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doi:10.1016/j.at

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Odour emission factors for the prediction of odour emissionsfrom plants for the mechanical and biological treatment of MSW

Selena Sironia, Laura Capellia,�, Paolo Centolaa, Renato Del Rossoa,Massimiliano Il Grandeb

aLaboratorio Olfattometrico, Dipartimento CMIC ‘‘Giulio Natta’’, Politecnico di Milano, P.za Leonardo Da Vinci, 32– 20133 Milano, ItalybProgress S.r.l., Via di Rocca Cencia, 95– 00132 Roma, Italy

Received 14 December 2005; received in revised form 29 June 2006; accepted 30 June 2006

Abstract

In this study, the results of odour concentration measurements sampled from the principal odour sources of 40

dimensionally different and representative Italian waste mechanical and biological treatment (MBT) plants are presented.

Experimental data are then used to estimate the odour emission factors (OEFs) relevant to single-process steps. An OEF is

a representative value that relates the quantity of odour released to the atmosphere to a specific activity index, which may

be for example the waste treatment capacity, the gross weight production, the site surface or a time unit. In this study, the

OEFs were calculated as a function of the plant capacity, and expressed in ouE t�1, because of the existence of a

proportionality between plant capacity and odour emissions. The results show that the major odour source of a waste

MBT plant is represented by the aerobic biological treatment (with an OEF equal to 1.40� 108 ouE t�1). In general, the

OEFs calculated according to this approach represent a model for a rough prediction of odour emissions independently

from the specific characteristics of the different plants.

r 2006 Elsevier Ltd. All rights reserved.

Keywords: Mechanical biological treatment; Composting; Specific odour emission rate; Odour emission factors; Odour prediction

1. Introduction

Although odorous compounds are not necessarilytoxic or hazardous for human health, the psycho-physical well being and behaviour of people can be

e front matter r 2006 Elsevier Ltd. All rights reserved

mosenv.2006.06.052

ing author. Department of Chemistry, Materials

Engineering, ‘‘Giulio Natta’’, Politecnico di

Leonardo da Vinci 32, 20133 Milan, Italy.

993206; fax: +3902 23993291.

esses: selena.sironi@polimi.it (S. Sironi),

olimi.it (L. Capelli), paolo.centola@polimi.it

nato.delrosso@polimi.it (R. Del Rosso),

attometria.com (M. Il Grande).

negatively influenced by exposure to odours (Berto-ni et al., 1993). Historically, odour emissions fromindustrial processes were accepted as part of theactivity itself, but in the last 20 years odours havebecome a serious environmental concern, particu-larly when associated with waste disposal ortreatment plants (Canovai et al., 2004; Sarkar &Hobbs, 2003).

Waste treatment plants in which the wasteorganic fraction undergoes an aerobic biodegrada-tion process represent a common source of odouremissions that can be the cause of odour nuisance tothe near living population (Epstein, 1997; Smet

.

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et al., 1999). The problems related to plants for themechanical and biological treatment (MBT) ofeither the segregated organic material (compostingplants) or the non-segregated organic fraction ofMSW (bio-stabilization plants), are particularlyimportant as their number on the Italian territoryand in other developed countries is continuouslyincreasing in the last years (Fig. 1) (APAT-ONR,2003). One reason for the rapid growth of this kindof plants is represented by the necessity of reducingthe amount of biodegradable waste that is going tolandfills, in order to obviate wasteful use of landand to reduce the production of methane and otherpollutant gases from landfills, which is one of themost important aims of modern waste managementpolicies (Council Directive 1999/31/EC, 1999; D.Lgs. n. 36, 2003).

Problems connected to odour emissions oftenrepresent the limiting factor to the activity orconstruction of composting and bio-stabilizationplants. A useful tool for the odour impact assess-ment and prediction is represented by odouremission factors (OEFs) (Sironi et al., 2005). OEFsare developed analogously to the emission factorsdefined by the United States Environmental Protec-tion Agency (1995) for other pollutants/chemicalcompounds, which relate the quantity of a pollutantreleased to the atmosphere to a given associatedactivity.

