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.     

Source apportionment of PM2.5 at an urban IMPROVE site in Seattle, Washington

The multivariate receptor models Positive Matrix Factorization (PMF) and Unmix were used along with the EPA's Chemical Mass Balance model to deduce the sources of PM2.5 at a centrally located urban site in Seattle, WA. A total of 289 filter samples were obtained with an IMPROVE sampler from 1996 through 1999 and were analyzed for 31 particulate elements including temperature-resolved fractions of the particulate organic and elemental carbon. All three receptor models predicted that the major sources of PM2.5 were vegetative burning (including wood stoves), mobile sources, and secondary particle formation with lesser contributions from resuspended soil and sea spray. The PMF and Unmix models were able to resolve a fuel oil combustion source as well as distinguish between diesel emissions and other mobile sources. In addition, the average source contribution estimates via PMF and Unmix agreed well with an existing emissions inventory. Using the temperature-resolved organic and elemental carbon fractions provided in the IMPROVE protocol, rather than the total organic and elemental carbon, allowed the Unmix model to separate diesel from other mobile sources. The PMF model was able to do this without the additional carbon species, relying on selected trace elements to distinguish the various combustion sources.     

Molecular characteristics of urban organic aerosols from Nanjing: a case study of A mega-city in China

Over 90 organic species have been determined in fine aerosols (PM2.5) collected during the summer and winter in Nanjing, a typical mega-city in China, using gas chromatography-mass spectrometry. The organic compounds detected were apportioned to four emission sources (i.e., plant emission, fossil fuel combustion, biomass burning, and soil resuspension) and secondary oxidation products. The most abundant classes of compounds are fatty acids, followed by sugars, dicarboxylic acids excluding oxalic and malonic acids, and n-alkanes, while alcohols, polyols/polyacids and lignin/sterols are less abundant. Total amounts of the seven classes of compounds were on average 938 ng m(-3) in the summer and 1301 ng m(-3) in the winter, respectively, contributing 0.26-1.96% of particle mass (PM2.5). In the summer, n-alkanes were heavily enhanced by vegetation emissions with a maximum carbon number (Cmax) at C29, whereas they were dominated by emissions from fossil fuels combustion with a Cmax at C22/ C23 in the winter. Concentrations of unsaturated fatty acids were lower in the summer than in the winter, being consistent with enhanced photooxidation of unsaturated fatty acids in the summer. Concentrations of dicarboxylic acids for the summer aerosols were much higher in the daytime than in the nighttime, indicating increased photochemical production in the daytime. In the summer, plant emissions were the most significant source of organic aerosols, contributing more than 33% of total compound mass (TCM), followed by fossil fuel combustion or secondary oxidation. In contrast, fossil fuel combustion was the dominant source of winter organic aerosols, contributing more than 51% of TCM, followed by plant emissions and secondary oxidation products. The quantitative results on sugars and lignin pyrolysis products further suggested that biomass burning and soil resuspension are also significant sources of urban organic aerosols.     

Sources of fine particles in a rural midwestern U.S. area

Ambient PM2.5 (particulate matter < or = 2.5 microm in aerodynamic diameter) samples collected at a rural monitoring site in Bondville, IL on every third day using Interagency Monitoring of Protected Visual Environments (IMPROVE) sampler were analyzed through the application of the positive matrix factorization (PMF). The particulate carbon fractions were obtained from the thermal optical reflectance method that divides particulate carbon into four organic carbon, pyrolyzed organic carbon (OP), and three elemental carbon fractions. A total of 257 samples collected between March 2001 and May 2003 analyzed for 35 species were used and eight sources were identified: summer-high secondary sulfate aerosol (40%), secondary nitrate aerosol (32%), gasoline vehicle (9%), OP-high secondary sulfate aerosol (7%), selenium-high secondary sulfate aerosol (4%), airborne soil (4%), aged sea salt (2%), and diesel emissions (2%). The compositional profiles for gasoline vehicle and diesel emissions are similar to those estimated in other U.S. areas. Backward trajectories indicate that the highly elevated airborne soil impacts were likely caused by Asian and Saharan dust storms. Potential source contribution function analyses show the potential source areas and pathways of secondary sulfate aerosols, especially the regional influences of the biogenic as well as anthropogenic secondary aerosol.     

