Characterisation for some emission sources in CMB calculation for Mae Moh area, Thailand

Particulate samples of agricultural waste burning, straw burning, forest leaf burning, heavy duty truck emission, paved road dust, soil, agricultural soil, coal, electrostatic precipitator ash, and emission from stack power plant were collected from the Mae Moh area. Chemical compositions of sampling filters were analysed to determine the particulate matter source profiles. The analysis included ICP-MS for elemental compositions, ion chromatography for water soluble ions and CHNS/O for carbon species. In all biomass burning profiles organic carbon (OC) was higher during smouldering phase, while elemental carbon (EC) was higher during flaming phase. Results relating to biomass emission during flaming stage showed increase in K⁺. Organic and elemental carbons were the most abundant in biomass burning and truck exhaust. The abundance of EC was much lower, and the abundance of OC was much higher in biomass burning relative to truck exhaust emission. Al, K, Mg, Ca, and Fe were presented with high abundance in road dust, soil, coal, fly ash and stack samples. The differences in chemical compositions were not sufficient to distinguish geological material and fugitive dust sources. Fly ash profile differed from the others since OC and EC were not detected. Na and Zn were most abundant in stack samples. These findings served as a starting point for source contribution study. For future application of source apportionment using the CMB modelling technique, these source profiles should be appropriately grouped and selected to generate reliable outcomes.     

Seasonal and spatial trends in the sources of fine particle organic carbon in Israel,Jordan, and Palestine

A study of carbonaceous particulate matter (PM) was conducted in the Middle East at sites in Israel, Jordan, and Palestine. The sources and seasonal variation of organic carbon, as well as the contribution to fine aerosol (PM_2.5) mass, were determined. Of the 11 sites studied, Nablus had the highest contribution of organic carbon (OC), 29%, and elemental carbon (EC), 19%, to total PM_2.5 mass. The lowest concentrations of PM_2.5 mass, OC, and EC were measured at southern desert sites, located in Aqaba, Eilat, and Rachma. The OC contribution to PM_2.5 mass at these sites ranged between 9.4% and 16%, with mean annual PM_2.5 mass concentrations ranging from 21 to 25 ug m^?3. These sites were also observed to have the highest OC to EC ratios (4.1–5.0), indicative of smaller contributions from primary combustion sources and/or a higher contribution of secondary organic aerosol. Biomass burning and vehicular emissions were found to be important sources of carbonaceous PM in this region at the non-southern desert sites, which together accounted for 30%–55% of the fine particle organic carbon at these sites. The fraction of measured OC unapportioned to primary sources (1.4 μgC m^?3 to 4.9 μgC m^?3; 30%–74%), which has been shown to be largely from secondary organic aerosol, is relatively constant at the sites examined in this study. This suggests that secondary organic aerosol is important in the Middle East during all seasons of the year.     

Contribution of motor vehicle emissions to organic carbon and fine particle mass in Pittsburgh, Pennsylvania: Effects of varying source profiles and seasonal trends in ambient marker concentrations

We present estimates of the vehicular contribution to ambient organic carbon (OC) and fine particle mass (PM) in Pittsburgh, PA using the chemical mass balance (CMB) model and a large dataset of ambient molecular marker concentrations. Source profiles for CMB analysis are selected using a method of comparing the ambient ratios of marker species with published profiles for gasoline and diesel vehicle emissions. The ambient wintertime data cluster on a hopanes/EC ratio–ratio plot, and therefore can be explained by a large number of different source profile combinations. In contrast, the widely varying summer ambient ratios can be explained by a more limited number of source profile combinations. We present results for a number of different CMB scenarios, all of which perform well on the different statistical tests used to establish the quality of a CMB solution. The results illustrate how CMB estimates depend critically on the marker-to-OC and marker-to-PM ratios of the source profiles. The vehicular contribution in the winter is bounded between 13% and 20% of the ambient OC (274±56–416±72 ng-C m⁻³). However, variability in the diesel profiles creates uncertainty in the gasoline–diesel split. On an OC basis, one set of scenarios suggests gasoline dominance, while a second set indicates a more even split. On a PM basis, all solutions indicate a diesel-dominated split. The summer CMB solutions do not present a consistent picture given the seasonal shift and wide variation in the ambient hopanes-to-EC ratios relative to the source profiles. If one set of source profiles is applied to the entire dataset, gasoline vehicles dominate vehicular OC in the winter but diesel dominates in the summer. The seasonal pattern in the ambient hopanes-to-EC ratios may be caused by photochemical decay of hopanes in the summer or by seasonal changes in vehicle emission profiles.     

