Source apportionment of fine particulate matter in the southeastern United States

Particulate matter (PM) less than 2.5 microm in size (PM2.5) source apportionment by chemical mass balance receptor modeling was performed to enhance regional characterization of source impacts in the southeastern United States. Secondary particles, such as NH4HSO4, (NH4)2SO4, NH4NO3, and secondary organic carbon (OC) (SOC), formed by atmospheric photochemical reactions, contribute the majority (>50%) of ambient PM2.5 with strong seasonality. Source apportionment results indicate that motor vehicle and biomass burning are the two main primary sources in the southeast, showing relatively more motor vehicle source impacts rather than biomass burning source impacts in populated urban areas and vice versa in less urbanized areas. Spatial distributions of primary source impacts show that each primary source has distinctively different spatial source impacts. Results also find impacts from shipping activities along the coast. Spatiotemporal correlations indicate that secondary particles are more regionally distributed, as are biomass burning and dust, whereas impacts of other primary sources are more local.     

Monitoring and source apportionment of particulate matter near a large phosphorus production facility

A source apportionment study was conducted to identify sources within a large elemental phosphorus plant that contribute to exceedances of the National Ambient Air Quality Standards (NAAQS) for 24-hr PM10. Ambient data were collected at three monitoring sites from October 1996 through July 1999, and included the following: 24-hr PM10 mass, 24-hr PM2.5 and PM10-2.5 mass and chemistry, continuous PM10 and PM2.5 mass, continuous meteorological data, and wind-direction-resolved PM2.5 and PM10 mass and chemistry. Ambient-based receptor modeling and wind-directional analysis were employed to help identify major sources or source locations and source contributions. Fine-fraction phosphate was the dominant species observed during PM10 exceedances, though in general, resuspended coarse dusts from raw and processed materials at the plant were also needed to create an exceedance. Major sources that were identified included the calciners, the CO flares, process-related dust, and electric-arc furnace operations.     

Future year ozone source attribution modeling study using CMAQ-ISAM

ABSTRACT

To achieve the current United States National Ambient Air Quality Standards (NAAQS) attainment level for ozone or particulate matter, current photochemical air quality models include tools to determine source apportionment and/or source sensitivity. Previous studies by the authors have used the Ozone and Particulate Matter Source Apportionment Technology and Higher-order Decoupled Direct Method probing tools in CAMx to investigate these source-receptor relationships for ozone. The recently available source apportionment for CMAQ, referred to as the Integrated Source Apportionment Method (ISAM), was used in this study to conduct future year (2030) source attribution modeling. The CMAQ-ISAM ozone source attribution results for selected cities across the U.S. showed boundary conditions were the dominant contributor to the future year highest July maximum daily 8-hour average (MDA8) ozone concentrations. Point sources were generally larger contributors in the eastern U.S. than in the western U.S. The contributions of on-road mobile emissions were around 5 ppb at most of the cities selected for analysis. Off-road mobile source contributions were around 20 ppb or nearly 30%. Since boundary conditions play an important role in future year ozone levels, it is important to characterize future year boundary conditions accurately. The current implementation of ISAM in CMAQ 5.0.2 requires significant computing resources for ozone source attribution, making it difficult to conduct long-term simulations for large domains. The computing requirements for PM source attribution are even more onerous. CMAQ 5.2 was released after this study was completed, and does not include ISAM. If an efficient version of ISAM becomes available, it could be used in long-term ozone and PM2.5 studies. Implications: Ozone source attribution results provide useful information on important emission source contribution categories and provide some initial guidance on future emission reduction strategies. This study explains a new source apportionment technique, CMAQ-ISAM, and compares it to CAMx OSAT. The techniques have similar results: ozone’s highest source contributor is boundary conditions, followed by point sources, then off-road mobile sources. The current version of ISAM in CMAQ 5.0.2 requires significant computing resources for ozone source attribution, while the computing requirements for PM source attribution are even more onerous. CMAQ 5.2 was released after this study was completed, and does not include ISAM.     

