Determination of PM2.5 sources using time-resolved integrated source and receptor models

Multivariate statistical techniques are applied to particulate matter (PM) and meteorological data to identify the sources responsible for evening PM spikes at Sunland Park, NM (USA). The statistical techniques applied are principal components analysis (PCA), redundancy analysis (RDA), and absolute principal components scores analysis (APCSA), and the data evaluated are 3-h average (6–9 p.m.) PM_2.5 mass and chemical composition and 1-h average PM_2.5 and PM₁₀ mass and environmental data collected in the winter of 2002. Although the interpretation of the data was complicated by the presence of sources which are likely changing in time (e.g. brick kilns), the multivariate analyses indicate that the evening high PM_2.5 is associated with burning-activities occurring to the south of Sunland Park, and these emissions are characterized by elevated Sb, Cl⁻, and elemental carbon; ∼68% of the PM_2.5 mass can be attributed to this source. The PM₁₀ evening peaks, on the other hand, are mainly caused by resuspended dust generated by vehicular movements south of the site and transported by the local terrain-induced drainage flow.     

PM source identification at Sunland Park, New Mexico, using a simple heuristic meteorological and chemical analysis

The causes for evening low-wind PM10 and PM2.5 peaks at Sunland Park, NM, were investigated by using wind sector analysis and by assessing relationships between PM loadings and meteorological parameters through canonical ordination analysis. Both PM10 and PM2.5 concentrations during the evening hours accounted for approximately 50% of their respective 24-hr averages, and the PM10 was mainly composed of coarse material (PM10-2.5 amounted to 77% of PM10). A wind sector analysis based on data from three surface meteorological monitoring stations in the region narrowed the potential source region for PM10 and PM2.5 to an area within a few kilometers south of Sunland Park. Canonical ordination analysis confirmed that the peak frequently occurred under stable conditions with weak southerly winds. Chemical analyses of PM showed that elemental and organic carbon (EC and OC, respectively) dominate PM2.5 and inorganic elements dominate PM10-2.5. The combined data for EC/OC, geologic elements, and various trace elements indicate that under low wind and stable conditions, traffic-related PM emissions (motor vehicle exhausts and re-suspended road dust) from the south of the site are the most likely sources for the evening PM10 and PM2.5 peaks.     

贵阳市污染源PM2.5中铂族元素的分布特征

为掌握贵阳市污染源PM2.5中铂族元素(PGE)的分布特征,采集7类主要污染源42个PM2.5样品,采用同位素稀释/电感耦合等离子体质谱法定量测定PGE中铂(Pt)、钯(Pd)、铑(Rh)的含量.结果表明:(1)金属冶炼尘PM2.5中Pt、Pd、Rh平均值分别为2186.136、1239.827、346.172 ng/...     

Source contributions to fine particulate matter in an urban atmosphere

This paper proposes a practical method for estimating source attribution by using a three-step methodology. The main objective of this study is to explore the use of the three-step methodology for quantifying the source impacts of 24-h PM2.5 particles at an urban site in Seoul, Korea. 12-h PM2.5 samples were collected and analyzed for their elemental composition by ICP-AES/ICP-MS/AAS to generate the source composition profiles. In order to assess the daily average PM2.5 source impacts, 24-h PM2.5 and polycyclic aromatic hydrocarbons (PAH) ambient samples were simultaneously collected at the same site. The PM2.5 particle samples were then analyzed for trace elements. Ionic and carbonaceous species concentrations were measured by ICP-AES/ICP-MS/AAS, IC, and a selective thermal MnO2 oxidation method. The 12-h PM2.5 chemical data was used to estimate possible source signatures using the principal component analysis (PCA) and the absolute principal component scores method followed by the multiple linear regression analysis. The 24-h PM2.5 source categories were extracted with a combination of PM2.5 and some PAH chemical data using the PCA, and their quantitative source contributions were estimated by chemical mass balance (CMB) receptor model using the estimated source profiles and those in the literature. The results of PM2.5 source apportionment using the 12-h derived source composition profiles show that the CMB performance indices; chi2, R2, and percent of mass accounted for are 2.3%, 0.97%, and 100.7%, which are within the target range specified. According to the average PM2.5 source contribution estimate results, motor vehicle exhaust was the major contributor at the sampling site, contributing 26% on average of measured PM2.5 mass (41.8 microg m-3), followed by secondary sulfate (23%) and nitrate (16%), refuse incineration (15%), soil dust (13%), field burning (4%), oil combustion (2.7%), and marine aerosol (1.3%). It can be concluded that quantitative source attribution to PM2.5 in an urban area where source profiles have not been developed can be estimated using the proposed three-step methodology approach.     