Fine particulate matter source apportionment for the Chemical speciation Trends Network site at Birmingham, Alabama, using Positive Matrix Factorization

The Positive Matrix Factorization (PMF) receptor model version 1.1 was used with data from the fine particulate matter (PM2.5) Chemical Speciation Trends Network (STN) to estimate source contributions to ambient PM2.5 in a highly industrialized urban setting in the southeastern United States. Model results consistently resolved 10 factors that are interpreted as two secondary, five industrial, one motor vehicle, one road dust, and one biomass burning sources. The STN dataset is generally not corrected for field blank levels, which are significant in the case of organic carbon (OC). Estimation of primary OC using the elemental carbon (EC) tracer method applied on a seasonal basis significantly improved the model's performance. Uniform increase of input data uncertainty and exclusion of a few outlier samples (associated with high potassium) further improved the model results. However, it was found that most PMF factors did not cleanly represent single source types and instead are "contaminated" by other sources, a situation that might be improved by controlling rotational ambiguity within the model. Secondary particulate matter formed by atmospheric processes, such as sulfate and secondary OC, contribute the majority of ambient PM2.5 and exhibit strong seasonality (37 +/- 10% winter vs. 55 +/- 16% summer average). Motor vehicle emissions constitute the biggest primary PM2.5 mass contribution with almost 25 +/- 2% long-term average and winter maximum of 29 +/- 11%. PM2.5 contributions from the five identified industrial sources vary little with season and average 14 +/- 1.3%. In summary, this study demonstrates the utility of the EC tracer method to effectively blank-correct the OC concentrations in the STN dataset. In addition, examination of the effect of input uncertainty estimates on model results indicates that the estimated uncertainties currently being provided with the STN data may be somewhat lower than the levels needed for optimum modeling results.     

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%).     

Identification of sources of Phoenix aerosol by positive matrix factorization

Chemical composition data for fine and coarse particles collected in Phoenix, AZ, were analyzed using positive matrix factorization (PMF). The objective was to identify the possible aerosol sources at the sampling site. PMF uses estimates of the error in the data to provide optimum data point scaling and permits a better treatment of missing and below-detection-limit values. It also applies nonnegativity constraints to the factors. Two sets of fine particle samples were collected by different samplers. Each of the resulting fine particle data sets was analyzed separately. For each fine particle data set, eight factors were obtained, identified as (1) biomass burning characterized by high concentrations of organic carbon (OC), elemental carbon (EC), and K; (2) wood burning with high concentrations of Na, K, OC, and EC; (3) motor vehicles with high concentrations of OC and EC; (4) nonferrous smelting process characterized by Cu, Zn, As, and Pb; (5) heavy-duty diesel characterized by high EC, OC, and Mn; (6) sea-salt factor dominated by Na and Cl; (7) soil with high values for Al, Si, Ca, Ti, and Fe; and (8) secondary aerosol with SO4(-2) and OC that may represent coal-fired power plant emissions. For the coarse particle samples, a five-factor model gave source profiles that are attributed to be (1) sea salt, (2) soil, (3) Fe source/motor vehicle, (4) construction (high Ca), and (5) coal-fired power plant. Regression of the PM mass against the factor scores was performed to estimate the mass contributions of the resolved sources. The major sources for the fine particles were motor vehicles, vegetation burning factors (biomass and wood burning), and coal-fired power plants. These sources contributed most of the fine aerosol mass by emitting carbonaceous particles, and they have higher contributions in winter. For the coarse particles, the major source contributions were soil and construction (high Ca). These sources also peaked in winter.     

