This article appeared in a journal published by Elsevier. The attached
copy is furnished to the author for internal non-commercial research
and education use, including for instruction at the authors institution
and sharing with colleagues.
Other uses, including reproduction and distribution, or selling or
licensing copies, or posting to personal, institutional or third party
websites are prohibited.
In most cases authors are permitted to post their version of the
article (e.g. in Word or Tex form) to their personal website or
institutional repository. Authors requiring further information
regarding Elsevier’s archiving and manuscript policies are
encouraged to visit:
http://www.elsevier.com/copyright
Author's personal copy
Atmospheric Environment 42 (2008) 7050–7058
Contents lists available at ScienceDirect
Atmospheric Environment
journal homepage: www.elsevier.com/locate/atmosenv
A comparative and critical evaluation of odour assessment
methods on a landfill site
Laura Capelli a, *, Selena Sironi a, Renato Del Rosso a,
Paolo Céntola a, Massimiliano Il Grande b
a
Politecnico di Milano, Olfactometric Laboratory, Department of Chemistry, Materials and Chemical Engineering ‘‘Giulio Natta’’, P.za Leonardo Da Vinci,
32, 20133 Milano, Italy
b
Progress S.r.l., Via N.A. Porpora, 147, 20131 Milano, Italy
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 1 October 2007
Received in revised form 11 April 2008
Accepted 12 June 2008
This paper discusses the application of three different odour characterization techniques,
i.e. chemical analyses, dynamic olfactometry and electronic noses, for the assessment of
odour emissions from a landfill site. The results of the chemical analyses, which are useful
to determine the chemical composition of odours, show no correlation with the odour
concentration values measured by dynamic olfactometry. Olfactometric analyses enabled
to measure odour concentration and thereby to quantify the sensory impact of odours.
Finally, the continuous ambient air monitoring by electronic noses allowed to quantify the
time percentage in which odours are detected at the landfill boundaries and at a receptor,
which always turned out to be lower than 15%. This study represents a critical review of
employing three different odour characterization methods for differing reasons on the
same site, showing that, whilst the results don’t necessarily correlate, they do have an
intrinsic value, and therefore demonstrating the complexity of environmental odour
measurement.
Ó 2008 Elsevier Ltd. All rights reserved.
Keywords:
Odour emissions
Electronic nose
Dynamic olfactometry
Odour concentration
Gas chromatography
1. Introduction
Odour emissions are one of the major environmental
problems that several industrial categories have to face.
Complaints from the population living near plants characterized by unpleasant odour emissions (e.g. waste treatment and disposal plants, wastewater treatment plants,
chemical industries, food industries, livestock activities,
rendering plants, tanneries, etc.) are becoming more and
more frequent, and they often are the origin of legal suits
(in the case of existing plants), or they may represent the
limiting factor for the construction of new plants (Schlegelmilch et al., 2005).
* Corresponding author. Tel.: þ39 02 23993206; fax: þ39 02 23993291.
E-mail addresses: laura.capelli@polimi.it (L. Capelli), selena.sironi@
polimi.it (S. Sironi), renato.delrosso@polimi.it (R. Del Rosso),
paolo.centola@polimi.it (P. Céntola), m.ilgrande@olfattometria.com (M. Il
Grande).
1352-2310/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved.
doi:10.1016/j.atmosenv.2008.06.009
Given the high number of industrial typologies facing
environmental odour problems, their relative abundance
on the territory and the fact that the population is
becoming more sensitive towards topics concerning air
quality, regulatory and environmental protection bodies
are in need of specific tools for odour nuisance assessment.
The techniques available for odour nuisance characterization and quantification are substantially of three
different kinds (Gostelow et al., 2001):
- Analytical: chemical analyses;
- Sensorial: dynamic olfactometry; and
- Senso-instrumental: electronic nose.
Analytical techniques allow to determine the qualitative
and quantitative composition of a gas mixture using
suitable separation and identification techniques, e.g. gaschromatography coupled with mass-spectrometry (GC–
MS) (Davoli et al., 2003). This technique has the advantage
Author's personal copy
L. Capelli et al. / Atmospheric Environment 42 (2008) 7050–7058
of being consolidated and therefore considered objective,
repeatable and accurate. The disadvantage relies in the
difficulty of relating the chemical composition of an
odorous mixture to its olfactory properties (Stuetz et al.,
1999). This is mainly due to the effects of synergy or
masking that can occur within the different compounds
(odour properties are not necessarily additive). Another
problem is given by the difficulty, when dealing with
complex odours, of identifying a limited number of
compounds, representative of the perceived odour. Moreover, in general it is also difficult to analytically detect the
presence of some compounds at extremely low concentrations, which may nonetheless originate odour due to
their low odour thresholds. As a result, good correlations
between olfactory properties and analytical concentrations
can be found for mixtures composed by few and well
defined different compounds.
