lable at ScienceDirect

Atmospheric Environment 43 (2009) 1730–1736

Contents lists avai

Atmospheric Environment

journal homepage: www.elsevier .com/locate/a tmosenv

Identifying source regions for the atmospheric input of PCDD/Fs to the Baltic Sea

Ulla Sellstrom*, Anna-Lena Egeback, Michael S. McLachlanDepartment of Applied Environmental Science (ITM), Stockholm University, SE-106 91 Stockholm, Sweden

a r t i c l e i n f o

Article history:Received 17 September 2008Received in revised form4 December 2008Accepted 8 December 2008

Keywords:PCDD/FBaltic SeaMonitoringAmbient airTrajectory

* Corresponding author. Tel.: þ46 8 674 7181; fax:E-mail address: ulla.sellstrom@itm.su.se (U. Sellstr

1352-2310/$ – see front matter � 2008 Elsevier Ltd.doi:10.1016/j.atmosenv.2008.12.014

a b s t r a c t

PCDD/F contamination of the Baltic Sea has resulted in the European Union imposing restrictions on themarketing of several fish species. Atmospheric deposition is the major source of PCDD/Fs to the BalticSea, and hence there is a need to identify the source regions of the PCDD/Fs in ambient air over the BalticSea. A novel monitoring strategy was employed to address this question. During the winter of 2006–2007air samples were collected in Aspvreten (southern Sweden) and Pallas (northern Finland). Shortsampling times (24 h) were employed and only samples with stable air mass back trajectories wereselected for analysis of the 2,3,7,8-substituted PCDD/F congeners. The range in the PCDD/F concentrationsfrom 40 samples collected at Aspvreten was a factor of almost 50 (range 0.6–29 fg TEQ/m3). When thesamples were grouped according to air mass origin into seven compass sectors, the variability was muchlower (typically less than a factor of 3). This indicates that air mass origin was the primary source of thevariability. The contribution of each sector to the PCDD/F contamination over the Baltic Sea during thewinter half year of 2006/2007 was calculated from the average PCDD/F concentration for each sector andthe frequency with which the air over the Baltic Sea came from that sector. Air masses originating fromthe south–southwest, south–southeast and east segments contributed 65% of the PCDDs and 75% of thePCDFs. Strong correlations were obtained between the concentrations of most of the PCDD/F congenersand the concentration of soot. These correlations can be used to predict the PCDD/F concentrationsduring the winter half year from inexpensive soot measurements.

� 2008 Elsevier Ltd. All rights reserved.

1. Introduction

The Baltic Sea ecosystem is contaminated with polychlorinateddibenzo-p-dioxins and dibenzofurans (PCDD/Fs). The concentra-tions of these chemicals in many of the commercially harvested fishfrom the Baltic Sea exceed the limits for dioxins and dioxin-likecompounds in food set by the Commission of the EuropeanCommunities (2006). As a result, the European Commission hasplaced restrictions on the marketing of fish from the Baltic Sea.

The sources of the PCDD/Fs in the Baltic Sea are not yet fullyunderstood. The pulp and paper industry and wood preservativesare suspected to have made a significant historical contribution.However, analysis of the PCDD/F congener patterns in Baltic Seasediments indicates that the impacts of these sources have beenlargely local, while atmospheric deposition is responsible for thebulk of the PCDD/Fs that have accumulated in the Baltic Sea (Rappeet al., 1989; Verta et al., 2007). This conclusion is supported by massbalance modeling of PCDD/Fs to the Baltic Sea (Armitage et al.,2008). Thus, a good understanding of the concentrations and

þ46 8 674 7637.om).

All rights reserved.

sources of PCDD/Fs in the atmosphere is necessary in order todevelop strategies to reduce the contamination of the Baltic Seaecosystem.

