Environ. Sci. Technol. 2008, 42, 3303–3309
Primary and Secondary Contributions to Ambient PM in the Midwestern United States M I C H A E L L E W A N D O W S K I , * ,† MOHAMMED JAOUI,‡ JOHN H. OFFENBERG,† TADEUSZ E. KLEINDIENST,† EDWARD O. EDNEY,† REBECCA J. SHEESLEY,§ AND JAMES J. SCHAUER§ National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, Alion Science and Technology, P.O. Box 12313, Research Triangle Park, North Carolina 27709, and Environmental Chemistry and Technology Program, University of Wisconsin-Madison, 660 North Park Street, Madison, Wisconsin 53706
Received August 15, 2007. Revised manuscript received February 07, 2008. Accepted February 14, 2008.
Ambient PM2.5 samples were collected in five midwestern United States cities throughout 2004: East St. Louis, Illinois; Detroit, Michigan; Cincinnati, Ohio; Bondville, Illinois; and Northbrook, Illinois. Monthly composites were analyzed using chemical derivatization coupled with GC-MS analysis to estimate the contributions of several sources to the total ambient organic carbon. A chemical mass balance (CMB) approach was used to estimate contributions from several primary sources. An additional, organic tracer-based technique was employed to estimate secondary contributions, including secondary organic carbon derived from isoprene, R-pinene, β-caryophyllene, and toluene. The sum of these contributions was compared with the total organic carbon measured at each sampling site, and reasonable carbon mass balances were observed for four of the five sites. In Bondville, Northbrook, Cincinnati, and Detroit a strong correlation was observed between the sum of the estimated primary and secondary contributions and the measured organic carbon (R 2 ) 0.73). The estimated secondary organic carbon concentrations were observed to vary considerably with season, with the strongest contributions coming from isoprene and R-pinene during the summer. While further research is required, there is some evidence that the contribution estimates for R-pinene, β-caryophyllene, and toluene SOC may to some degree represent the contributions from the broader classes of monoterpenes, sesquiterpenes, and aromatics.
Introduction Particulate matter, whether from anthropogenic or biogenic sources, can have a pronounced effect on atmospheric chemistry and air quality. Light scattering or absorption in * Corresponding author phone: 919-541-9421; fax: 919-541-1153; e-mail:
[email protected]. † U.S. Environmental Protection Agency. ‡ Alion Science and Technology. § University of Wisconsin-Madison. 10.1021/es0720412 CCC: $40.75
Published on Web 03/29/2008
2008 American Chemical Society
the atmosphere can lead to visibility degradation (1) and may potentially affect climate by influencing radiative forcing (2, 3). PM2.5 may also affect cloud formation, which in turn influences the hydrological cycle (4). In addition, several studies have suggested that PM2.5 exposure may be related to adverse health effects (5–7). However, a more complete cataloging of the composition of PM2.5, particularly of the organic fraction, may be required to more fully understand the effects of PM2.5 on global climate and human health. PM2.5 typically consists of inorganic salts and acids, liquid water, elemental carbon (EC), and organic matter (OM). A portion of the organic matter is the result of primary emissions, while additional organic matter is generated in the atmosphere as secondary organic aerosol (SOA) produced by reactions which convert volatile organic emissions into nonvolatile or semivolatile products. Analyzing the organic fraction of ambient PM can be challenging due to the large number and variety of compounds present. However, determining the contributions of various primary and secondary sources to ambient PM2.5 concentrations is necessary in order to develop effective control strategies. Schauer and co-workers have previously demonstrated source apportionment of primary organic carbon (POC) contributors through the use of the chemical mass balance (CMB) approach (8). This approach relies on emission source profiles, which are typically obtained by measuring primary particulate emissions from suspected sources under controlled