Comparison and evaluation of chemically speciated mobile source PM2.5 particulate matter profiles

Mobile sources are significant contributors to ambient PM2.5, accounting for 50% or more of the total observed levels in some locations. One of the important methods for resolving the mobile source contribution is through chemical mass balance (CMB) receptor modeling. CMB requires chemically speciated source profiles with known uncertainty to ensure accurate source contribution estimates. Mobile source PM profiles are available from various sources and are generally in the form of weight fraction by chemical species. The weight fraction format is commonly used, since it is required for input into the CMB receptor model. This paper examines the similarities and differences in mobile source PM2.5 profiles that contain data for elements, ions, elemental carbon (EC) and organic carbon (OC), and in some cases speciated organics (e.g., polycyclic aromatic hydrocarbons [PAHs]), drawn from four different sources. Notable characteristics of the mass fraction data include variability (relative contributions of elements and ions) among supposedly similar sources and a wide range of average EC:OC ratios (0.60 +/- 0.53 to 1.42 +/- 2.99) for light-duty gasoline vehicles (LDGVs), indicating significant EC emissions from LDGVs in some cases. For diesel vehicles, average EC:OC ratios range from 1.09 +/- 2.66 to 3.54 +/- 3.07. That different populations of the same class of emitters can show considerable variability suggests caution should be exercised when selecting and using profiles in source apportionment studies.     

Trends,temporal and spatial characteristics,and uncertainties in biomass burning emissions in the Pearl River Delta,China

Multi-year inventories of biomass burning emissions were established in the Pearl River Delta (PRD) region for the period 2003–2007 based on the collected activity data and emission factors. The results indicated that emissions of sulfur dioxide (SO₂), nitrogen oxide (NO_x), ammonia (NH₃), methane (CH₄), organic carbon (OC), non-methane volatile organic compounds (NMVOC), carbon monoxide (CO), and fine particulate matter (PM_2.5) presented clear declining trends. Domestic biofuel burning was the major contributor, accounting for more than 60% of the total emissions. The preliminary temporal profiles were established with MODIS fire count information, showing that higher emissions were observed in winter (from November to March) than other seasons. The emissions were spatially allocated into grid cells with a resolution of 3 km × 3  km, using GIS-based land use data as spatial surrogates. Large amount of emissions were observed mostly in the less developed areas in the PRD region. The uncertainties in biomass burning emission estimates were quantified using Monte Carlo simulation; the results showed that there were higher uncertainties in organic carbon (OC) and elemental carbon (EC) emission estimates, ranging from ?71% to 133% and ?70% to 128%, and relatively lower uncertainties in SO₂, NO_x and CO emission estimates. The key uncertainty sources of the developed inventory included emission factors and parameters used for estimating biomass burning amounts.     

Chemical composition and source apportionment of PM2.5 particles in the Sihwa area, Korea

To investigate the chemical characteristics of fine particles in the Sihwa area, Korea, atmospheric aerosol samples were collected using a dichotomous PM10 sampler and two URG PM2.5 cyclone samplers during five intensive sampling periods between February 1998 and February 1999. The Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS), ion chromatograph (IC), and thermal manganese dioxide oxidation (TMO) methods were used to analyze the trace elements, ionic species, and carbonaceous species, respectively. Backward trajectory analysis, factor analysis, and a chemical mass balance (CMB) model were used to estimate quantitatively source contributions to PM2.5 particles collected in the Sihwa area. The results of PM2.5 source apportionment using the CMB7 receptor model showed that (NH4)2SO4 was, on average, the major contributor to PM2.5 particles, followed by nontraffic organic carbon (OC) emission, NH4NO3, agricultural waste burning, motor vehicle emission, road dust, waste incineration, marine aerosol, and others. Here, the nontraffic OC sources include primary anthropogenic OC emitted from the industrial complex zone, secondary OC, and organic species from distant sources. The source impact of waste incineration emission became significant when the dominant wind directions were from southwest and west sectors during the sampling periods. It was found that PM2.5 particles in the Sihwa area were influenced mainly by both anthropogenic local sources and long-range transport and transformation of air pollutants.     

