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.     

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.     

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.     

Source Apportionment Using Positive Matrix Factorization on Daily Measurements of Inorganic and Organic Speciated PM(2.5)

Particulate matter less than 2.5 microns in diameter (PM(2.5)) has been linked with a wide range of adverse health effects. Determination of the sources of PM(2.5) most responsible for these health effects could lead to improved understanding of the mechanisms of such effects and more targeted regulation. This has provided the impetus for the Denver Aerosol Sources and Health (DASH) study, a multi-year source apportionment and health effects study relying on detailed inorganic and organic PM(2.5) speciation measurements.In this study, PM(2.5) source apportionment is performed by coupling positive matrix factorization (PMF) with daily speciated PM(2.5) measurements including inorganic ions, elemental carbon (EC) and organic carbon (OC), and organic molecular markers. A qualitative comparison is made between two models, PMF2 and ME2, commonly used for solving the PMF problem. Many previous studies have incorporated chemical mass balance (CMB) for organic molecular marker source apportionment on limited data sets, but the DASH data set is large enough to use multivariate factor analysis techniques such as PMF.Sensitivity of the PMF2 and ME2 models to the selection of speciated PM(2.5) components and model input parameters was investigated in depth. A combination of diagnostics was used to select an optimum, 7-factor model using one complete year of daily data with pointwise measurement uncertainties. The factors included 1) a wintertime/methoxyphenol factor, 2) an EC/sterane factor, 3) a nitrate/polycyclic aromatic hydrocarbon (PAH) factor, 4) a summertime/selective aliphatic factor, 5) an n-alkane factor, 6) a middle oxygenated PAH/alkanoic acid factor and 7) an inorganic ion factor. These seven factors were qualitatively linked with known PM(2.5) emission sources with varying degrees of confidence. Mass apportionment using the 7-factor model revealed the contribution of each factor to the mass of OC, EC, nitrate and sulfate. On an annual basis, the majority of OC and EC mass was associated with the summertime/selective aliphatic factor and the EC/sterane factor, respectively, while nitrate and sulfate mass were both dominated by the inorganic ion factor. This apportionment was found to vary substantially by season. Several of the factors identified in this study agree well with similar assessments conducted in St. Louis, MO and Pittsburgh, PA using PMF and organic molecular markers.     

Analysis and apportionment of organic carbon and fine particulate matter sources at multiple sites in the midwestern United States

Speciated fine particulate matter (PM2.5) data collected as part of the Speciation Trends Network at four sites in the Midwest (Detroit, MI; Cincinnati, OH; Indianapolis, IN; and Northbrook, IL) and as part of the Interagency Monitoring of Protected Visual Environments program at the rural Bondville, IL, site were analyzed to understand sources contributing to organic carbon (OC) and PM2.5 mass. Positive matrix factorization (PMF) was applied to available data collected from January 2002 through March 2005, and seven to nine factors were identified at each site. Common factors at all of the sites included mobile (gasoline)/secondary organic aerosols with high OC, diesel with a high elemental carbon/OC ratio (only at the urban sites), secondary sulfate, secondary nitrate, soil, and biomass burning. Identified industrial factors included copper smelting (Northbrook, Indianapolis, and Bondville), steel/manufacturing with iron (Northbrook), industrial zinc (Northbrook, Cincinnati, Indianapolis, and Detroit), metal plating with chromium and nickel (Detroit, Indianapolis, and Bondville), mixed industrial with copper and iron (Cincinnati), and limestone with calcium and iron (Bondville). PMF results, on average, accounted for 96% of the measured PM2.5 mass at each site; residuals were consistently within tolerance (+/-3), and goodness-of-fit (Q) was acceptable. Potential source contribution function analysis helped identify regional and local impacts of the identified source types. Secondary sulfate and soil factors showed regional characteristics at each site, whereas industrial sources typically appeared to be locally influenced. These regional factors contributed approximately one third of the total PM2.5 mass, on average, whereas local mobile and industrial sources contributed to the remaining mass. Mobile sources were a major contributor (55-76% at the urban sites) to OC mass, generally with at least twice as much mass from nondiesel sources as from diesel. Regional OC associated with secondary sulfate and soil was generally low.     