Exposure of trucking company workers to particulate matter during the winter

This study analyzed the workplace area concentrations and the personal exposure concentrations to fine particulate (PM_2.5), elemental carbon (EC), and organic carbon (OC) measured during the winter period in trucking companies. The averaged personal exposure concentrations at breathing zones of workers are much greater than those of the microenvironment concentrations. The highest difference between the area (microenvironment) and personal exposure concentrations was in the PM_2.5 concentrations followed by the OC concentrations. The area concentrations of PM_2.5, EC, and OC at a large terminal were higher than those at a small one. The highest area concentrations of PM_2.5, EC, and OC were observed in the shop areas followed by pick-up and delivery (P&D) areas. The area concentrations and personal exposure to PM_2.5, EC, and OC in the shop and P&D areas which are highly affected by diesel engine exhaust emissions were much higher than those in the docks which are significantly affected by liquefied petroleum gas (LPG) engine exhaust emissions. The highest EC fraction to the total carbon (EC + OC) concentrations was observed in the shops, while the lowest one was identified in the offices. The personal exposure of the smoking workers to PM_2.5 and OC was much higher than that of the non-smoking workers. However, the smoking might not significantly contribute to the personal exposure to EC. There were significant correlations between the PM_2.5 and OC concentrations in both the area and personal exposure concentrations. However, significant correlations between the PM_2.5 and EC concentrations and between the OC and EC concentrations were not identified.     

Urban airborne particulate: genotoxicity evaluation of different size fractions by mutagenesis tests on microorganisms and comet assay

The genotoxic effects of different size fractions of airborne particulate (Total, PM₁₀ and PM_2.5), extracted with acetone or toluene, were evaluated by: the Ames plate test (TA98 and TA100 strains, w/o S9), gene conversion and reversion (w/o endogenous metabolic activation) in the Saccharomyces cerevisiae D7 strain, and the comet assay on human leukocytes. The data on human leukocytes confirm the sensitivity of the comet assay and its applicability to assess genotoxicity in environmental samples. The PM_2.5 fraction of airborne particulate generally shows the highest concentration of DNA-damaging compounds. Genotoxic response, in all the test systems applied, is highly dependent on extraction solvent used. Acetone seems to extract compounds with more similar genotoxic responses in the three test systems used than toluene extracts. Toluene appears to extract air pollutants genotoxic on yeast and leukocytes but is mainly cytotoxic on Salmonella.     

Comparison of fine particles and the relationship between particle variations and meteorology at an urban site and a remote site in the Eastern United States

This study compared the variations in the mass of certain particles at an urban site, Washington, DC, and at a remote site, Shenandoah National Park, VA, in the eastern United States. Seven years (1991-1997) of Interagency Monitoring of Protected Visual Environments (IMPROVE) fine particulate matter (PM2.5), PM10, coarse fraction, SO4(2-), and total sulfur data were used for this study together with available meteorology/climatology data. Various statistical modeling and analysis procedures, including time series analysis, factor analysis, and regression modeling, were employed. Time series of the constituents were divided into four terms: the long-term mean, the intraannual perturbation, the interannual perturbation, and the synoptic perturbation. PM2.5 at the two sites made up approximately 72% of the total mass for PM10, and the coarse fraction made up the remaining 28%, on average. Thirty-one percent of the PM2.5 at the DC site and 42% at the Shenandoah site was SO4(2-), based on average data for the entire period. At the DC site, the two main contributors to the constituent mass were the long-term mean and the synoptic perturbation terms, and at the Shenandoah site, they were the long-term mean and the intra-annual perturbation terms. This suggested that the constituent mass at the two sites was affected by very different processes. The terms that provided the principal contribution to the constituent mass at the two sites were studied in detail. At the DC site, dew point trends, a climate variable, were the primary driver of the 7-year trends for PM2.5, PM10, the coarse fraction, and total sulfur, and SO2 emission trends were the primary driver of the trends for SO4(2-). SO2 emission trends influenced the trends for PM2.5 and total sulfur, appearing as the second term in the model, but only parameters dealing with climate trends had significant effects on the trends for PM10 and the coarse fraction. At the Shenandoah site, only parameters dealing with climate trends affected long-term particle trends.     