conditions. Profiles have been previously developed for a number of primary sources, including biomass burning (9, 10), motor vehicles equipped with spark-ignition or compression-ignition engines (11–13), natural gas combustion (14, 15), vegetative detritus (15, 16), and meat cooking (17). The CMB approach has been used to evaluate the impact of primary emissions on ambient organic carbon (OC) concentrations in a number of locations, including Los Angeles, California (8, 18); the San Joaquin Valley in California (19); the southeastern United States (20); and the midwestern United States (21). In most cases, the estimated primary contributions are not able to fully account for the bulk organic carbon concentrations measured at the same locations. This unapportioned OC may be derived from primary sources that are not included in the CMB modeling, or from secondary sources. A number of techniques have been used to estimate the contribution of secondary organic carbon (SOC) to ambient OC concentrations, including the use of OC/EC ratios (22), radiocarbon (14C) analysis (23), and aerosol mass spectrometer (AMS) measurements (24). However, these techniques are limited in that they are typically unable to determine which individual precursor hydrocarbons are contributing to the measured SOC. Recent work at the U.S. EPA (25, 26) has led to a technique for approximating the contributions of several individual secondary sources. Kleindienst and coworkers (25) conducted smog chamber experiments in which individual hydrocarbons, including isoprene, R-pinene, β-caryophyllene, and toluene, were irradiated in the presence of NOx. Using chemical derivatization and GC-MS analysis, they were able to identify a series of tracer compounds in the SOA derived from the different precursor hydrocarbons. By measuring these tracer concentrations, as well as the total SOC generated by the smog chamber reaction, tracer-toSOA mass fractions were obtained for each hydrocarbon of interest. If these mass fractions are assumed to be relevant to typical atmospheric conditions, they may be used to estimate SOC contributions to ambient organic carbon by VOL. 42, NO. 9, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 1. Estimated primary and secondary contributions compared with measured organic carbon for March 2004 through February 2005. analyzing ambient samples for the appropriate organic tracer compounds. Kleindienst et al. (25) applied the secondary organic tracer method to ambient samples collected in Research Triangle Park, North Carolina, throughout 2003. Contributions from isoprene, R-pinene, β-caryophyllene, and toluene were estimated by applying the laboratory-generated mass fractions to tracer compounds measured in 33 ambient samples. The results suggested that SOC from these four sources contributed from 18 to 69% of the measured organic carbon, with the three biogenic sources showing a pronounced seasonal dependence. In the present study, monthly composite samples from five Midwestern sampling locations were analyzed in order to examine the contributions of various sources to the ambient organic carbon concentrations. A CMB approach was used to estimate contributions from several primary sources, while the secondary organic tracer technique is used 3304
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to estimate the contributions of secondary organic carbon formed from isoprene, R-pinene, β-caryophyllene, and toluene. The combined estimates of the primary and secondary contributions are evaluated through comparison with the total measured organic carbon.
Experimental Section Sample Collection. Ambient samples were collected at five sampling sites in the Midwestern United States from March 2004 until February 2005. Samples were collected at one rural site, Bondville, Illinois, and four urban sites: East St. Louis, Illinois; Detroit, Michigan; Cincinnati, Ohio; and Northbrook, Illinois. The sampling protocols used were similar to those described previously by Bae et al. (27). Each sampling period lasted 24 h and sampling was conducted on a 1 in 6 day sampling schedule. The 24-h samples were assembled into monthly composites for each individual sampling site, each spanning 3-6 individual sampling periods. Samples were
