PM2.5 chemical source profiles for vehicle exhaust, vegetative burning, geological material, and coal burning in Northwestern Colorado during 1995

PM_2.5 (particles with aerodynamic diameters less than 2.5 μm) chemical source profiles applicable to speciated emissions inventories and receptor model source apportionment are reported for geological material, motor vehicle exhaust, residential coal (RCC) and wood combustion (RWC), forest fires, geothermal hot springs; and coal-fired power generation units from northwestern Colorado during 1995. Fuels and combustion conditions are similar to those of other communities of the inland western US. Coal-fired power station profiles differed substantially between different units using similar coals, with the major difference being lack of selenium in emissions from the only unit that was equipped with a dry limestone sulfur dioxide (SO₂) scrubber. SO₂ abundances relative to fine particle mass emissions in power plant emissions were seven to nine times higher than hydrogen sulfide (H₂S) abundances from geothermal springs, and one to two orders of magnitude higher than SO₂ abundances in RCC emissions, implying that the SO₂ abundance is an important marker for primary particle contributions of non-aged coal-fired power station contributions. The sum of organic and elemental carbon ranged from 1% to 10% of fine particle mass in coal-fired power plant emissions, from 5% to 10% in geological material, >50% in forest fire emissions, >60% in RWC emissions, and >95% in RCC and vehicle exhaust emissions. Water-soluble potassium (K⁺) was most abundant in vegetative burning profiles. K⁺/K ratios ranged from 0.1 in geological material profiles to 0.9 in vegetative burning emissions, confirming previous observations that soluble potassium is a good marker for vegetative burning.     

PM2.5 chemical source profiles for vehicle exhaust, vegetative burning, geological material, and coal burning in Northwestern Colorado during 1995

PM_2.5 (particles with aerodynamic diameters less than 2.5 μm) chemical source profiles applicable to speciated emissions inventories and receptor model source apportionment are reported for geological material, motor vehicle exhaust, residential coal (RCC) and wood combustion (RWC), forest fires, geothermal hot springs; and coal-fired power generation units from northwestern Colorado during 1995. Fuels and combustion conditions are similar to those of other communities of the inland western US. Coal-fired power station profiles differed substantially between different units using similar coals, with the major difference being lack of selenium in emissions from the only unit that was equipped with a dry limestone sulfur dioxide (SO₂) scrubber. SO₂ abundances relative to fine particle mass emissions in power plant emissions were seven to nine times higher than hydrogen sulfide (H₂S) abundances from geothermal springs, and one to two orders of magnitude higher than SO₂ abundances in RCC emissions, implying that the SO₂ abundance is an important marker for primary particle contributions of non-aged coal-fired power station contributions. The sum of organic and elemental carbon ranged from 1% to 10% of fine particle mass in coal-fired power plant emissions, from 5% to 10% in geological material, >50% in forest fire emissions, >60% in RWC emissions, and >95% in RCC and vehicle exhaust emissions. Water-soluble potassium (K⁺) was most abundant in vegetative burning profiles. K⁺/K ratios ranged from 0.1 in geological material profiles to 0.9 in vegetative burning emissions, confirming previous observations that soluble potassium is a good marker for vegetative burning.     

Variations in speciated emissions from spark-ignition and compression-ignition motor vehicles in California's south coast air basin

The U.S. Department of Energy Gasoline/Diesel PM Split Study examined the sources of uncertainties in using an organic compound-based chemical mass balance receptor model to quantify the contributions of spark-ignition (SI) and compression-ignition (CI) engine exhaust to ambient fine particulate matter (PM2.5). This paper presents the chemical composition profiles of SI and CI engine exhaust from the vehicle-testing portion of the study. Chemical analysis of source samples consisted of gravimetric mass, elements, ions, organic carbon (OC), and elemental carbon (EC) by the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Speciation Trends Network (STN) thermal/optical methods, polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, alkanes, and polar organic compounds. More than half of the mass of carbonaceous particles emitted by heavy-duty diesel trucks was EC (IMPROVE) and emissions from SI vehicles contained predominantly OC. Although total carbon (TC) by the IMPROVE and STN protocols agreed well for all of the samples, the STN/IMPROVE ratios for EC from SI exhaust decreased with decreasing sample loading. SI vehicles, whether low or high emitters, emitted greater amounts of high-molecular-weight particulate PAHs (benzo[ghi]perylene, indeno[1,2,3-cd]pyrene, and coronene) than did CI vehicles. Diesel emissions contained higher abundances of two- to four-ring semivolatile PAHs. Diacids were emitted by CI vehicles but are also prevalent in secondary organic aerosols, so they cannot be considered unique tracers. Hopanes and steranes were present in lubricating oil with similar composition for both gasoline and diesel vehicles and were negligible in gasoline or diesel fuels. CI vehicles emitted greater total amounts of hopanes and steranes on a mass per mile basis, but abundances were comparable to SI exhaust normalized to TC emissions within measurement uncertainty. The combustion-produced high-molecular-weight PAHs were found in used gasoline motor oil but not in fresh oil and are negligible in used diesel engine oil. The contributions of lubrication oils to abundances of these PAHs in the exhaust were large in some cases and were variable with the age and consumption rate of the oil. These factors contributed to the observed variations in their abundances to total carbon or PM2.5 among the SI composition profiles.     