Characterization of atmospheric particulate and metallic elements at Taichung Harbor near Taiwan Strait during 2004-2005

Air aerosol samples for TSP (total suspended particulate), coarse particulate (particle matter with aerodynamical diameter 2.5–10 μm, PM_2.5–10), fine particulate (particle matter with aerodynamical diameter <2.5 μm, PM_2.5) and metallic elements were collected during March 2004 to January 2005 at TH (Taichung Harbor) in central Taiwan. The seasonal variation average concentration of TSP (total suspended particulate), coarse particulate (particle matter with aerodynamical diameter 2.5–10 μm, PM_2.5–10) and fine particulate (particle matter with aerodynamical diameter <2.5 μm, PM_2.5) were in the range 132–171.1 μg m⁻³ and 43–49.5 μg m⁻³, respectively. Seasonal variation of metallic elements Cu, Mn, Zn and Fe in the TSP (total suspended particulate) shows that higher concentration was observed during spring. Seasonal variation of metallic elements Pb, Cr and Mg in the TSP (total suspended particulate) shows that higher concentration was observed during winter. The average metallic element TSP (total suspended particulate) concentration order was Fe > Zn > Mg > Cu > Cr > Mn > Pb in spring. In addition, at the TH sampling site, the average concentration variation of TSP (total suspended particulate) displayed the following order: spring > winter > autumn > summer. However, the average concentration variation of coarse particulate (particle matter with aerodynamical diameter 2.5–10 μm, PM_2.5–10) displayed the following order: spring > winter > summer > autumn. Finally, the average concentration variations of fine particulate (particle matter with aerodynamical diameter <2.5 μm, PM_2.5) were in the following order: winter > spring > summer > autumn at the TH sample site.     

Apportionment of ambient primary and secondary fine particulate matter at the Pittsburgh National Energy Laboratory particulate matter characterization site using positive matrix factorization and a potential source contributions function analysis

Fine particulate matter (PM2.5) concentrations associated with 202 24-hr samples collected at the National Energy Technology Laboratory (NETL) particulate matter (PM) characterization site in south Pittsburgh from October 1999 through September 2001 were used to apportion PM2.5 into primary and secondary contributions using Positive Matrix Factorization (PMF2). Input included the concentrations of PM2.5 mass determined with a Federal Reference Method (FRM) sampler, semi-volatile PM2.5 organic material, elemental carbon (EC), and trace element components of PM2.5. A total of 11 factors were identified. The results of potential source contributions function (PSCF) analysis using PMF2 factors and HYSPLIT-calculated back-trajectories were used to identify those factors associated with specific meteorological transport conditions. The 11 factors were identified as being associated with emissions from various specific regions and facilities including crustal material, gasoline combustion, diesel combustion, and three nearby sources high in trace metals. Three sources associated with transport from coal-fired power plants to the southeast, a combination of point sources to the northwest, and a steel mill and associated sources to the west were identified. In addition, two secondary-material-dominated sources were identified, one was associated with secondary products of local emissions and one was dominated by secondary ammonium sulfate transported to the NETL site from the west and southwest. Of these 11 factors, the four largest contributors to PM2.5 were the secondary transported material (dominated by ammonium sulfate) (47%), local secondary material (19%), diesel combustion emissions (10%), and gasoline combustion emissions (8%). The other seven factors accounted for the remaining 16% of the PM2.5 mass. The findings are consistent with the major source of PM2.5 in the Pittsburgh area being dominated by ammonium sulfate from distant transport and so decoupled from local activity emitting organic pollutants in the metropolitan area. In contrast, the major local secondary sources are dominated by organic material.     

