
Large scale production facilities, better use of bagasse and trash residues from sugarcane
production e.g. with advanced (gasification based) power generation or hydrolysis techniques
(see below) and further improvements in cropping systems, offer further perspectives for
sugarcane based ethanol production.
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Improvement options for sugarcane based ethanol production are plentiful (Damen, 2001;
Groen, 1999). It is expected that the historic cost decreases and productivity increments
will continue. An analysis of historic and potential future improvements in economic
performance of ethanol production in Brazil (Wall Bake et al., 2008) concludes that if
improvements in sugarcane yield, logistics (e.g. green can harvesting techniques and
utilisation of sugarcane trash), overall efficiency improvement in the sugar mills and ethanol
production (e.g. by full electrification and advanced distillation technology) as well as the
use of hydrolysis technology for conversion of bagasse and trash to ethanol, ethanol yields
per hectare of land may even be tripled compared to current average production.
The key limitations for sugarcane production are climatic and the required availability of
good quality soils with sufficient and the right rainfall patterns.
3.3. Ethanol from (ligno)-cellulosic biomass
Hydrolysis of cellulosic (e.g. straw) and lignocellulosic (woody) biomass can open the way
towards low cost and efficient production of ethanol from these abundant types of biomass.
The conversion is more difficult than for sugar and starch because from lignocellulosic
materials, first sugars need to be produced via hydrolysis. Lignocellulosic biomass requires
pretreatment by mechanical and physical actions (e.g. steam) to clean and size the biomass,
and destroy its cell structure to make it more accessible to further chemical or biological
treatment. Also, the lignin part of the biomass is removed, and the hemicellulose is hydrolysed
(saccharified) to monomeric and oligomeric sugars. The cellulose can then be hydrolysed to
glucose. Also C5 sugars are formed, which require different yeasts to be converted to ethanol.
The sugars are fermented to ethanol, which is to be purified and dehydrated. Two pathways
are possible towards future processes: a continuing consolidation of hydrolysis-fermentation
reactions in fewer reactor vessels and with fewer micro organisms, or an optimisation of
separate reactions. As only the cellulose and hemicellulose can be used in the process, the
lignin is used for power production (Figure 4).
Enzyme growth
Biomass
Chipping
Hemicellulose
hydrolysis
Cellulose
hydrolysis
Fermentation
Distillation
Gas turbine or boiler
Ethanol
Electricity
Steam turbine
Figure 4. Generic process scheme for the production of ethanol from lignocellulosic biomass.
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To date, acid treatment is an available process, which is so far relatively expensive and
inefficient. Enzymatic treatment is commercially unproven but various test facilities have
been built in North America and Sweden. The development of various hydrolysis techniques
has gained major attention over the past 10 years or so, particularly in Sweden and the
United States. Because breakthroughs seem to be necessary on a rather fundamental level,
it is relatively uncertain how fast attractive performance levels can be achieved (Hamelinck
et al., 2005).
Assuming, however, that mentioned issues are resolved and ethanol production is combined
with efficient electricity production from unconverted wood fractions (lignine in particular),
ethanol costs could come close to current gasoline prices (Lynd et al., 2005): as low as 12
Euroct/litre assuming biomass costs of about 2 Euro/GJ. Overall system efficiencies (fuel +
power output) could go up to about 70% (LHV).
It should be noted though that the assumed conversion extent of (hemi)cellulose to ethanol
by hydrolysis fermentation is close to the stoichiometric maximum. There is only little
residual material (mainly lignin), while the steam demand for the chosen concepts is high.
This makes the application of BIG/CC unattractive at 400MWHHV. Developments of pretreatment methods and the gradual ongoing reactor integration are independent trends and
it is plausible that at least some of the improved performance will be realised in the mediumterm. The projected long-term performance depends on development of technologies that
have not yet passed laboratory stage, and that may be commercially available earlier or
later than 20 years from now. This would mean either a more attractive ethanol product
cost in the medium-term, or a less attractive cost in the long-term. The investment costs
for advanced hemicellulose hydrolysis methods is still uncertain. Continuing development
of new micro-organisms is required to ensure fermentation of xylose and arabinose, and
decrease the cellulase enzyme costs.
The hydrolysis technology can also boost the competitiveness of existing production facilities
(e.g. by converting available crop and process residues), which provides an important market
niche on short term.
Table 1. gives an overview of estimates for costs of various fuels that can be produced from
biomass (Faaij, 2006). A distinction is made between performance levels on the short and
on the longer term. Generally spoken, the economy of ‘traditional’ fuels like Rapeseed
MethylEsther and ethanol from starch and sugar crops in moderate climate zones is poor
at present and unlikely to reach competitive price levels in the longer term. Also, the
environmental impacts of growing annual crops are not as good as perennials because per
unit of product considerable higher inputs of fertilizers and agrochemicals are needed. In
addition, annual crops on average need better quality land than perennials to achieve good
productivities.
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Production of methanol (and DME), hydrogen, Fischer-Tropsch liquids and ethanol produced
from lignocellulosic biomass that offer good perspectives and competitive fuel prices in
the longer term (e.g. around 2020). Partly, this is because of the inherent lower feedstock
prices and versatility of producing lignocellulosic biomass under varying circumstances.
Section 2 highlighted that a combination of biomass residues and perennial cropping
systems on both marginal and better quality lands could supply a few hundred EJ by midcentury in a competitive cost range between 1-2 Euro/GJ (see also Hoogwijk et al., 2005,
2008). Furthermore, as discussed in this paper, the (advanced) gasification and hydrolysis
technologies under development have the inherent improvement potential for efficient and
competitive production of fuels (sometimes combined with co-production of electricity).
Inherent to the advanced conversion concepts, it is relatively easy to capture (and subsequently
store) a significant part of the CO2 produced during conversion at relatively low additional
costs. This is possible for ethanol production (where partially pure CO2 is produced) and
for gasification concepts. Production of syngas (both for power generation and for fuels)
in general allows for CO2 removal prior to further conversion. For FT production about
half of the carbon in the original feedstock (coal, biomass) can be captured prior to the
conversion of syngas to FT-fuels. This possibility allows for carbon neutral fuel production
when mixtures of fossil fuels and biomass are used and negative emissions when biomass
is the dominant or sole feedstock. Flexible new conversion capacity will allow for multiple
feedstock and multiple output facilities, which can simultaneously achieve low, zero or
even negative carbon emissions. Such flexibility may prove to be essential in a complex
transition phase of shifting from large scale fossil fuel use to a major share of renewables
and in particular biomass.
At the moment major efforts are ongoing to demonstrate various technology concepts
discussed above. Especially in the US (but also in Europe), a number of large demonstration
efforts is ongoing on production of ethanol from lignocellulosic biomass. IOGEN, a
Canadian company working on enzymatic hydrolysis reported the production of 100,000
litres of ethanol from agricultural residues in September 2008. Also companies in India,
China and Japan are investing substantially in this technology area.
Gasification for production of synfuels gets support in the US and more heavily in the EU.
The development trajectory of the German company CHOREN (focusing on dedicated
biomass gasification systems for production of FT liquids) is ongoing and stands in the
international spotlights. Finland and Sweden have substantial development efforts ongoing,
partly aiming for integration gasification technology for synfuels in the paper & pulp
industry. Furthermore, co-gasification of biomass in (existing) coal gasifiers is an important
possibility. This has for example been demonstrated in the Buggenum coal gasifiier in the
Netherlands and currently production of synfuels is targeted.
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Table 1. Performance levels for different biofuels production routes (Faaij, 2006).
Concept
Hydrogen: via biomass gasification and
subsequent syngas processing. Combined fuel
and power production possible; for production
of liquid hydrogen additional electricity use
should be taken into account.
Methanol: via biomass gasification and
subsequent syngas processing. Combined fuel
and power production possible
Fischer-Tropsch liquids: via biomass gasification
and subsequent syngas processing. Combined
fuel and power production possible
Ethanol from wood: production takes place
via hydrolysis techniques and subsequent
fermentation and includes integrated electricity
production of unprocessed components.
Ethanol from beet sugar: production via
fermentation; some additional energy inputs
are needed for distillation.
Ethanol from sugarcane: production via
cane crushing and fermentation and power
generation from the bagasse. Mill size,
advanced power generation and optimised
energy efficiency and distillation can reduce
costs further on longer term.
Biodiesel RME: takes places via extraction
(pressing) and subsequent esterification.
Methanol is an energy input. For the total
system it is assumed that surpluses of straw
are used for power production.
Energy efficiency (HHV) + energy inputs
Short term
Long term
60% (fuel only)
(+ 0.19 GJe/GJ H2 for
liquid hydrogen)
55% (fuel)
6% (power)
(+ 0.19 GJe/GJ H2 for
liquid hydrogen)
55% (fuel only)
48% (fuel)
12% (power)
45% (fuel only)
45% (fuel)
10% (power
46% (fuel)
4% (power)
53% (fuel)
8% (power)
43% (fuel only)
43% (fuel only)
0.065 GJe + 0.24 GJth/ 0.035 GJe + 0.18 GJth/GJ
GJ EtOH
EtOH
85 litre EtOH per tonne of 95 litre EtOH per tonne
wet cane,
of wet cane. Electricity
generally energy neutral surpluses depend on
with respect
plant lay-out and power
to power and heat
generation technology.
88%; 0.01 GJe + 0.04 GJ MeOH per GJ output
Efficiency power generation on shorter term: 45%, on
longer term: 55%
Assumed biomass price of clean wood: 2 Euro/GJ. RME cost figures varied from 20 Euro/GJ (short term) to 12
Euro/GJ (longer term), for sugar beet a range of 12 to 8 Euro/GJ is assumed. All figures exclude distribution of
the fuels to fueling stations.
For equipment costs, an interest rate of 10%, economic lifetime of 15 years is assumed. Capacities of conversion
unit are normalized on 400 MWth input on shorter term and 1000 MWth input on longer term.
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Investment costs
(Euro/kWth input capacity)
Short term
O&M
(% of inv.)
Long term
480 (+ 48 for liquefying) 360 (+ 33 for liquefying)
Estimated production costs
(Euro/GJ fuel)
Shorter term Longer term
4
9-12
4-8
690
530
4
10-15
6-8
720
540
4
12-17
7-9
350
180
6
12-17
5-7
290
170
5
25-35
20-30
100 (wide range applied 230 (higher costs due
depending on scale and to more advanced
technology applied)
equipment)
2
8-12
7-8
150 (+ 450 for power
generation from straw)
5
4
25-40
20-30
Sugarcane ethanol
110 (+ 250 for power
generation from straw)
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Industrial interest in those areas comes from the energy sector, biotechnology as well
as chemical industry. Given the policy targets on (second generation) biofuels in North
America and the EU, high oil prices and increased pressure to secure sustainable production
of biofuels (e.g. avoiding conflicts with food production and achieve high reduction in GHG
emissions), pressure on both the market and policy to commercialize those technologies is
high. When turn-key processes are available is still uncertain, but such breakthroughs may
be possible already around 2010.
4. Energy and greenhouse gas balances of biofuels
4.1. Energy yields
The energy yield per unit of land surfaces resources depends to a large extent on the crop
choice and the efficiency of the entire energy conversion route from ‘crop to drop’. This
is illustrated by the figures in Table 2. It is important to stress that when lignocellulose is
the feedstock of choice production is not constrained to arable land, but amounts to the
sum of residues and production from degraded/marginal lands not used for current food
production. Ultimately, this will be the preferred option in most cases.
Table 2. Indicative ranges for biomass yield and subsequent fuel production per hectare per year
for different cropping systems in different settings. Starch and sugar crops assume conversion via
fermentation to ethanol and oil crops to biodiesel via esterification (commercial technology at present).
The woody and grass crops require either hydrolysis technology followed by ethanol or gasification to
syngas to produce synthetic fuel (both not yet commercial conversion routes).
Crop
Biomass yield
(odt/ha/yr)
Energy yield in fuel
(GJ/ha/yr)
Wheat
Maize
Sugar beet
Soy bean
Sugarcane
Palm oil
Jathropha
4-5
5-6
9-10
1-2
5-20
10-15
5-6
~50
~60
~110
~20
~180
~160
~60
SRC temperate climate
SRC tropical climate
Energy grasses good conditions
Perennials marginal/degraded lands
10-15
15-30
10-20
3-10
100-180
170-350
170-230
30-120
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4.2. Greenhouse gas balances
The net emissions over the full life cycle of biofuels – from changes in land use to combustion
of fuels – that determine their impact on the climate. Research on net emissions is far
from conclusive, and estimates vary widely. Calculations of net GHG emissions are highly
sensitive to assumptions about system boundaries and key parameter values – for example,
land use changes and their impacts, which inputs are included, such as energy embedded
in agricultural machinery and how various factors are weighted.
The primary reasons for differing results are different assumptions made about cultivation,
and conversion or valuation of co-products. (Larson, 2005), who reviewed multiple studies,
found that the greatest variations in results arose from the allocation method chosen for
co-products, and assumptions about N2O emissions and soil carbon dynamics. In addition,
GHG savings will vary from place to place – according to existing incentives for GHG
reductions, for example. And the advantages of a few biofuels (e.g. sugarcane ethanol in
Brazil) are location specific. As a result, it is difficult to compare across studies; however,
despite these challenges, some of the more important studies point to several useful
conclusions.
This analysis notwithstanding, the vast majority of studies have found that, even when all
fossil fuel inputs throughout the life cycle are accounted for, producing and using biofuels
made from current feedstock result in substantial reductions in GHG emissions relative to
petroleum fuels.
In general, of all potential feedstock options, producing ethanol from maize results in
the smallest decrease in overall emissions. The greatest benefit, meanwhile, comes from
ethanol produced from sugarcane grown in Brazil (or from using cellulose or wood waste
as feedstock). Several studies have assessed the net emissions reductions resulting from
sugarcane ethanol in Brazil, and all have concluded that the benefits far exceed those from
grain-based ethanol produced in Europe and the United States.
Fulton (2004) attributes the lower life-cycle climate impacts of Brazilian sugarcane ethanol
to two major factors: First, cane yields are high and require relatively low inputs of fertilizer,
since Brazil has better solar resources and high soil productivity. Second, almost all
conversion plants use bagasse (the residue that remains after pressing the sugar juice from
the cane stalk) for energy, and many recent plants use co-generation (heat and electricity),
enabling them to feed electricity into the grid. As such, net fossil energy requirements are
near zero, and in some cases could be below zero. (In addition, less energy is required for
processing because there is no need for the extra step to break down starch into simple
sugars. Because most process energy in Brazil is already renewable, this does not really
play a role.)
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According to Larson (2005), conventional grain- and oilseed-based biofuels can offer only
modest reductions in GHG emissions. The primary reason for this is that they represent
only a small portion of the above ground biomass. He estimates that, very broadly, biofuels
from grains or seeds have the potential for a 20–30 percent reduction in GHG emissions
per vehicle-kilometer, sugar beets can achieve reductions of 40–50 percent, and sugarcane
(average in southeast Brazil) can achieve a reduction of 90 percent.
Other new technologies under development also offer the potential to dramatically increase
yields per unit of land and fossil input, and further reduce life-cycle emissions. The cellulosic
conversion processes for ethanol offers the greatest potential for reductions because feedstock
can come from the waste of other products or from energy crops, and the remaining parts
of the plant can be used for process energy.
Larson (2005) projects that future advanced cellulosic processes (to ethanol, F-T diesel, or
DME) from perennial crops could bring reductions of 80–90 percent and higher. According
to Fulton et al. (2004), net GHG emissions reductions can even exceed 100 percent if the
feedstock takes up more CO2 while it is growing than the CO2-equivalent emissions released
during its full life cycle (for example, if some of it is used as process energy to offset coalfired power).
Typical estimates for reductions from cellulosic ethanol (most of which comes from
engineering studies, as few large-scale production facilities exist to date) range from 70–90
percent relative to conventional gasoline, according to Fulton (2004), though the full range
of estimates is far broader.
Figure 5 shows the range of estimated possible reductions in emissions from wastes and
other next-generation feedstock relative to those from current-generation feedstock and
technologies.
4.3. Chain efficiency of biofuels
When the use of such ‘advanced’ biofuels (especially hydrogen and methanol) in advanced
hybrid or Fuel Cell Vehicles (FCV’s) is considered, the overall chain (‘tree - to – tyre’)
efficiency can drastically improve compared to current bio-diesel or maize or cereal derived
ethanol powered Internal Combustion Engine Vehicles; the effective number of kilometres
that can be driven per hectare of energy crops could go up with a factor of 5 (from a
typical current 20,000 km/ha for a middle class vehicle run with RME up to over 100,000
km/ha for advanced ethanol in an advanced hybrid or FCV (Hamelinck and Faaij, 2002)).
Note though, that the current exception to this performance is sugarcane based ethanol
production; in Brazil the better plantations yield some 8,000 litre ethanol/ha*yr, or some
70,000 km/yr for a middle class vehicle at present. In the future, those figures can improve
174
Sugarcane ethanol
Reduction in CO2 equivalent emissions
(percent)
Biofuel conversion technologies
0
Wastes
Fibers
(waste oil,
harvest residues, (switchgrass,
poplar)
sewage)
Sugars
(sugar cane,
beet)
Starches
(corn,
wheat)
Vegetable oils
(rapeseed,
sunflower seed,
soybeans)
20
40
60
80
100
120
Figure 5. Reductions in greenhouse gas emissions per vehicle-kilometre, by feedstock and associated
refining technology (taken from Fulton, 2004).
further due to better cane varieties, crop management and efficiency improvement in the
ethanol production facilities (Damen, 2001).
Furthermore, FCV’s (and to a somewhat lesser extent advanced hybrids) offer the additional
and important benefits of zero or near zero emission of compounds like NOx, CO, sulphur
dioxide, hydrocarbons and small dust particulates, which are to a large extent responsible for
poor air quality in many urban zones in the world. Table 3 provides a quantification of the
range of kilometres that can be driven with different biofuel-vehicle combinations expressed
per hectare. The ranges are caused by different yield levels for different land-types and
variability and uncertainties in conversion and vehicle efficiencies. However, overall, there
are profound differences between first and second generation biofuels I favour of the latter.
4.4. Future expectations on biofuels
The future biofuels and specifically the bioethanol market is uncertain. There are fundamental
drivers (climate, oil prices and availability, rural development) that push for further
development of biofuels. On the one hand, recent developments and public debate point
towards conflicts with land use, food markets, poor GHG performance (especially when
indirect land-use changes are assumed caused by biofuel production) and, even with high
oil prices, high levels of subsidy for biofuels in e.g. Europe and the United States. Recently,
policy targets (as discussed in chapter 5 of this book) set for biofuels are rediscussed in
the EU, as well as in China. In most key markets (EU, US, China), the role of biofuels is
increasingly connected to rapid deployment of 2nd generation technologies. The bulk of the
growth beyond 2015 or so should be realized via such routes.
Sugarcane ethanol
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Chapter 7
Table 3. Distance that can be driven per hectare of feedstock for several combinations of fuels and
engines, derived from the net energy yield and vehicle efficiency as reported in (Hamelinck and Faaij,
2006). ICEV = Internal Combustion Engine Vehicle, FCV = Fuel Cell Vehicle.
Feedstock
Lignocellulose
Fuel
Hydrogen
Methanol
FT
Ethanol
Sugar beet
Ethanol
Rapeseed
RME
Engine
ICEV
FCV
ICEV
FCV
ICEV
FCV
ICEV
FCV
ICEV
FCV
ICEV
FCV
Distance (thousands km/ha)
Short term
Long term
26-37
44-140
34-49
68-83
22-38
50-67
29-30
38-72
15-37
19-93
5-28
6-84
80-97
189-321
75-287
113-252
56-167
97-211
82-238
129-240
57-88
58-138
15-79
19-137
Some projections as published by the International Energy Agency (World Energy Outlook)
and the OECD (Agricultural Outlook) focus on first generation biofuels only (even for
projections to 2030 in the IEA-WEO). Biofuels meet 2.7% of world road-transport fuel
demand by the end of the projection period in the Reference Scenario, up from 1% today. In
the Alternative Scenario, the share reaches 4.6%, thanks to higher demand for biofuels but
lower demand for road-transport fuels in total. The share remains highest in Brazil, though
the pace of market penetration will be fastest in the European Union in both scenarios.
The contribution of liquid biofuels to transport energy, and even more so to global energy
supply, will remain limited. By 2030, liquid biofuels are projected to still supply only 3.0-3.5
percent of global transport energy demand. This is however also due to the key assumption
that 2nd generation biofuel technology is not expected to become available to the market
(IEA, 2006).
In the Agricultural Outlook, similar reasoning is followed be it for a shorter time frame (up
to the year 2016), focusing on 1st generation biofuels. The outlook focuses in this respect on
the implications of biofuel production on demand for food crops. In general, a slowdown
in growth is expected (OECD, 2007).
Projections that take explicitly 2nd generation options into account are more rare, but studies
that do so, come to rather different outlooks, especially in the timeframe exceeding 2020.