Improving source apportionment of fine particles in the eastern United States utilizing temperature-resolved carbon fractions

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 (PM2.5) 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 PM2.5.     

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.     

Source apportionment of fine particles in Washington, DC, utilizing temperature-resolved carbon fractions

Integrated ambient particulate matter < or =2.5 microm in aerodynamic diameter (PM2.5) samples were collected at a centrally located urban monitoring site in Washington, DC, on Wednesdays and Saturdays using Interagency Monitoring of Protected Visual Environments samplers. Particulate carbon was analyzed using the thermal optical reflectance method that divides carbon into four organic carbon fractions, pyrolyzed organic carbon, and three elemental carbon fractions. A total of 35 variables measured in 718 samples collected between August 1988 and December 1997 were analyzed. The data were analyzed using Positive Matrix Factorization and 10 sources were identified: sulfate (SO4(2-))-rich secondary aerosol I (43%), gasoline vehicle (21%), SO4(2-)-rich secondary aerosol II (11%), nitrate-rich secondary aerosol (9%), SO4(2-)-rich secondary aerosol III (6%), incinerator (4%), aged sea salt (2%), airborne soil (2%), diesel emissions (2%), and oil combustion (2%). In contrast to a previous study that included only total organic carbon and elemental carbon fractions, motor vehicles were separated into fractions identified as gasoline vehicle and diesel emissions containing carbon fractions whose abundances were different between the two sources. This study indicates that the temperature-resolved carbon fraction data can be utilized to enhance source apportionment, especially with respect to the separation of diesel emissions from gasoline vehicle sources. Conditional probability functions using surface wind data and deduced source contributions aid in the identifications of local sources.     

Receptor modeling application framework for particle source apportionment

Receptor models infer contributions from particulate matter (PM) source types using multivariate measurements of particle chemical and physical properties. Receptor models complement source models that estimate concentrations from emissions inventories and transport meteorology. Enrichment factor, chemical mass balance, multiple linear regression, eigenvector. edge detection, neural network, aerosol evolution, and aerosol equilibrium models have all been used to solve particulate air quality problems, and more than 500 citations of their theory and application document these uses. While elements, ions, and carbons were often used to apportion TSP, PM10, and PM2.5 among many source types, many of these components have been reduced in source emissions such that more complex measurements of carbon fractions, specific organic compounds, single particle characteristics, and isotopic abundances now need to be measured in source and receptor samples. Compliance monitoring networks are not usually designed to obtain data for the observables, locations, and time periods that allow receptor models to be applied. Measurements from existing networks can be used to form conceptual models that allow the needed monitoring network to be optimized. The framework for using receptor models to solve air quality problems consists of: (1) formulating a conceptual model; (2) identifying potential sources; (3) characterizing source emissions; (4) obtaining and analyzing ambient PM samples for major components and source markers; (5) confirming source types with multivariate receptor models; (6) quantifying source contributions with the chemical mass balance; (7) estimating profile changes and the limiting precursor gases for secondary aerosols; and (8) reconciling receptor modeling results with source models, emissions inventories, and receptor data analyses.     

Source apportionment of ambient total suspended particulates and coarse particulate matter in urban areas of Jiaozuo, China

Approximately 750 total suspended particulates (TSPs) and coarse particulate matter (PM10) filter samples from six urban sites and a background site and >210 source samples were collected in Jiaozuo City during January 2002 to April 2003. They were analyzed for mass and abundances of 25 chemical components. Seven contributive sources were identified, and their contributions to ambient TSP/PM10 levels at the seven sites in three seasons (spring, summer, and winter days) and a "whole" year were estimated by a chemical mass balance (CMB) receptor model. The spatial TSP average was high in spring and winter days at a level of approximately 530 microg/m(3) and low in summer days at 456 microg/m(3); however, the spatial PMo0 average exhibited little variation at a level of approximately 325 microg/m(3), and PM10-to-TSP ratios ranged from 0.58 to 0.81, which suggested heavy particulate matter pollution existing in the urban areas. Apportionment results indicated that geological material was the largest contributor to ambient TSP/PM10 concentrations, followed by dust emissions from construction activities, coal combustion, secondary aerosols, vehicle movement, and other industrial sources. In addition, paved road dust and re-entrained dust were also apportioned to the seven source types and found soil, coal combustion, and construction dust to be the major contributors.     