Sources of fine urban particulate matter in Detroit, MI

Data from the speciation trends network (STN) was used to evaluate the amount and temporal patterns of particulate matter originating from local industrial sources and long-range transport at two sites in Detroit, MI: Allen Park, MI, southwest of both Detroit and the areas of heavy industrial activity; Dearborn, MI, located on the south side of Detroit near the most heavily industrialized region. Using positive matrix factorization (PMF) and comparing source contributions at Allen Park to those in Dearborn, contributions made by local industrial sources (power plants, coke refineries, iron smelting, waste incineration), local area sources (automobile and diesel truck) and long range sources of PM(2.5) can be distinguished in greater Detroit. Overall, the mean mass concentration measured at Dearborn was 19% higher than that measured at Allen Park. The mass at Allen Park was apportioned as: secondary sulfate 31%, secondary nitrate 28%, soil 8%, mixed aged sea and road salts 4%, gasoline 15%, diesel 4%, and biomass burning 3%. At Dearborn the mass was apportioned as: secondary sulfate 25%, secondary nitrate 20%, soil 12%, mixed aged sea and road salts 4%, gasoline 20%, diesel 8%, iron and steel, 5%, and mixed industrial 7%. The impact of the iron and steel, soil, and mixed aged sea and road salt was much higher at the Dearborn site than at the Allen Park site, suggesting that close proximity to a local industrial complex has a direct negative impact on local air quality.     

PM2.5 chemical source profiles for vehicle exhaust, vegetative burning, geological material, and coal burning in Northwestern Colorado during 1995

PM_2.5 (particles with aerodynamic diameters less than 2.5 μm) chemical source profiles applicable to speciated emissions inventories and receptor model source apportionment are reported for geological material, motor vehicle exhaust, residential coal (RCC) and wood combustion (RWC), forest fires, geothermal hot springs; and coal-fired power generation units from northwestern Colorado during 1995. Fuels and combustion conditions are similar to those of other communities of the inland western US. Coal-fired power station profiles differed substantially between different units using similar coals, with the major difference being lack of selenium in emissions from the only unit that was equipped with a dry limestone sulfur dioxide (SO₂) scrubber. SO₂ abundances relative to fine particle mass emissions in power plant emissions were seven to nine times higher than hydrogen sulfide (H₂S) abundances from geothermal springs, and one to two orders of magnitude higher than SO₂ abundances in RCC emissions, implying that the SO₂ abundance is an important marker for primary particle contributions of non-aged coal-fired power station contributions. The sum of organic and elemental carbon ranged from 1% to 10% of fine particle mass in coal-fired power plant emissions, from 5% to 10% in geological material, >50% in forest fire emissions, >60% in RWC emissions, and >95% in RCC and vehicle exhaust emissions. Water-soluble potassium (K⁺) was most abundant in vegetative burning profiles. K⁺/K ratios ranged from 0.1 in geological material profiles to 0.9 in vegetative burning emissions, confirming previous observations that soluble potassium is a good marker for vegetative burning.     

Regional transport and urban contributions to fine particle concentrations in southeastern Canada

The impact of various atmospheric transport directions on ambient fine particle (PM2.5) concentrations at several sites in southeastern Canada was estimated (for May-September) using back-trajectory analysis. Three-day back trajectories (four per day) were paired with 6-hr average PM2.5 mass concentrations measured using tapered element oscillating microbalances (TEOM). PM2.5 concentrations at rural locations in the region were affected by nonlocal sources originating in both Canada and the United States. Comparison of sites revealed that, on average, the local contribution to total PM2.5 in the greater Toronto area (GTA) is approximately 30-35%. At each location, average PM2.5 concentrations under south/southwesterly flow conditions were 2-4 times higher than under the corresponding northerly flow conditions. The chemical composition of both urban and rural PM2.5 was determined during two separate 2-week spring/summer measurement campaigns. Components identified included SO4(2-) NO3-, NH4+, black carbon and organic carbon (OC), and trace elements. Higher particle mass at the urban Toronto site was composed of a higher proportion of all components. However, black carbon, NO3-, NaCl, and trace elements were found to be the most enriched over the rural/regional background levels.     