Identification of Sources of Phoenix Aerosol by Positive Matrix Factorization

ABSTRACT

Chemical composition data for fine and coarse particles collected in Phoenix, AZ, were analyzed using positive matrix factorization (PMF). The objective was to identify the possible aerosol sources at the sampling site. PMF uses estimates of the error in the data to provide optimum data point scaling and permits a better treatment of missing and below-detection-limit values. It also applies nonnegativity constraints to the factors. Two sets of fine particle samples were collected by different samplers. Each of the resulting fine particle data sets was analyzed separately. For each fine particle data set, eight factors were obtained, identified as (1) biomass burning characterized by high concentrations of organic carbon (OC), elemental carbon (EC), and K; (2) wood burning with high concentrations of Na, K, OC, and EC; (3) motor vehicles with high concentrations of OC and EC; (4) nonferrous smelting process characterized by Cu, Zn, As, and Pb; (5) heavy-duty diesel characterized by high EC, OC, and Mn; (6) sea-salt factor dominated by Na and Cl; (7) soil with high values for Al, Si, Ca, Ti, and Fe; and (8) secondary aerosol with SO₄ ^-2 and OC that may represent coal-fired power plant emissions.

For the coarse particle samples, a five-factor model gave source profiles that are attributed to be (1) sea salt, (2) soil, (3) Fe source/motor vehicle, (4) construction (high Ca), and (5) coal-fired power plant. Regression of the PM mass against the factor scores was performed to estimate the mass contributions of the resolved sources. The major sources for the fine particles were motor vehicles, vegetation burning factors (biomass and wood burning), and coal-fired power plants. These sources contributed most of the fine aerosol mass by emitting carbonaceous particles, and they have higher contributions in winter. For the coarse particles, the major source contributions were soil and construction (high Ca). These sources also peaked in winter.     

Historical estimation of carbonaceous aerosol emissions from biomass open burning in China for the period 1990-2005

Multi-year inventories of carbonaceous aerosol emissions from biomass open burning at a high spatial resolution of 0.5° × 0.5° have been constructed in China using GIS methodology for the period 1990-2005. Black carbon (BC) emissions have increased by 383.03% at an annual average rate of 25.54% from 14.05 Gg in 1990 to 67.87 Gg in 2005; while organic carbon (OC) emissions have increased by 365.43% from 57.37 Gg in 1990 to 267.00 Gg in 2005. Through the estimation period, OC/BC ratio for biomass burning was averagely 4.09, suggesting that it was not the preferred control source from a climatic perspective. Spatial distribution of BC and OC emissions were similar, mainly concentrated in three northeastern provinces, central provinces of Shandong, Jiangsu, Anhui and Henan, and southern provinces of Guangxi, Guangdong, Hunan and Sichuan basin, covering 24.89% of China’s territory, but were responsible for 63.38% and 67.55% of national BC and OC emissions, respectively.     

Comparison and Evaluation of Chemically Speciated Mobile Source PM2.5 Particulate Matter Profiles

ABSTRACT

Mobile sources are significant contributors to ambient PM_{2 5}, accounting for 50% or more of the total observed levels in some locations. One of the important methods for resolving the mobile source contribution is through chemical mass balance (CMB) receptor modeling. CMB requires chemically speciated source profiles with known uncertainty to ensure accurate source contribution estimates. Mobile source PM profiles are available from various sources and are generally in the form of weight fraction by chemical species. The weight fraction format is commonly used, since it is required for input into the CMB receptor model. This paper examines the similarities and differences in mobile source PM_2.5 profiles that contain data for elements, ions, elemental carbon (EC) and organic carbon (OC), and in some cases speciated organics (e.g., polycyclic aromatic hydrocarbons [PAHs]), drawn from four different sources.

