How Do Climate Fluctuations AffectPersistent Organic PollutantDistribution in North America?Evidence from a Decade of AirMonitoringJ I A N M I N M A , * H A Y L E Y H U N G , A N DP I E R R E T T E B L A N C H A R D

Air Quality Research Branch, MeteorologicalService of Canada, 4905 Dufferin Street, Toronto,Ontario M3H 5T4, Canada

Interannual variations of persistent organic pollutant(POP) air concentrations from the Great Lakes region andthe Arctic during the 1990s are strongly associated withatmospheric low-frequency fluctuations, notably the NorthAtlantic Oscillation (NAO), the El Nino-Southern Oscillation(ENSO), and the Pacific North American (PNA) pattern. Thissuggests interactions between climate variation and theglobal distribution of POPs. Atmospheric concentrations ofhexachlorocyclohexanes (HCHs), hexachlorobenzene(HCB), and several lighter polychlorinated biphenyls (PCBs)measured around the Great Lakes basin increasedduring the positive phases of NAO and ENSO in thespring. This implies that anomalous high air temperaturesassociated with NAO and ENSO enhance volatilizationof POPs from reservoirs on the Earth’s surface accumulatedin the past. These compounds are then available fortransport from source regions to more pristine regionssuch as the Arctic under favorable flow patterns associatedwith global climate variations.

IntroductionThe ability of persistent organic pollutants (POPs) to moveover great distances coupled with their environmentalpersistence has attracted significant scientific attentionduring the past few decades. They tend to bioaccumulate inlipid-rich tissues of biota and biomagnify through terrestrialand aquatic foodchains (1, 2). Although the use of manyPOPs has been banned or restricted in industrializedcountries since the 1970s, their presence in various envi-ronmental compartments is a continuing concern becauseof their potential impacts on human health (3, 4) and on theglobal ecological systems (5, 6).

As primary emissions (fresh application/usage) diminish,secondary emissions (i.e., volatilization from previously con-taminated environments) could play an increasingly im-portant role in the global distribution of POPs (7). Secondaryemissions and subsequent transport are strongly affected bytemperature, which influences the compounds’ physical-chemical properties, such as vapor pressure and Henry’slaw constant. Winds also contribute to the atmospherictransport of these compounds. It has been well-known thatthe changes in both temperature and the large-scale wind

system are associated with certain atmospheric circulationpatterns (8). The effects of diurnal and seasonal fluctuationsof surface air temperature (SAT) on the changes in atmo-spheric concentrations of organochlorine compounds, acategory of POPs, have been documented (9-11), and higherSATs result in increased organochlorine compound volatil-ization from surfaces (12-14). Yet, the link between inter-annual changes in atmospheric POP concentrations andclimate variability has not been studied extensively. This ismainly due to the lack of continuous atmospheric POPmeasurements before the 1980s. Moreover, the associationsof climate fluctuations with air concentrations of POPs weredifficult to discern when current applications dominatedannual cycles.

During the 1990s, two major long-term air-monitoringprograms have been established in North America to measurePOP concentrations with the goal of determining spatial andtemporal trends of these substances. They are the CanadianNorthern Contaminants Program (NCP) measuring atmo-spheric POPs in the Canadian Arctic (15) and the IntegratedAtmospheric Deposition Network (IADN), operated byCanada and the U.S., in the Great Lakes region (11). Here,we report evidence of relationships among air concentrationsof hexachlorobenzene (HCB), R-hexachlorocyclohexane (R-HCH), γ-HCH, and the polychlorinated biphenyls (PCBs)sampled by these two programs, between December 1990and May 2000, and major climate variabilities in the NorthernHemisphere.

MethodologyField Data. Under the NCP, weekly air sampling has beenconducted for PCBs, organochlorine compounds, and poly-cyclic aromatic hydrocarbons with data collected since 1992for several Arctic locations. The sampling details and samplepreparation as well as the analytical methods have beendetailed in previous papers (15-17). For this study, airconcentrations measured at the longest operating site of Alert,Nunavut (82°30′ N, 62°20′ W), between January 1993 andMay 1999 are used.

