Assessment of Secondary Organic Carbon in the Southeastern United States: A Review

Abstract

Organic carbon (OC) is one of the major components of ambient PM_2.5 (particulate matter [PM] ≤ 2.5 µm in aerodynamic diameter) and a significant portion of OC is from secondary organic aerosol (SOA) formation in the southeastern United States. Various approaches (based on measurement and modeling results) are applied to estimate secondary organic carbon (SOC) and its origins in the region. SOC estimates by various methods are consistent as to clear seasonal variation (i.e., relatively higher SOC in summer) and little spatial variability (i.e., a regional characteristic of SOC). However, there are differences as to the origins of SOC. SOA organic tracer and emission-based modeling studies indicate that the biogenic origin of SOC is dominant in the Southeast, showing that biogenic-origin SOC accounts for 90% of SOC in summer and more than 70% even in other seasons. However, results from other studies suggest that the anthropogenic origin of SOC is dominant, significant amounts of anthropogenic-origin SOC, or important roles of anthropogenic pollutants for SOA formation, especially at urban areas, as strong correlations between water-soluble OC (an indicator of SOC) and anthropogenic pollutants, considerable amounts of fossil water-soluble OC, and significant contributions of fossil SOC (37–52% in summer months, 70–73% in winter months) are observed. Therefore, more studies are needed to reconcile the differences in the source attribution of SOC measurements.     

Characterization of carbonaceous species in PM2.5 in Xi'an during spring

The characterization of carbonaceous species in PM_2.5 during a spring period in a suburb of Xi'an, China was investigated. PM_2.5 samples were collected on quartz filters and analyzed for organic carbon (OC) and elemental carbon (EC). The thermal optical reflectance method was used. The minimum OC/EC ratio method was used to estimate the concentration of secondary organic carbon (SOC). The distribution of eight carbon fractions was investigated as well. The average mass concentrations of OC and EC were 15.90 and 8.38 μg/m³, respectively. The average OC/EC ratio ranged from 1.16 to 3.16 with an average value of 2.25. This implies the existence of SOC in PM_2.5. The mean SOC concentration was 7.20 μg/m³, accounting for 45.28% of total OC. This result suggests that SOC is a significant component of OC in the suburb of Xi'an. Results from the distribution of eight carbon fractions revealed that emissions from motor vehicle, coal combustion, and road dust were the main source of carbonaceous particles in the sampling period.     

PM2.5 source apportionment with organic markers in the Southeastern Aerosol Research and Characterization (SEARCH) study

Positive matrix factorization (PMF) and effective variance (EV) solutions to the chemical mass balance (CMB) were applied to PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) mass and chemically speciated measurements for samples taken from 2008 to 2010 at the Atlanta, Georgia, and Birmingham, Alabama, sites. Commonly measured PM_2.5 mass, elemental, ionic, and thermal carbon fraction concentrations were supplemented with detailed nonpolar organic speciation by thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS). Source contribution estimates were calculated for motor vehicle exhaust, biomass burning, cooking, coal-fired power plants, road dust, vegetative detritus, and secondary sulfates and nitrates for Atlanta. Similar sources were found for Birmingham, with the addition of an industrial source and the separation of biomass burning into open burning and residential wood combustion. EV-CMB results based on conventional species were qualitatively similar to those estimated by PMF-CMB. Secondary ammonium sulfate was the largest contributor, accounting for 27–38% of PM_2.5, followed by biomass burning (21–24%) and motor vehicle exhaust (9–24%) at both sites, with 4–6% of PM_2.5 attributed to coal-fired power plants by EV-CMB. Including organic compounds in the EV-CMB reduced the motor vehicle exhaust and biomass burning contributions at both sites, with a 13–23% deficit for PM_2.5 mass. The PMF-CMB solution showed mixing of sources within the derived factors, both with and without the addition of speciated organics, as is often the case with complex source mixtures such as those at these urban-scale sites. The nonpolar TD-GC/MS compounds can be obtained from existing filter samples and are a useful complement to the elements, ions, and carbon fractions. However, they should be supplemented with other methods, such as TD-GC/MS on derivitized samples, to obtain a wider range of polar compounds such as sterols, sugars, and organic acids. The PMF and EV solutions to the CMB equations are complementary to, rather than replacements for, each other, as comparisons of their results reveal uncertainties that are not otherwise evident.