Use of synthetic data to evaluate positive matrix factorization as a source apportionment tool for PM2.5 exposure data

Positive matrix factorization (PMF) was applied to synthetic datasets that simulate personal exposures to airborne PM2.5 from 12 sources. Three differentfilter analysis scenarios using different analytical chemistry techniques were considered. The full suite scenario quantified elemental carbon, organic carbon, inorganic ions, trace elements, and trace organic species including carboxylic acids and organic compounds with -OH functionality. A second scenario excluded trace elements and a third assumed that derivatization steps to quantify polar organic compounds were not performed. Similar errors in source apportionment were seen with all three scenarios. In most cases, PMF failed to separate out factors corresponding to road dust and vegetative debris, two sources that made relatively uniform contributions to the synthetic exposures. Factors representing wood smoke, natural gas combustion, and meat cooking sources were difficult to identify due to a lack of unique tracers with concentrations reliably above the detection limits assumed in the study. Factors representing cigarette smoke, candle smoke, gasoline exhaust, and secondary aerosols were comparatively easy to identify. When contributions from a pair of sources, such as diesel and gasoline exhaust, were highly correlated in the synthetic datasets, a single factor corresponding to both sources was usually found.     

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.     

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.     

Modeling ozone and aerosol formation and transport in the pacific northwest with the community Multi-Scale Air Quality (CMAQ) modeling system

The Community Multi-Scale Air Quality (CMAQ) modeling system was used to investigate ozone and aerosol concentrations in the Pacific Northwest (PNW) during hot summertime conditions during July 1-15, 1996. Two emission inventories (El) were developed: emissions for the first El were based upon the National Emission Trend 1996 (NET96) database and the BEIS2 biogenic emission model, and emissions for the second El were developed through a "bottom up" approach that included biogenic emissions obtained from the GLOBEIS model. The two simulations showed that elevated PM2.5 concentrations occurred near and downwind of the Interstate-5 corridor along the foothills of the Cascade Mountains and in forested areas of central Idaho. The relative contributions of organic and inorganic aerosols varied by region, but generally organic aerosols constituted the largest fraction of PM2.5. In wilderness areas near the 1-5 corridor, organic carbon from anthropogenic sources contributed approximately 50% of the total organic carbon with the remainder from biogenic precursors, while in wilderness areas in Idaho, biogenic organic carbon accounted for 80% of the total organic aerosol. Regional analysis of the secondary organic aerosol formation in the Columbia River Gorge, Central Idaho, and the Olympics/Puget Sound showed that the production rate of secondary organic carbon depends on local terpene concentrations and the local oxidizing capacity of the atmosphere, which was strongly influenced by anthropogenic emissions. Comparison with observations from 12 IMPROVE sites and 21 ozone monitoring sites showed that results from the two El simulations generally bracketed the average observed PM parameters and that errors calculated for the model results were within acceptable bounds. Analysis across all statistical parameters indicated that the NW-AIRQUEST El solution performed better at predicting PM2.5, PM1, and beta(ext) even though organic carbon PM was over-predicted, and the NET96 El solution performed better with regard to the inorganic aerosols. For the NW-AIRQUEST El solution, the normalized bias was 30% and the normalized absolute error was 49% for PM2.5 mass. The NW-AIRQUEST solution slightly overestimated peak hourly ozone downwind of urban areas, while the NET96 solution slightly underestimated peak values, and both solutions over-predicted average 03 concentrations across the domain by approximately 6 ppb.     

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.     

Contribution of biogenic emissions to the formation of ozone and particulate matter in the eastern United States

As anthropogenic emissions of ozone (O3) precursors, fine particulate matter (PM2.5), and PM2.5 precursors continue to decrease in the United States, the fraction of O3 and PM2.5 attributable to natural sources may become significant in some locations, reducing the efficacy that can be expected from future controls of anthropogenic sources. Modeling studies were conducted to estimate the contribution of biogenic emissions to the formation of O3 and PM2.5 in Nashville/TN and the northeastern United States. Two approaches were used to bound the estimates. In an anthropogenic simulation, biogenic emissions and their influence at the domain boundaries were eliminated. Contributions of biogenic compounds to the simulated concentrations of O3 and PM2.5 were determined by the deviation of the concentrations in the anthropogenic case from those in the base case. A biogenic simulation was used to assess the amounts of O3 and PM2.5 produced in an environment free from anthropogenic influences in emissions and boundary conditions. In both locations, the contribution of biogenic emissions to O3 was small (<23%) on a domain-wide basis, despite significant biogenic volatile organic compounds (VOC) emissions (65-89% of total VOC emissions). However, the production of O3 was much more sensitive to biogenic emissions in urban areas (22-34%). Therefore, the effects of biogenic emissions on O3 manifested mostly via their interaction with anthropogenic emissions of NOx. In the anthropogenic simulations, the average contribution of biogenic and natural sources to PM2.5 was estimated at 9% in Nashville/TN and 12% in the northeast domain. Because of the long atmospheric lifetimes of PM2.5, the contribution of biogenic/natural PM2.5 from the boundary conditions was higher than the contribution of biogenic aerosols produced within the domain. The elimination of biogenic emissions also affected the chemistry of other secondary PM2.5 components. Very little PM2.5 was formed in the biogenic simulations.     