In general, OEFs enable the estimation of theodour emission rate (OER) associated with anindustrial plant even before its construction. For

85

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50

100

150

200

250

300

1993 1994 1997

Year

Num

ber

of p

lant

s

Number of plants Treated waste qu

Fig. 1. Number of plants for the aerobic biodegradation of waste and

Italy.

the case of composting and bio-stabilization plants,OER values can be useful for odour impactassessment by using them as input data for theapplication of specific odour dispersion models(Sironi et al., 2003). Moreover, the predictiveeffectiveness of OEFs may allow to apply them forthe evaluation how the odour impact of a MSWbiological treatment plant will be influenced byplant modifications, such as the change of theconferred refuse quality or quantity, or the variationof the duration of any treatment phase. In this case,OEFs can be useful in order to evaluate thefeasibility of the planned technological or functionalmodifications.

This works describes the methodology that wasused for the calculation of OEFs based on theresults of olfactometric measurements that werecarried out on a significant number of waste MBTplants, which differ in constructional features, intype of treated waste and in geographical locationsin Italy.

2. Experimental

2.1. Sampling

The collection of air samples conformed with therequirements of EN 13725 (2003), using Nalo-phanTM bags equipped with a TeflonTM inlet tube.

The samplings were carried out at the followingtypes of emissions sources that are divided accord-

258

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1999 2002 20030

500

1000

1500

2000

2500

3000

Tre

ated

was

te q

uant

ity (

1000

t)

antity

amount of waste that is annually composted or bio-stabilized in

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ing to Bockreis and Steinberg (2005) and Gostelowet al. (2003) into:

�

point sources, i.e., canalized emissions; � area sources with outward flow (i.e., biofilters); � area sources without outward flow (surface of

heaps stored open air, without air insufflation).

Sampling on point sources is relatively easy: theair sample is collected by means of a vacuum pumpand a sampling bag realized with a suitable material(NalophanTM).

Sampling on area sources with outward flow canbe carried out by using a static hood, which allowsto isolate the sampling point from the externalatmospheric conditions and to collect the emissionsfrom a known surface portion in a sort of stack,which can be treated as a point source.

The sampling on area sources without outwardflow requires the use of hoods that have to beappropriately designed in order to simulate theenvironmental conditions to which the emittingsurface is usually subject. The design and therealization of a sampling system with such proper-ties are not banal and it is still under study (Frechenet al., 2004).

The data presented in this paper were obtained byusing a wind tunnel (WT) system, which enables tosimulate the wind action on the sampled surface(Jiang et al., 1995; Jiang & Kaye, 1996). The WTconsists of a PET hood that is positioned over theemitting surface. A neutral air stream, filteredthrough activated carbon, is introduced at a knownvelocity by a fan, simulating the wind action on theliquid or solid surface. Air samples are thencollected in the outlet duct by means of a vacuumpump. The WT (Fig. 2) used during the experi-mentation has a circular section inlet and outletduct, of 0.08m diameter. The central body of thehood used was a 0.25m wide, 0.08m high and 0.5mdeep rectangular section chamber. Inside the inlet

Fig. 2. Design of th

duct there is a perforated stainless-steel grid andinside the divergent that connects this duct to thecentral body of the hood there are three flowdeflection vanes. Both these devices have thefunction of making the airflow as homogeneous aspossible (Centola et al., 2004).

2.2. Analysis

Olfactometric analyses were conducted in con-formity with the European Norm EN 13725 (2003).

An olfactometer Mannebeck model TO7, based onthe ‘yes/no’ method, was used as a dilution device.This instrument with aluminium casing has fourpanellists’ places in separate open boxes. Each box isequipped with a stainless-steel sniffing port and apush button for ‘yes’ (odour threshold). Themeasuring range of the TO7 olfactometer starts froma maximum dilution factor of 64,000 with a dilutionstep factor of 2. All measurements were carried outwithin 30h after sampling, relying on a panelcomposed of eight panellists (4+4), adequatelyselected in conformity with EN 13725 (2003).