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Biofuel conversion technologies
The IPCC, providing an assessment of studies that deal with both supply and demand of
biomass and bioenergy. It is highlighted that biomass demand could lay between 70 – 130 EJ
in total, subdivided between 28-43 EJ biomass input for electricity and 45-85 EJ for biofuels
(Barker and Bashmakov, 2007; Kahn Ribeiro et al., 2007). Heat and biomass demand for
industry are excluded in these reviews. It should also be noted that around that timeframe
biomass use for electricity has become a less attractive mitigation option due to the increased
competitiveness of other renewables (e.g. wind energy) and e.g. [ and storage. At the same
time, carbon intensity of conventional fossil transport fuels increases due to the increased
use lower quality oils, tar sands and coal gasification.
In De Vries et al. (2007; based on the analyses of Hoogwijk et al. (2005, 2008)), it is indicated
that the biofuel production potential around 2050 could lay between about 70 and 300 EJ fuel
production capacity depending strongly on the development scenario. Around that time,
biofuel production costs would largely fall in the range up to 15 U$/GJ, competitive with
equivalent oil prices around 50-60 U$/barrel. This is confirmed by other by the information
compiled in this chapter: it was concluded that the, sustainable, biomass resource base,
without conflicting with food supplies, nature preservation and water use, could indeed be
developed to a level of over 300 EJ in the first half of this century.
5. Final remarks
Biomass cannot realistically cover the whole world’s future energy demand. On the other
hand, the versatility of biomass with the diverse portfolio of conversion options, makes
it possible to meet the demand for secondary energy carriers, as well as bio-materials.
Currently, production of heat and electricity still dominate biomass use for energy. The
question is therefore what the most relevant future market for biomass may be.
For avoiding CO2 emissions, replacing coal is at present a very effective way of using
biomass. For example, co-firing biomass in coal-fired power stations has a higher avoided
emission per unit of biomass than when displacing diesel or gasoline with ethanol or
biodiesel. However, replacing natural gas for power generation by biomass, results in levels
of CO2 mitigation similar to second generation biofuels. Net avoided GHG emissions
therefore depend on the reference system and the efficiency of the biomass production
and utilisation chain. In the future, using biomass for transport fuels will gradually become
more attractive from a CO2 mitigation perspective because of the lower GHG emissions
for producing second generation biofuels and because electricity production on average
is expected to become less carbon-intensive due to increased use of wind energy, PV and
other solar-based power generation, carbon capture and storage technology, nuclear energy
and fuel shift from coal to natural gas. In the shorter term however, careful strategies and
policies are needed to avoid brisk allocation of biomass resources away from efficient and
effective utilisation in power and heat production or in other markets, e.g. food. How this
is to be done optimally will differ from country to country.
Sugarcane ethanol
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Chapter 7
First generation biofuels in temperate regions (EU, North America) do not offer a sustainable
possibility in the long term: they remain expensive compared to gasoline and diesel (even at
high oil prices), are often inefficient in terms of net energy and GHG gains and have a less
desirable environmental impact. Furthermore, they can only be produced on higher quality
farmland in direct competition with food production. Sugarcane based ethanol production
and to a certain extent palm oil and Jatropha oilseeds are notable exceptions to this given
their high production efficiencies and low(er) costs.
Especially promising are the production via advanced conversion concepts biomass-derived
fuels such as methanol, hydrogen, and ethanol from lignocellulosic biomass. Ethanol
produced from sugarcane is already a competitive biofuel in tropical regions and further
improvements are possible. Both hydrolysis-based ethanol production and production
of synfuels via advanced gasification from biomass of around 2 Euro/GJ can deliver high
quality fuels at a competitive price with oil down to US$55/ barrel. Net energy yields for
unit of land surface are high and up to a 90% reduction in GHG emissions can be achieved.
This requires a development and commercialization pathway of 10-20 years, depending very
much on targeted and stable policy support and frameworks.
However, commercial deployment of these technologies does not have to be postponed for
such time periods. The two key technological concepts that have shorter term opportunities
(that could be seen as niches) for commercialization are:
1. Ethanol: 2nd generation can build on the 1st generation infrastructure by being built as
‘add-ons’ to existing factories for utilisation of crop residues. One of the best examples
is the use of bagasse and trash at sugar mills that could strongly increase the ethanol
output from sugarcane
2. Synfuels via gasification of biomass: can be combined with coal gasification as currently
deployed for producing synfuels (such as DME, Fischer-Tropsch and Methanol) to obtain
economies of scale and fuel flexibility. Carbon capture and storage can easily be deployed
with minimal additional costs and energy penalties as an add-on technology.
The biomass resource base can become large enough to supply 1/3 of the total world’s
energy needs during this century. Although the actual role of bioenergy will depend on its
competitiveness with fossil fuels and on agricultural policies worldwide, it seems realistic
to expect that the current contribution of bioenergy of 40-55 EJ per year will increase
considerably. A range from 200 to 400 EJ may be observed looking well into this century,
making biomass a more important energy supply option than mineral oil today. Considering
lignocellulosic biomass, about half of the supplies could originate from residues and biomass
production from marginal/degrade lands. The other half could be produced on good quality
agricultural and pasture lands without jeopardizing the worlds food supply, forests and
biodiversity. The key pre-condition to achieve this goal is increased agricultural land-use
efficiency, including livestock production, especially in developing regions. Improvement
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Sugarcane ethanol
Biofuel conversion technologies
potentials of agriculture and livestock are substantial, but exploiting such potentials is a
challenge.
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P.R. Bosch, R. Dave and L.A. Meyer (eds.), Climate Change 2007: Mitigation contribution of Working
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Fulton, L., 2004. International Energy Agency, Biofuels for transport – an international perspective, Office
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Hamelinck, C.N. and A.P.C. Faaij, 2002. Future prospects for production of methanol and hydrogen from
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Hamelinck, C.N., G van Hooijdonk and A.P.C. Faaij, 2005. Future prospects for the production of ethanol
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Hoogwijk, M., A. Faaij, B. de Vries and W. Turkenburg, 2008. Global potential of biomass for energy from
energy crops under four GHG emission scenarios Part B: the economic potential. Biomass & Bioenergy,
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Plotkin, D. Sperling, R. Wit and P.J. Zhou, 2007: Transport and its infrastructure. In: B. Metz, O.R.
Davidson, P.R. Bosch, R. Dave and L.A. Meyer (eds.), Climate Change 2007: Mitigation contribution of
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for Sustainable Development 11: October 2005.
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Biomass: An Update. Current Opinion in Biotechnology 16: 577-583.
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Chapter 8
The global impacts of US and EU biofuels policies
Wallace E. Tyner
1. Introduction
The major biofuels producers in the world are the US, EU, and Brazil. Figure 1 shows the
global breakdown of biofuels production for 2006. The US and Brazil combine to produce
three-fourths of global ethanol, and the EU produces three-fourths of global biodiesel. The
US overtook Brazil in ethanol production, and global production now exceeds 50 billion
liters. Biodiesel total production is much smaller.
In the US, Brazil, and the EU, the biofuels industries were launched with some combination
of subsidies and mandates plus border protection. As production levels have grown and as oil
prices have risen, all three are now switching in different degrees from reliance on subsidies
to reliance on mandates. One reason is the government budget cost of subsidies, which
increase as production increases. Mandates also have a cost, but it is paid by consumers
at the pump assuming the biofuel is more expensive to produce than the petroleum based
fuel it replaces. The consumer cost of a mandate is directly related to oil price. At low oil
prices, a mandate can be expensive for consumers because high cost renewable fuel is
mandated in lieu of a certain fraction of relatively lower cost petroleum. At high oil prices,
the renewable fuel may even be less expensive than petroleum based fuels, so the cost can
be much lower or zero.
Ethanol
EU
3%
India
4%
Biodiesel
others
4%
others
11%
USA
37%
USA
20%
China
8%
EU
76%
Brazil
37%
World ethanol production: 49.3 billion liters
World biodiesel production: 5.6 billion liters
Figure 1. Global biofuels production, 2006. Data sources: Earth Policy Institute (2006), Renewable
Fuels Association (2007), European Biodiesel Board (2007).
Sugarcane ethanol
181
Chapter 8
In Brazil, subsidies have been completely replaced with mandates. In the EU, subsidies are
determined by each country. In essence, the EU sets a target level of renewable fuels, and
each country decides how best to achieve that target. The original target was 5.75 percent
renewable fuels by 2010. Most countries were well behind the pace needed to achieve that
target. More recently a target of 10 percent by 2020 has been proposed. Given the recent food
price and greenhouse gas controversies (more later), it appears the EU is backing away from
that target. Germany has had relatively high levels of subsidies for biodiesel, but these have
now ended. At present, the future directions for biofuels policies in the EU are uncertain.
In the US, ethanol has been subsidized for 30 years (Tyner, 2008). The subsidy has ranged
from 10.6 to 15.9 cents per liter, and is currently 13.5 cents per liter. The subsidy on maize
ethanol will be reduced to 11.9 cents per liter on 1 January 2009, but a new subsidy of 26.7
cents per liter of cellulosic ethanol will be introduced (US Congress, 2008). In addition
to the subsidy, in December 2007, the US introduced biofuel mandates in the Energy
Independence and Security Act (US Congress, 2007). Figure 2 portrays the timing of the
US mandate, called a Renewable Fuel Standard (RFS). The Renewable Fuel Standard (RFS)
as amended in the 2007 Energy Independence and Security Act calls for 36 billion gallons
of renewable fuels by 2022. The RFS is divided into four categories of biofuels: conventional,
advanced, cellulosic, and biodiesel. The advanced category reaches 21 billion gallons by 2022
and includes cellulosic ethanol, ethanol from sugar, ethanol from waste material, biodiesel,
and other non-maize sources. In other words, the advanced category encompasses both the
cellulosic and biodiesel categories. Cellulosic ethanol as a sub-set of advanced reaches 16
40.00
35.00
Billions of gallons
30.00
25.00
20.00
15.00
10.00
5.00
0.00
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
0.75 1.00 1.50 2.00 2.50 3.00 3.50 3.50 3.50 4.00
1.00 1.75 3.00 4.25 5.50 7.00 8.50 10.5 13.5 16.0
13.8 14.4 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0
0.50 0.65 0.80 1.00
Biomass-based diesel
0.10 0.20 0.30 0.50
Non-celulosic advanced
0.10 0.25 0.50
Celulosic advanced
Conventional biofuels 4.00 4.70 9.00 10.5 12.0 12.6 13.2
Figure 2. US Renewable Fuel Standard (2007-2022). Source: Joel Valasco (pers. comm.).
182
Sugarcane ethanol
The global impacts of US and EU biofuels policies
billion by 2022, and biodiesel reaches 1 billion. The residual, likely to be sugarcane ethanol,
amounts to 4 billion gallons by 2022. The way the standard is written, there is the total RFS
requirement and the advanced requirement (with its sub-components specified separately)
with the difference being presumed to be maize based ethanol. However, there is no specific
RFS for maize ethanol. This residual, labeled conventional biofuels, reaches 15 billion gallons
by 2015 and stays at that level. The residual is the only category that permits maize ethanol.
However, it could also include any of the other categories of biofuels.
Associated with all the biofuel categories is a GHG reduction requirement. For maize
based ethanol, the reduction must be at least 20 percent. For all advanced biofuels except
cellulosic ethanol, the reduction required is 50 percent, and for cellulosic ethanol, it is
60 percent. Ethanol plants that were under construction or in operation as of the data of
enactment of the legislation are exempt from the GHG requirement (grandfathered). The
GHG requirements are to be developed and implemented by EPA. The EPA administrator
has flexibility to modify to some extent the GHG percentages. S/he also has authority to
reduce or waive the RFS levels.
In addition to the subsidy and RFS, the US also has a tariff on imported ethanol (Abbott
et al., 2008). The tariff is 2.5 percent ad valorem plus a specific tariff of 14.3 cents per liter
of ethanol. With an ethanol CIF price of 52.9 cents per liter, the total tariff becomes 15.6
cents per liter. The rationale for the tariff was that the US ethanol subsidy applies to both
domestic and imported ethanol. Congress clearly wanted to subsidize only domestically
produced ethanol, so the tariff was established to offset the domestic subsidy. At the time
the tariff was created, the domestic subsidy was also about 14.3 cents per liter (Tyner, 2008).
However, the domestic subsidy was reduced to 13.5 and has now been reduced further to
11.9 cents per liter. Thus, today, the import tariff, as a trade barrier, goes far beyond the
subsidy offset. The EU and Brazil also have import tariffs on ethanol. For Brazil, it is largely
irrelevant since Brazil is one of the world’s lowest cost producers of ethanol, so it is unlikely
to import ethanol.
2. Ethanol economics and policy
The lowest cost ethanol source is ethanol from sugarcane. It is also the most advantageous
from a net energy perspective. Brazil is the global leader in sugarcane based ethanol
production, and has ample land resources to expand production. The US uses maize to
produce ethanol. The cost of producing ethanol from maize varies with the price of maize.
The value of the ethanol produced is a function of the price of crude oil since ethanol
substitutes for gasoline. Figure 3 provides a breakeven analysis for maize ethanol at varying
prices of crude oil and maize. The top line is the breakeven values with no government
intervention and ethanol valued on an energy basis. The second line includes the 13.5 cent
per liter subsidy. Prior to 2005, maize often ranged between $80 and $90 per mt. Without
a subsidy oil would have had to be over $60 for maize ethanol to be economic. However,
Sugarcane ethanol
183
Chapter 8
140.00
Crude ($/bbl.)
120.00
Energy basis
100.00
80.00
Energy + subsidy
60.00
40.00
20.00
0.00
60
100
180
140
220
260
Corn ($/mt)
Figure 3. Breakeven ethanol prices with and without federal subsidy.
with the federal subsidy, maize ethanol was economic at around $30 crude. In addition to
the federal subsidy, many US states also offered subsidies, so ethanol was attractive in the
two decades prior to 2005 even though oil averaged $20/bbl. During that period It was not
hugely profitable, but enough so to see the industry grow slowly over the entire period.
Today with maize around $240/mt, the breakeven oil price is about $135 with no subsidy
and $105 with a subsidy. The nature of a fixed subsidy is such that regardless of the maize
price, the breakeven oil price difference with and without the subsidy is about $30/bbl. Or
conversely, at $120 oil, the maize breakeven prices with and without subsidy are $270 and
$207 per metric tonne, respectively.
2.1. Impacts of alternative US ethanol policies
This breakeven analysis is from the perspective of a representative firm. We can use a
partial equilibrium economic model to examine the fixed subsidy, a variable subsidy, and
the RFS over a range of oil prices (Tyner and Taheripour, 2008a,b). The model includes,
maize, ethanol, gasoline, crude oil, and distillers dried grains with solubles (DDGS). The
supply side of the maize market consists of identical maize producers. They produce maize
using constant returns to scale Cobb-Douglas production functions and sell their product
in a competitive market. Under these assumptions, we can define an aggregated CobbDouglas production function for the whole market. In the short-run the variable input
of maize producers is a composite input which covers all inputs such as seed, fertilizers,
chemicals, fuel, electricity, and so on. In short run capital and land are fixed. The demand
side of the maize market consists of three users: domestic users who use maize for feed
and food purposes; foreign users, and ethanol producers. We model the domestic and
foreign demands with constant price elasticity functions. The foreign demand for maize is
more elastic than the domestic demand. The demand of the ethanol industry for maize is
a function of the demand for ethanol.
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The global impacts of US and EU biofuels policies
The gasoline market has two groups of producers: gasoline and ethanol producers. It is
assumed that ethanol is a substitute for gasoline with no additive value. The gasoline and
ethanol producers produce according to short run Cobb-Douglas production functions. The
variable input of gasoline producers is crude oil and the variable input of ethanol producers
is maize. Both groups of producers are price takers in product and input markets. We model
the demand side with a constant price elasticity demand. The constant parameter of this
function can change due to changes in income and population. We assume that the gasoline
industry is well established and operates at long run equilibrium, but the ethanol industry
is expanding. The new ethanol producers opt in when there are profits. There is assumed to
be no physical or technical limit on ethanol production – only economic limits.
The model is calibrated to 2006 data and then solved for several scenarios. Elasticities are
taken from the existing literature. Endogenous variables are gasoline supply, demand, and
price: ethanol supply, demand, and price; maize price and production; maize use for ethanol,
domestic use, and exports; DDGS supply and price; land used for maize; and the price of
the composite input for maize. Exogenous variables include crude oil price, maize yield,
ethanol conversion rate, ethanol subsidy level and policy mechanism, and gasoline demand
shock (due to non-price variables such as population and income). The model is driven and
solved by market clearing conditions that maize supply equal the sum of maize demands
and that ethanol production expands to the point of zero profit. The model is simulated
over a range of oil prices between $40 and $140.
Figure 4 provides the results from this model simulation for maize price and Figure 5 for
ethanol production. In each figure, the far left bar is the 13.5 cent fixed subsidy, the second
is no subsidy, the third a subsidy that varies with the price of crude oil, the fourth the RFS
alone, and the fifth the RFS in combination with the fixed subsidy (current policy). The
variable subsidy is in effect only for crude oil prices below $70. The first thing to note from
Figure 4 is that, just as was evident from the perspective of the firm, there is now a tight
linkage between crude oil price and maize price. The basic mechanism is that gasoline price
is driven by crude price. Ethanol is a close substitute for gasoline, so a higher gasoline price
means larger ethanol demand. That demand stimulates investment in ethanol plants. More
ethanol plants means greater demand for maize, and that increased demand means higher
maize price. This is a huge change, as historically, there was very little correlation between
energy and agricultural prices.
The $40 oil price represents the approximate price in 2004. The model accurately ‘predicts’
the ethanol production and maize price corresponding to $40 oil. That is, the 2004 model
results are very close to the actual 2004 values. The ethanol production under no subsidy
also accurately shows ethanol production beginning only when oil reaches $60 and then at a
very low level. Of course, the RFS case has the ethanol production level at 56.7 bil. l., which
is the level of the RFS in 2015, and the level modeled in this analysis. The numbers above
the RFS bar in Figure 5 represent the implicit subsidy on ethanol ($/gal. ethanol) due to the
Sugarcane ethanol
185
Chapter 8
300.00
fixed sub no sub var sub RFS
RFS+sub
250.00
$/mt.
200.00
150.00
100.00
50.00
0.00
40
60
80
100
120
140
Oil price
Figure 4. Maize price under alternative policies and oil prices.
fixed sub
no sub
var sub
RFS
RFS+sub
80.0
0.07
70.0
0.00
0.29
60.0
1.06
0.83
0.55
40
60
80
Bil.l./yr
50.0
40.0
30.0
20.0
10.0
0.0
100
120
140
Oil price
Figure 5. Ethanol production under alternative policies and oil prices.
RFS. It is also an implicit tax on consumers. The model follows the RFS rule, and ‘requires’
that the stipulated level of ethanol be produced. To the extent that the cost of ethanol is
higher than the cost of gasoline, this higher cost gets passed on to consumers in the form
of an implicit tax on consumers. Thus, a RFS functions very differently from a subsidy.
The subsidy is on the government budget, whereas the mandate cost is paid by consumers
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The global impacts of US and EU biofuels policies
directly at the pump. When oil is very inexpensive, the ethanol costs considerably more than
petroleum. So the requirement to blend ethanol means consumers pay more at the pump
than they would without the mandate. For $40 oil, the implicit subsidy/tax is $1.06/gal. or
28 cents per liter. The subsidy/tax falls to zero at $140 oil. At $140 oil, the mandate is no
longer binding, and the amount of ethanol demanded is market driven – not determined
by the mandate. Thus the RFS is a form of variable subsidy for the ethanol producer and
variable tax for the consumer depending on the price of crude oil. Ethanol production stays
at the RFS level of 56.7 bil. l. until oil reaches $120. At that oil price and beyond the market
demands more than 56.7 bil. l., and the RFS becomes non-binding.
The final bar is the current policy of RFS plus subsidy. Note that at low oil prices, the RFS
production level is higher than that induced by the subsidy, and at high oil prices, the subsidy
induces higher production than the RFS. If the RFS represents the intent of Congress with
respect to level of ethanol production, the subsidy takes production well beyond that level
at high oil prices.
Another important question that can be addressed using these model results is what
proportion of the maize price increase is due to the oil price increase, and what proportion
to the subsidy. If we start at the no subsidy case with $40 oil, we have a maize price of $67,
which increases to $181 when oil triples to $120. If we add on the subsidy at $120 oil, the
maize price goes up to $222. The total maize price increase is $155, of which $41 is due to
the subsidy, and $113 to the oil price increase. So roughly ¾ of the maize price increase
has been due to higher oil prices, and ¼ to the US subsidy on maize ethanol. Even if the
subsidy went away, maize prices would not return to their historic levels because of the
new link between energy and agriculture. And if oil price went down, we would expect to
see the maize price fall as well. As the oil price fell, gasoline would fall as would the price
of ethanol. With lower ethanol prices, some plants could not produce profitably, so maize
demand would fall and also the maize price.
