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.     

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.     

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.     

Particulate matter speciation profiles for light-duty gasoline vehicles in the United States

Representative profiles for particulate matter particles less than or equal to 2.5 µm (PM_2.5) are developed from the Kansas City Light-Duty Vehicle Emissions Study for use in the U.S. Environmental Protection Agency (EPA) vehicle emission model, the Motor Vehicle Emission Simulator (MOVES), and for inclusion in the EPA SPECIATE database for speciation profiles. The profiles are compatible with the inputs of current photochemical air quality models, including the Community Multiscale Air Quality Aerosol Module Version 6 (AE6). The composition of light-duty gasoline PM_2.5 emissions differs significantly between cold start and hot stabilized running emissions, and between older and newer vehicles, reflecting both impacts of aging/deterioration and changes in vehicle technology. Fleet-average PM_2.5 profiles are estimated for cold start and hot stabilized running emission processes. Fleet-average profiles are calculated to include emissions from deteriorated high-emitting vehicles that are expected to continue to contribute disproportionately to the fleet-wide PM_2.5 emissions into the future. The profiles are calculated using a weighted average of the PM_2.5 composition according to the contribution of PM_2.5 emissions from each class of vehicles in the on-road gasoline fleet in the Kansas City Metropolitan Statistical Area. The paper introduces methods to exclude insignificant measurements, correct for organic carbon positive artifact, and control for contamination from the testing infrastructure in developing speciation profiles. The uncertainty of the PM_2.5 species fraction in each profile is quantified using sampling survey analysis methods. The primary use of the profiles is to develop PM_2.5 emissions inventories for the United States, but the profiles may also be used in source apportionment, atmospheric modeling, and exposure assessment, and as a basis for light-duty gasoline emission profiles for countries with limited data.

Implications: PM_2.5 speciation profiles were developed from a large sample of light-duty gasoline vehicles tested in the Kansas City area. Separate PM_2.5 profiles represent cold start and hot stabilized running emission processes to distinguish important differences in chemical composition. Statistical analysis was used to construct profiles that represent PM_2.5 emissions from the U.S. vehicle fleet based on vehicles tested from the 2005 calendar year Kansas City metropolitan area. The profiles have been incorporated into the EPA MOVES emissions model, as well as the EPA SPECIATE database, to improve emission inventories and provide the PM_2.5 chemical characterization needed by CMAQv5.0 for atmospheric chemistry modeling.     

Roadside measurements of size-segregated particulate organic compounds near gasoline and diesel-dominated freeways in Los Angeles,CA

Individual organic compounds such as hopanes and steranes (originating in lube oil) and selected polycyclic aromatic compounds (PAHs) (generated via combustion) found in particulate emissions from vehicles have proven useful in source apportionment of ambient particulate matter (PM). Detailed information on the size-segregated (ultrafine and accumulation mode) chemical characteristics of organic PM during the winter season originating from a pure gasoline traffic freeway (CA-110), and a mixed-fleet freeway with the highest fraction of heavy-duty diesel vehicles in the state of California (I-710) is reported in this study. Hopanes and steranes as well as high molecular weight PAHs such as benzo(ghi)perylene (BgP) and coronene levels are found comparable near these freeways, while elemental carbon (EC) and lighter molecular weight PAHs are found much elevated near I-710 compared to CA-110. The roadway organic speciation data presented here are compared with the emission factors (EFs) measured in the Caldecott tunnel, Berkeley, CA [Phuleria, H.C., Geller, M.D., Fine, P.M., Sioutas, C., 2006. Size-resolved emissions of organic tracers from light- and heavy-duty vehicles measured in a California roadway tunnel. Environmental Science and Technology 40, 4109–4118] for light-duty vehicles (LDVs) and heavy-duty vehicles. Very good agreement is observed between CA-110 measurements and LDV EFs as well as I-710 measurements and corresponding reconstructed EFs from Caldecott tunnel for hopanes and steranes as well as heavier PAHs such as BgP and coronene. Our results, therefore, suggest that the EFs for hopanes and steranes obtained in tunnel environments, where emissions are averaged over a large vehicle-fleet, enable reliable source apportionment of ambient PM, given the overall agreement between the roadway vs tunnel concentrations of these species.     

Comparison and evaluation of chemically speciated mobile source PM2.5 particulate matter profiles

Mobile sources are significant contributors to ambient PM2.5, 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 PM2.5 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.     

