Research Influence of Local Human Population on Atmospheric Polycyclic Aromatic Hydrocarbon Concentrations WILLIAM D. HAFNER, DANIEL L. CARLSON, AND RONALD A. HITES* School of Public and Environmental Affairs, Indiana University, Bloomington, Indiana 47405
Literature values of atmospheric polycyclic aromatic hydrocarbon (PAH) concentrations from sampling sites around the world were found, and using a high-resolution human population grid, the population within a 25-km radius of each sampling site was calculated. A regression of concentration vs population revealed much about PAH concentration differences among regions as well as site locations within a continent. The best fit for the regression was for sampling locations in North America. A small amount of scatter was present for the regression of all developed countries indicating slight differences in emission regulations or energy usage. The regression from this plot was used as a benchmark for the expected relationship between PAHs and human population. Sites located within 25 km of a coast tended to have concentrations lower than expected, due to dilution with clean ocean air, while sites near industrial outputs or other point sources had higher than expected concentrations. Sites from developing countries typically had PAH concentrations that were far higher than those of the rest of the world.
Introduction Polycyclic aromatic hydrocarbons (PAHs) are released into the atmosphere following the incomplete combustion of carbonaceous material (1). Although PAHs can have both natural and anthropogenic sources, anthropogenic sources typically dominate because of the burning of fuel for energy (2). Once in the atmosphere, PAHs partition between particulate matter and the gas phase (3). On a mass basis, most of the PAHs are present in the gas phase and therefore have lifetimes that are relatively short, on the order of hours or days (4, 5). Thus, one might assume that PAH concentrations in the atmosphere would be proportional to the local anthropogenic energy consumption. If one also assumes that this local energy consumption is proportional to the local human population, proximity to a large population would imply higher local PAH air concentrations. Various research efforts have noted such a relationship between human population and atmospheric concentrations of PAHs (6, 7). In particular, a French study found that there was a strong correlation between PAH concentrations in precipitation and population density (8), and Howe et al. (9) determined that PAH concentrations in pine needles * Corresponding author e-mail:
[email protected]; phone: 812855-0193; fax: 812-855-1076. 7374
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decreased as a function of distance from the urban population of Fairbanks, AK. Despite these findings, no research has demonstrated whether this relationship is consistent on a larger (global) scale. The goals of the current work are to verify that the widely held assumption that PAH concentrations are dependent upon human population is indeed valid, and then to examine and explain any deviations from the observed relationship. To accomplish this objective, literature values of PAH concentrations from sampling locations around the world were found and an average PAH concentration was calculated for each of these locations. Using sophisticated GIS techniques, the human populations around the sampling locations were calculated from a high-resolution database. The resultant regressions of PAH concentration vs local population represent a systematic and original way of comparing PAH concentrations across a wide geographic area. The results indicate not only a striking relationship between local population and atmospheric PAH concentration but also differences among industrial sites, coastal areas, and locations in developed and developing countries. The differences seen in these regressions and the comparisons drawn from them highlight the effects that meteorology, topography, and regulation have on PAH emissions.