2.3. Methodology

2.3.1. Collection of odour concentration data

The data used for the development of OEF arethe results of odour concentration measurementsthat were carried out from 2000 to 2005 on 40 wasteMBT plants (composting and bio-stabilizationplants) located all over the Italian territory. Thecapacity of the monitored plants goes from 10,000to 240,000 t y�1, with an average capacity of60,000 t y�1. The odour concentration values mea-sured on these two different kinds of plants werefirst valuated separately. About 50 air samples werecollected on each plant, giving a total of about 2000samples. The samplings were carried out in differentseasons and with different weather conditions, inorder to have a significant number of representative

e wind tunnel.

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samples for all the odour sources present on eachexamined plant.

The odour sources considered for the study arerepresented by the following process steps:

�

MSW receiving; � green waste receiving; � aerobic biological treatment; � curing; � finished product (refined compost or bio-stabi-

lized material) heaps storage;

� overscreen heaps storage.

Depending on the plant being considered, theseprocess steps can be carried out open air or in closedsheds, where the waste gases are collected.

Based on the odour concentration values thatwere measured on the monitored plants, the OEFsrelevant to every single odour source were calcu-lated by first evaluating the OER of each source andthen by dividing this value by a specific activityindex, which should be a characteristic quantityrelated to the release of odour into the atmosphere(e.g., waste treatment capacity, gross weight pro-duction, site surface, time unit, etc.).

2.3.2. Calculation of single odour sources specific

odour emission rate values for passive area sources

The evaluation of the OER for the open airprocess phases requires the calculation of theSpecific Odour Emission Rate (SOER), which isexpressed in ouE s

�1m�2. Once the odour concen-tration value of a sample collected at the outlet ofthe WT is determined, it is possible to obtain theSOER by multiplying the odour concentration(ouEm

�3) with the flow rate of the inlet air(m3 s�1) and dividing by the base area of the centralbody of the hood (m2).

The optimum air velocity inside the central bodyof the hood is about 0.3m s�1 (Bliss et al., 1995;Jiang and Kaye, 2001), which corresponds in thiscase to an inlet air velocity of 1.2m s�1. Eventhough the WT is equipped with a fan, during fieldmeasurements it was not always possible to achieveexactly the desired air velocity, because of the highlosses of pressure that may occur in the ductconnects the fan to the WT in some particular casesof difficult sampling conditions, in which these twodevices had to be positioned at a certain distancefrom each other. For these reasons SOER valueswere calculated considering the air velocity

measured in the outlet duct of the hood correspond-ing to each sample collection. Subsequently, theSOER value for each sample was normalized usingthe following equation (Sohn et al., 2003):

SOERv2 ¼ SOERv1v2

v1

� �1=2

meaning that odour emissions from the monitoredsolid surfaces were thus related to the optimumwind velocity of 0.3m s�1.

2.3.3. Calculation of the OER

The collected emissions from the sheds can beconsidered as point sources. In this case, the OER iscalculated simply by multiplying the odour concen-tration value (in ouEm

�3) by the normalized airflow (in m3 s�1).

For the open air process steps, the source ofodour emissions is represented by the air exposedsurface of the heaps. This can be considered as anarea source without outward flow, the evaluation ofthe OER value can therefore be obtained as theproduct of the SOER value and the correspondingemitting surface. For this calculation, the emittingsurface of each source must be estimated.

Since the aim of this work is to obtain ageneralized value (average emission factor) startingfrom particular data, it is neither possible nor usefulto take account of all differences existing betweenthe examined waste MBT plants (such as, forexample, plant operation practices). It is thereforenecessary to make some assumptions that enable thecomparison of different experimental results and theextension of particular data to a more general case.These assumptions should be reasonable and basedon effective conditions and plant operation prac-tices. For these reasons, the adopted assumptionswere verified and confirmed on the basis ofobservations made on the monitored plants.

The assumptions that were adopted for theestimation of the emitting surface are explained indetail as follows.