Sensorial techniques, such as dynamic olfactometry (EN
13725, 2003), use the human nose as a sensor, and therefore enable to characterize odours by referring directly on
their effects on a panel of qualified examiners. In addition
to olfactory properties there are several factors that may
influence odour perception. The most important one is the
variability of human olfaction between different subjects.
This problem is minimized by using a panel composed by
several examiners, selected with precise criteria in order to
have people with a standardized olfaction, and by averaging the single examiners’ responses.
Senso-instrumental techniques use artificial noses,
which perform instrumentally the functions of human
olfaction. Electronic noses are complex systems with
a human nose like structure (Pearce, 1997). An array of
partially selective sensors gives a characteristic pattern of
each analyzed odorous mixture, which is subsequently
classified based on a reference database acquired by the
instrument in a previous training phase (Persaud and Dodd,
1982). Performances of these instruments depend critically
on a set of operational choices, i.e. on the sensor realization
technique and working conditions, on the measurement
settings, on the data processing methods and on the classification algorithms (Sironi et al., 2007a). This technology
is widely used for odour recognition in the food industry
(Schaller et al., 1998; Ampuero and Bosset, 2003), but its
applications in the environmental sector are very recent
and still under study (Micone and Guy, 2007).
Among existing types of industrial installations that can
cause odour nuisance, landfills represent one of the most
common sources of odour emissions and complaint (Sironi
et al., 2005). Odours from landfill sites originate principally
from the atmospheric release of compounds that are
formed during the biological and chemical processes of
waste decomposition (El Fadel et al., 1997).
The aim of this paper is to discuss the application of the
above mentioned odour characterization and quantification techniques for the assessment of the odour emissions
of a municipal solid waste (MSW) landfill site of average
dimensions, having a surface of about 300,000 m2, located
in the North of Italy.
The monitoring campaigns were repeated in four
different periods of the year (winter, spring, summer and
fall), in order to improve the evaluation of the landfill odour
7051
impact by taking account of different meteorological
conditions. For a more complete evaluation of the results,
the meteorological data (especially wind speed and wind
direction) relevant to the four monitoring campaigns,
registered by a meteorological station installed inside the
landfill at issue, were analyzed.
This work represents a critical review of how three
different odour assessment methods can be employed for
evaluating the odour emissions from a landfill site. Through
the critical analysis of the results it is possible on one hand
to analyze the specificities of the three adopted odour
characterization techniques and on the other hand to
discuss the correlations between these techniques, thus
demonstrating the complexity of odour measurement in
the environment.
2. Experimental
2.1. Sampling
Independently from the adopted analysis technique, the
first problematic aspect of an odour monitoring campaign
is sampling. Representative gas samples should be
collected with the aim of characterizing the odour emissions associated with all the principal odour sources of the
landfill at issue (Bockreis and Steinberg, 2005). For this
purpose, specific strategies and suitable sampling equipment are needed (EN 13725, 2003).
Sampling on point sources (i.e. conveyed emissions, e.g.
through a stack) was carried out by sucking part of the
odorous airflow into an 8-L sampling bag in NalophanÔ
equipped with a TeflonÔ inlet tube by means of a depression pump. Sampling on passive area sources (i.e. liquid or
solid surfaces without an outward flow) was performed
using a wind tunnel system (Jiang and Kaye, 2001; Frechen
et al., 2004), which consists of a PET hood that is positioned
over the emitting surface. A neutral air stream is introduced
at known airflow rate from an air bottle into the hood,
simulating the wind action on the liquid or solid surface.
Air samples are then collected in the outlet duct by means
of a pump, which creates vacuum in a case in which the
sampling bag is inserted, thereby sucking air into the bag.
The wind tunnel used during the experimentation has
a circular section inlet and outlet duct, of 0.08 m diameter.
The central body of the hood used was a 0.25 m wide,
0.08 m high and 0.5 m deep rectangular section chamber.
