Characterization and source apportionment of water-soluble organic matter in atmospheric fine particles (PM2.5) with high-resolution aerosol mass spectrometry and GC-MS

Water-soluble organic matter (WSOM) in fine particles (PM(2.5)) collected at one rural and three urban sites from the Southeastern Aerosol Research and Characterization network were characterized with a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS). These samples were also analyzed for a suite of molecular markers by Gas Chromatography-Mass Spectrometry (GC-MS) to assist in the interpretation of WSOM sources. The HR-ToF-AMS measurements allow a direct determination of the organic mass-to-carbon ratios (average ± 1σ = 1.93 ± 0.12) and hence the quantification of WSOM on the same filters used to close the aerosol mass budget. WSOM constitutes a major fraction of total PM(2.5) mass (26-42%) and organic mass (50-90%) at all sites. The concentrations of WSOM are substantially higher in summer, mainly due to enhanced production of biogenic secondary organic aerosol (SOA). WSOM is composed mainly of oxygenated species with average oxygen-to-carbon (O/C) ratio of 0.56 (± 0.08). Positive matrix factorization (PMF) of the high resolution mass spectra of WSOM identifies a less oxidized component (denoted as lOOA, O/C = 0.50) associated with biogenic SOA and a more oxidized component (denoted as mOOA, O/C = 0.60) associated with WSOM contributed by wood combustion. On average, lOOA accounts for 75 (± 13) % of WSOM in summer while mOOA accounts for 78 (± 21) % in winter, suggesting that WSOM in the southeastern U.S. is primarily contributed by SOA production from biogenic species in summer and by wood burning emissions in winter. This work also demonstrates the utility of HR-ToF-AMS for investigating the bulk chemical composition of WSOM as well as for evaluating its source contributions.     

Source apportionment of PM2.5 in the Southeastern United States using solvent-extractable organic compounds as tracers

A chemical mass balance (CMB) receptor model using particle-phase organic compounds as tracers is applied to apportion the primary source contributions to fine particulate matter and fine particulate organic carbon concentrations in the southeastern United States to determine the seasonal variability of these concentrations. Source contributions to particles with aerodynamic diameter < or =2.5 microm (PM2.5) collected from four urban and four rural/suburban sites in AL, FL, GA, and MS during April, July, and October 1999 and January 2000 are calculated and presented. Organic compounds in monthly composite samples at each site are identified and quantified by gas chromatography/mass spectrometry and are used as molecular markers in the CMB model. The major contributors to identified PM2.5 organic carbon concentrations at these sites in the southeastern United States include wood combustion (25-66%), diesel exhaust (14-30%), meat cooking (5-12%), and gasoline-powered motor vehicle exhaust (0-10%), as well as smaller but statistically significant contributions from natural gas combustion, paved road dust, and vegetative detritus. The primary sources determined in the present study when added to secondary aerosol formation account for on average 89% of PM2.5 mass concentrations, with the major contributors to PM2.5 mass as secondary sulfate (30+/-6%), wood combustion (15+/-12%), diesel exhaust (16+/-7%), secondary ammonium (8+/-2%), secondary nitrate (4+/-3%), meat cooking (3+/-2%), gasoline-powered motor vehicle exhaust (2+/-2%), and road dust (2+/-2%). Distinct seasonality is observed in source contributions, including higher contributions from wood combustion during the colder months of October and January. In addition, higher percentages of unexplained fine organic carbon concentrations are observed in July, which are likely due to an increase in secondary organic aerosol formation during the summer season.     

Source contributions to atmospheric gases and particulate matter in the southeastern United States

A new approach for determining the contributions of emission sources to concentrations of particulate matter and gases is developed using the chemical mass balance (CMB) method and the U.S. EPA's National Emission Inventory (NEI). The approach apportions combined gas-phase and condensed-phase concentrations of individual compounds as well as PM(2.5) mass. Because the NEI is used to provide source emission profiles for CMB analysis, the method generates information on the consistency of the NEI with ambient monitoring data. The method also tracks secondary species to primary source emissions, permitting a more complete accounting of the impact of aggregated source types on PM(2.5) mass concentrations. An example application is presented using four years of monitoring data collected at eight sites in the Southeastern Aerosol Research and Characterization (SEARCH) network. Including both primary and secondary species, area sources contributed 2.0-3.7 μg m(-3) (13-26%), point sources contributed 3.0-4.6 μg m(-3) (22-33%), and mobile sources contributed 1.0-6.0 μg m(-3) (9-42%) to mean PM(2.5) mass concentrations. Whereas the NEI generally accounts for the ambient concentrations of gases and particles, certain anomalies are identified, especially related to carbonaceous compounds and dust.     