Compilation and assessment of recent positive matrix factorization and UNMIX receptor model studies on fine particulate matter source apportionment for the eastern United States

In 1997, the U.S. Environmental Protection Agency (EPA) revised its particulate matter standards to include an annual standard for fine particulate matter (PM2.5; 15 microg/m3) and a 24-hr standard (65 microg/m3). The 24-hr standard was lowered to 35 microg/m3 in 2006 in an effort to further reduce overall ambient PM2.5 concentrations. Identifying and quantifying sources of particulate matter affecting a particular location through source apportionment methods is now an important component of the information available to decision makers when evaluating the new standards. This literature compilation summarizes a subset of the source apportionment research and general findings on fine particulate matter in the eastern half of the United States using Positive Matrix Factorization. The results between studies are generally comparable when comparable datasets are used; however, methodologies vary considerably. Commonly identified source categories include: secondary sulfate/coal burning (sometimes over 50% of total mass), secondary organic carbon/mobile sources, crustal sources, biomass burning, nitrate, various industrial processes, and sea salt. The source apportionment tools and methodologies have passed the proof-of-concept stage and are now being used to understand the ambient composition of particulate matter for sites across the United States and the spatial relationship of sources to the receptor. Recommendations are made for further and standardized method development for source apportionment studies, and specific research areas of interest for the eastern United States are proposed.     

Evaluation of multisectional and two-section particulate matter photochemical grid models in the Western United States

Version 4.10s of the comprehensive air-quality model with extensions (CAMx) photochemical grid model has been developed, which includes two options for representing particulate matter (PM) size distribution: (1) a two-section representation that consists of fine (PM2.5) and coarse (PM2.5-10) modes that has no interactions between the sections and assumes all of the secondary PM is fine; and (2) a multisectional representation that divides the PM size distribution into N sections (e.g., N = 10) and simulates the mass transfer between sections because of coagulation, accumulation, evaporation, and other processes. The model was applied to Southern California using the two-section and multisection representation of PM size distribution, and we found that allowing secondary PM to grow into the coarse mode had a substantial effect on PM concentration estimates. CAMx was then applied to the Western United States for the 1996 annual period with a 36-km grid resolution using both the two-section and multisection PM representation. The Community Multiscale Air Quality (CMAQ) and Regional Modeling for Aerosol and Deposition (REMSAD) models were also applied to the 1996 annual period. Similar model performance was exhibited by the four models across the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network monitoring networks. All four of the models exhibited fairly low annual bias for secondary PM sulfate and nitrate but with a winter overestimation and summer underestimation bias. The CAMx multisectional model estimated that coarse mode secondary sulfate and nitrate typically contribute <10% of the total sulfate and nitrate when averaged across the more rural IMPROVE monitoring network.     

Emissions from charbroiling and grilling of chicken and beef

Emission rates for fine particle (<2.5 microm) mass (PM2.5), carbon (organic/elemental), inorganic ions (SO4(2-), NO3-, NH4+), elements (primarily metals), and speciated organic compounds are reported for charbroiling hamburger, steak, and chicken. The PM2.5 rates for charbroiling meats ranged from 4.4 to 11.6 g/kg of uncooked meat in this study. No mass-emission rates are available from grilling, but the speciated organic data are available for these samples. Emission rates varied by type of appliance, meat, meat-fat content, and cooking conditions. High-fat hamburger cooked on an underfired charbroiler emitted the highest amount of PM2.5. The emissions were almost exclusively composed of organic carbon, with small amounts of elements and inorganic ions. Water-soluble K+ and Cl-, which are used as indicators of wood smoke in source apportionment studies, were also present in meat-cooking emissions. The speciated organic compounds that were measured include polycyclic aromatic hydrocarbons (PAHs), cholesterol, and the long-chain gamma-lactones. Charbroiling emissions yielded an average of approximately 3-5 times more PAHs, approximately 20 times more cholesterol, and approximately 10 times more lactones than grilling. These data were utilized in the ambient source apportionment analysis for the 1997 Northern Front Range Air Quality Study source apportionment.     

