The text that follows is a PREPRINT.
Please cite as:
Fearnside, P.M. 1995. Hydroelectric dams in the Brazilian Amazon as sources of
'greenhouse' gases. Environmental Conservation 22(1): 7-19.
ISSN: 0376-8929
Copyright: Cambridge University Press
The original publication is available at http://journals.cambridge.org/
<publisher link>
HYDROELECTRIC DAMS IN BRAZILIAN AMAZONIA AS
SOURCES OF GREENHOUSE GASES
Philip M. Fearnside, MS, PhD (Michigan)
Research Professor, Department of Ecology,
National Institute for Research in the Amazon (INPA)
Caixa Postal 478
69011-970 Manaus, Amazonas
Brazil
7961 words
14 Nov. 1994
25 Feb. 1995
TABLE OF CONTENTS
Table of Contents ..........................................
i
List of Tables .............................................
ii
List of Figures ............................................ iii
INTRODUCTION ................................................. 1
AN APPROACH TO CALCULATING EMISSIONS FROM RESERVOIRS ......... 5
GREENHOUSE GAS EMISSIONS
Parameters for Emissions Calculations ................... 10
Simulation of Emissions over Time ....................... 12
Comparison with Fossil Fuel Emissions ................... 14
CONCLUSIONS .................................................. 15
ACKNOWLEDGMENTS .............................................. 16
SUMMARY ...................................................... 17
REFERENCES.................................................... 18
3
List of Tables
Table I:
Existing and planned dams in Brazilian Amazonia.
Table II:Riverbed areas in Amazonian reservoirs.
Table III:Flooding by hydroelectric dams.
Table IV:Biomass by stratum at Manaus: Approximate dry weights.
Table V:Biomass present and division by zones in Amazonian
reservoirs.
Table VI:Parameters for hydroelectric dam emissions calculations.
Table VII:Approximate quantities of biomass present in 1990.
Table VIII:Methane emissions from Amazon floodplain ecosystems.
Table IX:Greenhouse gas fluxes by process in 1990 from
hydroelectric dams.
Table X:Calculation of emissions from fossil fuel displaced by
Balbina and Tucuruí.
Table XI:Comparison of Balbina and Tucuruí 1990 hydroelectric
generating emissions with other emission sources.
List of Figures
Figure 1:
Brazilian Amazonia.
Figure 2:
Existing and planned reservoirs in Brazilian Amazonia.
Figure 3:
Zones for distribution of biomass in reservoirs.
Figure 4: Hydroelectric greenhouse gas emissions (CO2-equivalent
carbon).
Figure 5:
Balbina: CO2 and CH4 emissions (million t of gas).
Figure 6: Balbina: Greenhouse gas emissions (CO2-equivalent
carbon).
0
INTRODUCTION
Hydroelectric dams are commonly believed to have no serious
impact on the greenhouse effect, in contrast to fossil fuel use.
However, the principal reason for this frequent assumption is
ignorance of emissions of hydroelectric dams. Reservoirs in the
Brazilian Amazonia (Legal Amazon) contribute to greenhouse gas
emissions from the region, although contributions from currently
existing reservoirs are small relative to other anthropogenic
sources such as deforestation for cattle pasture. The four
existing 'large' [> 10 megawatt (MW)] dams in the region are
Balbina in the State of Amazonas (filled in 1987), Curuá-Una in
Pará (1977), Samuel in Rondônia (1988) and Tucuruí in Pará (1984)
(Figure 1). In addition, there are small reservoirs at Boa
Esperança in Maranhão (filled prior to 1989), Jatapu in Roraima
(1994), Paredão or Coarcy Nunes in Amapá (1975), and Pitinga in
Amazonas (1982).
The scale of hydroelectric development contemplated for
Amazonia makes this a potentially significant source of emissions
of greenhouse gases in the future. Existing and planned dams are
shown in Figure 2 and listed in Table I. Brazil's financial
difficulties have repeatedly forced the national power authority
(ELETROBRÁS) and the power monopoly in northern Brazil
(ELETRONORTE) to postpone dam building plans. However, the
overall scale of the plans, as distinguished from the expected
date of completion of each dam, remains unchanged and
consequently an important consideration for the future.
(Figures 1 and 2 and Table I here)
Little basis exists for calculating emissions from
reservoirs. However, existing information can be organized in
such a way as to draw the best possible conclusions given the
limitations of our knowledge. The present paper assesses the
amounts, types, and vertical distribution of biomass in areas
flooded by reservoirs. Rough inferences are drawn as to
emissions resulting from decay of this biomass, but the certainty
that can be attached to them is low due to poor understanding of
the rates and pathways of decay for flooded biomass.
Hydroelectric emissions are the least well-understood of
greenhouse gas emissions from Amazonian deforestation
(hydroelectric flooding is considered to be a form of
deforestation (cf. Fearnside, 1993).
The ultimate contribution of hydroelectric flooding to
atmospheric carbon is much easier to calculate than the impact of
this flooding on the annual balance of emissions, which requires
knowledge of the rates of decay and of the proportions of carbon
emitted as carbon dioxide (CO2) and methane (CH4); the latter of
these is much more effective than the former in greenhouse
1
warming per unit of weight. The ultimate contribution of dams to
carbon emissions is the difference between the carbon stock in
the forest prior to flooding and that in the reservoir once the
forest has decayed and an equilibrium is reached. Reservoirs in
tropical forest areas have a much greater potential for
greenhouse gas emissions than do reservoirs in low biomass
landscapes that characterize most of the world's existing
hydroelectric dams. The amount of power generated also strongly
affects the comparative impacts of hydroelectric versus fossil
fuel generation.
In Amazonia, dams are frequently worse than petroleum from
the point of view of the ultimate total of greenhouse gas
emissions. The worst case is the Balbina Dam. Junk & Nunes de
Mello (1987) calculated that it would take 114 years of fossil
fuel burning to equal the carbon emissions of the forest flooded
in Balbina. The calculation made by these authors considered
Balbina's installed capacity of 250 megawatts (MW) and an area of
1650 km2.
The installed capacity of a dam represents what would be
generated if all turbines were to operate year-round. Because
the flow of the Uatumã River at Balbina is only sufficient to run
all turbines for a fraction of the year, output at the dam
averages 112 MW, and losses in transmission to Manaus reduce the
average delivered to 109 MW (Brazil, ELETRONORTE/MONASA/ENGE-RIO,
1976). The area of the reservoir used by Junk & Nunes de Mello
(1987) was apparently chosen from preliminary estimates that
foresaw an area considerably smaller than do more recent
estimates. Considering the average power delivered to Manaus and
the 'official' reservoir area of 2360 km2 at the normal maximum
operating level of 50-m elevation above mean sea level, Fearnside
(1989) amended to 250 years Junk & Nunes de Mello's estimate of
the time that petroleum would need to be burned to equal
Balbina's ultimate emissions of carbon.
While useful as an illustration, calculation of the ultimate
contribution to carbon emissions tells us little about the
contribution to the annual balance of emissions. The United
Nations Framework Convention on Climate Change (UN-FCCC), signed
at the United Nations Conference on Environment and Development
(UNCED) in Rio de Janeiro in June 1992 by 155 countries plus the
European Union, stipulates that each nation must make an
inventory of carbon stocks and fluxes of greenhouse gases. This
implies that the annual balance of greenhouse gas fluxes will be
the criterion adopted for assigning responsibility among nations
for global warming. Because forest biomass in Amazonian
reservoirs decays exceedingly slowly, the contribution to the
annual balance is very different from the ultimate potential for
emitting carbon.
2
In addition to the timing of emissions, the amount that is
emitted as methane rather than carbon dioxide strongly influences
the global warming impact of reservoirs. Per ton of carbon,
methane is much more potent than carbon dioxide in provoking the
greenhouse effect. The average lifetime of methane in the
atmosphere is much shorter than that of carbon dioxide: 10.5
years versus 120 years, given a constant composition atmosphere
as assumed by the Intergovernmental Panel for Climate Change
(IPCC) (Isaksen et al., 1992: 56). Different methods of
calculating global warming equivalence of the various greenhouse
gases result in widely varying values for the importance of
methane; those methods that consider indirect effects and those
that give emphasis to impacts in the near future assign
substantially more weight to methane.
The IPCC's preferred method of calculation in its 1992
Supplementary Report considers a 100-year time horizon without
discounting and only considers direct effects (Isaksen et al.,
1992: 56). This assigns each ton of methane gas a weight 11
times greater than each ton of carbon dioxide. If indirect
effects are considered using the same time horizon, as was done
in the IPCC's 1990 report (Shine et al., 1990: 60), the weight
given to methane relative to CO2 (the global warming potential)
is 21. Because much of methane's global warming impact is
through indirect effects, the current state of disagreement over
an appropriate global warming potential for methane is likely to
be resolved in favor of higher values, thereby increasing the
relative importance of impacts from Amazonian hydroelectric
reservoirs.