To date, few measurements have been made of PCDD/Fs in air inthe Baltic region (Broman et al., 1991; Egeback et al., 1991; Tysklindet al., 1993; McLachlan et al., 1998; Hovmand et al., 2007; SwedishDioxin Survey Database, 2008). PCDD/F concentrations have beenshown to have a pronounced seasonality, with average levelsduring the coldest winter months that are more than an order ofmagnitude greater than during the summer (McLachlan et al., 1998;Hovmand et al., 2007). A similar, albeit not quite as pronouncedseasonality in bulk deposition of PCDD/Fs was observed in the samestudies. Furthermore, analysis of 14 samples from southernSweden, each collected over 3–5 days, and 20 samples from theSwedish island of Gotland, each collected over 2 days, providedstrong indications that air mass origin plays an important role indetermining the magnitude of the PCDD/F concentrations and thecongener pattern (Egeback et al., 1991; Tysklind et al., 1993;Swedish Dioxin Survey Database, 2008). A strong influence of airmass origin on PCDD/F concentrations in air has also been observedin other areas (Lohmann et al., 1999). This hypothesis is supportedby atmospheric dispersion and fate modeling of PCDD/Fs conductby the EMEP modeling center (EMEP/MSC-E), which predicts

U. Sellstrom et al. / Atmospheric Environment 43 (2009) 1730–1736 1731

strong gradients in average PCDD/F concentrations in air aroundthe Baltic Sea (Gusev et al., 2008). The EMEP/MSC-E modeling workdoes provide some insight into the potential source regions ofPCDD/Fs to the Baltic Sea. However, this tool is dependent onemissions estimates provided by the EMEP member states, whichare unreliable and often not produced in a consistent manner.Hence, there is a need for empirical studies to aid in identifying themajor source regions.

The goal of this study was to improve understanding of thecurrent PCDD/F concentrations in air around the Baltic Sea and toidentify their major source regions. One methodological approachfor identifying source regions of atmospheric contaminants thathas found widespread use in recent years is post-measurementinterpretation using air mass back trajectory. Egeback et al. (1991)and Tysklind et al. (1993) applied it in their exploratory work onPCDD/F levels in the Baltic Sea, and it has been used successfully inaddressing relatively simple questions, for instance in demon-strating that toxaphene was being transported to the Great Lakesfrom the south rather than the north (James and Hites, 2002).However, in less qualitative or more complex situations, air massback trajectory analysis is hampered by difficulties in assigning airmass origins to the samples (Hafner and Hites, 2005). It is commonfor air mass trajectories to have changed significantly during thesampling period, either because the weather systems were movingrapidly or because the sampling period was too long. In this studywe took a different approach, combining short sampling times withpre-measurement screening of the samples to identify those thathad a stable air mass origin over the whole sampling period. Onlythese samples were analysed for PCDD/Fs, providing a datasetcontaining clear air mass origin information.

2. Materials and methods

2.1. Samples

Air samples were collected at two locations, both well estab-lished atmospheric monitoring stations, located about 1000 kmapart (Fig. 1). Aspvreten is located to the south of Stockholm,Sweden, and Pallas is located in northern Finland close to theSwedish border. Both of these sites are remote and should not beinfluenced by local sources. Since PCDD/Fs are subject to long-rangeatmospheric transport, it is not important that the stations belocated on the Baltic Sea itself. Pallas gives information on airmasses impacting the northern part of the Baltic Sea (i.e. theBothnian Bay), while the results from Aspvreten are more directlyapplicable to deposition to the central and southern Baltic Sea.

Using back trajectories to identify contaminant source regionsis hampered by the dynamics of atmospheric circulation, whichfrequently results in rapidly changing back trajectories. This wasaccounted for in the sampling strategy, using a short samplingtime of 24 h. Sampling was conducted during the winter season2006–2007, as studies in Denmark and Germany have demon-strated a clear seasonality in ambient air levels of PCDD/Fs, withlevels during the coldest month that were typically one order ofmagnitude higher than during the warmest month (McLachlanet al., 1998; Hovmand et al., 2007). Since the particle bound fractionwas expected to make the greatest contribution to the PCDD/Fflux to the Baltic Sea, a greater emphasis was placed on analyzingthis fraction.

