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.     

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.     

Source Apportionment of Ambient Total Suspended Particulates and Coarse Particulate Matter in Urban Areas of Jiaozuo,China

Abstract

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 ～g/m³ and low in summer days at 456 ～g/m³; however, the spatial PM₁₀ average exhibited little variation at a level of approximately 325 ～g/m³, and PM_10-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.     

Source characterization of ambient fine particles at multiple sites in the Seattle area

To identify major PM_2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) sources with a particular emphasis on the ship engine emissions from a major port, integrated 24 h PM_2.5 speciation data collected between 2000 and 2005 at five United State Environmental Protection Agency's Speciation Trends Network monitoring sites in Seattle, WA were analyzed. Seven to ten PM_2.5 sources were identified through the application of positive matrix factorization (PMF). Secondary particles (12–26% for secondary nitrate; 17–20% for secondary sulfate) and gasoline vehicle emissions (13–31%) made the largest contributions to the PM_2.5 mass concentrations at all of the monitoring sites except for the residential Lake Forest site, where wood smoke contributed the most PM_2.5 mass (31%). Other identified sources include diesel vehicle emissions, airborne soil, residual oil combustion, sea salt, aged sea salt, metal processing, and cement kiln. Residual oil combustion sources identified at multiple monitoring sites point clearly to the Port of Seattle suggesting ship emissions as the source of oil combustion particles. In addition, the relationship between sulfate concentrations and the oil combustion emissions indicated contributions of ship emissions to the local sulfate concentrations. The analysis of spatial variability of PM_2.5 sources shows that the spatial distributions of several PM_2.5 sources were heterogeneous within a given air shed.     

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

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

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

ABSTRACT

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

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

Source apportionment of PM10 in six cities of northern China

Ambient PM₁₀ was sampled in six northern China cities (Urumqi, Yinchuan, Taiyuan, Anyang, Tianjin and Jinan) from December 1999 to July 2002, and analyzed for 16 chemical elements, two water-soluble ions, total carbon, and organic carbon. In addition, chemical source profiles consisting of the same particulate components were obtained from a number of naturally occurring geological sources (soil dust from exposed lands) and sources of atmospheric particulates resulting from human activities (resuspended dust, cement, coal combustion fly ash, vehicle exhaust, and secondary particles). Ambient and source data were used in a chemical mass balance (CMB) receptor model to determine the major source of PM₁₀ in these six cities. Results of CMB modeling showed that the major source of ambient PM₁₀ in all the cities was resuspended dust. Significant contributions from coal fly ash were also found in all six cities.     

Spatial and temporal variations in PM10 and PM2.5 source contributions and comparison to emissions during the 1995 integrated monitoring study

The ambient PM₁₀ and PM_2.5 data collected during the fall and winter portions of the 1995 Integrated Monitoring Study (IMS95) were used to conduct Chemical Mass Balance (CMB) Modeling to determine source contribution estimates. Data from the core and saturation monitoring sites provided an extensive database for evaluating the spatial and temporal variations of contributing sources. Geological sources dominated fall samples, while secondary ammonium nitrate and carbonaceous sources were the largest contributors for winter samples. Secondary ammonium nitrate concentrations were uniform across all sites during both the fall and winter. Site-to-site variability was primarily due to differences in geological contributions in the fall, and carbonaceous source contributions in the winter. During the winter, diurnal profiles of particulate matter (PM) were driven by variations in carbonaceous sources at urban sites, and by variations in secondary ammonium nitrate at rural sites. Although records of day-specific PM activities were recorded during the study, no correlation was observed between 24-h CMB results and specific activities. The ambient data collected during IMS95 was also used to evaluate the adequacy of the emissions inventory. Comparison of ambient and emissions based ratios of NMHC/NO_x, PM/NO_x, CO/NO_x, and SO_x/NO_x suggested that emissions of NMHC and CO in some locations may be underestimated, while emissions for PM and SO_x may be overestimated. Comparison of fractional primary CMB source contribution estimates to corresponding fractional emissions estimates indicated that geological sources were overemphasized in the inventory, while carbonaceous sources were underrepresented.     

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%).     