Compositions of Particles from Selected Sources in Philadelphia for Receptor Modeling Applications

As a part of a receptor model study of the Philadelphia, PA atmosphere, particulate samples were collected from seven air pollution sources in the area: two oil-fired power plants, a coal-fired power plant, a fluidized catalytic cracker, a refuse incinerator, a secondary aluminum smelter and an antimony ore roaster. Samples were collected In two size fractions with a dilution source sampler connected to a modified dichotomous sampler. Masses of collected material were determined gravlmetrlcally. Samples were analyzed for elements by x-ray fluorescence followed by Instrumental neutron activation analysis of some samples. Other samples were analyzed by chemical methods for volatile and nonvolatile carbon, SO₄ ^2? and NH₄ ⁺. Data are presented for up to 46 elements and species on fine (<2.5-μm aerodynamic equivalent diameter) and coarse (2.5 μm < diam < 7-10 μm) particles from each source. Although the data were collected for use in Philadelphia, they should be of value for receptor modeling of other areas having similar sources. The most unexpected results were the large amounts of rare earth elements on particles from the catalytic cracker (e.g., 0.31 percent La In fine fraction) and the oil-fired power plants (120 and 420 ppm La in fine fraction). Substantial amounts of primary SO₄ ^2? are released from the oil-fired plants, the SO₄ ^2? concentrations accounting for 40-45 percent of the fine particulate mass.     

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.     

Development of a United States-Mexico Emissions Inventory for the Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study

The Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study was commissioned to investigate the sources of haze at Big Bend National Park in southwest Texas. The modeling domain of the BRAVO Study includes most of the continental United States and Mexico. The BRAVO emissions inventory was constructed from the 1999 National Emission Inventory for the United States, modified to include finer-resolution data for Texas and 13 U.S. states in close proximity. The first regional-scale Mexican emissions inventory designed for air-quality modeling applications was developed for 10 northern Mexican states, the Tula Industrial Park in the state of Hidalgo, and the Popocatépetl volcano in the state of Puebla. Emissions data were compiled from numerous sources, including the U.S. Environmental Protection Agency (EPA), the Texas Natural Resources Conservation Commission (now Texas Commission on Environmental Quality), the Eastern Research Group, the Minerals Management Service, the Instituto Nacional de Ecología, and the Instituto Nacional de Estadistica Geografía y Informática. The inventory includes emissions for CO, nitrogen oxides, sulfur dioxide, volatile organic compounds (VOCs), ammonia, particulate matter (PM) < 10 microm in aerodynamic diameter, and PM < 2.5 microm in aerodynamic diameter. Wind-blown dust and biomass burning were not included in the inventory, although high concentrations of dust and organic PM attributed to biomass burning have been observed at Big Bend National Park. The SMOKE modeling system was used to generate gridded emissions fields for use with the Regional Modeling System for Aerosols and Deposition (REMSAD) and the Community Multiscale Air Quality model modified with the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (CMAQ-MADRID). The compilation of the inventory, supporting model input data, and issues encountered during the development of the inventory are documented. A comparison of the BRAVO emissions inventory for Mexico with other emerging Mexican emission inventories illustrates their uncertainty.     

Application of Infrared Spectroscopy to Exhaust Gas Analysis

Abstract

The Mohave Valley region of southern Nevada/southwestern Arizona has experienced elevated particulate concentrations and is classified as a PM₁₀ nonattainment area. Anthropogenic aerosol sources in the area include the Mohave Power Project (MPP), a 1,580-MW coal-fired power plant; motor vehicles; construction activities; and paved and unpaved road dust and disturbed desert soil. Aerosols may also be transported long distances from other areas, such as the Los Angeles Basin. Based on the infrequency of plume contact at sites in the valley (as determined by SO₂ measurements), it was believed that the contribution of the MPP to primary PM₁₀ was minimal and that fugitive dust was the primary source of ambient particulate matter.