Implications:?Organic markers can be measured on currently acquired PM_2.5 filter samples by thermal methods. These markers can complement element, ion, and carbon fraction measurements from long-term speciation networks. Applying the positive matrix factorization and effective variance solutions for the chemical mass balance equations provides useful information on the accuracy of the source contribution estimates. Nonpolar compounds need to be complemented with polar compounds to better apportion cooking and secondary organic aerosol contributors.     

Insights into the primary–secondary and regional–local contributions to organic aerosol and PM2.5 mass in Pittsburgh,Pennsylvania

This paper presents chemical mass balance (CMB) analysis of organic molecular marker data to investigate the sources of organic aerosol and PM_2.5 mass in Pittsburgh, Pennsylvania. The model accounts for emissions from eight primary source classes, including major anthropogenic sources such as motor vehicles, cooking, and biomass combustion as well as some primary biogenic emissions (leaf abrasion products). We consider uncertainty associated with selection of source profiles, selection of fitting species, sampling artifacts, photochemical aging, and unknown sources. In the context of the overall organic carbon (OC) mass balance, the contributions of diesel, wood-smoke, vegetative detritus, road dust, and coke-oven emissions are all small and well constrained; however, estimates for the contributions of gasoline-vehicle and cooking emissions can vary by an order of magnitude. A best-estimate solution is presented that represents the vast majority of our CMB results; it indicates that primary OC only contributes 27±8% and 50±14% (average±standard deviation of daily estimates) of the ambient OC in the summer and winter, respectively. Approximately two-thirds of the primary OC is transported into Pittsburgh as part of the regional air mass. The ambient OC that is not apportioned by the CMB model is well correlated with secondary organic aerosol (SOA) estimates based on the EC-tracer method and ambient concentrations of organic species associated with SOA. Therefore, SOA appears to be the major component of OC, not only in summer, but potentially in all seasons. Primary OC dominates the OC mass balance on a small number of nonsummer days with high OC concentrations; these events are associated with specific meteorological conditions such as local inversions. Primary particulate emissions only contribute a small fraction of the ambient fine-particle mass, especially in the summer.     

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.     

Sources of organic aerosol: Positive matrix factorization of molecular marker data and comparison of results from different source apportionment models

This paper presents results from positive matrix factorization (PMF) of organic molecular marker data to investigate the sources of organic carbon (OC) in Pittsburgh, Pennsylvania. PMF analysis of 21 different combinations of input species found essentially the same seven factors with distinctive source-class-specific groupings of molecular markers. To link factors with source classes we directly compare PMF factor profiles with actual source profiles. Six of the PMF factors appear related to primary emissions from sources such as motor vehicles, biomass combustion, and food cooking. Each primary factor contributed between 5% and 10% of the annual-average OC with the exception of the cooking related factor which contributed 20% of the OC. However, the contribution of the cooking factor was sensitive to the specific combinations of input species. PMF could not differentiate between gasoline and diesel emissions, but the aggregate contribution of primary emissions from these two source classes is estimated to be less than 10% of the annual-average OC. One factor appears related to secondary organic aerosol based on its substantial contribution to biogenic oxidation products. This secondary factor contributed more than 50% of the summertime average OC. Reasonable agreement was observed between the PMF results and those of a previously published chemical mass balance (CMB) analysis of the same molecular marker dataset. Individual PMF factors are correlated with specific CMB sources, but systematic biases exist between the two estimates. These biases were generally within the uncertainty of the two estimates, but there is also evidence that PMF is not cleanly differentiating between source classes.     