FIGURE 2. Detailed secondary contributions to ambient PM2.5 in Bondville, Northbrook, Cincinnati, Detroit, and East St. Louis for March 2004 through February 2005. collected using high-volume PM2.5 samplers operated at 92 L min-1. Each sampler consisted of a PM2.5 cyclone (URG, Chapel Hill, NC) followed by a single 90-mm precombusted quartz filter (Pall-Life Sciences, East Hills, NY). OC/EC Measurements. The monthly composites from each of the five field sites were analyzed for organic carbon and elemental carbon using the thermal-optical method described by Birch and Cary (28). A 1.45 cm2 punch was taken from each 90-mm quartz filter for analysis, including field blanks. The OC/EC analysis used protocols described previously by Schauer et al. (29). Volume-weighted averages of the OC and EC from each individual filter were used to calculate composite OC and EC concentrations. Analysis of Primary Contributions. Monthly composites from each of the five field sites were extracted and analyzed by GC-MS. The methods used are described only briefly here, but similar methods have been reported previously (21). One-
sixth of each filter was used for this analysis, and field blanks were analyzed in parallel with the filter composites. The monthly composites were spiked with isotopically labeled internal standards before being Soxhlet extracted using 1:1 methanol and dichloromethane. The extracts were then concentrated by rotary evaporation and nitrogen blowdown to 150 µL then derivatized with diazomethane to methylate acid groups prior to analysis by GC-MS. A chemical mass balance model was run using the concentrations of selected compounds measured in the composites to estimate primary contributions from several potential sources. Motor vehicle exhaust profiles for both gasoline-powered and diesel-powered vehicles were taken from a gasoline-diesel split study (13). An average profile from Fine et al. (10) was used to estimate biomass burning contributions, while profiles for vegetative detritus and natural gas combustion were drawn from Rogge et al. (16) VOL. 42, NO. 9, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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and Hildemann et al. (15), respectively. The soil profile was generated specifically for this study using a soil sample collected at Bondville. This soil sample was dried and dispersed into a dilution chamber. The PM2.5 fraction was then collected on a filter for further characterization, including metals analysis by ICP-MS. The resulting suspended soil profile is presented in Table S1 in the Supporting Information. The uncertainties associated with this analytical method have been examined previously by Manchester-Neesvig et al. (30). Further analyses of the sensitivity of the CMB approach to uncertainties in various source profiles have been conducted by Sheesley et al. (31) and Lough and Schauer (32). Analysis of Secondary Contributions. The monthly composites were analyzed by GC-MS using the method described previously by Kleindienst et al. (25). Insufficient filter material was available in two cases: the January sampling periods for Bondville and East St. Louis. For the remaining sampling periods, one-third of each filter was employed in this analysis, and field blanks were analyzed in parallel with the filter composites. The monthly composites were sonicated for 1 h using 50 mL of a 1:1 (v/v) dichloromethane and methanol mixture. Prior to the extraction, cis-ketopinic acid and d50-tetracosane were added as internal and recovery standards, respectively. Filter extracts were rotary evaporated to 1 mL, then evaporated to dryness under a gentle stream of ultrapure nitrogen. The samples were then derivatized with N,O-bis(trimethylsilyl)-trifluoroacetamide (BSTFA, with 1% trimethylchlorosilane) in the presence of pyridine to silylate hydroxyl groups prior to analysis by GC-ITMS in the methane-CI mode. The concentrations of the tracer compounds were measured as ketopinic acid. A summary of the organic tracers used and the calculated mass fractions for each hydrocarbon precursor is provided in Table S2 in the Supporting Information.