Inside the inlet duct there is a perforated stainless steel grid
and inside the divergent that connects this duct to the
central body of the hood there are three flow deflection
vanes. Both these devices have the function of making the
airflow as homogeneous as possible (Sironi et al., 2006).
Gas samples were collected in different positions:
- inside the landfill, in correspondence of the principal
odour sources: landfill gas extraction wells (on
exhausted and active parcels), exhausted landfill
surface, waste grinder, oxygenated leachate collection
tanks and cogeneration fumes abatement plant;
- at the landfill boundaries: cogeneration zone
(boundary NW), offices (boundary SW) and landfill
entrance (boundary SSE); and
Author's personal copy
7052
L. Capelli et al. / Atmospheric Environment 42 (2008) 7050–7058
- outside the landfill, at two receptors where the presence of malodours from the landfill were often
lamented: receptor 1, a sports ground located at 2 km
SSW from the landfill, and receptor 2, a farm at 1.2 km
SW from the landfill.
2.2. Chemical analyses
The chemical analyses were carried out with the aim of
identifying and quantifying the atmospheric pollutants in
some critical points inside and outside the landfill, focusing
on the pollutants with a low odour detection threshold,
which may originate odour nuisance.
The ambient air samples were analyzed by gaschromatography
and
mass-spectrometry
(GC–MS)
preceded by cryogenic pre-concentration with liquid
nitrogen, according to the methodology EPA TO15, modified in order to determine the concentration of 140
compounds belonging to different pollutant families.
The instrument used for the analyses is a GC–MS system
model 6890N-5973N (Agilent Technologies) equipped with
a cryogenic pre-concentration system TDS2 (Gerstel) and
workstation with processing software and spectral database Wiley with 275000 spectra.
2.3. Olfactometric analyses
Dynamic olfactometry is a sensorial technique that
allows to determine the odour concentration (cod) of an
odorous air sample relating to the sensation caused by
the sample directly on a panel of opportunely selected
people. cod is expressed in European odour units per
cubic meter (ouE m3), and it represents the number of
dilutions with neutral air that are necessary to bring the
odorous sample to its odour detection threshold
concentration. The analysis is carried out by presenting
the sample to the panel at increasing concentrations by
means of a particular dilution device called olfactometer,
until the panel members start perceiving an odour that is
different from the neutral reference air. The cod is then
calculated as the geometric mean of the odour threshold
values of each panellist. As defined by the EN 13725,
2003, the individual threshold estimate is defined by the
two presentations in one dilution series, sorted on
growing odour concentration, where a certain change in
response from ‘‘false’’ to a consistently ‘‘true’’ response
occurs. The individual threshold estimate is calculated as
the geometric mean of the dilution factors of the two
defined presentations.
An olfactometer ECOMA Mannebeck model TO7, based
on the ‘‘yes/no’’ method, was used as a dilution device. This
instrument with aluminium casing has 4 panellist places in
separate open boxes. Each box is equipped with a stainless
steel sniffing port and a push-button for ‘‘yes’’ (odour
threshold). The measuring range of the TO7 olfactometer
starts from a maximum dilution factor of 1:64,000, with
a dilution step factor 2. All the measurements were conducted within 30 h after sampling, relying on a panel
composed of 8 panellists (4 þ 4).
2.4. Electronic nose
The instruments used for this work (Falasconi et al., 2005)
include a pneumatic assembly for dynamic sampling (pump,
electro-valve, and electronic flow meter), a thermally
controlled sensor chamber with 35 cm3 of internal volume
and an electronic board for controlling the sensor operational conditions. Each instrument has been equipped with
an array of six thin film MOS (Metal Oxide Semiconductor)
sensors, which make the system sensitive to a large spectrum of volatile compounds, and a humidity sensor.
In order to use electronic noses for monitoring the
ambient air and detecting the odours from the landfill at
issue, it is necessary to train the instruments to recognize
odours qualitatively, by attributing them to a specific
olfactory class, and quantitatively, by estimating the cod of
the analyzed air. During the training phase, which is
particularly important and delicate, it is necessary to create
a complete database that the instrument uses as a reference
for the pattern recognition. The training consists in the
analysis of different gas samples of known olfactory quality
diluted at different cod values (Sironi et al., 2007b).
