An Assessment of Air Soil Introduction Exchange of … · 2009-08-21 · An Assessment of Air-Soil Exchange of Polychlorinated Biphenyls and Organochlorine Pesticides Across Central

An Assessment of Air-SoilExchange of PolychlorinatedBiphenyls and OrganochlorinePesticides Across Central andSouthern EuropeP E T R A R U Ž I C K O V Á , J A N A K L Á N O V Á , *P A V E L C U P R , G E R H A R D L A M M E L , A N DI V A N H O L O U B E K

RECETOX - Research Centre for Environmental Chemistry andEcotoxicology, Masaryk University, Kamenice 3/126,625 00 Brno, Czech Republic

Received June 12, 2007. Revised manuscript received October02, 2007. Accepted October 02, 2007.

Estimating the net flux direction of polychlorinated biphenylsand organochlorine pesticides is important for understanding therole of soil as a sink or source of these chemicals to theatmosphere. In this study, the soil-air equilibrium status wasinvestigated for various soil categories in Central and SouthernEurope using an extensive database of coupled soil and time-integrated air samples. Samples were collected from 47sites over a period of 5 months to assess both site-specific aswell as seasonal variations in fugacity fractions, calculatedas a potential measure of soil-air exchange. Sampling siteswere carefully selected to represent a variety of background,rural, urban, and industrial areas. Special attention wasgiven to sites in the former Yugoslavia, a country affected byrecentconflicts,wheresoilswerefoundtobehighlycontaminatedwith polychlorinated biphenyls (PCBs). Industrial soils fromthe Czech Republic, heavily polluted as a result of previouspesticide production, were also included in the survey. Soil wasfound to be a sink for highly chlorinated PCBs and fordichlorodiphenyltrichloroethane (DDT); for dichlorodiphenyldi-chloroethylene (DDE), the status was closer to equilibrium, witha tendency for net deposition during winter and net volatilizationduring summer. For lower-molecular-weight PCB congeners,as well as for R-HCH, soil tends to be a source of pollution tothe air, especially, but not exclusively, during summer.Fugacity fractions were found to decrease during the colderseasons, especially for the more volatile compounds, althoughin both the war-damaged areas and the heavily contaminatedindustrial sites, seasonal variability was very low, with fugacityfractions close to 1, indicating strong net soil-to-air transferfor all seasons. The original assumption that residents of theWestern Balkans are still exposed to higher levels of PCBs dueto the recent wars was confirmed. In general, the soil-airtransfer of PCBs and organochlorine pesticides was found tobe site-specific and dependent on the physicochemical propertiesof the contaminant in question, the soil properties, thehistorical contamination record and a site’s vicinity to sources,and the local meteorological conditions.

Introduction

Assigning current levels of persistent compounds such aspolychlorinated biphenyls (PCBs) or organochlorine pesti-cides (OCPs) to sources is not trivial since these compoundshave been banned in Europe and there are no fresh inputsof PCBs or OCPs into the environment. However, they arestill emitted from various secondary sources such as con-taminated soils, sediments, buildings, or equipment (1). Thesesemivolatile compounds are continuously cycling betweenthe atmosphere and the terrestrial environment over longperiods of time as they move toward equilibrium betweenenvironmental compartments or phases (2–5). Understand-ing the processes responsible for transport across phaseboundaries becomes even more important than quantifyingtransport within a phase, since processes like soil-airexchange influence the levels and fate of semivolatile organicchemicals in terrestrial ecosystems, as well as control therisks posed to humans by the presence of these chemicalsin the atmosphere. This fact is reflected by the number ofstudies devoted to the experimental and theoretical quan-tification of interphase transfer, including air–water, water-sediment, air-terrestrial, and various biological interphases(6).

There are generally two approaches to the characterizationof soil-air equilibrium: the use of partition coefficients andthe use of fugacity and Z values. Fugacity has the advantageof giving a clear statement of the relative equilibrium status(3, 6). A common way for estimating this status is to measureboth the gaseous concentration in the atmospheric boundarylayer and the corresponding soil concentration. Fugacityvalues can then be calculated for the compound in questionusing the concentrations in the two compartments and thefugacity capacities. Equal fugacity values in two compart-ments characterize the equilibrium (2, 7–12).

Backe et al. (8) measured PCBs in the air and precipitationto estimate a transfer of chemicals between the soil and aircompartments. Cousins et al. (2) have described a fieldexperiment where soil-air exchange was measured for anumber of PCBs, PAHs, and polychlorinated dibenzodioxinsand furans (PCDD/Fs). Meijer et al. (11) and Bidleman andLeone (12) have applied the fugacity fraction (defined as aratio of soil fugacity to the sum of soil and air fugacities) asan indication of the net direction of air-soil exchange.Fugacity calculations in both cases indicated general non-equilibrium between the soil and air (12).

In this study, a similar approach to assessing soil-airequilibrium was adopted to investigate the potential for soilsin the Western Balkan region to be a source of PCBs andOCPs to the atmosphere. The Western Balkans were selectedbecause there is a general lack of information regarding thelevels and fate of persistent organic pollutants (POPs). Furtherinterest in this region stems from the recent conflict, whichsaw a large number of destroyed military and industrialfacilities which resulted in the escape of various chemicals.The few investigations that have focused on POP contami-nation of the soil and aquatic environment have indicatedserious pollution problems in the vicinity of war-damagedfacilities in Croatia and Serbia (13–15), with regional con-tamination confirmed by pollution monitoring in neigh-boring countries after the wars (16–18). The only systematicdata, however, have been generated within the frameworkof the EU’s APOPSBAL project, aimed at evaluating the extentto which the residents of former Yugoslavia (YU) are exposedto elevated POP levels as a consequence of the Balkan conflict.

* Corresponding author. Phone: +420-549495149. Fax: +420-549492840. E-mail: [email protected].

Environ. Sci. Technol. 2008, 42, 179–185

10.1021/es071406f CCC: $40.75 2008 American Chemical Society VOL. 42, NO. 1, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY 9 179

Published on Web 11/30/2007

As a part of the APOPSBAL project, a high-volume ambientair sampling was performed in Croatia, Serbia, Bosnia andHerzegovina, and levels of PCBs and OCPs were determined(19–21). Significant PCB contamination of damaged facilitiesas well as of some storage and waste disposal sites wasconfirmed (PCB concentrations ranged between 67 pg m-3

and 40 ng m-3 for a sum of seven indicator congeners) (22).A total of 32 well categorized sites with known levels ofpollution along with the historical record of contaminationwere selected from the APOPSBAL sites for this soil-airexchange study. In addition, 15 sites in the Czech Republic(CR) were sampled, as a region not affected by the war, butheavily impacted by intensive industry. A coupled analysisof the soil samples and time-integrated passive air samplesallowed an assessment of the site-to-site and seasonalvariability in soil-air transfer.

Experimental SectionSampling Sites. A map of the sampling sites is provided inFigure 1, and a complete list of sites including their GIScoordinates can be found in the Supporting Information (SI;Table S1). This set includes four categories of sites: (i)background; (ii) rural, urban, and residential; (iii) industrial;and (iv) heavily contaminated. In the first category, Ivansedlo,Fruska Gora, and Zavizan are representatives of backgroundmountain sites to compare to PCB-contaminated sites inBosnia, Serbia, and Croatia. The remaining three sites (Libuš,Plánava, and Košetice) represented urban and rural back-grounds and an EMEP monitoring station in CR. In the groupof heavily contaminated sites (iv), there were two sites at theZastava factory in Kragujevac (YU) which suffered PCB spills.While contaminated soils are still expected to be responsiblefor the majority of PCB air pollution at this site, operationalPCB-filled transformers poses another source of contamina-tion. A similar situation was apparent at the Tuzla fire station,which serves as a storage site for discarded electricalequipment. On the other hand, there were no PCB trans-formers at the Zadar transformer station, and contaminated

soil was considered to be the only PCB source to theatmosphere at this site. An additional two sites, SpolanaArchive and Gate (CR), were considered as pollution “hotspots” due to contamination records related to the productionof OCPs and poor waste management. The group of industrialareas (iii) contains 14 sites affected by various types ofindustries (refinery, chemistry, cement, machinery, or carmanufacturing). The largest group (ii), offers a variety of 21rural, urban, and residential sites in YU and CR, with variouslevels of contamination and proximity to sources, with somesites located in the vicinity of the above-mentioned “hotspots”.