Source Apportionment of Fine Particulate Matter in the Southeastern United States

Abstract

Particulate matter (PM) less than 2.5 μm in size (PM_2.5)source apportionment by chemical mass balance receptor modeling was performed to enhance regional characterization of source impacts in the southeastern United States. Secondary particles, such as NH₄HSO₄, (NH₄)₂SO₄,NH₄NO₃, and secondary organic carbon (OC) (SOC), formed by atmospheric photochemical reactions, contribute the majority (<50%) of ambient PM_2.5 with strong seasonality. Source apportionment results indicate that motor vehicle and biomass burning are the two main primary sources in the southeast, showing relatively more motor vehicle source impacts rather than biomass burning source impacts in populated urban areas and vice versa in less urbanized areas. Spatial distributions of primary source impacts show that each primary source has distinctively different spatial source impacts. Results also find impacts from shipping activities along the coast. Spatiotemporal correlations indicate that secondary particles are more regionally distributed, as are biomass burning and dust, whereas impacts of other primary sources are more local.     

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.     

Chemical fingerprint and source apportionment of PM 2.5 in highly polluted events of southern Taiwan

To investigate the spatial distribution and diurnal variation of the chemical composition of PM2.5 pollution in an industrial city of southern Taiwan, 12-h PM2.5 was diurnally continuously collected simultaneously at the Kaoping Air Quality Zone (KAQZ) during one highly PM2.5-polluted episode. Water-soluble ions, metallic elements, carbonaceous contents, dicarboxylic acids, and anhydrosugars were analyzed to characterize the chemical fingerprint of PM2.5. Backward trajectory simulation and chemical mass balance (CMB) receptor modeling were applied to identify the potential sources of PM2.5 and their contributions. It showed that Chaozhou (rural area) accompanying the highest SORs and NORs suffered from the most severe PM2.5 pollution during the episode. Sulfate (SO42−) was probably formed by the atmospheric chemical reaction in the daytime, while NO3− processed at nighttime at the KAQZ. A homogeneous formation of NO3− occurred at Chaozhou. The concentrations of Zn, Pb, Fe, Cu, V, and Al, mainly emitted from anthropogenic sources, increased significantly at the KAQZ. The highest OC, SOC/OC, and DA/OCs at Daliao (industrial area) were attributed to the transformation of primary VOCs to secondary OC via photo-oxidation during the episode. Oxalic acid was mainly produced through photochemical reactions since a high correlation between oxalic acid and Ca2+ was observed at Nanzi (urban area) and Daliao during the episode. During the episode, PM2.5 mostly originated from local primary or secondary aerosol than long-range overseas transport. The dominant source was anthropogenic emissions, accounting for 67.1% and 70.4% of PM2.5 at Nanzi and Daliao, respectively. At Chaozhou, the contribution of anthropogenic emissions was the lowest (42.4%), but secondary aerosols had the highest contribution of 38.3% of PM2.5 among the three areas during the episode.     

Sensitivity of source apportionment of urban particulate matter to uncertainty in motor vehicle emissions profiles

A sensitivity analysis was conducted to characterize sources of uncertainty in results of a molecular marker source apportionment model of ambient particulate matter using mobile source emissions profiles obtained as part of the Gasoline/Diesel PM Split Study. A chemical mass balance (CMB) model was used to determine source contributions to samples of fine particulate matter (PM2.5) collected over 3 weeks at two sites in the Los Angeles area in July 2001. The ambient samples were composited for organic compound analysis by the day of the week to investigate weekly trends in source contributions. The sensitivity analysis specifically examined the impact of the uncertainty in mobile source emissions profiles on the CMB model results. The key parameter impacting model sensitivity was the source profile for gasoline smoker vehicles. High-emitting gasoline smoker vehicles with visible plumes were seen to be a significant source of PM in the area, but use of different measured profiles for smoker vehicles in the model gave very different results for apportionment of gasoline, diesel, and smoker vehicle tailpipe emissions. In addition, the contributions of gasoline and diesel emissions to total ambient PM varied as a function of the site and the day of the week.     