Figure 6 displays the annual costs of the various policy options. Recall that the method of
paying the costs is very different between the government subsidy and the RFS. The RFS is
paid by the consumer at the pump, and the fixed and variable subsidies are paid through
the government budget. The variable subsidy has no cost for oil above $70 by design, and
its cost at low oil prices is quite low. The cost of the fixed subsidy increases almost linearly
with oil price. The higher the oil price, the higher the government subsidy cost. The RFS
is exactly opposite. It has a high cost when oil price is low, and a very low or zero cost at
high oil prices.
The US tariff on imported ethanol introduces a potentially greater distortion than does the
subsidy or mandate. Since high oil prices directly lead to higher maize prices, maize ethanol
becomes much more expensive. Sugarcane-based ethanol is less expensive to produce
than maize ethanol at any oil price, but the gap widens at higher oil prices. So removal
Sugarcane ethanol
187
Chapter 8
18.0
fixed sub no sub
var sub RFS
RFS+sub
16.0
14.0
Bil.$/yr
12.0
10.0
8.0
6.0
4.0
2.0
0.0
40
60
80
100
120
140
Oil price
Figure 6. Costs of the policy alternatives.
of the tariff on imported ethanol would lead to the biofuel coming from the lowest cost
source–sugarcane–which would reduce some pressure on maize prices and provide the
United States with lower cost ethanol. Brazil has the potential to expand ethanol production
substantially without increasing world sugar prices substantially, so imports down the road
could be quite high.
However, the question is more complicated because it depends on the extent to which
imported ethanol adds to total consumption and the extent to which it displaces maize
ethanol. For the portion that displaced maize ethanol, each billion gallons of imports would
displace about 358 million bushels of maize used for ethanol (Tyner and Taheripour, 2007).
So you would get price impacts as the ethanol industry demanded less maize. The problem
is figuring out how much would go to increase total consumption and how much to displace
maize ethanol. In the United States, the limit of how much ethanol can be blended is called
the blending wall (Tyner et al., 2008). The blending wall is the maximum amount of ethanol
that can be blended at the regulatory maximum of 10%. Currently, we consume about 140
billion gallons of gasoline (Energy Information Administration, 2008), so the max level for
the blending wall would be 14 billion gallons of ethanol. However, for logistical reasons,
the practical level is likely to be much lower, perhaps around 12 billion gallons. See Tyner
et al. (2008) for a more complete analysis of this issue.
We already have in place or under construction 13 billion gallons of ethanol capacity. At
present E85 is tiny, and it would take quite a while to build that market. There are only about
1,700 E85 pumps in the nation and few flex-fuel vehicles that are required to consume the
fuel. It would require a massive investment to make E85 pumps readily available for all
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The global impacts of US and EU biofuels policies
consumers, and a huge switch to flex-fuel vehicle manufacture and sale to grow this market.
Without strong government intervention, it will not happen.
What options exist? The most popular among the ethanol industry is switching to E15 or
E20 instead of E10. The major problem is that automobile manufacturers believe the existing
fleet is not suitable for anything over E10. Switching to a higher blend would void warranties
on the existing fleet and potentially pose problems for older vehicles not under warranty.
In the US, the automobile fleet turns over in about 14 years, so it is a long term process. We
could not add yet another pump for E15 or E20. The costs would be huge. So the blending
wall in the near term is an effective barrier to growth of the ethanol industry. If a switch is
made to an E15 or E20 limit for standard cars, some agreement would have to be reached
on who pays for any vehicle repair or performance issues.
On the technical side, two options could emerge. One would be using cellulose through a
thermochemical conversion process to produce gasoline or diesel fuel directly. Today this
process is quite expensive, but the cost might be reduced over the next few years. A second
option is to convert cellulose to butanol instead of ethanol, which is much more similar to
gasoline. Without such a breakthrough, the EPA administrator likely will be forced to cap
the RFS far below the planned levels.
Until we hit the blending wall, most of the imports likely would increase total consumption
and not displace maize ethanol. However, we will probably reach the blending wall in
2009/10, at which point imports would likely displace domestic maize ethanol and thereby
lower maize price.
3. Impacts of US and EU policies on the rest of the world
Our analysis of global impacts is done using the Global Trade Analysis Project (GTAP)
model and data base. This work is based on Hertel et al. (2008). We begin with an analysis
of the origins of the recent bio-fuel boom, using the historical period from 2001-2006 for
purposes of model calibration and validation. This was a period of rapidly rising oil prices,
increased subsidies in the EU, and, in the US, there was a ban on the major competitor to
ethanol for gasoline additives (MTBE) (Tyner, 2008). Our analysis of this historical period
permits us to evaluate the relative contribution of each of these factors to the global biofuel
boom. We also use this historical simulation to establish a 2006 benchmark biofuel economy
from which we conduct our analysis of future mandates.
We then can do a forward-looking analysis of EU and US biofuel programs. The US Energy
Policy and Security Act of 2007 calls for 15 billion gallons of ethanol use by 2015, most of
which is expected to come from maize. In the EU, the target is 5.75% of renewable fuel use
in 2010 and 10% by 2020. However, there are significant doubts as to whether these goals are
attainable. For this analysis, we adopt the conservative mandate of 6.25% by 2015 in the EU.
Sugarcane ethanol
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Chapter 8
The starting point for our prospective simulations is the updated, 2006 fuel economy which
results from the foregoing historical analysis. Thus, we analyze the impact of a continued
intensification of the use of biofuels in the economy treating the mandates as exogenous
shocks.12 Ethanol exports from Brazil to the US grow in this simulation as well.
Table 1 reports the percentage changes in output for biofuels and the land-using sectors
in the USA, EU and Brazil. The first column in each block corresponds to the combined
impact of EU and US policies on a given sector’s output (USEU-2015). The second column
in each block reports the component of this attributable to the US policies (US-2015), and
the third reports the component of the total due to the EU policies (EU-2015) using the
decomposition technique of Harrison et al. (2000). This decomposition method is a more
sophisticated approach to the idea of first simulating the global impacts of a US program,
then simulating the impact of an EU biofuels program, and finally, simulating the impact
of the two combined. The problem with that (rather intuitive) approach is that the impacts
of the individual programs will not sum to the total, due to interactions. By adopting
this numerical integration approach to decomposition, the combined impacts of the two
programs are fully attributed to each one individually.
In the case of the US impacts (columns labeled Output in US), most of the impacts on the
land-using sectors are due to US policies. Coarse grains output rises by more than 16%, while
output of other crops and livestock falls when only US policies are considered. However,
oilseeds are a major exception. Here, the production impact is reversed when EU mandates
are introduced. In order to meet the 6.25% renewable fuel share target, the EU requires a
massive amount of oilseeds. Even though production in the EU rises by 52%, additional
imports of oilseeds and vegetable oils are required, and this serves to stimulate production
worldwide, including in the US. Thus, while US oilseeds output falls by 5.6% in the presence
of US-only programs, due to the dominance of ethanol in the US biofuel mix, when the EU
policies are added to the mix, US oilseed production actually rises.
In the case of the EU production impacts (Output in EU: the second group of columns
in Table 1), the impact of US policies is quite modest, with the main interaction again
through the oilseeds market. However, when it comes to third markets – in particular Brazil
(Output in Brazil), the US and EU both have important impacts. US policies drive sugarcane
production, through the ethanol sector, while the EU policies drive oilseeds production in
Brazil. Other crops, livestock, and forestry give up land to these sectors.
12
Technically, we endogenize the subsidy on biofuel use and exogenize the renewable fuel share, then shock
the latter. For simplicity, all components of the renewable fuels bundle are assumed to grow in the same
proportion.
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Sugarcane ethanol
Table 1. Change in output due to EU and US biofuel mandates: 2006-2015 (%).
Sector
Output in US
USEU-2015
Ethanol
177.5
Biodiesel
176.9
Coarse grains 16.6
Oilseeds
6.8
Sugarcane
-1.8
Other grains
-7.6
Other agri
-1.6
Livestock
-1.2
Forestry
-1.2
Output in EU
US-2015
177.4
176.8
16.4
-5.6
-1.9
-8.7
-1.7
-1.2
-1.4
EU-2015
0.1
0.1
0.2
12.4
0.1
1.2
0.2
0.0
0.1
USEU-2015
430.9
428.8
2.5
51.9
-3.7
-12.2
-4.5
-1.7
-5.4
Output in Brazil
US-2015
1.3
1.2
0.8
1.2
0.0
0.1
0.0
0.1
-0.3
EU-2015
429.7
427.6
1.7
50.7
-3.7
-12.3
-4.5
-1.8
-5.1
USEU-2015
18.1
-0.3
21.1
8.4
-8.7
-3.8
-1.4
-2.7
US-2015
17.9
1.1
0.6
9.3
-2.0
-1.5
-0.6
-1.0
EU-2015
0.2
-1.4
20.5
-0.9
-6.8
-2.4
-0.7
-1.8
Note: Ethanol in the US and EU is from grains, and it is sugarcane-based in Brazil.
The global impacts of US and EU biofuels policies
191
Chapter 8
Table 2 reports changes in crop harvested area as a result of the biofuel mandates in the US
and EU for all regions in the model. The simulation includes only the biofuels shock, and
does not include population growth, income growth, trend yield increases, or anyother
‘baseline’ factors. It is designed just to isolate the biofuels impacts. Coarse grains acreage
in the US is up by about 10%, while sugar, other grains, and other crops are all down. The
productivity-weighted rise in coarse grains acreage is 10% (Table 3). This increase in maize
acreage in the US comes from contribution of land from other land-using sectors such as
other grains (Table 3) as well as pasture land and commercial forest land – to which we
will turn momentarily.
From Table 2, we see that US oilseeds acreage is up slightly due to the influence of EU
policies on the global oilseeds market. However, this marginal increase is dwarfed by the
increased acreage devoted to oilseeds in other regions, where the percentage increases range
from 11 to 16% in Latin America, and 14% in Southeast Asia and Africa, to 40% in the EU.
If the EU really intends to implement its 2015 renewable fuels target, there will surely be
a global boom in oilseeds. Coarse grains acreage in most other regions is also up, but by
much smaller percentages. Clearly the US-led ethanol boom is not as significant a factor
as the EU oilseeds boom. Sugarcane area rises in Brazil, but declines elsewhere, and other
grains and crops are somewhat of a mixed bag, with acreage rising in some regions to make
up for diminished production in the US and EU and declines elsewhere.
From an environmental point of view, the big issue is not which crops are grown, but how
much cropland is demanded overall, and how much (and where) grazing and forestlands
are converted to cropland. These results are very sensitive to the productivity of land in the
pasture and forest categories compared to cropland. We recognize that more work needs
to be done on certain land categories such as idled land and cropland pasture in the US
and the savannah in Brazil. Therefore the numerical results reported here must be taken
as only illustrative of the results that will be available once the land data base is improved.
Table 3 reports the percentage changes in different land cover areas as a result of the EU
and US mandates. Furthermore, as with the output changes in Table 1, we decompose
this total into the portion due to each region’s biofuels programs. From the first group of
columns, we see that crop cover is up in nearly all regions. Here we also see quite a bit of
interaction between the two sets of programs. For example, in the US, about one-third of
the rise in crop cover is due to the EU programs. In the EU, the US programs account for a
small fraction of the rise in crop cover. In other regions, the EU programs play the largest
role in increasing crop cover. For example, in Brazil, the EU programs account for nearly
11% of the 14.2% rise in crop cover.
Where does this crop land come from? In our framework it is restricted to come from
pastureland and commercial forest lands, since we do not take into account idle lands, nor do
we consider the possibility of accessing currently inaccessible forests. The largest percentage
reductions tend to be in pasturelands (Table 3, final set of columns). For example, in Brazil,
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The global impacts of US and EU biofuels policies
Table 2. Change in crop harvested area by region, due to EU and US biofuel mandates: 2006-2015 (%).
Region
Crops
Coarse
grains
USA
9.8
Canada
3.5
EU-27
-2.3
Brazil
-3.2
Japan
10.7
China-Hong Kong
1.2
India
-0.7
Latin American energy
1.8
exporters
Rest of Latin America &
1.7
Caribbean
EE & FSU energy exporters
0.5
Rest of Europe
2.3
Middle Eastern North Africa
4
energy exporters
Sub Saharan energy exporters -0.8
Rest of North Africa & SSA
1.5
South Asian energy exporters -0.5
Rest of high income Asia
3.7
Rest of Southeast & South Asia -0.2
Oceania countries
3.9
Oilseeds
Sugarcane
Other grains Other agri
1.6
16.9
40
16
7.6
8.2
0.9
11.3
-5.7
-3.2
-7.4
3.8
-0.7
-0.6
-0.7
-2.3
-10
-2.6
-15.1
-10.9
0.8
-0.5
0.5
-0.2
-2.7
-1.6
-6.1
-5.1
-0.1
-0.5
-0.2
-0.8
11.5
-1.6
-0.6
-0.3
18.1
10.5
8.6
-0.6
0
-0.9
0.4
1.8
2.5
-0.5
0.4
-0.4
13.7
14.2
3.7
6.1
2.9
17.2
0
-0.4
-0.9
-0.1
-0.8
-0.6
2.3
1.1
-0.6
-0.2
0
-1.3
1.2
1.1
-0.1
0
-0.1
0.3
Note: These results are solely illustrative of the kinds of numerical results that are produced by the
analysis. They are not definitive results.
we estimate that pasturelands could decline by nearly 11% as a result of this global push for
biofuels, of which 8% decline is from EU mandates alone. The largest percentage declines
in commercial forestry cover are in the EU and Canada, followed by Africa. In most other
regions, the percentage decline in forest cover is much smaller.
Our prospective analysis of the impacts of the biofuels boom on commodity markets focused
on the 2006-2015 time period, during which existing investments and new mandates in the
US and EU are expected to substantially increase the share of agricultural products (e.g.
maize in the US, oilseeds in the EU, and sugar in Brazil) utilized by the biofuels sector. In
Sugarcane ethanol
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Chapter 8
Table 3. Decomposition of change land cover by EU and US biofuel mandates (with Sensitivity Analysis):
2006-2015 (% change).
Crop cover
USEU
2015
US
Canada
EU-27
Brazil
Japan
China-Hong Kong
India
Latin American EEx.
Rest of Latin Am.
EE & FSU EEx.
Rest of Europe
Middle Eastern N Africa EEx.
Sub Saharan EEx.
Rest of North Africa & SSA
South Asian EEx.
Rest of high income Asia
Rest of Southeast & South Asia
Oceania countries
7
11.3
14.3
14.2
1.3
1.9
1
6.2
5.5
4.6
6.8
1.7
6.9
9.9
-0.2
0.1
1.2
6.6
US
2015
4.7
2.9
0.9
3.5
0.5
0.5
0.1
2.1
1.5
0.9
1.3
0.4
1.6
2.1
0
0
0.2
1.5
EU
2015
2.3
8.4
13.4
10.7
0.8
1.4
0.9
4.1
4.1
3.7
5.5
1.2
5.3
7.8
-0.2
0
1
5.1
Confidence
interval (95%)
Lower
Upper
3.5
4.7
8.0
7.0
-0.1
-0.5
-0.6
1.6
1.3
0.1
2.1
0.2
1.7
3.3
-0.9
-0.1
-0.3
1.6
10.8
18.0
20.7
21.5
2.7
4.3
2.7
10.9
9.9
9.1
11.5
3.2
12.1
16.6
0.5
0.2
2.7
11.7
the US, this share could more than double from 2006 levels, while the share of oilseeds going
to biodiesel in the EU could triple. In analyzing the biofuel policies in these regions, we
decompose the contribution of each set of regional policies to the global changes in output
and land use. The most dramatic interaction between the two sets of policies is for oilseed
production in the US, where the sign of the output change is reversed in the presence of EU
mandates (rising rather than falling). The other area where they have important interactions
is in the aggregate demand for crop land. About one-third of the growth in US crop cover
is attributed to the EU mandates. When it comes to the assessing the impacts of these
mandates on third economies, the combined policies have a much greater impact than just
the US or just the EU policies alone, with crop cover rising sharply in Latin America, Africa
194
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The global impacts of US and EU biofuels policies
Forest cover
USEU
2015
-1.7
-6
-7.3
-1.7
-0.8
0.1
0
-2
-0.3
-0.8
-0.7
-0.9
-3.4
-3.4
0.5
0.1
0
-2.4
US
2015
Pasture cover
EU
2015
-1.3
-1.6
-0.5
-0.5
-0.3
0
0
-0.8
-0.3
-0.2
-0.3
-0.2
-0.8
-0.8
0.1
0
0
-0.6
-0.5
-4.4
-6.8
-1.2
-0.5
0.2
0
-1.2
0
-0.5
-0.4
-0.6
-2.6
-2.6
0.4
0.1
0
-1.8
Confidence
interval (95%)
Lower
Upper
-2.6
-9.2
-10.4
-2.5
-1.8
-0.2
-0.4
-3.3
-1.5
-3.6
-2.0
-1.7
-6.3
-5.8
-0.2
0.0
-0.3
-4.0
-0.9
-2.8
-4.3
-0.9
0.2
0.5
0.4
-0.6
0.9
2.0
0.7
0.0
-0.5
-1.1
1.2
0.2
0.2
-0.8
USEU
2015
-4.9
-4.4
-5.6
-10.9
-0.4
-2
-1
-4
-5
-3.6
-5.7
-0.8
-3.2
-5.8
-0.3
-0.1
-1.1
-3.9
US
2015
-3.2
-1.1
-0.4
-2.7
-0.2
-0.4
-0.1
-1.3
-1.1
-0.6
-0.9
-0.2
-0.7
-1.1
-0.1
0
-0.2
-0.8
EU
2015
-1.7
-3.4
-5.3
-8.3
-0.3
-1.6
-0.9
-2.7
-3.9
-3
-4.8
-0.6
-2.5
-4.6
-0.2
-0.1
-0.9
-3.1
Confidence
interval (95%)
Lower
Upper
-7.3
-6.9
-7.8
-15.8
-0.8
-4.1
-2.4
-6.8
-8.3
-6.0
-9.2
-1.4
-5.1
-9.2
-0.5
-0.3
-2.5
-6.8
-2.6
-2.1
-3.5
-6.1
-0.1
0.1
0.3
-1.2
-1.7
-1.2
-2.3
-0.2
-1.2
-2.4
0.0
0.0
0.2
-1.0
and Oceania as a result of the biofuel mandates. These increases in crop cover come at the
expense of pasturelands (first and foremost) as well as commercial forests. It is these land
use changes that have attracted great attention in the literature (e.g. Searchinger et al., 2008)
and a logical next step would be to combine this global analysis of land use with estimates
of the associated greenhouse gas emissions.
4. Conclusions
This paper examines US ethanol policy options using a partial equilibrium model and
US and EU options using a global general equilibrium model. The partial equilibrium
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results clearly illustrate the new linkage between energy and agricultural markets. Prices
of agricultural commodities in the future will be driven not only by demand and supply
relationships for the agricultural commodities themselves, but also by the price of crude oil.
Ethanol from maize and sugarcane can be produced economically at high crude oil prices.
The US policy interventions have enabled the ethanol industry to exist and grow over the
past 30 years. Today the government interventions continue to be important, but the new
added driver is high oil prices.
When one examines the US and EU policies together, one sees clearly that the impacts are
felt around the world. Trade and production patterns are affected in every region. The results
presented here are very preliminary, but they serve to illustrate how the analysis can be used
to estimate global production, trade, and land use impacts of US and EU policies.
Acknowledgements
The author acknowledges the collaboration of Dileep Birur, Tom Hertel, and Farzad
Taheripour.
References
Abbott, P., C. Hurt and W. Tyner, 2008. What’s Driving Food Prices? Farm Foundation Issue Report, July
2008. Available at: www.farmfoundation.org.
Earth Policy Institute, 2006. World Ethanol Production. Available at: www.earthpolicy.org/Updates/2005/
Update49_data.htm.
Energy Information Administration, 2008. U.S. Department of Energy. Available at: www.eia.doe.gov.
European Biodiesel Board, 2007. The EU Biodiesel Industry. Available at: www.ebb-eu.org/stats.php.
Harrison, W.J., J.M. Horridge and K.R. Pearson, 2000 Decomposing Simulation Results with Respect to
Exogenous Shocks. Computational Economics 15: 227-249.
Hertel, T.W., W.E. Tyner and D.K. Birur, 2008 Biofuels for all? Understanding the Global Impacts of
Multinational Mandates GTAP Working Paper No. 51, 2008.
Renewable Fuels Association, 2007. World Fuel Ethanol Production. Available at: www.ethanolrfa.org/
industry/statistics/#A.
Searchinger, T., R. Heimlich, R.A. Houghton, F. Dong, A. Elobeid, J. Fabiosa, S. Tokgoz, D. Hayes and T.H. Yu, 2008. Use of U.S. Croplands for Biofuels Increases Greenhouse Gases Through Emissions from
Land-Use Change. Science 317: 1238-1240.
