Determination of source contributions to ambient PM2.5 in Kaohsiung, Taiwan, using a receptor model

Ambient particulates of PM2.5 were sampled at three sites in Kaohsiung, Taiwan, during February and March 1999. In addition, resuspended PM2.5 collected from traffic tunnels, paved roads, fly ash of a municipal solid waste (MSW) incinerator, and seawater was obtained. All the samples were analyzed for twenty constituents, including water-soluble ions, organic carbon (OC), elemental carbon (EC), and metallic elements. In conjunction with local source profiles and the source profiles in the model library SPECIATE EPA, the receptor model based on chemical mass balance (CMB) was then applied to determine the source contributions to ambient PM2.5. The mean concentration of ambient PM2.5 was 42.69-53.68 micrograms/m3 for the sampling period. The abundant species in ambient PM2.5 in the mass fraction for three sites were OC (12.7-14.2%), SO4(2-) (12.8-15.1%), NO3- (8.1-10.3%), NH4+ (6.7-7.5%), and EC (5.3-8.5%). Results of CMB modeling show that major pollution sources for ambient PM2.5 are traffic exhaust (18-54%), secondary aerosols (30-41% from SO4(2-) and NO3-), and outdoor burning of agriculture wastes (13-17%).     

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.     

Mass-size distributions of particulate sulfate, nitrate, and ammonium in a particulate matter nonattainment region in southern Taiwan

Concentrations and distributions of three major water-soluble ion species (sulfate, nitrate, and ammonium) contained in ambient particles were measured at three sampling sites in the Kao-ping ambient air quality basin, Taiwan. Ambient particulate matter (PM) samples were collected in a Micro-orifice Uniform Deposit Impactor from February to July 2003 and were analyzed for water-soluble ion species with an ion chromatograph. The PM1/ PM2.5 and PM1/PM10 concentration ratios at the emission source site were 0.73 and 0.53 and were higher than those (0.68 and 0.48) at the background site because there are more combustion sources (i.e., industrial boilers and traffic) around the emission source site. Mass-size distributions of PM NO3- were found in both the fine and coarse modes. SO4(2-)and NH4+ were found in the fine particle mode (PM2.5), with significant fractions of submicron particles (PM1). The source site had higher PM1/PM10(79, 42, and 90%) and PM1/PM2.5 concentration ratios (90, 58, and 93%) for the three major inorganic secondary aerosol components (SO4(2-), NO3-, and NH4+) than the receptor site (65, 27, and 65% for PM1/PM10, 69, 51, and 70% for PM1/PM2.5. Results obtained in this study indicate that the PM1 (submicron aerosol particles) fraction plays an important role in the ambient atmosphere at both emission source and receptor sites. Further studies regarding the origin and formation of ambient secondary aerosols are planned.     

Spatial characteristics of fine particulate matter: identifying representative monitoring locations in Seattle, Washington

This study investigates how PM2.5 varies spatially and how these spatial characteristics can be used to identify potential monitoring sites that are most representative of the overall ambient exposures to PM2.5 among susceptible populations in the Seattle, WA, area. Data collected at outdoor sites at the homes of participants of a large exposure assessment study were used in this study. Harvard impactors (HIs) were used at 40 outdoor sites throughout the Seattle metropolitan area. Up to six sites at a time were monitored for 10 consecutive 24-hr average periods. A fixed-effect analysis of variance (ANOVA) model that included date and location effects was used to analyze the spatial variability of outdoor PM2.5 concentrations. Both date and location effects were shown to be highly significant, explaining 92% of the variability in outdoor PM2.5 measurements. The day-to-day variability was 10 times higher than the spatial variability between sites. The site mean square was more than twice the error mean square, showing that differences between sites, while modest, are potentially an important contribution to measurement error. Variances of the model residuals and site effects were examined against spatial characteristics of the monitoring sites. The spatial characteristics included elevation, distance from arterials, and distance from major PM2.5 point sources. Results showed that the most representative PM2.5 sites were located at elevations of 80-120 m above sea level, and at distances of 100-300 m from the nearest arterial road. Location relative to industrial PM2.5 sources is not a significant predictor of residential outdoor PM2.5 measurements. Additionally, for sites to be representative of the average population exposures to PM2.5 among those highly susceptible to the health effects of PM2.5, areas of high elderly population density were considered. These representative spatial characteristics were used as multiple, overlapping criteria in a Geographic Information System (GIS) analysis to determine where the most representative sites are located.     