Identification and chemical characterization of industrial particulate matter sources in southwest Spain

A detailed physical and chemical characterization of coarse particulate matter (PM10) and fine particulate matter (PM2.5) in the city of Huelva (in Southwestern Spain) was carried out during 2001 and 2002. To identify the major emission sources with a significant influence on PM10 and PM2.5, a methodology was developed based on the combination of: (1) real-time measurements of levels of PM10, PM2.5, and very fine particulate matter (PM1); (2) chemical characterization and source apportionment analysis of PM10 and PM2.5; and (3) intensive measurements in field campaigns to characterize the emission plumes of several point sources. Annual means of 37, 19, and 16 microg/m3 were obtained for the study period for PM10, PM2.5, and PM1, respectively. High PM episodes, characterized by a very fine grain size distribution, are frequently detected in Huelva mainly in the winter as the result of the impact of the industrial emission plumes on the city. Chemical analysis showed that PM at Huelva is characterized by high PO4(3-) and As levels, as expected from the industrial activities. Source apportionment analyses identified a crustal source (36% of PM10 and 31% of PM2.5); a traffic-related source (33% of PM10 and 29% of PM2.5), and a marine aerosol contribution (only in PM10, 4%). In addition, two industrial emission sources were identified in PM10 and PM2.5: (1) a petrochemical source, 13% in PM10 and 8% in PM2.5; and (2) a mixed metallurgical-phosphate source, which accounts for 11-12% of PM10 and PM2.5. In PM2.5 a secondary source has been also identified, which contributed to 17% of the mass. A complete characterization of industrial emission plumes during their impact on the ground allowed for the identification of tracer species for specific point sources, such as petrochemical, metallurgic, and fertilizer and phosphate production industries.     

Modeling air quality during the California Regional PM10/PM2.5 Air Quality Study (CPRAQS) using the UCD/CIT source-oriented air quality model – Part III. Regional source apportionment of secondary and total airborne particulate matter

A comprehensive air quality modeling project was carried out to simulate regional source contributions to secondary and total (=primary + secondary) airborne particle concentrations in California's Central Valley. A three-week stagnation episode lasting from December 15, 2000 to January 7, 2001, was chosen for study using the air quality and meteorological data collected during the California Regional PM₁₀/PM_2.5 Air Quality Study (CRPAQS). The UCD/CIT mechanistic air quality model was used with explicit decomposition of the gas phase reaction chemistry to track source contributions to secondary PM. Inert artificial tracers were used with an internal mixture representation to track source contributions to primary PM. Both primary and secondary source apportionment calculations were performed for 15 size fractions ranging from 0.01 to 10 μm particle diameters. Primary and secondary source contributions were resolved for fugitive dust, road dust, diesel engines, catalyst equipped gasoline engines, non-catalyst equipped gasoline engines, wood burning, food cooking, high sulfur fuel combustion, and other anthropogenic sources.Diesel engines were identified as the largest source of secondary nitrate in central California during the study episode, accounting for approximately 40% of the total PM_2.5 nitrate. Catalyst equipped gasoline engines were also significant, contributing approximately 20% of the total secondary PM_2.5 nitrate. Agricultural sources were the dominant source of secondary ammonium ion. Sharp gradients of PM concentrations were predicted around major urban areas. The relative source contributions to PM_2.5 from each source category in urban areas differ from those in rural areas, due to the dominance of primary OC in urban locations and secondary nitrate in the rural areas. The source contributions to ultra-fine particle mass PM_0.1 also show clear urban/rural differences. Wood smoke was found to be the major source of PM_0.1 in urban areas while motor vehicle sources were the major contributor of PM_0.1 in rural areas, reflecting the influence from two major highways that transect the Valley.     