Tyner, W.E., 2008. The US Ethanol and Biofuels Boom: Its Origins, Current Status, and Future Prospects.
BioScience 58: 646-53.
Tyner, W.E. and F. Taheripour, 2007. Future Biofuels Policy Alternatives. paper presented at the Farm
Foundation/USDA conference on, April 12-13, 2007, St. Louis, Missouri. In: Biofuels, Food, and
Feed Tradeoffs, pp. 10-18. Available at: http://www.farmfoundation.org/projects/documents/
Tynerpolicyalternativesrevised4-20-07.pdf.
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Tyner, W. and F. Taheripour, 2008a. Policy Options for Integrated Energy and Agricultural Markets. Review
of Agricultural Economics 30, in press.
Tyner, W. and F. Taheripour, 2008b. Policy Analysis for Integrated Energy and Agricultural Markets in
a Partial Equilibrium Framework. Paper Presented at the Transition to a Bio-Economy: Integration
of Agricultural and Energy Systems conference on February 12-13, 2008. Available at: www.agecon.
purdue.edu/papers.
Tyner, W.E., F. Dooley, C. Hurt and J. Quear, 2008. Ethanol Pricing Issues for 2008. Industrial Fuels and
Power, February 2008: 50-57.
U.S. Congress, 2007. Energy Independence and Security Act of 2007. H.R. 6, 110 Congress, 1st session.
Available at: http://www.whitehouse.gov/news/releases/2007/12/20071219-1.html.
U.S. Congress, 2008. 2008 Farm Bill. H. R. 6124 (P.L. 110-246).
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Impacts of sugarcane bioethanol towards the Millennium
Development Goals
Annie Dufey
1. Introduction
At the Millennium Summit in September 2000 the largest gathering of world leaders in
history adopted the United Nations Millennium Declaration. They committed to a new
global partnership to reduce extreme poverty by 2015 in line with a series of targets that
have become known as the Millennium Development Goals (MDGs). The MDGs are crafted
around eight themes to promote sustainable development addressing extreme poverty in its
different dimensions including hunger, health, education, the promotion of gender quality
and environmental sustainability (see Box 1).
At the same time, during the last five years or so, the world has witnessed the global emergence
of a new sector – the biofuels sector. Biofuels potential for achieving simultaneously
economic, poverty reduction and environmental goals have combined and placed biofuels
at the top of today’s most pressing policy agendas.
This chapter argues that sugarcane bioethanol can be supportive of sustainable development
and poverty reduction, thus contributing to the achievement of the MDGs. In some
contexts there might be synergies between the pursue of different goals but there may be
Box 1. The Millennium Development Goals.
The eight Millennium Development Goals were agreed at the United Nations Millennium Summit
in September 2000. The eight Millennium Development Goals are:
• Eradicate extreme poverty and hunger
• Achieve universal primary education
• Promote gender equality and empower women
• Reduce child mortality
• Improve maternal health
• Combat HIV and AIDS, malaria and other diseases
• Ensure environmental sustainability
• Develop a global partnership for development
Source: http://www.un.org/millenniumgoals/
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also risks and serious trade-offs over food security, small farmers inclusion, environment
and the economy.
Much of the available evidence comes from Brazil, which has the main longstanding
experience with the launching of the PROALCOOL Programme in 1975 to replace
imported gasoline with bioethanol produced from locally grown sugarcane. Today Brazil is
the second bioethanol producer after the United States and the main exporter. In addition,
there have been other smaller initiatives with different rate of success. These include
African and East Asian countries such as Zimbabwe, Malawi, Kenya, Pakistan and India
that have promoted bioethanol from sugarcane molasses, some of them since the early
eighties. More widely, at present, many countries around the world, in their search for
development and poverty reduction opportunities are trying to replicate the Brazilian
experience with sugarcane bioethanol. Their vast majority are developing countries in
tropical and semitropical areas in the Caribbean, Africa, Latin America and East Asia in
which sugarcane is traditionally grown.
The chapter is organized as follows. After this brief introduction, Section 2 argues that
sugarcane bioethanol may offer some genuine opportunities for sustainable development
and poverty reduction and identify the key potential benefits. Section 3 points out that
benefits are not straightforward and identifies several challenges and trade-offs that need to
be confronted in order to realize their full potential for achieving sustainable development
and poverty reduction. Finally, section 4 concludes and provides some recommendations.
2. Opportunities for sugarcane bioethanol in achieving sustainable
development and the Millennium Development Goals
Sugarcane bioethanol can contribute to sustainable development and poverty reduction
through a varied range of environmental, social and economic advantages over fossil fuels.
These include: (a) enhanced energy security both at national and local level; (b) improved
social well-being through better energy services especially among the poorest; (c) improved
trade balance by reducing oil imports; (d) rural development and better livelihoods; (e)
product diversification leaving countries better-off to deal with market fluctuations; (f)
creation of new exports opportunities; (g) potential to help tackling climate change through
reduced emissions of greenhouse gases (h) reduced emissions of other air contaminants;
and (i) opportunities for investment attraction through the carbon finance markets. This
section briefly addresses each of these aspects.
2.1. Enhanced energy security
Enhanced energy security has become a universal geopolitical policy concern and it was a
key policy driver behind the first attempts to introduce sugarcane bioethanol at a massive
scale in the mid-1970s in Brazil (Dufey et al., 2007b). Current increasing energy costs and
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uncertainty regarding future energy supply are giving many governments incentive to
encourage the production of petroleum substitutes from agricultural commodities. Indeed,
the volatility of world oil prices, uneven global distribution of oil supplies, uncompetitive
structures governing the oil supply and heavy dependence on imported fuels are all factors
that leave many countries vulnerable to disruption of supply, imposing serious energy
security risks which can result in physical hardships and economic burden (Dufey, 2006).
For instance, crude oil imports to African, Caribbean and Pacific countries were expected
to increase to 72 percent of their requirements in 2005 (Coelho, 2005).
Energy diversification makes countries less vulnerable to oil price shocks, compromising
macro-stability affecting variables such as the exchange rate, inflation and debt levels
(Cloin, 2007). Sugarcane bioethanol is a rational choice in countries where sugarcane can
be produced at reasonable cost without adverse social and environmental impacts (Dufey
et al., 2007b). For remote places, locally produced sugarcane bioethanol can offer a highly
competitive alternative to other fuels. This might be the case of several sugarcane producing
countries in Pacific island nations and land-locked countries in Africa where the high costs
of fossil fuel transportation and the related logistics make them prohibitive.
2.2. Benefits at the household level - improved social well-being
A large part of the poor, mostly in rural areas, do not have access to affordable energy services
which affects their chances of benefiting from economic development and improved living
standards. In this context the use of bioethanol and other renewable sources can directly
or indirectly lead to several MDGs including gender equality, reduction of child mortality,
poverty reduction, improvement of maternal health and environmental sustainability.
Firstly, they can reduce the time spent by women and children on basic survival activities
(gathering firewood, fetching water, cooking, etc.). Women in least developed countries
may spend more than one third of their productive life collecting and transporting wood.
Additional help needed from children often prevents them from attending school (FAO,
2007). Secondly, the use of bioethanol (and other liquid biofuels) for household cooking
and heating could help to reduce respiratory disease and death associated with burning of
other traditional forms of fuels usually used in the poorest countries (e.g charcoal, fuelwood
and paraffin solid biomass fuels indoors), to which women and children are especially
vulnerable (UN-Energy, 2007; Woods and Read, 2005). In some African countries charcoal
and woodfuel account for over 95 percent of household fuel (Johnson and Rosillo-Calle,
2007). As Box 2 suggests, experiences promoting the use of sugarcane bioethanol in stoves
at the household level are expected to report important socio-economic and environmental
benefits. Finally, the use of biofuels can improve access to pumped drinking water, which can
reduce hunger by allowing for cooked food (95% of food needs cooking) (Gonsalves, 2006a).
However, adaptation of bioethanol for domestic uses would of course require a cultural shift
away from the traditional hearth, plus attention to safety in fuel storage, as liquid biofuels
are highly flammable (Dufey et al., 2007b). Overall, electricity through transmission lines to
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Box 2. Bioethanol stoves to condominium residents in Addis Ababa in Ethiopia
In Ethiopia the Municipality of Addis Ababa EPA (Environmental Protection Authority) and a SubCity district are working closely with Gaia Association, Dometic AB, Makobu Enterprises, and
Finchaa Sugar Factory to develop a project whereby initially 2000 CleanCook (CC) stoves will be
installed in newly built condominium apartments. Wood and charcoal stoves are not permitted
in these condominium buildings.
The CC stove is financed within the condominium unit price. Financing is provided by the
condominium association with the assistance of the Municipal EPA, the Sub-City Administration
and a financing entity. The finance rate is regulated by the government and is kept low. The
bioethanol used in the project is produced at one of three state-owned sugar factories at a
contractual price by Makobu Enterprises and delivered to the condominium. The fuel storage and
distribution infrastructure will be financed by the condominium association. The Ethiopian EPA
will work with one Sub-City Administration to package the stove financing into the condominium
financing through the national bank. As a result, 2000 CC stoves will be financed in 2008 and
approximately 360,000 liters of domestically produced bioethanol will supplant kerosene,
charcoal and firewood use. The other nine Sub-City administrations could replicate the model.
Since the CC stove is clean burning, its introduction will improve indoor air quality and,
consequently, household health. Another advantage of this model lies in the potential for Clean
Development Mechanism (CDM) financing. It is important to note the government has had a
central role for the development of a domestic bioethanol industry in Ethiopia, as well as for
building a local market for bioethanol as a household cooking fuel. Indeed, after considering
allocating bioethanol for fuel blending in the transport sector in 2006, the Government got
convinced that the most significant socioeconomic and environmental benefits would stem from
prioritizing the use in the domestic household sector.
Source: adapted from Lambe (2008).
many rural areas is unlikely to happen in the near future, so access to modern decentralized
small-scale energy technologies, particularly renewables are an important element for
effective poverty alleviation policies (Gonsalves, 2006a). In this context, bioethanol can
be directed towards high value added uses such as lighting or motors, which can lead to
income generating activities.
But the effectiveness of using sugarcane bioethanol for these uses would need to be assessed
against those of other energy crops or renewable sources such as small hydropower.
2.3. Improved trade balance
Heavy reliance on foreign energy sources means countries have to spend a large proportion
of their foreign currency reserves on oil imports. Oil import dependency is especially acute
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in Sub-Saharan and East Asian countries, where 98 percent and 85 percent of their oil needs
are met by imports, respectively (ESMAP, 2005a). Changes in oil prices have devastating
effects in these countries. For instance, the 2005 oil price surge reduced Gross Domestic
Product growth of net oil importing countries from 6.4 percent to 3.7 percent, and, as a
consequence, the number of people in poverty rose by as much as 4-6 percent, with nearly
20 countries experiencing increases of more than 2 percent (ESMAP, 2006).
Domestically produced bioethanol offers oil importing countries an opportunity to improve
their trade balance. In Brazil, for instance, the replacement of imported gasoline by sugarcane
bioethanol saved the country some US$ 61 billion in avoided oil imports during the last
eight years – equating the total amount of the Brazilian external public debt (FAO, 2007).
In Colombia, the implementation of the bioethanol programme would result in foreign
exchange savings of US$ 150 million a year (Echeverri-Campuzano, 2000).
2.4. Rural development and creation of sustainable livelihoods
Biofuels provide new economic opportunities and employment in the agricultural sector,
key aspects for poverty reduction. They generate a new demand for agricultural products
that goes beyond traditional food, feed and fibre uses, expanding domestic markets for
agricultural produce and paving the way for more value-added produce. All of these
aspects enhance rural development, especially in developing countries where most of the
population live in rural areas. For instance, Echeverri-Campuzano (2002) estimates that
every Colombian farming family engaged in bioethanol production will earn two to three
times the minimum salary (US$ 4,000/year). In South Africa meeting targets of E8 and
B2 would contribute 0.11 percent to the country’s Gross Domestic Product. Most of the
positive effect would take place in rural areas characterized by unemployment and rising
poverty (Cartwright, 2007).
Compared to other sources of energy, biofuels are labour intensive. Their production is
expected to generate more employment per unit of energy than conventional fuels and
more employment per unit investment than in the industrial, petrochemical or hydropower
sector (UN-Energy, 2007). Creation of rural employment and the related livelihoods are
all key aspects for rural development and poverty reduction. In Brazil estimations of direct
employment associated with sugarcane bioethanol production ranges from 500,000 and 1
million (Worldwatch Institute, 2006; FAO, 2007) with indirect employment in the order of
6 million. Although most of them are filled by the lower-skilled, poorest workers in rural
areas (Macedo, 2005), average earnings are considered better than in other sectors as the
average family income of the employees ranks in the upper 50 percentile (FAO, 2007). In
India, country that houses 22 percent of the world’s poor, the sugarcane industry including
bioethanol production is the biggest agroindustry in the country and the source of livelihood
of 7.5 percent of the rural population. Half a million people are employed as skilled or semiskilled labourers in sugarcane cultivation (Gonsalves, 2006a).
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The highest impact on poverty reduction is likely to occur where sugarcane bioethanol
focuses on local consumption, involving the participation and ownership of small farmers
in the production and processing (FAO, 2007; Dufey et al., 2007b) and where processing
facilities are near to the cultivation fields.
2.5. Product diversification and value added
International sugarcane market is one of the most distorted markets. It is highly protected,
in general countries manage to negotiate quotas, a limited access to different markets,
and because it is a commodity, it has important price fluctuations (Murillo, 2007). In this
context, sugarcane bioethanol is an opportunity to promote agricultural diversification
leaving producers in a more favourable situation to deal with changes in prices and other
market fluctuations. In Brazil, for instance, besides the pursue of enhanced energy security,
the government promoted the PROALCOOL programme in order to deal with the fall
in international sugar prices preventing thus the industry of having idle capacity (FAO,
2007). Moreover, the production of both sugar and bioethanol gives the Brazilian industry
flexibility in responding to the changing profitability of sugar and bioethanol production
worldwide. In most cases, sugar and bioethanol are produced in the same mills (Bolling
and Suarez, 2001).
Sugarcane bioethanol can also reduce vulnerability through diversification. The changes in
the European Union’s sugar regime will imply that many African, Caribbean and Pacific
countries will see their market access preferences eroded generating negative impacts
on poverty levels. In the Caribbean, for instance, the associated possible loss of export
revenues is expected to be 40 percent with a heavy contraction in the industry. The resulting
sugar surpluses therefore could be accommodated for biofuels production thus helping the
industry to diversify, avoiding or mitigating the expected contraction (E4Tech, 2006).
Another element to consider is the fact that sugarcane bioethanol production provides value
added to sugarcane production. For instance, Murillo (2007) notes for Costa Rica that if the
molasses and sugar producers substitute their production by those of bioethanol the price
received would be much more than what they would get if they were to continue producing
molasses or sugar for the surplus market.
2.6. Export opportunities
Although at present very little bioethanol enter the international market (about 10%),
international trade is expected to expand rapidly, as the global increase in consumption
(especially countries in the North) will not coincide geographically with the scaling up of
production (countries in the South) (Dufey, 2006). The geographical mismatch between global
supply and demand represents an opportunity for countries with significant cost advantages
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in sugarcane production to develop new export markets and to increase their export revenues.
These are invariably developing countries in tropical and semitropical areas.
Brazil, the main global bioethanol exporter, increased its exports considerably over the
last few years and today supplies about 50 percent of international demand. (Dufey et al.,
2007b). The Brazilian government expects that by 2015 about 20 percent of the national
production to be exported (Ministerio da Agricultura et al., 2006). Countries from the
Caribbean Basin Initiative are developing export-oriented sugarcane bioethanol industries
taking advantage of preferential market access provided by the trade agreement with the
United States. Other exporters include Peru, Zimbabwe and China. As them other Latin
American, African and East Asian countries are exploring the benefits of export-oriented
sugarcane bioethanol sectors.
In absence of trade distorting policies and where effective distributional and social policies
are supportive, the development of a successful sugarcane bioethanol export-oriented
industry could effectively reduce poverty.
2.7. Reduced greenhouse gas emissions
At present global warming is considered one of the key global threats facing the humanity
(Stern, 2006). Biofuels alleged reduced greenhouse gas emissions compared to fossil fuels
are one of the main policy rationales for their promotion especially in Northern countries.
There are two ways in which biofuels can reduce carbon emissions. First, over their life cycle,
biofuels absorb and release carbon from the atmospheric pool without adding to the overall
pool (in contrast to fossil fuels). Second, they displace use of fossil fuels (Kartha, 2006).
However, biofuels production does, in most cases, involve consumption of fossil fuels.
Compared to other types of liquid biofuels and under certain circumstances, Brazilian
sugarcane bioethanol and second generation biofuels show the higher reductions in
greenhouse gas emissions relative to standard fuels. IEA (2004) estimates that greenhouse
emissions from sugarcane bioethanol in Brazil are 92 percent lower than standard fuel, while
wheat bioethanol points to reductions ranging from 19 percent to 47 percent and reductions
from sugar beet bioethanol vary between 35 percent and 53 percent. In addition to Brazil’s
exceptional natural conditions in terms of high soil productivity and that most sugarcane
crops are rain fed, a key factor behind its great greenhouse emissions performance is that
nearly all conversion plants’ processing energy is provided by ‘bagasse’ (the remains of the
crushed cane after the juice has been extracted). This means energy needs from fossil fuel are
zero and the surplus bagasse is even used for electricity co-generation. In 2003, Brazil avoided
5.7 million tonnes CO2 equivalent due to the use of bagasse in sugar production (Macedo,
2005). Moreover, new developments in the sector such as the commercial application of
lignocelulosic technology that will allow the use of bagasse for bioethanol production and
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the increased generation of electricity from bagasse will improve their greenhouse emissions
balance (Dufey et al., 2007a).
However the Brazilian experience is not necessarily replicable in other contexts. For example,
efficiency gains and the greenhouse emissions reductions associated with co-generation are
an option for those countries whose electricity sectors regulation allows power sale to the
grid (E4Tech, 2006).
Finally, these estimations do not include the emissions resulting from changes in land use
and land cover induced by sugarcane plantations for bioethanol production. For example,
the evaluation of greenhouse emissions from Brazil for the 1990-1994 period points out
the change in land use and forests as the factor accounting for most of the emissions (75%),
followed by energy (23%). This implies that if additional land use for sugarcane production
leads (directly or indirectly) to conversion of pastures or forests as suggested later in this
chapter, the greenhouse emissions may be severe and could have a major impact on the
overall greenhouse emission balance (Smeets et al., 2006). Overall, the land use issue
requires further attention and is addressed in another chapter of this book.
2.8. Outdoor air quality
Road transport is a growing contributor to urban air pollution in many developing country
cities. One of the greatest costs of air pollution is the increased incidence of illness and
premature death that result from human exposure to elevated levels of harmful pollutants.
The most important urban air pollutants to control in developing countries are lead, fine
particulate matter, and, in some cities, ozone. Sugarcane bioethanol, when used neat, is a
clean fuel (aside from increased acetaldehyde emissions). More typical use of bioethanol
is in low blends. Bioethanol also has the advantage of having a high blending octane
number, thereby reducing the need for other high-octane blending components such as
lead that cause adverse environmental effects. Venezuela, for instance, began importing
Brazilian bioethanol as part of the effort to eliminate lead from gasoline. Bioethanol can
be effective for cutting carbon monoxide emissions in winter in old technology vehicles as
well as hydrocarbons emissions. The latter are ozone-precursors, in old technology vehicles
(ESMAP, 2005b).
On the other hand, there is air pollution associated with the slush and burn of sugarcane
and the burning of the straw, a common practice in developing countries to facilitate the
harvesting. This issue is further addressed in Section 3.b on Environmental Impacts.
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2.9. Opportunities for investment attraction – including the Clean Development
Mechanism
Developing countries can make use of the carbon finance markets for attracting investment
into biofuels projects using the market value of expected greenhouse emission reductions.
The Clean Development Mechanism (CDM) under the Kyoto Protocol is the most important
example of the carbon market for developing countries. The CDM allows developed countries
(or their nationals) to implement project activities that reduce emissions in developing
countries in return for certified emission reductions (CERs). Developed countries can use
the CERs generated by such project activities to help meet their emissions targets under the
Kyoto Protocol. For instance, it is calculated the Colombian Programme on bioethanol would
reduce CO2 emissions by six million tons, offering opportunities to obtain financial resources
for the project trough the CDM (Echeverri-Campuzano, 2000). For Costa Rica, Horta (2006)
estimates that considering an avoided ton of carbon at a conservative price of US$ 5, in the
scope of the Kyoto Protocol and the valid mechanisms of carbon trade, US$ 320,000/year
can be obtained using a 10 percent of sugarcane bioethanol in the gasoline blend.