The IADN program operates five major sites on the shoresof the Great Lakes. These include Point Petre on Lake Ontario(43°50′34′′ N, 77°9′13′′ W), Burnt Island on Lake Huron(45°48′30′′ N, 82°57′00′′ W), Eagle Harbor on Lake Superior(47°27′47′′ N, 88°08′59′′ W), Sleeping Bear Dunes on LakeMichigan (44°45′40′′ N, 86°03′31′′ W), and Sturgeon Point onLake Erie (42°41′35′′ N, 79°03′18′′ W). Sampling occurs for 24h every 12 days. The sampling details and analytical methodsare given in previous papers (11, 18, 19). IADN data includedin this study are from Point Petre (January 1992 to May 2000),Burnt Island (January 1993 to May 1998), Eagle Harbor (De-cember 1990 to May 1998), and Sturgeon Point and SleepingBear Dune (December 1991 to May 1998).

Climatological Indices. Atmospheric circulation exhibitssubstantial variability due to weather patterns and circulationsystems that occur on time scales from a few days to severalyears. Atmospheric circulation patterns that persist for arelatively long time over a large area are often defined byatmospheric circulation teleconnection patterns. A telecon-nection pattern (also called a “preferred mode”) is a recurringand persistent, large-scale pattern of pressure and circulationanomalies that spans vast geographical areas. Many atmo-spheric circulation teleconnections have been identified inthe last 50 years (20). Among them, the North AtlanticOscillation (NAO) (21), the El Nino-Southern Oscillation(ENSO), (22), and the Pacific North American (PNA) circula-tion pattern (20) are dominant sources of Northern Hemi-

* Corresponding author phone: (416) 739-4857; fax: (416) 739-4288; e-mail: jianmin.ma@ec.gc.ca.

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spheric climate variability. These three teleconnection pat-terns are also associated closely with the upper-level (g850hPa) flow patterns in the troposphere and surface temper-atures and precipitations in North America (21-23).

NAO, ENSO, and PNA are represented by their respectiveindices, which can be obtained from the Climate DiagnosticsCenter of the National Oceanic and Atmospheric Adminis-tration at http://www.cdc.noaa.gov/Teleconnections/, namely,the standardized NAO index, multivariate ENSO index (MEI),and PNA index. The NAO and PNA indices are derived fromthe first rotated principal component based on monthly 700hPa geopotential height anomalies. NAO indices can bedefined as the difference of the sea level pressure betweenLisbon, Portugal, and Stykkisholmur, Iceland (21). It refersto a meridional shift in atmospheric mass between subpolarand subtropical latitudes and is an indication of the strengthof westerly winds blowing across the North Atlantic Oceanbetween 40° and 60° N. Such strength influences the SATand balance of precipitation and evaporation across theAtlantic Ocean and the adjoining landmasses (24). In the

spring, sea level pressure anomaly patterns shift betweenthe Arctic and the northern Atlantic during the positiveand negative phases of the NAO (NAO index > 0 and < 0,Figure 1). During the positive NAO phase, the largest nega-tive sea level pressure anomalies occur in Greenland withthe positive anomalies in the northern Atlantic. Accordingly,positive SAT anomalies in western and central North America(yellow and green regions in Figure 1a) indicate warmer thannormal spring seasons in these regions. Roughly reversedconditions occur during the negative NAO phases wheneastern and central North America experiences colder springs(blue regions in Figure 1b).

The MEI is defined by the first unrotated principal com-ponent based on six main observed variables over the tropicalPacific. These six variables are sea level pressure, zonal andmeridional components of the surface wind, sea surfacetemperature, surface air temperature, and total cloudinessfraction of the sky (22). MEI is related to the fluctuations oftropical Pacific sea surface temperature. During a warm ENSOevent (El Nino, positive MEI), considerably warmer equatorial

FIGURE 1. Composite SAT and sea level pressure (SLP) anomalies in the springs of 1992-1998, expressed as departures from the 1968-1996mean. The intervals are 0.5 °C for SAT and 0.5 hPa for SLP. Color shading indicates SAT, and solid and dash contour lines indicate positiveand negative SLP anomalies, respectively. Key: (a) SAT and SLP anomalies derived from 1992, 1994, and 1998 in the positive phase ofNAO; (b) SAT and SLP anomalies derived from 1993, 1995, 1996, and 1997 in the negative phase of NAO.