To evaluate the magnitude of source contributors, PM₁₀ measurements were made using a medium-volume sampler along with ancillary meteorological and air quality measurements in the Mohave Valley at Bullhead City, Arizona, for a period of longer than one year (September 1988 through mid-October 1989). The aerosol filter samples were analyzed for mass, elements, ions, and carbon. Source apportionment using the Chemical Mass Balance (CMB) receptor model was performed. On average, geological dust was the major contributor to PM10 (79.5%), followed by primary motor vehicle sources (16.7%), secondary ammonium sulfate (3.5%), secondary ammonium nitrate (0.1%), and primary coal-fired power plant emissions (0.1%).     

Investigation of sources of atmospheric aerosol at a hot spot area in Dhaka, Bangladesh

Samples of fine and coarse fractions of airborne particulate matter were collected at the Farm Gate area in Dhaka from July 2001 to March 2002. Dhaka is a hot spot area with very high pollutant concentrations because of the proximity of major roadways. The samples were collected using a "Gent" stacked filter unit in two fractions of 0- to 2.2-microm and 2.2- to 10-microm sizes. The samples were analyzed for elemental concentrations by particle-induced X-ray excitation (PIXE) and for black carbon by reflectivity methods, respectively. The data were analyzed by positive matrix factorization (PMF) to identify the possible sources of atmospheric aerosols in this area. Six sources were found for both the coarse and fine PM fractions. The data sets were also analyzed by an expanded model to explore additional sources. Seven and six factors were obtained for coarse and fine PM fractions, respectively, in these analyses. The identified sources are motor vehicle, soil dust, emissions from construction activities, sea salt, biomass burning/brick kiln, resuspended/fugitive Pb, and two-stroke engines. From the expanded modeling, approximately 50% of the total PM2.2 mass can be attributed to motor vehicles, including two-stroke engine vehicle in this hot spot in Dhaka, whereas the PMF modeling indicates that 45% of the total PM2.2 mass is from motor vehicles. The PMF2 and expanded models could resolve approximately 4% and 3% of the total PM2.2 mass as resuspended/fugitive Pb, respectively. Although, Pb has been eliminated from gasoline in Bangladesh since July 1999, there still may be substantial amounts of accumulated lead in the dust near roadways as well as fugitive Pb emissions from battery reclaimation and other industries. Soil dust is the largest component of the coarse particle fraction (PM2.2-10) accounting for approximately 71% of the total PM2.2-10 mass in the expanded model, whereas from the PMF modeling, the dust (undifferentiated) contribution is approximately 49%.     

Spatial, temporal, and interspecies patterns in fine particulate matter in Texas

The Big Bend Regional Aerosol and Visibility Observational (BRAVO) field study was conducted from July to October 1999 and was followed by several years of modeling and data analyses to examine the causes of haze at Big Bend National Park TX (BBNP). During BRAVO, daily speciated fine (diameter <2.5 microm) particulate concentrations were measured at 37 sites throughout Texas. At the primary receptor site, K-Bar Ranch, there were many additional measurements including a "high-sensitivity" version of the 24-hr fine particulate elemental data. The spatial, temporal, and interspecies patterns in these data are examined here to qualitatively investigate source regions and source types influencing the fine particulate concentrations in Texas with an emphasis on sources of sulfates, the largest contributor to fine mass and light extinction. Peak values of particulate sulfur (S) varied spatially and seasonally. Maximum S was in Northeast Texas during the summer, whereas peak S at BBNP was in the fall. Sulfate acidity at BBNP also varied by month. Sources of Se were evident in Northeast Texas and from the Carbón I and II plants. High S episodes at BBNP during BRAVO had several different trace element characteristics. Carbon concentrations at BBNP during BRAVO were probably mostly urban-related, with arrival from the Houston area likely. The Houston artificial tracer released during the second half of BRAVO was highly correlated with some carbon fractions. There was evidence of the influence of African dust at sites throughout Texas during the summer. Patterns in several trace elements were also examined. Vanadium was associated with air masses from Mexico. Lead concentrations in southern Texas have dropped dramatically over the past several years.     

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.     

Profile analysis of ambient and source emitted particle-bound polycyclic aromatic hydrocarbons from three sites in northern Greece

Polycyclic aromatic hydrocarbons (PAHs) adsorbed to ambient PM(10) were determined at three sites in Thessaloniki, northern Greece, during the period June 1997-July 1998. Ambient PAH profiles exhibited significant seasonal and spatial variations. Source PAH profiles were obtained for a number of urban, industrial and geological sources including cement, fertilizer and asphalt production, quarry operations, metal electroplating, metal welding and tempering, steel manufacture, lead and bronze smelters, metal scrap incineration, oil burning, non-catalyst equipped passenger cars, diesel fueled taxies and buses, paved road dust and soil dust. Principal component analysis (PCA) and diagnostic ratios were employed to compare ambient and source PAH profiles in an attempt to recognize compositional patterns. Similarities between the ambient PAH profiles and the profiles of certain sources, such as vehicular emissions, oil burning and metal industries, were identified.     