Although the CDM is a potential source of financing for biofuels projects, taking advantage
of it can present a number of challenges for the developing country host. Firstly, so far
there is no liquid-biofuels baseline and monitoring methodology approved. Calculation
of greenhouse gases emissions is not straightforward and for many countries biofuels are
still a relatively expensive means of reducing these emissions relative to other mitigation
measures. An additional challenge is that the existing experience with CDM projects shows
that approved projects are strongly concentrated in a handful of large developing countries,
with over 60 percent of all CDM projects distributed across China, India and Brazil alone.
While there are simplified procedures for small-scale projects, the current structure of
the CDM tends to select for large-scale projects. The transaction costs associated with
registering a CDM project are often prohibitively expensive for smaller developing countries,
which imply that economies of scale are relevant (Bakker, 2006). For bioenergy projects
specifically, the exclusion of all land use activities from the CDM except for afforestation and
reforestation is another significant limiting factor, since in the poorest developing countries,
land-use related emissions make up the bulk of greenhouse gases emissions from biomass
energy systems (Schlamadinger and Jürgens, 2004). Overall, as FAO (2007) concludes, while
carbon credits might be influential in the future, currently the carbon market does not have
a large influence over the economics of bioenergy production.
3. Risks and challenges
Section 2 analysed a diverse range of benefits associated with sugarcane bioethanol in terms of
its potential to support poverty reduction and environmental sustainability. However, as this
section argues, these benefits are not straightforward. There is a range of challenges and tradeoffs that need to be confronted in order to realize the full potential that sugarcane bioethanol
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offers to support the MDGs, which include: (a) impacts on food security; (b) environmental
pressure; (c) small farmer inclusion and fair distribution of the value chain benefits; (d) land
impacts; (e) employment quality; (f) need of government support; (g) existence of market
access and market entry barriers and; (h) issues related to improved efficiency, access to
technology, credit and infrastructure. These issues are addressed in the following.
3.1. The food versus fuel debate
Current food prices increases, the role that biofuels play on such rises and their related
impacts on food security are, probably, one of the most controversial debates being held both
at national and international fora. Indeed, food prices increased by 83 percent during the
last three years (World Bank, 2008). The Food and Agriculture Organization of the United
Nations (FAO) food index price rose by nearly 40 percent in 2007, from a 9 percent increase
in 2006 (IFPRI, 2008). World prices rose much more strongly in 2006 than anticipated for
cereals, and to a lesser extent for oilseeds, but weakened for sugar (OECD-FAO, 2007).
The understanding of biofuels impacts on food security is a wider and complex. It requires
considering that the link between food prices increases and food security is not unique
and necessarily negative. It needs to be analysed in the context that changes in food prices
not only impact food availability but also its accessibility through changes in incomes for
farmers and rural areas (Schmidhuber, 2007).
3.1.1. Impacts on food availability
The key question at the national level is whether the savings and gains from biofuels will
outweigh additional food costs. Biofuels compete with food crops for land and water,
potentially reducing food production where new agricultural land or water for irrigation are
scarce (Dufey et al., 2007b). For biofuels that are manufactured from food crops, there is also
direct competition for end-use. To what extent sugarcane bioethanol creates competition for
land and crowd out food crops is an issue that is not very clear. The limited available evidence
would suggest a lesser impact compared to other feedstocks. Zarrilli (2006), for example,
points out that sugarcane producing regions in Brazil stimulate rather than compete with
food crops, which is done by two means. Firstly, through the additional income generated
by sugarcane related agro-industrial activities which ‘capitalises’ agriculture and improves
the general conditions for producing other crops. This is also noted by Murillo (2007) for
Costa Rica, where under current weather conditions and land use, sugarcane bioethanol
production is seen as a complement in income generation rather than a competition for basic
products and vegetables. Secondly, the high productivity of cane per unit of land compared
to other feedstocks enables a significant production of cane, with a relatively small land
occupation (Zarrilli, 2006). Sugarcane’s minimal land requirements but in the context of
sub-Saharan Africa is noted by Johnson et al. (2006), but needs to be proven (Dufey et al.,
2007b). Moreover, in those countries where bioethanol is produced from sugarcane molasses
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there is no displacement of food crops (Rafi Khan et al., 2007). In addition, in many African
countries, cassava and maize are grown for subsistence purposes while cane is often grown
for sugar export. Diversion to fuel production is therefore more likely to adversely affect
food availability in the case of cassava (Johnson and Rosillo-Calle, 2007)
At the international level, the growing international demand for biofuels is expected to
reverse the long-term downward trend in global prices of agricultural commodities. Several
studies have been conducted linking increased global biofuels production with rising
agricultural commodity prices. Estimations vary widely with most credible ones going
up to 30 percent. Other contributing factors to price increases are the weather-related
shortfalls in many key producing countries, reduced global stocks, increased demand from
new emerging economies in Asia (OECD-FAO, 2007) and speculation (IFPRI, 2008). In
that sense, the higher demand for biofuel feedstocks is viewed as increasing pressure on an
already tight supply.
However, it is one issue trying to isolate how much biofuels, in overall, are responsible
for the sector’s inflationary pressure and, a different one, understanding to what extent
sugarcane bioethanol is responsible for the price increase. Although the available evidence
in this sense is also scant, it would suggest that, compared to other feedstocks, sugarcane
bioethanol would have a slighter impact on food security. A key reason behind this is that
sugarcane is not a principal food crop. Staple grains like maize and rice are often the main
food source for the poorest people, accounting for 63 percent of the calories consumed in
low-income Asian countries, nearly 50 percent in Sub-Saharan Africa, and 43 percent in
lower-income Latin American countries (IFPRI, 2008). Rosegrant (2008) in an exercise in
which biofuel production was frozen at 2007 levels for all countries and for all crops used
as feedstocks, shows the smaller price reductions for sugarcane followed by wheat while the
higher reductions are for maize (Figure 1). Another reason been argued is that sugarcane
price would be relatively uncorrelated with other food crops (Oxfam, 2008).
3.1.2. Impacts on accessibility
The issue of how the gains and costs of biofuels to food security are distributed across society
has been less explored in the literature. FAO and other commentators agree that hunger
is largely a matter of access rather than supply, so that a focus on rural development and
livelihoods makes more sense that trying to maximise global food supply, which for now
at least is adequate for global needs (Murphy, 2007).
Higher agricultural commodity prices are good news for agricultural producers, but they
have an adverse impact on poorer consumers, who spends a much larger share of their
income on food (IFPRI, 2008). There are also differences depending on whether households
are net food producers or buyers. For small farmers that are net food producers, overall
gains in welfare and food security are expected due to rising revenues from biofuel crops and
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14
2010
2015
Price variation (%)
12
10
8
6
4
2
0
Maize
Wheat
Sugar
Oils
Cassava
Figure 1. Change in selected crop prices if biofuel demand was fixed at 2007 levels. Source: Rosegrant
(2008).
food crops (Peskett et al., 2007). In overall, poor consumers in urban areas who purchase
all their food are expected to be worst off. From this perspective and compared to other
feedstocks, sugarcane bioethanol is likely to provide more limited opportunities to meet
food security for small farmers. In Brazil, for example, sugarcane is a crop mainly grown
under large-scale schemes, with limited participation of small farmers. In regions such as
Asia, although small farmers participation in sugarcane cultivation is important, the need
to use irrigation makes more unlikely to involve poorest farmers (ICRISAT, 2007). More
widely, it is agreed that despite being producers of agricultural crops, most poor farming
households in rural areas are net buyers of food (Dufey et al., 2007b; IFPRI, 2008).
Finally, it should be noted that, historically, domestic food prices have not been tightly
linked to international food or energy prices, as price transmission mechanisms are not
straightforward (Hazell et al., 2005). For instance, agricultural pricing policies such as
price fixation, the remoteness of some rural areas, trade distortions and power structures
governing agricultural commodity markets are key factors preventing world prices from
reaching domestic markets. This may imply that farmers may not see the incentives to
change feedstock production in tandem with changes in international prices.
3.2. Environmental pressure
Traditional environmental impacts associated with sugarcane appear when it comes
to managing soil, water, agrochemicals, agricultural frontier expansion and the related
biodiversity impacts. Among them, impacts on agricultural frontier and on water deserve
especial attention. Regarding the former, it should be noted that the bulk of the sugarcane
expansion in the last thirty years in Brazil has been concentrated in the central southern
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Impacts of sugarcane bioethanol towards the Millennium Development Goals
region of the country. Between 1992 and 2003, 94 percent of the expansion occurred in
existing areas of agriculture or pastureland and only a small proportion of new agricultural
borders were involved (Macedo, 2005). Often the sugarcane crop replaced cattle grazing and
other agricultural activities (e.g. citrus crops), which in turn moved to the central region of
Brazil where the land is cheaper (Smeets et al., 2006). Land converted to agriculture in the
sensitive area of the Cerrado savanna (which accounts for 25% of the national territory)
has been used for cattle grazing and/or planted to soya, with only a small proportion for
sugarcane. However, given the new phase of expansion experiencing the sector for bioethanol
production, new areas are expected to be converted to sugarcane, including the Cerrado
of Mato Grosso do Sul, Goiás and Minas Gerais (Dufey et al., 2007a). This could further
increase the pressure on the already affected biodiversity and produce greenhouse emissions.
There is concern in this sense on the impacts that the substitution effect - sugarcane taking
over existing pastureland or other crops that become less profitable which in turn advance
into protected or marginal areas – may have on biodiversity. Indeed, in Brazil, substitution
effect related impacts are considered more significant than the direct effects of sugarcane
expansion (Dufey, 2007). In Africa, on the other hand, land constraints appear unlikely in
any near-term scenario, and resources such as water, as explained in the next paragraph,
may turn out to be the key limiting factor (Johnson and Rosillo-Calle, 2007).
Regarding water, sugarcane requires large amounts of water, both at the farming and
processing level. Even in Brazil where most sugarcane is rain fed, irrigation is increasing.
Energy cane, which is especially bred for energy production, requires more water and
fertiliser than conventional sugarcane (Cloin, 2007). Water is likely to be a key limiting factor
especially in dry and semi-dry areas in Africa and Asia. Bioethanol impact on water quality
is another issue and not only at the farming level due to the use of agrochemicals but also at
the processing level. Vinasse, - a black residue resulting from the distillation of cane syrup - is
hot and requires cooling. In the mountainous areas of north-eastern Brazil, for instance, the
costs of pumping storing vinasse were prohibitive, and it was therefore released into rivers,
resulting in the pollution of rivers causing eutrophication and fish kills. Currently, vinasse is
used for ferti-irrigation of cane crops, together with wastewaters. Moreover, legislation has
been implemented in Brazil to avoid the negative impacts of vinasse applications, although
its coverage is incomplete and its enforcement is rather weak (Smeets et al., 2006). All in all,
while steps have been taken in Brazil order to manage vinasse disposal, in countries such
as Malawi it is still a major concern (Johnson and Rosillo-Calle, 2007).
Furthermore, the air pollution associated with the slush and burn of sugarcane and the
burning of the straw, a common practice in developing countries to facilitate the harvesting,
is an additional issue. Sugarcane burning emits several gases including CO, CH2, ozone,
non-methane organic compounds and particle matter that are potentially damaging for
human health. Several studies were conducted in São Paulo in Brazil during the 1980s
and 1990s to identify the impacts of sugarcane burning on human health. Although some
studies did not found a link, others studies did confirm the relationship (Smeets et al., 2006;
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Dufey et al., 2007a). Legislation has been passed in Brazil by which sugarcane burning is
to be completely phased out in the São Paulo State by 2031. In Southern Africa efforts to
reduce sugarcane burning pre-harvesting have also been reported (Jackson, 2004), but in
other countries it still remain a major practice.
Overall, sugarcane bioethanol production poses some specific environmental challenges that
need to be carefully identified and managed using a life cycle approach in order to achieve
the MDG on environmental sustainability.
3.3. Small farmers inclusion and fair distribution of the value chain benefits
Addressing poverty means that biofuels should benefit poor and small farmers overall.
An emphasis on small farmers would provide livelihoods across the greatest section of
the populations (Johnson and Rosillo-Calle, 2007). But the competitiveness of a biofuels
industry is highly dependent on gaining economies of scale. Often large-scale systems are
more globally competitive and export oriented, while small-scale systems offer greater
opportunities for employment generation and poverty alleviation (Dufey et al., 2007b).
In Brazil, the sugarcane business model is characterised by enormous concentration of
land and capital, which highlights the need for a better inclusion of small-scale producers
(Dufey et al., 2007a). Increasing economies of scale and land concentration have meant
that benefits of sugarcane bioethanol production for small land owners have so far been
limited and large farmers and industrialists have benefited more from the expansion of
the industry (Peskett et al., 2007). In contrast, in countries such as India and South Africa
small farmers are key players in the sugarcane sector. In India, they represent between 60
and 70 percent of the cane growers (Johnson and Rosillo-Calle, 2007). In Costa Rica, the
proportion of small producers in the sugarcane sector increased by 97 percent between
2000 and 2005 (Murillo, 2007).
Small farmers face several obstacles in trying to access supply chains. They trade-off high
transportation costs getting crops to processing plants with selling through middlemen
(Peskett et al., 2007; Rafi Khan et al., 2007). In India, farmers must access to irrigation to be
competitive, which is increasingly difficult and expensive due to growing water scarcity and
cost (ICRISAT, 2007). At processing plants they have to time delivery to fit daily plant capacity
and meet plant standards. Either way, small producers are price-takers (Peskett et al., 2007).
Box 3 highlights some of the challenges faced by sugarcane small farmers in Pakistan.
However, large-scale and small-scale systems are not mutually exclusive and can interact
successfully in a number of different ways (Dufey et al., 2007b). Some of the models for
partnership between large-scale and small-scale enterprises include outgrower schemes,
cooperatives, marketing associations, service contracts, joint ventures and share-holding
by small-scale producers (Mayers and Vermeulen, 2002). Concerning sugarcane, in Brazil
co-operatives operate in certain areas (Oxfam, 2008). In India some of the sugar mills are
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Box 3. Unfair distribution of benefits against small farmers - middleman in Pakistan.
In Pakistan, where bioethanol is produced from sugarcane molasses, middlemen play a key role
in sugarcane procurement and often end up exploiting small-scale farmers forcing them to sell at
distress prices. In collusion with mill owners, they orchestrate delays at the mill gate; the problem
becomes exacerbated during surplus years. The farmer has no option but to accept the price
offered (lower than the support price) or face further delays. Large farmers are better placed
as their crop represents a large proportion of the mill intake and they also have greater political
clout. Small farmers are indebted to middlemen for their consumption and input needs, which
also leads to under pricing. Further, a report by the Agricultural Prices Commission of Pakistan
indicates that the scales installed to weigh sugarcane do not provide correct readings. However,
given the high level of illiteracy among small-scale growers, such practices go undetected.
Moreover, mills are also known to make undue deductions contending that sugarcane quality is
low and contains high trash content.
Source: adapted from Rafi Khan et al. (2007).
cooperatives in which farmers also hold ownership shares in the factory (ICRISAT, 2007).
The South African sugar industry distinguishes itself by operating a successful small-scale
outgrower scheme, which supplies 11 percent of the country’s sugarcane under contract
farming arrangements to one of the three major mills (Cartwright, 2007).
The need for economies of scale to increase competitiveness constitutes a pressure to reduce
costs. The main mechanisms for doing this – introduction of improved varieties, switch away
from diversified production systems to monocropping, move to larger land holdings, and
shift to increasingly capitalised production - are difficult or risky for small producers. For
example, in Brazil, selection of improved cane varieties (e.g. energy cane) and investment
in irrigation have helped to improve yields but the benefits of these have mostly been felt on
plantations. Other mechanisms, such as increasing labour productivity without increasing
wages, are likely to be detrimental to poor households (Peskett et al., 2007). This presents
a serious challenge to identifying pro-poor biofuels production systems.
Analysis by a UN consortium suggests that efficient clusters of small and medium-scale
enterprises could participate effectively in different stages of the value chain (UN-Energy,
2007). The main challenge is how to provide appropriate policy conditions to promote valuesharing and prevent monopolisation along the chain (Dufey et al., 2007b). Controlling valueadded parts of the production chain ‘is critical for realising the rural development benefits and
full economic multiplier effects associated with bioenergy’ (UN-Energy, 2007). In countries
such as Thailand policy interventions are addressing the sharing of the earning between
sugarcane growers and producers (70% and 30%, respectively). However, for bioethanol
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manufactured directly from sugarcane juice, producers argue the Government has to come
with a better agreement as they have to invest on bioethanol plants (Gonsalves, 2006b).
At the international level this implies that the biofuels value chain must shift to the countries
that produce the feedstock.
Overall, economies of scale are important and small-farmers will need to adapt and get
organised towards that direction. Challenges and difficulties will be confronted and more
research is needed to understand the role partnership schemes (Dufey et al., 2007b).
3.4. Landlessness and land rights
The strength and nature of land rights are key determinants of patterns of land ownership
under biofuel production. As the above point suggests, the need of costs reduction offers
considerable incentives for large-scale, mechanised agribusiness and concentrated land
ownership. This is turn can displace small farmers and other people living from the forests
and depriving them from its main source of livelihoods. This may have devastating effects
on rural poverty. Indeed, the primary threat associated with biofuels is landlessness and
resultant deprivation and social upheaval, as has been seen for example with the expansion
of the sugarcane industry in Brazil (Worldwatch Institute, 2006; Dufey et al., 2007b) which is
summarised in Box 4. Johnson and Rosillo-Calle (2007) also highlight land related problems
in the African context, where the high proportion of subsistence farming and complexities
of land ownership under traditional land regimes make large acquisition of land, for largescale sugarcane operations, a highly controversial issue.
Box 4. Access, ownership and use of land in Brazil.
Biothanol production in Brazil has inherited problems faced by the sugar industry over the last
50 years, including violent conflict over land between indigenous groups and large farmers.
Problems stem from weak legal structures governing land ownership and use which have
increased land concentration, monoculture cropping and minimisation of production costs. Land
occupation planning is carried out at municipal level, but not all municipalities have developed
guidelines governing monocultures. Land concentration in Brazil is very high, with only 1.7% of
real estate covering 43.8% of the area registered. Land concentration and subsequent inequality
is increasing with expansion of monocropping areas, reduction of sugar mill numbers, growth in
foreign investment and land acquisition. The need of economies of scale for efficient sugarcane
production in part drives these effects.
Source: adapted from Peskett et al. (2007).
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Impacts of sugarcane bioethanol towards the Millennium Development Goals
Rossi and Lambrou (2008) note some gender-differentiated risks. Marginal lands are
particularly important for women. The conversion of these lands to energy crops might
cause displacement of women’s agricultural activities towards increasingly marginal lands,
with negative effects in their ability to meet household obligations. This highlights the
urgent need of a careful analysis of what the concept of ‘marginal’, ‘idle’ or ‘unproductive’
lands really entails. It is in these lands where most government are mandating biofuels to
be grown.
3.5. Quality of the employment
Sugarcane bioethanol will generate a range of employment opportunities, mostly in rural
areas, which is certainly good for poverty reduction. However there are limitations and tradeoffs. Firstly, there is concern about the quality of employment, whether self-employment
(small-scale farmers) or employment within large-scale operations (Worldwatch Institute,
2006; UN-Energy, 2007). Sugarcane harvesting is extreme physically demanding. Production
is highly seasonal and, in Brazil, for example, the ratio between temporary and permanent
workers is increasing. Low skilled labour dominates the industry and a high rate of migrant
labour is employed. In southern Africa the sudden influx of seasonal workers has had
negative effects on community cohesion, causing ethnic tension and disintegration of
traditional structures of authorities. Migrants behaviour is also linked with higher rates of
HIV infection around sugarcane plantations (Johnson and Rosillo-Calle, 2007).
Whilst over the latest years in some plantations in Brazil improvements in working conditions
have been done, in other plantations, sugarcane cutters continue to work in appalling
conditions. Cases of forced labour and poor working conditions within the sector are still
reported (Oxfam, 2008). Other problems include a lack of agreed or enforceable working
standards in many countries, and lack of labour representation (Dufey et al., 2007b).
Moreover, compared to other feedstocks (e.g. palm oil, castor oil, sweet sorghum) sugarcane
is less labour-intensive and thus provide less on-farm and off-farm employment (Dufey
et al., 2007b). The industry greater mechanisation in turn reduces labour demands. One
harvester can replace 80 cutters and thus facilitate the whole harvesting process (Johnson
and Rosillo-Calle, 2007). In Brazil mechanization of sugarcane harvesting has been driven by
increasing labour costs and more recently by legislation to eliminate sugarcane burning. Total
employment in the industry decreased by a third between 1992 and 2003 (ESMAP, 2005b).
Indeed sugarcane related unemployment is expected to become the key social challenge
faced by the sugarcane industry in Brazil (Dufey et al., 2007a). This can have devastating
effects on poverty levels as it is unemployment among the lower-skilled workers.