Quantifying PM2.5 source contributions for the San Joaquin Valley with multivariate receptor models

UNMIX and Positive Matrix Factorization (PMF) solutions to the Chemical Mass Balance (CMB) equations were applied to chemically speciated PM2.5 measurements from 23 sites in California's San Joaquin Valley to estimate source contributions. Six and seven factors were determined by UNMIX for the low_PM2.5 period (February to October) and high_PM2.5 period (November to January), respectively. PMF resolved eightfactors for each period that corresponded with the UNMIX factors in chemical profiles and time series. These factors are attributed to marine sea salt, fugitive dust, agriculture-dairy, cooking, secondary aerosol, motor vehicle, and residential wood combustion (RWC) emissions, with secondary aerosol and RWC accounting for over 70% of PM2.5 mass during the high_PM2.5 period. A zinc factor was only resolved by PMF. The contribution from motor vehicles was between 10 and 25% with higher percentages occurring in summer. The PMF model was further evaluated by examining (1) site-specific residuals between the measured and calculated concentrations, (2) comparability of motor vehicle and RWC factors against source profiles obtained from recent emission tests, (3) edges in bi-plots of key indicator species, and (4) spatiotemporal variations of the factors' strengths. These evaluations support the compliance with model assumptions and give a higher confidence level to source apportionment results for the high_PM2.5 period.     

Identification of the major sources contributing to PM2.5 observed in Toronto

The chemical composition of Toronto PM2.5 was measured daily from Feb 2000 to Feb 2001, and source apportionment was undertaken using positive matrix factorization (PMF). In Toronto, PM2.5 levels were influenced both by local urban activities and also by regional-scale transport. Although several PMF solutions were possible, an eight-source model for explaining the observed Toronto PM2.5 was found to provide realistic results and interesting insights into sources. The four main sources were coal combustion related to regional transport and secondary sulfate (26%), secondary nitrate related to both local and upwind sources of NOx and NH3 (36%), secondary organic aerosols (SOA) formed from a variety of precursor organic emissions (15%), and motor vehicle traffic (10%). The other detectable sources were road salt (winter) and three types of primary PM2.5 hypothesized to be associated with smelters, coal and oil combustion, industry, and local construction. Overall, motor vehicle-related emissions (including road salt and nitrate) were estimated to be responsible for about 40% of the PM2.5. In the summer, the SOA mass was estimated to contribute approximately 20% to the PM2.5. Inclusion of water-soluble, low-molecular-weight organic acids led to identification of this component, thus providing a significant improvement in PMF's ability to resolve sources. Without organic acid measurements the SOA portion of the observed PM2.5 was assigned to the secondary coal component, increasing its contribution and resulting in a source profile with an unrealistic amount of organic mass. This suggests that in the northeastern part of North America, there are physical and/or chemical processes that lead to close interaction between secondary organic and inorganic aerosols.     

Identification of particulate matter sources on an hourly time-scale in a wood burning community

Particulate matter (PM) sources at two different sites in a rural town in New Zealand were investigated on an hourly time-scale. Streaker samplers were used to collect hourly, size-segregated PM(10-2.5) and PM(2.5) samples that were analyzed for elemental content using ion beam analysis techniques. Black carbon concentrations were determined using light reflection and PM(10) concentrations were recorded using colocated continuous PM monitors. PM(10) concentrations at both sites displayed a diurnal pattern, with hourly PM(10) concentration maxima in the evening (7 pm-midnight) and in the morning (7-9 am). One of the monitoring sites experienced consistently higher average PM(10) concentrations during every hour and analysis indicated that katabatic flows across the urban area contributed to the increased concentrations observed. Source apportionment using positive matrix factorization on the hourly data revealed four primary PM(10) sources for each site: biomass burning, motor vehicles, marine aerosol and crustal matter. Biomass burning was the most dominant source at both sites and was responsible for both the evening and morning PM(10) concentration peaks. The use of elemental speciation combined with PM(10) concentrations for source apportionment on an hourly time-scale has never been reported and provides unique and useful information on PM sources for air quality management.     