Particle mass emission rates from current-technology, light-duty gasoline vehicles

Now that the U.S. Environmental Protection Agency has promulgated new National Ambient Air Quality Standards for PM2.5, work will begin on generating the data required to determine the sources of ambient PM2.5 and the magnitude of their contributions to air pollution. This paper summarizes the results of an Environmental Research Consortium program, carried out under the auspices of the U.S. Council for Automotive Research. The program focused on particulate matter (PM) emissions from representative, current-technology, light-duty gasoline vehicles produced by DaimlerChrysler Corp., Ford Motor Co., and General Motors Corp. The vehicles, for the most part taken from the manufacturer's certification and durability fleets, were dynamometer-tested using the three-phase Federal Test Procedure in the companies' laboratories. The test fleet was made up of a mixture of both low-mileage (2K-35K miles) and high-mileage (60K-150K miles) cars, vans, sport utility vehicles, and light trucks. For each vehicle tested, PM emissions were accumulated over 4 cold-start tests, which were run on successive days. PM emission rates from the entire fleet (22 vehicles total) averaged less than 2 mg/mile. All 18 vehicles tested using California Phase 2 reformulated gasoline had PM emission rates less than 2 mg/mile at both low and high mileages.     

Size and composition distributions of particulate matter emissions: part 1--light-duty gasoline vehicles

Size-resolved particulate matter (PM) emitted from light-duty gasoline vehicles (LDGVs) was characterized using filter-based samplers, cascade impactors, and scanning mobility particle size measurements in the summer 2002. Thirty LDGVs, with different engine and emissions control technologies (model years 1965-2003; odometer readings 1264-207,104 mi), were tested on a chassis dynamometer using the federal test procedure (FTP), the unified cycle (UC), and the correction cycle (CC). LDGV PM emissions were strongly correlated with vehicle age and emissions control technology. The oldest models had average ultrafine PM0.1 (0.056- to 0.1-microm aerodynamic diameter) and fine PM1.8 (< or =1.8-microm aerodynamic diameter) emission rates of 9.6 mg/km and 213 mg/km, respectively. The newest vehicles had PM0.1 and PM1.8 emissions of 51 microg/km and 371 microg/km, respectively. Light duty trucks and sport utility vehicles had PM0.1 and PM1.8 emissions nearly double the corresponding emission rates from passenger cars. Higher PM emissions were associated with cold starts and hard accelerations. The FTP driving cycle produced the lowest emissions, followed by the UC and the CC. PM mass distributions peaked between 0.1- and 0.18-microm particle diameter for all vehicles except those emitting visible smoke, which peaked between 0.18 and 0.32 microm. The majority of the PM was composed of carbonaceous material, with only trace amounts of water-soluble ions. Elemental carbon (EC) and organic matter (OM) had similar size distributions, but the EC/OM ratio in LDGV exhaust particles was a strong function of the adopted emissions control technology and of vehicle maintenance. Exhaust from LDGV classes with lower PM emissions generally had higher EC/OM ratios. LDGVs adopting newer technologies were characterized by the highest EC/OM ratios, whereas OM dominated PM emissions from older vehicles. Driving cycles with cold starts and hard accelerations produced higher EC/OM ratios in ultrafine particles.     

Particle Mass Emission Rates from Current-Technology,Light-Duty Gasoline Vehicles

ABSTRACT

Now that the U.S. Environmental Protection Agency has promulgated new National Ambient Air Quality Standards for PM_2.5, work will begin on generating the data required to determine the sources of ambient PM_2.5 and the magnitude of their contributions to air pollution. This paper summarizes the results of an Environmental Research Consortium program, carried out under the auspices of the U.S. Council for Automotive Research. The program focused on particulate matter (PM) emissions from representative, current-technology, light-duty gasoline vehicles produced by DaimlerChrysler Corp., Ford Motor Co., and General Motors Corp. The vehicles, for the most part taken from the manufacturer's certification and durability fleets, were dynamometer-tested using the three-phase Federal Test Procedure in the companies' laboratories. The test fleet was made up of a mixture of both low-mileage (2K-35K miles) and high-mileage (60K-150K miles) cars, vans, sport utility vehicles, and light trucks. For each vehicle tested, PM emissions were accumulated over 4 cold-start tests, which were run on successive days. PM emission rates from the entire fleet (22 vehicles total) averaged less than 2 mg/mile. All 18 vehicles tested using California Phase 2 reformulated gasoline had PM emission rates less than 2 mg/ mile at both low and high mileages.     

Emission factors for high-emitting vehicles based on on-road measurements of individual vehicle exhaust with a mobile measurement platform

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO(x)), and particle mass with aerodynamic diameter below 2.5 microm (PM2.5) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low- and high-speed acceleration, low- and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO(x), black carbon (BC), PM2.5, and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO(x) and CO fleet-average emission factors and more than 60% of PM2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM2.5, and NO(x) tended to cluster among the same vehicles.     