In order to balance trade-offs between environmental needs, mechanisation and
unemployment, Johnson and Rosillo-Calle (2007) propose the use of half-mechanisation
which was successfully used in Brazil as a transition towards full mechanisation. It consists
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in mechanical aid for the harvesting, in which a machine is used for cutting the cane
and workers are used to gather the crops. As the cutting of the cane is the hardest part
physically, the authors argue this system would also contribute to opening up the labour
force for women.
All in all, although recognising that many of the above mentioned issues are not exclusive
for sugarcane bioethanol, employment generation that leads to effective poverty reduction
requires addressing these problems.
3.6. Government support
Experience suggests the biofuels sector requires some form of policy support, at the very
least in the initial phases development. Even Brazil, the most efficient biofuel producing
country, still maintains a significant tax differential between gasoline and hydrous ethanol
to promote the sector (ESMAP, 2005b) and fixes a mandatory blend (between 20% to
25%). More generally, the PROALCOOL programme in the past required heavy support.
Between 1975 and 1987 it produced savings for US$ 10.4 billion but it costs were US$ 9
billion (World Watch Institute, 2006). Moreover, with falling oil prices, rising sugar prices,
and a national economic crisis the programme simply became too expensive and collapsed
by end of 1980s.
In many countries, the main rationale behind biofuels production is to decrease the costs
associated with imported fossil fuels. Among the costs of such a policy that need to be
accounted is the foregone duty on fuel imports, which results in a decline in government
revenues. For instance, in Brazil, the forgone tax revenue in the state of São Paulo, which
accounts for more than one-half of the total hydrous ethanol consumption in the country, was
about US$ 0.6 billion in 2005 (ESMAP, 2005b). In many developing countries a substantial
portion of public revenues are derived from import duties. In addition, the diversion of sugar
exports for bioethanol production for domestic markets means that countries may suffer
reductions in their export earnings. All these pose significant challenges in poorest countries,
where there are a multitude of urgent needs competing for scarce fiscal resources.
Another issue is that once granted and the biofuel industry has been launched, subsidies
are difficult to withdraw. A major challenge to reduce policy support is the vested interests
created in the domestic industry (Henniges and Zeddies, 2006).
On the other hand, the existence of contentious domestic policies and practices can
undermine industry development. For instance, Rafi Khan et al. (2007) and Gonsalves
(2006a) report the negative effects on bioethanol development of policy measures such as a
high central excise duty and sales tax on alcohol that exist in Pakistan and India, respectively.
The lack of policy provenance - reflected by the fact that the Pakistani government directed
the Petroleum Ministry (who houses the oil lobby) to develop the bioethanol conversion plan
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Impacts of sugarcane bioethanol towards the Millennium Development Goals
also constitutes an additional policy constraint. Pricing issues - whether to use bioethanol
international price or its cost of production - can also affect industry development (Rafi
Khan et al., 2007).
All the above suggest the promotion of a sugarcane bioethanol industry can become very
expensive, not only due to the high up front investments that are required but also due to
the financial resources that are needed to make it viable in the long term.
From a poverty reduction strategy point of view this means that governments should design
their sugarcane bioethanol policies so as to reach the desired target group. As ESMAP (2005b)
notes, resources that flow to agriculture all too often benefit politically powerful, large
producers and modern enterprises disproportionately at the expense not only of the society as
a whole, but of those that are supposed to be the main beneficiary group: smallholder farmers
and landless workers. Examples include untargeted producer subsidies and distortionary
subsidies for privately used inputs such as water and electricity. According to the same source,
promoting biofuels for energy diversification can make sense if large government subsidies
are not required. However, UN-Energy (2007) holds the view that if the large subsidies are
targeting small producers this may be money well spent. Governments tend to get higher
returns on their public spending by fostering small-scale production due to the lowered
demand for social welfare spending and greater economic multiplier effects.
Overall, governments need to conduct a careful assessment of the pros and cons of promoting
sugarcane bioethanol to support poor rural communities versus those of other alternatives.
Similarly, from a climate change mitigation strategy, although sugarcane bioethanol may
show the greatest greenhouse reductions compared to other first generation feedstocks, these
should be assessed against the costs of other policy instruments to achieve the same goal.
3.7. Market access and market entry barriers
The strategic nature of bioethanol implies the existence of some degree of protectionism in
almost any producing country. Protectionism is especially acute where energy security is
equated with self-sufficiency or where biofuels are promoted to help domestic farmers in
high-cost producing countries (Dufey et al., 2007b). The use of tariffs to protect domestic
biofuel industries is a common practice and, as Table 1 shows, these can be very high.
However, these tariffs are only indicative as their actual level applied vary widely as both
the European Union and the United States have trade agreements providing preferential
market access to several developing countries. In particular, the extra US$ 0.14 to each litre
(US$ 0.54 per gallon) of imported bioethanol on top of the 2.5 percent tariff applied by the
United States, it is said to be targeting Brazilian imports as it brings the cost of Brazilian
bioethanol in line with that produced domestically (Severinghaus, 2005). Tariff escalation,
which discriminates against the final product, can also be an issue, for example, where there
are differentiated tariffs on bioethanol and feedstock such as raw molasses (Dufey, 2006).
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Table 1. Import tariffs on bioethanol1.
Country
Import tariff
US
EU
Canada
Brazil2
Argentina
China
Thailand
India
2.5% + extra US$ 14 cents/litre (46% ad valorem)
€ 19.2/hl (63% ad valorem)
4.92 US$ cent/litre
20%
20%
30%
30%
186% on undenatureated alcohol
Source: adapted from Dufey et al. (2007b)
alcohol.
2 Temporarily lifted in February 2006.
1 Undenaturated
On the other hand, the planning of an export-oriented bioethanol industry based on the
rationale of preferential market access is a risky strategy. As Box 5 suggests for Pakistan,
trade preferences can be withdrawn at any time with devastating effects on the industry.
Subsidies is another key concern. In industrialised countries, government support for the
domestic production of energy crops, the processing or commercialisation of biofuels seems
to be the rule (Dufey, 2006). Amounts involved are enormous. In the United States, Koplow
(2006) estimated that subsidies to the biofuels industry to be between US$ 5.5 billion and
US$ 7.3 billion a year. In the European Union, Kutas and Lindberg (2007) estimated that
total support to bioethanol amounted € 0.52/litre.
The impacts these policies have on the developing countries competitiveness and on their
potential for poverty reduction needs to be understood as domestic support in these
countries is likely to be very limited. Moreover, subsidies impacts on environmental
sustainability are also questionable as they promote bioethanol industries based on the
less efficient energy crops and with the least greenhouse gases reductions such as maize
and wheat (Dufey, 2006).
The proliferation of different technical, environmental and social standards and regulations
for biofuels – without a system for mutual recognition – cause additional difficulties. For
instance, at present not all biofuels are perceived as ‘sustainable’ especially those coming from
overseas. As a consequence, several initiatives towards the development of sustainability
certification for both bioethanol and biodiesel have started. Some of them are led by
governments (e.g. the United Kingdom, Netherlands and the European Union); others by
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Impacts of sugarcane bioethanol towards the Millennium Development Goals
Box 5. The elimination of Pakistan from the EU GSP.
Until recently, Pakistan was the second largest industrial alcohol exporter to the EU after Brazil,
under the General System of Preferences (GSP). In May 2005, the Commission of Industrial
Ethanol Producers of the EU (CIEP) accused Pakistan and Guatemala (the largest duty free
exporters for the period 2002-2004) of dumping ethyl alcohol in the EU market, causing material
harm to domestic producers. The Commission dropped proceedings a year later when full custom
tariffs were restored on Pakistani imports. Later, following a complaint lodged by India at the
World Trade Organization (WTO), a panel concluded that by granting tariff preferences to 12
countries under this special arrangement the EU was violating GATT/WTO preferential treatment
obligations. The EU consequently removed Pakistan from the GSP. In the revised GSP regime, the
anti-drug system has been replaced by GSP Plus, for which Pakistan does not qualify.
Elimination of Pakistan from the GSP had devastating effects on the local industry. Distilleries
begun to suffer important losses and some had no option but to cease operations. Whilst
between 2002 and 2003, the number of distilleries in the country increased from 6 to 21, the
more stringent EU tariff measures together with a rise in molasses exports, the distilleries were
soon running idle capacities. Currently, at least 2 distilleries have shut down, with another 5
contemplating that option.
Source: adapted from Rafi Khan et al. (2007).
NGOs (e.g. WWF); and also by Universities (e.g. Lausanne University). These schemes tend
to focus on traditional environmental and social aspects of feedstocks production, with
several of them including greenhouse emission issues and with some few of them expanding
to food security concerns. Although environmental and social assurance is needed in the
industry, where these schemes are developed by importing nations, with little participation
by producing country stakeholders, insufficient reflection of the producing countries’
environmental and social priorities and without mutual recognition between them, they
are bound to constitute significant trade barriers. Moreover, the experience with assurance
schemes in the agriculture and forestry sector indicates that the complex procedures and
high costs usually associated with them have regressive effects in detriment of small and
poorest producers in developing countries. All in all, sustainability standards for bioethanol
trade are to become more and more important. Countries wanting to benefit from bioethanol
exports need to invest in the development of robust and credible certification systems that
satisfy importing countries requirements.
Overall, it is widely agreed that developing countries would benefit from enhanced bioethanol
trade and therefore the need to eliminate trade barriers.
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3.8. Improving efficiency, access to technology, credit and channelling investment
The development of a successful bioethanol sector goes beyond having available land, cheap
labour and good climate. It crucially depends on countries’ domestic capacity to expand
production efficiently, accessing the technology and assuring best practice. Indeed, Brazil’s
success in developing an efficient bioethanol industry is in a large extent explained by the
enormous endogenous efforts devoted to R&D, capacities building and infrastructure (Dufey
et al., 2007a). This implies that having a number of technical skills for research, technology
transfer as well as access to credit are critical issues. Moreover, those countries wanting to
develop an export oriented sector also need to be in compliance with the relevant technical
standards in importing markets and to invest in suitable transport infrastructure (roads,
water ways and ports) to reach exports markets. Countries also need to have sufficient
capacity in policy implementation and project management to run biofuels production and
processing effectively (Dufey et al., 2007b).
At present, many countries foresee a major participation of the sugar industry in bioenergy
production. However, the current low efficiency and productivity of the sector in many
of them implies that major changes to the industry’s structure will be needed to make
sugarcane an important feedstock (FAO, 2007). In countries where bioethanol is produced
from molasses and wanting a significant scale of production, efforts will need to be made
to produce from sugarcane juice, which is a relatively more efficient source of bioethanol
and capable of supplying larger volumes (Woods and Read, 2005). Other specific needs
include adaptive agricultural research and extension development for enhanced transfer
of bioethanol technologies. Investment is also important to bring agricultural practices up
to the required level of technical capacity, scale of operations, and intensity of production
(Johnson and Rosillo-Calle, 2007)
4. Conclusions
Sugarcane bioethanol can contribute to the achievement of several Millennium Development
Goals through a varied range of environmental, social and economic advantages over fossil
fuels. The highest impact on poverty reduction is likely to occur where sugarcane bioethanol
production focuses on local consumption, involving the participation and ownership of
small farmers and where processing facilities are near to the cultivation fields.
Realising the greatest potential of sugarcane bioethanol on poverty reduction implies that
several challenges will need to be confronted and dealing with serious trade-offs. Especially
tough will be those related to efficiency gains through large-scale operations, mechanisation
and land concentration versus small farmers inclusion. Economies of scale are important
and small farmers will need to adapt and get organised towards that direction. Likewise, the
resulting unemployment among the lower-skilled workers is a key aspect to be addressed.
Whilst the domestic use of sugarcane bioethanol may imply opportunities in terms of
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Impacts of sugarcane bioethanol towards the Millennium Development Goals
general well-being, the increasing use of marginal land for biofuels cultivation may imply
negative impacts among the most vulnerable such as women. From a poverty reduction
strategy this means that governments should explicitly design their sugarcane bioethanol
policies to provide the right environment to promote business models that maximises rural
development, small farmer inclusion and equitable access to ownership and value along
the chain. One example in that direction can be the use of tax-breaks for companies that
include small producers among their suppliers, which is already being used in the context
of biodiesel in Brazil through the PROBIODIESEL programme.
The impacts of sugarcane bioethanol on food security are less clear. Regarding food
availability and compared to other feedstocks, sugarcane bioethanol would provide better
opportunities to meet food security as long as it creates less competition for land and crowd
out other crops. However, from an accessibility point of view, it would provide more limited
opportunities to the extent that its production is less likely to involve small or poorest
farmers. Overall, more research is needed to understand these linkages.
From an environmental sustainability perspective, compared to other first generation
biofuels, sugarcane bioethanol offers opportunities to achieve one of the greatest reductions
in greenhouse emissions under certain circumstances. However, available estimations need
to be revised to include the emissions directly and indirectly associated with changes in
land use and cover. Similarly, biodiversity impacts linked to changes in land use and cover
especially those associated with the substitution effect appear as crucial environmental
aspects to be addressed and more research to understand them is needed. Likewise, impacts
on water, especially in the context of dry and semi-dry lands, are other key aspects that
deserve better analysis. Only the adequate understanding and management of these impacts,
using a life cycle approach, will help to improve the environmental sustainability of sugarcane
bioethanol and thus achieving the Millennium Development Goal on environmental
sustainability.
In some contexts, the promotion of a sugarcane bioethanol industry can be a very expensive
means of achieving poverty reduction and promoting environmental sustainability.
Governments need to conduct a careful assessment of the pros and cons of promoting
sugarcane bioethanol to support poor rural communities versus those of other policy
choices. Similarly, from a climate change mitigation strategy, although under certain
circumstances sugarcane bioethanol shows the greatest greenhouse reductions compared
to other first generation feedstocks, these should be assessed against the costs and benefits
of other policy instruments for achieving the same goal.
Another crucial issue involved in realising the full potential of sugarcane bioethanol is the
building of an adequate set of national capabilities on technical skills, policy implementation,
project management and development of R&D programmes. These should come hand in
hand with promoting access to technology, credit and finance as well as the provision of
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Chapter 9
some minimum transport infrastructure. For those countries wanting to take advantages
of an export oriented industry, capacities building on standard setting and compliance as
well as the negotiation of favourable terms of trade constitute other key aspects.
Policy coherence is another issue. The promotion of a sugarcane bioethanol sector that
contributes to sustainable development and poverty reduction should be aligned with
existing relevant national and international policies and frameworks such as Sustainable
Development Strategies, Poverty Reduction Strategies, Environmental and Social Impact
Assessments, the Kyoto Protocol or the Convention on Biological Biodiversity. Coordination
therefore is required among different government bodies (e.g. Ministry of Agriculture,
Energy, Environment, Industry, Trade, etc.), levels and actors.
Finally, at the international level, cooperation is also crucial for the development of a
sugarcane bioethanol industry oriented towards poverty reduction and environmental
sustainability. South-South cooperation can play an important role in overcoming many of
the technical challenges. Countries can benefit from the technical and scientific knowledge
of Brazil, which is at the forefront of the industry. One example in that sense is the illustrated
by the Brazil-UK-Africa Partnership for bioethanol development. International financial
institutions can help, for example, by mitigating political risk for project development in
developing countries. Elimination of trade barriers is another issue to be addressed by
governments to enhance development opportunities associated with sugarcane bioethanol.
This would be also aligned with the last Millennium Development Goal that calls to ‘develop
a global partnership for development’.
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Why are current food prices so high?
Martin Banse, Peter Nowicki and Hans van Meijl
1. World agricultural prices in a historical perspective
World agricultural prices are very volatile which is due to traditional characteristics of
agricultural markets such as inelastic (short run) supply and demand curves (see, Meijl et
al. 2003).13 The volatility is also high because the world market is a relatively small residual
market in a world distorted by agricultural policies.14 The combination of high technological
change and inelastic demand cause real world prices to decline in the long run (trend). The
prices, however, of many (major) agricultural commodities have risen quickly over recent
years (see Figure 1).
Recent increase in agricultural prices are strong, but even with the increase that we have
observed in the last three years, real agricultural prices are still low compared to the peaks
in prices of the mid-70s. Local prices are linked with these world prices. The transmission
effect depends on the transparency of markets, market power and accessibility
13 ‘World food prices are instable and will remain unstable in the future. Forecast errors are large in predictions
of world prices. There are always unexpected events in important drivers such as yields which are dependent on
weather, plagues and diseases’ (See Van Meijl et al., 2003).
14 Trade share (2006) in global production: rice (7%), cheese (7%), coarse grains (11%) and wheat (20%), FAO
Statistics.
1,600
1,400
1,200
1,000
800
600
400
200
0
1960
1965
1970
Maize
1975
1980
Wheat
1985
Rice
1990
1995
Palmoil
2000
2005
Soybeans
Figure 1. Development of world agricultural prices, 1960–2007, USD/ton, in constant USD (1990).
Source: World Bank data base (2008).
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Chapter 10
Figure 2 depicts the price index for food commodities along with an index for the average
of all commodities and an index for crude oil. Although the food commodity index has
risen more than 60 percent in the last 2 years, the index for all commodities has also risen
60 percent and the index for crude oil has risen even more (see also Trostle, 2008). Since
1999 food commodity prices have risen 98 percent (as of March 2008); the index for all
commodities has risen 286 percent; and the index for crude oil has risen 547 percent. In
this perspective, the recent rise in food commodity prices is moderate. Figure 3 shows that
spot prices in early 2008 for soybean and wheat are declining again while the spot prices
for rice and crude oil continue to rise. The prices of wheat and soybeans declined by almost
30% and almost 20%, respectively, since their peak at the end of February this year.
700
600
500
400
300
200
100
0
1992
1994
1996
Oil
1998
2000
2002
All commodities
2004
2006
2008
Food commodities
Figure 2. Index of oil, food and all commodities, 1992-2008, January 1992=100. Source: International
Monetary Fund: International Financial Statistics.
600
500
400
300
200
100
0
2005
2006
Crude oil, $/bbl
Maize, $/mt
2007
2008
Wheat, $/mt
Soybeans, $/mt
Figure 3. Daily price notations for crude oil, wheat, maize and soybeans; spot prices, 2005-2008, at
current USD. Source: World Bank data base (2008) from January, 1 2005 to May, 15 2008.
228
Sugarcane ethanol
Why are current food prices so high?
However, although real food prices are not extremely high in a historical perspective and
other commodities have risen more, an increase in the price of food – a basic necessity
– causes hardships for many lower income consumers around the world. This makes foodprice inflation socially and politically sensitive. This is why much of the world’s attention is
now focused on the increase in food prices more than on the more rapid increase in prices
of other commodities, (see Trostle, 2008: 4).
The question on the minds of many consumers around the world is, ‘Will food prices drop
again this time?’ Or, stated another way, ‘Is the current price spike any different from those
of the past, and if so, why?’
2. Long run effects
2.1. Long run drivers of demand15
Population and macro-economic growth are important drivers of demand for agricultural
products. In past years, rapid population growth has accounted for the bulk of the increase
in food demand for agricultural products, with a smaller effect from income changes and
other factors (Nowicki et al., 2006)16. The world’s population growth will fall to about 1%
in the coming ten years. Continued economic growth is expected over the coming period
in almost all regions of the world and this driver of demand will become more important
than population growth in the future (see Figure 4).
2.2. Expected population developments in period 2005-2020
• The world’s population growth will fall from 1.4% in the 1990-2003 period to about 1%
in the coming ten years. This is mainly due to birth or fertility rates, which are declining
and are expected to continue to do so.
• Almost all annual population growth will occur in low and middle income countries,
whose population growth rates are much higher than those in high income countries.
• Europe’s share in world population has declined sharply and is projected to continue
declining during the 21st century.
• Population growth in Europe is very low (0.3% yearly for EU-15: old EU member states)
or slightly negative (-0.2% for EU-10: new EU member states).
• The uncertainty with regard to birth and death rates at world or regional level is not
too large. However, migration flows between countries and regions are much more
uncertain.
15 Based
on Scenar 2020 (Nowicki et al., 2006).
16 Projections for population and GDP for the EU member states are taken from a study of the Economic Policy
Committee of the European Commission called ‘The 2005 EPC projection of age-related expenditure: agreed
underlying assumptions and projections methodologies, 2005’. The projections for the rest of the world are based
on assumptions used in the OECD and USDA agricultural Outlooks.
Sugarcane ethanol
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Chapter 10
7
Population
6
GDP
5
4
3
2
1
0
-1
1970-1990
EU15
1990-2005
EU10
2005-2020
HDC
1970-1990
C&S Amer
1990-2005
Asia
2005-2020
Africa
Figure 4. World population and GDP growth (annual growth %). Source: USDA for 1970-1990 and
1990-2005. Projections for 2005-2020 derived from Scenar 2020, Nowicki et al. (2006). HDC =
High Income Developed Countries, C&S Amer = Central and South America
2.3. Global income growth
• Robust economic growth is expected over the coming period in almost all regions of
the world in the baseline scenario (see Figure 4).