The Amazonian várzea (white water floodplain) has been
identified as one of the world's major sources of atmospheric
methane (Mooney et al., 1987). The várzea occupies about 2% of
the 5 X 106 km2 Legal Amazon, the same percentage that would be
flooded if all of the 100,000 km2 of reservoirs planned for the
region are created (Brazil, ELETROBRÁS, 1987: 150). Virtually
all planned hydroelectric dams are in the forested portion of the
region, of which they would represent approximately 2.5-2.9%.
Were these reservoirs to contribute an output of methane per km2
on the same order as that produced by the várzea, they would
together represent a significant contribution to the greenhouse
effect. This methane source would be a virtually permanent
addition to greenhouse gas fluxes, rather than a one-time input
like the CO2 releases from forest decay.
AN APPROACH TO CALCULATING EMISSIONS FROM RESERVOIRS
In order to calculate emissions from hydroelectric
reservoirs one must know the amounts of biomass present and the
likely paths by which it will decay. The trees left standing in
the reservoir are obviously an important component. The portion
3
of the tree projecting out of the water can be assumed to decay
through processes similar to those affecting trees in clearings
for agriculture and ranching, with part of the biomass being
ingested by termites (which emit a small amount of methane), and
part decomposing through other forms of decay which, in the
aerobic environment above the water, produce only CO2. The
biomass above the water level eventually falls into the water,
thereby being transferred to the anoxic environments where decay
is much slower--but also more likely to yield methane. The
leaves and vines fall off the trees very quickly, and the
branches and trunks fall at a much slower rate.
The reservoir can be divided into different zones, where
aerobic and anoxic conditions will have different relative
importance (Fig. 3). Part of the reservoir is alternately
exposed and flooded as water levels fluctuate between the minimum
and maximum normal operating levels. All biomass components in
this zone, including litter and below-ground biomass, will be
exposed to aerobic conditions at some time during the year. The
portion of standing trunks in the permanently flooded zone that
are located between the minimum and maximum normal operating
levels will also be exposed to aerobic conditions.
(Figure 3 here)
For underwater biomass, a part of the biomass near the
surface will be in an environment that has some oxygen. The
anoxic zone does not correspond directly to the hypolimnion, and
for purposes of decay is even closer to the water surface. At
Balbina, for example, although a very small amount of oxygen is
measurable as deep as 5-m (G. V. Peña, personal communication,
1993), persons interested in commercial exploitation of flooded
timber consider any wood below 1-m to be unaffected by decay (E.
V. C. Monteiro de Paula, personal communication, 1993).
Decay in the anoxic water zone is exceedingly slow, even for
leaves that are generally believed to decay rapidly. ELETRONORTE
commissioned the Delft Hydraulics Laboratory in Delft, The
Netherlands, to produce a model for water quality in Balbina,
(Brazil, ELETRONORTE, 1987: 261). The model, known as OXYSTRATIF, assumes that all leaves, litter and fine branches will
decay within ten years. However, over five years after filling
Balbina, much of this material is still present (although no
quantitative information is available). The very slow nature of
decay in the anoxic zone is illustrated by bundles of leaves that
were placed at 5-m depth for studies of insects and other
organisms in Balbina: after ten months the visual appearance of
the leaves remained as green as the day when they were placed in
the water. No macroscopic organisms colonized the leaves, and
not even the slime that typically forms on decaying material was
present (G. V. Peña, personal communication, 1993).
4
In shallow areas of the reservoirs, methane bubbling is
easily observed. At both Balbina and Tucuruí, bubbles can be
seen everywhere, even when no pressure is exerted, as by stepping
on the bottom. The nature of the environment--devoid of oxygen,
with relatively high temperatures and high levels of nutrients-makes it ideal for methane-producing decay processes.
Emissions from decaying forest biomass will be supplemented
from decay of organic matter that enters the reservoir from
rivers and streams that feed it, from soil organic matter, and
from macrophytes that grow in the reservoir. The production of
methane from these sources must be considered, although carbon
dioxide need not be considered as a net addition (with the
exception of any soil organic matter oxidized). Data on methane
production from these sources, which may be loosely described as
production from the water itself, are not available for any
Amazonian reservoir, the closest available surrogate being
natural lakes in the várzea.
Methane production from decomposition is not strictly
identical to methane emission to the atmosphere, as some of the
methane dissolved in the water column will instead by oxidized to
CO2 before entering the atmosphere. Because of the limited
amount of mixing through the thermocline, high concentrations of
methane in the water in the hypolimnion will only enter the
atmosphere as the water passes through the turbines; at this
point great quantities of methane can be expected to be released
due to the abrupt reduction in pressure. This occurs, for
example, in water passing through turbines in reservoirs in
Canada (M. Lucotte, personal communication, 1993). However, not
all methane will be exposed to the atmosphere in the reservoir
and at the turbines, and some will occur downstream of the dam.
The dissolved concentration of CH4 in the water released from the
turbines or over the spillway is an important measurement that
needs to be made, but not all CH4 present in these water flows
can be considered as methane emissions--some CH4 may be oxidized
to CO2 in the river (Rosa, 1992).
Methane-rich water from the hypolimnion is occasionally
released in reservoirs in central and western Amazonia (Balbina
and Samuel) when a cold wave (friagem) reduces surface
temperature and causes dissolution of the thermocline (the
barrier created by thermal stratification of the water column
that prevents vertical mixing), resulting in a turnover in the
water. Many fish die during these events, for example, in April
1993 at Balbina. These events are more frequent in the western
part of Amazonia, and are not a factor in the eastern part of the
region, where most planned reservoirs would be located.
5
GREENHOUSE GAS EMISSIONS
Parameters for Emissions Calculations
Estimating emissions from reservoirs first requires
estimates of the area of forest flooded in each impoundment. The
riverbed area within each reservoir must be estimated and
subtracted from the water surface area. Riverbed areas are
calculated in Table II from estimates of the length and average
width of the rivers. The surface areas of the reservoirs were
measured from LANDSAT-TM 1:250,000 scale images (Fearnside et
al., nd). Previously deforested areas and riverbed areas are
deducted when forest loss is calculated (Table III).
(Tables II and III here)
Vertical distribution of biomass, and classification into
trunks, leaves and other components, is important for determining
what portion of the biomass will decay above the water and what
will decay underwater in the permanently flooded and seasonally
flooded zones. The only existing biomass study that assigns the
biomass to vertical strata is that of Klinge & Rodrigues (1973),
done at INPA's Reserva Egler, 64 km east of Manaus. The
approximate dry weights are given in Table IV. The forest at the
Reserva Egler has a maximum height of 38.1 m, which must be
assumed to apply to the forests in the four existing large
reservoirs.
(Table IV here)
Biomass estimates specific for each reservoir are available
for all except Curuá-Una (Table V). Fortunately, the forest
flooded at Curuá-Una has an area of only 65 km2, representing
only 1.3% of the total 4824 km2 of forest flooded by 1990 in the
region (Table V). Biomass for Curuá-Una is assumed to be the
average estimated for all areas deforested in the 1989-1990
period (Fearnside, nd-a). Based on the proportion in vertical
strata (Table IV), the water depths at minimum and maximum
operating levels (Table V), and the areas in each zone (Table V),
the biomass is calculated for each reservoir in the following
categories: above-water zone wood, surface water zone wood,
anoxic water zone leaves and other non-wood (all assumed to fall
to the bottom of the reservoir), and below-ground wood (Table V).
The amounts of wood removed by logging prior to filling and
after filling (through 1990) are also roughly estimated (Table
V). After these calculations, the progression of biomass values
is calculated for each year for each reservoir, zone and biomass
component. This is done using rates of decay in each zone and
rates of biomass falling from the above-water to the below-water
zones; these rates and other parameters for emission calculations
6
are given in Table VI. The resulting biomass distributions in
1990 are given in Table VII.
(Tables V, VI and VII here)
The decay rates for underwater biomass are known to be
exceedingly slow, but actual measurements are completely lacking.
The average lifetimes assumed here are: 50 years for wood in the
surface water zone, 200 years for leaves in the anoxic water
zone, 500 years for wood in the anoxic water zone, 500 years for
below-ground biomass in the permanently flooded zone, and 50
years for below-ground biomass in the seasonally flooded zone
(Table VI).
Methane is also produced from ongoing biological processes
that are independent of the stock of original forest biomass.
These include decomposition of organic matter entering the
reservoir from the river, and from decay of macrophytes that grow
on a portion of the reservoir surface. These rates are assumed
to be equal to those that have been found for open water and for
macrophyte beds in studies of natural várzea lakes (Table VIII).