Air and Soil Sampling. Passive air samplers were em-ployed at 32 sampling sites in YU and at 15 sites in CR forfive consecutive periods of 28 days between July andDecember of 2005. Polyurethane foam disks (PUFs; 15 cmdiameter, 1.5-cm-thick, density 0.030 g cm-3, type N 3038;Gumotex Breclav, Czech Republic) housed in protectivestainless steel chambers were employed as passive airsamplers in this study (23, 24). The soil samples (top 10 cm)were collected at each site at the beginning of the samplingcampaign. Sampling and analytical procedures includingquality assurance/quality control measures were describedearlier (1, 25) (see also the Experimental Section in the SI fordetails).

Air Concentrations. The air concentrations (ng m-3) werecalculated from PUF concentrations (ng PUF-1) by applica-tion of a conversion factor, derived from laboratory calibra-tion experiments (where the average sampling rate was 100m3 per 28 days) (24). We are aware that air concentrationdata are underestimated for those compounds with asignificant particle-bound fraction because passive samplershave a limited ability to collect particles. However, thepredominance of gaseous PCBs in the atmosphere is well-known. On average, particle-bound PCBs account for lessthan 5% of the total amount of PCBs in the atmosphere (26).

FIGURE 1. The map of all sampling sites in Central and Southern Europe.

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Fugacity Calculations. In this work, the fugacities of acompound in the soil (fs) and air (fa) were calculated accordingto Harner et al. (27):

fs )CsRT ⁄ 0.41ΦOMKOA (1)

fa )CaRT (2)

where C is the concentration in the medium (mol m-3), R isthe gas constant (8.314 J mol-1 K-1), T is the absolutetemperature (K), �OM is the fraction of the organic matter inthe soil (1.7 times the organic carbon fraction), and KOA

is the octanol-air partitioning coefficient of the compound.The factor 0.411 improves the correlation between the soil-airpartitioning coefficient and KOA (12, 28, 29). KOA can beobtained from the relation:

KOA ) KOW ⁄KAW (3)

KAW )H ⁄ 100RT (4)

R)R′100 (5)

where KOW is the octanol–water partitioning coefficient, KAW

is the air–water partitioning coefficient, H is Henry’s lawconstant (Pa m3 mol-1), and R ′ is the gas constant (0.08205l atm K-1 mol-1). A temperature correction of H was obtainedusing the integrated van’t Hoff equation (cf., e.g., Cousinsand Jones 7, 8):

ln(H1 ⁄ H2) ) -∆HAW(1 ⁄T1 - 1 ⁄T2) ⁄ R (6)

where H1 and H2 are Henry’s law constants at two temper-atures, T1 and T2 are temperatures (K), and ∆HAW is theenthalpy of vaporization (J mol-1).

The fugacity fraction (ff) is calculated as the fugacity insoil divided by the sum of fugacities in soil and air and givesan indication of the net direction of air-soil exchange (27).

ff ) fs ⁄ (fs + fa) (7)

The fugacity fractions near 0.5 indicate equilibrium; fractions>0.5 indicate net volatilization from the soil into air, whereasvalues <0.5 indicate net deposition from air to soil (see alsoSI for more details). However, due to uncertainties and thepropagation of errors in the calculation using eq 7, fugacityfractions between 0.3 and 0.7 were not considered to differsignificantly from equilibrium (11, 27).

Results and DiscussionSoil and Air Concentrations. An overview of the soil and airconcentrations of PCBs and OCPs found in four categoriesof sampling sites is provided in Table 1. Detailed informationon the soil and air concentrations measured at the individualsites is presented in Table S2, SI.

In the soil samples (uppermost soil layer), PCB concen-trations ranged between 1 ng g-1 and 3 µg g-1 for a sum ofseven indicator congeners, with the highest values found in

the Zastava factory in Kragujevac, Gorica, and Tuzla firestation. Similarly, the highest PCB air concentration of 90 ngm-3 was observed in Zastava.

OCP concentrations in the Balkan soils were below 1 ngg-1 for HCHs, and between 1 and 60 ng g-1 for thedichlorodiphenyltrichloroethanes (DDTs). Correspondingmaximum concentrations in the soils from CR (Spolanafactory) were much higher: 0.4 µg g-1 for R-HCH, 4.3 µg g-1

for �-HCH, 0.1 µg g-1 for γ-HCH, 1.8 µg g-1 for DDT, and 1.4µg g-1 for dichlorodiphenyldichloroethylene (DDE). Ambientair concentrations as high as 55 ng m-3 for the sum of HCHsand 1 ng m-3 for the sum of DDTs were determined at thismost contaminated site from CR.

Fugacity Fractions. Fugacity fractions (ff) of six PCBcongeners and six OCPs were calculated for three seasons atall sampling sites: a full list of ff values is provided in the SI(see Tables S3 and S4). For the individual compounds, thefugacity fractions varied widely between 0 and 1 except forγ-HCH, which showed very low values (bellow 0.1) at allsites. In general, PCBs displayed a decrease in ff values withthe degree of chlorination, whereby median values were0.64–0.76 for the less-chlorinated PCBs, while PCB 180 hada low value of 0.24. This is accounted for by an increasingfugacity capacity, ZO, from low-chlorinated to high-chlori-nated PCBs (in line with variation of KOW and KOA).

From the range of fugacity fractions for the variouscompounds shown in the SI, Figure S1, it can be concludedthat soil is a sink for highly chlorinated PCBs (PCB 180), forDDT, and for γ-HCH. For DDE, the status is closer toequilibrium, with a tendency toward net air-to-soil transfer(depositional behavior) during winter and net volatilizationduring summer. For most of the PCB congeners, as well asfor R-HCH, soil tends to be a source of these chemicals tothe air especially, but not exclusively, during summer. Thisis in a good agreement with previously published studies(11, 12). For most substances, these findings are explainedby their physicochemical properties: notably, low vaporpressures and a high KOA corresponding to low ff values andvice versa. For example, PCB-180 and p,p′-DDT (displayingff values of 0.35 and 0.48 at the Praha urban background site,for instance) have low vapor pressures of 0.13 and 0.034 mPa,at 298 K, respectively (30, 31), and high values of KOA at 1010.9

and 1010.1, respectively (32), whereas PCB 28 and R-HCH hadff values of 0.88 and 0.98 at the same site but have relativelyhigh vapor pressures (23 and 8.4 mPa at 298 K, respectively)(30, 31) and lower values of KOA (108.2 and 107.8, respectively)(32). On the other hand, γ-HCH, which has a high vaporpressure and moderate KOA (6.6 mPa and 108.1, respectively),was less easy to predict, as these physicochemical propertieswould suggest that this chemical undergoes net volatilizationfrom soil, whereas the ff values were all <0.5, indicating netdeposition. We speculate that fugacity from soil might havebeen overcompensated for by depositional processes: wetdeposition of γ-HCH is particularly effective due to its

TABLE 1. Summary of Air and Soil Concentrations (ng m-3 and ng g-1, Respectively) for the Various Site Categories

CA (ng m-3) CS (ng g-1)

min max mean med min max mean med

PCBsa

background sites (n ) 6) 0.04 0.016 0.11 0.12 1.3 2.3 1.8 1.8residential, rural, urban sites (n ) 21) 0.04 0.73 0.20 0.16 1.8 20.1 6.8 5.9industrial sites (n ) 14) 0.08 1.35 0.29 0.22 0.7 68.4 27.2 23.3heavily contaminated sites (n ) 6) 0.08 90.6 7.56 0.64 42.5 3085 839 563

OCPsb

background sites (n ) 6) 0.10 0.59 0.22 0.15 1.2 3.2 2.4 2.9residential, rural, urban sites (n ) 21) 0.07 0.90 0.23 0.18 0.5 59.3 12.5 7.9industrial sites (n ) 14) 0.07 0.95 0.29 0.26 0.2 95.5 18.1 6.1heavily contaminated sites (n ) 6) 0.10 54.9 1.88 0.43 3.9 5243 870 54.5

a Sum of seven congeners. b Sum of p,p′-DDT; DDE; DDD; and R-, �-, γ-HCH.

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significant water solubility (7.4 mg L-1, while it is only 2.0 mgL-1 for R-HCH). For this reason, retention in the aqueousphase within humid soils will be enhanced.