Determination of Microgram Quantities of Inorganic Sulfate in Atmospheric Particulates

Abstract

Before a community-wide woodstove changeout program, a chemical mass balance (CMB) source apportionment study was conducted in Libby, MT, during the winter of 2003–2004 to identify the sources of fine particulate matter (PM_2.5) within the valley. Results from this study showed that residential woodstoves were the major source, contributing approximately 80% of the ambient PM_2.5 throughout the winter months. In an effort to lower the ambient PM_2.5, a large woodstove changeout program was conducted in Libby from 2005 to 2007 in which nearly 1200 old woodstoves were changed out with cleaner burning models. During the winter of 2007–2008, a follow-up CMB source apportionment study was conducted to evaluate the effectiveness of the changeout. Results from this study showed that average winter PM_2.5 mass was reduced by 20%, and woodsmoke-related PM_2.5 (as identified by the CMB model) was reduced by 28% when compared with the pre-changeout winter of 2003– 2004. These results suggest that a woodstove changeout can be an effective tool in reducing ambient levels of PM_2.5 in woodstove-impacted communities.     

Sources of fine particles in the South Coast area,California

PM_2.5 (particulate matter less than 2.5 μm in aerodynamic diameter) speciation data collected between 2003 and 2005 at two United State Environmental Protection Agency (US EPA) Speciation Trends Network monitoring sites in the South Coast area, California were analyzed to identify major PM_2.5 sources as a part of the State Implementation Plan development. Eight and nine major PM_2.5 sources were identified in LA and Rubidoux, respectively, through PMF2 analyses. Similar to a previous study analyzing earlier data (Kim and Hopke, 2007a), secondary particles contributed the most to the PM_2.5 concentrations: 53% in LA and 59% in Rubidoux. The next highest contributors were diesel emissions (11%) in LA and Gasoline vehicle emissions (10%) in Rubidoux. Most of the source contributions were lower than those from the earlier study. However, the average source contributions from airborne soil, sea salt, and aged sea salt in LA and biomass smoke in Rubidoux increased.To validate the apportioned sources in this study, PMF2 results were compared with those obtained from EPA PMF (US EPA, 2005). Both models identified the same number of major sources and the resolved source profiles and contributions were similar at the two monitoring sites. The minor differences in the results caused by the differences in the least square algorithm and non-negativity constraints between two models did not affect the source identifications.     

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.     

Sources and seasonal variation of atmospheric polycyclic aromatic hydrocarbons in Dalian,China: Factor analysis with non-negative constraints combined with local source fingerprints

Vapor- and particulate-phase polycyclic aromatic hydrocarbon (PAH) samples were continuously collected at an urban site in Dalian, China, during the heating and non-heating period. There is strong temperature dependence and obvious seasonal trend for atmospheric PAHs, and significant positive correlations of atmospheric PAHs with SO₂ and CO concentrations were observed. Factor analysis model with non-negative constraints (FA–NNC) combined with local and literature PAH source fingerprints was successful in source identification of particulate PAHs in the atmospheric samples. The results suggested that, in heating period, the main pollution sources were identified as coal-fired boiler emission (56%), residential coal combustion (33%) and traffic emissions (11%). As for non-heating period, the main sources were gasoline engine emission, traffic tunnel emission and coal-fired power plant, and the overall source contributions of traffic emission (gasoline engine + traffic tunnel) were 79% and coal-fired power plant 21%. The current results support our previous study and provide new insights. This can be the first attempt to quantitatively apportion air organic pollutants using receptor models combined with local source fingerprints. The source fingerprints can be used as reference data for source apportionment of atmospheric PAHs of China.     

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 airborne particulate matter in Southeast Texas using a source-oriented 3D air quality model

A nested version of the source-oriented externally mixed UCD/CIT model was developed to study the source contributions to airborne particulate matter (PM) during a two-week long air quality episode during the Texas 2000 Air Quality Study (TexAQS 2000). Contributions to primary PM and secondary ammonium sulfate in the Houston–Galveston Bay (HGB) and Beaumont–Port Arthur (BPA) areas were determined.The predicted 24-h elemental carbon (EC), organic compounds (OC), sulfate, ammonium ion and primary PM_2.5 mass are in good agreement with filter-based observations. Predicted concentrations of hourly sulfate, ammonium ion, and primary OC from diesel and gasoline engines and biomass burning organic aerosol (BBOA) at La Porte, Texas agree well with measurements from an Aerodyne Aerosol Mass Spectrometer (AMS).The UCD/CIT model predicts that EC is mainly from diesel engines and majority of the primary OC is from internal combustion engines and industrial sources. Open burning contributes large fractions of EC, OC and primary PM_2.5 mass. Road dust, internal combustion engines and industries are the major sources of primary PM_2.5. Wildfire dominates the contributions to all primary PM components in areas near the fires. The predicted source contributions to primary PM are in general agreement with results from a chemical mass balance (CMB) model. Discrepancy between the two models suggests that further investigations on the industrial PM emissions are necessary.Secondary ammonium sulfate accounts for the majority of the secondary inorganic PM. Over 80% of the secondary sulfate in the 4 km domain is produced in upwind areas. Coal combustion is the largest source of sulfate. Ammonium ion is mainly from agriculture sources and contributions from gasoline vehicles are significant in urban areas.     