As the air masses coming from the south were expected to bethe source of the large majority of the PCDD/Fs to the Baltic Sea,a greater emphasis was put on analyzing samples from Aspvreten.In Aspvreten, four HiVol samplers were run almost continuously,one after the other, from mid October 2006 to mid April 2007.The samplers, which employed an inverted sampling head with

a glass fiber filter (MG 160, 293 mm diameter, Munktell, Sweden) tocollect the PCDD/Fs associated with atmospheric particles, and twopolyurethane foam plugs (PUFs, 78 � 75 mm, r ¼ 22–25 kg/m3, DPSunde, Norway) in series, to collect the PCDD/Fs in gaseous form,were operated at w30 m3 h�1. The station was visited twice a weekto change the sampling materials and check sampler performance.Field blanks were obtained using an extra HiVol sampler loadedwith PUFs and a filter and left for a whole week without airsampling. In Pallas the sampling capacity was lower with two HiVolsamplers from Nov 2006 to mid April 2007. These samplers wereturned on and off with a remote control according to the backtrajectory forecasts, with prolonged sampling time when the windconditions were very stable. Field blanks from Pallas were obtainedfrom the two HiVol samplers after the exposure of PUFs and filter toambient air for 7–13 days without air sampling.

The glass fiber filters were pre-baked at 450 �C for 24 h, and thePUFs pre-cleaned with toluene in an accelerated solvent extractor(three cycles, temperature 100 �C, pressure 100 bars, cell size100 ml) before use. The sample volume was measured with a flowmeter for air, calibrated for atmospheric pressure and a workingtemperature of 10 �C, and was corrected for the average outdoortemperature during the sampling period.

Only samples with stable air mass back trajectories duringthe 24 h sampling period were selected for analysis. The backtrajectories (96 h) were produced with the NOAA HYSPLIT model(http://www.arl.noaa.gov/ready.html) at three different heights(20, 100 and 500 m). Of the samples with stable back trajectories,a sub-set was selected to give good representation of different airmass origin. The air mass origin was categorized using severalcompass sectors (Fig. 1). Air from the north–northwest (NNW)sector had passed over northern Sweden/Norway/Greenland andSvalbard, while air from the northwest (NW) sector had passedover southern Norway/Greenland and Iceland. Air from thesouthwest (SW) compass sector had passed over the British Isles,while the south–southwest (SSW) sector covered western Europeexcept the British Isles. The boundary between the NW and SWcompass sectors was drawn through Scotland as many years ofatmospheric particle measurements at Aspvreten have shown thatthis represents a dividing line between the more polluted air to thesouth and the cleaner air to the north (HC Hansson, ITM, StockholmUniversity, personal communication). Air from easterly directionswas divided into three compass sectors: south–southeast (SSE)for air that had passed over eastern Europe, east (E) covering themajor part of the former Soviet Union, and north–northeast(NNE) for air that had passed over Finland and northern Russiaincluding the Kola Peninsula.

In total, 60 different air samples were analyzed, 45 fromAspvreten and 15 from Pallas (Tables S1–S4 in the SupplementaryMaterials). The particle bound fraction was analyzed in all ofthe samples and the gaseous fraction was analyzed in 36 of them.The aim was to select about the same number of samples from eachsector, but due to prevailing meteorological conditions during thesampling campaign this was not possible.

2.2. Analysis

The analyses were performed at a German commercial labora-tory (Okometric GmbH), accredited for the analysis of PCDD/Fsaccording to DIN EN ISO/IEC 17025:2005. In brief, the sampleswere extracted using pressurized fluid extraction (Dionex modelASE 300) employing the following parameters: solvent toluene,temperature 125 �C (filters) or 100 �C (PUFs), pressure 100 bar,three static cycles of 5 min each. A suite of 13C-labeled PCDD/Fs wasadded after the extraction. The extracts were cleaned up on a mixedsilica column (successive layers of H2SO4/silica gel, silica gel, and

Fig. 1. Location of the field stations at Aspvreten (58�800N, 17�400E), Sweden, and Pallas (68�000N, 24�140E), Finland. Dashed lines indicate the compass sector division applied whengrouping samples due to air mass origin (the labels of the sectors for Pallas given in brackets, see also Fig. S1 in Supplementary Materials). The locations used for estimation of winddirection frequencies over the Baltic Sea are indicated with a star: (57�100N, 19�000E) for the southern and central parts, (64�800N, 23�000E) for the Bothnian Bay.

Gas phaseParticle phase

fg T

EQ

/m3

< <<<

<05

10

1520

25

3035

Nov

1, 2

006

Apr

1, 2

007

Mar

1, 2

007

Feb

1, 2

007

Jan

1, 2

007

Dec

1, 2

006

* *

Fig. 2. Total PCDD/F concentrations (fg WHO-TEQ/m3) in air samples from Aspvreten.Concentrations in the gas phase (when analyzed) were added on top of the concen-trations in the particle phase. < and * means that all congeners were below thedetection limit (gas and particle phase, respectively).The X-axis is a time scale and thesamples are arranged in the order that they were sampled.