2.3.3.1. Waste density. The mean density of theMSW was considered to be equal to 0.6 tm�3 whilethe mean density of the green waste was set equal to0.4 tm�3 (US EPA, 1991).

2.3.3.2. Geometric shape of the waste heaps. Thevariation of the exposed surface as a function of theheap geometric shape was calculated considering

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different geometric shapes. The shapes to beconsidered were chosen based on experimentalobservations, i.e., according to the ones that wereobserved most frequently on the monitored plants,which were hemispheres and hemicylinders. Thisevaluation showed that passing from two extremecases of a hemisphere and hemicylinder withr/L ¼ 1/15 the difference of the emitting surfacedid not exceed 20%. As the error that can be madeby considering different shapes is relatively small,the shape of the heaps for each process phase wereassumed to be either hemispheres with a 2m radiusor hemicylinders with r/L ¼ 1/5 and r ¼ 3m, basedon the conditions that were observed in the majorityof the monitored plants.

2.3.3.3. Waste mass in each process step. The massof the waste in each process step was evaluatedseparately.

�

Receiving area: the waste mass in the receivingarea (mrec, in t) can be calculated from the plantcapacity (C, in t y�1), by dividing the mass of thewaste conferred annually to the plant by theworking days (WD, in d y�1) and then multiplyingby the stay time of the waste in the receiving area(trec, in d), according to the following equation:

mrec ¼C

WDtrec,

where mrec is the waste mass in the receiving area(t). C is the plant capacity (t y�1 ), WD is theworking days (d y�1) and trec is the stay time ofwaste in the receiving area (d).

The waste conferred to the plant is treated dailyin order to avoid the occurrence of anaerobicdegradation processes, the stay time of waste inthe receiving area was therefore considered to beequal to 1d. One year was considered equal to 300working days.

� Aerobic biological treatment: the calculation of

the waste mass in the aerobic biological treatmentphase (mbio) was carried out analogously to thecase of the receiving area. In this case, a stay time(tbio) of 30 d was considered (D. M. n. 22, 1998).In the following equation the weight losses due tothe MSW screening (wlscr) and to the water lossesduring the aerobic process (wlbio) were taken intoaccount.

mbio ¼C

WDtbio 1� wlscrð Þ 1�

1

2wlbio

� �,

where mbio is the waste mass in the aerobicbiological treatment phase (t), C, plant capacity(t y�1), WD is the working days (d y�1), tbio is thestay time of waste in the aerobic biologicaltreatment phase (d), wlscr is the weight lossesdue to the MSW screening (t), and wlbio is thewater losses during the aerobic process (t).

In composting plants, which treat the organicmaterial from source segregation, a preliminaryscreening process for the separation of the organicfraction is not necessary. The weight losses due tothe screening process are therefore equal to zero. Forthe case of bio-stabilization plants, which treat thenon-segregated organic fraction of MSW, the weightlosses during the preliminary screening process wereconsidered equal to 50% of the initial weight,according to the conditions observed on themonitored plants, and to APAT-ONR (2003). Theweight losses due to the loss of water after theaerobic biological treatment are about 35% (Ep-stein, 1997; IPPC, 2005; Viel et al., 1987). The factor1/2 was used in order to consider the average weightlosses of the material in the aerobic biologicaltreatment phase.

� Curing: the calculation of the waste mass in the

curing phase (mcur) was carried out exactly as forthe aerobic biological treatment phase. In thiscase, a stay time of 60 d (tcur) was considered (D.M. n. 22, 1998). In the following equation theweight losses due to the MSW screening (wlscr), tothe water losses during the aerobic process (wlbio)and to the water losses during the curing process(wlcur) were taken into account.

mcur ¼C

WDtcur 1� wlscrð Þ 1� wlbio þ

1

2wlcur

� �� �,

where mcur is the waste mass in the curing phase(t), C is the plant capacity (t y�1), WD is theworking days (d y�1), tcur is the stay time of wastein the curing phase (d), wlscr is the weight lossesdue to the MSW screening (t), wlbio is the waterlosses during the aerobic process (t), wlcur is thewater losses during the curing process (t).