Short-term temporal variation in PM2.5 mass and chemical composition during the Atlanta Supersite Experiment, 1999

Measurements in urban Atlanta of transient aerosol events in which PM2.5 mass concentrations rapidly rise and fall over a period of 3-6 hr are reported. The data are based on new measurement techniques demonstrated at the U.S. Environmental Protection Agency (EPA) Atlanta Supersite Experiment in August 1999. These independent instruments for aerosol chemical speciation of NO3-, SO4(2-), NH4+, and organic and elemental carbon (OC and EC), reconstructed the observed hourly dry PM2.5 mass to within 20% or better. Data from the experiment indicated that transient PM2.5 events were ubiquitous in Atlanta and were typically characterized by a sudden increase of EC (soot) and OC in the early morning or SO4(2-) in the late afternoon. The frequent temporal decoupling of these events provides insights into their origins, suggesting mobile sources in metro Atlanta as the main contributor to early morning PM2.5 and more regionally located point SO2 sources for afternoon PM2.5 events. The transient events may also have health implications. New data suggest that short-term PM2.5 exposures may lead to adverse health effects. Standard integrated filter-based techniques used in PM2.5 compliance monitoring networks and in most past PM2.5 epidemiologic studies collect samples over 24-hr periods and thus are unable to capture these transient events. Moreover, health-effects studies that focus on daily PM2.5 mass alone cannot evaluate the health implications of the unique and variable chemical properties of these episodes.     

Source apportionment of airborne particulate matter in Southeast Texas using a source-oriented 3D air quality model

A nested version of the source-oriented externally mixed UCD/CIT model was developed to study the source contributions to airborne particulate matter (PM) during a two-week long air quality episode during the Texas 2000 Air Quality Study (TexAQS 2000). Contributions to primary PM and secondary ammonium sulfate in the Houston–Galveston Bay (HGB) and Beaumont–Port Arthur (BPA) areas were determined.The predicted 24-h elemental carbon (EC), organic compounds (OC), sulfate, ammonium ion and primary PM_2.5 mass are in good agreement with filter-based observations. Predicted concentrations of hourly sulfate, ammonium ion, and primary OC from diesel and gasoline engines and biomass burning organic aerosol (BBOA) at La Porte, Texas agree well with measurements from an Aerodyne Aerosol Mass Spectrometer (AMS).The UCD/CIT model predicts that EC is mainly from diesel engines and majority of the primary OC is from internal combustion engines and industrial sources. Open burning contributes large fractions of EC, OC and primary PM_2.5 mass. Road dust, internal combustion engines and industries are the major sources of primary PM_2.5. Wildfire dominates the contributions to all primary PM components in areas near the fires. The predicted source contributions to primary PM are in general agreement with results from a chemical mass balance (CMB) model. Discrepancy between the two models suggests that further investigations on the industrial PM emissions are necessary.Secondary ammonium sulfate accounts for the majority of the secondary inorganic PM. Over 80% of the secondary sulfate in the 4 km domain is produced in upwind areas. Coal combustion is the largest source of sulfate. Ammonium ion is mainly from agriculture sources and contributions from gasoline vehicles are significant in urban areas.     