Variability of the fugacity fractions was higher for thelower-chlorinated PCB congeners. At the Košetice back-ground site, ff ranged between 0.30 and 0.53 for PCB 52, butonly 0.02–0.11 for PCB 180. Similarly, at Pancevo City Hall,values ranged from 0.10 to 0.31 for PCB 28 but only 0.02–0.08for PCB 180. Differences in mobility of the PCB congenersprovide a possible explanation for this observation. Due totheir higher volatility and low retention in soil (lower ZO), theless-chlorinated PCB congeners are probably more mobileand subject to soil-to-air transfer, resulting in their wide-spread dispersal to soils in rural and background areas. Thetemporal variability displayed in the air concentrations ofthe lower-chlorinated PCBs (in turn determined by varyingspatial and temporal patterns of emissions and atmospherictransport) is reflected in elevated but varying values of ff.Consistent with this explanation, this effect (i.e., the differencein ff variability between the lower- and higher-chlorinatedcongeners) was not pronounced at the heavily contaminatedsites, where for example ff values ranged from 0.75 to 0.99for PCB 52 and 0.79–0.89 for PCB 180 in the Spolana factory,

and similarly 0.93–0.98 for PCB 28 and 0.77–0.90 for PCB 180in Pancevo, Petrochimika. A special case is the polluted siteof the Zadar transformer station, where the soil was--unlikethe other sites--contaminated with Pyralene oil with a highcontent of PCB 28 but less PCB 180 when the station wasdamaged. This is reflected in the very high ff values for PCB28 (0.86–0.90), with relatively low values for PCB 180 (ff )0.18–0.27).

For OCPs, the median values of fugacity fractions werehigher in CR than in YU. R-HCH, for instance, had a medianof 0.45 in YU and 0.93 in CR. Similarly, DDE and DDT medianff values were 0.32 and 0.14, respectively, in YU, but 0.62 and0.33, respectively, in CR. This corresponds to higher soilcontamination in CR. For example, both DDE and DDT hadsoil concentrations ranging from 0.3 to 41.3 and 0.1 to 53.2ng g-1 (median 1.8 and 1.3 ng g-1), respectively, while at YU,concentrations ranged from 1.0 to 1135.7 and 0.7 to 1906.9ng g-1 (median 7.0 and 4.3 ng g-1).

Effect of Soil Properties. Strong correlations between thefugacity fractions for the various compounds and soil organiccarbon were not evident across the whole data set. A weakcorrelation was observed for the most volatile compounds,that is, R-HCH (see SI, Figure S2), PCB 28, and PCB 52, with

FIGURE 2. Seasonal variability of the fugacity fractions, ff ) fs/(fs + fa), of selected PCBs and OCPs as measured at 47 samplingsites between July and December, 2005.


the exception of γ-HCH. The correlation did not appear tobe influenced by season and hence temperature. Thesefindings suggest that the organic carbon content can only

control air-soil equilibrium if retention in soils is limited bysignificant variations in physicochemical properties such asvapor pressure or KOA. It means that, for low-volatile

FIGURE 3. (a) Site-specific and seasonal variability of the fugacity fractions, ff, of PCB 153. Three bars at each sampling siterepresent ff determined in July (summer), September (autumn), and November (winter). (b) Site-specific and seasonal variability ofthe fugacity fractions, ff, of DDE. Three bars at each sampling site represent ff determined in July (summer), September (autumn), andNovember (winter).


compounds and substances with a high KOA, coupled to highsoil concentrations, the air-soil equilibrium cannot beachieved unless strong sources maintain very high atmo-spheric concentrations (which may be the case at the Zastavafactory site where high levels of PCBs are maintained byevaporation from the PCB-filled transformer). A strongercorrelation was achieved when soils were analyzed separatelyfor the background sites and heavily contaminated sites (seeSI, Table S5).

Seasonality of Soil-Air Equilibrium Status. From Julyto December, a decreasing trend in the levels of PCBs andOCPs in the atmosphere was observed. As this correspondedto the decrease of average daily temperatures as well as tothe reduced average daytime atmospheric mixing depth, weconclude that during the warm season enhanced evaporationfrom soil to air overcompensated for more efficient dilutionof the contaminants emitted from surfaces. A seasonal trendof corresponding fugacity fractions (reduction in median ff

values toward the colder season) for selected PCBs and OCPs(more pronounced for more volatile compounds, such asPCB 28 and R-HCH) can be observed in Figure 2.

Effect of Historical Records of Contamination. In Figure2, the overall seasonal variability of ff values is shown. Thisvariability, however, differs from site to site, as presented inthe sampling sites in Figure 3a and b, for example (highlightedin Table S2, see SI).

For PCB 153, very low fugacity fractions were observedat the background sites (Kosetice observatory, no. 47: ff )0.3–0.5, Zavizan, no. 28) where soil serves as a depositionalsink (Figure 3a). Zavizan observatory, for instance, wasselected as a background site to the Zadar transformer station(no. 29). Although most of the soil from the immediate vicinityof the damaged transformer had been removed, enhancedPCB evaporation was still apparent during the warm season.While in Zadar the fugacity fractions varied between 0.60 inwinter and 0.75 in summer, the corresponding values forZavizan stayed between 0.25 and 0.45. At this site, the soilis relatively uncontaminated, with PCBs present due todeposition from air advected over contaminated sites likeZadar and other facilities in the area damaged during thewar.

A similar situation can be observed in Pancevo. Forexample, contaminated soils in Petrochimika (no. 15) act asa source of pollution, causing an increase in the fugacityfraction (0.88–0.95), whereas downtown Pancevo (Cityhall,no. 16) is affected by this locally contaminated air, with soilhere acting as a sink (ff ) 0.13–0.28).

As discussed earlier, the fugacity fraction does not decreasesignificantly in the cold months at heavily contaminated sites(Spolana, no. 34, ff)0.95–0.97 throughout July to December).The exception is, however, Zastava factory (no. 11), wherethe fugacity fraction stayed between 0.52 and 0.66 throughoutJuly to December despite possessing very high PCB soilconcentrations. The reason for this is an operational PCB-filled transformer which most likely serves as a strong sourceof PCBs to the air, particularly during the warmer months.

Our findings suggest that contaminated soils in the war-damaged areas (Kragujevac, Zadar) are still sources of PCBsto the atmosphere. Moreover, many of the PCB-filledcapacitors remaining in service (Kragujevac) pose furtherrisks. Taking a preliminary estimation that currently useddevices in former Yugoslavia contain 65 tons of PCBs, thenthis risk cannot be underestimated. Even though operationof some damaged capacitors was already discontinued, thereis apparently no systematic solution to this problem, sincemany of these devices are stored without proper managementin place (i.e., Tuzla). The original assumption that residentsof the Western Balkans are exposed to higher levels of PCBsdue to the recent wars was further confirmed by an ongoingpassive air sampling campaign performed at background

sites in the countries of Central, Eastern, and Southern Europe(33). While mean atmospheric concentrations of PCBs (sevenindicator congeners) at background sites in Estonia, Latvia,Lithuania, the Czech and Slovak Republics, or Romania variedbetween 27 and 53 ng m-3 in 2006, concentrations reached117 and 187 ng m-3 in Bosnia and Serbia, respectively.

Variability of the ff values of DDE (Figure 3b) revealedsimilar trends. In the Spolana factory (no. 34), where the soilwas heavily contaminated with DDE (and HCHs), as aconsequence of pesticide production and storage in the 1960sand 1970s, ff values show almost no variation (0.85–0.90),whereas seasonal variation was more apparent at the less-contaminated sites. Summer values were typically 3 timeshigher than the winter values observed in some urban (Praha,no. 36: ff ) 0.11–0.48; Zagreb, no. 25: ff ) 0.20–0.69) and rural(Plánava, no. 46: ff ) 0.36–0.94) sites. At these sites, whichhave been influenced by contamination from regional “hotspots” over recent decades (CR), or at least in recent years(YU), air-soil exchange oscillated around equilibrium, withsoils acting more as sinks in winter and as sources in summer.Several sites with very low values of ff for DDE were evident,particularly the background sites Zavizan (no. 28: ff )0.06–0.26) and Novi Sad (no. 18: ff ) 0.04–0.19). We concludethat, for DDTs, the historical record of contamination, longerin CR than in YU, can influence the variation in ff values.