The weight losses due to the loss of water afterthe aerobic biological treatment and the curingprocess are about 50% (Epstein, 1997; Reinhartet al., 1993). The term wlcur was therefore setequal to 15%. The factor 1/2 was used in order toconsider the average weight losses of the materialin the curing phase.

� Compost/bio-stabilized material storage: the cal-

culation of the final product mass (mfp) was

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carried out analogously as for the previousphases. The final product storage time depends(tfp) on several factors, such as the plant capacityand the size of the store yards. In this study, astorage time of 7 d was considered, whichrepresent the average of the final product storagetimes for the examined plants. The mass of thestored final product is calculated with thefollowing equation:

mfp ¼C

WDtfp 1� wlscrð Þ 1� wlbio þ wlcurð Þð Þ 1� wlrefð Þ,

where mfp is the final product mass (t), C is theplant capacity (t y�1), WD, working days (d y�1),tfp is the final product storage time (d), wlscr is the weight losses due to the MSW screening (t),wlbio is the water losses during the aerobic process(t) wlcur is the water losses during the curingprocess (t), wlref is the weight losses during thefinal refining process (t).

Both for composting and bio-stabilizationplants, the sum of wlbio and of wlcur was set equalto 50%. For composting plants, wlscr is equal tozero, whereas the percentage of weight that is lostduring the final refining process (wlref) was setequal to 50% (Epstein, 1997; IPPC, 2005). On thecontrary, for bio-stabilization plants, wlref is equalto zero and wlshred is equal to 50%.

� Overscreen storage: the calculation of the over-

screen mass (mos) was carried out analogously asfor the previous phases. The overscreen storagetime (tos) depends on several factors, such as theplant capacity, the size of the overscreen storeyards, and the frequency of the landfill confer-ring. In this study, a storage time of 7 d wasconsidered, which represents the average of thestorage times for the examined plants. In thiscase, the calculation must be carried out sepa-rately for composting and for bio-stabilizationplants. In bio-stabilization plants, the overscreenis represented by the non-organic fraction sepa-rated during the preliminary screening process,whereas in composting plants the overscreen isseparated during the final refining process. Theoverscreen mass was therefore calculated bymeans of following equations:

mos ¼C

WDtoswlscr,

mos ¼C

WDtos 1� wlbio þ wlcurð Þð Þwlref ,

where mos is the overscreen mass, C is the plantcapacity (t y�1), WD is the working days (d y�1),tos is the overscreen storage time (d), wlscr is theweight losses due to the MSW screening (t), wlbiois the water losses during the aerobic process (t),wlcur is the water losses during the curing process(t), wlref is the weight losses during the finalrefining process (t).

2.3.3.4. Heap volume and number. The total volumeof material in each process step can be calculated asthe product of the waste mass in each phase by thewaste density.

The number of heaps in each phase wascalculated as follows.

First, a theoretical number of heaps was calcu-lated by dividing the total volume by the volume ofthe assigned heap shape. In the receiving area andon the final product and overscreen store yards theheaps were considered to be hemispheres with 2mradius. In the aerobic biological treatment andcuring phase the heaps were considered as hemi-cylinders with 3m radius and 15m length.

The heap number that was used for the estima-tion of the emitting surface was obtained byapproximating the theoretical heap number to thenearest whole number. This number was used todivide the total volume of material in each phase inorder to obtain the real volume of each heap.

The emitting surface of every single phase wasfinally calculated according to the assumptions asthe sum of the air exposed surface of all the heaps ineach process step.

2.3.4. Estimation of odour emission factors

The OEF should enable the estimation of thetotal OER (ouE s

�1) of an industrial site based on aspecific activity index, which should be representa-tive of the examined plant and associated withemitted odour quantity. In waste MBT plants,odour emissions can be influenced by differentfactors, for example plant dimensions, daily wasteacceptance, waste composition and age of theconferred waste. Because of the predictive andnon-descriptive character of an emission factor(description of plant emissions should be based onmore specific data), it is useful to express theemission factor as a function of one possible ‘rough’aspect of the considered plant. In this case the OEFwas related to the plant capacity. This choice isjustified by the existence of some documentedproportionality between plant capacity and odour

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emissions (Epstein, 1997). The OEFs calculated inthis study are therefore expressed in ouE t

�1.The OEFs were evaluated separately for each

process step by dividing the average OER valueassociated to each step, obtained as geometric meanof the average OER values for each plant, by theplant capacity.

