Numerical evaluation of the PCBs transport over theNorthern Hemisphere

Alexander Malanichev, Elena Mantseva, Victor Shatalov*, Boris Strukov,Nadezhda Vulykh

Meteorological Synthesizing Centre East of EMEP, Arhitector Vlaslov Str. 51, Moscow 117393, Russia

Received 14 July 2003; accepted 11 August 2003

‘‘Capsule’’: Transfer of PCBs to the Arctic is assessed using a model of the whole Northern Hemisphere.

Abstract

The numerical evaluation of selected PCB congener (28, 118, 153, 180) transport over the Northern Hemisphere is carried out for1996 using MSCE–POP model. This model is a multicompartment three-dimensional one and includes various environmentalmedia such as the atmosphere, soil, vegetation, seawater, and sea ice. The spatial resolution is 2.5��2.5� for all media except

marine one (1.25��1.25�). The main model output information is deposition fluxes, spatial distribution of concentrations inenvironmental media, pathways and source–receptor relationships. Calculation results are analysed for the whole hemisphereand the Arctic region. In particular, this gives an opportunity to estimate the contributions of individual emission source

groups to the Arctic pollution. The reliability of the model assessment is analysed by comparison between calculated andobserved data.# 2003 Elsevier Ltd. All rights reserved.

Keywords: PCBs; POP transport modelling; Hemispheric multicompartment model; Source–receptor relationships

1. Introduction

In spite of essential reduction of PCB emissions sincethe 1970s, current observation data indicates the pre-sence of these substances in the atmosphere and otherenvironmental media (e.g. Meijer et al., 2003; Bror-strom-Lunden, 2002; Davidson et al., 2003). Due tohigh persistence and volatility PCBs undergo long-rangetransportation and are detected in the remote regionslike the Arctic and the North Atlantic (e.g. AMAP,1998), where there is no anthropogenic emission sour-ces. This indicates, that the problem of PCB pollutionbears the global character and there is an urgent needfor information on the pollution levels and the ways oftheir formation, i.e. source–receptor relationships andtransport pathways.

This information can be obtained as a result of amathematical simulation of the pollutant transport.

There are a number of approaches to pollutant trans-port modelling differing by the set of the consideringmedia and processes, spatial and temporal resolution.Some of them give opportunity to assess pollutionlevels at the hemispheric/global scale with high spatialresolution (e.g. Koziol and Pudykiewicz, 2001; Lammelet al., 2001; Malanichev et al., 2002). This study pre-sents the assessment of selected PCB congener trans-port using hemispheric multicompartment MSCE–POPmodel.

PCB mixture includes more than 200 different con-geners. To illustrate the peculiarity of their environ-mental behaviour we have selected for modelling PCB-28, 118, 153 and 180. In our opinion, these congenerscover the diversity of PCB properties. Moreover, PCB-118 belongs to the group of toxic congeners, which is ofspecial concern.

Calculated pollution levels for the whole hemisphereare analysed for 1996. To take into account the mediaaccumulations due to the emissions in the previousyears preliminary model calculations (spin-up) for1970–1995 were carried out. For the Arctic region the

0269-7491/$ - see front matter # 2003 Elsevier Ltd. All rights reserved.

doi:10.1016/j.envpol.2003.08.040

Environmental Pollution 128 (2004) 279–289

www.elsevier.com/locate/envpol

* Corresponding author. Fax: +7-095-125-24-09.

E-mail addresses: alexandr.malanichev@msceast.org (A. Mala-

nichev), victor.shatalov@msceast.org (V. Shatalov).

source–receptor relationships and features of the atmo-spheric pathways are considered.

The reliability of the model assessment is analysed bya comparison between the calculated and observed data.The survey of possible uncertainties is carried out. Theresults are rather tentative and will be refined in furtherinvestigations. At the same time, the authors believe,that this study partly fills a gap in our knowledge onPCBs’ fate in the environment and its further develop-ment would have important implications for policymakers and regulators.

2. Model approach

2.1. Hemispheric MSCE–POP model description

MSCE–POP is a multi-compartment hemisphericthree-dimensional model. It includes a description ofPOP behaviour in different environmental media(atmosphere, soil, vegetation, seawater, sea ice andsnow), incorporated as different program modules(Fig. 1).