Experimental Section Data Collection and Organization. An analysis of the data from North America’s Integrated Atmospheric Deposition Network (IADN) showed that differences in average atmospheric PAH concentrations were correlated to the siting criteria. Remote sites had lower PAH concentrations than urban sites, a trend that formed the basis of this study. For this reason, the IADN data were used as a benchmark for selecting which PAHs would be used to best represent atmospheric PAH concentrations. IADN is a long-term atmospheric monitoring project in the Great Lakes region that was established as a joint venture between the United States and Canada, with Indiana University operating the U.S. sampling stations since 1994 (10). We have found that the majority of atmospheric PAHs are composed of a few compounds in the vapor phase, with a smaller portion partitioned to particles. Averaged among all five U.S. IADN sites, the vapor phase makes up about 83% of total atmospheric PAH concentration. For this reason, only those published studies that included vapor phase or both vapor and particle phase data were used. Although many different sample collection strategies exist, only those samples collected using polyurethane foam (PUF) plugs or XAD resin for the vapor phase and quartz filter fibers (QFF) or glass filter fibers (GFF) for the particulate phase were selected. These sampling media are the standard for collection of persistent organic pollutants, including PAHs. Passive sampling data were not used because of difficulties in determining a sampled volume, and hence, concentrations. Questionable and novel means of sampling were also not used. PAH data from a large number of studies were collated. A uniform suite of the most frequently reported individual PAH with the highest concentrations was chosen from each of the studies to represent total PAHs. The seven PAHs chosen were summed: fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, and triphenylene. Within the IADN dataset, these seven compounds make up >80% of total vapor and particle phase PAHs, and, with the exception 10.1021/es0508673 CCC: $30.25
2005 American Chemical Society Published on Web 08/23/2005
of triphenylene, these compounds are part of the U.S. Environmental Protection Agency’s list of priority PAHs (1). Phenanthrene is the single largest contributor to this total, making up ∼40% of atmospheric PAHs as measured by IADN. If phenanthrene was not reported at a sampling site, that particular sampling location was not used. There are some PAHs that were not included on this list that merit a separate explanation. Retene is often associated with forest fires (11) and cannot be relied upon to be primarily anthropogenic. Acenaphthene and acenaphthylene are poorly retained on XAD resin or PUF. Similarly naphthalene, which has been measured at concentrations 10-100 times higher than phenanthrene (12, 13), is often poorly retained on XAD or PUF and was frequently not reported. In choosing this measure of total PAHs, it is important to remember that these concentrations serve as a surrogate for the heavier and more carcinogenic PAHs such as benzo[a]pyrene (1). Averaged over all the IADN data, benzo[a]pyrene is only detected in ∼18% of the vapor phase samples and in ∼51% of the particle phase samples, with the frequency of detection being the lowest at the rural and remote sites. This suggests that there is not a large enough body of data to determine truly representative average concentrations for a regression. For this reason, we focused on the lighter PAHs, which happen to be found in higher concentrations than the heavier PAHs. In cases where concentrations were already reported in the form of total PAHs, discretion was used in accepting these values. As mentioned, breakthrough problems are known to exist with naphthalene, acenaphthene, and acenaphthylene. If the total PAH concentration contained any of these three compounds, the data were generally discarded. In some instances, such as when there were no other sampling locations nearby and when the data would not affect the regression (not-representative data as defined below), the data were kept to ensure a greater spatial range. A total of 278 separate sampling locations from 102 references were found around the globe with the majority being in North America and Europe (see Tables S1-S3 in the Supporting Information). The first of these studies was published in 1984, and only 17 studies were conducted up until 1994. PAH concentrations are known to have decreased substantially over time in the United States as seen in several sediment cores (14, 15). Thus, there is a possibility that some of these older studies may have slightly inflated concentrations relative to later studies. However, this is not likely to affect the overall regression because few of these older studies were included due to their failure to meet further criteria as discussed below. Along with the PAH concentrations, location was recorded in terms of sampling site, city, state or province (if applicable), and country. When available, the latitude and longitude were recorded. Otherwise, coordinates were determined using details provided in the paper. Categorization. Some sampling locations were established with the intent to capture industrial impacts; other locations were sampled under extreme circumstances, such as fire or pollution events. Although both of these categories will fall under the categorization of “Industrial”, there are some important differences between them. The emissions from industrial sources can presumably be controlled, whereas extreme circumstances, such as a forest fire, are unalterable. The remaining sites were categorized according to the location, number, and temporal range of the samples. Atmospheric PAHs are known to be both seasonally and temperature dependent (2, 16-18). For example, the IADN data show that concentrations of particle-bound PAHs tend to peak in the winter, and the lighter compounds that primarily comprise the PAHs used in this study peak in the summer. Because of these variations, obtaining an accurate