Emission factors are generally considered up-stream of abatement systems (US EPA, 1995). Forthe estimation of an industrial plant odour impact,it is possible to introduce a correction factor thattakes account of the adopted abatement systemefficiency for each collected and treated waste gasstream.

3. Results and discussion

3.1. Odour concentration measurements

The odour concentration values were collectedseparately for composting and bio-stabilizationplants. Also point and area sources were firstconsidered separately. The comparison of the datashowed no significant differences between the odourconcentration values relevant to the same processstep. For this reason, the average odour concentra-tion value for each process step was calculatedwithout distinguishing between composting andbio-stabilization plants or between point and areasources.

Table 1 resumes the results of the odourconcentration measurements for each process step.Given the nature of the odour concentrationmeasurement, the statistical calculations must con-sider the logarithms of the odour concentrationvalues (EN 13725, 2003). The first column ofTable 1 represents the arithmetic mean of the

Table 1

Arithmetic mean, median and standard deviation of the logarithms of

Arithmetic mean of log

Waste receiving 3.445

Green waste receiving 2.754

Aerobic biological treatment 4.003

Green waste aerobic biological treatment 3.353

Curing 3.231

Overscreen storage 2.690

Final product storage 2.617

Aerobic biological treatment+receiving 3.937

Aerobic biological treatment+curing 3.568

All process steps 3.898

logarithms of the odour concentrations. In orderto highlight the data variability and the nature ofdistribution, the second and third columns reportthe median and the standard deviation of thesevalues.

Table 2 reports the antilogarithms of the datareported in Table 1, which were calculated in orderto express the average odour concentration and themedian of the odour concentration values inouEm

�3. The antilogarithm of the standard devia-tion is not meaningful, as it does not give anyinformation about data variability and distribution.An indication of this distribution can be given bythe percent deviation reported in the third columnof Table 2. This percent deviation was calculated bydividing the logarithmic standard deviation by thearithmetic mean of the logarithms of the odourconcentration values.

The last three rows of Tables 1 and 2 report thedata relevant to the samples taken in ducts thatcollect the waste gases from more process steps. Thelast row refers to the plants without open airemission sources in which the only emission isrepresented by a mixture of the waste gases collectedfrom all process steps.

As an example, the single odour concentrationvalues measured respectively on the open air storedheaps of green waste (green waste receiving) and inthe duct that collects the waste gases from allprocess steps are illustrated in Figs. 3 and 4. Theplant numbers were assigned in increasing order ofannual waste acceptance.

3.2. OEF from odour emission data

Table 3 resumes the OEF that were calculated foreach process step. Also in this case, the statistical

the odour concentration values

(cod) Median of log(cod) Standard deviation of log(cod)

3.477 0.407

2.820 0.312

4.041 0.358

3.431 0.505

3.591 0.779

2.922 0.783

2.723 0.538

3.844 0.463

3.875 0.471

3.916 0.304

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Table 2

Average odour concentration values, median and percent deviation

Geometric mean of cod (ouEm�3) Median of cod (ouEm

�3) % Deviation

Waste receiving 2786 3000 11.8

Green waste receiving 568 661 11.3

Aerobic biological treatment 10,079 11,000 8.9

Green waste aerobic biological treatment 2256 2700 15.1

Curing 1701 3899 24.1

Overscreen storage 490 836 29.1

Final product storage 414 529 20.5

Aerobic biological treatment+receiving 8646 6979 11.8

Aerobic biological treatment+curing 3701 7500 13.2

All process steps 7903 8234 7.8

calculations must consider the logarithms of theOEF values (EN 13725, 2003). The first column ofTable 3 represents the arithmetic mean of thelogarithms of the OEFs. The second and thirdcolumns report the median and the standarddeviation of these values, which are useful in orderto highlight the data variability.