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.     

Emission rates and comparative chemical composition from selected in-use diesel and gasoline-fueled vehicles

Emission samples for toxicity testing and detailed chemical characterization were collected from a variety of gasoline- and diesel-fueled in-use vehicles operated on the Unified Driving Cycle on a chassis dynamometer. Gasoline vehicles included normal particle mass (particulate matter [PM]) emitters (tested at 72 and 30 degrees F), "black" and "white" smokers, and a new-technology vehicle (tested at 72 degrees F). Diesel vehicles included current-technology vehicles (tested at 72 and 30 degrees F) and a high PM emitter. Total PM emission rates ranged from below 3 mg/mi up to more than 700 mg/mi for the white smoker gasoline vehicle. Emission rates of organic and elemental carbon (OC/EC), elements (metals and associated analytes), ions, and a variety of particulate and semi-volatile organic compounds (polycyclic aromatic hydrocarbons [PAH], nitro-PAH, oxy-PAH, hopanes, and steranes) are reported for these vehicles. Speciated organic analysis also was conducted on the fuels and lube oils obtained from these vehicles after the emissions testing. The compositions of emissions were highly dependent on the fuel type (gasoline vs. diesel), the state of vehicle maintenance (low, average, or high emitters; white or black smokers), and ambient conditions (i.e., temperature) of the vehicles. Fuel and oil analyses from these vehicles showed that oil served as a repository for combustion byproducts (e.g., PAH), and oil-burning gasoline vehicles emitted PAH in higher concentrations than did other vehicles. These PAH emissions matched the PAH compositions observed in oil.     

Comparing lifetime emissions of natural gas and conventional fuel vehicles: an application of the generalized ANCOVA model

New regulations and incentives are encouraging the use of clean, alternative fuel vehicles (AFVs) in urban areas. These vehicles are seen as one option for reducing air pollution from mobile sources. However, because of the limited number of AFVs on the road, little is known about actual lifetime emissions characteristics of in-use AFVs. This study describes the use of a generalized analysis of covariance model to evaluate and compare the emissions from natural gas vehicles with emissions from reformulated gasoline vehicles. The model describes fleet-wide emissions deterioration, while also accounting for individual vehicle variability within the fleet. This ability to measure individual vehicle variability can then be used to provide realistic bounds for the emissions deterioration in individual vehicles and the fleet as a whole. In order to illustrate the use of the model, the carbon monoxide, oxides of nitrogen (NOx), non-methane hydrocarbon (NMHC), and carbon dioxide emissions characteristics of a fleet of dedicated natural gas Dodge Ram vans and a fleet of dedicated reformulated gasoline Dodge Ram vans operating in the U.S. government fleet are explored. The analysis demonstrates the utility of the statistical method and suggests a potential for natural gas Dodge Ram vans to be generally cleaner than their conventional fuel counterparts. However, in the case of NOx and NHMCs, the analysis also suggests that these emissions benefits might be reduced over the vehicle lifetime due to higher emissions deterioration rates for natural gas vehicles. As this paper is aimed at illustrating the analysis of the covariance model, the results reported herein should be considered within the context of a more comprehensive study of these data before general conclusions are possible. Generalization of these findings to other vehicle models and alternative fuel technologies is not justified without further study.     

Characterization of the fugitive particulate emissions from construction mud/dirt carryout

Although the fugitive dust associated with construction mud/dirt carryout can represent a substantial portion of the particulate matter (PM) emissions inventory in nonattainment areas, it has not been well characterized by direct sampling methods. In this paper, a research program is described that directly determined both PM10 and PM2.5 (particles < or =10 and 2.5 microm in classical aerodynamic diameter, respectively) emission factors for mud/dirt carryout from a major construction project located in metropolitan Kansas City, MO. The program also assessed the contribution of automotive emissions to the total PM2.5 burden and determined the baseline emissions from the test road. As part of the study, both time-integrated and continuous exposure-profiling methods were used to assess the PM emissions, including particle size and elemental composition. This research resulted in overall PM10 and PM2.5 emission factors of 6 and 0.2 g/vehicle, respectively. Although PM10 is within the range of prior U.S. Environmental Protection Agency (EPA) guidance, the PM2.5 emission factor is far lower than previous estimates published by EPA. In addition, based on both the particle size and chemical data obtained in the study, a major portion of the PM2.5 emissions appears to be attributable to automotive exhaust from light-duty, gasoline-powered vehicles and not to the fugitive dust associated with reentrained mud/dirt carryout.     