Only methane is considered from these sources, as the carbon
dioxide that they also generate is recycled when the macrophytes
and other plants regrow. Chemical characteristics of water in
the Balbina reservoir, for example, (located on a black water
river) differ in a number of ways from white water várzea lakes,
making clear the importance of direct measurements of methane
production in reservoirs.
(Table VIII here)
Simulation of Emissions over Time
The greenhouse gas fluxes by process in 1990 are presented
in Table IX. While information on emissions from all sources at
a given time, such as 1990, is needed as a baseline for assessing
changes in greenhouse gas emissions, the evolution of emissions
over time is important for evaluating potential impacts of
planned projects. The timing of emissions is also very important
in any system of emissions evaluation that gives differential
weight to short-term and long-term impacts, as by discounting.
(Table IX here)
The emissions of CO2 and CH4 from Balbina are simulated for
50 years after closing in Figure 4. Methane emissions are fairly
constant over the entire period, but carbon dioxide emissions are
concentrated in a tremendous pulse in the first decade after
closing. As of 1994, approximately half of the total CO2
emission from Balbina had taken place, according to the
simulation reported here.
7
(Figure 4 here)
The global warming impact of emissions can be converted to
CO2-equivalent carbon using global warming potentials adopted by
the Intergovernmental Panel on Climate Change (IPCC) for direct
effects only, over a 100-year time horizon without discounting
(Isaksen et al., 1992). This is an underestimate of the true
impact of reservoirs, as at least half of the global warming
provoked by methane is through indirect rather than direct
effects. In Figure 5 the CO2-equivalent carbon of the emissions
is simulated for 50 years for the four existing large reservoirs
in Brazilian Amazonia.
(Figure 5 here)
Comparison with Fossil Fuel Emissions
Comparisons of emissions from hydroelectric projects with
the avoided emissions from generating the same amount of power
from fossil fuels are important because of the frequency with
which hydroelectric projects have been promoted as offering a
'clean' alternative to thermoelectric generation. The examples
of Balbina and Tucuruí are given in Table X. The mix of diesel
and fuel oil burned at thermoelectric plants in Manaus (the city
served by Balbina) is assumed to also apply to avoided emissions
from Tucuruí. Emissions factors for these fuels applying to
thermoelectric plants in Canada are assumed to apply to Brazil
(probably an optimistic assumption). Power from Balbina
substitutes for approximately 1.3 million t of CO2-equivalent
carbon (Table X, part F), far less than the emission of 6.9
million t from decaying biomass in the reservoir (Table XI).
Table XI also compares 1990 emissions of Balbina and Tucuruí with
emissions from other sources.
These Amazonian reservoirs compare poorly with two
reservoirs in Canada that have been identified as sources of
greenhouse gases (Rudd et al., 1993). The comparative impact of
Balbina and Tucuruí is even worse than these emissions estimates
indicate because the Canadian study used a global warming
potential (GWP) for calculating the CO2 equivalent of methane,
which was over five times higher than the IPCC GWP used in the
present paper. By converting emissions to CO2 carbon equivalents
using the same IPCC GWPs used in the current calculation, Rosa
and Schaeffer (1994) have shown that the Canadian reservoirs
studied by Rudd et al. (1993) have less global warming impact
than would generating the same amount of energy from fossil fuel.
(Tables X and XI here)
8
In Figure 6 the emissions of Balbina are simulated over 50
years, in comparison to the emissions that would be produced by
supplying the same energy to Manaus from fossil fuels. The
tremendous disadvantage of hydroelectric generation in the
initial years is evident. In the case of Balbina (which has a
very large area per unit of electricity generated), even after 50
years (and probably for an indefinite period), the emissions will
continue to exceed those from fossil fuels. These results call
into question the image of Amazonian hydroelectric dams as
helping to reduce global warming.
(Figure 6 here)
CONCLUSIONS
Hydroelectric reservoirs in Brazilian Amazonia emitted very
approximately 0.26 million tons of CH4 gas and 38 million tons of
CO2 gas in 1990. Of the CH4, approximately 0.11 million tons
were emitted from open water, 0.04 from macrophyte beds, < 0.01
from above-water decay of forest biomass, and 0.11 from
underwater decay of forest biomass. The underwater decay rates
are the least reliable of these estimates. No net carbon dioxide
emissions come from open water or macrophytes. Above-water decay
contributed approximately 99% of the estimated 38 million tons of
CO2 emitted. Using 1992 IPCC global warming potentials, these
emissions are equivalent to approximately 11 million tons of CO2equivalent carbon.
The total area of planned reservoirs in Brazilian Amazonia
is approximately 20 times the area present in 1990, implying a
potential annual emission rate of about 5.2 million tons of
methane. While the methane emission represents an essentially
permanent addition to gas fluxes, the carbon dioxide is released
in a tremendous pulse during the first decade after closure.
These CO2 emissions greatly exceed the avoided emissions from
fossil fuel combustion.
ACKNOWLEDGMENTS
I thank Summer V. Wilson, Bruce R. Forsberg and Gladys V.
Peña for comments on the manuscript.
9
SUMMARY
Existing hydroelectric dams in Brazilian Amazonia emitted
about 0.26 million tons of methane and 38 million tons of carbon
dioxide in 1990. The methane emissions represent an essentially
permanent addition to gas fluxes from the region, rather than a
one-time release. The total area of reservoirs planned in the
region is about 20 times the area existing in 1990, implying a
potential annual methane release of about 5.2 million tons.
About 40% of this estimated release is from underwater decay of
forest biomass, which is the most uncertain of the components in
the calculation. Methane is also released in reservoirs from
open water, macrophyte beds, and above-water decay of forest
biomass.
Hydroelectric dams release a large pulse of carbon dioxide
from above-water decay of trees left standing in the reservoirs,
especially during the first decade after closing. This elevates
the global warming impact of the dams to levels much higher than
would occur by generating the same power from fossil fuels. In
1990, the impoundment behind the Balbina Dam (closed in 1987) had
over 20 times more impact on global warming than would generating
the same power from fossil fuels, while the Tucuruí Dam (closed
in 1984) had 0.4 times the impact of fossil fuels. Because of
the large area flooded per unit of electricity generated at
Balbina, greenhouse gas emissions are expected to exceed avoided
fossil fuel emissions indefinitely.
10
REFERENCES
ASELMANN, I. & CRUTZEN, P. J. (1990). A global inventory of
wetland distribution and seasonality, net productivity, and
estimated methane emissions. Pp. 441-9 in Soils and the
Greenhouse Effect (Ed. A. F. Bouwman). Wiley, New York: 575 pp.,
illustr.
BARTLETT, K. B., CRILL, P. M., BONASSI, J. A., RICHEY, J. E. &
HARRISS, R. C. (1990). Methane flux from the Amazon River
floodplain: Emissions during rising water. J. Geophysical
Research, 95 (D10), pp. 16,773-8.
BRAZIL, ELETROBRÁS. (1986). Plano de Recuperação Setorial.
Ministério das Minas e Energia, Centrais Elétricas do Brasil
(ELETROBRÁS), Brasília, Brazil.
BRAZIL, ELETROBRÁS. (1987). Plano 2010: Relatório Geral. Plano
Nacional de Energia Elétrica 1987/2010. (dezembro de 1987).
Ministério das Minas e Energia, Centrais Elétricas do Brasil
(ELETROBRÁS), Brasília, Brazil: 269 pp.
BRAZIL, ELETRONORTE. (1985a). Aproveitamento Hidrelétrico de
Balbina: Reservatório - N.A. 50 m. Centrais Elétricas do Norte do
Brasil, S.A. (ELETRONORTE), Balbina, Amazonas, Brazil. Map scale:
1:100,000.
BRAZIL, ELETRONORTE. (1985b). UHE Balbina e Atendimento do
Mercado Energético de Manaus. Junho/85. Relatório 26.657.
Centrais Elétricas do Norte do Brasil, S.A. (ELETRONORTE),
Brasília, Brazil.
BRAZIL, ELETRONORTE. (1985c). Políticas e Estratégias para
Implementação de Vilas Residenciais. Centrais Elétricas do Norte
do Brasil, S.A. (ELETRONORTE), Brasília, Brazil. Map.
BRAZIL, ELETRONORTE. (1987). Estudos Ambientais do Reservatório
de Balbina. Relatório "Diagnóstico" BAL-50-1001-RE. Centrais
Elétricas do Norte do Brasil, S.A. (ELETRONORTE), Brasília,
Brazil: 308 pp.
BRAZIL, ELETRONORTE. (nd-a). Reservatório da UHE Samuel:
Levantamento Planimêtrico. Centrais Elétricas do Norte do Brasil,
S.A. (ELETRONORTE), Brasília, Brazil. Map scale: 1:40,000.