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.     

Impact of trash burning on air quality in Mexico City

Air pollution experienced by expanding urban areas is responsible for serious health effects and death for millions of people every year. Trash burning is a common disposal method in poor areas, yet it is uncontrolled in many countries, and its contribution to air pollution is unclear due to uncertainties in its emissions. Here we develop a new trash burning emission inventory for Mexico City based on inverse socioeconomic levels and recently measured emission factors, and apply a chemistry-transport model to analyze the effects on pollutant concentrations. Trash burning is estimated to emit 25 tons of primary organic aerosols (POA) per day, which is comparable to fossil fuel POA emissions in Mexico City, and causes an increase in average organic aerosol concentrations of ～0.3 μg m(-3) downtown and up to 2 μg m(-3) in highly populated suburbs near the sources of emission. An evaluation using submicrometer antimony suggests that our emission estimates are reasonable. Mitigation of trash burning could reduce the levels of organic aerosols by 2-40% and those of PM(2.5) by 1-15% over the metropolitan area. The trash burning contributions to carbon monoxide, nitrogen oxides, and volatile organic compounds were found to be very small (<3%), and consequently the contributions to secondary nitrate, sulfate, and secondary organic aerosols are also very small.     

Speciation of gas-phase and fine particle emissions from burning of foliar fuels

Fine particle matter with aerodynamic diameter <2.5 microm (PM2.5) and gas-phase emissions from open burning of six fine (foliar) fuels common to fire-prone U.S. ecosystems are investigated. PM2.5 distribution is unimodal within the 10-450 nm range, indicative of an accumulation mode. Smoldering relative to flaming combustion shows smaller particle number density per unit time and median size. Over 100 individual organic compounds in the primarily carbonaceous (>70% by mass) PM2.5 are chemically speciated by gas chromatography/mass spectrometry. Expressed as a percent of PM2.5 mass, emission ranges by organic compound class are as follows: n-alkane (0.1-2%), polycyclic aromatic hydrocarbon (PAH) (0.02-0.2%), n-alkanoic acid (1-3%), n-alkanedioic acid (0.06-0.3%), n-alkenoic acid (0.3-3%), resin acid (0.5-6%), triterpenoid (0.2-0.5%), methoxyphenol (0.5-3%), and phytosterol (0.2-0.6%). A molecular tracer of biomass combustion, the sugar levoglucosan is abundant and constitutes a remarkably narrow PM2.5 mass range (2.8-3.6%). Organic chemical signatures in PM2.5 from open combustion of fine fuels differ with those of residential wood combustion and other related sources, making them functional for source-receptor modeling of PM. Inorganic matter [PM2.5 - (organic compounds + elemental carbon)] on average is estimated to make up 8% of the PM2.5. Wavelength dispersive X-ray fluorescence spectroscopy and ion chromatography identify 3% of PM2.5 as elements and water-soluble ions, respectively. Compared with residential wood burning, the PM2.5 of fine fuel combustion is nitrate enriched but shows lower potassium levels. Gas-phase C2-C13 hydrocarbon and C2-C9 carbonyl emissions are speciated by respective EPA Methods T0-15 and T0-11A. They comprise mainly low molecular weight C2-C3 compounds and hazardous air pollutants (48 wt % of total quantified volatile organic carbon).     

Geographic sensitivity of fine particle mass to emissions of SO2 and NOx

An air quality model, URM-1ATM, was used to investigate tendencies in fine particle (PM2.5) species in response to changes in SO2 and NOx emissions in the eastern United States. The model employed the decoupled direct method (DDM) to estimate sensitivities without the need for multiple model runs for different emissions species and geographic regions. The baseline for sensitivities was emissions projected to 2010. Principal geographic regions investigated were east of the Mississippi River, although the contribution of a region to the immediate west of the river was also included in the study. Sensitivities to emissions changes from point sources (SO2 and NOx) and low-level sources (NOx) were computed. PM2.5 species examined were sulfate, organic carbon, and nitrate as well as total fine mass. Results for the midwest, mid-Atlantic, and southeast regions indicated that those regions affect their own aerosol levels the most. Aerosols in the northeast were most strongly linked to emissions from the midwest and mid-Atlantic regions. In general, midwest emissions had the most influence of any region on other regions. In addition, the southeast was relatively isolated, having the least influence outside itself and being least affected by neighboring regions. Sulfate was the species most sensitive to emission changes. Finally, the largest potential relative sensitivities of sulfate and organic aerosols, along with PM2.5 mass, to emissions changes were usually modeled to occur outside those areas computed to experience the highest aerosol levels.     