average concentration requires at least a year’s worth of data. Thus, the sampling locations were sorted into “Representative” or “Not-Representative” categories. To qualify as representative, at least 10 samples had to have been collected over a year or in more than one nonconsecutive season. This removes the bias due to temperature effects or outliers. Notrepresentative samples were either composed of fewer than 10 samples or featured data that did not cover a year. The representative and not-representative data were further categorized according to location. Sites located within 25 km of coastal areas or samples that were taken over water were designated as “Coastal”. “Developed Continental” sites were those that were more than 25 km from the coast and in regions with developed economies and governmental structures. Last, “Developing Continental” sites were those that were more than 25 km from the coast and in regions of relatively low economic input or in countries that have undergone rapid economic or political change in recent years: China, for example. Population Estimation. To make a valid comparison between human population and atmospheric PAH concentration, a consistent method was needed for calculating the local population. We chose to calculate the population within a 50-km-diameter circle centered on the sampling location. This area was large enough to include the majority of the conurbation for major cities, while generally excluding nearby metropolitan areas for less populated regions. In addition to a consistent method, a systematic and highresolution database was needed to calculate accurate local populations throughout the large spatial range of sampling sites found in our literature search. LandScan, created by the Oak Ridge National Laboratory’s (ORNL) Global Population Project, is a worldwide human population database on a 30 by 30 seconds (30′′ × 30′′, which is 0.93 km × 0.93 km at the equator) latitude/longitude grid. Census counts form the basis of the LandScan population estimates, with the population being further distributed based on nighttime lights, proximity to roads, land cover and slope, and other data sets. The LandScan database compiled in 2002 was used for this project; see http://www.ornl.gov/sci/gist/landscan/. The LandScan data were downloaded for each continent in the form of a raster dataset, and ArcGIS 8.3 (ESRI, Redlands, CA) was used to calculate local populations for each site. Each continent was projected using the Lambert Azimuthal projection, with the central meridian and latitude of origin being the center of the continent (see Table S4 in the Supporting Information for the coordinates used). Using the same projection, a separate point coverage was created for each sampling location. Each point was buffered with a radius of 25 and 30 km. The larger buffer was used to remove a portion of the raster dataset. Because of software limitations, the portion removed from this raster dataset was rectangular, rather than the desired circular buffer. The raster data were then converted to a polygon coverage in which adjacent grid cells from the raster data with the same populations were combined to form a larger polygon. Grid cells with unique populations formed separate polygons. The population density for each of these polygons was calculated and stored in the polygon attribute table for that coverage. This polygon coverage was clipped using the 25-km radial buffer. This buffer contained population data in terms of density. Backcalculation using the new clipped area gave the absolute population of each circular buffer. All population estimates were reviewed, and if the result seemed unreasonable it was double-checked using online census data or other sources as a guide. Particular attention was given to remote regions where LandScan seemed most likely to misrepresent the population. In all, populations from 13 sampling locations were modified. Most of these exceptions occurred in rural or remote regions of Canada and are VOL. 39, NO. 19, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 1. Human population and atmospheric PAH concentrations from continental sites in North America. Only so-called representative data are plotted. The regression parameters are given in Table 1 as regression I. The regression parameters obtained when the data for the three Arctic sites (denoted as A) are removed are given in Table 1 as regression II. The dotted lines are the 95% prediction limits. likely due to both poor apportionment of census data and transient populations. Many of the modified sites are military installations or scientific outposts, the populations of which have changed in the time since the PAH sampling occurred. These locations are flagged with the corrected population reference listed in Tables S1-S3 in the Supporting Information.