Results The estimated primary contributions obtained through the CMB analysis are provided for reference in Table S3 in the Supporting Information. Concentrations of the individual secondary organic tracers were measured using the method described by Kleindienst et al. (25), and are presented on a monthly basis for the five field sites in Tables S4 through S8 in the Supporting Information. Using the laboratory-generated mass fractions (Table S2), these tracer concentrations were then converted into estimated contributions from SOA derived from isoprene, R-pinene, β-caryophyllene, and toluene. However, the use of a single value for the mass fraction of each individual hydrocarbon cannot fully capture the wide range of potential compounds, mechanisms, or atmospheric conditions involved in SOA formation in the ambient environment. The SOC contributions calculated using these single-hydrocarbon, laboratory-generated mass fractions must be considered to be estimated values, and these estimates are subject to significant uncertainties. For example, Kleindienst et al. (25) reported standard deviations of 25% for the laboratory-generated isoprene mass fraction, 48% for R-pinene, 22% for β-caryophyllene, and 33% for the toluene mass fraction. Other potential uncertainties are discussed in greater detail in Kleindienst et al. (25). The total estimated primary organic carbon (POC) and secondary organic carbon (SOC) contributions for each of the monthly composites in the five locations are presented in Figure 1. In addition, the total measured organic carbon (OC) is displayed for comparison with the estimated values. In most cases, the total apportioned carbon concentrations correlated well with the measured OC. The sums of the estimated POC and SOC concentrations were within 33% of the measured OC concentrations in 50 of the 60 monthly 3306
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TABLE 1. Seasonal and Annual SOC Averages in µg m-3 Mar-May Jun-Aug Sep-Nov Dec-Feb annual Bondville isoprene β-caryophyllene R-pinene toluene
0.25 0.09 0.14 0.12
0.89 0.14 0.42 0.25
0.03 0.12 0.12 0.09
0.02 0.13 0.13 0.12
0.32 0.12 0.21 0.15
Northbrook isoprene β-caryophyllene R-pinene toluene
0.12 0.18 0.16 0.12
0.50 0.14 0.32 0.21
0.24 0.22 0.16 0.13
0.01 0.21 0.05 0.06
0.22 0.18 0.17 0.13
Cincinnati isoprene β-caryophyllene R-pinene toluene
0.42 0.09 0.16 0.16
1.27 0.15 0.37 0.29
0.56 0.20 0.16 0.13
0.01 0.14 0.05 0.02
0.56 0.14 0.18 0.15
Detroit isoprene β-caryophyllene R-pinene toluene
0.07 0.26 0.20 0.19
0.69 0.31 0.51 0.33
0.23 0.41 0.27 0.18
0.00 0.22 0.04 0.07
0.25 0.30 0.25 0.19
East St. Louis isoprene β-caryophyllene R-pinene toluene
0.02 0.06 0.04 0.06
1.05 0.08 0.20 0.22
2.18 0.07 0.32 0.26
0.07 0.14 0.13 0.15
0.90 0.09 0.18 0.18
composite samples analyzed. The estimated concentrations were more than 33% below the measured values in four samples: Bondville in April, September, and January and East St. Louis in May. The OC concentrations exceeded the measured values by more than 33% in six samples: Bondville in June and East St. Louis in August, September, October, November, and December. The measured OC concentrations ranged from 1.2 to 2.6 µg C m-3 at the rural site, Bondville, and from 1.7 to 5.7 µg C m-3 at the urban sites. The total primary contributions are relatively low in Bondville ( 0.63). The slope of the regression fits ranged from 0.73 to 1.1, indicating that nearly all of the measured OC is being apportioned to specific sources. A poor correlation was observed for the 11 monthly samples available for Bondville (R 2 ) 0.16), but this fit is
FIGURE 3. Comparison of estimated OC (primary and secondary contributions) and measured OC for Bondville, Northbrook, Cincinnati, and Detroit. VOL. 42, NO. 9, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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heavily influenced by a single data point (September). If this point is excluded, the correlation improves substantially (R 2 ) 0.75). A reasonable correlation is obtained for East St. Louis (R 2 ) 0.60), but the slope of the fit (2.16) suggests that the combined analysis method is overestimating OC in this location. A recent study by Jaeckels et al. (33) identified several emission point sources in the St. Louis area. These point sources contained a number of compounds used as tracers in the CMB analysis, which are typically associated with mobile source or combustion profiles. Since no CMB profiles were available for apportionment of these specific point sources, their presence during the sampling would likely cause other POC contribution estimates obtained with the CMB method to be overstated at the East St. Louis site. Although it appears unlikely that these local sources are generating compounds that would influence the secondary organic tracer analysis, it is also worth noting that the estimated isoprene SOC concentrations obtained for the East St. Louis sampling location were markedly different from those of the other four sampling sites. While isoprene