HCH contamination of the Spolana factory, as a formermajor HCH producer, is suspected of having of regionalsignificance with regard to HCH emissions. During the years1961–1965 when only pure lindane was marketed, the ballastcongeners were dumped within the factory grounds. There-fore, soils in this area are heavily polluted with R-HCH and�-HCH, while the level of γ-HCH is very low. This is reflectedin the fugacity fractions ff ) 0.92–1.00 for R-HCH and ff )0.03–0.27 for γ-HCH. This is also the case for all the samplesites in the vicinity of Spolana, with a similar pattern (i.e.,high fugacity fractions for R-HCH and low for γ-HCH) foundat most sampling sites in CR. The situation is different in YU,where the fugacity fraction ofR-HCH is much more variable.In urban areas, such as Sarajevo (ff)0.22–0.33) or Kragujevac(ff ) 0.11–0.20), very low values were observed, while inIvansedlo (a background site), the values ranged between0.61 and 0.84, and in Pancevo between 0.73 and 0.98.

While only the net direction of the soil-air exchange wasaddressed in this study, supplementary field and laboratoryexperiments focused on quantification of the volatilizationfluxes from the region are currently in progress. Generateddata are being used not only for transport and distributionmodels but also for the national POPs inventories, organizedin compliance with reporting commitments of the memberstates of the Stockholm Convention.

AcknowledgmentsThis project was supported by EU 5FP Project ICA2-CT2002-10007 and Ministry of Education of the Czech Republic ProjectMSM 0021622412. Authors express their gratitude to CrisHalsall for editing the manuscript.

Supporting Information AvailableExperimental section, GIS coordinates of the sampling sites(Table S1), median soil and air concentrations of PCBs andOCPs at all sampling sites (Table S2), fugacity fractions forselected PCBs (Table S3) and OCPs (Table S4) at all sites,ranges of the fugacity fractions (Figure S1), and correlationbetween the fugacity fractions and the organic carbon contentin the top soils (Figure S2, Table S5). This information isavailable free of charge via the Internet at http://pubs.acs.org/.

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(16) Rapsomanikis, S.; Zerefos, C.; Melas, D.; Tsangas, N. Transportof toxic organic aerosol pollutants from Yugoslavia to Greeceduring the operation allied force. Environ. Technol. 2002, 23,1119–1125.

(17) Kerekes, A.; Capote-Cuellar, A.; Koteles, G. J. Did NATO attacksin Yugoslavia cause a detectable environmental effect inHungary. Health Phys. 2001, 80, 177–178.

(18) Melas, D.; Zerefos, C.; Rapsomanikis, S.; Tsangas, N.; Alexan-dropoulou, A. The war in Kosovo - Evidence of pollution

transport in the Balkans during operation “Allied Force”.Environ. Sci. Pollut. R. 2000, 7, 97–104.

(19) Klanova, J.; Kohoutek, J.; Kostrhounova, R.; Holoubek, I. Are theresidents of former Yugoslavia still exposed to elevated PCBlevels due to the Balkan wars? - Part 1: air sampling in Croatia,Serbia, Bosnia and Herzegovina. Environ. Int. 2007, 33, 719–726.

(20) Skarek, M.; Cupr, P.; Bartos, T.; Kohoutek, J.; Klanova, J.;Holoubek, I. A combined approach to the evaluation of organicair pollution - A case study of urban air in Sarajevo and Tuzla(Bosna and Hercegovina). Sci. Total Environ. 2007, 384, 182–193.

(21) Zencak, Z.; Klanova, J.; Holoubek, I.; Gustafsson, O. Sourceapportionment of atmospheric PAHs in the western balkans bynatural abundance radiocarbon analysis. Environ. Sci. Technol.2007, 41, 3850–3855.

(22) Klanova, J.; Kohoutek, J.; Cupr, P.; Holoubek, I. Are the residentsof former Yugoslavia still exposed to elevated PCB levels dueto the Balkan wars? Part 2: Passive air sampling network. Environ.Int. 2007, 33, 727–735.

(23) Harner, T.; Shoeib, M.; Diamond, M.; Stern, G.; Rosenberg, B.Using passive air samplers to assess urban - Rural trends forpersistent organic pollutants. 1. Polychlorinated biphenyls andorganochlorine pesticides. Environ. Sci. Technol. 2004, 38, 4474–4483.

(24) Shoeib, M.; Harner, T. Characterization and comparison of threepassive air samplers for persistent organic pollutants. Environ.Sci. Technol. 2002, 36, 4142–4151.

(25) Holoubek, I.; Klánová, J.; Jarkovský, J.; Kubík, V.; Helešic, J. Trendsin background levels of persistent organic pollutants at Koseticeobservatory, Czech Republic. Part II. Aquatic and terrestricenvironments 1988–2005. J. Environ. Monit. 2007, 9, 564–571.

(26) Mandalakis, M.; Stephanou, E. G. Atmospheric concentrationchracteristics and gas-particle partitioning of PCBs in a ruralarea of eastern Germany. Environ. Pollut. 2006, 147, 211–221.

(27) Harner, T.; Bidleman, T. F.; Jantunen, L. M. M.; Mackay, D.Soil-air exchange model of persistent pesticides in the US CottonBelt. Environ. Toxicol. Chem. 2001, 20, 1612–1621.

(28) Hippelein, M.; McLachlan, M. S. Soil/air partitioning of semi-volatile organic compounds. 1. Method development andinfluence of physical-chemical properties. Environ. Sci. Technol.1998, 32, 310–316.

(29) Meijer, S. N.; Shoeib, M.; Jones, K. C.; Harner, T. Air-soilexchange of organochlorine pesticides in agricultural soils. 2.Laboratory measurements of the soil-air partition coefficient.Environ. Sci. Technol. 2003, 37, 1300–1305.

(30) Shiu, W. Y.; Mackay, D. A Chritical Review of Aqueous Solubities,Vapor Pressures, Henry’s Law Constants, and Octanol-WaterPartition Coefficients of the Polychlorinated Biphenyls. J. Phys.Chem. Ref. Data 1986, 15, 911–929.

(31) Rippen, G. Umweltchemikalien, CD-ROM ed.; Ecomed Publish-ers: Landsberg, Germany, 2000.

(32) Harner, T.; Mackay, D. Measurements of octanol-air partitioningcoefficients for chlorobenzenes, PCB and DDT. Environ. Sci.Technol. 1995, 29, 1599–1606.

(33) Klánová, J.; Cupr, P.; Holoubek, I. Application of the passivesampler for determination of the POPs concentrations in ambientair; Masaryk University: Brno, Czech Republic, 2007.

ES071406F


S1

Application of fugacity fractions of polychlorinated 1

biphenyls and organochlorine pesticides for the 2

assessment of dynamic nature of soil-air equilibrium.3

4

Petra Růžičková, Jana Klánová*, Pavel Čupr, Gerhard Lammel, and Ivan Holoubek5

6

RECETOX - Research Centre for Environmental Chemistry and Ecotoxicology, Masaryk University, 7Kamenice 3/126, 625 00 Brno, Czech Republic8

9

Corresponding author: [email protected], phone: +420-549495149; fax: +420-54949284010

Supporting Information 11

Summary12

Pages: 2013

Tables: 514

Figures: 215

16

mailto:[email protected]

S2

Experimental section17

18

Air and soil sampling19

Sampling chambers were prewashed and solvent-rinsed with acetone prior to installation. All filters 20

were prewashed, cleaned (8 hours extraction in acetone and 8 hours in dichloromethane), wrapped in 21

two layers of aluminum foil, placed into zip-lock polyethylene bags and kept in the freezer. Exposed 22

PUFs were wrapped in two layers of aluminum foil, labeled, placed into zip-lock polyethylene bags and 23

transported to the laboratory in cooler at 5 °C.24

25

Soil samples were taken from the top 10 cm layer in 25 m×25 m sampling plots as 5-10 sub-samples, 26

which were combined and homogenized. Soil samples were transported to the laboratory in 27

polyethylene bags, air-dried at laboratory temperature, and sieved through a 2-mm mesh. The organic 28

carbon content was determined in all soil samples using a High Temperature TOC Analyzer Liqui TOC 29

II (Elementar Analysensysteme, Germany).30

31

Sample analysis32

All samples were extracted with dichloromethane in a Büchi System B-811 automatic extractor. A 33

laboratory blank and standard reference material were analyzed with each set of ten samples. Prior to 34

extraction, PUFs were spiked with surrogate recovery standards (PCB 30 and PCB 185), PCB 121 was 35

used as an internal standard. After extraction, the volume was reduced under a gentle nitrogen stream at 36

ambient temperature. A sulphuric acid modified silica gel column was used for a clean up of PCB/OCP 37

samples. The samples were analyzed using GC-ECD (HP 5890) supplied with a Quadrex fused silica 38

column (Quadrex, 5% Ph) for PCBs (PCB 28, PCB 52, PCB 101, PCB 153, PCB 138, PCB 180), and 39