Notable characteristics of the mass fraction data include variability (relative contributions of elements and ions) among supposedly similar sources and a wide range of average EC:OC ratios (0.60 ± 0.53 to 1.42 ± 2.99) for light-duty gasoline vehicles (LDGVs), indicating significant EC emissions from LDGVs in some cases. For diesel vehicles, average EC:OC ratios range from 1.09 ± 2.66 to 3.54 ± 3.07. That different populations of the same class of emitters can show considerable variability suggests caution should be exercised when selecting and using profiles in source apportionment studies.     

Fine Particle Receptor Modeling in the Atmosphere of Mexico City

Abstract

Source apportionment analyses were carried out by means of receptor modeling techniques to determine the contribution of major fine particulate matter (PM_2.5) sources found at six sites in Mexico City. Thirty-six source profiles were determined within Mexico City to establish the fingerprints of particulate matter sources. Additionally, the profiles under the same source category were averaged using cluster analysis and the fingerprints of 10 sources were included. Before application of the chemical mass balance (CMB), several tests were carried out to determine the best combination of source profiles and species used for the fitting. CMB results showed significant spatial variations in source contributions among the six sites that are influenced by local soil types and land use. On average, 24-hr PM_2.5 concentrations were dominated by mobile source emissions (45%), followed by secondary inorganic aerosols (16%) and geological material (17%). Industrial emissions representing oil combustion and incineration contributed less than 5%, and their contribution was higher at the industrial areas of Tlalnepantla (11%) and Xalostoc (8%). Other sources such as cooking, biomass burning, and oil fuel combustion were identified at lower levels. A second receptor model (principal component analysis, [PCA]) was subsequently applied to three of the monitoring sites for comparison purposes. Although differences were obtained between source contributions, results evidence the advantages of the combined use of different receptor modeling techniques for source apportionment, given the complementary nature of their results. Further research is needed in this direction to reach a better agreement between the estimated source contributions to the particulate matter mass.     

The distribution of particle-phase organic compounds in the atmosphere and their use for source apportionment during the Southern California Children''s Health Study

Atmospheric particulate matter (PM) samples from 12 sites in southern California, collected as part of the Southern California Children's Health Study (SCCHS), were analyzed using gas chromatography/mass spectrometry (GC/MS) techniques. Ninety-four organic compounds were quantified in these samples, including n-alkanes, fatty acids, polycyclic aromatic hydrocarbons (PAH), hopanes, steranes, aromatic diacids, aliphatic diacids, resin acids, methoxyphenols, and levoglucosan. Annual average concentrations of all detected compounds, as well as average concentrations for three seasonal periods, were determined at all 12 sites for the calendar year of 1995. These measurements provide important information about the seasonal and spatial distribution of particle-phase organic compounds in southern California. Also, co-located samples from one site were analyzed to assess precision of measurement. Excellent agreement was observed between annual average concentrations for the broad range of organic compounds measured in this study. Measured concentrations from the 12 sampling sites were used in a previously developed molecular-marker source apportionment model to quantify the primary source contributions to the PM10 organic carbon and mass concentrations at these 12 sites. Source contributions to atmospheric PM from six important air pollution sources were quantified: gasoline-powered motor vehicle exhaust, diesel vehicle exhaust, wood smoke, vegetative detritus, tire wear, and natural gas combustion. Important trends in the seasonal and spatial patterns of the impact of these six sources were observed. In addition, contributions from meat smoke were detected in selected samples.     

Evaluations of the chemical mass balance method for determining contributions of gasoline and diesel exhaust to ambient carbonaceous aerosols