• Economic growth will be considerably higher for most of the transitional and developing
countries than for the EU-15, the United States and Japan, in particular for Brazil, China,
India and the new EU member states. Incomes in Europe are expected to increase slightly
over the coming years.
• Annual income growth in Europe is about 2% for EU-15 and 3.8% for EU-10.
• World and EU economic growth in the future stays uncertain and depends on the
amount of investments in education and research, on technological opportunities, on
the degree of (labour) participation in the political, societal and market arenas, and on
the liberalisation of world commodity and factor markets.
The robust growth of income per capita leads to more ‘luxury’ consumption in developed
countries. This implies more convenience food, processed products (ready to eat) and food
safety, environmental and health concerns. In developed countries the total amount of food
consumed will only grow in a limited manner. However, in developing countries a higher
income induces more consumption and a shift to more value-added products. Important is
the switch from cereals to meat consumption, as an increased demand for meat induces a
relatively higher demand for grain and protein feed. To produce 1 kg of chicken, pork and
beef, respectively 2.5 kg, 6.5 kg and 7 kg of feed are required.17
17 The
numbers describe upper-bound estimates of conversion rates: 7 kg of maize to produce 1 kg of beef, 6.5
kg of maize to produce 1 kg of pork, and 2.6 kg of maize to produce 1 kg of chicken (Leibtag, 2008). Modern
technology, however, require much less feed especially in pork production; here average feed conversion rates
are between 3.2-2.6 kg of feed per kg of meat.
230
Sugarcane ethanol
Why are current food prices so high?
2.4 Long-term drivers of supply
With regard to grain and oilseed production, yield and area developments are important
drivers of supply. Figure 5 shows that production growth was almost totally determined by
yield increase while the total area harvested was more or less constant. The growth in yields
declined from 2% per year in the 1970-1990 period to 1.1% in the 1990-2007 period. USDA
expects the growth to decline to 0.8% per year for the period 2009-2017 (USDA, 2008). At
the global scale, crop production area increased in the 1970-2007 period by 0.15% per year,
and USDA expects the area to grow by 0.4% per year in the period 2007-2017.
Figure 6 shows that growth rates of yields for major cereals in developing countries are
slowing. It should be mentioned that the decline in annual growth rates is not necessarily
related to a decline in absolute yield growth per annum. An important explanation for
the decreasing yield growth rates might be the declining public agricultural research and
development spending over time in both developing and developed countries (Figure 7).
Although private sector research has grown, private sector R&D is mostly cost reducing\
short run oriented instead of public R&D, which is often more yield enhancing\long term
oriented.
• The direct link between R&D spending and yield growth had been intensively discussed
amongst agricultural scientists and is not fully clear.
• The general outcome of this discussion is that an additional growth in yield rates requires
more than additional spending in capital stock but also investment in human capital
stock and improvements in market institutions
260
240
220
200
180
160
140
120
100
80
1970
1975
1980
1985
1990
1995
Production
Yield
Per capita production
2000
2005
2010
2015
Population
Area harvested
Figure 5. Development of world grain and oilseed production. Source: USDA Agricultural Projections
to 2017.
Sugarcane ethanol
231
Average annual growth rate (%)
Chapter 10
6
maize
rice
wheat
5
4
3
2
1
0
1963 1967 1971 1975 1979 1983 1987 1991 1995 1999 2003
Figure 6. Development annual yields for selected cereals in developing countries. Source: World
Development Report 2008.
Average annual growth (percent per year)
12.0
1976-81
1981-91
1991-2000
10.0
8.0
6.0
4.0
2.0
0.0
Asia-Pacific
-2.0
Latin America
and the
Carribean
Sub-Saharan
Africa
Developing
countries
High-income
countries
Figure 7. Public Agricultural R&D Spending Trends, 1976-2000. Source: Pardey et al. (2006).
3. What explains the recent increase in agricultural prices?
A combination of record low global inventory levels, weather induced supply side shocks,
surging outside investor influence, record oil prices and structural changes in demand for
grains and oilseeds due to biofuels have created the high prices. The question is whether it
is a coincidence that the past and current high price levels coincide with high oil prices or
whether other reasons for the current price peak are more important.
232
Sugarcane ethanol
Why are current food prices so high?
3.1. Effects on the supply side
As mentioned above the variation of yields due to climatic conditions, the development of
input prices – fertilizer, diesel and pesticides – as well as the level of political support are
the main drivers of supply. The following items provide some information on these points
(Figure 8):
• Poor harvests in Australia, Ukraine and Europe for wheat and barley. According to
FAO statistics, these three regions contributed on average 51% of total world barley
production and 27% of total world wheat production for the period 2005-2006.
• Lower harvests in wheat and barley are more than compensated by a bumper harvest
for maize worldwide.
– Therefore, world cereal production increased in total even in 2007.
– The bumper harvest in maize kept maize prices low and the wheat-maize spread
increased significantly (Figure 3).
– Only recently have maize prices also strongly increased.
• Higher energy prices lead to higher food prices as costs (e.g. fertilizer, processing, and
transport) increase. Higher transport costs induce higher price effects as distances
increase.
• CAP policies such as mandatory set-aside regulation or production quota restrained
supply. Furthermore, there was a change from price to income support and compensatory
payments became decoupled, set aside was introduced and export subsidies were
diminished. Some of these measures limited supply within the EU. However, the general
aim of the last CAP reforms was an enforcement of farmers’ ability to react to market
signals instead of following policy signals given by market price support. Measures
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Australia
Canada
EU (27)
US
Figure 8. Deviation from trend in yields (wheat and coarse grains) in tons/ha. Source: OECD-FAO
Agricultural Outlook 2008-2017 (2008).
Sugarcane ethanol
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Chapter 10
aimed to restrict supply, e.g. production quota or set-aside requirements, are instruments
designed for a world with declining prices, but which may act to reinforce prices in case
of food shortages.
• Low prices in the last decades did not provide an incentive to invest in productivity
enhancing technologies.
3.2. Effects on the demand side
Compared to the variability of agricultural supply, the demand of agri-food products is
rather inelastic. For most agricultural commodities price and income elasticities are small,
i.e. long-term demand for primary agricultural products is more determined by population
growth and less by income growth. Within the last years the demand for agri-food products
have been determined by the following driver:
• Constant demand in Europe and Northern America with an increase in demand in
Asian countries
• Change in diet in emerging economies.
• Additional demand for biofuels:
– 5% of global oilseed production is processed to biodiesel or is used directly for
transportation.
– 4.5% of global cereal production is used for ethanol production.
– Therefore, this marginal extra demand triggered the markets.
– However, biofuels are not new. Ethanol based on sugarcane exists in an economically
profitable way in Brazil for a long time.
– Increasing food and feedstock prices make biofuels less profitable and food more
profitable. This shifts production back to food (in US is this already visible; Trostle,
2008, p.17). With current high prices for soybeans in the US margins for biodiesel
became already negative and the biodiesel production slowed down [see presentation
of Gerald A. Bange (USDA) on the Agricultural Markets Roundtable held April 22,
2008 Washington, DC at the Commodity Futures Trading Commission].
The development of both – supply and demand side – contribute to the development of
stocks which is illustrated in the following Figure 9. The trend of a declining stock to use
ratio as has increased and stocks for wheat are currently running on empty. This implies that
all the shocks mentioned above could not be mitigated by using stocks but lead immediately
to price increases. Furthermore, it enabled speculation (with stocks available there would
have been less room for speculation)
234
Sugarcane ethanol
Why are current food prices so high?
50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
6
1
00
00
/2
05
20
00
20
/1
95
/2
99
99
19
19
90
/1
/1
Wheat
6
1
6
98
1
85
19
80
19
/1
75
19
/1
97
98
6
1
97
/1
70
19
/1
65
19
19
60
/1
96
96
1
6
0%
Corn
Figure 9. Development of stock to use ratio, 1960-2007. Source: US Department of Agriculture PSD
View database, June 2008.
3.3 Policy responses to rising food prices
• The rapidly increasing world prices for food grains, feed grains, oilseeds, and vegetable
oils are causing domestic food prices at the consumer level to rise in many countries. In
response to rising food prices, some countries are beginning to take protective policy
measures designed to reduce the impact of rising world food commodity prices on their
own consumers. However, such measures typically force greater adjustments and higher
prices onto global markets.
• In the fall of 2007, some exporting countries made policy changes designed to discourage
exports so as to keep domestic production within the country. The objective was to
increase domestic food supplies and restrain increases in food prices. Table 1 depicts a
partial list of these policy changes.
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Table 1. Policy responses to rising food prices.
Eliminated export subsidies:
China eliminated rebates on value-added taxes on exported grains and grain products. The rebate
was effectively an export subsidy that was eliminated.
Export taxes:
China, with food prices still rising after eliminating the value-added tax rebate, imposed an export
tax on a similar list of grains and products.
Argentina raised export taxes on wheat, maize, soybeans, soybean meal, and soybean oil.
Russia and Kazakhstan raised export taxes on wheat.
Malaysia imposed export taxes on palm oil.
Export quantitative restrictions:
Argentina restricted the volume of wheat that could be exported even before raising export taxes
on grains.
Ukraine established quantitative restrictions on wheat exports.
India and Vietnam put quantitative restrictions on rice exports.
Export bans:
Ukraine, Serbia, and India banned wheat exports.
Egypt, Cambodia, Vietnam, and Indonesia banned rice exports. India, the world’s third largest
rice exporter, banned exports of rice other than basmati, significantly reducing global exportable
supplies.
Kazakhstan banned exports of oilseeds and vegetable oils. Early in 2008, importing countries also
began to take protective policy measures to combat rising food prices. Their objective was to make
high-cost imports available to consumers at lower prices. A partial list of policy changes follows.
The following countries reduced import tariffs:
India (wheat flour).
Indonesia (soybeans and wheat; streamlined the process for importing wheat flour).
Serbia (wheat).
Thailand (pork).
EU (grains).
Korea and Mongolia (various food commodities)
Subsidizing consumers:
Some countries, including Morocco and Venezuela, buy food commodities at high world prices and
subsidize their distribution to consumers.
Other decisions by importers:
Iran imported maize from the United States, something that has occurred rarely – only when they
could not procure maize elsewhere at reasonable prices.
The policies adopted by importing countries also changed price relationships in world markets. Their
policy changes increased the global demand for food commodities even when world prices were
already rapidly escalating.
Source: Trostle (2008).
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Why are current food prices so high?
3.4. Other effects
• USD exchange rate developments. World prices are denominated in dollars and the
dollar depreciated against most currencies. The increase in prices in other currencies
is therefore much less.
Speculation:
• In recent months spot and future prices do not fully converge.
• Future prices remain higher than prices on spot markets.
– Reason for this development:
› Most hedging (90%) is Index-hedging, i.e. ‘traditional’ short- and long hedging
does not dominate the price development in the future markets.
› Thus, if everybody expects high prices, then future prices tend to be higher than
the spot prices.
– So, part of current high prices can be attributed to this ‘bubble’.
• Difficult to estimate the impact of speculation in this story.
– The crises on the financial markets are diverting funds away from traditional
financial institutions leading to a large pool of funds available for investments in
other markets.
– There is definitely a impact of speculation in current high prices
– Hard to say it makes X %.
– Growing volatility in food markets due to the fact that most of hedging is based on
index funds and not anymore on the ‘traditional’ short and long hedging. This share
is less than 10% in total market volume.
– An example for the current volatility: In the 1st week of March the fluctuation of
maize prices was more than 150 USD/t, which is more than last year’s average maize
price!
• Impact of speculation on current spike in agricultural prices is difficult to quantify.
Figure 10 shows the composition of the maize futures markets broken down between
commercial merchants, managed money funds and commodity index traders together
with the price development in USD per bushel of maize (right-hand scale).
– It clearly shows that not only the ‘speculative’ index and fund hedging but also the
increase in short futures by commercial merchants contributed to the dramatic
increase in maize future prices.
– However, the managed money funds which are mostly pension funds – which
diversify their portfolio now also to agricultural commodities – cut down their
purchase of additional contracts on long position when prices increased dramatically
(Figure 10).
– A formal assessment is hampered by data and methodological problems, including
the difficulty of identifying speculative and hedging-related trades.
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237
6.00
5.75
5.50
5.25
5.00
4.75
4.50
4.25
4.00
3.75
3.50
3.25
3.00
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2.50
1/
1/ 3
2
2/ 2
26
2/
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30
4/
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5/
5/ 4
22
6/
7/ 8
1
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8/
16
9/
9/ 4
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/2
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/
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/
12 28
/1
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4/
1
500
400
300
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0
-100
-200
-300
-400
-500
-600
-700
-800
-900
Dollars per bushel
Long
Short
Thousand contracts
Chapter 10
Commercial merchants
CIT
Managed money funds
CBOT nearby future
Figure 10. CBOT Corn Market Composition January 2007 – April 2008. Source: Derived from a
presentation of Dave Kass at the Agricultural Markets Roundtable held April 22, 2008 Washington,
DC at the Commodity Futures Trading Commission.
– A number of recent studies seem to suggest that speculation has not systematically
contributed to higher commodity prices or increased price volatility.
› For example, a recent IMF staff analysis (September 2006 World Economic
Outlook) shows that speculative activity tends to respond to price movements
(rather than the other way around), suggesting that the causality runs from prices
to changes in speculative positions.
› The Commodity Futures Trading Commission has argued that speculation
may have reduced price volatility by increasing market liquidity, which allowed
market participants to adjust their portfolios, thereby encouraging entry by new
participants.
4. First quantitative results of the analysis of key driving factors
• OECD Outlook 2007-2017: The OECD performed some scenarios to see the impact of
various drivers on their Outlook projection (OECD-FAO, 2008). This analysis highlights
the outcome of a situation where biofuel policies are in place under the reference scenario
and different assumptions are moderate, e.g. income growth, development of crude oil
prices, etc.:
– If biofuel production stays at its 2007 level, then world wheat prices would be 5% lower,
maize 13% lower and vegetable oil 15% lower compared to the reference scenario
where biofuel production in 2017 more than doubles relative to the 2007 level.
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Why are current food prices so high?
Wheat
0%
-5%
-10%
-15%
-20%
-25%
-30%
-35%
-40%
-45%
Maize
Vegetable oil
Scenario 5 : Scenario 4 and yields for wheat, oilseeds and coarse grains 5 % higher
than over the projection period
Scenario 4 : Scenario 3 and Progressive appreciation of the USD exchange rates to
reach 10% higher rates in 2017
Scenario 3 : Scenario 2 and Lower income growth in EE5 countries
(half annual growth rate)
Scenario 2 : Scenario 1 and Oil price constant at 2007 level (72$)
Scenario 1 : Biofuel production constant at 2007 level
Figure 11. Sensitivity on analysis of world price changes. Source: OECD-FAO Agricultural Outlook
2008-2017. Highlights. (2008).
– A constant crude oil price implies 10% lower prices for all three commodities, due
to the fact that the assumed high crude oil price under the reference scenario will
make biofuel crops more profitable.
– Lower income growth is especially relevant for vegetable oils (more than 10%).
– A stronger US dollar of 10% leads to about 5% lower prices for wheat, maize and
vegetable oil relative to the baseline.
– Higher growth rates in yields for important biofuel crops will lower the world market
prices for their production by more than 5% for wheat and maize.
These results are inline with our own results on the impact of biofuel policies, which are
presented in Figure 12.
• International Food Policy Research Institute (IFPRI) study (e.g. Von Braun et al., 2008).
– The percentage contribution of biofuels demand to price increases from 2000-07 is
the difference between 2007 prices in the two scenarios, divided by the increase in
prices in the baseline from 2000-2007.
– The increased biofuel demand between 2000 and 2007, compared with previous
historical rates of growth, is estimated to have accounted for 30 percent of the increase
in weighted average cereal prices during 2000-07.
› Maize – 39%.
› Rice – 21%.
› Wheat – 22%.
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160
actual biofuel growth, 2000-2007
continuation of 1990-2000 biofuel growth
150
140
130
120
110
100
2000
2001
2002
2003
2004
2005
2006
2007
Figure 12. Biofuels: Impact on world cereal prices since 2000. Source: Impact Simulations 2008.
IFPRI.
– Rapid growth in biofuel demand has contributed to the rapid rise in cereal prices,
but it has not been a dominant driving force in the 2000-07 period, except perhaps
in the case of maize.
– The fundamentals of supply and demand seem to be playing more of a role in the rapid
increase in prices during this period, especially for commodities like rice and wheat.
– After 2007 prices increases – for rice in particular – seem to be driven by the relatively
‘thin’ nature of the rice market with a limited amount of international trade compared
to total production.
– Unilateral trade policy actions of individual Asian countries, which have sought to
put into place export bans and import subsidies for rice.
– Speculative trading and storage behaviour; private operators taking advantage of
opportunities.
• Agri-Canada quantified the impact of all the policy responses (Figure 13). The impact
of policies added a few percent for almost all commodities, except for rice where the
impact is substantial (16%).
Experts are pointing out that it is hard to quantify the separate impacts. The contribution
of biofuel demand to the increase in average cereal prices of 30% presented by IFPRI was
criticized by some colleagues. Some find it too high, other too low. However, all studies
point out that a combination of factors was responsible for the rise. The analyses of OECD,
FAPRI and also of Banse et al. (2008a,b) indicated that the impact on world price levels is
commodity specific. For maize the impact is relatively high due to the fact that most US
ethanol production is maize-based. For other cereals – e.g. wheat and rice, where the use for
biofuels is almost zero – only indirect effects over the land use affects the world price level.
For those commodities an estimated increase of 30% – as indicated in the IFPRI estimates
– seems to be rather high.
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Why are current food prices so high?
18
16
14
12
10
8
6
4
2
0
Wheat
Maize
Rice
2007-08
Oilseeds
Veg.oil
2008-09
Figure 13. Impact of export restriction policies on world prices. Source: Agriculture and Agri-Food
Canada, unpublished.
5. The future
After the discussion of those driving elements which contributed to the current spike in
food prices this section depicts some elements which might contribute to the long-term
development of agri-food prices. This sections also allows to identify possible solutions for
the current crisis on world food markets.
• High prices are their own worst enemy. Increased profit margins entice entrepreneurial
investment, which results in increased production. Lower market prices inevitably
follow. The ‘invisible hand’ of Adam Smith ensures that winners’ gains and losers’ losses
will be temporary, as entrepreneurs correct market imbalances. In the USA, in the 2008
spring planting farmers are shifting from maize to wheat and soybeans, setting the prices
of the latter on a downward trajectory and stabilising the price of the former.
• Higher prices induce more production as planted areas increase and available arable land
will be used more intensively. Therefore, the current situation is not structural and as
a result prices will go down again. However, first stocks have to be built up again. Both
effects take some time. In Brazil and Russia there are ample opportunities as additional
land can be taken into production, whereas in many other countries production can
only be higher due to intensification. According to USDA analyses, Russia, Ukraine and
Argentina can become one of the world’s top grain exporters.
• R&D investments in agriculture (e.g. yields, etc.) become more profitable with higher
food prices.
• Strategic stocks are essential to limit price volatility in world agricultural markets, but
they are costly.
• The expected impact on world prices of the 10% EU-biofuel directive and the various
global biofuel initiatives is depicted in the graph below (Banse et al., 2008a,b). If all
initiatives are implemented together and technological change stays on the historic trend,
Sugarcane ethanol
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Chapter 10
20%
15%
10%
5%
0%
-5%
-10%
-15%
Cereals
Oilseeds
Reference
Biofuel, EU
Sugar
Crude oil
Biofuel, global
Figure 14. Change in real world prices, in percent, 2020 relative to 2001. Source: Banse et al.
(2008a,b).
then the impact on world prices is substantial and the long term trend of declining world
prices in the reference scenario might be dampened or reversed. The arrival and impact
of second generation biofuels is uncertain. According to Banse et al. (2008a,b), biofuels
lead to higher agricultural income, land use and land prices, and a loss of biodiversity.
Development of oil prices is crucial for the development of biofuels. Some experts point
that prices stay high due to increased demand in Asia and depleting supply resources.
Others indicate that this is a temporary situation as capacity is lacking at the moment due
to too few investments in the past. If oil prices stay high, food and energy markets will be
more interlinked. The oil prices will then put both a floor and a ceiling18 for prices in the
food markets (Schmidhuber, 2007). As energy markets are more elastic, the long-term
trend of food prices might be changed (less negative to positive dependent on development
oil price).
• High feedstock prices make biofuels less profitable (ceiling effect), as does a low oil
price (floor effect). Even at current level of crude oil prices of 120 USD per barrel almost
no biofuels are economically viable without policies. A low oil price implies that only
biofuels will be produced under mandates or that they are heavily subsidized. Without
an increase in oil prices the impact of biofuels is therefore limited to the impact of filling
the mandates.