Estimating ground-level PM2.5 in the eastern United States using satellite remote sensing

An empirical model based on the regression between daily PM2.5 (particles with aerodynamic diameters of less than 2.5 microm) concentrations and aerosol optical thickness (AOT) measurements from the multiangle imaging spectroradiometer (MISR) was developed and tested using data from the eastern United States during the period of 2001. Overall, the empirical model explained 48% of the variability in PM2.5 concentrations. The root-mean-square error of the model was 6.2 microg/m3 with a corresponding average PM2.5 concentration of 13.8 microg/m3. When PM2.5 concentrations greater than 40 microg/m3 were removed, model results were shown to be unbiased estimators of observations. Several factors, such as planetary boundary layer height, relative humidity, season, and other geographical attributes of monitoring sites, were found to influence the association between PM2.5 and AOT. The findings of this study illustrate the strong potential of satellite remote sensing in regional ambient air quality monitoring as an extension to ground networks. With the continual advancement of remote sensing technology and global data assimilation systems, AOT measurements derived from satellite remote sensors may provide a cost-effective approach as a supplemental source of information for determining ground-level particle concentrations.     

Determination of the sources of indoor PM2.5 in Amsterdam and Helsinki

Daily PM2.5 samples were repeatedly collected (1-8 times) in the homes of elderly nonsmoking individuals with coronary heart disease in Amsterdam, The Netherlands (33 individuals) and Helsinki, Finland (44 individuals). Sources of indoor PM2.5 were evaluated using a two-way multilinear engine model. Because the indoor elemental data lacked a traffic marker, separation of traffic related PM was attempted by combining the indoor data with fixed site outdoor data that also contained NO. Six outdoor sources, including long-range transport (LRT), urban mixture, oil combustion, traffic, sea-salt, and soil were identified, and three indoor sources were resolved: resuspension, potassium-rich and copper-rich sources. The average contribution of the indoor factors was 6% (1.1 microg m(-3)) and 22% (2.4 microg m(-3)) in Amsterdam and Helsinki, respectively. The highest longitudinal correlations between source-specific outdoor and indoor PM2.5 concentrations were found for LRT and urban mixture; the median R was above 0.6 for most sources. The longitudinal correlations were lower in Helsinki than in Amsterdam. Indoor-generated PM2.5 was not related to ambient concentrations. We conclude that using outdoor and indoor data together improved the source apportionment of indoor PM2.5. The results support the use of fixed site outdoor measurements in epidemiological time-series studies on outdoor air pollution.     

Spatial variability of carbonaceous aerosol concentrations in East and West Jerusalem

Carbonaceous aerosol concentrations and sources were compared during a year long study at two sites in East and West Jerusalem that were separated by a distance of approximately 4 km. One in six day 24-h PM(2.5) elemental and organic carbon concentrations were measured, along with monthly average concentrations of particle-phase organic compound tracers for primary and secondary organic aerosol sources.Tracer compounds were used in a chemical mass balance ICMB) model to determine primary and secondary source contributions to organic carbon. The East Jerusalem sampling site at Al Quds University experienced higher concentrations of organic carbon (OC) and elemental carbon (EC) compared to the West Jerusalem site at Hebrew University. The annual average concentrations of OC and EC at the East Jerusalem site were 5.20 and 2.19 μg m(-3), respectively, and at the West Jerusalem site were 4.03 and 1.14 μg m(-3), respectively. Concentrations and trends of secondary organic aerosol and vegetative detritus were similar at both sites, but large differences were observed in the concentrations of organic aerosol from fossil fuel combustion and biomass burning, which was the cause of the large differences in OC and EC concentrations observed at the two sites.     