contributions rose in May at the other four sampling locations investigated in this study, the increase in isoprene contribution in East St. Louis did not occur until July. These isoprene contributions also reached monthly average concentrations as high as 3.0 µg C m-3, more than 60% higher than any of the other sites. While these high estimated isoprene contributions could potentially represent an interference in the organic tracer analysis, there is also evidence to suggest that East St. Louis may be affected by unusually high isoprene emissions. Wiedinmyer et al. (34) have reported significant isoprene emissions originating from the Ozark Mountains to the west of St. Louis. This potent local emission source may have a strong influence on SOA formation in nearby downwind locations, including St. Louis. This potential for large isoprene emissions may make the data from East St. Louis particularly susceptible to uncertainties inherent in the isoprene mass fraction. The mass fraction for isoprene reported by Kleindienst et al. (25) has a standard deviation of approximately 25%, which could have a significant impact on a sample containing high concentrations of isoprene tracer compounds. Evaluation of Contribution Estimates from Multiple Sites. Figure 3 presents a correlation analysis of the sum of the monthly estimates of POC and SOC versus the measured OC for Bondville, Northbrook, Cincinnati, and Detroit. The data from East St. Louis has been omitted here due to the frequent overestimation of the measured OC described above. A regression analysis on these 47 monthly averages generates an R 2 of 0.73 and a slope close to one. Although the regression analysis suggests a 1-to-1 correlation between the estimated contributions and the measured OC, this does not necessarily imply that all contributing sources of POC or SOC have been fully identified. For example, the secondary organic tracer analysis addresses individual hydrocarbons that are believed to be emitted in significant quantities and to contribute significantly to SOC in the ambient atmosphere, but other, similar hydrocarbons (i.e., other monoterpenes, sesquiterpenes, and aromatics) are also suspected of contributing to ambient PM2.5. Kleindienst et al. (25) have noted, however, that there is some evidence that the tracer compounds used for R-pinene may also be produced from other monoterpenes, such as β-pinene and d-limonene (35), while the tracer compound for toluene may be generated from certain other aromatic compounds, such as m-xylene (25). If other compounds are capable of producing these tracers with similar yields, then the contribution estimates presented here for R-pinene, β-caryophyllene, and toluene SOC may already incorporate contributions from the broader classes of monoterpenes, sesquiterpenes, and aromatics. 3308
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While considerable additional research is required to determine the extent to which these single-compound mass fractions may represent broader classes of hydrocarbons, particularly among the aromatics and sesquiterpenes, the impact of additional contributing hydrocarbons would not necessarily have a pronounced impact. The estimated contributions from toluene and β-caryophyllene are both typically less than 10% of the total measured OC, with modest seasonal variations. Contributions from additional aromatic compound or sesquiterpenes would probably have a relatively limited impact on the overall correlation between estimated and measured OC concentrations. Although there are still uncertainties associated with both the CMB method and the secondary organic tracer technique, the strong correlations between the estimates and the measured OC at these four sampling sites suggest that the secondary organic tracer technique may be a valuable addition to the more established CMB method for source apportionment of ambient PM2.5.
Acknowledgments The U.S. Environmental Protection Agency through its Office of Research and Development funded and collaborated in the research described here under Contract EP-D-05-065 to Alion Science and Technology. The manuscript has been subjected to external peer review and has been cleared for publication. Mention of trade names or commercial products does not constitute an endorsement or recommendation for use. Funding for this study was also provided by the Lake Michigan Air Directors Consortium, LADCO, (STI-9035202942-FR). We thank Hilary Hafner and Steve Brown of Sonoma Technology, Inc. for their work coordinating the Midwest Urban Organics Study. We also thank Jason Wolf, Ofori Bandoh, Chris Ewing, Dan Short, Clyde Sweet, Mike Caughey, David Gay, Jerry Mazurek, Min-Suk Bae, and Jeff DeMinter for their help with sampling. Finally, we thank Jay Turner, director of the St. Louis Supersite.
Supporting Information Available Additional details provided in eight tables. This information is available free of charge via the Internet at http:// pubs.acs.org.
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