The relationship between real-time and time-integrated coarse (2.5-10 micrm), intermodal (1-2.5 microm), and fine (<2.5 microm) particulate matter in the Los Angeles basin

A periodic review of the National Ambient Air Quality Standards for Particulate Matter by the U.S. Environmental Protection Agency (EPA) will assess the standards with respect to levels, particle size, and averaging times. Some members of the scientific community in the United States and Europe have suggested the use of PM1 instead of PM2.5 as the fine particle measurement standard. This proposed standard is intended to reduce the influence of coarse particle sources on PM2.5, because some evidence suggests that PM1-2.5 is dominated by coarse particulate matter (PM) sources. In this study, coarse (PM2.5-10), intermodal (PM1-2.5), and fine (PM2.5) mass concentrations at four different sites are measured with continuous and time-integrated sampling devices. The main objective is to compare variations in these three size ranges while considering the effects of location, sources, weather, wind speed, and wind direction. Results show strong correlations between PM1 and intermodal PM in receptor sites. The contribution of PM1-2.5 to PM2.5 is highest in the summer months, most likely due to enhanced long-range transport. Coarse PM is poorly correlated with intermodal PM. Continuous data suggest that PM1 is growing into PM1-2.5 via complex processes involving stagnation of the aerosol during high relative humidity conditions, followed by advection during daytime hours.     

Effects of wind direction on coarse and fine particulate matter concentrations in southeast Kansas

Field data for coarse particulate matter ([PM] PM10) and fine particulate matter (PM2.5) were collected at selected sites in Southeast Kansas from March 1999 to October 2000, using portable MiniVol particulate samplers. The purpose was to assess the influence on air quality of four industrial facilities that burn hazardous waste in the area located in the communities of Chanute, Independence, Fredonia, and Coffeyville. Both spatial and temporal variation were observed in the data. Variation because of sampling site was found to be statistically significant for PM10 but not for PM2.5. PM10 concentrations were typically slightly higher at sites located within the four study communities than at background sites. Sampling sites were located north and south of the four targeted sources to provide upwind and downwind monitoring pairs. No statistically significant differences were found between upwind and downwind samples for either PM10 or PM2.5, indicating that the targeted sources did not contribute significantly to PM concentrations. Wind direction can frequently contribute to temporal variation in air pollutant concentrations and was investigated in this study. Sampling days were divided into four classifications: predominantly south winds, predominantly north winds, calm/variable winds, and winds from other directions. The effect of wind direction was found to be statistically significant for both PM10 and PM2.5. For both size ranges, PM concentrations were typically highest on days with predominantly south winds; days with calm/variable winds generally produced higher concentrations than did those with predominantly north winds or those with winds from "other" directions. The significant effect of wind direction suggests that regional sources may exert a large influence on PM concentrations in the area.     

Fine particulate matter and visibility in the Lake Tahoe Basin: chemical characterization, trends, and source apportionment

Speciated PM2.5 (particulate matter with an aerodynamic diameter相似文献   

The Steubenville comprehensive air monitoring program (SCAMP): overview and statistical considerations

Average concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5) in Steubenville, OH, have decreased by more than 10 microg/m3 since the landmark Harvard Six Cities Study associated the city's elevated PM2.5 concentrations with adverse health effects in the 1980s. Given the promulgation of a new National Ambient Air Quality Standard (NAAQS) for PM2.5 in 1997, a current assessment of PM2.5 in the Steubenville region is warranted. The Steubenville Comprehensive Air Monitoring Program (SCAMP) was conducted from 2000 through 2002 to provide such an assessment. The program included both an outdoor ambient air monitoring component and an indoor and personal air sampling component. This paper, which is the first in a series of four that will present results from the outdoor portion of SCAMP, provides an overview of the outdoor ambient air monitoring program and addresses statistical issues, most notably autocorrelation, that have been overlooked by many PM2.5 data analyses. The average PM2.5 concentration measured in Steubenville during SCAMP (18.4 microg/m3) was 3.4 microg/m3 above the annual PM2.5 NAAQS. On average, sulfate and organic material accounted for approximately 31% and 25%, respectively, of the total PM2.5 mass. Local sources contributed an estimated 4.6 microg/m3 to Steubenville's mean PM2.5 concentration. PM2.5 and each of its major ionic components were significantly correlated in space across all pairs of monitoring sites in the region, suggesting the influence of meteorology and long-range transport on regional PM2.5 concentrations. Statistically significant autocorrelation was observed among time series of PM2.5 and component data collected at daily and 1-in-4-day frequencies during SCAMP. Results of spatial analyses that accounted for autocorrelation were generally consistent with findings from previous studies that did not consider autocorrelation; however, these analyses also indicated that failure to account for autocorrelation can lead to incorrect conclusions about statistical significance.     