Assessing the relationship between personal particulate and gaseous exposures of senior citizens living in Baltimore, MD

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (> 64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM2.5, PM10, SO4(2-), O3, NO2, SO2, and exhaust-related VOCs. Results of this study showed that longitudinal associations between ambient PM2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM2.5 exposures and resulting personal-ambient associations. Associations between personal PM2.5 exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM2.5 sources. Evidence for this was provided by SO4(2-) measurements, which can be thought of as a tracer for ambient PM2.5. For SO4(2-), personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM2.5 sources to personal PM2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments. Results also indicate that the potential for confounding by PM2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM2.5 exposures were not significantly correlated with personal exposures to PM2.5-10, PM2.5 of non-ambient origin, O3, NO2, and SO2. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM2.5 epidemiologic studies are unlikely to be due to confounding by the PM2.5 co-pollutants measured in this study.     

Influence of organic and inorganic markers in the source apportionment of airborne PM10 in Zaragoza (Spain) by two receptor models

Improving knowledge on the apportionment of airborne particulate matter will be useful to handle and fulfill the legislation regarding this pollutant. The main aim of this work was to assess the influence of markers in the source apportionment of airborne PM10, in particular, whether the use of particle polycyclic aromatic hydrocarbon (PAH) and ions provided similar results to the ones obtained using not only the mentioned markers but also gas phase PAH and trace elements. In order to reach this aim, two receptor models: UNMIX and positive matrix factorization were applied to two sets of data in Zaragoza city from airborne PM10, a previously reported campaign (2003–2004) (Callén et al. Chemosphere 76:1120-1129, 2009), where PAH associated to the gas and particle phases, ions and trace elements were used as markers and a long sampling campaign (2001–2009), where only PAH in the particle phase and ions were analyzed. For both campaigns, positive matrix factorization was able to explain a higher number of sources than the UNMIX model. Independently of the sampling campaign and the receptor model used, soil resuspension was the main PM10 source, especially in the warm period (21st March–21st September), where most of the PM10 exceedances were produced. Despite some of the markers of anthropogenic sources were different for both campaigns, common sources associated to different combustion sources (coal, light-oil, heavier-oil, biomass, and traffic) were found and PAH in particle phase and ions seemed to be good markers for the airborne PM10 apportionment.     

Chemical characterisation of PM episodes in NE Spain

The chemical composition of ambient particulate matter (PM) varies widely as a function of its main emission sources and of the chemical reactions which take place in the atmosphere. The aim of this study is to obtain the chemical profile of PM10 and PM2.5 during peak PM episodes, thus identifying the main emission sources and/or atmospheric processes which originate the PM episodes. To this end, cluster analysis was applied to a set of PM10 and PM2.5 data collected throughout 2001 in two urban and industrialised areas in NE Spain. As a result of this analysis, five clusters were identified for each site, and the interpretation of their chemical profiles lead to the identification of five types of peak PM episodes for each site: industrial, traffic and regional re-circulation episodes at both sites, plus crustal episodes in Barcelona, and peak traffic and industrial episodes (T+I) in Tarragona. Traffic episodes are characterised by daily means of 23 and 10 microg/m3 of OM+EC in Barcelona and Tarragona in PM10. Levels of secondary inorganic aerosols reach average daily means of 19 and 11 microg/m3 in Barcelona and Tarragona in PM10 during industrial episodes. High levels of sulphate (>5 microg/m3) and ozone (up to 77 microg/m3 daily mean) are good tracers of regional re-circulation episodes. During crustal episodes daily means of crustal elements reach up to 34 microg/m3 in Barcelona. Special attention has been drawn to the composition of the mineral matter during the different PM episodes.     

Monitoring study of the near-road PM2.5 concentrations in Maryland

The Maryland State Highway Administration (SHA) monitoring program monitored the impact of vehicular emissions on the concentrations of the fine particles smaller than 2.5 microns (PM2.5). PM2.5 concentrations were monitored in close proximity to a highway in order to determine whether traffic conditions on the roadway impact concentrations at this location. The monitoring program attempted to connect monitored concentrations with the roadway traffic exhaust or with the other sources of PM2.5. PM2.5 concentrations were collected near the Capital Beltway (I-495/I-95) in Largo, Maryland. The monitoring program was launched on May 13, 2009 and continued through the end of 2012. Two co-located monitors, one for continuous PM2.5 measurements and the other for speciation measurements, were used in this program. Meteorological and traffic information was also continuously collected at or near the monitoring site. Additionally, data from the two other monitoring locations, one at the Howard University-Beltsville, MD and one at McMillan Reservoir, DC, was used for comparison with the data collected at the SHA monitoring location. The samples collected by the speciation monitor were analyzed at the RTI and DRI Laboratories to determine the composition and the sources of the collected PM2.5 samples. Based on the apportionment analysis, the contribution of roadway sources is about 12 to 17 percent of PM2.5 at the near-road site.