Table 4 reports the antilogarithms of the datareported in Table 3, which were calculated in orderto express the average OEFs and the median inouE t

�1. Analogously to the case of odour concen-tration values, the antilogarithm of the standarddeviation does not give any clear informationabout data variability and distribution. An indica-tion of this distribution can be given by thepercent deviation reported in the third column ofTable 4. This percent deviation was calculated bydividing the logarithmic standard deviation bythe arithmetic mean of the logarithms of theOEF values.

The average OEF values were reported in Fig. 5in order to compare the entity of the odour emissionfrom each odour source being considered in thisstudy. Fig. 5 shows that the aerobic biologicaltreatment represents the major odour source of awaste MBT plant, having an OEF of about108 ouE t

�1. It must be considered that the Italianregulation in matter of composting (D. M. n. 22,1998) provides that the aerobic biological treatmentand the waste receiving, which has an OEF of about107 ouE t

�1, are conduced in closed sheds with anair-collection system that conveys the waste gases toa specific odour-abatement system. This means thatthe Italian law allows to carry out all the otherprocess steps open air. It is important to highlightthat some of the process steps that can be carriedout open air have a very high OEF value, such as for

example the curing (4� 107 ouE t�1) or the final

product storage (7� 106 ouE t�1). The odour impact

of these process steps is of the same order ofmagnitude as the odour impact relevant to the wastereceiving. For this reason, these process steps mayrepresent an important odour source if they areconduced open air, they can therefore be the causeof odour nuisance near a composting or bio-stabilization plant.

3.3. How to use the OEF

The overall OER (in ouE s�1) relevant to a waste

MBT plant can be obtained as the product of theplant capacity and the sum of the OEFs relevant toeach process step, according to the followingequation:

OERTOT ¼ C OEFrec þOEFbio þOEFcurð ,

þOEFfp þOEFos

�where C is the plant capacity (t y�1) and the OEFare expressed in ouE t

�1. The index indicate theprocess step that the OEFs are referred to. In thiscase, ‘rec’ indicates the waste receiving, ‘bio’ theaerobic biological treatment, ‘cur’ the curing, ‘fp’the final product storage and ‘os’ the overscreenstorage. The equation that allows to determine theoverall OER, once the plant capacity is given, wasobtained by substituting the OEFs values that werecalculated in this study:

OERTOT ¼ Cð1:26� 107 þ 1:40� 108 þ 3:99� 107

þ 2:42� 106 þ 7:54� 106Þ.

As an example, the overall OER relevant to aplant with an average treatment capacity of

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Fig. 3. Odour concentration values relevant to the open air green waste receiving.

Fig. 4. Odour concentration values relevant to the mixture of waste gases collected from all process steps.

50,000 t y�1 may be calculated according to theproposed model.

In this specific case, the overall OER would be

OERTOT ¼ 50000ð1:26� 107 þ 1:40� 108

þ 3:99� 107 þ 2:42� 106 þ 7:54� 106Þ,

OERTOT ¼ 1:01� 1013 ouE y�1 ¼ 3:21� 105 ouE s�1.

If any process step is carried out in sheds with anair-collection system that conveys the waste gases to

an abatement system, the effective OER of the plantcan be calculated by multiplying the single OEFs bya term that takes account of the efficiency of theadopted abatement system.

As an example, it is possible to consider theabove-mentioned plant, with a treatment capacityof 50,000 t y�1, assuming that the effluents comingfrom the receiving and from the aerobic biologicaltreatment are collected from the working sheds andsent to a biofilter, with an average odour-abatementefficiency (Effab) of 90%.