U. Sellstrom et al. / Atmospheric Environment 43 (2009) 1730–17361732

NaOH/silica gel). They were then fractionated on an aluminumoxide column which separated PCBs and other non-polar constit-uents (first fraction) from the PCDD/Fs (second fraction). Theanalysis was conducted on a MAT 90/95 sector field high resolutionmass spectrometer coupled to a Varian 3400 gas chromatograph,which was equipped with a Gerstel cold injection system and a DBDioxin column (30 m, 0.25 mm i.d., and 0.15 mm film thickness).

2.3. QA/QC

Six field blanks from Aspvreten and three from Pallas wereanalyzed. The field blanks (both filters and PUFs) were handled thesame way as the sample materials for the real samples, exceptfor the sampling itself. The sample identities (field blank or airsample) were not known to the analytical laboratory. Filters andPUFs were always analyzed separately. The recoveries of theinternal standards were always within the method specifications(60–120%). Only a few PCDD/F congeners were present in the fieldblanks, and mostly at levels close to the detection limits (1,2,3,6,7,8-HxCDD, one filter, one PUF, Aspvreten; TCDF, one filter, one PUF,Aspvreten and two PUFs, Pallas; 1,2,3,4,6,7,8-HpCDF and OCDF, twoPUFs, Aspvreten; 1,2,3,4,6,7,8-HpCDD, five/six filters and PUFs,Aspvreten). OCDD was present in similar amounts in all field blanksamples, both filters and PUFs. No correlation was found betweenlevels in field blanks and time of exposure to ambient air (Pallas)or sample location (Pallas/Aspvreten).

The limits of quantification (LOQ) were set to three timesthe signal to noise (S/N) ratio, or, if the analyte was present inthe field blanks, to the average blank value plus three times thestandard deviation. Samples above this value were blank correctedusing the mean field blanks.

The 2,3,7,8-TCDD toxicity equivalents (TEQs) were calculatedusing the WHO 2005 toxicity equivalency factors (van denBerg et al., 2006). The calculation of TEQs is problematic when theconcentrations of some congeners are below the LOQ. To circum-vent this problem, missing values were estimated based on theassumption of congener pattern similarity between the air samples.The missing value was calculated with respected to the most

similar quantified congener in the same sample (e.g. 2,3,7,8-TCDDusing 1,2,3,7,8-PeCDD), employing the average ratio of theconcentrations of these congeners from other similar samples inwhich the two congeners had been quantified. When an estimatedvalue was higher than the LOQ, the latter was considered as thebest estimate. When most of the congeners in a sample were belowthe LOQ, the procedure was not employed and the sample was notincluded in the data interpretation. Although this estimationprocedure is fraught with uncertainty, it was judged to be superiorto the more commonly used approaches of replacing missingvalues by either zero or half the limit of quantification, which iscompletely arbitrary. In Table S5 (Supplementary Materials) thepercentage of estimated data for each congener is shown.

3. Results and discussion

The concentrations of all measured congeners in the filtersand PUFs from Aspvreten and Pallas are given in Tables S1–S4 in theSupplementary Materials, together with sampling date, sampledair volume, average temperature, precipitation and average sootconcentration.

U. Sellstrom et al. / Atmospheric Environment 43 (2009) 1730–1736 1733

The average concentration (filter þ PUF) measured in this study(w10 fg TEQ m�3) is almost identical to what was found in wintersamples collected in 1990–1993 (11 samples) at the Swedish islandof Gotland in the Baltic Sea (Swedish Dioxin Survey Database,2008). This is somewhat lower than what was been reported forother air samples collected in winter in this region (45 fg TEQ m�3

in three samples from 1989 (Tysklind et al., 1993), 33 fg TEQ m�3 insix samples from 1995/96 (McLachlan et al., 1998), w40 fg TEQ m�3

in 11 samples from 2002/03 (Hovmand et al., 2007)). The lowerlevels may be a consequence of Aspvreten and Gotland being moreremote from the major industrial centers in Europe than thesampling stations used in the other studies and hence havinga lower frequency of exposure to air masses that have passed over

2. SSW

6. NNW

7. NW

1. SW

*

A

2. SSW

6. NNW

7. NW

1. SW

B

*

Fig. 3. Concentrations of PCDDs and PCDFs in air from Aspvreten, grouped according to air mmarked #. a) Particle phase, b) gas phase.

the major source areas (see below). The congener patternsobserved in this work were generally consistent with the earliermeasurements. The particle/gas partitioning of the PCDD/Fs wasalso similar to what has been reported earlier (Eitzer and Hites,1989; Hippelein et al., 1996), namely increasing gaseous fractionswith decreasing chlorine number and increasing ambienttemperature.