Source identification of personal exposure to fine particulate matter using organic tracers

Personal exposure to fine particulate matter (PM2.5) is due to both indoor and outdoor sources. Contributions of sources to personal exposure can be quite different from those observed at ambient sampling locations. The primary goal of this study was to investigate the effectiveness of using trace organic speciation data to help identify sources influencing PM2.5 exposure concentrations. Sixty-four 24-h PM2.5 samples were obtained on seven different subjects in and around Boulder, CO. The exposure samples were analyzed for PM2.5 mass, elemental and organic carbon, organic tracer compounds, water-soluble metals, ammonia, and nitrate. This study is the first to measure a broad distribution of organic tracer compounds in PM2.5 personal samples. PM2.5 mass exposure concentrations averaged 8.4 μg m^?3. Organic carbon was the dominant constituent of the PM2.5 mass. Forty-four organic species and 19 water-soluble metals were quantifiable in more than half of the samples. Fifty-four organic species and 16 water-soluble metals had measurement signal-to-noise ratios larger than two after blank subtraction.The dataset was analyzed by Principal Component Analysis (PCA) to determine the factors that account for the greatest variance. Eight significant factors were identified; each factor was matched to its likely source based primarily on the marker species that loaded the factor. The results were consistent with the expectation that multiple marker species for the same source loaded the same factor. Meat cooking was an important source of variability. The factor that represents meat cooking was highly correlated with organic carbon concentrations (r = 0.84). The correlation between ambient PM2.5 and PM2.5 exposure was relatively weak (r = 0.15). Time participants spent performing various activities was generally not well correlated with PCA factor scores, likely because activity duration does not measure emissions intensity. The PCA results demonstrate that organic tracers can aid in identifying factors that influence personal exposures to PM2.5.     

Analysis and apportionment of organic carbon and fine particulate matter sources at multiple sites in the midwestern United States

Speciated fine particulate matter (PM2.5) data collected as part of the Speciation Trends Network at four sites in the Midwest (Detroit, MI; Cincinnati, OH; Indianapolis, IN; and Northbrook, IL) and as part of the Interagency Monitoring of Protected Visual Environments program at the rural Bondville, IL, site were analyzed to understand sources contributing to organic carbon (OC) and PM2.5 mass. Positive matrix factorization (PMF) was applied to available data collected from January 2002 through March 2005, and seven to nine factors were identified at each site. Common factors at all of the sites included mobile (gasoline)/secondary organic aerosols with high OC, diesel with a high elemental carbon/OC ratio (only at the urban sites), secondary sulfate, secondary nitrate, soil, and biomass burning. Identified industrial factors included copper smelting (Northbrook, Indianapolis, and Bondville), steel/manufacturing with iron (Northbrook), industrial zinc (Northbrook, Cincinnati, Indianapolis, and Detroit), metal plating with chromium and nickel (Detroit, Indianapolis, and Bondville), mixed industrial with copper and iron (Cincinnati), and limestone with calcium and iron (Bondville). PMF results, on average, accounted for 96% of the measured PM2.5 mass at each site; residuals were consistently within tolerance (+/-3), and goodness-of-fit (Q) was acceptable. Potential source contribution function analysis helped identify regional and local impacts of the identified source types. Secondary sulfate and soil factors showed regional characteristics at each site, whereas industrial sources typically appeared to be locally influenced. These regional factors contributed approximately one third of the total PM2.5 mass, on average, whereas local mobile and industrial sources contributed to the remaining mass. Mobile sources were a major contributor (55-76% at the urban sites) to OC mass, generally with at least twice as much mass from nondiesel sources as from diesel. Regional OC associated with secondary sulfate and soil was generally low.