Implications: PM_2.5 monitoring at 150 m (approximately 500 feet) from a major highway in Maryland near Washington, DC, demonstrated that roadway traffic contributes to the total PM_2.5 concentration near the roadway, but the contribution at such distance is small, in the order of 12–17% of the total.     

Chemical speciation of PM2.5 and PM10 in south Phoenix, AZ, USA

Phoenix, AZ, experiences high particulate matter (PM) episodes, especially in the wintertime. The spatial variation of the PM concentrations and resulting differences in exposure is of particular concern. In this study, PM2.s (PM with aerodynamic diameter <2.5 microm) and PM10 (PM with aerodynamic diameter <10 microm) samples were collected simultaneously from the east and west sides of South Phoenix and at a control site in Tempe and analyzed for trace elements and bulk elemental and organic carbon. Measurements showed that although PM2.5 concentrations had similar trends in temporal scale across all sites, concentrations of PM10 did not. The difference in PM10 concentrations and fluctuation across the three sites suggest effects of a local soil source as evidenced by high concentrations of Al, Ca, and Fe in PM10. K and anthropogenic elements (e.g., Cu, Pb, and Zn) in PM2.5 samples on January 1 were strikingly high, suggesting the influence of New Year's fireworks. Concentrations of toxic elements (e.g., Pb) in the study presented here are not different from similar studies in other U.S. cities. Application of principal component analysis indicated two broad categories of emission sources--soil and combustion--together accounting for 80 and 90% of variance, respectively, in PM2.5 and PM10. The soil and combustion components explained approximately 60 and 30% of the variance in PM10, respectively, whereas combustion sources dominated PM2.5 (>50% variance). Many elements associated with anthropogenic sources were highly enriched, with enrichment factors in PM2.5 an order of magnitude higher than in PM10 relative to surface soil composition in the study area.     

Spatial and temporal variations of PM(2.5) concentration and composition throughout an urban area with high freeway density-the Greater Cincinnati study

The PM(2.5) concentration and its elemental composition were measured in the Cincinnati metropolitan area, which is characterized by intense highway traffic. The spatial and temporal variations were investigated for various chemical elements that contributed to the PM(2.5) fraction during a 1-year-long measurement campaign (December 2001-November 2002). The ambient aerosol monitoring was performed in 11 locations around the city during nine measurement cycles. During each cycle, four Harvard-type impactors were operating in parallel in specific locations to explore various factors affecting the PM(2.5) elemental concentrations. The sampling was performed during business days, thus assuring traffic uniformity. The 24-h PM(2.5) samples were collected on Teflon and quartz filters. Teflon filters were analyzed by X-ray fluorescence (XRF) analysis while quartz filters were analyzed by thermal-optical transmittance (TOT) analysis. In addition to PM(2.5) measurements, particle size-selective sampling was performed in two cycles using micro-orifice uniform deposit impactor; the collected fractionated deposits were analyzed by XRF. It was found that PM(2.5) concentration ranged from 6.70 to 48.3 mug m(-3) and had low spatial variation (median coefficient of variation, CV=11.3%). The elemental concentrations demonstrated high spatial variation, with the median CV ranged from 38.2% for Fe to 68.7% for Ni. For traffic-related trace metals, the highest concentration was detected in the city center site, which was close to a major highway. The particle size selective measurement revealed that mass concentration of the trace metals, such as Zn, Pb, Ni, as well as that of sulfur reach their peak values in the particle size range of 0.32-1.0 mum. Meteorological parameters and traffic intensity were not found to have a significant influence on the PM(2.5) elemental concentrations.     