During each monitoring, three electronic noses were
used contemporaneously, in order to analyze the ambient
air in three different positions. Two instruments were
installed at the plant boundaries (respectively at the offices
and at the landfill entrance), while the third instrument
was installed outside the plant, at receptor 1, located at
about 2 km SSW from the landfill. Each monitoring had
a duration of 10 days, during which the instruments
analyzed the air repeatedly every 15 min. For each of these
time intervals, the electronic noses pumped in the external
air for three consecutive minutes, and a recovery time of
12 min was left between each measurement.
3. Results
3.1. Determination of chemical composition by GC–MS
The analyses by GC–MS allowed to determine the
concentration trend of the chemical compounds for each
sampling point being considered.
As an example, Fig. 1 illustrates the concentration values
of the pollutant families determined in the ambient air
samples collected near the waste grinder.
The results show that the ratio between the different
pollutant families remains constant in all monitored points.
The relative abundance of the pollutant families has the
following trend:
Hydrocarbons > oxygenated comp: > halogenated comp:
> nitrogenous comp: > sulphured comp:
Once the chemical composition of an odorous gas mixture
is known, it is possible to estimate its cod based on the
analytical concentration of the single odorous compounds
and their odour threshold concentration values, according
to the following equation (Pagé et al., 2007):
cod;OT ¼
N
X
ci
OT
i
i¼1
Author's personal copy
7053
L. Capelli et al. / Atmospheric Environment 42 (2008) 7050–7058
10,000
1,000
Hydrocarbons
Oxygenated comp.
Halogenated comp.
Nitrogenous comp.
Sulphured comp.
µg/m3
100
10
1
0.1
I Camp.
Feb. 2006
II Camp.
May 2006
III Camp.
Aug. 2006
IV Camp.
Nov. 2006
Fig. 1. Waste grinder: analytical concentration of pollutant families.
Where ci is the analytical concentration of the odorous
compound i (in mg m3), OTi is the odour threshold
concentration of compound i (in mg ou1
E ), N is the number
of compounds in the mixture and cod,OT is the cod of the
mixture (in ouE m3) calculated from the chemical
concentration and the odour threshold of its components,
which will be defined as ‘‘theoretical odour concentration’’.
As an example, Fig. 2 reports the theoretical odour
concentration values associated with the examined
pollutant compounds relevant to the samples collected at
the waste grinder.
The results show that, even though the analytical
concentration of the oxygenated compounds is lower than
the analytical concentration of the hydrocarbons, the
theoretical cod values of both pollutant families are comparable, due to the fact that the odour threshold concentration
values relevant to the oxygenated compounds are generally
lower than the odour threshold concentration values of the
hydrocarbons. These two pollutant families are the ones that
mostly contribute to the overall odour mixture.
3.2. Determination of odour concentration by dynamic
olfactometry
Figs. 3 and 4 show the trends of the cod values of the
samples collected on the odour sources inside the landfill
and in the ambient air at the boundaries and outside the
landfill, respectively.
Based on the results of the olfactometric analyses it is
possible to make some consideration about the odour
emissions associated with the olfactory classes being
considered.
cod,OT = conc/OT (ouE/m3)
1,000
100
Hydrocarbons
Oxygenated comp.
Halogenated comp.
Nitrogenous comp.
Sulphured comp.
10
1
0.1
I Camp.
Feb. 2006
II Camp.
May 2006
III Camp.
Aug 2006
IV Camp.
Nov. 2006
Fig. 2. Waste grinder: theoretical odour concentration of pollutant families.
Author's personal copy
7054
L. Capelli et al. / Atmospheric Environment 42 (2008) 7050–7058
10,000,000
1,000,000
ouE/m3
100,000
10,000
1,000
100
10
I Camp.
Feb. 2006
II Camp.
May 2006
III Camp.
Aug. 2006
Waste grinder
Cog. fumes abatement plant
Leachate collection tanks
IV Camp.
Nov. 2006
Surface of exhausted parcels
LFG extraction wells
Fig. 3. Geometrical mean of cod values measured in correspondence of the landfill odour sources.
The cod values of the landfill gas (LFG) in the different
monitoring campaigns are rather stable. A decrease of the
cod level is observed in correspondence of the II and part of
the III campaign, may be due to the high atmospheric
pressure of the period. High atmospheric pressure may
cause the infiltration of air inside the body of the landfill,
which causes a dilution of the LFG and therefore of its cod.