Sensitivity of Source Apportionment of Urban Particulate Matter to Uncertainty in Motor Vehicle Emissions Profiles

Abstract

A sensitivity analysis was conducted to characterize sources of uncertainty in results of a molecular marker source apportionment model of ambient particulate matter using mobile source emissions profiles obtained as part of the Gasoline/Diesel PM Split Study. A chemical mass balance (CMB) model was used to determine source contributions to samples of fine particulate matter (PM_2.5) collected over 3 weeks at two sites in the Los Angeles area in July 2001. The ambient samples were composited for organic compound analysis by the day of the week to investigate weekly trends in source contributions. The sensitivity analysis specifically examined the impact of the uncertainty in mobile source emissions profiles on the CMB model results. The key parameter impacting model sensitivity was the source profile for gasoline smoker vehicles. High-emitting gasoline smoker vehicles with visible plumes were seen to be a significant source of PM in the area, but use of different measured profiles for smoker vehicles in the model gave very different results for apportionment of gasoline, diesel, and smoker vehicle tailpipe emissions. In addition, the contributions of gasoline and diesel emissions to total ambient PM varied as a function of the site and the day of the week.     

Source contributions to fine particulate matter in an urban atmosphere

This paper proposes a practical method for estimating source attribution by using a three-step methodology. The main objective of this study is to explore the use of the three-step methodology for quantifying the source impacts of 24-h PM2.5 particles at an urban site in Seoul, Korea. 12-h PM2.5 samples were collected and analyzed for their elemental composition by ICP-AES/ICP-MS/AAS to generate the source composition profiles. In order to assess the daily average PM2.5 source impacts, 24-h PM2.5 and polycyclic aromatic hydrocarbons (PAH) ambient samples were simultaneously collected at the same site. The PM2.5 particle samples were then analyzed for trace elements. Ionic and carbonaceous species concentrations were measured by ICP-AES/ICP-MS/AAS, IC, and a selective thermal MnO2 oxidation method. The 12-h PM2.5 chemical data was used to estimate possible source signatures using the principal component analysis (PCA) and the absolute principal component scores method followed by the multiple linear regression analysis. The 24-h PM2.5 source categories were extracted with a combination of PM2.5 and some PAH chemical data using the PCA, and their quantitative source contributions were estimated by chemical mass balance (CMB) receptor model using the estimated source profiles and those in the literature. The results of PM2.5 source apportionment using the 12-h derived source composition profiles show that the CMB performance indices; chi2, R2, and percent of mass accounted for are 2.3%, 0.97%, and 100.7%, which are within the target range specified. According to the average PM2.5 source contribution estimate results, motor vehicle exhaust was the major contributor at the sampling site, contributing 26% on average of measured PM2.5 mass (41.8 microg m-3), followed by secondary sulfate (23%) and nitrate (16%), refuse incineration (15%), soil dust (13%), field burning (4%), oil combustion (2.7%), and marine aerosol (1.3%). It can be concluded that quantitative source attribution to PM2.5 in an urban area where source profiles have not been developed can be estimated using the proposed three-step methodology approach.     

A retrospective comparison of model-based forecasted PM2.5 concentrations with measurements