OCPs (α-HCH, β-HCH, γ-HCH, p,p´-DDE, p,p´-DDD, p,p´-DDT). 40

41

42

S3

Quality assurance / quality control43

Recovery factors were not applied to any of data since recoveries were higher than 76 % for all 44

samples. Recoveries of native analytes determined in the reference material varied from 88 to 100 % for 45

PCBs and from 75 to 98 % for OCPs. Field blanks consisted of pre-extracted PUF disks were taken on 46

each sampling site. The levels in field blanks never exceeded 3 % of quantities detected in samples for 47

PCBs and 1 % for OCPs indicating minimal contamination during the transport, storage and analysis. 48

Samples were not blank-corrected.49

50

Fugacity calculations51

A fugacity (f) of a compound is a equilibrium criterion for the mass diffusion between phases and it 52

has the units of pressure. Thus, the fugacity of a gas is closely related to partial pressure. When a 53

chemical achieves equilibrium between two phases i and j, its fugacity fi equals fj, but its concentrations 54

Ci and Cj in units of mol m-3 are usually not equal. A fugacity is related to concentration in each phase 55

through a Z-value. Z-value is a fugacity capacity for a substance in given phase with the units of 56

concentration and reciprocal pressure (mol m-3 Pa-1). An equilibrium partitioning coefficient Kij is thus a 57

ratio of Z-values:58

Ci = Zi f (Eq.1)59

Kij = Ci / Cj = Zif / Zjf = Zi / Zj (Eq.2)60

Z-value can be determined for all phases from physico-chemical and environmental properties: They 61

can be derived by starting in the gas-phase (air) and proceeding to subsequent neighboring phases using 62

measured partitioning coefficients between pairs of adjacent phases. It is important to note that all Z-63

values depend on temperature, the properties of the substance, and the nature of the phase to which the 64

substance is associated. The fugacity capacity and the phase volume of the environmental system are the 65

key parameters needed to determine the distribution of a substance into different phases at equilibrium. 66

In a multiphase system, a chemical tends to concentrate in phases with high Z-values.67

Definition of Z-values:68

S4

ZA(air) = 1/RT R – gas constant (8,314 Pa m3 mol-1 K-1), T – temperature (K)69

ZW(water) = 1/H H – Henry’s law constant (Pa m3 mol-1)70

or WS/VP WS – water solubility (mol m-3), VP – vapor pressure (Pa)71

ZS(sediment) = KD.ρS/H ρS – sediment density (kg l-1), KD – sediment-water partitioning coefficient (l kg-1)72

ZO(octanol/lipid) = KOW/H KOW – partitioning coefficient octanol-water73

ZF(fish) = KBρB/H KB – bioconcentration factor (l kg-1)74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

S5

Table S1. WGS 84 coordinates of the sampling sites92

Sampling site X Y Z

1 Sarajevo Standard 43.8447340 18.3305820 1670

2 Sarajevo HMI 43.8677850 18.4228720 2117

3 Sarajevo VW 43.8998750 18.3599110 1741

4 Sarajevo Vlakovo 43.8577770 18.2509430 1726

5 Sarajevo Ivansedlo 43.7511320 18.0362860 3191

6 Tuzla hotel 44.5301030 18.6857950 817

7 Tuzla firestation 44.5319070 18.6550750 812

8 Tuzla mine 44.5472450 18.6655000 829

9 Tuzla meteo 44.5420830 18.6851770 1025

10 Tuzla Bukyne 44.5236760 18.6004480 745

11 Kragujevac Zastava 44.0177778 20.9069444 205

12 Kragujevac FN 44.0027778 20.9127778 204

13 Kragujevac UNI 44.0036111 20.9125000 199

14 Pancevo refinery 44.8322222 20.6902778 82

15 Pancevo Petrochimika 44.8325630 20.6713860 265

16 Pancevo cityhall 44.8700000 20.6400000 100

17 Novi Sad refinery 45.2783890 19.8701810 286

18 Novi Sad Sanghaj 45.2729700 19.8733510 254

19 Novi Sad Sport 45.2482130 19.8464850 269

20 Fruska Gora 45.1591690 19.8627970 1700

21 Western Slavonia Poljana 45.2388610 17.3112460 350

22 Western Slavonia Gorica 45.2177830 17.2934400 476

23 Zagreb MI 45.8352080 15.9783430 555

24 Zagreb IRB 45.8306480 15.9883890 677

25 Zagreb MS 45.8218130 16.0337760 410

26 Zagreb Jak 45.7646850 16.0179280 356

27 Zagreb Dep 45.7687960 16.0232740 441

28 Zavizan 44.8146200 14.9752880 5241

29 Zadar transformer 44.1066470 15.2635730 60

30 Zadar Adria 44.0965450 15.2608180 4

S6

31 Zadar HS 44.1126400 15.2287230 107

32 Zadar meteo 44.1300870 15.2058780 19

33 Spolana archive 50.2656400 14.5206500 165

34 Spolana gate 50.267130 14.525150 163

35 Spolana Libiš 50.278060 14.506310 161

36 Praha Libuš 50.0066100 14.4462400 218

37 Mokrá Nová pole 49.1766200 16.5728600 277

38 Napajedla 49.1708900 17.5163500 207

39 Otrokovice 49.2083000 17.5354900 208

40 Zlín 49.2238600 17.6605800 218

41 Slušovice 49.2494700 17.8092000 276

42 Vizovice 49.2220400 17.8540800 294

43 Val.Mez. observatory 49.4636500 17.9737100 339

44 Mštěnovice 49.5057900 17.9590600 304

45 Příluky 49.5092500 17.9417400 276

46 Pláňava 49.047760 18.007810 605

47 Košetice 49.568490 15.085370 445

93

94

95

96

97

98

99

100

101

S7

Table S2. Median air and soil concentrations of PCBs (sum of 7 indicator congeners), HCHs (sum of α-, 102

β-, γ-HCH) and DDTs (sum of p,p’-DDT, DDE, DDD) measured at 47 sampling sites. Sampling site 103

category is assigned to each entry. Highlighted items were selected for graphical presentation in Fig. 3a, 104

3b showing site-to-site variability of equilibrium status for PCB 153 (*) and p,p‘-DDE (#).105