A significant increase of the cod values measured on the
surface of the exhausted parcel was observed in correspondence of the III and IV monitoring campaign. This may
be due to the fact that in these cases the samples were
collected at the base of a LFG extraction well, where
probably LFG leaks occurred causing a rise of the cod.
On the leachate collection tank, particularly high cod
values were measured in correspondence of prolonged
periods of drought (II, III an IV campaign), which caused
a concentration of the leachate.
The highest cod values at the waste grinder were
measured in correspondence of the III campaign. This fact
can be explained considering that during the summer the
waste is conferred to the landfill in an advanced fermentation status and therefore it is characterized by more
intense odour emissions. This advanced fermentation level
is due to the high temperatures, which accelerate the
organic matter degradation processes, and to the higher
content of organic matter, such as fruit and vegetable rests,
whose consumption is increased during the summer.
The cod values of the ambient air at the landfill boundaries and at the receptors were rather low and therefore not
particularly relevant, except for a sample collected near the
1,000
ouE/m3
380
100
76
53
42
54
40
28
19
10
I Camp.
Feb. 2006
II Camp.
May 2006
III Camp.
Aug. 2006
IV Camp.
Nov. 2006
Fig. 4. cod values of ambient air at landfill boundaries ( ) and at receptors ( ).
Author's personal copy
L. Capelli et al. / Atmospheric Environment 42 (2008) 7050–7058
landfill entrance during the IV monitoring campaign, which
had a cod of 380 ouE m3.
3.3. Continuous ambient air monitoring by electronic nose
The results of the ambient air monitoring by electronic
nose are represented by large tables that report the olfactory class and the cod value attributed by each instrument
to the analyzed air for each measurement carried out
during the monitoring period.
Table 1 reports the relative recognition frequencies of
the considered olfactory classes in the three monitoring
positions.
As an example, Fig. 5 is a graphical representation of the
relative recognition frequencies of the different olfactory
classes in the four monitoring campaigns at receptor 1, i.e.
the sports ground located at 2 km SSW from the landfill at
issue. The graph also reports the sum of the relative odour
detection frequencies, i.e. the time percentage in which the
electronic nose detected the presence of odours from the
landfill in the analyzed ambient air.
Based on the results of the ambient air monitoring by
electronic noses, it is possible to make some considerations
about the landfill odour impact on the three points where
the instruments were installed.
The high relative recognition frequency of odours
attributed to the olfactory class ‘‘LFG’’, allows to affirm that
the LFG emitted through the landfill surface or through the
not perfectly airtight extraction wells represents the principal odour source of the monitored landfill.
During Wednesday, 22nd November 2006, in correspondence of the IV monitoring campaign, the three electronic noses attributed most of the measures to the
olfactory class ‘‘LFG’’. This may be due to the fact that
during the night between Tuesday, 21st November 2006,
and Wednesday, 22nd November 2006, a current drop
Table 1
Relative recognition frequencies in the three monitoring positions
Analyzed air quality
I Camp.
II Camp.
III Camp.
Feb.2006
May 2006
Aug.2006
Relative recognition frequency of the considered olfactory classes
the offices (boundary SW)
Neutral air
73.0%
95.4%
90.1%
LFG
24.1%
4.1%
0.3%
Fresh waste
1.4%
0.5%
7.1%
Cog. fumes abat. pant
–
0.0%
0.0%
Leachate
1.5%
0.0%
2.5%
IV Camp.
Nov.2006
at
77.0%
22.7%
0.0%
0.3%
0.0%
Relative recognition frequency of the considered olfactory classes at
the landfill entrance (boundary SSE)
Neutral air
79.2%
77.5%
44.9%
51.0%
LFG
16.4%
20.0%
45.4%
44.1%
Fresh waste
3.9%
1.9%
9.7%
3.1%
Cog. fumes abat. pant
–
0.4%
0.0%
1.6%
Leachate
0.5%
0.2%
0.0%
0.2%
Relative recognition frequency of the considered olfactory classes at
receptor I
Neutral air
90.7%
85.7%
91.6%
97.4%
LFG
9.0%
10.6%
1.6%
1.4%
Fresh waste
0.3%
3.2%
0.8%
0.0%
Cog. fumes abat. pant
–
0.1%
5.3%
1.1%
Leachate
0.0%
0.3%
0.7%
0.0%
7055
caused the interruption of the functioning of the LFG
extraction system for several hours.