A salient feature of the dataset is the day to day variation inthe atmospheric concentrations of PCDD/Fs in Aspvreten (Fig. 2).The bars show the total PCDD/F-TEQ concentrations in the filterfraction, with the PUF fraction (when analyzed), added on top. Mostof the PCDD/Fs were associated with particles – as was expectedduring the cold season of the year (Hippelein et al., 1996).

3. SSE

5. NNE

4. E

PCDD-TEQ PCDF-TEQ

0

5

10

15

20

(fg/m3)

(fg/m3)

#

*

#

3. SSE

5. NNE

4. E

PCDD-TEQ PCDF-TEQ

0

0.5

1

1.5

2

2.5

3

#*

#

ass origin. Summer samples are marked *, and winter samples taken 1 year earlier are

-1.0

-0.5

1.0

-1.5 -1.0 -0.50.0

0.5

PCDDs (r2=0.68)

log

WH

O-T

EQ

(fg

/m3 )

0.5

1.0

-1.0

-1.0

-0.5

1.5

-1.5 -1.0 -0.5

0.0

0.0

0.5

PCDFs (r2=0.79)

-0.5

0.5

1.5

-1.5 -1.0 -0.5 0.5

PCDD/Fs (r2=0.79)

log soot concentration (µg/m3)

Fig. 4. Correlations between concentrations of PCDDs and PCDFs and concentrations ofsoot in air from Aspvreten (particle phase).

U. Sellstrom et al. / Atmospheric Environment 43 (2009) 1730–17361734

In Fig. 3 the samples are grouped according to the compasssector through which the air mass primarily passed before reachingthe sampling station. The variability in particle phase concentra-tions was much lower within a sector than it was between thesectors (Fig. 3a). The highest concentrations were found in samplesthat had passed over the European continent (SSW, SSE and E). Inair that had passed over the British Isles and air from northerlydirections (SW, NW, NNW and NNE), the concentrations were low.

A few winter samples taken 1 year earlier were also analyzed(marked with #) and had similar TEQ levels to the samples fromthis year. This could indicate fairly similar year-to-year seasonalconcentrations. Two air samples from the summer of 2006 (markedwith *) had lower TEQ levels than the winter samples from thesame sector. This was expected, since there is a strong seasonalcomponent to the variations in PCDD/F concentration in air innorthern Europe, with much lower levels during the summer(Konig et al., 1993; Hippelein et al., 1996).

The proportion of PCDF-TEQs to PCDD-TEQs was higher in airfrom the SSW, SSE, E and NNE sectors, while in the air from westerlydirections the proportion of PCDD-TEQs was higher (Fig. 3a).Differences in congener patterns depending on the air mass originwere also observed by Egeback et al. (1991) and Tysklind et al.(1993). Since only three of the 14 samples reported in (Tysklindet al., 1993) were collected during the winter, it is difficult to makecomparisons. However, they did report an increased dominance ofOCDD in samples with low concentrations, which is consistent withour observations (see Table S1, Supplementary Materials).

For the gaseous phase the directional trends were not as clearas for the particle phase (Fig. 3b). The concentrations were moresimilar between the transects. The difference in the directionaltrends between Figs. 3a,b is partially due to the higher sootconcentrations in the SSW, SE and E sectors (see Table S2,Supplementary Materials), which resulted in higher PCDD/Fconcentrations in the particle fraction of the air samples fromthose sectors. Temperature is another factor that could influencethe directional trends, as lower temperatures result in a smallerfraction of the PCDD/Fs partitioned into the gas phase. Lowertemperatures were observed in several of the samples from the Esector, but this effect was compensated by lower soot concentra-tions. It is important to note that the fraction of the PCDD/Fs in thegas phase was small and that the total PCDD/F concentrations inair therefore show the same directionality as the particle phaseconcentrations.