Below we briefly describe each module. More detailedinformation on the parameterisation of the media pro-cesses can be found in the report (Malanichev et al.,2002) and on the Internet (http://www.msceast.org/pops/). The hemispheric model has a structure similarto the regional one described in (Shatalov et al.,2000, 2001, 2002). These reports are availablethrough the Internet (http://www.msceast.org/publications.html).

2.1.1. The atmospheric moduleThe atmospheric module includes the following pro-

cesses: transport (advection and diffusion), partitioningbetween the gas and particulate phases, degradation,dry and wet depositions, and gas exchange with under-lying surface.

The transport module described in Travnikov (2001)is based on the advection Bott scheme and operates inthe geographical coordinates with spatial resolution2.5��2.5�. The computational domain covers the wholeNorthern Hemisphere (Fig. 2). In order to take intoaccount the influence of the relief on the pollutant air-borne transport, the terrain-following �-coordinate (theratio of the surface pressure to pressure at the con-sidered height) is employed in the vertical direction(Fig. 3). The domain consists of nine �-levels of variablethickness up to approximately 12-km height.

The partitioning process is described by Junge–Pan-kow equation (Junge, 1977; Pankow, 1987). The degra-dation process in the atmosphere is accounted for by thereaction of the gaseous phase of pollutant with OHradicals. Wet depositions of gaseous and particle phasesfrom the atmosphere are distinguished in the model.For the description of the gaseous phase scavenging theinstantaneous equilibrium between the gaseous phase inair and the dissolved phase in precipitation is assumed.The parameterisation of the particlulate phase scaven-ging is based on the washout ratio coefficient deter-mined experimentally for each substance.

Deposition velocities for particulate POP phasedepends on the underlying surface (forest, other terrestrialsurface, sea). Deposition to the forest is described by the

Fig. 1. The scheme of processes included into the MSCE–POP model.

280 A. Malanichev et al. / Environmental Pollution 128 (2004) 279–289

model by (Ruijgrok et al., 1997). For other terrestrialsurface velocities are calculated according to (Sehmel,1980). The model published in (Lindfors et al., 1991) isapplied at the sea surface. Gas exchange between theatmosphere and other environmental media (soil, veget-ation, sea, sea ice) is described using a resistance analogy.

2.1.2. The soil moduleThe soil module is based on the model developed by

of Jacobs and van Pul (1996). It is assumed that POP insoil instantly redistributed between gaseous, dissolvedand sorbed phases. A pollutant undergoes transport invertical direction due to diffusion and convection. Inorder to consider vertical profile of a pollutant concen-tration, the calculation domain is split into five layers ofdifferent thickness. The degradation of POP is describedas a first-order reaction with a temperature dependentdegradation rate constant. The soil properties (porosity,volumetric water and air contents) are accepted thesame for the whole soil domain. The spatial distributionof organic carbon is employed.

2.1.3. The vegetation moduleVegetation uptakes a pollutant due to particle dry

deposition and gas exchange processes. Three types ofvegetation are distinguished in the model: coniferousforest, deciduous forest, and grass. Coefficients definingexchange processes between the atmosphere and vege-

tation are determined separately for each of the abovevegetation types and depend on the pollutant proper-ties. These coefficients are obtained from the experi-mental data described in (McLachlan and Horstmann,1998; Thomas et al., 1998). The spatial distribution ofthe vegetation is determined with use of Leaf AreaIndex that also determines its seasonal variability. Fromvegetation pollutant comes to the litterfall with fallenleaves, and then in some time migrate to soil.

2.1.4. The sea water moduleIt is presumed that POPs in the marine environment

instantly redistributed between dissolved and particlephases. POPs undergo transport by sea currents, turbu-lent diffusion (taking into account intensive verticalmixing within the upper mixed layer), sedimentationwith settling particles and degradation. The gasexchange process between the atmosphere and sea isdescribed on the basis of the approach of two molecularfilms taking into account chopping and foam formationprocesses. Fifteen calculation layers from the surface tothe ocean bottom are considered. Horizontal resolutionis 1.25��1.25�.

2.1.5. The sea ice moduleFor the assessment of the Arctic pollution it is neces-

sary to consider the effect of ice coverage over vast areasof the Arctic Ocean. On the upper snow–ice surface theprocess of POP exchange with the atmosphere takesplace. When snow and ice are melting on the uppersurface, or ice is melting on the lower or lateral surfaces,POP passes to the water environment. In the case of iceaccretion on the lower or lateral ice surfaces POP canpenetrate into ice medium. Besides, POP trapped by thesea ice and snow may be transported with ice drift.