Identification of haze-creating sources from fine particulate matter in Dhaka aerosol using carbon fractions

Fine particulate matter (PM_2.5) samples were simultaneously collected on Teflon and quartz filters between February 2010 and February 2011 at an urban monitoring site (CAMS2) in Dhaka, Bangladesh. The samples were collected using AirMetrics MiniVol samplers. The samples on Teflon filters were analyzed for their elemental composition by PIXE and PESA. Particulate carbon on quartz filters was analyzed using the IMPROVE thermal optical reflectance (TOR) method that divides carbon into four organic carbons (OC), pyrolized organic carbon (OP), and three elemental carbon (EC) fractions. The data were analyzed by positive matrix factorization using the PMF2 program. Initially, only total OC and total EC were included in the analysis and five sources, including road dust, sea salt and Zn, soil dust, motor vehicles, and brick kilns, were obtained. In the second analysis, the eight carbon fractions (OC1, OC2, OC3, OC4, OP, EC1, EC2, EC3) were included in order to ascertain whether additional source information could be extracted from the data. In this case, it is possible to identify more sources than with only total OC and EC. The motor vehicle source was separated into gasoline and diesel emissions and a fugitive Pb source was identified. Brick kilns contribute 7.9 μg/m³ and 6.0 μg/m³ of OC and EC, respectively, to the fine particulate matter based on the two results. From the estimated mass extinction coefficients and the apportioned source contributions, soil dust, brick kiln, diesel, gasoline, and the Pb sources were found to contribute most strongly to visibility degradation, particularly in the winter.

Implications: Fine particle concentrations in Dhaka, Bangladesh, are very high and cause significant degradation of urban visibility. This work shows that using carbon fraction data from the IMPROVE OC/EC protocol provides improved source apportionment. Soil dust, brick kiln, diesel, gasoline, and the Pb sources contribute strongly to haze, particularly in the winter.     

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.     

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.     

Source apportionment of fine particles utilizing partially speciated carbonaceous aerosol data at two rural locations in New York State

A source apportionment study was conducted at two rural locations, Potsdam and Stockton, to assess the in-state/out-of-state sources of PM_2.5 and Hg in New York State. At both locations, samples were collected between November 2002 and August 2005 and analyzed for fine PM mass and its chemical constituents. The measured chemical constituents included elements, cations, anions, organic and elemental carbon (OC and EC), black carbon (BC), and water-soluble short-chain (WSSC) organic acids. Positive matrix factorization (PMF) was applied to the measured concentrations and eight and seven factors were resolved at Potsdam and Stockton, respectively. Four factors were resolved in common between the two locations including secondary sulfate, secondary nitrate, secondary OC, and a crustal factor. The factor profiles of mixed industrial and motor vehicle factors resolved at Potsdam were different compared with the corresponding profiles for these factors at Stockton. A resuspended road salt factor was identified at Potsdam, while an aged sea salt factor was identified at Stockton. At Potsdam, a wood smoke factor was also resolved. Among the resolved factors, secondary sulfate was the highest contributor to the measured mass at both sites. Potential source contribution function (PSCF) analysis indicated the Ohio River Valley region as a common potential source region for this factor at both locations. For the secondary nitrate factor, at Potsdam PSCF analysis indicated the Midwestern US (NO_x emissions), and the US farm belt (ammonia emissions) as potential source regions, while at Stockton, the Midwestern US (power plant NO_x emissions) was indicated as a major potential source region.     

Comparison of SOC estimates and uncertainties from aerosol chemical composition and gas phase data in Atlanta

In the Southeastern US, organic carbon (OC) comprises about 30% of the PM_2.5 mass. A large fraction of OC is estimated to be of secondary origin. Long-term estimates of SOC and uncertainties are necessary in the evaluation of air quality policy effectiveness and epidemiologic studies. Four methods to estimate secondary organic carbon (SOC) and respective uncertainties are compared utilizing PM_2.5 chemical composition and gas phase data available in Atlanta from 1999 to 2007. The elemental carbon (EC) tracer and the regression methods, which rely on the use of tracer species of primary and secondary OC formation, provided intermediate estimates of SOC as 30% of OC. The other two methods, chemical mass balance (CMB) and positive matrix factorization (PMF) solve mass balance equations to estimate primary and secondary fractions based on source profiles and statistically-derived common factors, respectively. CMB had the highest estimate of SOC (46% of OC) while PMF led to the lowest (26% of OC). The comparison of SOC uncertainties, estimated based on propagation of errors, led to the regression method having the lowest uncertainty among the four methods. We compared the estimates with the water soluble fraction of the OC, which has been suggested as a surrogate of SOC when biomass burning is negligible, and found a similar trend with SOC estimates from the regression method. The regression method also showed the strongest correlation with daily SOC estimates from CMB using molecular markers. The regression method shows advantages over the other methods in the calculation of a long-term series of SOC estimates.     

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.     