Apportionment of primary and secondary organic aerosols in southern California during the 2005 study of organic aerosols in riverside (SOAR-1)

Ambient sampling was conducted in Riverside, California during the 2005 Study of Organic Aerosols in Riverside to characterize the composition and sources of organic aerosol using a variety of state-of-the-art instrumentation and source apportionmenttechniques. The secondary organic aerosol (SOA) mass is estimated by elemental carbon and carbon monoxide tracer methods, water soluble organic carbon content, chemical mass balance of organic molecular markers, and positive matrix factorization of high-resolution aerosol mass spectrometer data. Estimates obtained from each ofthese methods indicate that the organic fraction in ambient aerosol is overwhelmingly secondary in nature during a period of several weeks with moderate ozone concentrations and that SOA is the single largest component of PM1 aerosol in Riverside. Average SOA/OA contributions of 70-90% were observed during midday periods, whereas minimum SOA contributions of approximately 45% were observed during peak morning traffic periods. These results are contraryto previous estimates of SOAthroughout the Los Angeles Basin which reported that, other than during severe photochemical smog episodes, SOA was lower than primary OA. Possible reasons for these differences are discussed.     

Comparison of black smoke and PM2.5 levels in indoor and outdoor environments of four European cities

Recent studies on separated particle-size fractions highlight the health significance of particulate matter smaller than 2.5 microm (PM2.5), but gravimetric methods do not identify specific particle sources. Diesel exhaust particles (DEP) contain elemental carbon (EC), the dominant light-absorbing substance in the atmosphere. Black smoke (BS) is a measure for light absorption of PM and, thus, an alternative way to estimating EC concentrations, which may serve as a proxy for diesel exhaust emissions. We analyzed PM2.5 and BS data collected within the EXPOLIS study (Air Pollution Exposure Distribution within Adult Urban Populations in Europe) in Athens, Basel, Helsinki, and Prague. 186 indoor/outdoor filter pairs were sampled and analyzed. PM2.5 and BS levels were lowest in Helsinki, moderate in Basel, and remarkably higher in Athens and Prague. In each city, Spearman correlation coefficients of indoor versus outdoor were higher for BS (range rspearman: 0.57-0.86) than for PM2.5 (0.05-0.69). In a BS linear regression model (all data), outdoor levels explained clearly more of indoor variation (86%) than in the corresponding PM2.5 model (59%). In conclusion, ambient BS seizes a health-relevant fraction of fine particles to which people are exposed indoors and outdoors and exposure to which can be assessed by monitoring outdoor concentrations. BS measured on PM2.5 filters can be recommended as a valid and cheap additional indicator in studies on combustion-related air pollution and health.     

Receptor modeling of toronto PM2.5 characterized by aerosol laser ablation mass spectrometry

Urban Toronto fine particulate matter (PM2.5) was physically and chemically characterized by online aerosol laser ablation mass spectrometry (LAMS) between January 2002 and February 2003. The mass spectra from the analysis of individual aerosol particles were classified according to chemical composition by a neural network approach called adaptive resonance theory (ART-2a). Temporal trends of the hourly analysis rate of over 120 different particles types were constructed and subjected to positive matrix factorization (PMF). This receptor modeling technique enabled the identification of nine distinct emission sources responsible for these particle types: biogenic, mixed crustal, organic nitrate, construction dust, Toronto soil/road salt, secondary salt, wood burning, intercontinental dust, and an unknown source of aluminum fluoride dust. Episodic events occurred with the wood burning, intercontinental dust, and unknown dust sources. This is the first paper reporting the application of PMF to single-particle spectral data.     