Insights into the nature of secondary organic aerosol in Mexico City during the MILAGRO experiment 2006

This study targets understanding the secondary sources of organic aerosol in Mexico City during the Megacities Impact on Regional and Global Environment (MIRAGE) 2006 field campaign. Ambient PM_2.5 was collected daily at urban and peripheral locations. Particle-phase secondary organic aerosol (SOA) products of anthropogenic and biogenic precursor gases were measured by gas chromatography mass spectrometry. Ambient concentrations of SOA tracers were used to estimate organic carbon (OC) from secondary origins (SOC). Anthropogenic SOC was estimated as 20–25% of ambient OC at both sites, while biogenic SOC was less abundant, but was relatively twice as important at the peripheral site. The OC that was not attributed secondary sources or to primary sources in a previous study showed temporal consistency with biomass-burning events, suggesting the importance of secondary processing of biomass-burning emissions in the region. The best estimate of biomass-burning-related SOC was in the range of 20–30% of ambient OC during peak biomass burning events. Low-molecular weight (MW) alkanoic and alkenoic dicarboxylic acids (C₂–C₅) were also measured, of which oxalic acid was the most abundant. The spatial and temporal trends of oxalic acid differed from tracers for primary and secondary sources, suggesting that it had different and/or multiple sources in the atmosphere.     

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

Abstract

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

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.     

Chemical characterization and source apportionment of fine and coarse particulate matter in Lahore,Pakistan

Lahore, Pakistan is an emerging megacity that is heavily polluted with high levels of particle air pollution. In this study, respirable particulate matter (PM_2.5 and PM₁₀) were collected every sixth day in Lahore from 12 January 2007 to 19 January 2008. Ambient aerosol was characterized using well-established chemical methods for mass, organic carbon (OC), elemental carbon (EC), ionic species (sulfate, nitrate, chloride, ammonium, sodium, calcium, and potassium), and organic species. The annual average concentration (±one standard deviation) of PM_2.5 was 194 ± 94 μg m^?3 and PM₁₀ was 336 ± 135 μg m^?3. Coarse aerosol (PM_10?2.5) was dominated by crustal sources like dust (74 ± 16%, annual average ± one standard deviation), whereas fine particles were dominated by carbonaceous aerosol (organic matter and elemental carbon, 61 ± 17%). Organic tracer species were used to identify sources of PM_2.5 OC and chemical mass balance (CMB) modeling was used to estimate relative source contributions. On an annual basis, non-catalyzed motor vehicles accounted for more than half of primary OC (53 ± 19%). Lesser sources included biomass burning (10 ± 5%) and the combined source of diesel engines and residual fuel oil combustion (6 ± 2%). Secondary organic aerosol (SOA) was an important contributor to ambient OC, particularly during the winter when secondary processing of aerosol species during fog episodes was expected. Coal combustion alone contributed a small percentage of organic aerosol (1.9 ± 0.3%), but showed strong linear correlation with unidentified sources of OC that contributed more significantly (27 ± 16%). Brick kilns, where coal and other low quality fuels are burned together, are suggested as the most probable origins of unapportioned OC. The chemical profiling of emissions from brick kilns and other sources unique to Lahore would contribute to a better understanding of OC sources in this megacity.     

Chemical Composition and Source Apportionment of PM25 Particles in the Sihwa Area,Korea

ABSTRACT

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 PM_2.5 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 PM_{2 5} particles collected in the Sihwa area.

The results of PM_2.5 source apportionment using the CMB7 receptor model showed that (NH₄)₂SO₄ was, on average, the major contributor to PM_2.5 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 PM_2.5 particles in the Sihwa area were influenced mainly by both anthropogenic local sources and long-range transport and transformation of air pollutants.     

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.     