Characterization of ambient fine particles in the northwestern area and Anchorage, Alaska

Ambient PM2.5 (particulate matter less than 2.5 microm in aerodynamic diameter) in the northwestern United States and Alaska is dominated by carbonaceous compounds associated with wood burning and transportation sources. PM2.5 source characterization studies analyzing recent PM2.5 speciation data have not been previously reported for these areas. In this study, ambient PM2.5 speciation samples collected at two monitoring sites located in the northwestern area, Olympic Peninsula, WA, and Portland, OR, and one monitoring site located in Anchorage, AK, were characterized through source apportionments. Gasoline vehicle, secondary sulfate, and wood smoke were the largest sources of PM2.5 collected at the Anchorage, Olympic, and Portland monitoring sites, respectively. Secondary sulfates showed an April peak at Anchorage and a November peak at Portland that are likely related to the increased photochemical reaction and long-range transport in Anchorage and meteorological stagnation in Portland. Secondary nitrate at the Olympic site showed a weak summer high peak that could be caused by seasonal tourism in the national park. Backward trajectories suggested that the elevated aged sea salt concentrations at the Portland monitoring site could be regional transport of sea salt that passed through other contaminated air sheds along the coast. Oil combustion emissions that might originate from ships and ferries were observed at the Olympic monitoring site.     

Characterization of saccharides and other organic compounds in fine particles and the use of saccharides to track primary biologically derived carbon sources

A total of 134 aerosol samples (d_p < 2.5 μm) were collected at one rural site and one urban site in Texas from November 2005 to July 2006 to investigate the different sources that contribute to the ambient levels of different compounds. In particular, saccharide compounds were studied as potential tracers to track aerosols of biologically derived origin. The ambient concentration, seasonal variation, and urban/rural comparison of major saccharides and other organic compounds including normal alkanes, hopanes, and carboxylic acids were determined and analyzed relative to characterizing sources of PM2.5. Saccharides, together with other known molecular markers, were analyzed by a positive matrix factorization model and eight source factors were isolated that provide meaningful interpretation of aerosol sources. Three isolated factors were characterized by the dominance of different saccharide compounds and were attributed to wood smoke, sucrose rich bio-aerosols, and fungal spore derived bio-aerosols. It was estimated that wood smoke and primary biologically derived carbon sources contributed 22% and 14% to the measured ambient PM2.5 mass at San Augustine and 16% and 5% to the measured ambient PM2.5 mass at Dallas. The relative PM contribution from other resolved sources were also calculated.     

Application of a microscale emission factor model for particulate matter to calculate vehicle-generated contributions to fine particulate emissions

This paper discusses the evaluation and application of a new generation of particulate matter (PM) emission factor model (MicroFacPM). MicroFacPM that was evaluated in Tuscarora Mountain Tunnel, Pennsylvania Turnpike, PA shows good agreement between measured and modeled emissions. MicroFacPM application is presented to the vehicle traffic on the main approach road to the Ambassador Bridge, which is one of the most important international border entry points in North America, connecting Detroit, MI, with Windsor, Ontario, Canada. An increase in border security has forced heavy-duty diesel vehicles to line up for several kilometers through the city of Windsor causing concern about elevated concentrations of ambient PM. MicroFacPM has been developed to model vehicle-generated PM (fine [PM2.5] and coarse < or = 10 microm [PM10]) from the on-road vehicle fleet, which in this case includes traffic at very low speeds (10 km/h). The Windsor case study gives vehicle generated PM2.5 sources and their breakdown by vehicle age and class. It shows that the primary sources of vehicle-generated PM2.5 emissions are the late-model heavy-duty diesel vehicles. We also applied CALINE4 and AERMOD in conjunction with MicroFacPM, using Canadian traffic and climate conditions, to describe the vehicle-generated PM2.5 dispersion near this roadway during the month of May in 2003.     

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.     

PM2.5 assessment in 21 European study centers of ECRHS II: Method and first winter results

The follow-up of a cohort of adults from 29 European centers of the former European Community Respiratory Health Survey (ECRHS) I (1989-1992) will examine the long-term effects of exposure to ambient air pollution on the incidence, course, and prognosis of respiratory diseases, in particular asthma and decline in lung function. The purpose of this article is to describe the methodology and the European-wide quality control program for the collection of particles with 50% cut-off size of 2.5 microm aerodynamic diameter (PM2.5) in the ECRHS II and to present the PM2.5 results from the winter period 2000-2001. Because PM2.5 is not routinely monitored in Europe, we measured PM2.5 mass concentrations in 21 participating centers to estimate background exposure in these cities. A standardized protocol was developed using identical equipment in each center (U.S. Environmental Protection Agency Well Impactor Ninety-Six [WINS] and PQ167 from BGI, Inc.). Filters were weighed in a single central laboratory. Sampling was conducted for 7 days per month for a year. Winter mean PM2.5 mass concentrations (November 2000-February 2001) varied substantially, with Iceland reporting the lowest value (5 microg/m3) and northern Italy the highest (69 microg/m3). A standardized procedure appropriate for PM2.5 exposure assessment in a multicenter study was developed. We expect ECRHS II to have sufficient variation in exposure to assess long-term effects of air pollution in this cohort. Any bias caused by variation in the characteristics of the chosen monitoring location (e.g., proximity to traffic sources) will be addressed in later analyses. Given the homogenous spatial distribution of PM2.5, however, concentrations measured near traffic are not expected to differ substantially from those measured at urban background sites.     