BRAZIL, ELETRONORTE. (nd-b). UHE Tucuruí: Plano de Utilização do
Reservatório, Caracterização e Diagnóstico do Reservatório e de
sua Área de Influência. TUC-10-263-46-RE Volume 1 - Texto.
Centrais Elétricas do Norte do Brasil, S.A. (ELETRONORTE),
Brasília, Brazil. Irregular pagination.
11
BRAZIL, ELETRONORTE. (nd [c. 1983]). Usina Hidrelétrica Tucuruí
8.000 MW. Centrais Elétricas do Norte do Brasil, S.A.
(ELETRONORTE), Brasília, Brazil: 27 pp.
BRAZIL, ELETRONORTE. (nd [1987]). Livro Branco sobre o Meio
Ambiente da Usina Hidrelétrica de Tucuruí. Centrais Elétricas do
Norte do Brasil, S.A. (ELETRONORTE), Brasília, Brazil: 288 pp.
BRAZIL, ELETRONORTE. (nd [1992]a). Ambiente Desenvolvimento
Tucuruí. Centrais Elétricas do Norte do Brasil, S.A.
(ELETRONORTE), Brasília, Brazil: 32 pp.
BRAZIL, ELETRONORTE. (nd [1992]b). Ambiente Desenvolvimento
Samuel. Centrais Elétricas do Norte do Brasil, S.A.
(ELETRONORTE), Brasília, Brazil: 24 pp.
BRAZIL, ELETRONORTE/MONASA/ENGE-RIO. (1976). Estudos Amazônia,
Relatório Final Volume IV: Aproveitamento Hidrelétrico do Rio
Uatumã em Cachoeira Balbina, Estudos de Viabilidade. Centrais
Elétricas do Norte do Brasil (ELETRONORTE)/MONASA Consultoria e
Projetos Ltda./ENGE-RIO Engenharia e Consultoria, S.A., Brasília,
Brazil. Irregular pagination.
BRAZIL, PROJETO RADAMBRASIL. (1981). Mosaico semi-controlado de
Radar. Map Scale: 1:250,000. Folhas SA-22-ZC, SB-22-XA, SB-22-XB
and SB-22-SD. Departamento Nacional de Produção Mineral (DNPM),
Rio de Janeiro, Brazil.
DEVOL, A. H., RICHEY, J. H., FORSBERG, B. R. & MARTINELLI, L. A.
(1990). Seasonal dynamics in methane emissions from the Amazon
River floodplain to the troposphere. J. Geophysical Research, 95
(D10), pp. 16,417-26, 5 figs.
FEARNSIDE, P. M. (1989). Brazil's Balbina Dam: Environment versus
the legacy of the pharaohs in Amazonia. Environmental Management,
13 (4), pp. 401-23, 5 figs.
FEARNSIDE, P.M. (1993). Deforestation in Brazilian Amazonia: The
effect of population and land tenure. Ambio, 22(8), pp. 537-545,
4 figs.
FEARNSIDE, P. M. (nd-a). Biomass of Brazil's Amazonian forests.
(In preparation).
FEARNSIDE, P. M. (nd-b). Amazonia and global warming: Annual
balance of greenhouse gas emissions from land use change in
Brazil's Amazon region. (In preparation).
12
FEARNSIDE, P. M., MEIRA FILHO, L. G. & TARDIN, A. T. (nd).
Deforestation rate in Brazilian Amazonia. (In preparation).
FEARNSIDE,
Rainforest
combustion
Amazon. J.
P. M., LEAL FILHO, N. & FERNANDES, P. M. (1993).
burning and the global carbon budget: Biomass,
efficiency and charcoal formation in the Brazilian
Geophysical Research, 98 (D9), pp. 16,733-43, 6 figs.
GOREAU, T. J. & MELLO, W. Z. (1987). Effects of deforestation on
sources and sinks of atmospheric carbon dioxide, nitrous oxide,
and methane from central Amazonian soils and biota during the dry
season: A preliminary study. Pp. 51-66 in Proceedings of the
Workshop on Biogeochemistry of Tropical Rain Forests: Problems
for Research. (Ed. D. Athié, T.E. Lovejoy & P. de M. Oyens).
Universidade de São Paulo, Centro de Energia Nuclear na
Agricultura (CENA), Piracicaba, São Paulo, Brazil: 85 pp.,
illustr.
ISAKSEN, I. S. A., RAMASWAMY, V., RODHE, H. & WIGLEY, T. M. L.
(1992). Radiative forcing of climate. Pp. 47-67 in Climate Change
1992: The Supplementary Report to the IPCC Scientific Assessment.
(Ed. J. T. Houghton, B. A. Callander & S. K. Varney). Cambridge
University Press, Cambridge, UK: 200 pp.
JAQUES, A. P. (1992). Canada's Greenhouse Gas Emissions:
Estimates for 1990. Report EPS 5/AP/4. Environment Canada,
Ottawa, Canada: 78 pp.
JUNK, W. J. & NUNES DE MELLO, J. A. (1987). Impactos ecológicos
das represas hidrelétricas na bacia amazônica brasileira. Pp.
367-85 in Homem e Natureza na Amazônia. (Ed. G. Kohlhepp & A.
Schrader). Tübinger Geographische Studien 95 (Tübinger Beiträge
zur Geographischen Lateinamerika-Forschung 3). Geographisches
Institut, Universität Tübingen, Tübingen, Germany: iii + 507 pp.,
illustr.
JURAS, A. A. (1988). Progama de Estudos da Ictiofauna na Área de
Atuação das Centrais Elétricas do Norte do Brasil, S.A.
(ELETRONORTE). ELETRONORTE, Brasília, Brazil: 48 pp + annexes.
KLINGE, H. (1973). Biomasa y materia orgánica del suelo en el
ecosistema de la pluviselva centro-amazónico. Acta Científica
Venezolana, 24 (5), pp. 174-81.
KLINGE, H. & RODRIGUES, W. A. (1973). Biomass estimation in a
central Amazonian rain forest. Acta Científica Venezolana, 24
(5), pp. 225-37.
KLINGE, H., RODRIGUES, W. A., BRUNIG, E. & FITTKAU, E. J. (1975).
Biomass and structure in a Central Amazonian rain forest. Pp.
13
115-22 in Tropical Ecological Systems: Trends in Terrestrial and
Aquatic Research. (Ed. F. Golley & E. Medina). Springer-Verlag,
New York: 398 pp., illustr.
MARTINELLI, L. A., VICTORIA, R. L., MOREIRA, M. Z., ARRUDA JR.,
G., BROWN, I. F., FERREIRA, C. A. C., COELHO, L. F., LIMA, R. P.
& THOMAS, W. W. (1988). Implantação de parcelas para
monitoreamento de dinâmica florestal na área de proteção
ambiental, UHE Samuel, Rondônia: Relatório preliminar. Centro de
Energia Nuclear na Agricultura (CENA), Piracicaba, São Paulo,
Brazil. (Unpublished report: 72 pp).
MARTIUS, C., FEARNSIDE, P. M., WASSMANN, R. & BANDEIRA, A. G.
(nd). Deforestation and methane release from termites in
Amazonia. (In preparation).
MARTIUS, C., WASSMANN, R., THEIN, U., BANDEIRA, A.G.,
RENNENBERG, H., JUNK, W. & SEILER, W. (1993). Methane emission
from wood-feeding termites in Amazonia. Chemosphere 26 (1-4), pp.
623-632.
MOONEY, H. A., VITOUSEK, P. M. & MATSON, P. A. (1987). Exchange
of materials between terrestrial ecosystems and the atmosphere.
Science, 238, pp. 926-32.
PAIVA, M. P. (1977). The Environmental Impact of Man-Made Lakes
in the Amazonian Region of Brazil. Centrais Elétricas
Brasileiras, S.A. (ELETROBRÁS), Diretoria de Coordenação, Rio de
Janeiro, Brazil: 69 pp.
REVILLA CARDENAS, J. D. (1986). Estudos de ecologia e controle
ambiental na região do reservatório da UHE de Samuel. Convênio:
ELN/MCT/CNPQ/INPA de 01.07.82. Relatório Setorial, Segmento:
Estimativa da Fitomassa. Período julho-dezembro 1986. Instituto
Nacional de Pesquisas da Amazônia (INPA), Manaus, Amazonas,
Brazil: 194 pp.
REVILLA CARDENAS, J. D. (1987). Relatório: Levantamento e Análise
da Fitomassa da UHE de Kararaô, Rio Xingú. Instituto Nacional de
Pesquisas da Amazônia (INPA), Manaus, Amazonas, Brazil: 181 pp.,
illustr.
REVILLA CARDENAS, J. D. (1988). Relatório: Levantamento e Análise
da Fitomassa da UHE de Babaquara, Rio Xingú. Instituto Nacional
de Pesquisas da Amazônia (INPA), Manaus, Amazonas, Brazil: 277
pp., illustr.