On-road particulate matter (PM2.5 and PM10) emissions in the Sepulveda Tunnel, Los Angeles, California

Total and speciated particulate matter (PM2.5 and PM10) emission factors from in-use vehicles were measured for a mixed light- (97.4% LD) and heavy-duty fleet (2.6% HD) in the Sepulveda Tunnel, Los Angeles, CA. Seventeen 1-h test runs were performed between July 23, 1996, and July 27, 1996. Emission factors were calculated from mass concentration measurements taken at the tunnel entrance and exit, the volume of airflow through the tunnel, and the number of vehicles passing through the 582 m long tunnel. For the mixed LD and HD fleet, PM2.5 emission factors in the Sepulveda Tunnel ranged from 0.016 (+/-0.007) to 0.115 (+/-0.019) g/vehicle-km traveled with an average of 0.052 (+/-0.027) g/vehicle.km. PM10 emission factors ranged from 0.030 (+/-0.009) to 0.131 (+/-0.024) g/vehicle. km with an average of 0.069 (+/-0.030) g/vehicle.km. The PM2.5 emission factor was approximately 74% of the PM10 factor. Speciated emission rates and chemical profiles for use in receptor modeling were also developed. PM2.5 was dominated by organic carbon (OC) (31.0 +/- 19.5%) and elemental carbon (EC) (48.5 +/- 20.5%) that together account for 79% (+/-24%) of the total emissions. Crustal elements (Fe, Mg, Al, Si, Ca, and Mn) contribute approximately 7.8%, and the ions Cl-, NO3-, NH3+, SO4(2-), and K+ together constitute another 9.8%. In the PM10 size fraction the particulate emissions were also dominated by OC (31 +/- 12%) and EC (35 +/- 13%). The third most prominent species was Fe (18.5 +/- 9.0%), which is greater than would be expected from purely geological sources. Other geological components (Mg, Al, Si, K, Ca, and Mn) accounted for an additional 12.6%. PM10 emission factors showed some dependence on vehicle speed, whereas PM2.5 did not. For test runs in which the average vehicle speed was 42.6 km/h a 1.7 times increase in PM10 emission factor was observed compared to those runs with an average vehicle speed of 72.6 km/h. Speciated emissions were similar. However, there is significantly greater mass attributable to geological material in the PM10, indicative of an increased contribution from resuspended road dust. The PM2.5 shows relatively good correlation with NOx emissions, which indicates that even at the low percent of HD vehicles, which emit significantly more NOx than LD vehicles, they may also have a significant impact on the PM2.5 levels.     

Fine (PM2.5) and coarse (PM2.5-10) particulate matter on a heavily trafficked London highway: sources and processes

A large dataset for PM2.5 and PMcoarse (PM2.5-10) concentrations monitored near a busy London highway (Marylebone Road) has been analyzed to define the factors that lead to high concentrations. The following have been highlighted as major influencing parameters: wind speed, prevailing wind direction (because of its role on the microscale dispersion within the street), the daily cycle of the atmospheric boundary layer (stable during the night/ convective and mixed during the day), and traffic density. The mainly diesel heavy-duty vehicles are the main source of fine particulate matter at Marylebone Road. In particular, lorries (trucks) dominate PM10 exhaust emissions which are mainly in the fine (<2.5 microm) size range. A strong correlation with PMcoarse suggests that the heavy-duty traffic is largely responsible for this component also. Substantial local increments in PM2.5 and PMcoarse due to traffic have been estimated and a large part of the increment in PMcoarse concentrations is inferred to arise from resuspended road dust emissions since the contribution of abrasion processes estimated from emission factors is modest. Despite the strong influence of traffic on PM concentrations measured at Marylebone Road the analysis of factors leading to the highest 5% of hourly concentrations of PM10 at Marylebone Road reveals that almost half of these events were due to building works. The other events occurred when all or most of the key factors occurred simultaneously (heavy traffic, poor dispersion, etc.). Some episodes of high PM2.5 concentrations were associated with long-range transport in which the regional PM2.5 constituted most of the local concentrations.     