Effect of SME biodiesel blends on PM2.5 emission from a heavy-duty engine

To explore the effect of biodiesel and sulfur content on PM_2.5 emissions, engine dynamometer tests were performed on a Euro II engine to compare the PM_2.5 emissions from four fuels: two petroleum diesel fuels with sulfur contents of 50 and 100 ppm respectively, and two B20 fuels in which soy methyl ester (SME) biodiesel was added to each of the above mentioned petroleum diesel fuels (v/v: 80%/20% for petroleum diesel and SME respectively). Gaseous pollutants and PM_2.5 emissions were sampled with an AVL AMA4000 and Model 130 High-Flow Impactor (MSP Corp). Measurements were made of the PM_2.5 mass, organic carbon (OC), elemental carbon (EC) and the water-soluble ion distribution. The results showed that PM_2.5 emissions decreased with lower sulfur content or blending with SME biodiesel, and the decrease would be more by applying both two methods together. Particles of approximately 0.13 μm contributed 48–83% of PM_2.5 emissions. The impact of sulfur content on this percentage was different for low and high engine speed. The majority of PM_2.5 was comprised of OC and EC, and the carbon emission rate had the same trend as PM_2.5. Since the EC abatement of B20 was larger than OC, the OC/EC ratio of B20 was always larger than that of petroleum diesel. For petroleum diesel, the OC/EC increased with sulfur content, which was not the case for B20. The SO₄^2? had highest emission rate in the water-soluble ions of PM.     

Evaluation of model simulated atmospheric constituents with observations in the factor projected space: CMAQ simulations of SEARCH measurements

Two-year CMAQ simulations of gases and aerosols over the southeast are evaluated using SEARCH observations for 2000 and 2001, both by direct comparison to observations and by projecting both datasets to the factor space using the Positive Matrix Factorization (PMF) model. Model performance for secondary species (sulfate, ozone) is generally better than for primary species (EC, CO). Nitrate concentrations are overestimated, mainly due to wintertime over-partitioning to the particulate phase. Projecting both observed and simulated constituents to the factor space using PMF, four common factors are resolved for each surface site (two urban sites and two rural sites). The resolved factors include (1) secondary sulfate, (2) secondary nitrate, (3) a fresh motor vehicle factor characterized by EC, OC, CO, NO and NO_y, and (4) a mixed factor characterized by EC, OC, and CO. Performance for the sulfate and nitrate factors follow that of the corresponding driving species, while the motor vehicle and “mixed” factors exhibit performance corresponding to that of primary species. Comparing observations and CMAQ simulations in the projected space allow for an evaluation of the co-variability between species, an indicator of source impacts. The fact that similar factors were resolved by PMF from both the observations and the CMAQ simulations suggests that temporal processes related to emissions from specific source categories, as well as the subsequent dispersion and reactivity, are well captured by the CMAQ model. The ability to identify additional factors can be enhanced by adding tracer species in CMAQ simulations.     

Sources of ambient volatile organic compounds and their contributions to photochemical ozone formation at a site in the Pearl River Delta, southern China

The Positive Matrix Factorization (PMF) receptor model and the Observation Based Model (OBM) were combined to analyze volatile organic compound (VOC) data collected at a suburban site (WQS) in the PRD region. The purposes are to estimate the VOC source apportionment and investigate the contributions of these sources and species of these sources to the O₃ formation in PRD. Ten VOC sources were identified. We further applied the PMF-extracted concentrations of these 10 sources into the OBM and found "solvent usage 1", "diesel vehicular emissions" and "biomass/biofuel burning" contributed most to the O₃ formation at WQS. Among these three sources, higher Relative Incremental Reactivity (RIR)-weighted values of ethene, toluene and m/p-xylene indicated that they were mainly responsible for local O₃ formation in the region. Sensitivity analysis revealed that the sources of "diesel vehicular emissions", "biomass/biofuel burning" and "solvent usage 1" had low uncertainties whereas "gasoline evaporation" showed the highest uncertainty.     

Sources and characteristics of carbonaceous aerosol in two largest cities in Pearl River Delta Region,China

PM_2.5 samples were collected at five sites in Guangzhou and Hong Kong, Pearl River Delta Region (PRDR), China in both summer and winter during 2004–2005. Elemental carbon (EC) and organic carbon (OC) in these samples were measured. The OC and EC concentrations ranked in the order of urban Guangzhou > urban Hong Kong > background Hong Kong. Total carbonaceous aerosol (TCA) contributed less to PM_2.5 in urban Guangzhou (32–35%) than that in urban Hong Kong (43–57%). The reason may be that, as an major industrial city in South China, Guangzhou would receive large amount of inorganic aerosol from all kinds of industries, however, as a trade center and seaport, urban Hong Kong would mainly receive organic aerosol and EC from container vessels and heavy-duty diesel trucks. At Hong Kong background site Hok Tsui, relatively lower contribution of TCA to PM_2.5 may result from contributions of marine inorganic aerosol and inland China pollutant. Strong correlation (R²=0.76–0.83) between OC and EC indicates minor fluctuation of emission and the secondary organic aerosol (SOA) formation in urban Guangzhou. Weak correlation between OC and EC in Hong Kong can be related to the impact of the long-range transported aerosol from inland China. Averagely, secondary OC (SOC) concentrations were 3.8–5.9 and 10.2–12.8 μg m⁻³, respectively, accounting for 21–32% and 36–42% of OC in summer and winter in Guangzhou. The average values of 4.2–6.8% for SOA/ PM_2.5 indicate that SOA was minor component in PM_2.5 in Guangzhou.     