REVILLA CARDENAS, J. D. & DO AMARAL, I. L. (1986). Estudos de
Ecologia e Controle Ambiental na Região do Reservatório da UHE de
Samuel: Convênio ELN/CNPq/INPA, de 01.07.82. Relatório Setorial,
14
Segmento Minhocucus, Período janeiro/junho 1986. Instituto
Nacional de Pesquisas da Amazônia (INPA), Manaus, Amazonas,
Brazil: 5 pp.
REVILLA CARDENAS, J. D., KAHN, F. L. & GUILLAMET, J. L. (1982).
Estimativa da fitomassa do reservatório da UHE de Tucuruí. Pp. 111 in Projeto Tucuruí, Relatório Semestral, Período janeiro/junho
1982, Vol. 2: Limnologia, Macrófitas, Fitomassa, Degradação da
Fitomassa, Doenças Endêmicas, Solos. Brazil, Centrais Elétricas
do Norte do Brasil, S.A. (ELETRONORTE) & Instituto Nacional de
Pesquisas da Amazônia (INPA). INPA, Manaus, Amazonas, Brazil: 32
pp.
ROBERTSON, B.A. (1980). Composição, Abundância e Distribuição de
Cladocera (Crustacea) na Região de Água Livre da Represa de
Curuá-Una, Pará. Masters Thesis, Fundação Universidade do
Amazonas (FUA) & Instituto Nacional de Pesquisas da Amazônia
(INPA). INPA, Manaus, Amazonas, Brazil: 105 pp.
ROSA, L.P. (1992). Untitled presentation at the INPE/OECD
Workshop on Inventories of Net Anthropogenic Emissions of
Greenhouse Gases, São José dos Campos, São Paulo, Brazil, 9-10
March 1992.
ROSA, L.P. & SCHAEFFER, R. (1994). Greenhouse gas emissions from
hydroelectric reservoirs. Ambio 23(2), pp. 164-165.
RUDD, J. W. M., HARRIS, R., KELLY, C. A. & HECKY, R. E. (1993).
Are hydroelectric reservoirs significant sources of greenhouse
gases? Ambio, 22 (4), pp. 246-8, 1 fig.
SEVA, O. (1990). Works on the Great Bend of the Xingu--A Historic
Trauma? Pp. 19-35 in Hydroelectric Dams on Brazil's Xingu River
and Indigenous Peoples. (Ed. L. A. de O. Santos & L. M. M. de
Andrade). Cultural Survival Report 30. Cultural Survival,
Cambridge, Massachusetts, USA: 192 pp., illustr.
SHINE, K. P., DERWENT, R. G., WUEBBLES, D. J. & MORCRETTE, J-J.
(1990). Radiative forcing of climate. Pp. 41-68 in Climate
Change: The IPCC Scientific Assessment. (Ed. J. T. Houghton,
G. J. Jenkins & J. J. Ephraums). Cambridge University Press,
Cambridge, UK: 365 pp.
WASSMANN, R. & THEIN, U. G. (1989). Spatial and seasonal
variation of methane emission from an Amazon floodplain lake.
Paper presented at the Workshop on 'Cycling of Reduced Gases in
the Hydrosphere,' SIL Congress, Munich, Germany, 17 August 1989.
(Manuscript, 8 pp.)
15
FIGURE LEGENDS
Figure 1:Brazil's Legal Amazon region with the four existing
large dams.
Figure 2:Seventy-nine planned and existing dams in Brazilian
Amazonia. Only dams in the ELETRONORTE system are
included, not those planed by State Governments or
private firms. Redrawn from Seva (1990), who based the
map on Brazil, ELETROBRÁS (1986) and Brazil,
ELETRONORTE (1985c).
Figure 3:Zones for distribution of biomass in reservoirs.
Figure 4:Balbina: CO2 and CH4 emissions (million t of gas).
Figure 5:Hydroelectric greenhouse gas emissions (CO2-equivalent
carbon).
Figure 6:Balbina: Greenhouse gas emissions (CO2-equivalent
carbon).
16
TABLE I: EXISTING AND PLANNED DAMS IN BRAZILIAN AMAZONIAa
Dam
No.
Dam name
River
Valley
Projected
Installed
Capacity
(MW)
---------------------------------------------------------1
São Gabriel
Uaupés/Negro
2,000
2.
Santa Isabel
Uaupés/Negro
2,000
3.
Caracaraí-Mucajaí
Branco
1,000
4.
Maracá
Uraricoera
500
5.
Surumu
Cotingo
100
6.
Bacarão
Cotingo
200
7.
Santo Antônio
Cotingo
200
8.
Endimari
Ituxi
200
9.
Madeira/Caripiana
Mamoré/Madeira 3,800
10.
Samuel
Jamarí
200
11.
Tabajara-JP-3
Ji-Paraná
400
12.
Jaru-JP-16
Ji-Paraná
300
13.
Ji-Paraná-JP-28
Ji-Paraná
100
14.
Preto RV-6
Roosevelt
300
15.
Muiraquitã RV-27
Roosevelt
200
16.
Roosevelt RV-38
Roosevelt
100
17.
Vila do Carmo AN-26
Aripuanã
700
18.
Jacaretinga AN-18
Aripuanã
200
19.
Aripuanã AN-26
Aripuanã
300
20.
Umiris SR-6
Sucunduri
100
21.
Itaituba
Tapajós
13,000
22.
Barra São Manuel
Tapajós
6,000
17
23.
Santo Augusto
Juruena
2,000
24.
Juruena
1,000
25.
Barra do Madeira
(Juruena)
Barra do Apiacás
Teles Pires
2,000
26.
Talama (Novo Horizonte)
Teles Pires
1,000
27.
Curuá-Una
Curuá-Una
28.
Belo Monte (Cararaô)
Xingu
8,400
29.
Babaquara
Xingu
6,300
30.
Ipixuna
Xingu
2,300
31.
Kokraimoro
Xingu
1,900
32.
Jarina
Xingu
600
33.
Iriri
Iriri
900
34.
Balbina
Uatumã
300
35.
Fumaça
Uatumã
100
36.
Onça
Jatapu
300
37.
Katuema
Jatapu
300
38.
Nhamundá/Mapuera
Nhamundá
200
39.
Cachoeira Porteira
Trombetas
1,400
40.
Tajá
Trombetas
300
41.
Maria José
Trombetas
200
42.
Treze Quedas
Trombetas
200
43.
Carona
(Trombetas)
300
44.
Carapanã
Erepecuru
600
45.
Mel
Erepecuru
500
46.
Armazém
Erepecuru
400
47.
Paciência
Erepecuru
300
100
18
48.
Curuá
Curuá
100
49.
Maecuru
Maecuru
100
50.
Paru III
Paru
200
51.
Paru II
Paru
200
52.
Paru I
Paru
100
53.
Jari IV
Jari
300
54.
Jari III
Jari
500
55.
Jari II
Jari
200
56.
Jari I
Jari
100
57.
F. Gomes
Araguari
100
58.
Paredão
Araguari
200
59.
Caldeirão
Araguari
200
60.
Arrependido
Araguari
200
61.
Santo Antônio
Araguari
100
62.
Tucuruí
Tocantins
6,600
63.
Marabá
Tocantins
3,900
64.
Santo Antônio
Tocantins
1,400
65.
Carolina
Tocantins
1,200
66.
Lajeado
Tocantins
800
67.
Ipueiras
Tocantins
500
68.
São Félix
Tocantins
1,200
69.
Sono II
Sono
200
70.
Sono I
Sono
100
71.
Balsas I
Balsas
100
72.
Itacaiúnas II
Itacaiúnas
200
73.
Itacaiúnas I
Itacaiúnas
100
19
74.
Santa Isabel
Araguaia
2,200
75.
Barra do Caiapó
Araguaia
200
76.
Torixoréu
Araguaia
200
77.
Barra do Peixe
Araguaia
300
78.
Couto de Magalhães
Araguaia
200
79.
Noidori
Mortes
100
---------Total:
85,900
---------------------------------------------------------------a Based on list derived from ELETRONORTE sources by Seva (1990:
26-27).
Dam numbers correspond to numbering in Figure 2.