Multisite study of particle number concentrations in urban air

Particle number concentration data are reported from a total of eight urban site locations in the United Kingdom. Of these, six are central urban background sites, while one is an urban street canyon (Marylebone Road) and another is influenced by both a motorway and a steelworks (Port Talbot). The concentrations are generally of a similar order to those reported in the literature, although higher than those in some of the other studies. Highest concentrations are at the Marylebone Road site and lowest are at the Port Talbot site. The central urban background locations lie somewhere between with concentrations typically around 20 000 cm(-3). A seasonal pattern affects all sites, with highest concentrations in the winter months and lowest concentrations in the summer. Data from all sites show a diurnal variation with a morning rush hour peak typical of an anthropogenic pollutant. When the dilution effects of windspeed are accounted for, the data show little directionality at the central urban background sites indicating the influence of sources from all directions as might be expected if the major source were road traffic. At the London Marylebone Road site there is high directionality driven by the air circulation in the street canyon, and at the Port Talbot site different diurnal patterns are seen for particle number count and PM10 influenced by emissions from road traffic (particle number count) and the steelworks (PM10) and local meteorological factors. Hourly particle number concentrations are generally only weakly correlated to NO(x) and PM10, with the former showing a slightly closer relationship. Correlations between daily average particle number count and PM10 were also weak. Episodes of high PM10 concentration in summer typically show low particle number concentrations consistent with transport of accumulation mode secondary aerosol, while winter episodes are frequently associated with high PM10 and particle number count arising from poor dispersion of local primary emissions.     

Measurements of isoprene-derived organosulfates in ambient aerosols by aerosol time-of-flight mass spectrometry - part 1: single particle atmospheric observations in Atlanta

Organosulfate species have recently been identified as a potentially significant class of secondary organic aerosol (SOA) species, yet little is known about their behavior in the atmosphere. In this work, organosulfates were observed in individual ambient aerosols using single particle mass spectrometry in Atlanta, GA during the 2002 Aerosol Nucleation and Characterization Experiment (ANARChE) and the 2008 August Mini-Intensive Gas and Aerosol Study (AMIGAS). Organosulfates derived from biogenically produced isoprene were detected as deprotonated molecular ions in negative-ion spectra measured by aerosol time-of-flight mass spectrometry; comparison to high-resolution mass spectrometry data obtained from filter samples corroborated the peak assignments. The size-resolved chemical composition measurements revealed that organosulfate species were mostly detected in submicrometer aerosols and across a range of aerosols from different sources, consistent with secondary reaction products. Detection of organosulfates in a large fraction of negative-ion ambient spectra - ca. 90-95% during ANARChE and ~65% of submicrometer particles in AMIGAS - highlights the ubiquity of organosulfate species in the ambient aerosols of biogenically influenced urban environments.     

Lanthanoid geochemistry of urban atmospheric particulate matter

Relatively little is known about the lanthanoid element (La to Lu) chemistry of inhalable urban atmospheric particulate matter (PM). PM samples collected during an air sampling campaign in the Mexico City area contain lanthanoid concentrations of mostly 1-10 ng m(-3), increasing with mass where resuspension of crustal PM is important (low PM2.5/PM10), but not where fine emissions from traffic and industry dominate (high PM2.5/ PM10). Samples show anthropogenic enrichment of lighter over heavier lanthanoids, and Ce enrichment relative to La and Sm occurs in the city center (especially PM10) possibly due to PM from road vehicle catalytic converters. La is especially enriched, although many samples show low La/V values (< 0.11), suggesting the dominating influence of fuel oil combustion sources rather than refinery emissions. We use La/Sm v La/ Ce, LaCeSm, and LaCeV plots to compare Mexico City aerosols with PM from other cities. Lanthanoid aerosol geochemistry can be used not only to identify refinery pollution events, but also as a marker for different hydrocarbon combustion emissions (e.g., oil or coal power stations) on urban background atmospheric PM.     