Meteorological data, information on sea currents andsea ice dynamics are provided by HydrometeorologicalCentre of Russia.

2.2. Input data

Apart from meteorological and geophysical data,input information for modelling implies physical-che-mical properties of a pollutant and its emission data.Physical-chemical parameters of considered PCB con-geners used for calculations are presented in Table 1.

For modelling the high scenario of global emissioninventory of 22 PCB congeners for 1930–2000 (Breiviket al., 2002) was used, since simulation results obtainedunder this scenario agree better with measurements. Toconvert the countries’ emission annual totals into spatialdistribution (2.5��2.5�) the population distribution dataset available from the CGEIC website (htpp://www.oartech.ca/cgeic) was used. Seasonal variations ofemissions were not taken into account because of a lackof information.

Fig. 2. Horizontal grid structure of the model domain, 2.5��2.5�.

Fig. 3. Vertical grid structure of the model domain. Nine terrain-fol-

lowing �-levels: �I=0.99; �2=0.96; �3=0.91; �4=0.85; �5=0.77;

�6=0.68; �7=0.55; �8=0.4;�9=0.26.

A. Malanichev et al. / Environmental Pollution 128 (2004) 279–289 281

3. Model results

3.1. Model spin-up

The contamination of environmental media by PCBsis a long-term process. To estimate the media accumu-lations obtained by the beginning of 1996, model pre-liminary calculations (spin-up) were carried out from1970 to 1995 for each considered congener (PCB-28,�118,�153,�180).

The dynamics of the accumulation process in mediaalong with the emission trend for each congener arepresented in Fig. 4. Considering the PCB-153, we notethat the emissions are increasing up to 1985 and then godown (Fig. 4.c). The media contents follow after theemissions, approaching the maximum in 1985–1986.This testifies that the saturation of environmental mediais attained. Therefore the period of the model spin-up isenough for media accumulation description.

The bulk part of the pollutant is in the soil. Thencome seawater and vegetation. Diagrams for other con-geners indicate that the medium saturation is alsoattained for these pollutants, although content dynamicis a little different.

3.2. Contamination of the Northern Hemisphere

The description of contamination levels in the North-ern Hemisphere is exemplified by PCB-153. Calculatedfields of PCB-153 depositions (dry particle+wet) andconcentrations in air and seawater in comparison withemissions of 1996 are presented in Fig. 5.

The most significant emission sources of PCB-153 arelocated in European and North American regions

(Fig. 5.a), which condition high enough concentrationlevels there. Annual averaged air concentrations in theeast part of the North America and most part of Europerange from 5 to 20 pg/m3 (Fig. 5.b). In some areas ofcentral Europe they can be higher than 20 pg/m3. Thereis the distinct decrease of air concentrations from Eur-opean region towards the east part of the continent,where they fall down to the levels of 1–3 pg/m3. Thesame level of concentrations takes place in the most partof the North American continent.

Emitted over the continental part of the NorthernHemisphere, the pollutant is transported to the remoteregions like the Atlantic and the Arctic where the emis-sions are negligible. The characteristic levels of air con-centrations for these regions are 0.3–1 pg/m3. Pollutiontransport to the Pacific and Indian Ocean is limited. Airconcentrations over vast areas of these oceans involvedinto the Northern Hemisphere do not exceed 0.3 pg/m3.

Air concentrations levels and the precipitation inten-sity in many respects determine the deposition fluxvalues (Fig. 5.b). High deposition fluxes (more than 0.5g/km2/y) occur in the central Europe. Considerablefluxes 0.2–0.5 g/km2/y take place in most of Europe andthe East part of North America. Similarly to the airconcentrations, deposition fluxes decrease from thewestern to the eastern part of the Eurasia continentfrom 0.2 down to 0.05 g/km2/y. The same depositionlevels are characteristic for North America. In theremote regions (the Arctic and North Atlantic)the deposition fluxes of 0.01–0.05 g/km2/y take place.Over vast areas of the Atlantic, Indian and PacificOceans depositions are less than 0.005 g/km2/y.