The concentrations in Aspvreten were higher than in Pallas,regardless of air mass origin. Fig. S1 (Supplementary Materials)shows the estimated average PCDD/F-TEQs in air from differentcompass sectors. Higher concentrations in Aspvreten, also in aircoming from the north, indicate a net addition of PCDD/Fs to theair as it travels from north to south over Scandinavia. There are,however, uncertainties, especially due to the few samples from forthe northeast in Aspvreten and Pallas.

The contribution of each compass sector to the PCDDs andPDCFs present in the air over the Baltic Sea during the 6 monthsampling period was estimated by multiplying the averageconcentrations for each sector by the frequency with which the airoriginated from that sector. The wind frequencies were estimatedby studying wind back trajectories (72 h) at three different heights(20, 100 and 500 m), every 8 h for the whole sampling campaign.Because the air circulation over the northernmost part differs fromthat over the rest of the Baltic Sea (HC Hansson, ITM, StockholmUniversity, Sweden, personal communication), this was done fortwo locations (Fig. 1). The average concentrations for each sector,the air mass frequency for each sector, and the estimated averagedconcentrations (sum of each sector’s contribution) over the BalticSea are listed in Tables S6 and S7 (Supplementary Materials).

The relative contributions of each compass sector to theestimated averaged particle phase PCDD- and PCDF-TEQ concen-trations over the southern Baltic Sea are shown in Fig. S2a in theSupplementary Materials. The large majority originates from theEuropean continent and the former Soviet Union (SSW, SSE and Esectors). The SSW sector contributes about 25% of both PCDD-and PCDF-TEQs. The SSE and E sectors each contribute a little less(20%) of the PCDD-TEQs but about the same fraction (25%) ofthe PCDF-TEQs. The SW and NW sectors together contribute about25% of the PCDD-TEQs and less than 15% of the PCDF-TEQs. Littleoriginates from the northern sectors (NNW and NNE).

The gas phase contributions were more evenly distributedamong the sectors (Fig. S2b, Supplementary Materials). Thereis however considerable uncertainty in the contribution fromthe SW, NW, NNW and NNE sectors due to the small number ofdata points for these sectors.

The results from this study clearly indicate that the levels ofPCDD/Fs in the air over the Baltic Sea are determined by the sourcesof the air masses. As these can vary from one year to another, theresults from this study might not be representative for periods withdifferent wind conditions. In order to better be able to extrapolatethe results from this study in space and time, correlations betweenthe PCDD/F concentrations and the concentrations of a routinelydetermined atmospheric parameter, soot, were explored. A strongcorrelation was found for the particle bound PCDDs and PCDFs(Fig. 4). An explanation for this correlation is that both soot andPCDD/Fs are primarily formed during combustion. Generally,

Table 1Parameters from the linear regression of the logarithm of the concentrations ofPCDD and PCDF congeners in the particle phase against the logarithm of theconcentrations of soot in air from Aspvreten.

Slope Intercept r2

2,3,7,8-TCDD 0.63 �0.72 0.481,2,3,7,8-PeCDD 0.80 0.11 0.731,2,3,4,7,8-HxCDD 0.69 �0.79 0.601,2,3,6,7,8-HxCDD 0.79 �0.29 0.661,2,3,7,8,9-HxCDD 0.79 �0.44 0.631,2,3,4,6,7,8-HpCDD 0.62 �0.37 0.45OCDD 0.52 �1.6 0.342,3,7,8-TCDF 0.94 �0.60 0.721,2,3,7,8-PeCDF 1.0 �0.98 0.752,3,4,7,8-PeCDF 0.99 0.27 0.741,2,3,4,7,8-HxCDF 1.1 �0.10 0.781,2,3,6,7,8-HxCDF 1.1 �0.077 0.761,2,3,7,8,9-HxCDF 1.1 �0.97 0.802,3,4,6,7,8-HxCDF 1.2 0.006 0.781,2,3,4,6,7,8-HpCDF 1.1 �0.44 0.841,2,3,4,7,8,9-HpCDF 1.1 �1.4 0.86OCDF 1.0 �2.1 0.84

Number of samples ¼ 38.