Results and Discussion In general, higher atmospheric PAH concentrations are found near centers of high population density such as in Eastern Europe and China, and the lowest PAH concentrations are found where there are few people such as near the Arctic and in remote regions of Canada, the northern Great Lakes, and Scandinavia. The following sections discuss these observations in terms of regressions between the observed PAH concentration and the human population within a 25km radius of the sampling site. Continental North American Sites. Figure 1 shows the relationship between PAH concentration and population for the representative data from 36 continental sites throughout North America. Because the range is several orders of magnitude for both population and concentration, the data are plotted on logarithmic scales. The regression parameters are listed in Table 1 (see regression I), and they were calculated using a linear regression of the logarithms of the population and concentration. The 25-km radial zone populations range
from 16 at the Dye 3 radar station in Greenland to 5 042 000 in Elizabeth, New Jersey. The Dye 3 site also has the lowest PAH concentration at ∼0.05 ng/m3, while the highest PAH concentration was at the University of Illinois at Chicago (UIC) site in Chicago, IL, at 136 ng/m3. The overall r2 for this regression is 0.926, which is highly significant (P < 0.0001 for both parameters). Dashed lines in Figure 1 represent the 95% prediction limits. The only point outside of the lower limit is for samples collected at Egbert, Ontario. The UIC site, with the highest concentration in Figure 1, is nearly outside of the higher limit. The site at UIC was used as a companion to a site at the Illinois Institute of Technology (IIT) in Chicago in an effort to determine whether persistent organic pollutant concentrations were consistent across the city. In a direct comparison between the UIC and IIT sites by Basu et al. (19), it was shown that PAH concentrations at the two sites were not significantly different. However, there may be different PAH sources to the UIC site because of different traffic patterns or because of a closer proximity to industrial areas (such as train yards). Arctic Sites. As outlined above, atmospheric PAH concentrations usually depend on atmospheric temperature; thus, to compensate for this effect, we used data from the literature that covered the full annual cycle. Nevertheless, several of the sites in North America represented in Figure 1 are located in Arctic regions with low atmospheric temperatures. Thus, it is possible that PAH would behave differently with respect to population at these sites than at sites with similar populations but located in more temperate regions. In addition, these sites have the lowest populations and PAH concentrations, and their absence from the regression could alter the parameters. To test this possibility, data at three sites considered to be much colder than the others (greater than 60° latitude; no other site in the regression has a latitude greater than 50°) were removed from the regression of the continental North American data, and the regression was recalculated. The results are given in Table 1 (see regression II). Without these points (see points A in Figure 1), r2 decreased to 0.876, but the regression parameters did not change significantly. This suggests that the inclusion of the Arctic sites in this regression is justified. All Continental Data. PAH concentrations and populations from all continental locations in developed countries are shown in Figure 2. This includes 75 representative and 51 not-representative sampling locations from countries in Western European and from the United States, Canada, Australia, Japan, and South Korea. In Figure 2, the lowest population and PAH concentration is at the Dye 3 site. The highest populations are for Tokyo, Japan and Seoul, Korea with 12.6 and 13.6 million people, respectively. UIC in Chicago
TABLE 1. Regression Parameters for Figures 1 and 2 as Well as for Figure 1 with the Arctic Sites Removed and for All Data from Developing Countriesa coefficient Continental North America (regression I) North America without cold sites (regression II) all continental (regression III) developing continental (regression IV) a
N y a N y a N y a N y a
36 -1.694 0.515 33 -1.466 0.476 75 -1.536 0.482 39 -1.157 0.596
std error
t
P
r2
0.131 0.025
-12.89 20.70
< 0.0001 < 0.0001
0.926
0.177 0.032
-8.31 14.77
< 0.0001 < 0.0001
0.876
0.137 0.025
-11.20 19.72
< 0.0001 < 0.0001
0.840
0.612 0.106
-1.89 5.65
0.0667 < 0.0001
0.470
The parameters are from a linear regression of the form log(PAH) ) y + a log(population).