Apart from the atmosphere, the main transport med-ium is seawater. The pollutant penetrates to this media

Table 1

Basic physical-chemical parameters selected for model parameterisation from literaturea

PCB congener

28

118 153 180

Henry’s law constant

H ¼H0

RTexp �aH

1

T�

1

T0

� �� �

H0 Pa.m3/mol 7.642 3.046 4.146 2.388

aH

K 7430 8082 8347 8575

Washout ratio for the particle phase W � �� �

W dimensionless 21,000b 150,000

Subcooled liquid

p0L ¼ p00Lexp �aP

1

T�

1

T0

p00L

Pa 6.43.10�3 1.77.10�4 9.69.10�5 1.67.10�5

vapour pressure

aP K 9383 10739 10995 11610

Degradation rate

kair ¼ A � expðEa=RTÞ A cm3/(mol.s) 2.7.10�10 6.15.10�11 8.12.10�11 1.4.10�10

constant for the

atmosphere

EA

J/mol 13,720 12,920 15,380 17,840

Degradation rate constant for soil

ksoild s�1 7.4.10�9 3.21.10�9 1.17.10�9 5.83.10�10

Degradation rate constant for sea

ksead s�1 1.33.10�7 3.21.10�9 1.6.10�9 8.02.10�10

Molar volume Vmol

Vmol cm3/mol 247.3 289.1 310 330.9

Octanol/water partition coefficient

Kow dimensionless 6.31.105 5.5.106 7.94.106 2.29.107

Organic carbon/water partition coefficient � �� �

Koc m3/kg 2.59.102 2.25.103 3.26.103 9.39.103

Octanol/air

partition coefficient

Koa ¼ K 0

oaexp aK1

T�

1

T0

K0oa

aK

dimensionless

K

5.78.108

8731

4.51.1010

10,806

3.64.1010

10,811

2.07.1011

10,442

Molecular diffusion

In air Da m2/s 5.42.10�6 4.82.10�6 4.58.10�6 4.38.10�6

coefficient,

In water Dw 6.1.10�10 5.40.10�10 5.14.10�10 4.91.10�10

a R, universal gas constant; T0=283.15 K.b Used also for the gas phase deposition

282 A. Malanichev et al. / Environmental Pollution 128 (2004) 279–289

via depositions from the atmosphere and then is trans-ported by sea currents. For example, the exchange ofwater masses between the North Atlantic and the ArcticOcean considerably affects the seawater pollution levels.Seawater with PCB concentrations of 1–1.5 pg/l inflowsto the Arctic region along Norwegian and Russiancoasts and the water masses with concentrations in therange of 0.1–0.2 pg/l flow from the Arctic Ocean to theNorthern Atlantic along Greenland coast.

The seawater pollution in the Arctic Ocean is notice-ably affected by sea ice cover, which accumulates andtransports a pollutant and hampers the gas exchangebetween the atmosphere and seawater. The screeningeffect of sea ice reduces the water contamination duringthe emission growth in 1970–1985 and keeps it up dur-ing the emission decrease (after 1985).

3.3. Contamination of the Arctic region

Here we pass to the consideration of the Arctic regioncontamination. According to the model assessment, theatmospheric transport with the subsequent deposition isthe main pathway of PCB penetration into the Arcticregion. The calculated spatial distribution of annualPCB-153 depositions is given in Fig. 6.

Looking at the map, one can assume, that the maincontributions to the Arctic contamination are made byNorth-Western European and American emission sour-ces (30 and 19% respectively, see below). However, thecontributions of these sources to the Arctic pollutiondepend on the season. In Fig. 7 (a,b) air concentrationsof PCB-153 derived from American and North-western

European emission sources in January are shown. Thefields of air concentrations originated from the samesources in May are given in Fig. 7(c,d).

As seen from the maps, PCB-153 from Americansources mainly penetrate into the Arctic in May(Fig. 7c), whereas from European ones- in January(Fig. 7b). This is in line with the annual pattern of theatmospheric circulation in the Arctic region. Accordingto it the mean flow in winter is from Eurasia into theArctic. The inflow from America to the Arctic takesplace mainly in the warm period.

3.4. Source–receptor relationships

To determine the relative contribution of differentemission sources to the Arctic pollution, the source–receptor approach was applied. To this end the PCBemission field of the Northern Hemisphere was dividedinto 6 macro source groups (Fig. 8). Separate modelruns for the assessment of the pollution transport in1996 from each source group under the assumption ofzero emissions from other sources and zero initial con-centrations of the pollutants in media were carried out.These calculations allow us to evaluate the contribu-tions of each emission source to depositions to the Arc-tic.