In the four monitoring campaigns the electronic nose
installed at receptor 1 registered several episodes during
which the odours from the landfill were detected. Nonetheless, the percentage of measures attributed to an olfactory class different from ‘‘neutral air’’ always turned out to
be lower than 15%, which is the limit fixed by the German
guideline ‘‘GIRL Geruchsimmission-Richtlinie’’ about odour
immissions (LAI, 1998) for industrial or agricultural zones.
4. Discussion
In this paragraph, the three different monitoring techniques adopted for odour impact assessment are compared.
For a more complete evaluation, the meteorological data
have also been considered and discussed together with the
monitoring results.
4.1. Olfactometric analyses vs. chemical analyses
In order to evaluate the results obtained with these two
odour characterization techniques, the odour concentration values measured by dynamic olfactometry were
compared with the theoretical cod values (see Section 3.1),
which are based on the chemical composition of the
odorous mixture (Fig. 6).
It is possible to observe that there is no precise correlation between the results obtained with these two
different odour characterization techniques. The main
problem consists in the high degree of inaccuracy that
characterizes the evaluation of the theoretical odour
concentration of a gas sample based on the analytical
concentration and the odour threshold concentration of its
components. This may be due to the fact that this evaluation, based on a simple summation of the contribution of
each compound to the overall odour of the mixture,
doesn’t take account of the synergy and masking effects
that occur between the single compounds in a complex
mixture, which make their olfactory properties not
additive.
Moreover, it is important to highlight that the odour
threshold concentration values that can be found in literature have unknown accuracy, as the values relevant to
a single odorous compound often differ by several orders of
magnitude.
4.2. Electronic nose vs. olfactometric analyses
The comparison of the results of the olfactometric
analyses and the results of the continuous ambient air
monitoring campaigns by electronic noses enable the
formulation of some considerations relevant to the
different monitoring positions.
In general, the olfactory class that was recognized more
frequently by all the instruments is the olfactory class
‘‘LFG’’. This result is in agreement with the fact that the cod
values measured in the LFG samples collected directly at
the LFG extraction wells are by several orders of magnitude
higher than the cod values relevant to the other monitored
odour sources. This observation allows to identify the LFG
Author's personal copy
7056
L. Capelli et al. / Atmospheric Environment 42 (2008) 7050–7058
16.0%
15.0%
14.3%
14.0%
13.0%
12.0%
11.0%
10.0%
9.3%
9.0%
Landfill
LFG
Fresh waste
Cog. fumes abat. plant
Leachate
8.4%
8.0%
7.0%
6.0%
5.0%
4.0%
2.6%
3.0%
2.0%
1.0%
0.0%
I Camp.
Feb. 2006
II Camp.
May 2006
III Camp.
Aug. 2006
IV Camp.
Nov. 2006
Fig. 5. Relative recognition frequencies of the different olfactory classes at receptor 1.
emitted through the landfill surface or through the not
perfectly airtight LFG extraction wells as the most critical
odour source of the monitored landfill.
An exception is represented by the results of the
ambient air monitoring by electronic nose conducted at the
offices in the month of August, during which the electronic
nose attributed the majority of the odour detections to the
olfactory class ‘‘fresh waste’’. The offices are located in
proximity of the waste grinder, where the fresh waste is
conferred, and the high relative detection frequency may
be justified observing that in correspondence of the III
monitoring campaign the ambient air samples collected
near the waste grinder presented particularly high cod
values (320 ouE m3 and 710 ouE m3, respectively).
Another exception is represented by the monitoring at
receptor 1 in the month of August, during which the
majority of the odour detections where attributed to the
olfactory class ‘‘cogeneration fumes abatement plant’’.
These results are in agreement with the particularly high cod
values that were measured in the samples collected at the
stack through which the gases coming out from the cogeneration fumes abatement plant are emitted into the atmosphere in correspondence of the III monitoring campaign
(4000 ouE m3 and 16,000 ouE m3, respectively).
The monitoring campaign during which the odours
from the landfill were detected at receptor 1 for the highest
time percentage is the second one, conducted in the month
of May. This is not justified by the determination of
particularly high cod values in the samples collected in
correspondence of the landfill principal odour sources. For
this reason, it is reasonable to assume that the more
frequent detection of odours from the landfill at receptor 1
500
450
400
ouE/m3
350
300
cod-OT
cod-Olf
250
200
150
100
50
Waste
grinder
Landfill
entrance
Receptor
1
Receptor
2
Waste
grinder
Landfill
entrance
Receptor
1
Receptor
2
Waste
grinder
Landfill
entrance
Receptor
1
Receptor
2
Waste
grinder
Landfill
entrance
Receptor
1
Receptor
2
0
I Camp.