TEM study of PM2.5 emitted from coal and tire combustion in a thermal power station

The research presented here was conducted within the scope of an experiment investigating technical feasibility and environmental impacts of tire combustion in a coal-fired power station. Previous work has shown that combustion of a coal+tire blend rather than pure coal increased bulk emissions of various elements (e.g., Zn, As, Sb, Pb). The aim of this study is to characterize the chemical and structural properties of emitted single particles with dimensions <2.5 microm (PM2.5). This transmission electron microscope (TEM)-based study revealed that, in addition to phases typical of coal fly ash (e.g., aluminum-silicate glass, mullite), the emitted PM2.5 contains amorphous selenium particles and three types of crystalline metal sulfates never reported before from stack emissions. Anglesite, PbSO4, is ubiquitous in the PM2.5 derived from both fuels and contains nearly all Pb present in the PM. Gunningite, ZnSO4-H2O, is the main host for Zn and only occurs in the PM derived from the coal+tire blend, whereas yavapaiite, KFe3+(SO4)2, is present only when pure coal was combusted. We conclude that these metal sulfates precipitated from the flue gas, may be globally abundant aerosols, and have, through hydration or dissolution, a major environmental and health impact.     

Emissions of air pollutants from household stoves: honeycomb coal versus coal cake

Domestic coal combustion can emit various air pollutants. In the present study, we measured emissions of particulate matter (PM) and gaseous pollutants from burning a specially formulated honeycomb coal (H-coal) and a coal cake (C-coal). Flue gas samples for PM2.5, PM coarse (PM2.5-10), and TSP were collected isokinetically using a cascade impactor; PM mass concentrations were determined gravimetrically. Concentrations of SO2, NOx, and ionic Cr(VI) in PM were analyzed using spectrometric methods. Fluoride concentrations were measured using a specific ion electrode method. PM elemental components were analyzed using an X-ray fluorescence technique. Total (gas and particle phase) benzo[a]pyrene (BaP) concentration was determined using an HPLC/fluorescence method. Elemental and organic carbon contents of PM were analyzed using a thermal/optical reflectance technique. The compositional and structural differences between the H-coal and C-coal resulted in different emission characteristics. In generating 1 MJ of delivered energy, the H-coal resulted in a significant reduction in emissions of SO2 (by 68%), NOx (by 47%), and TSP (by 56%) as compared to the C-coal, whereas the emissions of PM2.5 and total BaP from the H-coal combustion were 2-3-fold higher, indicating that improvements are needed to further reduce emissions of these pollutants in developing future honeycomb coals. Although the H-coal and the C-coal had similar emission factors for gas-phase fluoride, the H-coal had a particle-phase fluoride emission factor that was only half that of the C-coal. The H-coal had lower energy-based emissions of all the measured toxic elements in TSP but higher emissions of Cd and Ni in PM2.5.     

How does infiltration behavior modify the composition of ambient PM2.5 in indoor spaces? An analysis of RIOPA data

The indoor environment is an important venue for exposure to fine particulate matter (PM2.5) of ambient (outdoor) origin. In this work, paired indoor and outdoor PM2.5 species concentrations from three geographically distinct cities (Houston, TX, Los Angeles County, CA, and Elizabeth, NJ) were analyzed using positive matrix factorization (PMF) and demonstrate that the composition and source contributions of ambient PM2.5 are substantially modified by outdoor-to-indoor transport. Our results suggest that predictions of "indoor PM2.5 of ambient origin" are improved when ambient PM2.5 is treated as a combination of four distinct particle types with differing infiltration behavior (primary combustion, secondary sulfate and organics, secondary nitrate, and mechanically generated PM) rather than as a "single internally mixed entity". Study-wide average infiltration factors (i.e., fraction of ambient PM2.5 found indoors) for Relationship of Indoor, Outdoor, and Personal Air (RIOPA) study homes were 0.51, 0.78, and 0.04 (consistent with P = 0.6, 0.9, and 0.09; k = 0.2, 0.1, and 0.6 h(-1)) for PM2.5 associated with primary combustion, secondary formation (excluding nitrate), and mechanical generation, respectively. Modification of the composition, properties, and source contributions of ambient PM2.5 in indoor environments has important implications for exposure mitigation strategies, development of health hypotheses, and evaluation of exposure error in epidemiological studies that use ambient central-site PM2.5 as a surrogate for PM2.5 exposure.     