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surface waters extend from the international date line to thewest coast of South America. It was found that, under theinfluence of such an event, warmer SAT extend from south-western Canada and northwestern United States to the GreatLakes region from late fall to early spring, and cooler thannormal SATs prevailed over the same region during a coldENSO phase (La Nina, negative MEI) (25-27).

The PNA indices were originally defined by the form-ula in ref 8: PNA ) 0.25[Z(20N,160W) - Z(45N,165W) +Z(55N,115W) - Z(30N,85W)], where Z represents standard-ized 700 hPa geopotential values. It is one of the majoratmospheric circulation patterns associated with climatevariation in North America. The PNA is characterized byatmospheric flow in which the west coast of North Americais out of phase with the Eastern Pacific and southeasternUnited States. During its positive phase (PNA index > 0),increasing wavelike flow occurs over the continent withincreased temperatures and decreased storminess in theNorthwest and cold temperatures in the Southeast. Thiscirculation pattern leads to strong southwesterly flow alongthe west coast of Canada. Accordingly, Canada experienceswarmer than normal spring seasons.

Correlation Analysis. Relationships between climaticpatterns and interannual variations of POP concentrationsare assessed using seasonal averages of all parameters in thewinter (December to February) and spring (March to May),during which large-scale atmospheric teleconnections aremost prominent. NAO and PNA indices, which are availableas monthly values, were directly averaged according toseasons (e.g., spring represents March, April, and May). MEI

is given as bimonthly values, and seasonal means wereobtained by averaging the three bimonthly values in thewinter and spring. For example, the winter average MEI valueis the average of November/December, December/January,and January/February.

A Spearman rank-order correlation was used to determinethe associations of POP air concentrations with NAO, MEI,and PNA indices. The Spearman rank-order correlation is adistribution-free, nonparametric measure of associationbased on the rank of the data values, which is exact for smallsample sizes and weakens the effect of outliers (28). Followingthese relatively simple correlation analyses and because ofthe known relationships between surface air temperature(SAT) and organochlorine compound air concentrations,spatial linear regression analyses between NAO/MEI and SATand between γ-HCH/HCB and SAT were conducted. SATdata were obtained from the U.S. National Center forEnvironmental Prediction reanalysis (29). This was done byregressing the time series of mean spring γ-HCH concentra-tion (averaged over five IADN sites) and NAO and MEI indicesagainst SAT values over the region between 40-140°W and20-70°N at a 2.5° × 2.5° grid resolution. Results are presentedin Figure 2. Color shadings in Figure 2 indicate values of thelinear regression slope between the two parameters with unitsof pg‚m-3/°C or unit index/°C as shown on the bar to theright of each map. Positive values of the slope are shown inred, indicating that the two regressing parameters increaseand decrease together. Negative values are shown in blue.White contours encircle regions where the correlations arestatistically significant with a confidence level of g90%.

FIGURE 2. Left panel: (a) regressions of spring mean γ-HCH air concentrations (pg‚m-3) averaged over five IADN sites (1992-1998) againstspring SATs with an interval of 0.01 pg‚m-3/°C and (b) the standardized spring NAO index against spring SATs with an interval of 0.2 perunit NAO index/°C. Right panel: (c) regressions of winter mean HCB air concentrations (pg‚m-3) averaged over five IADN sites (1992-1999)against winter SATs with an interval of 0.05 pg‚m-3/°C and (d) the winter MEI against spring SATs with an interval of 0.2 per unit MEI/°C.White contours encircle regions where the regression is significant at greater than or equal to the 90% confidence level.

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ResultsTable 1 lists the Spearman rank-order correlation coeffi-cients between POP air concentrations and NAO in the win-ter and spring seasons. For the Great Lakes region, it wasfound that HCB, R- and γ-HCH, and four lighter PCBcongeners (e.g., PCBs 8, 31, 44, and 52) correlated significantly(>95% confidence) with the NAO averaged indices. In thespring, POP air concentrations in the Great Lakes region tendto increase during the positive phase of the NAO, whenhigher-than-usual temperatures were observed in westernand central North America (Figure 1a). The similarity inpatterns between parts a and b of Figure 2 confirms theassociation between γ-HCH and NAO. The spatial distri-bution of the regression coefficients in Figure 2a indicatesa statistically significant relationship (g90% confidence,shown by a white contour) between larger Great Lakesγ-HCH air concentrations and increased SATs in the regionfrom the west to northwest of the Great Lakes basin.Correlations during the winters of 1992-1999 occurred onlybetween NAO and two heavier PCB concentrations (PCBs101 and 105) and γ-HCH (Table 1). At the Canadian HighArctic site of Alert, the analysis resulted in significantcorrelations for PCBs 31, 44, and 138 with the spring NAO,but the lighter compounds of HCB and the HCHs do notshow such a correlation.