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FIGURE 2. Human population and atmospheric PAH concentrations for all continental sites. Solid shapes are the representative sites, and open shapes are the not-representative sites. The regression line shown is calculated only from the representative data, and these regression parameters are given in Table 1 as regression III. The dotted lines are the 95% prediction limits. shows the highest PAH concentration among the representative data, while the highest PAH concentration overall is for a not-representative site in downtown Rome at 146 ng/ m3 . The regression line and 95% prediction limits in Figure 2 are calculated based only on the data from the representative sites. There are a total of 11 sites that are not within the prediction limits, seven of which are considered notrepresentative. Of the representative data, one of the four outliers is from Paris, France with a PAH concentration of 14.7 ng/m3. Using the regression parameters from Table 1 with a population of 7 582 703, this site would be expected to have a concentration of ∼60 ng/m3, which is substantially higher than the reported value. The PAH concentrations for this site do not contain fluorene, which could be expected to increase this number up to 30%. Even with fluorene taken into account, this concentration is still low. Although it is within the prediction limits, a second site in Paris also has a concentration lower than the regression line. Taken together these data suggest that the atmosphere over Paris is relatively clean in terms of PAH pollution. The remaining three outliers are from Austria, and these deviations highlight the importance of sampling site location. The cities of Graz and Linz are comparable in population with 415 800 and 459 050 people, respectively. Predicted PAH concentrations from the regression are, respectively, 15 and 16 ng/m3, which are much lower than the actual concentrations of 74 and 64 ng/m3. Atmospheric inversions are known to occur frequently in Graz (20) and may explain the relatively high concentrations there. Linz and Graz are both located in low-lying areas surrounded by relatively mountainous areas, suggesting that inversions are possible in Linz as well. The third Austrian outlier has a concentration lower than the lower prediction limit. The site is located in the Tyrolean Alps, at an altitude above the tree line (21). The concentration is more than a factor of 4 lower than the predicted value and nearly a factor of 40 less than the PAH concentrations at Graz and Linz. Interestingly, a fourth Austrian site (in Vienna) has a population of 1.4 million and a PAH concentration of 38 ng/m3. This site is on the regression line in Figure 2. Although regional differences in home heating systems and the fuels used may play a role in the different PAH concentrations seen in Austria, the more likely explanation for these differences is topography and local meteorology. Higher elevations allow for mixing with clean air which reduces the PAH concentrations accordingly, a phenomenon
FIGURE 3. Human population and atmospheric PAH concentrations from industrial and coastal sites from developed countries. The regression shown is regression III. Points 1 and 2 are from San Nicolas Island, CA, and Sable Island, Nova Scotia, respectively. Points 3a and 3b are samples from New York City after September 11, 2001 in the WTC smoke plume and on a clear day, respectively. Points 4a and 4b are samples from Los Angeles, CA, collected during the worst smog event of 1993 and throughout the year, respectively. that has also been noted with particulate-only PAH concentrations in the Alps (22). Like the regression for North America (see Figure 1), the regression parameters for all the continental sites in developed countries are highly significant (P < 0.0001), and overall, there seems to be little difference in PAH concentrations between sites with similar populations. For example, in the 13 representative sites with populations between 1 and 2 million (see Tables S1 and S2), concentrations fall in the narrow range of 12.4-43.5 ng/m3. However, the correlation coefficient (r2) of 0.840 is somewhat lower than that for North America alone (see Table 1, regressions I and III). A likely reason for this slight drop in correlation is the increased number of countries represented on the plot. Fuel type (oil and natural gas as opposed to coal), regulations, and emission control strategies certainly differ between countries, which undoubtedly affect the levels of atmospheric PAHs. In addition, Europe and Asia have a greater overall population density resulting in fewer sites with populations less than 10 000. In this case, the x-axis covers 6 orders of magnitude, three of which represent populations less than 10 000. Only 10 of the 75 representative sites have populations within this range, and seven of these are in North America. By contrast, 52 of these sites have populations between 100 000 and 10 000 000 people. To verify that the regression for the developed countries (as shown in Figure 2) is real, the Spearman’s rank correlation coefficient was determined for the representative data. An rS value of 0.803 (P < 0.0001) indicates that a strong relationship exists between atmospheric PAH concentrations and local population throughout the United States, Canada, Western Europe, Japan, Korea, and Australia. Validation of this regression is important, because the relationship it depicts will be used here as a benchmark for comparisons of the data from sites categorized as industrial, coastal, and continental in developing countries. Industrial and Coastal Sites. PAH concentrations and populations from coastal sites (blue) and from industrial sites (red) from developed countries are plotted in Figure 3 on top of the regression line and prediction limits from Figure 2. Note the increase in the range of