20
TABLE II:
RIVERBED AREAS IN AMAZONIAN RESERVOIRS
Reservoir River
Length
Average
Riverbed Source
in
width
area
reservoir (m)b
(km2)
a
(km)
----------------------------------------------------------------Balbina
Uatumã
210
139
29
Pitinga
100
99
10
c
Balbina total:
39
CuruáUna
Curuá-Una
Muju
Mojui dos Campos
80
69
40
35
20
15
Curuá-Una total:
6
1
0
7
d
Samuel
Jamari
255
116
29
e
Tucuruí
Tocantins
170
1891
321
f
TOTAL
397
---------------------------------------------------------------a Lengths of Balbina and Tucuruí from Juras (1988).
b River widths measured at approximately 5-km intervals using
the following maps or images indicated under Source at the
following scales: Balbina: 1:100,000; Samuel: 1:40,000; Tucuruí:
1:250,000. Widths of Curuá-Una and tributaries are based on 6
direct measurements by Robertson (1980).
c Brazil, ELETRONORTE, 1985a.
d Robertson, 1980.
e Brazil, ELETRONORTE, nd-a.
f Brazil, Projeto RADAMBRASIL, 1981.
21
TABLE III:
Dam
FLOODING BY HYDROELECTRIC DAMS
State
Dates of filling
----------------------------------------------------------------1
2
3
----------------------------------------------------------------Balbina
Amazonas
1 Oct. 1987 - 15 July 1989
Curuá-Una
Pará
Jan. 1977 - May 1977
Samuel
Rondônia
Oct. 1988- July 1989
Tucuruí
Pará
6 Sept. 1984 - 30 Mar. 1985
----------------------------------------------------------------TOTALS
----------------------------------------------------------------a Balbina riverbed area estimated from ELETRONORTE (1985a)
1:100,000 scale map; Curuá-Una riverbed area calculated from map
and river width measurements of Robertson (1980); Samuel riverbed
area estimated from length; Tucuruí riverbed area from Brazil,
Projeto RADAMBRASIL, 1981.
b Official areas for comparison only. Sources: Balbina: Brazil,
ELETRONORTE, 1987; Curuá-Una: Robertson, 1980: 9; Samuel: Revilla
Cardenas, 1986; Tucuruí: Brazil, ELETRONORTE, nd [1987]: 24-25.
c Three small dams outside the ELETRONORTE system are: Pitinga
(filled in 1982 and raised in 1993; 1989 LANDSAT-measured area =
62 km2) near Balbina in Amazonas, Boa Esperança (filled prior to
1989; LANDSAT-measured area = 24 km2) in Maranhão, and Jatapu
(filled in 1994; official area = 45 km2) in Roraima. All of the
area flooded by these dams represents forest loss. The two dams
filled prior to 1989 would bring the LANDSAT-measured total area
to 6017 km2 and the estimated forest loss to 5620 km2.
d LANDSAT-measured water surface includes riverbed and previous
deforestation. To avoid double counting, estimated forest loss
does not include previous deforestation: Column 8 = Column 7 Column 5. (Source: Fearnside et al., nd).
e Balbina 1988-1989 rate is an overestimate due to lack of a
1988 image (230/61) covering approximately 10-20% of the
reservoir area nearest the dam. If unimaged area represented 10%
22
of the measured 1988 area, then Balbina loss rate in 1988-1989
was 348 km2 yr-1 (a decrease of 34%); if 20%, then loss rate was
162 km2 yr-1 (a 70% decrease).
f Area measured by Robertson (1980) from Centrais Elétricas do
Para (CELPA) map. Paiva (1977) gives the official area as 86
km2.
g Area cleared by ELETRONORTE only (Brazil, ELETRONORTE,
nd[1987].
23
[Table III part 2]
Previous
RiverOfficial
LANDSATEstimated
1988-1989
deforesbed
area
measured
forest
forest
tation in
area
of
water
loss
loss
water
surface
(km2)d
rate
flooded
(km2)a
area
surface
area in
(km2 yr-1)
(km2)b
1989 (km2)c
(km2)
----------------------------------------------------------------4
5
6
7
8
9
----------------------------------------------------------------39
2,360
3,147
0
7
102
72
91
29
645
465
436
436
321
2,430
2,247
1,926
0
400g
3,108
693e
55
65f
0
----------------------------------------------------------------546
397
5,537
5,931
5,534
1,129
-----------------------------------------------------------------
24
TABLE IV:
BIOMASS BY STRATUM AT MANAUS: APPROXIMATE DRY WEIGHTSa
Mean height
Approximate dry weight biomass (t ha-1)
b
(m)
---------------------------------------------------------Leaves
Stems
Branches
Midpoint Range
(±)
----------------------------------------------------------------A
29.6
5.9
1.1
66.1
23.1
Stratum
B
21.1
4.4
3.4
127.9
58.5
C1
11.5
3.1
1.9
22.5
12.4
C2
4.8
1.2
1.0
4.8
1.7
D
2.4
0.7
1.0
0.9
0.3
E
0.6
0.5
0.3
0.4
0.0
----------------------------------------------------------------8.6
222.5
96.0
----------------------------------------------------------------Vines
21.9
Epiphytes
0.1
Totals for non-wood,
wood and all live
above-ground biomass
30.6
Fine litterc
10.9
Downed dead woodd
Standing dead woodd
Totals for non-wood,
41.5
wood and all
above-ground biomass
-----------------------------------------------------------------
25
a Data for fresh weights from Klinge & Rodrigues (1973),
converted to dry weights using a constant correction factor of
0.475 derived for these data by the same authors (Klinge et al.,
1975).
b Maximum height of the stand was 38.1 m. The stand is located
64 km east of Manaus at INPA's Reserva Egler.
c Average of 5 measurements at hydroelectric dam sites at
Samuel, Belo Monte and Babaquara (Revilla Cardenas, 1987, 1988;
Martinelli et al., 1988).
d
Klinge, 1973: 179.
26
[Table IV, part 2]
---------------Total
Total
live
live
wood
biomass
---------------89.3
90.3
Percent of total above-ground biomass
----------------------------------------------Leaves Stems
Branches
Total
Total
live
live
wood
biomass
----------------------------------------------0.28
17.15
6.00
23.14
23.43
186.4
189.8
0.87
33.17
15.16
48.33
49.21
34.9
36.7
0.48
5.83
3.21
9.04
9.52
6.5
7.4
0.25
1.23
0.44
1.68
1.92
1.2
2.2
0.27
0.22
0.09
0.31
0.58
0.4
0.7
0.07
0.10
0.00
0.10
0.17
----------------------------------------------------------------318.5
327.1
2.23
57.69
24.91
82.60
84.83
----------------------------------------------------------------5.67
0.03
318.5
349.1
7.92
82.60
90.52
2.83
18.02
4.67
7.6
1.97
344.2
385.6
10.76
89.24
100.00
-----------------------------------------------------------------
27
TABLE V: BIOMASS PRESENT AND DIVISION BY ZONES IN AMAZONIAN
RESERVOIRS
Dam
Year
filled
Water
Forest
Forest
surface
flooded
flooded
area at
at operat
operating ating
minimum
level
level
level
(ha)
(ha)
(ha)
-------------------------------------------------Balbina
1987
314,700
310,840
206,829
Curuá-Una
1977
7,200
6,480
5,500
Samuel
1988
46,500
43,551
30,901
Tucuruí
1984
224,700
192,553
106,787
-------------------------------------------------TOTALS
593,100
553,424
350,017
-------------------------------------------------a Brazil, ELETRONORTE, 1987; forest flooded at minimum level is
adjusted by ratio of LANDSAT-measured area to official area at
the operating level.
b Paiva, 1977: 17 (value for average depth at maximum operating
level).
c Revilla Cardenas & do Amaral, 1986; forest area flooded at
minimum water level taken as proportional to water volumes at
these two levels from Brazil, ELETRONORTE, nd [1992]b: 5.
d
Revilla Cardenas et al., 1982.
e Uses 58.0 m above mean sea level as minimum normal operating
level (Brazil, ELETRONORTE, nd [ca. 1983]. A minimum operating
level of 51.6 m (Brazil, ELETRONORTE, nd-b: p. 2-1; Brazil
ELETRONORTE, nd [1992]a) implies drawdown depth of only 3.3 m.
Forest area flooded at minimum water level is taken as
proportional to water volumes at these two levels from Brazil,
ELETRONORTE, nd [ca. 1983], p. 6).
f
Brazil, ELETRONORTE, nd [1992]a.
g
Brazil, ELETRONORTE, nd [1992]b.
28
[Table V, part 2]
ApproxAboveBiomass
Average
Depth
imate
ground
source
depth at
source
total
biomass
minimum
biomass
(t ha-1)
level
-1
(m)
(t ha )
------------------------------------------------------441
336
a, pp.