Improving Source Apportionment of Fine Particles in the Eastern United States Utilizing Temperature-Resolved Carbon Fractions

Abstract

The objectives of this study were to examine the use of carbon fractions to identify particulate matter (PM) sources, especially traffic‐related carbonaceous particle sources, and to estimate their contributions to the particle mass concentrations. In recent studies, positive matrix factorization (PMF) was applied to ambient fine PM (PM_2.5) compositional data sets of 24‐hr integrated samples including eight individual carbon fractions collected at three monitoring sites in the eastern United States: Atlanta, GA, Washington, DC, and Brigantine, NJ. Particulate carbon was analyzed using the Interagency Monitoring of Protected Visual Environments/Thermal Optical Reflectance method that divides carbon into four organic carbons (OC): pyrolized OC and three elemental carbon (EC) fractions. In contrast to earlier PMF studies that included only the total OC and EC concentrations, gasoline emissions could be distinguished from diesel emissions based on the differences in the abundances of the carbon fractions between the two sources. The compositional profiles for these two major source types show similarities among the three sites. Temperature‐resolved carbon fractions also enhanced separations of carbon‐rich secondary sulfate aerosols. Potential source contribution function analyses show the potential source areas and pathways of sulfate‐rich secondary aerosols, especially the regional influences of the biogenic, as well as anthropogenic secondary aerosol. This study indicates that temperature‐resolved carbon fractions can be used to enhance the source apportionment of ambient PM_2.5.     

Exposure of chronic obstructive pulmonary disease patients to particulate matter: relationships between personal and ambient air concentrations

Mot time-series studies of particulate air pollution and acute health outcomes assess exposure of the study population using fixed-site outdoor measurements. To address the issue of exposure misclassification, we evaluate the relationship between ambient particle concentrations and personal exposures of a population expected to be at risk of particle health effects. Sampling was conducted within the Vancouver metropolitan area during April-September 1998. Sixteen subjects (non-smoking, ages 54-86) with physician-diagnosed chronic obstructive pulmonary disease (COPD) wore personal PM2.5 monitors for seven 24-hr periods, randomly spaced approximately 1.5 weeks apart. Time-activity logs and dwelling characteristics data were also obtained for each subject. Daily 24-hr ambient PM10 and PM2.5 concentrations were measured at five fixed sites spaced throughout the study region. SO4(2-), which is found almost exclusively in the fine particle fraction and which does not have major indoor sources, was measured in all PM2.5 samples as an indicator of accumulation mode particulate matter of ambient origin. The mean personal and ambient PM2.5 concentrations were 18 micrograms/m3 and 11 micrograms/m3, respectively. In analyses relating personal and ambient measurements, ambient concentrations were expressed either as an average of the values obtained from five ambient monitoring sites for each day of personal sampling, or as the concentration obtained at the ambient site closest to each subject's home. The mean personal to ambient concentration ratio of all samples was 1.75 (range = 0.24 to 10.60) for PM2.5, and 0.75 (range = 0.09 to 1.42) for SO4(2-). Regression analyses were conducted for each subject separately and on pooled data. The median correlation (Pearson's r) between personal and average ambient PM2.5 concentrations was 0.48 (range = -0.68 to 0.83). Using SO4(2-) as the exposure metric, the median r between personal and average ambient concentrations was 0.96 (range = 0.66 to 1.0). Use of the closest ambient site did not improve the median correlation of the group for either PM2.5 or SO4(2-). All pooled analyses resulted in lower correlation coefficients than the median correlation coefficient of individual regressions. Personal SO4(2-) was more highly correlated with all ambient measures than PM2.5. Inclusion of time-activity and dwelling characteristics data did not result in a useful predictive regression model for PM2.5 personal exposure, but improved the model fit from simply regressing against ambient concentration (R2 = 0.27). The model for SO4(2-) was predictive (R2 = 0.82), as personal exposures were largely explained by ambient levels. These results indicate a relatively low correlation between personal exposure and ambient PM2.5 that is not improved by assigning exposure to the closest ambient monitor. The correlation between personal exposure and ambient concentration is high, however, when using SO4(2-), an indicator of accumulation mode particulate matter of ambient origin.     