Feb. 2006
II Camp.
May 2006
III Camp.
Aug. 2006
IV Camp.
Nov. 2006
Fig. 6. Comparison between cod values measured by dynamic olfactometry and theoretical odour concentration values.
Author's personal copy
L. Capelli et al. / Atmospheric Environment 42 (2008) 7050–7058
is not due to an increase of the landfill odour emissions, but
rather to meteorological factors.
The landfill entrance is the monitoring position in
which, in all four monitoring campaigns, the highest
number of odour detections was registered, i.e. the highest
number of measures attributed to one of the olfactory
classes relevant to the landfill odour emissions. These
results clearly indicate that the landfill entrance represents a critical zone as far as the presence of odours is
concerned.
4.3. Electronic nose vs. meteorological data
The in depth study of meteorological data can be in
general very useful in order to evaluate the dispersion of
odours emitted from the monitored landfill on the
surrounding territory. In this case, a rough analysis of the
meteorological data relevant to the four monitoring
campaigns (especially wind speed and wind direction) was
performed (Fig. 7), just with the aim of comparing them
with the results of the ambient air monitoring by electronic
noses, in order to look for possible connections between
meteorological conditions and odour detections outside
the landfill.
It can be noticed that the highest odour detection
percentage at receptor 1 was registered during the II
monitoring campaign, which was characterized by
unstable meteorological conditions, i.e. weak wind with
unstable direction. On the contrary, during the remaining
three monitoring campaigns, characterized by the clear
presence of a predominant wind direction, the odour
detection frequency at the same receptor was significantly
lower. These results show that, in this case, the presence of
unstable meteorological conditions is particularly unfavourable to the dispersion of odours into the atmosphere.
5. Conclusions and future work
This study represents a critical review of employing
three different odour evaluation techniques for the
assessment of odour emissions from a landfill site.
The discussion of the results achieved by the parallel
application of GC–MS, dynamic olfactometry and electronic
nose technology effectively show how these three odour
characterization methods can be effectively used, for
differing reasons, on the same site.
Although there is no evidence of correlation between
the chemical composition of the analyzed samples and
their cod measured by dynamic olfactometry, chemical
analyses can be useful to analyze odour composition, in
order to design intervention and treatment strategies.
The results of the olfactometric analyses enabled
a quantification of the landfill odour emissions, giving
indicative values of sensory impacts that are liable to affect
off-site.
Finally, electronic nose technology could be effectively
used as a management tool in order to monitor site changes
or operational failures. In this specific case, the results of
the ambient air monitoring by electronic noses allowed to
quantify the time percentage in which the presence of
odours is perceived at the landfill boundaries and at
a receptor located at 2 km from the landfill, which always
turned out to be lower than the limit of 15% fixed by the
German guideline ‘‘GIRL Geruchsimmission-Richtlinie’’
about odour immissions (LAI, 1998) for industrial or agricultural zones in all the four monitoring campaigns.
Moreover, the analysis of the meteorological data relevant to the four monitoring campaigns, conducted in four
different seasons (winter, spring, summer and fall) allowed
to highlight that the presence of unstable meteorological
conditions (i.e. weak wind with unstable direction) is
N
NNW
35.0%
NNE
I Campaign - February 2006
II Campaign - May 2006
III Campaign - August 2006
IV Campaign - November 2006
30.0%
NW
NE
25.0%
20.0%
15.0%
WNW
ENE
10.0%
5.0%
0.0%
W
E
WSW
ESE
SE
SW
SSW
7057
Wind calms (v<0.1 m/s):
I Campaign: 2.2%
II Campaign: 4.1%
III Campaign: 2.5%
IV Campaign: 9.4%
SSE
S
Fig. 7. Wind roses relevant to the four monitoring campaigns.
Author's personal copy
7058
L. Capelli et al. / Atmospheric Environment 42 (2008) 7050–7058
particularly unfavourable to the dispersion of odours into
the atmosphere.
As a conclusion, this study shows that whilst the results
of the three different odour characterization techniques
don’t necessarily correlate, they do have an intrinsic value,
thus demonstrating the complexity of odour measurement
in the environment.