U. Sellstrom et al. / Atmospheric Environment 43 (2009) 1730–1736 1735

the correlations were higher for the PCDFs (r2 ¼ 0.72–0.86 forthe individual congeners) than for the PCDDs (r2 ¼ 0.34–0.73)(Table 1 and Fig. S3 (Supplementary Materials)). HpCDD and OCDDcorrelated to a lesser extent (r2 ¼ 0.45 and 0.34, respectively).The correlations for TCDD and 1,2,3,4,7,8-HxCDD were also fairlylow (r2 ¼ 0.48 and 0.60, respectively), whereby most of the TCDDdata used were estimates as only in a few air samples were themeasured concentrations above detection limit (Table S5, Supple-mentary Materials). For the other congeners it is possible to esti-mate the concentrations with fairly high accuracy using soot data.Note that the most reliable correlations are likely those forcongeners that had a low percentage of estimated values (Table S5).

The correlation of the total PCDD/F concentrations (particlebound and gaseous) with the soot concentrations was also evalu-ated. The sample size was smaller, as the gas phase was notanalyzed for all samples. The correlation coefficients were similarto those between soot and the particle bound PCDD/F only (seeTable S8, Supplementary Materials). Exceptions to this were TCDDand TCDF for which the correlation with particle phase only washigher (r2 ¼ 0.54 and 0.76, respectively) than with the total airconcentrations (r2 ¼ 0.25 and 0.53, respectively).

Other authors have reported a relationship between PCDD/Fconcentrations and the levels of inorganic pollutants. On the basisof a principle component analysis, Tysklind et al. (1993) found thathigher PCDD/F concentrations were associated with higher levels ofSO2, NO2, NO3

�, and soot. Hovmand et al. (2007) reported a goodcorrelation between PCDD/F concentrations and SO2 þ SO4 inwinter samples (r2 ¼ 0.81). In summer samples, however, nocorrelation was observed. Thus there is considerable evidence thatPCDD/F concentrations in the Baltic region can, at least in winter, bepredicted from other parameters which are frequently availableand much less expensive to determine.

4. Conclusions

In conclusion, the methodology employed in this study, namelypre-measurement screening of the samples to identify those thathad a stable air mass origin, proved to be very successful. It couldpotentially be used in contaminant monitoring programs forsubstances for which air mass origin is a principle determinant ofconcentration to generate data with greater information content atless cost. Data collected in this manner should be particularly usefulfor evaluating atmospheric dispersion and fate models to check

the correctness of their algorithms and emissions estimates. Thiswould be a logical next step in identifying the sources of PCDD/Finput to the Baltic Sea.

Acknowledgements

We thank Hans Karlsson (ITM) for assistance with sampling atAspvreten and Peter Tunved (ITM) for helping with the calculationof the back trajectories. We are particularly grateful to Jussi Paateroand Juha Hatakka at the Finnish Meteorological Institute, andEveliina Paakkola and Ahti Ovaskainen at the Finnish ForestResearch Institute for their generous help with sampling in Pallas.Stimulating discussions with Hans-Christen Hansson (ITM) werevery useful in planning the project. This work was financed by theSwedish Environmental Protection Agency under the guidance ofNiklas Johansson.

Appendix A. Supplemental material

Supplementary information for this manuscript can be down-loaded at doi:10.1016/j.atmosenv.2008.12.014.

References

Armitage, J.M., McLachlan, M.S., Wiberg, K., Jonsson, P., 2008. A model assessmentof dibenzo-p-dioxin and dibenzofuran sources and fate in the Baltic Sea.Manuscript submitted.

Broman, D., Naf, C., Zebuhr, Y., 1991. Long-term high- and low-volume air samplingof polychlorinated dibenzo-p-dioxins and dibenzofurans and polycyclicaromatic hydrocarbons along a transect from urban to remote areas on theSwedish Baltic coast. Environmental Science and Technology 25, 1841–1850.

Commission of the European Communities, 2006. Commission regulation (EC)No 1881/2006 of 19 December 2006 setting maximum levels for certaincontaminants in foodstuffs. Official Journal of the European Union L364.