The emissions of the considered source groups andtheir contributions to annual depositions to the Arcticfor PCB-28, 118, 153, 180 are displayed in Fig. 9.Essential emissions of PCB-153 are characteristic ofNorth-Western European, South-eastern European andAmerican source groups (30, 21 and 19% respectively,

Fig. 4. Trends in emission and accumulation of PCB-28 (a), PCB-118 (b), PCB-153 (c) and PCB-180 (d) in the environmental media of the Northern

Hemisphere during model spin-up 1970–1995.

A. Malanichev et al. / Environmental Pollution 128 (2004) 279–289 283

Fig.9e). It might be expected, that these source groupsmake the major contribution to the depositions to theArctic. However, as seen from Fig. 9f, essential con-tributions are made by North-western Europe (about40%), then come Russia (19%), Americas (17%), and

only then South-eastern Europe (16%). The increasedshare of Russian contribution can be explained by theproximity of its emission sources to the Arctic.

As to the other congeners, the major contribution toPCB-180 depositions is made by North-Western Europe(Fig. 9h). Depositions of PCB-28 and 118 in a greatextent are determined by Russian emission sources (Fig.9b, d).

On the whole, the diagram analysis shows that theshare of Russian and North-Western Europe sources inemissions is less than their share in depositions. This isconditioned by proximity of these sources to the Arcticand peculiarities of the atmospheric circulation. For theother emission sources the situation is opposite.

Characteristic values of total depositions to the Arcticregion of the considered PCB congeners are 2.7, 1.1,1.15, 0.5 t for PCB-28,�118,�153,�180 respectively. Itshould be noted, that these depositions are formed bothby emissions of 1996 and re-emissions from media

Fig. 6. Annual depositions of PCB-153 to the Arctic in 1996.

Fig. 5. PCB-153 annual emissions, depositions and concentrations in media of the Northern Hemisphere in 1996. Red line means the Arctic

boundary.

284 A. Malanichev et al. / Environmental Pollution 128 (2004) 279–289

accumulations obtained during the previous period(1970–1995). The rough estimate of total PCB mixturedeposition to the Arctic equals 40 t. We note that thisfigure is rather conditional and needs to be refined infurther investigations.

4. Discussion

4.1. Model results verification

To validate model results, calculated PCB con-centrations in air were compared with measurementdata available from literature (Berg and Hjellbrekke,1998, 1999; Berg et al., 1996, 1997; Brorstrom-Lundenet al., 2000; Coleman et al., 1998; Oehme et al., 1995).Locations of monitoring stations are depicted inFig. 10.

The comparison of mean annual air concentrations offour PCB congeners (PCB 28, 118, 153, and 180) for theperiod of 1989–1996 is presented in Fig. 11. Most of thecomputed air concentration values (95%) are within afactor of 4 with respect to observed levels. On average,the model overestimates small atmospheric concentra-tions of PCB-118, 153 and 180. For PCB-28 the reversesituation is observed. Obtained significant correlationsbetween the calculated and measurement data (0.5–0.8)testify to the fact that the model reasonably representsthe spatial distribution of the selected PCB congeners inair.

Fig. 7. Air concentrations of PCB-153 emitted in Americas and North-western Europe for January and May.

Fig. 8. Splitting of PCB emission sources into groups.

A. Malanichev et al. / Environmental Pollution 128 (2004) 279–289 285

Fig. 9. Contributions of considered source groups to overall emissions and depositions to the Arctic for PCB-28, 118, 153, 180 in 1996.

286 A. Malanichev et al. / Environmental Pollution 128 (2004) 279–289

4.2. Basic uncertainties and further model development

Discussing the reliability of the model results, weseparate the resulting uncertainty into two parts: uncer-tainty of the calculation input data and the uncertaintyof the model itself. The input data consists of meteoro-logical and geophysical information, data on sea cur-rents and ice dynamics and emissions. It is difficult toobtain any quantitative estimates of the input datauncertainty, however, it is believed, that the mostessential one is related to the emission data.

The second group of uncertainties is connected withthe model formulation. This implies a possible neglectof some processes, which we have poor information on,and a generalized character of their description.