Source strengths of ultrafine and fine particles due to cooking with a gas stove

Cooking, particularly frying, is an important source of particles indoors. Few studies have measured a full range of particle sizes, including ultrafine particles, produced during cooking. In this study, semicontinuous instruments with fine size discriminating ability were used to calculate particle counts in 124 size bins from 0.01 to 2.5 microm. Data were collected at 5 min intervals for 18 months in an occupied house. Tracer gas measurements were made every 10 min in each of 10 rooms of the house to establish air change rates. Cooking episodes (N = 44) were selected meeting certain criteria (high concentrations, no concurrent indoor sources, long smooth decay curves), and the number and volume of particles produced were determined for each size category. For each episode, the particle decay rate was determined and used to determine the source strength for each size category. The selected cooking episodes (mostly frying) were capable of producing about 10(14) particles over the length of the cooking period (about 15 min), more than 90% of them in the ultrafine (< 0.1 microm) range, with an estimated whole-house volume concentration of 50 (microm/cm)3. More than 60% of this volume occurred in the 0.1-0.3 microm range. Frying produced peak numbers of particles at about 0.06 microm, with a secondary peak at 0.01 microm. The peak volume occurred at a diameter of about 0.16 microm. Since the cooking episodes selected were biased toward higher concentrations, the particle concentrations measured during about 600 h of morning and evening cooking over a full year were compared to concentrations measured during noncooking periods at the same times. Cooking was capable of producing more than 10 times the ultrafine particle number observed during noncooking periods. Levels of PM2.5 were increased during cooking by a factor of 3. Breakfast cooking (mainly heating water for coffee and using an electric toaster) produced concentrations about half those produced from more complex dinnertime cooking. Although the number and volume concentrations observed depend on air change rates, house volume, and deposition rates due to fans and filters, the source strengths calculated here are independent of these variables and may be used to estimate number and volume concentrations in other types of homes with widely varying volumes, ventilation rates, and heating and air-conditioning practices.     

Application of EPA unmix and nonparametric wind regression on high time resolution trace elements and speciated mercury in Tampa, Florida aerosol

Intensive ambient air sampling was conducted in Tampa, FL, during October and November of 2002. Fine particulate matter (PM(2.5)) was collected at 30 min resolution using the Semicontinuous Elements in Aerosol Sampler II (SEAS-II) and analyzed off-line for up to 45 trace elements by high-resolution ICPMS (HR-ICPMS). Divalent reactive gaseous mercury and particulate bound mercury were also measured semicontinuously (2 h). Application of the United States Environmental Protection Agency's (EPA) Unmix receptor model on the 30 min resolution trace metals data set identified eight possible sources: residual oil combustion, lead recycling, coal combustion, a Cd-rich source, biomass burning, marine aerosol, general industrial, and coarse dust contamination. The source contribution estimates from EPA Unmix were then run in a nonparametric wind regression (NWR) model, which convincingly identified plausible source origins. When the 30 min ambient concentrations of trace elements were time integrated (2 h) and combined with speciated mercury concentrations, the model identified only four sources, some of which appeared to be merged source profiles that were identified as separate sources by using the 30 min resolution data. This work demonstrates that source signatures that can be captured at 30 min resolution may be lost when sampling for longer durations.     

Chemical characterization and redox potential of coarse and fine particulate matter (PM) in underground and ground-level rail systems of the Los Angeles Metro

A campaign was conducted to assess personal exposure of coarse (2.5 μm < d(p) < 10 μm) and fine (d(p) < 2.5 μm) PM for two lines of the L.A. Metro-a subway (red) and light-rail (gold) line. Concurrent measurements were taken at University of Southern California (USC) to represent ambient conditions. A comprehensive chemical analysis was performed including total and water-soluble metals, inorganic ions, elemental and organic carbon, and organic compounds. Mass balance showed that in coarse PM, iron makes up 27%, 6%, and 2% of gravimetric mass for the red line, the gold line, and USC, respectively; in fine PM, iron makes up 32%, 3%, and 1%. Ambient air is the primary source of inorganic ions and organic compounds for both lines. Noncrustal metals, particularly Cr, Mn, Co, Ni, Mo, Cd, and Eu, were elevated for the red line and, to a lesser degree, the gold line. Mo exhibited the greatest crustal enrichment factors. The enriched species were less water-soluble on the red line than corresponding species on the gold line. Bivariate analysis showed that reactive oxygen species (ROS) activity is strongly correlated with water-soluble Fe (R(2) = 0.77), Ni (R(2 )= 0.95), and OC (R(2 )= 0.92). A multiple linear regression model (R(2) = 0.94, p < 0.001) using water-soluble Fe and OC as predictor variables was developed to explain the variance in ROS. In addition, PM from the red line generates 65% and 55% more ROS activity per m(3) of air than PM from USC and the gold line, respectively; however, one unit of PM mass from the gold line may be as intrinsically toxic as one unit of PM from the red line.