Egeback, A.-L., Jansson, B., Jarnberg, U., Lexen, K., Strandell, M., de Wit, C., Wideqvist,U., Kjeller, L.-O., Rappe, C., 1991. Levels of PCDD, PCDF and PCB in ambient airsamples collected in Sweden. Dioxin ’91, 11th International Symposium onChlorinated Dioxins and Related Compounds, Research Triangle Park, NCSeptember 1991, University of North Carolina, Chapel Hill, 1991, p. 114.

Eitzer, B.D., Hites, R.A., 1989. Polychlorinated dibenzo-p-dioxins and dibenzofuransin the ambient atmosphere of Bloomington, Indiana. Environmental Scienceand Technology 23, 1389–1395.

Gusev, A., Ilyin, I., Shatalov, V., Sokovych, V., 2008. Modelling of transboundaryatmospheric pollution by heavy metals and POPs in Europe and Central Asia.EMEP/MSC-E, Technical Report 1/2008, July 2008.

Hafner, W.D., Hites, R.A., 2005. Effects of wind and air trajectory directions onatmospheric concentrations of persistent organic pollutants near the GreatLakes. Environmental Science and Technology 39, 7817–7825.

Hippelein, M., Kaupp, H., Dorr, G., McLachlan, M., Hutzinger, O., 1996. Baselinecontamination assessment for a new resource recovery facility in Germany, PartII: atmospheric concentrations of PCDD/F. Chemosphere 32, 1605–1616.

Hovmand, M.F., Vikelsøe, J., Andersen, H.V., 2007. Atmospheric bulk deposition ofdioxin and furans to Danish background areas. Atmospheric Environment 41,2400–2411.

James, R.R., Hites, R.A., 2002. Atmospheric transport of toxaphene from thesouthern United States to the Great Lakes region. Environmental Science andTechnology 36, 3474–3481.

Konig, J., Theisen, J., Gunther, W.J., Liebl, K.H., Buchen, M., 1993. Ambient air levels ofpolychlorinated dibenzofurans and dibenzo(p)dioxins at different sites inHessen. Chemosphere 26, 851–861.

Lohmann, R., Green, N.J.L., Jones, K.C., 1999. Detailed studies of the factorscontrolling atmospheric PCDD/F concentrations. Environmental Science andTechnology 33, 4440–4447.

McLachlan, M.S., Horstmann, M., Towara, J., Bopp, U., Pfitzenmaier, F., Scholz, M.,1998. Untersuchung der atmospharischen belastung, des weitraumigentransports und des verbleibs von polychlorierten dibenzodioxinen, dibenzo-furanen und coplanaren biphenylen in ausgewahlten gebieten Deutschlands.Report in German, Department of Environmental Chemistry and Geochemistry.Bayreuth University, Germany.

Rappe, C., Bergqvist, P.-A., Kjeller, L.-O., 1989. Levels, trends and patterns of PCDDsand PCDFs in Scandinavian environmental samples. Chemosphere 18, 651–658.

Swedish Dioxin Survey Database, 2008. Stockholm University, Att: MichaelStrandell, Department of Applied Environmental Science (ITM), SE-106 91Stockholm, Sweden.

Tysklind, M., Fangmark, I., Marklund, S., Lindskog, A., Thaning, L., Rappe, C.,1993. Atmospheric transport and transformation of polychlorinated

U. Sellstrom et al. / Atmospheric Environment 43 (2009) 1730–17361736

dibenzo-p-dioxins and dibenzofurans. Environmental Science and Tech-nology 27, 2190–2197.

van den Berg, M., Birnbaum, L.S., Denison, M., De Vito, M., Farland, W., Feeley, M.,Fiedler, H., Håkansson, H., Hanberg, A., Haws, L., Rose, M., Safe, S., Schrenk, D.,Tohyama, C., Tritscher, A., Tuomisto, J., Tysklind, M., Walker, N., Peterson, R.E.,2006. The 2005 World Health Organization reevaluation of human and

mammalian toxic equivalency factors for dioxins and dioxin-like compounds.Toxicological Sciences 93, 223–241.

Verta, M., Salo, S., Korhonen, M., Assmuth, T., Kiviranta, H., Koistinen, J.,Ruokojarvi, P., Isosaari, P., Bergqvist, P.-A., Tysklind, M., Cato, I., Vikelsøe, J.,Larsen, M.M., 2007. Dioxin concentrations in sediments of the Baltic Sea – asurvey of existing data. Chemosphere 67, 1762–1775.