Sources of PM10 and sulfate aerosol at McMurdo Station, Antarctica

Source contributions to PM10 and sulfate aerosol at McMurdo Station, Antarctica during the austral summers of 1995-1996 and 1996-1997 were estimated using Chemical Mass Balance (CMB) receptor modeling. The average PM10 (particles with aerodynamic diameters less than 10 microm) concentration at Hut Point, located less than 1 km downwind of downtown McMurdo, was 3.4 microg/m3. Emissions profiles were determined for potentially important aerosol source types in McMurdo: exposed soil, power generation, space heating, and surface vehicles. Soil dust, sea salt, combustion emissions, sulfates, marine biogenic emissions as methanesulfonate, and nitrates contributed 57%, 15%, 14%, 10%, 3%, and 1%, respectively, of average estimated PM10 at Hut Point (3.2 microg/m3). Soil dust, sea salt, and combustion sources contributed 12%, 8%, and 20%, respectively, of the average PM10 sulfate concentration of 0.46 microg/m3. Marine biogenic sources contributed 0.17 microg/m3 (37%). The remaining sulfate is thought to have come from emissions from Mt. Erebus or hemispheric pollution sources.     

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.     

Metal content in street dust as a reflection of atmospheric dust emissions from coal power plants, metal smelters, and traffic

Resuspended street dust is a source of inhalable particles in urban environments. Despite contaminated street dust being a possible health risk factor for local population, little is known about the contribution of atmospheric dust emissions and other factors to the content of toxic metals in street dust. The impact of smelting, traffic, and power plants on metal contaminates in street dust is the focus of street dust sampling at 46 locations in the Witbank area (Republic of South Africa). This area is characterized by numerous open-pit coal mines in the Karoo coal basin, which provides a cheap source of energy to numerous metallurgical smelters and ironworks and supplies coal to the coal-fired power plants located nearby. Street dust was collected on asphalt or concrete surfaces with hard plastic brushes, avoiding collecting of possible sand, soil, or plant particles. Chemical analysis was done on the <0.125 mm fraction using inductively coupled plasma mass spectrometry subsequent to total digestion. Exceptionally high concentrations of metals were detected with concentrations of Fe reaching 17.7 %, Cr 4.3 %, Mn 2 %, Ni 366 mg/kg, and V 4,410 mg/kg. Factor analysis indicates three sources for the pollution. Road traffic which contributes to the high concentrations of Cu, Pb, Sb, and Sn, with the highest impacts detected in the town of Witbank. The second source is associated with the metal smelting industry, contributing to Fe, Co, Mn, and V emissions. The highest factor scores were observed around four metallurgical smelter operations, located in the Ferrobank, Highveld, and Clewer industrial areas. Impact of vanadium smelter to street dust composition could still be detected some 20 km away from the sources. Exceptionally high concentrations of Cr were observed in four samples collected next to the Ferrobank industrial area, despite Cr not being loaded in factor 2. The last source of the pollution is most probably fly ash associated with the coal-fired power plants and fly ash dumps. Elements which are associated with this source are Al, Sr, and Li. This factor is abundant in the coal mining part of the study area.     

Source Profiles of Particulate Matter Emissions from a Pilot-Scale Boiler Burning North American Coal Blends

ABSTRACT

Recent awareness of suspected adverse health effects from ambient particulate matter (PM) emission has prompted publication of new standards for fine PM with aerodynamic diameter less than 2.5 μm (PM_2.5). However, scientific data on fine PM emissions from various point sources and their characteristics are very limited. Source apportionment methods are applied to identify contributions of individual regional sources to tropospheric particulate concentrations. The existing industrial database developed using traditional source measurement techniques provides total emission rates only, with no details on chemical nature or size characteristics of particulates. This database is inadequate, in current form, to address source-receptor relationships.

A source dilution system was developed for sampling and characterization of total PM, PM_2.5, and PM₁₀ (i.e., PM with aerodynamic diameter less than 10 μm) from residual oil and coal combustion. This new system has automatic control capabilities for key parameters, such as relative humidity (RH), temperature, and sample dilution. During optimization of the prototype equipment, three North American coal blends were burned using a 0.7-megawatt thermal (MW_t) pulverized coal-fired, pilot-scale boiler. Characteristic emission profiles, including PM_2.5 and total PM soluble acids, and elemental and carbon concentrations for three coal blends are presented.