106

PCBs HCHs DDTs PCBs HCHs DDTsNo Sampling site Sampling site

category air air air soil soil soil

1 Sarajevo Standard Industrial 0.236 0.070 0.021 3.4 0.1 8.0

2 Sarajevo HMI Urban 0.231 0.134 0.039 3.1 0.1 7.4

3 * # Sarajevo VW Industrial 0.226 0.076 0.026 68.4 0.2 6.6

4 Sarajevo Vlakovo Industrial 0.275 0.064 0.023 5.1 0.04 0.5

5 # Sarajevo Ivansedlo Background 0.117 0.076 0.028 83.1 0.3 10.8

6 Tuzla hotel Industrial 0.533 0.289 0.036 55.9 0.1 1.7

7 Tuzla firestation Heavily contaminated 0.658 0.148 0.067 883.3 0.8 47.5

8 Tuzla mine Urban 0.136 0.100 0.036 23.8 0.1 4.1

9 Tuzla meteo Urban 0,147 0.106 0.048 6.9 0.2 5.1

10 Tuzla Bukyne Industrial 0.201 0.159 0.054 11.5 0.1 7.1

11 * Kragujevac Zastava Heavily contaminated 45.823 0.431 0.912 1292.5 0.2 60.6

12 Kragujevac FN Heavily contaminated 2.065 0.333 0.083 197.9 0.7 18.5

13 Kragujevac UNI Urban 0.164 0.335 0.045 22.8 0.4 3.6

14 Pancevo refinery Industrial 0.347 0.379 0.183 34.4 0.3 5.2

15 * Pan. Petrochimika Industrial 0.379 0.206 0.094 37.6 0.6 3.0

16 * Pancevo cityhall Urban 0.233 0.417 0.184 1.8 0.2 26.7

17 Novi Sad refinery Industrial 0.188 0.253 0.131 0.7 0.03 0.2

18 # Novi Sad Sanghaj Urban 0.155 0.331 0.109 6.8 0.1 2.8

19 Novi Sad Sport Urban 0.154 0.270 0.077 4.2 0.1 3.2

20 Fruska Gora Background 0.122 0.212 0.108 1.8 0.02 2.9

21 W. Slavonia Poljana Rural 0.078 0.098 0.050 3.7 0.1 2.1

22* W. Slavonia Gorica Urban 0.092 0.229 0.034 3085.2 0.4 23.5

23 Zagreb MI Urban 0.133 0.112 0.038 11.0 0.2 14.8

24 Zagreb IRB Urban 0.133 0,109 0.042 11.3 0.3 2.5

25 # Zagreb MS Urban 0.197 0,133 0,055 2.3 0.1 14.9

S8

PCBs HCHs DDTs PCBs HCHs DDTsNo Sampling site Sampling site

category air air air soil soil soil

26 Zagreb Jak Urban 0.268 0.138 0.051 11.3 0.1 0.9

27 * Zagreb Dep Urban 0.444 0.136 0.058 8.3 0.4 12.7

28 * # Zavizan Background 0.128 0.133 0.055 2.3 0.1 1.0

29 * Zadar transformer Heavily contaminated 3.455 0.103 0.047 242.5 147.4 754.1

30 Zadar Adria Industrial 0.149 0.064 0.035 9.6 0.1 2.1

31 # Zadar HS Urban 0.123 0.070 0.305 15.3 0.1 61.6

32 Zadar meteo Urban 0.080 0.070 0.069 5.3 0.1 1.3

33 Spolana archive Heavily contaminated 0.233 0.665 0.200 68.8 147.4 754.1

34 * # Spolana gate Heavily contaminated 0.612 5.284 0.531 901.4 1 642.0 3 601.3

35 Spolana Libiš Urban 0.232 0.181 0.200 41.8 7.6 657.9

36 # Praha Libuš Background 0.149 0.084 0.078 3.0 2.4 6.0

37 Mokrá Nová pole Industrial 0.107 0.095 0.230 6.8 92.5 3.0

38 Napajedla Industrial 0.128 0.074 0.097 5.3 1.7 7.1

39 # Otrokovice Industrial 0.245 0.125 0.162 30.3 0.6 10.1

40 * Zlín Industrial 0.200 0.101 0.108 60.7 1.1 40.0

41 # Slušovice Rural 0.125 0.084 0.057 7.4 27.0 11.5

42 Vizovice Rural 0.152 0.095 0.102 20.1 0.8 58.5

43 * # Val.Mez. observ. Urban 0.154 0.126 0.086 6.4 0.3 2.2

44 Mštěnovice Rural 0.101 0.090 0.049 9.9 0.4 10.4

45 * Příluky Rural 0.149 0.124 0.059 3.0 0.8 23.2

46 # Pláňava Background 0.138 0.184 0.204 1.4 26.4 110.2

47 * Košetice Background 0.068 0.067 0.062 1.3 0.6 2.7

107

108

109

110

111

112

S9

Table S3. Fugacity fractions, ff, for selected PCBs at all sampling sites. Sampling periods July, 113

September and November (average temperature 22 °C, 15 °C, and 5 °C, respectively, for YU, and 19 114

°C, 13 °C, and 4 °C, respectively, for CR).115

Site fr(PCB 28) fr (PCB 52) fr (PCB 101) fr (PCB 153) fr (PCB 138) fr (PCB 180)

0.28 0.74 0.78 0.66 0.57 0.32

0.55 0.67 0.53 0.36 0.30 0.10

Sarajevo Standard

5.7 % OC

Industrial 0.09 0.37 0.64 0.46 0.43 0.14

0.34 0.62 0.75 0.74 0.67 0.43

0.21 0.38 0.60 0.34 0.27 0.13

Sarajevo HMI

5.8 % OC

Urban 0.15 0.31 0.37 0.28 0.26 0.09

0.47 0.78 0.94 0.96 0.94 0.89

0.26 0.57 0.90 0.93 0.90 0.82

Sarajevo VW

8.0 % OC

Industrial 0.20 0.37 0.81 0.90 0.88 0.71

0.55 0.52 0.64 0.57 0.44 0.24

0.22 0.35 0.60 0.69 0.58 0.35

Sarajevo Vlakovo

5.6 % OC

Industrial 0.15 0.06 0.08 0.47 0.25 0.18

0.86 0.99 1.00 0.98 0.98 0.90

0.81 0.98 0.99 0.97 0.96 0.87

Sarajevo Ivansedlo

5.0 % OC

Background 0.65 0.85 0.88 0.95 0.94 0.81

0.97 0.97 0.94 0.90 0.87 0.72

0.98 0.97 0.98 0.91 0.90 0.65

Tuzla hotel

3.9 % OC

Industrial 0.99 0.94 0.76 0.77 0.73 0.44

0.82 0.97 0.99 0.99 0.99 0.97

0.67 0.95 0.99 0.99 0.98 0.97

Tuzla fire station

10.1 % OC

Heavily contaminated 0.61 0.89 0.98 0.99 0.99 0.97

0.80 0.92 0.97 0.94 0.93 0.81

0.73 0.80 0.97 0.92 0.91 0.76

Tuzla mine

8.5 % OC

Urban 0.47 0.57 0.74 0.71 0.65 0.37

0.79 0.85 0.92 0.87 0.79 0.58

0.71 0.67 0.93 0.79 0.81 0.53

Tuzla meteo

5.1 % OC

Urban 0.31 0.41 0.61 0.74 0.69 0.41

S10


0.65 0.96 0.98 0.89 0.87 0.53

0.62 0.93 0.99 0.87 0.85 0.45

Tuzla Bukyne

3.6 % OC

Industrial 0.49 0.83 0.88 0.77 0.70 0.27

0.37 0.60 0.60 0.66 0.53 0.24

0.26 0.53 0.53 0.61 0.49 0.21

Kragujevac Zastava

8.1 % OC

Industrial 0.28 0.52 0.50 0.53 0.38 0.14

0.49 0.67 0.75 0.79 0.68 0.27

0.49 0.68 0.78 0.86 0.82 0.72

Kragujevac FN

9.7 % OC


0.69 0.42 0.39 0.45 0.79 0.19

0.56 0.58 0.78 0.78 0.97 0.48

Kragujevac UNI

7.5 % OC

Urban 0.50 0.32 0.84 0.52 0.93 0.18

0.99 0.98 0.36 0.38 0.24

0.99 0.98 0.00 0.29 0.38 0.07

Pancevo refinery

6.6 % OC

Industrial 0.96 0.93 0.00 0.28 0.29 0.15

0.99 0.94 0.83 0.95 0.91 0.90

0.98 0.90 0.74 0.90 0.84 0.86

Pancevo Petrochim.