PM2.5 source apportionment: reconciling receptor models for U.S. nonurban and urban long-term networks

Chemical mass balance (CMB) and trajectory receptor models were applied to speciated particulate matter with aerodynamic diameter < or =2.5 microm (PM2.5) measurements from Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network across the state of Minnesota as part of the Minnesota PM2.5 Source Apportionment Study (MPSAS). CMB equations were solved by the Unmix, positive matrix factorization (PMF), and effective variance (EV) methods, giving collective source contribution and uncertainty estimates. Geological source profiles developed from local dust materials were either incorporated into the EV-CMB model or used to verify factors derived from Unmix and PMF. Common sources include soil dust, calcium (Ca)-rich dust, diesel and gasoline vehicle exhausts, biomass burning, secondary sulfate, and secondary nitrate. Secondary sulfate and nitrate aerosols dominate PM2.5 mass (50-69%). Mobile sources outweigh area sources at urban sites, and vice versa at rural sites due to traffic emissions. Gasoline and diesel contributions can be separated using data from the STN, despite significant uncertainties. Major differences between MPSAS and earlier studies on similar environments appear to be the type and magnitude of stationary sources, but these sources are generally minor (<7%) in this and other studies. Ensemble back-trajectory analysis shows that the lower Midwestern states are the predominant source region for secondary ammoniated sulfate in Minnesota. It also suggests substantial contributions of biomass burning and soil dust from out-of-state on occasions, although a quantitative separation of local and regional contributions was not achieved in the current study. Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for a summary of input data, Unmix and PMF factor profiles, and additional maps.     

Fine particulate matter emissions inventories: comparisons of emissions estimates with observations from recent field programs

Emissions inventories of fine particulate matter (PM2.5) were compared with estimates of emissions based on data emerging from U.S. Environment Protection Agency Particulate Matter Supersites and other field programs. Six source categories for PM2.5 emissions were reviewed: on-road mobile sources, nonroad mobile sources, cooking, biomass combustion, fugitive dust, and stationary sources. Ammonia emissions from all of the source categories were also examined. Regional emissions inventories of PM in the exhaust from on-road and nonroad sources were generally consistent with ambient observations, though uncertainties in some emission factors were twice as large as the emission factors. In contrast, emissions inventories of road dust were up to an order of magnitude larger than ambient observations, and estimated brake wear and tire dust emissions were half as large as ambient observations in urban areas. Although comprehensive nationwide emissions inventories of PM2.5 from cooking sources and biomass burning are not yet available, observational data in urban areas suggest that cooking sources account for approximately 5-20% of total primary emissions (excluding dust), and biomass burning sources are highly dependent on region. Finally, relatively few observational data were available to assess the accuracy of emission estimates for stationary sources. Overall, the uncertainties in primary emissions for PM2.s are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods.     

Improving source apportionment of fine particles in the eastern United States utilizing temperature-resolved carbon fractions

The objectives of this study were to examine the use of carbon fractions to identify particulate matter (PM) sources, especially traffic-related carbonaceous particle sources, and to estimate their contributions to the particle mass concentrations. In recent studies, positive matrix factorization (PMF) was applied to ambient fine PM (PM2.5) compositional data sets of 24-hr integrated samples including eight individual carbon fractions collected at three monitoring sites in the eastern United States: Atlanta, GA, Washington, DC, and Brigantine, NJ. Particulate carbon was analyzed using the Interagency Monitoring of Protected Visual Environments/Thermal Optical Reflectance method that divides carbon into four organic carbons (OC): pyrolized OC and three elemental carbon (EC) fractions. In contrast to earlier PMF studies that included only the total OC and EC concentrations, gasoline emissions could be distinguished from diesel emissions based on the differences in the abundances of the carbon fractions between the two sources. The compositional profiles for these two major source types show similarities among the three sites. Temperature-resolved carbon fractions also enhanced separations of carbon-rich secondary sulfate aerosols. Potential source contribution function analyses show the potential source areas and pathways of sulfate-rich secondary aerosols, especially the regional influences of the biogenic, as well as anthropogenic secondary aerosol. This study indicates that temperature-resolved carbon fractions can be used to enhance the source apportionment of ambient PM2.5.