6.2
a, p. 14
172-3
428
327
Fearnside,
6.2
b
nd-a
557
425
c, p. 4
5.3
b
517
394
d, p. 90
9.7
e
-------------------------------------------------------------------------------------------------------------
29
[Table V, part 3]
Dam
Initial biomass by zone (t dry matter ha-1)
---------------------------------------------------------------AboveSurface Anoxic
Anoxic
BelowTotal
water
water
water
water
ground
wood
wood
wood
leaves
wood
and other
non-wood
---------------------------------------------------------------Balbina 264.69
4.55
31.44
35.70
104.74
441.12
Curuá-Una 257.11
4.42
30.54
34.68
101.74
428.50
Samuel
5.74
34.56
45.11
132.34
557.34
339.59
Tucuruí
291.40 5.33
55.47
41.82
122.69
516.71
----------------------------------------------------------------
30
[Table V, part 4]
Dam
Logging removals
of biomass
(t ha-1of
reservoir area)
----------------Before
After
filling filling
Fraction
Years of postof original filling logging
anoxic
activity
zone
-----------------wood
Begin End
removed
after
filling
----------------------------------------------------------------Balbina
0
0
0.5
1993
2000
Curuá-Una
Samuel
0
0
Fraction
of aboveground
wood
removed
before
filling
0
0
0.2
0
Tucuruí
0.01
0.5
1988
2000
-----------------------------------------------------------------
31
[Table V, part 5]
Area cleared prior
Draw- Drawto filling (ha)
down
down
---------------------------- depth depth
SeasonPermaTotal
(m)
source
ally
nently
flooded
flooded
zone
zone
--------------------------------------------0
5,000
5,000
4
4.5
guess
7
f, p. 5
2,000
8,000
10,000
14
g, p. 5
---------------------------------------------
32
TABLE VI:
PARAMETERS FOR HYDROELECTRIC DAM EMISSION CALCULATIONS
Parameter
Value
----------------------------------------------------------------Above-ground fraction
Average depth of surface water zone
Leaf decay rate in seasonally inundated zone
Above-water decay rate (0-4 yrs)
Above-water decay rate (5-7 yrs)
Above-water decay rate (8-10 yrs)
Above-water decay rate (>10 yrs)
Fraction of above-water decay via termites
Wood decay rate in surface water zone
Leaf decay rate in anoxic water zone
Wood decay rate in anoxic water zone
Below-ground decay rate in permanently flooded zone
Below-ground decay rate in seasonally flooded zone
Fraction of C released as CH4 in termite decay
Fraction of C released as CH4 in termite decay (high
trace gas scenario)
Fraction of C released as CH4 in surface water zone decay
0.773
1
-0.5
-0.1691
-0.1841
-0.0848
-0.0987
0.0844
-0.0139
-0.0035
-0.0014
-0.0014
-0.0139
0.002
0.0079
0
Fraction of C released as CH4 in anoxic water zone decay
1
1
Fraction of C released as CH4 in below-ground decay
Fraction of water covered by macrophytes
0.1
Methane release from macrophyte beds
174.67
Methane release from open water
53.93
Carbon content of wood
0.50
Carbon content of leaves and fine litter
0.45
Carbon content of vines and epiphytes
0.45
Rate of wood fall from above-water zone
0.1155
Fraction of CH4 oxidized in water
0
Leaf aerobic decay, first year
0.025
Leaf aerobic decay, after first year
0.0085
-----------------------------------------------------------------
33
Biomass of components in unlogged original forests
Average
Average
Initial
Initial
Initial
Initial
Initial
Initial
Initial
total biomass of forest
water depth at minimum level
biomass present: leaves
biomass present: fine litter
biomass present: vines and epiphytes
biomass present: wood above water
biomass present: wood in surface zone
biomass present: wood in anoxic zone
biomass present: below-ground
428
10
7.30
8.75
18.64
240.33
4.42
47.32
101.74
34
[Table VI, part 2]
Units
------------
Source
---------------------------------------------------
meter
Fearnside, nd-a
Assumption, based on commercial timber spoilage
Fraction
Fraction
Fraction
Fraction
yr-1 Assumption
yr-1Assumed same as felled forest (Fearnside, nd-b)
yr-1Assumed same as felled forest (Fearnside, nd-b)
yr-1 Assumed same as felled forest (Fearnside, nd-b)
Fraction yr-1 Assumed same as felled forest (Fearnside, nd-b)
Fraction
Fraction
Fraction
Fraction
Fraction
Fraction
Assumed same as felled forest (Martius et al., nd)
yr-1
yr-1
yr-1
yr-1
yr-1
Assumption: average lifetime = 50 years
Assumption: average lifetime = 200 years
Assumption: average lifetime = 500 years
Assumption: average lifetime = 500 years
Assumption: average lifetime = 50 years
Calculated from measurement by Martius et al., 1993
for Nasutitermes macrocephalus (a várzea species)
Calculated from measurement by Martius et al., 1993
for Nasutitermes macrocephalus (a várzea species)
Assumption
Assumption
Assumption
Assumption
µg m-2 day-1
Table VIII
Table VIII
µg m-2 day-1
Fearnside et al., 1993
Assumption
Assumption
Fraction yr-1 Assumption: average lifetime = 6 years
Assumption
Fraction of
Calculated from Brazil, ELETRONORTE, 1987: 261
original
(OXY-STRATIF model parameter for Balbina). Value
leaf biomass divided by 10 (as a guess at the exaggeration in
lost annually OXY-STRATIF)
Fraction of
Calculated from Brazil, ELETRONORTE, 1987: 261.
original
Value divided by 10 (as a guess at the exaggeration
leaf biomass
in OXY-STRATIF)
lost annually
------------ ---------------------------------------------------
35
t ha-1
meters
t
t
t
t
t
t
t
ha-1
ha-1
ha-1
ha-1
ha-1
ha-1
ha-1
Assumption
Calculated
Calculated
Calculated
Calculated
Calculated
Calculated
Calculated
from
from
from
from
from
from
from
total
total
total
total
total
total
total
biomass
biomass
biomass
biomass
biomass
biomass
biomass
and
and
and
and
and
and
and
Table
Table
Table
Table
Table
Table
Table
IV.
IV.
IV.
IV.
IV.
IV.
IV.
36
TABLE VII: APPROXIMATE QUANTITIES OF BIOMASS PRESENT IN 1990
(106 t of biomass)
PERMANENTLY FLOODED ZONE (at minimum operating water level)
Abovewater
wood
Surface
water
wood
Anoxic
water
wood
Anoxic
water
leaves
and other
non-wood
----------------------------------------------------------------Balbina
28.85
0.89
20.50
7.09
Curuá-Una
0.04
0.02
0.84
0.15
Samuel
6.17
0.11
2.17
1.07
Tucuruí
---------TOTALS
----------
6.00
0.41
13.01
3.52
-------------------------------------------41.06
1.44
36.52
11.84
--------------------------------------------
37
SEASONALLY FLOODED ZONE (at maximum normal operating water level)
Abovewater
wood
---------Balbina
Leaves
UnderBelowand
water
ground
other
wood
wood
non-wood
--------------------------------------------19.61
2.02
2.41
10.11
Curuá-Una
0.04
0.00
0.01
0.08
Samuel
2.77
0.42
0.46
1.57
Tucuruí
----------TOTALS
-----------
7.47
0.78
6.35
9.54
--------------------------------------------29.88
3.22
9.23
21.30
---------------------------------------------
38
[Table VII, part 2]
Belowground
wood
Total
---------------27.19
84.52
0.51
1.56
3.04
12.57
10.46
33.41
---------------41.20 132.05
----------------
39
Total
-------34.14
0.13
5.22
24.14
-------63.64
--------
40
TABLE VIII:
METHANE EMISSIONS FROM AMAZON FLOODPLAIN ECOSYSTEMS
Habitat
-------------------------
------------------------Lakes, open water
Lakes, macrophyte beds
Lakes, flooded forest
Methane flux
(mg CH4 m-2 day-1
----------------------------------Low
High
Eight
water
water
lakes
CAMREX
CAMREX
near
cruise 11
cruise 9
Manaus
(1)
(1)
(1)
----------------------------------40
88
58
(±12)
(±30)
(±16)
131
(±47)
390
(±109)
251
(±58)
7.1
74
55
(±3.4)
(±19)
(±13)
----------------------------------------------------------Sources:
(1) Devol et al., 1990.
(2) Wassmann & Thein, 1989.
(3) Bartlett et al., 1990.
(4) For comparison, Aselmann & Crutzen (1990: 446) estimate the
average for lakes of the world to be 43 mg CH4 m-2 day-1.