3.0 % OC


0.31 0.25 0.76 0.28 0.30 0.08

0.16 0.16 0.58 0.23 0.31 0.05

Pancevo cityhall

8.4 % OC

Urban 0.10 0.05 0.25 0.13 0.13 0.02

0.19 0.08 0.12 0.23 0.04

0.17 0.21 0.08 0.33 0.02

Novi Sad refinery

5.6 % OC

Industrial 0.12 0.38 0.10 0.35 0.02

0.96 0.94 0.73 0.41 0.65 0.26

0.96 0.94 0.86 0.45 0.83 0.27

Novi Sad Sanghaj

4.1 % OC

Urban 0.91 0.81 0.59 0.41 0.70 0.22

0.82 0.73 0.62 0.48 0.76 0.13

0.80 0.83 0.88 0.52 0.83 0.14

Novi Sad Sport

6.8 % OC

Urban 0.58 0.47 0.59 0.15 0.35 0.06

Fruska Gora 0.68 0.76 0.82 0.70 0.61 0.18

S11


0.74 0.83 0.92 0.66 0.66 0.173.1 % OC

Background 0.31 0.36 0.60 0.48 0.48 0.16

0.98 0.95 0.86 0.23 0.75 0.05

0.98 0.96 1.00 0.16 0.70 0.02

W. Slavonia Poljana

4.4 % OC

Rural 0.87 0.70 0.34 0.04 0.28 0.01

1.00 1.00 1.00 0.99 0.99 0.97

1.00 1.00 1.00 0.99 0.98 0.85

W. Slavonia Gorica

6.9 % OC

Urban 1.00 1.00 1.00 0.97 0.97 0.88

0.90 0.87 0.77 0.70 0.89 0.46

0.89 0.84 0.79 0.64 0.91 0.45

Zagreb MI

8.3 % OC

Urban 0.76 0.59 0.61 0.35 0.70 0.07

0.92 0.66 0.82 0.65 0.91 0.31

0.90 0.58 0.78 0.58 0.92 0.34

Zagreb IRB

6.7 % OC

Urban 0.73 0.26 0.70 0.45 0.81 0.16

0.75 0.64 0.66 0.31 0.59 0.12

0.61 0.46 0.57 0.36 0.58 0.08

Zagreb MS

6.5 % OC

Urban 0.35 0.24 0.49 0.13 0.37 0.04

0.88 0.84 0.81 0.59 0.74 0.29

0.85 0.82 0.79 0.59 0.73 0.21

Zagreb Jak

6.8 % OC

Industrial 0.85 0.78 0.89 0.47 0.70 0.12

0.39 0.44 0.61 0.68 0.60 0.23

0.38 0.40 0.57 0.64 0.55 0.15

Zagreb Dep

7.2 % OC

Urban 0.34 0.26 0.51 0.61 0.49 0.19

0.86 0.60 0.77 0.46 0.43 0.05

0.83 0.47 0.75 0.43 0.27 0.03

Zavizan

7.5 % OC

Background 0.45 0.15 0.57 0.27 0.27 0.03

0.90 0.95 0.98 0.75 0.74 0.27

0.86 0.92 0.97 0.69 0.66 0.15

Zadar transformer

11.7 % OC


0.61 0.53 0.39 0.40 0.67 0.16Zadar Adria

13.3 % OC 0.54 0.41 0.40 0.39 0.65 0.11

S12


Industrial 0.41 0.19 0.31 0.24 0.59 0.10

0.30 0.47 0.83 0.70 0.95 0.24

0.37 0.45 0.86 0.60 0.92 0.13

Zadar HS

8.5 % OC

Urban 0.13 0.14 0.63 0.32 0.78 0.04

0.90 0.96 0.98 0.87 0.89 0.32

0.84 0.93 0.96 0.79 0.84 0.23

Zadar meteo

2.4 % OC

Urban 0.75 0.80 0.97 0.61 0.72 0.17

0.71 0.82 0.86 0.79 0.54

0.73 0.89 0.88 0.84 0.63

Spolana archive

7.6 % OC

Heavily contaminated 0.36 0.79 0.81 0.75 0.56

1.00 0.97 0.97 0.94 0.89

0.89 0.97 0.96 0.93 0.88

Spolana gate

8.9 % OC


0.79 0.87 0.89 0.83 0.60

0.72 0.89 0.88 0.81 0.62

Spolana Libiš

5.2 % OC

Urban 0.00 0.56 0.79 0.79 0.67 0.42

0.88 0.85 0.35

0.85 0.32 0.77 0.09

Praha Libuš

6.4 % OC

Background 0.83 0.21 0.76 0.00 0.00 0.27

0.80 0.96 1.00 0.85 0.53

0.59 0.90 0.61 0.44 0.11

Mokrá Nová pole

2.2 % OC

Industrial 0.73 0.81 0.00 0.87 0.82 0.55

0.74 0.74 0.62 0.66 0.50 0.24

0.73 0.90 0.66 0.66 0.36 0.16

Napajedla

5.4 % OC

Industrial 0.67 0.43 0.44 0.41 0.47 0.19

0.50 0.82 0.82 0.87 0.75 0.55

0.60 0.79 0.81 0.88 0.81 0.72

Otrokovice

4.3 % OC

Industrial 0.34 0.57 0.78 0.81 0.69 0.57

0.39 0.69 0.57 0.64 0.49 0.23

0.50 0.68 0.92 0.96 0.95 0.88

Zlín

7.9 % OC

Industrial 0.35 0.48 0.70 0.80 0.70 0.49

S13


0.76 0.80 0.45 0.47 0.30 0.12

0.52 0.58 0.20 0.29 0.15 0.05

Slušovice

6.2 % OC

Rural 0.58 0.50 0.43 0.62 0.61 0.38

0.71 0.83 0.78 0.86 0.75 0.65

0.71 0.79 0.77 0.83 0.65 0.60

Vizovice

7.3 % OC

Rural 0.47 0.54 0.45 0.77 0.56 0.53

0.59 0.65 0.71 0.64 0.52 0.46

0.57 0.60 0.62 0.60 0.45 0.36

Val.Mez. observatory

6.1 % OC

Urban 0.39 0.26 0.64 0.33 0.21 0.09

0.76 0.72 1.00 0.90 0.83 0.58

0.61 0.77 0.59 0.84 0.64 0.44

Mštěnovice

7.0 % OC

Rural 0.33 0.24 0.45 0.52 0.38 0.21

0.85 0.69 0.53 0.68 0.57 0.34

0.83 0.72 0.25 0.63 0.29 0.22

Příluky

5.9 % OC

Rural 0.21 0.17 0.41 0.40 0.13 0.11

0.78 0.86 0.31 0.62 0.40 0.19

0.66 0.68 0.17 0.39 0.20 0.10

Pláňava

4.4 % OC

Background 0.44 0.28 0.07 0.25 0.05 0.02

0.91 0.53 0.29 0.11

0.73 0.32 0.20 0.05

Košetice

2.0 % OC

Background 0.41 0.31 0.14 0.02

116

117

118

119

120

121

S14

Table S4. Fugacity fractions, ff, for selected OCPs at all sampling sites. Sampling periods July, 122

September and November (average temperature 22 °C, 15 °C, and 5 °C, respectively, for YU, and 19 123

°C, 13 °C, and 4 °C, respectively, for CR).124

Site ff (a-HCH) ff (b-HCH) ff (g-HCH) f(p,p DDE) ff (p,p-DDD) ff(p,pDDT)

0.64 0.01 0.76 0.92 0.63

0.50 0.01 0.71 0.84 0.45

Sarajevo Standard

5.7 % OC

Industrial 0.03 0.30 0.60 0.18

0.84 0.57 0.20

0.69 0.50 0.04

Sarajevo HMI

5.8 % OC

Urban 0.41 0.21 0.03

0.33 0.61 0.01 0.57 0.74 0.62

0.32 0.23 0.01 0.34 0.56 0.37

Sarajevo VW

8.0 % OC

Industrial 0.22 0.05 0.00 0.10 0.27 0.20

0.01 0.29 0.13 0.11

0.12 0.08 0.08

Sarajevo Vlakovo

5.6 % OC

Industrial 0.04 0.02 0.01

0.84 0.69 0.02 0.82 1.00 0.72

0.72 0.61 0.01 0.75 0.70 0.59

Sarajevo Ivansedlo

5.0 % OC

Background 0.61 0.07 0.46 0.38 0.32

0.60 0.37 0.49 0.51

0.73 0.30 0.30 0.46

Tuzla hotel

3.9 % OC

Industrial 0.59 0.05 0.12 0.08

0.64 0.91 0.01 0.70 0.52 0.64

0.39 0.69 0.01 0.54 0.33 0.93

Tuzla fire station

10.1 % OC


0.48 0.01 0.55 0.58 0.44

0.48 0.26 0.39 0.41

Tuzla mine

8.5 % OC

Urban 0.01 0.06 0.16 0.02

0.77 0.01 0.62 0.77 0.37

0.71 0.01 0.59 0.62 0.25

Tuzla meteo

5.1 % OC

Urban 0.03 0.20 0.32 0.03

S15


0.01 0.80 0.89 0.63

0.01 0.62 0.67 0.27

Tuzla Bukyne

3.6 % OC


0.82 0.82 0.11

0.76 1.00 0.07

Kragujevac Zastava

8.1 % OC


0.20 0.93 0.01 0.65 0.37 0.25

0.18 0.90 0.43 0.34 0.34

Kragujevac FN

9.7 % OC


0.55 0.61 0.16

0.29 0.42 0.14

Kragujevac UNI

7.5 % OC

Urban 0.09 0.11 0.10

0.54 0.01 0.19 0.18

0.51 0.10 0.23

Pancevo refinery

6.6 % OC


0.98 0.02 0.44 0.57

0.93 0.01 0.13 0.21

Pancevo Petrochim.