Calibration and Certification of Audit Devices for Transmissometers

Abstract

Speciated fine particulate matter (PM_2.5) data collected as part of the Speciation Trends Network at four sites in the Midwest (Detroit, MI; Cincinnati, OH; Indianapolis, IN; and Northbrook, IL) and as part of the Interagency Monitoring of Protected Visual Environments program at the rural Bondville, IL, site were analyzed to understand sources contributing to organic carbon (OC) and PM_2.5 mass. Positive matrix factorization (PMF) was applied to available data collected from January 2002 through March 2005, and seven to nine factors were identified at each site. Common factors at all of the sites included mobile (gasoline)/secondary organic aerosols with high OC, diesel with a high elemental carbon/OC ratio (only at the urban sites), secondary sulfate, secondary nitrate, soil, and biomass burning. Identified industrial factors included copper smelting (North–brook, Indianapolis, and Bondville), steel/manufacturing with iron (Northbrook), industrial zinc (North–brook, Cincinnati, Indianapolis, and Detroit), metal plating with chromium and nickel (Detroit, Indianapolis, and Bondville), mixed industrial with copper and iron (Cincinnati), and limestone with calcium and iron (Bondville). PMF results, on average, accounted for 96% of the measured PM_2.5 mass at each site; residuals were consistently within tolerance (±3), and goodness–of–fit (Q) was acceptable. Potential source contribution function analysis helped identify regional and local impacts of the identified source types. Secondary sulfate and soil factors showed regional characteristics at each site, whereas industrial sources typically appeared to be locally influenced. These regional factors contributed approximately one third of the total PM_2.5 mass, on average, whereas local mobile and industrial sources contributed to the remaining mass. Mobile sources were a major contributor (55–76% at the urban sites) to OC mass, generally with at least twice as much mass from nondiesel sources as from diesel. Regional OC associated with secondary sulfate and soil was generally low.     

Source apportionment of fine particles at urban background and rural sites in the UK atmosphere

Airborne fine particulate matter (PM_2.5) has been collected at two sites in the West Midlands conurbation, UK, representing urban background and rural locations. Chemical analyses have been carried out for major anions, trace metals, total OC and EC, and for individual organic marker species including n-alkanes, hopanes, PAHs, organic acids and sterols. Source apportionment has been conducted using both a pragmatic mass closure model and the US EPA chemical mass balance (CMB) model. The pragmatic mass closure model is well able to account for the measured PM_2.5 mass in terms of chemical/source components, and the chemical mass balance model has been used to apportion the carbonaceous component of the aerosol. The dominant components of PM_2.5 at both sites are secondary inorganic (sulphate and nitrate) and carbonaceous particles. The CMB model shows the latter to arise mainly from road traffic sources, with smaller contributions from vegetative detritus, wood smoke, natural gas, coal, and dust/soil. The CMB model also identifies an important component of the organic aerosol not associated with these primary sources, which correlates very strongly with secondary organic aerosol estimated from the OC/EC ratio. The split between different automotive source types does not relate well to UK emission inventories, and may indicate that CMB source profiles from North American studies and different carbon analysis protocols may lead to erroneous conclusions.     

Assessment of secondary organic carbon in the Southeastern United States: a review

Organic carbon (OC) is one of the major components of ambient PM2.5 (particulate matter [PM] < or = 2.5 microm in aerodynamic diameter) and a significant portion of OC is from secondary organic aerosol (SOA) formation in the southeastern United States. Various approaches (based on measurement and modeling results) are applied to estimate secondary organic carbon (SOC) and its origins in the region. SOC estimates by various methods are consistent as to clear seasonal variation (i.e., relatively higher SOC in summer) and little spatial variability (i.e., a regional characteristic of SOC). However, there are differences as to the origins of SOC. SOA organic tracer and emission-based modeling studies indicate that the biogenic origin of SOC is dominant in the Southeast, showing that biogenic-origin SOC accounts for 90% of SOC in summer and more than 70% even in other seasons. However, results from other studies suggest that the anthropogenic origin of SOC is dominant, significant amounts of anthropogenic-origin SOC, or important roles of anthropogenic pollutants for SOA formation, especially at urban areas, as strong correlations between water-soluble OC (an indicator of SOC) and anthropogenic pollutants, considerable amounts of fossil water-soluble OC, and significant contributions of fossil SOC (37-52% in summer months, 70-73% in winter months) are observed. Therefore, more studies are needed to reconcile the differences in the source attribution of SOC measurements.     