41
[Table VIII, part 2]
-------------------------------------------------Lago da Machantaria
NASA/
Value
(near Manaus)
ABLE
assumed for
------------------------- rising Amazonian
Low
Rising High
water
reservoirs
water
water
water
(2)
(2)
(2)
(3)
(4)
---------------------------------------50-100
5-50
5-25
74
53.9
(±14)
dry
0-50
0-100
dry
0-200
0-200
201
(±35)
174.7
126
(±20)
----------------------------------------
42
TABLE IX: GREENHOUSE GAS FLUXES BY PROCESS IN 1990 FROM
HYDROELECTRIC DAMSa
PERMANENTLY INUNDATED ZONE
Area
of
permanently
inundated zone
(ha)
Underwater decay
---------------Wood in surface
water zone
---------------CH4
(106
t gas)
-------------------- --------------------------- ---------------Balbina
206,829
0.00
0.28
8.61
0.00
Curuá-Una
Samuel
Above-water decay
--------------------------Termites
Other
-----------------CH4
CO2
CO2
(106
(106
(106
t gas)
t gas) t gas)
5,500
0.00
0.00
0.01
0.00
30,901
0.00
0.06
1.84
0.00
Tucuruí
106,787
0.00
0.06
1.98
0.00
-------------------- ----------------------------- -------------TOTALS
350,017
0.00
0.41
12.43
0.00
-------------------- ----------------------------- --------------
43
[Table IX, part 2]
Below-ground decay
---------------------------------------------- -----------------Wood in anoxic
Leaves and other
water zone
non-wood biomass
----------------------------------------------CH4
CO2
CO2
CH4
CO2
CH4
CO2
(106
(106
(106
(106
(106
(106
t gas)
t
(106
gas)
t gas)
t gas)
t gas)
t gas)
t gas)
---------------------------------------------- ----------------0.02
0.02
0.00
0.01
0.10
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.00
0.01
0.01
0.00
0.01
0.05
0.01
0.00
---------------------------------------------- -----------------0.04
0.03
0.00
0.02
0.20
0.04
0.00
---------------------------------------------- ------------------
44
[Table IX, part 3]
SEASONALLY INUNDATED ZONE
Area
of
seasonally
inundated zone
(ha)
Above-water decay
--------------------------Termites
Other
-----------------CO2
CO2
CH4
(106
(106
(106
t gas)
t gas)
t gas)
------------------- --------------------------Balbina
104,011
0.0004
0.46
14.22
Curuá-Una
Samuel
980
0.0000
0.00
0.03
12,650
0.0001
0.07
2.16
Tucuruí
85,766
0.0002
0.23
7.06
------------------- --------------------------TOTALS
203,407
0.0006
0.77
23.47
------------------- ---------------------------
45
[Table IX, part 4]
Underwater decay
Below-ground decay
--------------------------------------Wood
Leaves and other
-----------------non-wood biomass
CO2
---------------------------------------- CH4
CH4
CO2
CH4
CO2
(106
(106
(106
(106
(106
t gas)
t gas)
(106
t gas)
t gas)
t gas)
t gas)
---------------------------------------- ----------------0.002
0.000
0.005
0.05
0.00007 0.00
0.000
0.000
0.000
0.00
0.00000
0.00
0.000
0.000
0.001
0.02
0.00001
0.00
0.006
0.000
0.002
0.05
0.00006 0.00
---------------------------------------- ----------------0.009
0.000
0.007
0.13
0.00014 0.00
---------------------------------------- -----------------
46
[Table IX, part 5]
ENTIRE RESERVOIR
Area of
Open
MacroTotal from abovereserwater
phyte
water decay
voir
beds
---------------------at operCH4
CH4
CO2
ating
CH4
level
(106
(106
(106
(106
(ha)
t gas)
t gas)
t gas)
t gas)
----------------------------------------------------------------Balbina
314,700
0.06
0.02
0.00
23.58
Curuá-Una
Samuel
7,200
0.00
0.00
0.00
0.03
46,500
0.01
0.00
0.00
4.13
Tucuruí
224,700
0.04
0.01
0.00
9.34
----------------------------------------------------------------TOTALS
593,100
0.11
0.04
0.00
37.07
----------------------------------------------------------------a These results use the "low trace gas scenario" emission factor
for termites (Table VI). Using the "high" value (based on Goreau
and Mello, 1987) increases the total emission only marginally
from 0.259 to 0.260 X 106 t of methane gas.
47
[Table IX, part 6]
Total from
underwater
decay
-----------------CH4
CO2
(106
(106
t gas)
t gas)
Total
CH4
Total
CO2
CO2-equivalent carbon
(100-yr, zero discount;
direct effects)
(106
t gas)
(106
t gas)
(106 t carbon)
------------------------------------------------------0.07
0.18
0.14
23.75
6.91
0.00
0.00
0.00
0.03
0.02
0.01
0.07
0.02
4.20
1.21
0.04
0.11
0.09
9.45
2.85
------------------------------------------------------0.12
0.36
0.26
37.44
10.99
-------------------------------------------------------
48
TABLE X: CALCULATION OF EMISSIONS FROM FOSSIL FUELS DISPLACED BY
BALBINA AND TUCURUI
A.) DAM CHARACTERISTICS
Sources
----------------Balbina Tucuruí
--------------------------------------------------------------Installed capacity
MW
250
4000
Installed capacity
TWh yr-1
2.19
35.06
Average generation
MW
110.3
2057
a
Average generation
TWh yr-1
0.97
18.03
b
Percent of capacity (%)
44.1
51.4
Units
Balbina
(1993)
Tucuruí
(1991)
49
B.) MANAUS POWER AND FUEL USE
Units
Amounts
Source
-------------------------------------------------------------Power consumption in 1986
TWh
0.94
Projected substitution
for 1993:
Diesel
106 l 316
Diesel
GWh
791
Fuel oil
103 t 113
Fuel oil
GWh
333
Total:
TWh
1.12
c
--------------------------------------------------------------
50
C.) EMISSION FACTORS FOR FUELS
Emission factor (t gas per 106 l)d
-------------------------------------CO2
CH4
N2O
----------------------------------------------------Diesel
2,730
0.12
0.16
(0.06-0.25)
(0.13-0.4)
Fuel
Light oil
2,830
Heavy oil
3,090
0.02
(0.01-0.21)
0.16
(0.13-0.4)
0.13
0.16
(0.03-0.12)
(0.13-0.4)
-----------------------------------------------------
51
D.) BALBINA FOSSIL FUEL SUBSTITUTION (official projection for
1993)
Fuel
Million
Density
Million
liters
(t m-3)e
tons
--------------------------
Avoided emissions (t gas)
CO2
CH4
N2O
----------------------------------------------------------------Diesel
316
0.87
275
862,680
38
51
Fuel oilf 122
0.93
113
375,452
15
20
TOTAL
388
1,238,132
53
71
----------------------------------------------------------------E.) GLOBAL WARMING POTENTIALS OF GASES
Global warming potentialg
CH4
N2O
CO2
--------------------------1
11
270
--------------------------------------------------------
52
F.)
CO2-GAS EQUIVALENTS OF FUELS DISPLACED BY BALBINA
Fuel
CO2-gas equivalent (t)
-----------------------------------------------------------CO2
CH4
N2O
Total
-----------------------------------------------------------Diesel
862,680
417
13,865
876,962
Fuel oil
375,452
167
5,331
380,950
TOTAL
1,238,132
584
19,196
1,257,911
-----------------------------------------------------------NOTES:
a Brazil, ELETRONORTE, 1985b. Note: Brazil, ELETRONORTE/
MONASA/ENGE-RIO, 1976 gives average generation as 109 MW (= 0.96
TWh yr-1).
b Brazil, ELETRONORTE, nd [1992]a: 3.
c Brazil, ELETRONORTE, 1985b: Quadro 3.7.
d Jaques, 1992.
e Jaques, 1992: 48.
f Assumed to be heavy fuel oil.
g Radiative forcing relative, per t of gas, relative to 1 t of
CO2, over a 100-yr time horizon without discounting (Isaksen et
al. 1992: 56).
53
TABLE XI: COMPARISON OF BALBINA AND TUCURUI 1990 HYDROELECTRIC
GENERATING EMISSIONS WITH OTHER EMISSIONS SOURCES
Emission
source
Hydro.
Hydro./
Emission/generation
Note
annual
fossil
------------------106 t
emission
fuel
106 t
(CO2-C
emission CO2CO2equiv.)
ratio
equiv./
equiv. C/
(t)
TWh
TWh
----------------------------------------------------------------Balbina
6,908,399
20.1
26.20
7.14
Tucuruí
2,852,731
0.4
0.58
0.16
a
Manaus fossil fuel
Coal-fired
Natural gas
1.30
0.4
1.0
0.35
0.11
0.27
b, c
b
Churchill/Nelson Dam (Canada)
0.04-0.06 0.01
b
Grand Rapids Dam (Canada)
0.30-0.5 0.11
b, c
----------------------------------------------------------------a Assumes fossil fuel mix substituted by Tucuruí
is the same as that used in Manaus.
b Comparisons from Rudd et al., 1993 (N.B.: these authors use a
value of 60 for the global warming potential of methane, much
higher than the IPCC value of 11 used for Balbina and Tucuruí).
c Uses
54
midpoint.
55
56
Fig. 3.
Fig. 4
57
Fig 6
58