3.0 % OC

Heavily contaminated 0.73 0.01 0.06

0.46 0.64 0.89 0.23

0.32 0.54 0.65 0.22

Pancevo cityhall

8.4 % OC

Urban 0.15 0.15 0.19 0.09

0.01 0.02 0.01

0.01 0.01 0.02

Novi Sad refinery

5.6 % OC


0.53 0.19 0.49 0.14

0.41 0.18 0.61 0.29

Novi Sad Sanghaj

4.1 % OC

Urban 0.24 0.04 0.37 0.09

0.32 0.25 0.20

0.31 0.17 0.26

Novi Sad Sport

6.8 % OC

Urban 0.04 0.04 0.01

Fruska Gora 0.41 0.75 0.13

S16


0.40 0.71 0.103.1 % OC

Background 0.05 0.39 0.02

0.01 0.60 0.40 0.00

0.50 1.00 0.00

W. Slavonia Poljana

4.4 % OC

Rural 0.12 0.11 0.00

0.03 0.00 0.94

0.01 0.00 0.86

W. Slavonia Gorica

6.9 % OC

Urban 0.00 0.54

0.69 0.86 0.76 0.80 0.61

0.55 0.31 0.63 1.00 0.49

Zagreb MI

8.3 % OC

Urban 0.35 0.08 0.29 0.39 0.19

0.70 0.02 0.46 0.27 0.41

0.57 0.02 0.22 1.00 0.16

Zagreb IRB

6.7 % OC

Urban 0.32 0.08 0.03 0.07

0.69 0.83 0.56

0.55 0.84 0.38

Zagreb MS

6.5 % OC

Urban 0.20 0.58 0.14

0.22 0.17 0.14 0.04

0.10 0.10 0.13 0.02

Zagreb Jak

6.8 % OC

Industrial 0.06 0.03 0.07 0.01

0.31 0.51 0.02 0.63 0.77 0.32

0.27 0.21 0.01 0.51 0.67 0.21

Zagreb Dep

7.2 % OC

Urban 0.06 0.30 0.18 0.34 0.10

0.46 0.57 0.26 0.24 0.08

0.29 0.28 0.09 0.06 0.02

Zavizan

7.5 % OC

Background 0.45 0.02 0.06 0.05 0.02

0.60 0.34 0.01 0.60 0.00 0.00

0.45 0.14 0.01 0.36 0.00 0.00

Zadar transformer

11.7 % OC


0.13 0.27 0.14Zadar Adria

13.3 % OC 0.06 0.24 0.08

S17



0.44 0.81 0.46 0.23

1.00 0.60 0.26 0.12

Zadar HS

8.5 % OC

Urban 0.16 0.42 0.14 0.12

0.02 0.47 0.46 0.13

0.01 0.27 0.24 0.04

Zadar meteo

2.4 % OC

Urban 0.01 0.12 0.23 0.05

0.96 0.94 0.05 0.94 0.75 0.89

0.99 0.96 0.09 0.92 0.85 0.91

Spolana archive

7.6 % OC


1.00 1.00 0.27 0.97 0.90 0.96

0.99 1.00 0.26 0.95 0.88 0.95

Spolana gate

8.9 % OC


0.99 0.96 0.10 0.98 0.91 0.94

0.98 0.84 0.04 0.95 0.92 0.90

Spolana Libiš

5.2 % OC

Urban 0.95 0.63 0.02 0.86 0.81 0.77

0.98 0.93 0.04 0.48 0.12 0.16

0.96 0.53 0.02 0.20 0.03 0.07

Praha Libuš

6.4 % OC

Background 0.94 0.39 0.01 0.11 0.01 0.04

0.86 0.05 1.00 0.99 1.00

0.75 0.03 1.00 0.99 0.99

Mokrá Nová pole

2.2 % OC

Industrial 0.57 0.01 0.99 0.99 0.99

0.99 1.00 0.04 0.63 0.22 0.22

0.97 1.00 0.02 0.33 0.12 0.10

Napajedla

5.4 % OC

Industrial 0.93 0.14 0.00 0.12 0.11 0.05

0.90 0.88 0.02 0.51 0.13 0.35

0.87 0.39 0.01 0.27 0.07 0.36

Otrokovice

4.3 % OC

Industrial 0.66 0.15 0.00 0.09 1.00 0.11

0.91 0.95 0.03 0.66 0.38 0.43

0.84 0.38 0.02 0.62 0.67 0.86

Zlín

7.9 % OC

Industrial 0.70 0.22 0.00 0.25 0.28 0.25

S18


1.00 0.88 0.16 0.78 0.24 0.22

1.00 0.26 0.04 0.31 0.06 0.13

Slušovice

6.2 % OC

Rural 1.00 0.21 0.02 0.26 1.00 0.14

0.86 1.00 0.03 0.87 0.52 0.68

0.75 0.44 0.02 0.74 0.56 0.64

Vizovice

7.3 % OC

Rural 0.54 0.13 0.00 0.41 1.00 0.20

0.77 1.00 0.03 0.24 0.15

0.56 0.15 0.01 0.09 0.07

Val.Mez. observatory

6.1 % OC

Urban 0.33 0.03 0.00 0.03 0.02

0.90 1.00 0.03 0.73 1.00 0.33

0.78 0.15 0.01 0.53 1.00 0.16

Mštěnovice

7.0 % OC

Rural 0.50 0.03 0.00 0.15 1.00 0.06

0.96 0.87 0.04 0.89 1.00 1.00

0.93 0.19 0.01 0.72 1.00 0.33

Příluky

5.9 % OC

Rural 0.58 0.01 0.00 0.29 1.00 0.08

1.00 0.88 0.14 0.94 0.94 0.94

1.00 1.00 0.03 0.70 0.80 0.87

Pláňava

4.4 % OC

Background 0.99 0.24 0.01 0.36 1.00 0.24

0.02 0.58 0.50 0.17

0.01 0.22 0.37 0.16

Košetice

2.0 % OC

Background 0.07 0.01 0.03

125

126

127

128

S19

PC

B 2

8

PC

B 5

2

PC

B 1

01

PC

B 1

53

PC

B 1

38

PC

B 1

80

a H

CH

b H

CH

g H

CH

DD

E

DD

D

DD

T

-0,2-0,10,00,10,20,30,40,50,60,70,80,91,01,11,2

f f

Median 25%-75% Non-Outlier Range Outliers Extremes

129

130

Figure S1. Ranges of fugacity fractions, ff, of selected PCBs and OCPs measured at 47 sampling sites in 131

Central and Southern Europe between July and December, 2005 in 5 sampling periods, 28 days each 132

(outlier coefficient o.c. is equal to 1.5).133

Organic carbon content (%)

f f

M: July

M: November

0 2 4 6 8 10 12 140,00,10,20,30,40,50,60,70,80,91,01,11,2

f f

M: July

0 2 4 6 8 10 12 140,00,10,20,30,40,50,60,70,80,91,01,11,2

M: September

0 2 4 6 8 10 12 14

1,01,11,2

f f

Organic carbon content (%)

α HCH

134M: July OC: α HCH: r2 = 0,1605; r = -0,4006, p = 0,0346; y = 1,04228547 - 0,0446356005*x135M: September OC: α HCH: r2 = 0,2139; r = -0,4625, p = 0,0132; y = 1,05811288 - 0,0574058548*x136M: November OC: α HCH: r2 = 0,1355; r = -0,3682, p = 0,0539; y = 0,882533503 - 0,0506535619*x137

138

Figure S2. Correlation between the α-HCH fugacity fraction, ff, and organic carbon content (%) in the 139

top soil for all sampling sites.140

S20

141

Table S5. Correlation between the fugacity fraction, ff, and the organic carbon content in the top soil (%) 142

for the selection of compounds and various groups of the sampling sites143

All sites Hot spots Hot spots excluded

Hot spots and industry excluded

PCB 28 -0,212 (n=129) 0,972 (n=12) -0,251 (n=117) -0,262 (n=57)PCB 52 -0,245 (n=136) 0,599 (n=17) -0,412 (n=119) -0,499 (n=62)PCB 101 0,025 (n=135) 0,542 (n=18) -0,129 (n=117) -0,239 (n=60)PCB 153 0,046 (n=139) 0,066 (n=18) -0,123 (n=121) -0,210 (n=61)PCB 138 0,162 (n=139) 0,147 (n=18) 0,069 (n=121) -0,143 (n=61)PCB 180 0,078 (n=141) 0,053 (n=18) -0,064 (n=123) -0,110 (n=63)a HCH -0,371 (n=84) -0,578 (n=15) -0,429 (n=69) -0,337 (n=39)b HCH 0,007 (n=81) -0,630 (n=18) -0,174 (n=63) -0,183 (n=36)g HCH -0,033 (n=75) -0,749 (n=11) -0,139 (n=64) -0,035 (n=37)DDE 0,054 (n=141) -0,737 (n=18) -0,093 (n=123) -0,036 (n=63)DDD -0,123 (n=126) -0,854 (n=15) -0,087 (n=111) -0,082 (n=60)DDT 0,041 (n=141) -0,443 (n=18) -0,001 (n=123) -0,065 (n=63)

144red mark - Statistically significant Spearman rank correlation Rho (P<0.05)145

146

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