Quantification of self pollution from two diesel school buses using three independent methods

We monitored two Seattle school buses to quantify the buses’ self pollution using the dual tracers (DT), lead vehicle (LV), and chemical mass balance (CMB) methods. Each bus drove along a residential route simulating stops, with windows closed or open. Particulate matter (PM) and its constituents were monitored in the bus and from a LV. We collected source samples from the tailpipe and crankcase emissions using an on-board dilution tunnel. Concentrations of PM₁, ultrafine particle counts, elemental and organic carbon (EC/OC) were higher on the bus than the LV. The DT method estimated that the tailpipe and the crankcase emissions contributed 1.1 and 6.8 μg m^?3 of PM_2.5 inside the bus, respectively, with significantly higher crankcase self pollution (SP) when windows were closed. Approximately two-thirds of in-cabin PM_2.5 originated from background sources. Using the LV approach, SP estimates from the EC and the active personal DataRAM (pDR) measurements correlated well with the DT estimates for tailpipe and crankcase emissions, respectively, although both measurements need further calibration for accurate quantification. CMB results overestimated SP from the DT method but confirmed crankcase emissions as the major SP source. We confirmed buses’ SP using three independent methods and quantified crankcase emissions as the dominant contributor.     

Contribution of Primary and Secondary Sources to Organic Aerosol and PM2.5 at SEARCH Network Sites

Abstract

Chemical tracer methods for determining contributions to primary organic aerosol (POA) are fairly well established, whereas similar techniques for secondary organic aerosol (SOA), inherently complicated by time-dependent atmospheric processes, are only beginning to be studied. Laboratory chamber experiments provide insights into the precursors of SOA, but field data must be used to test the approaches. This study investigates primary and secondary sources of organic carbon (OC) and determines their mass contribution to particulate matter 2.5 µm or less in aerodynamic diameter (PM_2.5) in Southeastern Aerosol Research and Characterization (SEARCH) network samples. Filter samples were taken during 20 24-hr periods between May and August 2005 at SEARCH sites in Atlanta, GA (JST); Birmingham, AL (BHM); Centerville, AL (CTR); and Pensacola, FL (PNS) and analyzed for organic tracers by gas chromatography-mass spectrometry. Contribution to primary OC was made using a chemical mass balance method and to secondary OC using a mass fraction method. Aerosol masses were reconstructed from the contributions of POA, SOA, elemental carbon, inorganic ions (sulfate [SO₄ ^2?], nitrate [NO₃ ^?], ammonium [NH₄ ⁺]), metals, and metal oxides and compared with the measured PM_2.5. From the analysis, OC contributions from seven primary sources and four secondary sources were determined. The major primary sources of carbon were from wood combustion, diesel and gasoline exhaust, and meat cooking; major secondary sources were from isoprene and monoterpenes with minor contributions from toluene and β-caryophyllene SOA. Mass concentrations at the four sites were determined using source-specific organic mass (OM)-to-OC ratios and gave values in the range of 12–42 µg m^?3. Reconstructed masses at three of the sites (JST, CTR, PNS) ranged from 87 to 91% of the measured PM_2.5 mass. The reconstructed mass at the BHM site exceeded the measured mass by approximately 25%. The difference between the reconstructed and measured PM_2.5 mass for nonindustrial areas is consistent with not including aerosol liquid water or other sources of organic aerosol.     

Determination of Source Contributions to Ambient PM2.5 in Kaohsiung,Taiwan, Using a Receptor Model

ABSTRACT

Ambient particulates of PM_2.5 were sampled at three sites in Kaohsiung, Taiwan, during February and March 1999. In addition, resuspended PM_2.5 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 PM_2.5.