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Table 4

Average OEFs, median and percent deviation

Geometric mean of

OEF (106 ouE t�1)

Median of OEF

(106 ouE t�1)

% Deviation

Waste receiving 12.553 11.051 5.0

Green waste receiving 3.015 3.296 9.9

Aerobic biological treatment 139.948 127.042 6.1

Green waste aerobic biological

treatment

12.501 5.248 12.2

Curing 39.943 29.946 7.4

Overscreen storage 2.424 3.196 12.0

Final product storage 7.536 9.247 8.3

Aerobic biological treatment+receiving 118.879 124.590 4.9

Aerobic biological treatment+curing 68.717 94.217 5.7

All process steps 100.673 123.460 6.5

Table 3

Arithmetic mean, median and standard deviation of the logarithms of the OEFs

Arithmetic mean

of log(OEF)

Median of log(OEF) Standard deviation

of log(OEF)

Waste receiving 7.099 7.043 0.356

Green waste receiving 6.479 6.518 0.641

Aerobic biological treatment 8.146 8.104 0.501

Green waste aerobic biological treatment 7.097 6.720 0.867

Curing 7.602 7.740 0.561

Overscreen storage 6.385 6.505 0.767

Final product storage 6.877 6.966 0.572

Aerobic biological treatment+receiving 8.075 8.095 0.394

Aerobic biological treatment+curing 7.837 7.974 0.443

All process steps 8.003 8.092 0.517

Fig. 5. Average OEFs for each considered odour source.

ARTICLE IN PRESS

In this case, the overall OER would be

OERTOT ¼ C½ðOEFrec þOEFbioÞð1� EffabÞ

þOEFcur þOEFfp þOEFos�,

OERTOT ¼ 50; 000½ð1:26� 107 þ 1:40� 108Þð1� 0:9Þ

þ 3:99� 107 þ 2:42� 106 þ 7:54� 106�,

OERTOT ¼ 3:26� 1012 ouE y�1 ¼ 1:03� 105 ouE s�1.

One immediate and rather rough way to verifythe reliability of these results, is to compare themwith previous works conducted by other authors. Infact, the OER values calculated in this section,which represent the entity of odour emissions froma waste MBT plant of average dimensions (i.e.,50,000 t of waste treated yearly), are consistent withthe OER values estimated by Bidlingmaier (1996) ina study regarding odour emissions from compostingplants, which were calculated to be about105 ouE s

�1, even though the cited study did nottake account of the connection between entity ofodour emissions and plant size, i.e., treatmentcapacity.

4. Conclusions

Based on the discussed results it is possible to listthe following conclusions.

This paper discusses an approach for the creationof a model for a rough and simple prediction of theodour emissions from a waste MBT plant fromexperimental data, i.e., from the results of olfacto-metric analyses conducted on several Italian com-posting and bio-stabilization plants.

Considering the same process step, a similarityamong the OEFs relevant to the different wasteMBT plants is noticeable. This similarity demon-strates the appropriateness of having chosen theplant capacity (t y�1) as activity index for thecalculation of the OEFs.

The obtained results show that the major odoursource of a waste MBT plant is represented by theaerobic biological treatment. The OEF relevant tothis process step is equal to 1.4� 108 ouE t

�1, whichis one order of magnitude higher than the OEFsrelevant to the other considered process steps.

An indication of the margin of error introducedin the OEF calculation is given by the standarddeviations of the odour concentration measure-ments of the different odour sources (see Table 1).The effectiveness of the OEFs is not compromised

by such errors, as OEFs must be useful for anestimation of a plant total odour impact.

The OEFs should be updated continuously, forexample by adding more data from further olfacto-metric analyses. This procedure may be facilitatedby creating an electronic database for the insertionor variation of useful data for the OEF calculation.

The precision of the OEFs can be improved byfirst verifying the applicability of this model withaccurate datasets describing the actual conditionson site. The margin of error associated with the useof OEFs for the prediction of the odour impactcaused by a waste MBT plant may be reduced bysubstituting some of the simplifying assumptionsthat were adopted by the real conditions that areobserved on each plant. Moreover, the OEFs maybe further ‘refined’ by evaluating its dependencefrom other parameters that were not considered inthis study, such as for example temperature orhumidity.

Acknowledgements

We would like to thank the anonymous reviewerfor the thorough and stimulating review, which wethink enhanced the quality of the paper.

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