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.     

Sources and characteristics of carbonaceous aerosols at Agra “World heritage site” and Delhi “capital city of India”

Agra, one of the oldest cities “World Heritage site”, and Delhi, the capital city of India are both located in the border of Indo-Gangetic Plains (IGP) and heavily loaded with atmospheric aerosols due to tourist place, anthropogenic activities, and its topography, respectively. Therefore, there is need for monitoring of atmospheric aerosols to perceive the scenario and effects of particles over northern part of India. The present study was carried out at Agra (AGR) as well as Delhi (DEL) during winter period from November 2011 to February 2012 of fine particulate (PM_2.5: d?<?2.5 μm) as well as associated carbonaceous aerosols. PM_2.5 was collected at both places using medium volume air sampler (offline measurement) and analyzed for organic carbon (OC) and elemental carbon (EC). Also, simultaneously, black carbon (BC) was measured (online) at DEL. The average mass concentration of PM_2.5 was 165.42?±?119.46 μg m^?3 at AGR while at DEL it was 211.67?±?41.94 μg m^?3 which is ~27 % higher at DEL than AGR whereas the BC mass concentration was 10.60 μg m^?3. The PM_2.5 was substantially higher than the annual standard stipulated by central pollution control board and United States Environmental Protection Agency standards. The average concentrations of OC and EC were 69.96?±?34.42 and 9.53?±?7.27 μm m^?3, respectively. Total carbon (TC) was 79.01?±?38.98 μg m^?3 at AGR, while it was 50.11?±?11.93 (OC), 10.67?±?3.56 μg m^?3 (EC), and 60.78?±?14.56 μg m^?3 (TC) at DEL. The OC/EC ratio was 13.75 at (AGR) and 5.45 at (DEL). The higher OC/EC ratio at Agra indicates that the formation of secondary organic aerosol which emitted from variable primary sources. Significant correlation between PM_2.5 and its carbonaceous species were observed indicating similarity in sources at both sites. The average concentrations of secondary organic carbon (SOC) and primary organic carbon (POC) at AGR were 48.16 and 26.52 μg m^?3 while at DEL it was 38.78 and 27.55 μg m^?3, respectively. In the case of POC, similar concentrations were observed at both places but in the case of SOC higher over AGR by 24 in comparison to DEL, it is due to the high concentration of OC over AGR. Secondary organic aerosol (SOA) was 42 % higher at AGR than DEL which confirms the formation of secondary aerosol at AGR due to rural environment with higher concentrations of coarse mode particles. The SOA contribution in PM_2.5 was also estimated and was ~32 and 12 % at AGR and DEL respectively. Being high loading of fine particles along with carbonaceous aerosol, it is suggested to take necessary and immediate action in mitigation of the emission of carbonaceous aerosol in the northern part of India.     

PM2.5 carbon measurements in two urban areas: Seoul and Kwangju,Korea

24-h PM_2.5 carbonaceous samples were collected between 27 November and 9 December 1999 in Seoul, and between 7 and 20 June 2000 in Kwangju to investigate characteristics of carbonaceous species, and the relationship between elemental carbon (EC) and Aethalometer-based black carbon (BC) measurements. 5-min PM_2.5 BC and criteria air pollutant data were also measured using the Aethalometer and ambient air monitoring system. The PM_2.5 samples were analyzed for EC and OC using a selective thermal manganese dioxide oxidation (TMO) method. The daily average EC and OC concentrations in Seoul were higher in the winter than in the summer (Atmos. Environ. 35 (2001a) 657). It was found that difference between ambient BC levels in the two cities was not directly proportional to the population ratio (∼8) or diesel traffic ratio (∼5.9) since particulate matter or BC concentration is strongly influenced by a result of varying traffic and meteorological conditions at the site. Using the primary OC/EC ratio approach, the results suggest that most of the measured OC in Kwangju is of primary origin during the summer. In Seoul, the observed OC includes additional secondary organic aerosol during the wintertime conditions. The relationship between the 24-h TMO-EC and Aethalometer BC measurements in PM_2.5 reflected very good agreement for the two urban sites, with correlation coefficients of R²=0.99 and 0.92, and BC/EC slopes of 0.93 and 1.07, respectively. It was found that comparing TMO-EC to BC at a different location in Korea, a different scaling factor was needed.     

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.     

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.