The mean concentration of ambient PM_2.5 was 42.6953.68 μj.g/m³ for the sampling period. The abundant species in ambient PM_2.5 in the mass fraction for three sites were OC (12.7-14.2%), SO₄ ^2- (12.8-15.1%), NO₃ ^- (8.110.3%), NH₄+ (6.7-7.5%), and EC (5.3-8.5%). Results of CMB modeling show that major pollution sources for ambient PM_2.5 are traffic exhaust (18-54%), secondary aerosols (30-41% from SO₄ ^2- and NO₃ ^-), and outdoor burning of agriculture wastes (13-17%).     

Source apportionment of PM2.5 and PM10 aerosols in Brisbane (Australia) by receptor modelling

Aerosol samples for PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameters less than 2.5 and 10 μm, respectively) were collected from 1993 to 1995 at five sites in Brisbane, a subtropical coastal city in Australia. This paper investigates the contributions of emission sources to PM_2.5 and PM₁₀ aerosol mass in Brisbane. Source apportionment results derived from the chemical mass balance (CMB), target transformation factor analysis (TTFA) and multiple linear regression (MLR) methods agree well with each other. The contributions from emission sources exhibit large variations in particle size with temporal and spatial differences. On average, the major contributors of PM₁₀ aerosol mass in Brisbane include: soil/road side dusts (25% by mass), motor vehicle exhausts (13%, not including the secondary products), sea salt (12%), Ca-rich and Ti-rich compounds (11%, from cement works and mineral processing industries), biomass burning (7%), and elemental carbon and secondary products contribute to around 15% of the aerosol mass on average. The major sources of PM_2.5 aerosols at the Griffith University (GU) site (a suburban site surrounded by forest area) are: elemental carbon (24% by mass), secondary organics (21%), biomass burning (15%) and secondary sulphate (14%). Most of the secondary products are related to motor vehicle exhausts, so, although motor vehicle exhausts contribute directly to only 6% of the PM_2.5 aerosol mass, their total contribution (including their secondary products) could be substantial. This pattern of source contribution is similar to the results for Rozelle (Sydney) among the major Australian studies, and is less in contributions from industrial and motor vehicular exhausts than the other cities. An attempt was made to estimate the contribution of rural dust and road side dust. The results show that road side dusts could contribute more than half of the crustal matter. More than 80% of the contribution of vehicle exhausts arises from diesel-fuelled trucks/buses. Biomass burning, large contributions of crustal matter, and/or local contributing sources under calm weather conditions, are often the cause of the high PM₁₀ episodes at the GU site in Brisbane.     

Characterization of carbon fractions for atmospheric fine particles and nanoparticles in a highway tunnel

Fine particles (PM_2.5) and nanoparticles (PM_0.1) were sampled using Dichotomous sampler and MOUDI, respectively, in Xueshan Tunnel, Taiwan. Eight carbon fractions were analyzed using IMPROVE thermal-optical reflectance (TOR) method. The concentrations of different temperature carbon fractions (OC1–OC4, EC1–EC3) in both PM_2.5 and PM_0.1 were measured and the correlations between OC and EC were discussed. Results showed that the ratios of OC/EC were 1.26 and 0.67 for PM_2.5 and PM_0.1, respectively. The concentration of EC1 was found to be more abundant than other elemental carbon fractions in PM_2.5, while the most abundant EC fraction in PM_0.1 was found to be EC2. The variation of contributions for elemental carbon fractions was different among PM_2.5 and PM_0.1 samples, which was partly owing to the metal catalysts for soot oxidation. The correlations between char-EC and soot-EC showed that char-EC dominated EC in PM_2.5 while soot-EC dominated EC in PM_0.1. Using eight individual carbon fractions, the gasoline and diesel source profiles of PM_0.1 and PM_2.5 were extracted and analyzed with the positive matrix factorization (PMF) method.