The effect of ENSO on POP air concentrations in the GreatLakes region is less apparent than that of NAO. No correlationwas observed between the HCH concentrations and MEIover the Great Lakes. Spring and winter mean HCB and PCB18 and spring mean PCB 52 showed statistically significantcorrelations (>95% confidence) with MEI at two of thewesternmost IADN sites, namely, Eagle Harbor located onLake Superior and Sleeping Bear Dune on Lake Michigan(Table 2). This is in agreement with the fact that the highestpositive SAT anomalies during El Nino winters in NorthAmerica were observed in the western part of the upper GreatLakes (26). Regression maps between SAT and mean HCBair concentrations (averaged over five IADN sites) (Figure2c) and between SAT and MEI (Figure 2d) illustrate thegeographical correlation of these three parameters. Redshading with statistically significant correlations greater than90% (white contour) of similar shape covers the same areaover western and central North America in Figure 2c,d. Theresult suggests that the response of HCB air concentrationsover the Great Lakes region to SAT anomalies is in reality a

response to the ENSO events, because ENSO dominates theinterannual variations of SAT.

PNA patterns are correlated significantly with the ENSOin cold months of the year (e.g., December through March)(23, 25). POP air concentrations measured at the IADN siteswere also weakly correlated with the PNA indices (rS < 0.7)in winters, while no significant correlations were observedfor the spring season. Interestingly, strong correlationsbetween the PNA and the POPs measured at Alert in theCanadian high Arctic were observed. Among them, γ-HCHair concentrations at Alert show a statistically significantpositive correlation with the PNA in the spring (rS ) 0.86, p) 0.01, N ) 7).

DiscussionResponses of POP atmospheric concentrations to the climatefluctuation patterns vary with seasons and locations. Thislikely depends on the physical-chemical properties ofindividual compounds, which will affect their degree ofresponse to changes in SAT associated with climate variability.The response of air concentrations of HCB, HCH, and thelighter PCBs in the Great Lakes region to NAO and to a lesserextent ENSO is likely a result of volatilization from soil. Forcertain compounds, soils seem to be oversaturated withrespect to the atmosphere, so that soil-air exchange takesplace. The rate of this process is temperature dependent andthus shows a strong association with SAT and therefore alsowith NAO and ENSO. However, with the currently availablesmall datasets on POP air concentrations in North America,which lack spatial and temporal resolutions (only one Arcticsite and five Great Lake sites with time series of less than 10years), it is, at this point, difficult to determine why somecompounds show strong correlations with these large-scaleatmospheric phenomena and others do not. One must alsobear in mind that a statistical relationship does not necessarilyimply causal connections.

Ma et al. (30) has shown that γ-HCH is readily volatilizedfrom soil and subsequently transported to the Great Lakesfrom the Prairies region in the springtime. However, in thecurrent study, no correlation was observed between the HCHconcentrations and MEI over the Great Lakes in contrast tothe NAO index. This again may be due to the limited ambientair concentration datasets. Differences between the physical-chemical properties of the various compounds may alsocontribute to the discrepancies in the observed correlations.HCB and PCB 18, for which their concentrations showedcorrelation with MEI, have much higher Henry’s law con-stants, H, than the HCHs (at 25 °C, H values of HCB, PCB 18,and R- and γ-HCH are 130, 92, 0.87, and 0.15 Pa‚m3‚mol-1,respectively (31)). HCB and PCB 18 are not only more volatilebut also less water soluble than the HCHs. These compoundstransported from source regions to the Great Lakes wouldhave a higher tendency to stay in the air rather than depositinto the water, resulting in a more significant response in airconcentrations than that of the HCHs.