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 of PM2.5 for supporting control strategies in the Monterrey Metropolitan Area,Mexico

The Monterrey Metropolitan Area (MMA) in Northeast Mexico has shown high PM_2.5 concentrations since 2003. The data shows that the annual average concentration exceeds from 2 to 3 times the Mexican PM_2.5 annual air quality standard of 12 µg/m³. In a previous work we studied the chemical characterization of PM_2.5 in two sites of the MMA during the winter season. Among the most important components we found ammonium sulfate and nitrate, elemental and organic carbon, and crustal matter. In this work we present the results of a second chemical characterization study performed during the summer time and the application of the chemical mass balance (CMB) model to determine the source apportionment of air pollutants in the region. The chemical analysis results show that the chemical composition of PM_2.5 is similar in both sites and periods of the year. The results of the chemical analysis and the CMB model show that industrial, traffic, and combustion activities in the area are the major sources of primary PM_2.5 and precursor gases of secondary inorganic and organic aerosol (SO₂, NOx, NH₃, and volatile organic compounds [VOCs]). We also found that black carbon and organic carbon are important components of PM_2.5 in the MMA. These results are consistent with the MMA emission inventory that reports as major sources of particles and SO₂ a refinery and fuel combustion, as well as nitrogen oxides and ammonium from transportation and industrial activities in the MMA and ammonium form agricultural activities in the state. The results of this work are important to identify and support effective actions to reduce direct emissions of PM_2.5 and its precursor gases to improve air quality in the MMA. Implications: The Monterrey Metropolitan Area (MMA) has been classified as the most air-polluted area in Mexico by the World Health Organization (WHO). Effective actions need to be taken to control primary sources of PM_2.5 and its precursors, reducing health risks on the population exposed and their associated costs. The results of this study identify the main sources and their estimated contribution to PM_2.5 mass concentration, providing valuable information to the local environmental authorities to take decisions on PM_2.5 control strategies in the MMA.     

Atmospheric particulate matter in the city of Sao Carlos/SP, Brazil

This paper presents experimental data and source apportionment simulations on particulate matter (PM₁₀ and PM_2.5) in the atmosphere of Sao Carlos/SP, Brazil. Both a Hi-vol sampler equipped with glass fibre filters and a Dichotomous sampler with nucleopore filters were used. The collected material was analysed for total carbon, using a thermometric method, and for traces of several chemical species, using X-ray fluorescence spectroscopy. Source apportionment estimations were made with a chemical mass balance receptor model software (CMB8), with source profiles taken and adapted from the literature. The results indicate that both PM₁₀ concentration and source apportionment vary seasonally, and that vegetative burning can be a significant source of PM₁₀ in the dry season     

Tracer-based source apportionment of polycyclic aromatic hydrocarbons in PM2.5 in Guangzhou, southern China, using positive matrix factorization (PMF)

From 28 November to 23 December 2009, 24-h?PM_2.5 samples were collected simultaneously at six sites in Guangzhou. Concentrations of 18 polycyclic aromatic hydrocarbons (PAHs) together with certain molecular tracers for vehicular emissions (i.e., hopanes and elemental carbon), coal combustion (i.e., picene), and biomass burning (i.e., levoglucosan) were determined. Positive matrix factorization (PMF) receptor model combined with tracer data was applied to explore the source contributions to PAHs. Three sources were identified by both inspecting the dominant tracer(s) in each factor and comparing source profiles derived from PMF with determined profiles in Guangzhou or in the Pearl River Delta region. The three sources identified were vehicular emissions (VE), biomass burning (BB), and coal combustion (CC), accounting for 11?±?2 %, 31?±?4 %, and 58?±?4 % of the total PAHs, respectively. CC replaced VE to become the most important source of PAHs in Guangzhou, reflecting the effective control of VE in recent years. The three sources had different contributions to PAHs with different ring sizes, with higher BB contributions (75?±?3 %) to four-ring PAHs such as pyrene and higher CC contributions (57?±?4 %) to six-ring PAHs such as benzo[ghi]perylene. Temporal variations of VE and CC contributions were probably caused by the change of weather conditions, while temporal variations of BB contributions were additionally influenced by the fluctuation of BB emissions. Source contributions also showed some spatial variations, probably due to the source emission variations near the sampling sites.     

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

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