The way, which can lead to reduction of this group ofuncertainties, is the permanent analysis of new processeslikely to be included into the model. The decision oninvolving the new process is taken on the basis of thesensitivity study, which reveals the significance of thatprocess in comparison with that already considered. Forexample, the recent sensitivity analysis with respect toinvolving into the soil module the process of POPtransport with dissolved organic, dynamic redistributioninside solid soil phases, transport with upward soilsolute, and bioturbation has revealed the principal roleof these processes.

On the other hand a number of processes includedinto the model have a too generalized parameterisation,which can lead to some kind of uncertainties. Forexample, describing POP partitioning between gas andparticulate phases with the Junge–Pankow equation, weuse the constant value of the specific aerosol surface.This assumption, first of all, causes the uncertainty ofdeposition amounts. Another example of the general-ized parameterisation is the neglect of the latitudinaldistribution of OH radical and its diurnal variations,which provokes the uncertainty of the degradation pro-cess description. Special analysis showed that theseuncertainties might result in a deposition deviation ofseveral tens of percents and should be controlled.

Fig. 10. Locations of monitoring sites.

Fig. 11. Computed mean annual air concentrations of four PCB congeners against measured, pg/m3. Logarithmic scale is used. Dashed lines on the

diagrams limit the area with agreement between the measured and computed values within a factor of 4.

A. Malanichev et al. / Environmental Pollution 128 (2004) 279–289 287

According to this analysis following modificationshould be incorporated into the model first of all:

� usage of the spatial distribution of aerosol spe-cific area in the atmosphere;

� taking into account of the spatial distribution ofOH radical in the atmosphere and its diurnalvariation;

� modification of the soil processes description(POP transport with dissolved organic, dynamicredistribution inside solid soil phases, dynamictransport with upward soil solute, and bio-turbation);

Note, that the ultimate verification of the model canbe fulfilled only via comparison of its results withmeasurement data. The comprehensive comparisonboth for the atmosphere and other environmental media(soil, seawater, vegetation) is considered to be thepriority direction of further research.

5. Conclusions

The first results of the numerical evaluation of thePCBs transport over the Northern Hemisphere obtainedby multicompartment MSCE-POP model with resolu-tion of 2.5��2.5� are presented. They include annualaveraged fields of air and seawater concentrations andtotal annual depositions for PCB-28, 118, 153 and 180in 1996. The comparison with measurements shows thatmost of the air concentrations are in the factor 4 withrespect to observations. Deposition levels in the Arcticand their formation are considered in more detail. Tothis end the main atmospheric pathways are revealedand contributions of selected emission source groups todepositions are determined.

Unfortunately in the framework of this paper only anarrow circle of the important applied questions havebeen considered. Outside we have left two questions,which could be answered on the basis of the modelresults’ analysis and would be valuable for understandingthe general mechanism of POP fate in the environment.

The first one is the question of whether the PCB airconcentrations are still largely controlled by primaryemissions, rather than re-emission from the majorenvironmental repositories (soil, sea water). The discus-sions on this topic e.g. (Meijer et al., 2003) are in favourof the primary emissions, which is in accordance to ourcalculation results. On the other hand, to get properestimates of the re-emission importance, the modifi-cation of the soil module is needed. This conclusion isobtained both in our (Vasileva and Shatalov, 2002) andother studies, e.g. (Mclachlan et al., 2002).

The second important question concerns the fractio-nation/cold condensation effects. To this end the modelresults should be considered in context of the congenercomposition change during transport from the southtowards the north direction. The discussion on thistopic is put into the AMAP report, which is under pre-paration. Now we can assert that the model clearlydemonstrates the cold condensation effect, whichappears in enhanced soil concentration levels in theregions with low ambient temperature. This applies toboth high latitude regions and mountainous areas,which is marked in the literature, e.g. (Davidson et al.,2003).

6. Supporting information available

More detailed information on PCB transport assess-ment is given in AMAP and EMEP reports, which areunder preparation and will be available from the Inter-net page http://www.msceast.org/publications.html.There information on the spatial distribution of con-tamination (including soil and vegetation) by the PCB-28, 118, 180, more detailed comparison betweenmeasurement and the calculation data and the analysisof congener composition changing during transport ispresented. Besides, the model parameterization andinput information are described.

Acknowledgements

This work is carried out under financial support ofAMAP, EMEP and WHO. We would like to thank Mr.Sergey Dutchak for fruitful discussion, Mr. VladimirGusev and Mr. Michael Fedjunin for invaluable help inthe data preparation and the calculation implemen-tation, Ms. Irina Strizhkina for help in the picturepreparation.

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