18 Ceiling price effect: as feedstock costs are the most important cost element of all (large scale) forms of bioenergy
use, feed stock prices (food and agricultural prices) cannot rise faster than energy prices in order for agriculture
to remain competitive in energy markets. Floor price effect: if demand is particular pronounced as in the case
of cane-based ethanol, bioenergy demand has created a quasi intervention system and an effective floor price
for sugar in this case.
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Why are current food prices so high?
• The interrelation with the energy markets may slowdown or reverse Cochrane’s treadmill
or Owens development squeeze which imply declining real agricultural prices, less
farmers, larger scale farming and possible depopulated areas.
• Volatility of world prices might be an important problem in the future that causes hunger
in terms of very high prices for poor consumers and problems for poor farmers when
prices are low. The ceiling and especially the floor may act as an intervention price in
case of very volatile prices. A floor may also stimulate agriculture in the (poor) world.
Hunger is not a problem directly related with biofuels but often of bad policies, and
improperly functioning factor and commodity markets.19 In principle, there is enough
food in the world but there is a distribution problem.
• Rising food commodity prices tend to negatively affect lower income consumers more
than higher income consumers. First, lower income consumers spend a larger share
of their income on food. Second, staple food commodities such as maize, wheat, rice,
and soybeans account for a larger share of food expenditures in low-income families.
Third, consumers in low-income, food-deficit countries are vulnerable because they
must rely on imported supplies, usually purchased at higher world prices. Fourth,
countries receiving food aid donations based on fixed budgets receive smaller quantities
of food aid. A simplified comparison of the impact of higher food commodity prices
on consumers in high-income countries and on consumers in low-income, food-deficit
countries illustrates these differences (see Table 2).
19
AG assessment (2008), ‘Policy options for improving livelihoods include access to microcredit and other
financial services; legal frameworks that ensure access and tenure to resources and land; recourse to fair conflict
resolution; and progressive evolution and proactive engagement in Intellectual Property Rights (IPR) regimes
and related instruments.’
Table 2. Impact of higher food commodity prices on consumers’ food budgets.
High income
countries
Initial situation
Income
Food expenditure
Food costs as % of income
30% increase in food prices
New costs for total food expenditure
Food costs as % of income
Sugarcane ethanol
Low income,
food deficit countries
€ 40,000
€ 4,000
10%
€ 1,000
€ 500
50%
€ 5,200
13%
€ 650
65%
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Chapter 10
This illustrative comparison shows that for a consumer in a high-income country a 30percent increase in food prices causes food expenditures to rise 3 percent (€1,200), while for
a consumer in a low-income country food expenditures increase by 15 percentage points.
6. Concluding remarks
The motivation at the origin of this chapter can be summarised in four questions:
• Is the current price increase driven by real or monetary issues (notably a speculation
phenomenon)?
• Are natural resource and basic food commodity prices linked together?
• Is the shortfall in production also linked to governance issues that limit investment and
production?
• To what extent is the underused capacity in land and man-power a result of lack of
investment capacity, both at the micro level (tools and seed) and at the macro level
(storage and transportation infrastructure)?
The work on these questions allows the formulation of responses, and also some broader
observations. From our work it is clear that the price increases have several roots and that
a normally functioning market will in time provide a certain degree of corrective action.
But policy/political decisions can prevent the market from doing so. In any case, the time
lapse for the market to act does not remove the acuity of the price distortion that affects the
poorest people, and urgent intervention is necessary to alleviate the effects of short-term
price peaks.
Natural resource prices lead basic food commodity prices; the rate of growth of the former
has historically been (and is again at present) higher than the latter. Biofuels create a more
direct link between food and fuel prices, if fuel prices are high: the long-term trend of
declining real food prices might be dampened or reversed.
The influence of policy/political decisions mentioned above is certainly present when
considering why production in many countries is below the potential capacity to produce
food. Not only has land been voluntarily removed from production in some cases, but the
access to technology and markets is sometimes also limited by factors that are strictly in the
realm of governance. But then there are also potential producers, who simply can not make
it into the market, and they can be assisted through micro-credit or through the donation of
tools, seeds and the development of irrigation, storage capacity and transportation facilities
to integrate into market structures.
Our further observations are of several orders, and theses are with regard to policy
implications, market failure, social equity, and required policy action.
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Why are current food prices so high?
6.1. Policy implications
With regard to the EU, CAP reform was designed to enforce farmers’ reaction to market
signals. There should be no surprise, therefore, when farmers do, and therefore production
falls close to the level of world demand. The problem, however, is the time lag between the
demand in the market and a farmer’s decision on what – and how much – to plant. There is
always some degree of ‘inadequate’ response on the supply side. Around the world, farmers
are now responding to price signals and are increasing their production of cereals. Building
up and managing stocks is not the primary responsibility of farmers, and in a free market
this is left to traders; some government intervention might be considered, but a return to
automatic intervention based solely on commodity prices should be absolutely avoided!
6.2. Will current price level persist?
High prices can only ‘cured’ by high prices. This may initially seem to be a provocative
statement, but the simple fact is that – as stated above – farmers do react to price signals.
So do all the other agents in the economy, including speculators! The food price ‘crisis’ will
certainly be prolonged through protective measures by national governments, although the
issue of civil stability may encourage some governments to take such actions, to reassure
their populations that ‘something is being done’. Biofuels, however, create a more direct
link between food and fuel prices and if fuel prices increase further, the long-term trend of
declining real food prices might be dampened or reversed.
6.3. Who is mostly affected?
The consumers of food in low-income countries with food and energy deficits are those
who will suffer most in any sudden or rapid price shift for basic commodities, of which
foremost is food. In principle, current high prices provide additional income opportunities
for farmers. Whether farmers in developing countries will benefit from current high prices
on world food markets remains questionable and depends on the degree of integration of
regional in global food markets. But if there is no structural market failure involved per se,
as stated above, then this means that the conditions of productivity and market access are
the priorities that have not been addressed successfully for a long period of time before a
price crisis occurs.
6.4. Required policy action
Short-term action is to urgently increase spending on food aid (which has gone down
during the last years). Long-term production capacity improvement (including publically
financed agricultural research) is essential to avoid repeated price crises. The current crisis
is not a crisis in terms of shortage of food, but a crisis in terms of income shortage (in terms
of purchasing power and of investment potential to increase productive capacity). Policy
Sugarcane ethanol
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Chapter 10
measures should enable especially the poor to be able to participate in the economy, and
therefore for the poor countries to generate income within a world market.
Acknowledgements
We consulted the following experts: Patt Westhoff (FAPRI), Josef Schmidhuber (FAO),
Loek Boonekamp (OECD), Ron Trostle (ERS/USDA), Pavel Vavra (OECD), Willie Meyers
(FAPRI) and Pierre Charlebois (Agriculture and Agri-Food Canada). Furthermore,
we benefited greatly from insights and the discussions during the World Agricultural
Outlook Conference, organized by ERS/USDA Washington DC, May, 14-15, 2008 and the
Modeling Workshop on Biofuel, May, 16 organized by Farm Foundation and ERS/USDA
Washington DC.
References
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OECD-FAO, 2008. Agricultural Outlook 2008-2017. Paris, France.
Pardey, P.G., N. Beintema, S. Dehmer and S. Wood, 2006. Agricultural research: a growing global divide,
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Schmidhuber, J., 2007. Biofuels: An Emerging Threat to Europe’s Food Security? Impact of an Increased
Biomass Use on Agricultural Markets, Prices and Food Security: A Longer-term Perspective. Available
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Trostle, R., 2008. Global Agricultural Supply and Demand: Factors Contributing to the Recent Increase in
Food Commodity Prices. ERS/USDA. WRS-0801.
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usda.gov/psdonline/. Accessed 21/05/2008.
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Projections Report. OCE-2008-1. February 2008. Washington D.C.
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Van Meijl, H., T.J. Achterbosch, A.J. de Kleijn, A.A. Tabeau and M. Kornelis, 2003. Prijzen op agrarische
wereldmarkten; Een verkenning van projecties [Agricultural world market prices; an explorative study
to projections]. Agricultural Economics Research Institute, Rapport 8.03.06.
Von Braun, J., A. Ahmed, K. Asenso-Okyere, S. Fan, A. Gulati, J. Hoddinott, R. Pandya-Lorch, M.W.
Rosegrant, M. Ruel, M. Torero, T. van Rheenen and K. von Grebmer, 2008. High Food Prices: The What,
Who, and How of Proposed Policy Actions. IFPRI Policy Brief, Washington, USA.
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Acknowledgements
We would like to express our gratitude to the authors of the different chapters of this book
for their valuable contributions, their creativity, positive attitude and willingness to accept
our role of coordinators. The thorough work of the peer reviewers contributed to the quality
of the contents of the different chapters.
The choice of the subjects, the selection of authors, the selection of peer reviewers and the
structure of the publication was ours.
Regarding Chapter 10, the underlying study - Why are current food prices so high? by
Martin Banse, Peter Nowicki and Hans van Meijl, The Hague, 2008 - was financed by the
Ministry of Agriculture, Nature and Food Quality, for which they are expressing their
thanks as well.
We thank Wageningen International, part of Wageningen University and Research Centre to
facilitate the management of the project. Finally, we gratefully acknowledge the important
contribution of Wageningen Academic Publishers. Mike Jacobs and his team did a great
job within a limited timeframe.
Peter Zuurbier
Jos van de Vooren
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249
Authors
Dr. Marcos Adami, senior researcher at INPE - Instituto Nacional de Pesquisas Espaciais, Divisão
de Sensoriamento Remoto, Jose dos Campos (SP), Brazil.
Daniel Alves de Aquiar, Msc and currently researcher at INPE - Instituto Nacional de Pesquisas
Espaciais, Direção, Coordenação Geral de Observação da Terra, Jose dos Campos (SP), Brazil.
Dr. Weber Antonio Neves do Amaral is full professor at the University of São Paulo, ESALQ - Escola
Superior de Agricultura ‘Luiz de Queiroz’, Piracicaba (SP), Brazil.
Laura Barcellos Antoniazzi, Msc is working at ICONE - Instituto de Estudos do Comércio e
Negociações, São Paulo (SP), Brazil.
Dr. Miriam Rumenos Piedade Bacchi, researcher at CEPEA - Centro de Estudos Avançados em
Economia Aplicada, University of São Paulo, ESALQ - Escola Superior de Agricultura ‘Luiz de
Queiroz’, Piracicaba (SP), Brazil.
Dr. Martin Banse, senior researcher at the Agricultural Economics Research Institute of Wageningen
University and Research Centre, The Hague, the Netherlands.
Dr. Augusto Beber, researcher at Venture Partners do Brazil - São Paulo (SP), Brazil.
Dr. Annie Dufey, senior researcher at IIED - International Institute for Environment and Development,
London, United Kingdom.
Dr. Andre Faay, associate professor at the Copernicus Institute, Utrecht University, the Netherlands.
Dr. Günther Fischer leads the Land Use Change and Agriculture Program (LUC) at IIASA International Institute for Applied Systems Analysis, in Laxenburg, Austria.
Dr. Eduardo Giuliani is partner at Venture Partners do Brazil - São Paulo (SP), Brazil
Dr. Eva Tothne Hizsnyik joined the Land Use Change and Agriculture Program (LUC) at IIASA
- International Institute for Applied Systems Analysis - in 2003 as a part-time Research Scholar,
Laxenburg, Austria.
Dr. Isaias Macedo is visiting researcher at NIPE - Núcleo Interdisciplinar de Planejamento Energético,
Universidade Estadual de Campinas (UNICAMP), Campinas (SP), Brazil. Since 2001, he has been
consultant in Energy for the Brazilian Government and the private sector.
João Paulo Marinho, Msc is graduate student at the University of São Paulo, ESALQ - Escola Superior
de Agricultura ‘Luiz de Queiroz’, Piracicaba (SP), Brazil.
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251
Authors
Dr. Andre Meloni Nassar is director-general ICONE - Instituto de Estudos do Comércio e Negociações,
São Paulo (SP), Brazil.
Dr. Peter Nowocki, senior researcher at the Agricultural Economics Research Institute of Wageningen
University and Research Centre, The Hague, the Netherlands.
Dr. Bernardo F.T. Rudorff is senior research at INPE - Instituto Nacional de Pesquisas Espaciais,
Divisão de Sensoriamento Remoto, Jose dos Campos (SP), Brazil.
Dr. Joaquim E.A. Seabra, professor at FEM - Faculdade de Engenharia Mecânica, Universidade
Estadual de Campinas (UNICAMP), Campinas (SP), Brazil.
Dr. Alfred Szwarc, consultant at ADS - Technology and Sustainable Development, São Paulo, Brazil.
Rudy Tarasantchi, Msc is graduate student at the University of São Paulo, ESALQ - Escola Superior
de Agricultura ‘Luiz de Queiroz’, Piracicaba (SP), Brazil.
Dr. Edmar Teixeira joined the Land Use Change and Agriculture Program of IIASA - International
Institute for Applied Systems Analysis, in April 2007 as a Postdoctoral Research Scholar, Laxenburg,
Austria.
Dr. Wallace E. Tyner, professor at the Department of Agricultural Economics, Purdue University,
West Lafayette (IN), USA.
Dr. Jos van de Vooren is manager of the Latin America Office Wageningen University and Research
Centre, the Netherlands, located at University of São Paulo, ESALQ - Escola Superior de Agricultura
‘Luiz de Queiroz’, Piracicaba (SP), Brazil.
Dr. Hans van Meijl, senior researcher at the Agricultural Economics Research Institute of Wageningen
University and Research Centre, The Hague, the Netherlands.
Dr. Harrij van Velthuizen is a land resources ecologist and specialist in agro-ecological zoning. Since
1995 he has been engaged with the activities of the Land Use Change and Agriculture Program (LUC)
of IIASA - International Institute for Applied Systems Analysis, Laxenburg, Austria..
Dr. Arnaldo Walter, professor at UNICAMP - Universidade Estadual de Campinas, Campinas (SP),
Brazil.
Dr. Peter Zuurbier is director of the Latin America Office of Wageningen University and Research
Centre, the Netherlands. He is also professor at the University of São Paulo, ESALQ - Escola Superior
de Agricultura ‘Luiz de Queiroz’, Piracicaba (SP), Brazil and at Wageningen University.
252
Sugarcane ethanol
Keyword index
A
Africa 204, 205, 209, 211
Amazon 41, 42, 51, 64
– biome 73, 86, 88, 92
– ecosystem 73
– rainforest 42, 58
Asia 23, 29, 52, 59, 148, 160, 192, 200,
203, 205, 209, 210, 234
Australia 233
B
bagasse 22, 23, 58, 95, 100, 141, 154, 173,
205
biodiversity 19, 24, 41, 42, 52, 57, 58,
129, 132, 154, 161, 163, 178, 210,
211, 221, 222, 242
bioenergy 26, 54, 142, 151, 163, 178
bioethanol 215, 216, 217
biomass 19, 21, 22, 24, 47, 88, 91, 95,
109, 113, 120, 121, 135, 139, 142,
150, 151, 154, 159, 160, 161, 162,
163, 164, 165, 167, 168, 177
biotechnology 58
Brazil 20, 22, 23, 29, 30, 31, 33, 35, 39,
40, 41, 44, 45, 56, 63, 65, 67, 73, 84,
91, 103, 108, 113, 117, 124, 129,
139, 140, 144, 148, 174, 181, 182,
190, 200, 203, 205, 208, 210, 211,
214, 234, 241
C
carbon
– capture 177, 178
– debts 52
– stocks 102, 104, 106, 121
Caribbean 23, 29, 30, 144, 148, 200, 204,
205
castor oil 215
cattle 63, 71, 84, 90, 108, 110, 211
Central America 35, 144
Sugarcane ethanol
Cerrado 42, 46, 56, 63, 73, 84, 88, 103,
123, 211
– biome 65
– ecosystem 52
– region 57
China 21, 23, 29, 36, 139, 166, 169, 175,
205
citrus 83
climate change 19, 34, 145, 153, 200
– mitigation 19, 221
Colombia 140
consumption
– energy 19
– fuel 20
criteria 25, 132, 146, 155, 163
criticism 12
Cuba 30
D
deforestation 41, 42, 52, 58, 63, 64, 81,
88, 92
developing countries 25, 26, 31, 47, 52,
134, 152, 200, 206, 216, 219, 245
E
emission
– acetaldehyde 206
– carbon monoxide 206
– CO2 19, 96
– hydrocarbons 206
– life-cycle 174
– N2O 173
– noxious 142
– polluting 24
energy 19, 20, 24, 47, 54, 96, 109, 113,
132, 135, 140, 145, 151, 153, 155,
161, 162, 164, 172, 176, 182, 187,
196
– security 23, 24, 31, 113, 139, 145, 200,
217
253
Keyword index
– solar 11
environment 19
environmental licensing 73
ethanol
– anhydrous 22, 141
– gasoline 22
– hydrous 22
Europe 234
European Union 148, 172, 181, 190, 192,
218
expansion 31, 33, 34, 40, 41, 47, 56, 57,
63, 65, 73, 78, 84, 92, 108, 210
F
fermentation 11, 21, 23, 96, 127, 140,
142, 160, 164, 167, 168
ferti-irrigation 126
FFVs – See: flex-fuel vehicles
flex-fuel vehicles (FFVs) 22, 139, 142,
148, 152
food prices 25, 26, 227, 229, 233, 235,
241
forest 88, 103
– riparian 46
fossil 200, 201, 205, 216, 220
H
hydrolysis 11, 22, 95, 96, 141, 154, 160,
164, 166, 167, 168, 169, 178
I
India 29, 30, 36, 38, 51, 139, 140, 166,
169, 200, 203, 212
indicators 115, 120, 132, 164
industry
– automotive 24
– biofuel 26, 218
– ethanol 23, 24
– gasoline 185
– paper & pulp 169
– sugar 30
– sugarcane 30, 43, 95, 203, 214
intercropping 103
irrigation 38, 51, 124, 208, 212
J
Jatropha 160, 178
K
Kenya 200
L
G
generation
– first 148, 152, 159, 160, 176, 178, 217,
221
– second 139, 145, 148, 151, 152, 154,
155, 159, 160, 161, 165, 172, 175,
176, 177, 178, 205, 242
GHG – See: greenhouse gas
global impacts 181, 189
greenhouse gas (GHG) 54, 172, 200
– emissions 23, 24, 25, 34, 57, 63, 95,
96, 99, 100, 101, 102, 107, 108, 109,
120, 133, 142, 146, 160, 172, 173,
174, 177, 178, 205, 207, 221
254
land allocation 73
land use changes (LUC) 45, 54, 63, 64,
65, 66, 68, 84, 91, 92, 107, 113, 121,
123, 173, 195
– direct 63
– indirect 57, 63
Latin America 47, 148, 192, 200
legal framework 116, 117
license
– operation (LO) 73
– previous (LP) 73
lignocellulosic 22, 95, 139, 154, 160, 164,
167, 178
LUC – See: land use changes
Sugarcane ethanol
Keyword index
M
S
maize 20, 83, 104, 173, 184, 187, 209, 240
Malawi 200, 211
methyl-tertiary-butyl-ether (MTBE) 20,
189
Millennium Development Goals 26, 199,
200, 220
Miscanthus 23
mitigation 95, 96, 100, 102, 109, 153, 207
MTBE – See: methyl-tertiary-butyl-ether
saccharification 11
satellite images 86, 90, 103
– analysis 66
savannah 46, 192
small farmers 24, 200, 209, 210, 212, 213,
220
soil 23, 24, 40, 43, 52, 69, 104, 126, 161,
210
sorghum 22, 23, 215
South Africa 212
South America 29, 52
starch 22
sugar beet 22, 159
sustainability 25, 54, 63, 120, 126, 146,
151, 153, 159, 199, 218
Sweden 134, 139
switchgrass 23
Switzerland 134
N
natural vegetation 43
Netherlands 218
North America 172, 178, 234
P
Pakistan 38, 200
palm 146, 159, 160, 164, 178, 215
Panicum virgatum 23
pasture 25, 42, 44, 52, 56, 63, 69, 74, 78,
86, 91, 103, 104, 106, 107, 108, 109,
123, 126, 161, 163, 178, 192, 195,
206, 211
– cultivated 42, 57, 104
– degraded 12
– extensive 43
photosynthesis 48, 96
policies 20, 24, 26, 29, 40, 113, 132, 181,
184, 189, 190, 196, 202, 210, 217,
218, 238
Proalcool program 33, 113
productivity 38, 51, 102, 107, 135, 208
Puerto Rico 32
T
Thailand 140
U
United Kingdom 218
United States of America 20, 26, 139,
148, 181, 190
V
vinasse 43, 58, 126, 211
W
water 43, 58, 124, 128, 132, 146, 154, 161,
201, 208, 211
wheat 22
R
rain-fed sugarcane 38, 51, 52, 54
rainforest 129, 160
rapeseed 164
residues 22, 43, 139, 152, 161, 178
– forestry 155
Russia 241
Sugarcane ethanol
Z
Zea mays 20
Zimbabwe 200
255