References
Ampuero, S., Bosset, J.O., 2003. The electronic nose applied to dairy
products: a review. Sensors and Actuators B, Chemical 94, 1–12.
Bockreis, A., Steinberg, I., 2005. Measurement of odour with focus on
sampling techniques. Waste Management 25, 859–863.
Davoli, E., Gangai, M.L., Morselli, L., Tonelli, D., 2003. Characterisation of
odorants emissions from landfills by SPME and GC/MS. Chemosphere
51, 357–368.
El Fadel, M., Findikakis, A.N., Leckie, J.O., 1997. Environmental impacts of
solid waste landfilling. Journal of Environmental Management 50,
1–25.
EN 13725, 2003. Air Quality – Determination of Odour Concentration by
Dynamic Olfactometry. Comité Européen de Normalisation, Brussels,
pp. 1–70.
Falasconi, M., Pardo, M., Sberveglieri, G., Riccò, I., Bresciani, A., 2005. The
novel EOS835 electronic nose and data analysis for evaluating coffee
ripening. Sensors and Actuators B, Chemical 110, 73–80.
Frechen, F.-B., Frey, M., Wett, M., Löser, C., 2004. Aerodynamic performance of a low-speed wind tunnel. Water Science and Technology 50
(4), 57–64.
Gostelow, P., Parsons, S.A., Stuetz, R.M., 2001. Odour measurements for
sewage treatment works. Water Research 35, 579–597.
Jiang, J.K., Kaye, R., 2001. Sampling techniques for odour measurement.
In: Stuetz, Richard, Frechen, Franz-Bernd (Eds.), Odours in Wastewater Treatment: Measurement, Modelling and Control. IWA
Publishing, London, UK, pp. 98–117.
LAI (Länderausschuss für Immissionsschutz), 1998. GeruchsimmissionsRichtlinie (GIRL – Odour Emissions Guidelines), Ministry of
Environment, Environmental Planning, and Agriculture of the State
Nordrhein-Westfalen, Germany.
Micone, P.G., Guy, C., 2007. Odour quantification by a sensor array: an
application to landfill gas odours from two different municipal waste
treatment works. Sensors and Actuators B, Chemical 120, 628–637.
Pagé, T., Narjoux, A., Guy, C., Caron, R.F., Fécil, B., 2007. Impact evaluation
of landfills on air quality: odours and toxic compounds. In: Cossu, R.,
Diaz, L.F., Stegmann, R. (Eds.), Proceedings Sardinia 2007. CISA Pub.,
Cagliari, Italy, pp. 215–216.
Pearce, T.C., 1997. Computational parallels between the biological
olfactory pathway and its analogue ‘The Electronic Nose’: part II.
Sensor-based machine olfaction. Biosystems 41, 69–90.
Persaud, K., Dodd, G.H., 1982. Analysis of discrimination mechanisms in
the mammalian olfactory system using a model nose. Nature 299,
352–355.
Schaller, E., Bosset, J.O., Escher, F., 1998. Electronic Noses’ and their application to food. Lebensmittel-Wissenschaft und -Technologie 31, 305–316.
Schlegelmilch, M., Streese, J., Stegmann, R., 2005. Odour management and
treatment technologies: an overview. Waste Management 25, 928–939.
Sironi, S., Capelli, L., Céntola, P., Del Rosso, R., Il Grande, M., 2005. Odour
emission factors for the assessment and prediction of Italian MSW
landfills odour impact. Atmospheric Environment 39, 5387–5394.
Sironi, S., Capelli, L., Céntola, P., Del Rosso, R., Il Grande, M., 2006. Odour
emission factors for the prediction of odour emissions from plants for
the mechanical and biological treatment of MSW. Atmospheric
Environment 40, 7632–7643.
Sironi, S., Capelli, L., Céntola, P., Del Rosso, R., Il Grande, M., 2007a.
Continuous monitoring of odours from a composting plant using
electronic noses. Waste Management 27, 389–397.
Sironi, S., Capelli, L., Céntola, P., Del Rosso, R., 2007b. Development of
a system for the continuous monitoring of odours from a composting
plant: focus on training, data processing and results validation
methods. Sensors and Actuators B, Chemical 124, 336–346.
Stuetz, R.M., Fenner, R.A., Engin, G., 1999. Assessment of odours from
sewage treatment works by an electronic nose, H2S analysis, and
olfactometry. Water Research 33, 453–461.