This study presents an assessment of the performance of the Community Multiscale Air Quality (CMAQ) photochemical model in forecasting daily PM2.5 (particulate matter < or = 2.5 microm in aerodynamic diameter) mass concentrations over most of the eastern United States for a 2-yr period from June 14, 2006 to June 13, 2008. Model predictions were compared with filter-based and continuous measurements of PM2.5 mass and species on a seasonal and regional basis. Results indicate an underprediction of PM2.5 mass in spring and summer, resulting from under-predictions in sulfate and total carbon concentrations. During winter, the model overpredicted mass concentrations, mostly at the urban sites in the northeastern United States because of overpredictions in unspeciated PM2.5 (suggesting possible overestimation of primary emissions) and sulfate. A comparison of observed and predicted diurnal profiles of PM2.5 mass at five sites in the domain showed significant discrepancies. Sulfate diurnal profiles agreed in shape across three sites in the southern portion of the domain but differed at two sites in the northern portion of the domain. Predicted organic carbon (OC) profiles were similar in shape to mass, suggesting that discrepancies in mass profiles probably resulted from the underprediction in OC. The diurnal profiles at a highly urbanized site in New York City suggested that the overpredictions at that site might be resulting from overpredictions during the morning and evening hours, displayed as sharp peaks in predicted profiles. An examination of the predicted planetary boundary layer (PBL) heights also showed possible issues in the modeling of PBL.     

Methods of characterizing the distribution of exhaust emissions from light-duty, gasoline-powered motor vehicles in the U.S. fleet

Mobile sources significantly contribute to ambient concentrations of airborne particulate matter (PM). Source apportionment studies for PM10 (PM < or = 10 microm in aerodynamic diameter) and PM2.5 (PM < or = 2.5 microm in aerodynamic diameter) indicate that mobile sources can be responsible for over half of the ambient PM measured in an urban area. Recent source apportionment studies attempted to differentiate between contributions from gasoline and diesel motor vehicle combustion. Several source apportionment studies conducted in the United States suggested that gasoline combustion from mobile sources contributed more to ambient PM than diesel combustion. However, existing emission inventories for the United States indicated that diesels contribute more than gasoline vehicles to ambient PM concentrations. A comprehensive testing program was initiated in the Kansas City metropolitan area to measure PM emissions in the light-duty, gasoline-powered, on-road mobile source fleet to provide data for PM inventory and emissions modeling. The vehicle recruitment design produced a sample that could represent the regional fleet, and by extension, the national fleet. All vehicles were recruited from a stratified sample on the basis of vehicle class (car, truck) and model-year group. The pool of available vehicles was drawn primarily from a sample of vehicle owners designed to represent the selected demographic and geographic characteristics of the Kansas City population. Emissions testing utilized a portable, light-duty chassis dynamometer with vehicles tested using the LA-92 driving cycle, on-board emissions measurement systems, and remote sensing devices. Particulate mass emissions were the focus of the study, with continuous and integrated samples collected. In addition, sample analyses included criteria gases (carbon monoxide, carbon dioxide, nitric oxide/nitrogen dioxide, hydrocarbons), air toxics (speciated volatile organic compounds), and PM constituents (elemental/organic carbon, metals, semi-volatile organic compounds). Results indicated that PM emissions from the in-use fleet varied by up to 3 orders of magnitude, with emissions generally increasing for older model-year vehicles. The study also identified a strong influence of ambient temperature on vehicle PM mass emissions, with rates increasing with decreasing temperatures.     