Diagnosis of aged prescribed burning plumes impacting an urban area

An unanticipated wind shift led to the advection of plumes from two prescribed burning sites that impacted Atlanta, GA, producing a heavy smoke event late in the afternoon on February 28, 2007. Observed PM2.5 concentrations increased to over 140 microg/m3 and O3 concentrations up to 30 ppb in a couple of hours, despite the late hour in February when photochemistry is less vigorous. A detailed investigation of PM2.5 chemical composition and source apportionment analysis showed that the increase in PM2.5 mass was driven mainly by organic carbon (OC). However, both results from source apportionment and an observed nonlinear relationship between OC and PM2.5 potassium (K) indicate that the increased OC was not due solely to primary emissions. Most of the OC was water-soluble organic carbon (WSOC) and was dominated by hydrophobic compounds. The data are consistent with large enhancements in isoprenoid (isoprene and monoterpenes) and other volatile organic compounds emitted from prescribed burning that led to both significant O3 and secondary organic aerosol (SOA) production. Formation of oligomers from oxidation products of isoprenoid compounds or condensation of volatile organic compounds (VOCs) with multiple functional groups emitted during prescribed burning appears to be a major component of the secondary organic contributor of the SOA. The results from this study imply that enhanced emissions due to the fire itself and elevated temperature in the burning region should be considered in air quality models (e.g., receptor and emission-based models) to assess impacts of prescribed burning emissions on ambient air quality.     

Spatiotemporal aspects of real-time PM(2.5): low- and middle-income neighborhoods in Bangalore, India

We measured outdoor fine particulate matter (PM(2.5)) concentrations in a low- and a nearby middle-income neighborhood in Bangalore, India. Each neighborhood included sampling locations near and not near a major road. One-minute average concentrations were recorded for 168 days during September 2008 to May 2009 using a gravimetric-corrected nephelometer. We also measured wind speed and direction, and PM(2.5) concentration as a function of distance from road. Average concentrations are 21-46% higher in the low- than in the middle-income neighborhood, and exhibit differing spatiotemporal patterns. For example, in the middle-income neighborhood, median concentrations are higher near-road than not near-road (56 versus 50 μg m(-3)); in the low-income neighborhood, the reverse holds (68 μg m(-3) near-road, 74 μg m(-3) not near-road), likely because of within-neighborhood residential emissions (e.g., cooking; trash combustion). A moving-average subtraction method used to infer local- versus urban-scale emissions confirms that local emissions are greater in the low-income neighborhood than in the middle-income neighborhood; however, relative contributions from local sources vary by time-of-day. Real-time relative humidity correction factors are important for accurately interpreting real-time nephelometer data.     

Source apportionment of PAH in Hamilton Harbour suspended sediments: comparison of two factor analysis methods

A total of 26 suspended sediment samples collected over a 5-year period in Hamilton Harbour, Ontario, Canada and surrounding creeks were analyzed for a suite of polycyclic aromatic hydrocarbons and sulfur heterocycles. Hamilton Harbour sediments contain relatively high levels of polycyclic aromatic compounds and heavy metals due to emissions from industrial and mobile sources. Two receptor modeling methods using factor analyses were compared to determine the profiles and relative contributions of pollution sources to the harbor; these methods are principal component analyses (PCA) with multiple linear regression analysis (MLR) and positive matrix factorization (PMF). Both methods identified four factors and gave excellent correlation coefficients between predicted and measured levels of 25 aromatic compounds; both methods predicted similar contributions from coal tar/coal combustion sources to the harbor (19 and 26%, respectively). One PCA factor was identified as contributions from vehicular emissions (61%); PMF was able to differentiate vehicular emissions into two factors, one attributed to gasoline emissions sources (28%) and the other to diesel emissions sources (24%). Overall, PMF afforded better source identification than PCA with MLR. This work constitutes one of the few examples of the application of PMF to the source apportionment of sediments; the addition of sulfur heterocycles to the analyte list greatly aided in the source identification process.