The US. Department of Energy Gasoline/Diesel PM Split Study was conducted to assess the sources of uncertainties in using an organic compound-based chemical mass balance receptor model to quantify the relative contributions of emissions from gasoline (or spark ignition [SI]) and diesel (or compression ignition [CI]) engines to ambient concentrations of fine particulate matter (PM2.5) in California's South Coast Air Basin (SOCAB). In this study, several groups worked cooperatively on source and ambient sample collection and quality assurance aspects of the study but worked independently to perform chemical analysis and source apportionment. Ambient sampling included daily 24-hr PM2.5 samples at two air quality-monitoring stations, several regional urban locations, and along freeway routes and surface streets with varying proportions of automobile and truck traffic. Diesel exhaust was the dominant source of total carbon (TC) and elemental carbon (EC) at the Azusa and downtown Los Angeles, CA, monitoring sites, but samples from the central part of the air basin showed nearly equal apportionments of CI and SI. CI apportionments to TC were mainly dependent on EC, which was sensitive to the analytical method used. Weekday contributions of CI exhaust were higher for Interagency Monitoring of Protected Visual Environments (IMPROVE; 41+/-3.7%) than Speciation Trends Network (32+/-2.4%). EC had little effect on SI apportionment. SI apportionments were most sensitive to higher molecular weight polycyclic aromatic hydrocarbons (indeno[123-cd]pyrene, benzo(ghi)perylene, and coronene) and several steranes and hopanes, which were associated mainly with high emitters. Apportionments were also sensitive to choice of source profiles. CI contributions varied from 30% to 60% of TC when using individual source profiles rather than the composites used in the final apportionments. The apportionment of SI vehicles varied from 1% to 12% of TC depending on the specific profile that was used. Up to 70% of organic carbon (OC) in the ambient samples collected at the two fixed monitoring sites could not be apportioned to directly emitted PM emissions.     

Estimates of the contributions of biogenic and anthropogenic hydrocarbons to secondary organic aerosol at a southeastern US location

An organic tracer-based method containing laboratory and field study components was used to estimate the secondary organic aerosol (SOA) contributions of biogenic and anthropogenic hydrocarbons to ambient organic carbon (OC) concentrations in PM_2.5 during 2003 in Research Triangle Park, NC. In the laboratory, smog chamber experiments were conducted where isoprene, α-pinene, β-caryophyllene, and toluene were individually irradiated in the presence of NO_X. In each experiment, SOA was collected and analyzed for potential tracer compounds, whose concentrations were used to calculate a mass fraction of tracer compounds for each hydrocarbon. In the field, 33 PM_2.5 samples were collected and analyzed for (1) tracer compounds observed in the laboratory irradiations, (2) levoglucosan, a biomass burning tracer, and (3) total OC. For each of the four hydrocarbons, the SOA contributions to ambient OC concentrations were estimated using the tracer concentrations and the laboratory-derived mass fractions. The estimates show SOA formation from isoprene, α-pinene, β-caryophyllene, and toluene contributed significantly to the ambient OC concentrations. The relative contributions were highly seasonal with biomass burning in the winter accounting for more than 50% of the OC concentrations, while SOA contributions remained low. However, during the 6-month period between May and October, SOA from the precursor hydrocarbons contributed more than 40% of the measured OC concentration. Although the tracer-based method is subject to considerable uncertainty due to the simplification of replacing the complex set of chemical reactions responsible for SOA with a laboratory-derived single-valued mass fraction, the results suggest this approach can be used to identify major sources of SOA which can assist in the development of air quality models.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.     

Comparison of the physical and chemical characteristics of fine road dust at different urban sites

The size distribution and chemical components of a fine fraction (<2.5 μm) of road dust collected at urban sites in Korea (Gwangju) and Mongolia (Ulaanbaatar) where distinct urban characteristics exist were measured. A clear bimodal size distribution was observed for the resuspended fine road dust at the urban sites in Korea. The first mode peaked at 100–110 nm, and the second peak was observed at 435–570 nm. Ultrafine mode (~30 nm) was found for the fine road dust at the Mongolia site, which was significantly affected by residential coal/biomass burning. The contribution of the water-soluble ions to the fine road dust was higher at the sites in Mongolia (15.8–16.8%) than at those in Korea (1.2–4.8%). Sulfate and chloride were the most dominant ionic species for the fine road dust in Mongolia. As (arsenic) was also much higher for the Mongolian road dust than the others. The sulfate, chloride, and As mainly come from coal burning activity, suggesting that coal and biomass combustion in Mongolia during the heating season should affect the size and chemical components of the fine road dust. Cu (copper) and Zn (zinc), carbonaceous particles (organic carbon [OC] and elemental carbon [EC]) increased at sites in Korea, suggesting that the fine road dust at these sites was significantly affected by the high volume of traffic (engine emission and brake/tire wear). Our results suggest that chemical profiles for road dust specific to certain sites should be applied to more accurately apportion road dust source contributing to the ambient particulate matter.