concentration. Not surprisingly, the industrial sites (red) have concentrations that are generally higher than would be expected based solely on population. The highest concentrations measured in the VOL. 39, NO. 19, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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developed countries are from Shawinigan and Jonquiere, Quebec, with PAH concentrations of 1035 and 1160 ng/m3, respectively. Both of these sites are located next to aluminum smelters and are expected to receive direct PAH emissions (23). A high PAH concentration of 232 ng/m3 is also measured at the remote site of Whitehorse, Yukon Territory, Canada, which had been labeled an industrial site by Dann (7) with high PAH concentrations due to excessive wood smoke. Coastal sites display the opposite trend; typically, these concentrations are beneath the regression line and are frequently outside the lower prediction limit. These low PAH concentrations suggest that there is significant mixing between contaminated urban costal air and clean ocean air at many of these sites. However, there is still a substantial amount of variation, with some of the coastal sites above the regression line. This is probably because of our relatively arbitrary definition of coastal sites and because of strong meteorological variations among sites. Two coastal points are well above the upper prediction limit of the regression. The point marked 1 in Figure 3 is for data from San Nicolas Island, which is located ∼100 km southwest of the southern California coast (12). A low PAH concentration is expected because the site is an island, implying that it is both coastal and has a low population. However, the high reported concentration suggests a local source. Further investigation of this site reveals that the island is owned by the U.S. Navy. Testing and training activities are frequently conducted that presumably contribute to the higher than expected measured PAH concentrations. A second site, marked 2, is also an island: Sable Island is located 240 km east of Nova Scotia. The site was selected with the intent of capturing background contaminant levels (24). The annual population consists of just a few weather station operators with no agricultural or industrial activity on the island. However, at the time of sampling there was some occasional oil exploration on the continental shelf nearby that may have been contributing to a higher PAH burden in the atmosphere surrounding Sable Island. In addition to the deviations of the coastal and industrial sites from the regression line, there are also some interesting inter-comparisons between the two datasets. The points marked 3a and 3b were from samples collected shortly after the September 11, 2001 attacks on the World Trade Center (WTC). The samples were collected about 500 m northwest of the WTC site. During the collection of these four samples, the wind direction was from the southwest. The average PAH concentration of these samples is represented by point 3a at 530 ng/m3. The fifth sample showing a PAH concentration of 28 ng/m3 (point 3b) was collected during a prevailing north wind with intermittent precipitation, and it was assumed to represent “background” concentrations during this time (25). PAH concentrations are nearly a factor of 20 less in this sample. A separate study conducted in the Bronx, New York City found PAH concentrations of 71 ng/m3 (26). The Bronx is classified as greater than 25 km from the open ocean, qualifying it as a continental site. This 71 ng/m3 point from the Bronx is located directly on the regression line in Figure 3. These three New York sampling studies demonstrate the amount of variation possible over a short distance and period of time. Another interesting comparison is on the West Coast of the United States. Points 4a and 4b represent sampling studies from Los Angeles, CA during the worst smog event of 1993 (12) and an annual average throughout 1999-2000, respectively (27). Similar to results from New York, these sites are on opposite sides of the regression line with a factor of 15 difference between them. Continental Sites from Developing Countries. The data from developing (rapid economic or societal change) countries are shown in Figure 4. This plot includes sites from a 7378
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FIGURE 4. Human population and atmospheric PAH concentrations from developing countries. Point 1 is a 1998 haze event in Brunei, and point 2 is from Hangzhou, China. The regression shown is regression III. The regression of just the data from developing countries is regression IV (not shown); see Table 1 for these parameters. wide geographic range representing the countries of Brazil, Iran, the Congo, India, China, Taiwan, Brunei, Croatia, the Czech Republic, and Slovakia. A regression of these data including both representative and not-representative data and excluding industrial and coastal sites gives an r2 value of only 0.470, and one regression parameter (y) is not significant at the 5% level (see Table 1, regression IV). Clearly, the PAH sources in these developing countries are highly varied and not well related to population. In general, the PAH concentrations in developing countries are consistently over an order of magnitude higher than those in developed countries of the same population. In addition, there is little difference between PAH concentrations at the industrial and continental sites in developing countries. These similarities imply that atmospheric PAH concentrations are so high that local air conditions are irrelevant. A likely reason for elevated PAHs in these countries, and particularly China, is their increased reliance on coal for domestic energy. Emissions from coal stoves and individual boilers are not as easy to control as emissions from coal-fired power plants. Domestic coal use accounts for