Roadside particulate air pollution in Bangkok

Airborne fine particles of PM(2.5-10) and PM2.5 in Bangkok, Nonthaburi, and Ayutthaya were measured from December 22, 1998, to March 26, 1999, and from November 30, 1999, to December 2, 1999. Almost all the PM10 values in the high-polluted (H) area exceeded the Thailand National Ambient Air Quality Standards (NAAQS) of 120 microg/m3. The low-polluted (L) area showed low PM10 (34-74 microg/m3 in the daytime and 54-89 microg/m3 at night). PM2.5 in the H area varied between 82 and 143 microg/m3 in the daytime and between 45 and 146 microg/m3 at night. In the L area, PM2.5 was quite low both day and night and varied between 24 and 54 microg/m3, lower than the U.S. Environmental Protection Agency (EPA) standard (65 microg/m3). The personal exposure results showed a significantly higher proportion of PM2.5 to PM10 in the H area than in the L area (H = 0.80 +/- 0.08 and L = 0.65 +/- 0.04). Roadside PM10 was measured simultaneously with the Thailand Pollution Control Department (PCD) monitoring station at the same site and at the intersections where police work. The result from dual simultaneous measurements of PM10 showed a good correlation (correlation coefficient: r = 0.93); however, PM levels near the roadside at the intersections were higher than the concentrations at the monitoring station. The relationship between ambient PM level and actual personal exposures was examined. Correlation coefficients between the general ambient outdoors and personal exposure levels were 0.92 for both PM2.5 and PM10. Bangkok air quality data for 1997-2000, including 24-hr average PM10, NO2, SO2, and O3 from eight PCD monitoring stations, were analyzed and validated. The annual arithmetic mean PM10 of the PCD data at the roadside monitoring stations for the last 3 years decreased from 130 to 73 microg/m3, whereas the corresponding levels at the general monitoring stations decreased from 90 to 49 microg/m3. The proportion of days when the level of the 24-hr average PM10 exceeded the NAAQS was between 13 and 26% at roadside stations. PCD data showed PM10 was well correlated with NO2 but not with SO2, suggesting that automobile exhaust is the main source of the particulate air pollution. The results obtained from the simultaneous measurement of PM2.5 and PM10 indicate the potential environmental health hazard of fine particles. In conclusion, Bangkok traffic police were exposed to high levels of automobile-derived particulate air pollution.     

Chemical mass balance model with fractionation for apportioning PM2.5: a test case for Los Angeles traffic sources

Chemical mass balance receptor models (CMBs) use measured pollutant concentrations, along with source information, to apportion the contributions of primary sources to the measured concentrations. CMBs can be used to evaluate the accuracy of the emission inventories that underlie State Implementation Plan (SIP) modeling, by providing an allocation of emissions to individual source categories. CMBs, however, traditionally have not accounted for the chemical reaction and differential deposition or fractionation that occur between the source and receptor. This means that they have historically had severe limitations in apportioning secondary particulate matter (PM), which is an especially important component of fine PM (PM2.5). Stafford and Liljestrand developed a method to account for fractionation in CMBs using depletion factors based on a solution of the steady-state advection-dispersion equation, including gravitational settling, dry deposition, and first-order chemical reaction.     

Characterization of particulate matter for three sites in Kuwait

Many studies have shown strong associations between particulate matter (PM) levels and a variety of health outcomes, leading to changes in air quality standards in many regions, especially the United States and Europe. Kuwait, a desert country located on the Persian Gulf, has a large petroleum industry with associated industrial and urban land uses. It was marked by environmental destruction from the 1990 Iraqi invasion and subsequent oil fires. A detailed particle characterization study was conducted over 12 months in 2004-2005 at three sites simultaneously with an additional 6 months at one of the sites. Two sites were in urban areas (central and southern) and one in a remote desert location (northern). This paper reports the concentrations of particles less than 10 microm in diameter (PM10) and fine PM (PM2.5), as well as fine particle nitrate, sulfate, elemental carbon (EC), organic carbon (OC), and elements measured at the three sites. Mean annual concentrations for PM10 ranged from 66 to 93 microg/m3 across the three sites, exceeding the World Health Organization (WHO) air quality guidelines for PM10 of 20 microg/m3. The arithmetic mean PM2.5 concentrations varied from 38 and 37 microg/m3 at the central and southern sites, respectively, to 31 microg/m3 at the northern site. All sites had mean PM2.5 concentrations more than double the U.S. National Ambient Air Quality Standard (NAAQS) for PM2.5. Coarse particles comprised 50-60% of PM10. The high levels of PM10 and large fraction of coarse particles comprising PM10 are partially explained by the resuspension of dust and soil from the desert crust. However, EC, OC, and most of the elements were significantly higher at the urbanized sites, compared with the more remote northern site, indicating significant pollutant contributions from local mobile and stationary sources. The particulate levels in this study are high enough to generate substantial health impacts and present opportunities for improving public health by reducing airborne PM.     

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.