Implications: Size and chemical characteristics of fine road dust at sites having distinct urban characteristics were examined. Residential coal and biomass burning and traffic affected physiochemical properties of the fine road dust. Different road dust profiles at different sites should be needed to determine the ambient PM2.5 sources more accurately.     

Wood burning impact on PM10 in three Austrian regions

Anhydrosugars (levoglucosan, mannosan and galactosan) were investigated during one year in three Austrian regions at three types of sites (city-heavy traffic-impacted, city-residential and background) in order to assess the magnitude of the contribution of wood smoke to the particulate matter load and its organic fraction. The annually averaged concentrations of levoglucosan ranged from 0.12 to 0.48 μg m^?3. The levoglucosan concentration exhibited a strong annual cycle with higher concentrations in the cold season. The minor anhydrosugars had a similar annual trend, but their concentrations were lower by a factor of about 5 and about 25 in the cold season for mannosan and galactosan, respectively. Levoglucosan concentrations were higher at the inner-urban as compared to rural sites. The contribution of wood smoke to organic carbon and PM₁₀ levels was calculated using a constant ratio of levoglucosan and OC, respectively PM₁₀ as derived for fire wood typical for Alpine European regions [Schmidl, C., Marr, I.L., Caseiro, A.e, Kotianová, P., Berner, A., Bauer, H., Kasper-Giebl, A., Puxbaum, H., 2008a. Chemical characterisation of fine particle emissions from wood stove combustion of common woods growing in mid-European Alpine regions. Atmospheric Environment 42, 126–141]. The estimated contribution of wood smoke-OC to the OC of PM₁₀ ranged from one third to more than half in the cold season with higher contributions up to 70% in winter (December, January and February) in the smaller cities and the rural background. This indicates, that wood smoke is the predominant source of organic material at rural and small urban sites in central Europe. Consistently, wood smoke was an important contributor to PM₁₀ during the cold season, with contributions of around 10% in the Vienna larger region and around 20% at rural sites in the densely forested regions of Salzburg and Styria during the winter months. In those regions residential sites exhibited highest relative wood smoke contents in PM₁₀ during autumn (September till November), indicating the use of wood stoves for auxiliary heating in the transition of warm to cold season. Using the relationships between the different anhydrosugars the combustion of softwood was found to be dominant for the wood smoke occurrence in ambient air at the investigated sites. Potassium, a commonly used tracer for biomass burning, correlated well to levoglucosan, with a mass ratio of around 0.80 in the cold season.     

Source contribution of atmospheric aerosols in Bangkok metropolitan area by CMB8 receptor model

The CMB₈ model was applied for source apportionment of particulate matter in Bangkok area. The 24 h of ambient data were collected and analysed for elemental composition during December 1996 to January 1997 by high volume air samplers at a station in Bangkok, Thailand. Seven source profiles and the average mass concentrations of 42 ambient data were used to run the chemical mass balance (CMB₈) model. The source apportionment by CMB₈ gave similar results comparing with factor analysis – multiple regression (FA–MR) model of the same data. The results revealed that major sources of particulate matter in Bangkok were: soil (33%), road dust (33%) and automobile (15%). The minor source contributions were: sea salt (4.34%), refuse incineration and biomass burning (0.84%), steel mill (0.62%) and fuel oil combustion (0.35%). The lack of source profile for biomass or open burning in Bangkok resulted in much lower predicted contribution of this source when compared to that from FA–MR. When apply this CMB₈ model with daily ambient data, the result revealed that one fourth of daily CMB₈ source apportionment had high value of ² (>4). These exceedance values of Chi² also point out that one of the selected sources (biomass burning) may not be the true contributing sources. Presumably, accurate biomass burning source profile is needed to improve the CMB calculation of source contributions for particulate matter in Bangkok metropolitan area.