TABLE 1. Spearman’s Coefficients (rS) between AirConcentrations of Organochlorine Compounds andStandardized Winter and Spring NAO Indicesa

station compd rS p N

SpringAlert PCB 31 0.71 0.05 8

PCB 44 0.74 0.04 8PCB 138 0.76 0.03 8

Point Petre PCB 8 0.72 0.03 9PCB 31 0.82 0.02 7PCB 52 0.73 0.02 9

Burnt Island PCB 44 0.83 0.04 6Eagle Harbor HCB 0.86 0.01 7

R-HCH 0.76 0.03 8Sleeping Bear Dune R-HCH 0.82 0.02 7Sturgeon Point γ-HCH 0.86 0.01 7

WinterBurnt Island PCB 105 0.83 0.04 6Eagle Harbor PCB 101 0.71 0.05 8Sturgeon Point γ-HCH 0.75 0.05 7

a Only compounds with rS > 0.7, p < 0.05, and the number ofseasonally average organochlorine concentrations N > 5 are presented.Correlations are statistically significant at the 95% level.

TABLE 2. Spearman’s Coefficients (rS) between AirConcentrations of Organochlorine Compounds and MEIa

winter spring

station compd rS p N rS p N

Alert PCB 28 0.71 0.05 8Eagle Harbor HCB 0.78 0.04 7Sleeping Bear HCB 0.93 0.002 7 0.78 0.04 7

Dune PCB 18 0.75 0.05 7 0.86 0.01 7PCB 52 0.75 0.05 7

Sturgeon Point HCB 0.82 0.02 7a Only correlations that are statistically significant with >95%

confidence are listed.

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While atmospheric concentrations of POPs in the GreatLakes fluctuate according to temperature variations associ-ated with large-scale atmospheric phenomena, such as NAOand ENSO, those in the Arctic are usually less dependent onlocal temperatures. At Alert, long-range transport plays amore important role than revolatilization (16, 17). A strongSpearman correlation between γ-HCH concentrations mea-sured at Alert and the PNA index in the spring supports this.The PNA affects primarily the North Pacific and NorthAmerican climate variation and weather. Figure 3 depictslinear regression coefficients between the PNA and zonalflow at 700 hPa in North America in the springs of 1993-1999. During the positive phase of PNA, amplification of thewestern Canadian ridge and weaker zonal flows in NorthAmerica (blue region in Figure 3) may enhance atmosphericmass exchange between polar and midlatitude regions.Consequently, increasing wavelike flow patterns during thepositive phase give rise to a poleward transport of air masses,which would explain the strong positive correlation observedbetween γ-HCH air concentrations at Alert and the PNA index.Since large amounts of lindane were used for seed treatmentin the Canadian Prairies (32), it is not surprising that γ-HCHair concentrations increase at Alert in the spring plantingseason during a positive phase of PNA. An anomalous SATincrease in northwestern Canada at this time enhances thevolatilization of γ-HCH, which is then transported to theArctic.

Despite the relatively small datasets (<10 years) of POPair concentrations used, the results of this study havehighlighted the potential influence of climate variation onthe distribution of POPs, both spatially and temporally. Thus,

the inclusion of planetary atmospheric patterns in globalPOP transport models should be considered. The strongassociations of POPs with these well-documented atmo-spheric low-frequency fluctuations may also create pos-sibilities to use atmospheric teleconnection indices fromclimate models to predict interannual changes in POPs.Temperature is not the only parameter of climate variationthat would affect the transport processes of compounds. Forinstance, changes in other climate parameters, e.g., windintensity, ice cover over the Great Lakes, and quantity, quality,and spatial variation of rain and snow, associated with variousclimate patterns would also affect scavenging and depositionof organic pollutants. Therefore, it is essential to continuelong-term atmospheric monitoring of POPs in the Arctic aswell as in temperate North America to further establishrelationships between POP concentrations and the fluctua-tions of different climate parameters.

AcknowledgmentsWe thank all the members of the NCP and IADN teams forthe use of POP air concentration data measured in theirprograms. H.H. acknowledges financial support from theArctic Environmental Strategy NCP, Department of IndianAffairs, and Northern Development (DIAND).

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Received for review September 2, 2003. Revised manuscriptreceived February 19, 2004. Accepted February 23, 2004.

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