Development of a microscale emission factor model for particulate matter for predicting real-time motor vehicle emissions

The U.S. Environmental Protection Agency's National Exposure Research Laboratory is pursuing a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source through the air pathway to human exposure in significant exposure microenvironments. Current particulate matter (PM) emission models, particle emission factor model (used in the United States, except California) and motor vehicle emission factor model (used in California only), are suitable only for county-scale modeling and emission inventories. There is a need to develop a site-specific real-time emission factor model for PM emissions to support human exposure studies near roadways. A microscale emission factor model for predicting site-specific real-time motor vehicle PM (MicroFacPM) emissions for total suspended PM, PM less than 10 microm aerodynamic diameter, and PM less than 2.5 microm aerodynamic diameter has been developed. The algorithm used to calculate emission factors in MicroFacPM is disaggregated, and emission factors are calculated from a real-time fleet, rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacPM requires input information necessary to characterize the site-specific real-time fleet being modeled. Other variables required include average vehicle speed, time and day of the year, ambient temperature, and relative humidity.     

Modification in the soil and traffic-related sources of particle matter between 1998 and 2007 in Santiago de Chile

Santiago de Chile is one of the most polluted South American cities, concentrating its pollution episodes during winter. Daily PM2.5 (particulate matter [PM] < or = 2.5 microm in aerodynamic diameter) concentrations over 80 microg/m3 have been reached frequently since 1998. Despite several regulations introduced over the past 20 yr to improve the air quality, PM concentration levels remain high. In this work, sampling in downtown Santiago was conducted from April 1998 to August 2007 for PM2.5 and from October 2003 to March 2006 for PM10-2.5 (PM between 2.5 and 10 microm in aerodynamic diameter) with dichotomous samplers. Elemental analysis was performed on the samples with X-ray fluorescence. The resuming series of 859 samples and 216 elements identified were divided into semiannual periods and analyzed with factor analysis. Five factors are clearly discerned: soil, motor vehicles, residual oil, marine aerosols, and secondary sulfates. The soil factor in the fine fraction shows a clear increase from 2002 to 2006, whereas the coarse fraction of this factor shows a stable trend. The most probable cause for this trend is the growth in the number of vehicles in Santiago (6.5%/yr), which increases the resuspension of particles from the ground. Another cause for the increase is the growth in the construction activity (4.2%/yr). The motor vehicle factor in the fine fraction shows a decrease between 1998 and 2006. The decrease in the apportionment of this factor can be explained by the improvement in the vehicle fleet. In Santiago, the number of noncatalytic vehicles has been reduced from 389,000 in 2001 to 275,000 in 2006. The residual oil factor also shows a decrease between 1998 and 2006. The decrease could be attributed to the adoption of cleaner technologies and norms regarding gasoline and diesels.     

The Denver Aerosol Sources and Health (DASH) Study: Overview and Early Findings

Improved understanding of the sources of air pollution that are most harmful could aid in developing more effective measures for protecting human health. The Denver Aerosol Sources and Health (DASH) study was designed to identify the sources of ambient fine particulate matter (PM(2.5)) that are most responsible for the adverse health effects of short-term exposure to PM (2.5). Daily 24-hour PM(2.5) sampling began in July 2002 at a residential monitoring site in Denver, Colorado, using both Teflon and quartz filter samplers. Sampling is planned to continue through 2008. Chemical speciation is being carried out for mass, inorganic ionic compounds (sulfate, nitrate and ammonium), and carbonaceous components, including elemental carbon, organic carbon, temperature-resolved organic carbon fractions and a large array of organic compounds. In addition, water soluble metals were measured daily for 12 months in 2003. A receptor-based source apportionment approach utilizing positive matrix factorization (PMF) will be used to identify PM (2.5) source contributions for each 24-hour period. Based on a preliminary assessment using synthetic data, the proposed source apportionment should be able to identify many important sources on a daily basis, including secondary ammonium nitrate and ammonium sulfate, diesel vehicle exhaust, road dust, wood combustion and vegetative debris. Meat cooking, gasoline vehicle exhaust and natural gas combustion were more challenging for PMF to accurately identify due to high detection limits for certain organic molecular marker compounds. Measurements of these compounds are being improved and supplemented with additional organic molecular marker compounds. The health study will investigate associations between daily source contributions and an array of health endpoints, including daily mortality and hospitalizations and measures of asthma control in asthmatic children. Findings from the DASH study, in addition to being of interest to policymakers, by identifying harmful PM(2.5) sources may provide insights into mechanisms of PM effect.     

Application of a microscale emission factor model for particulate matter to calculate vehicle-generated contributions to fine particulate emissions

This paper discusses the evaluation and application of a new generation of particulate matter (PM) emission factor model (MicroFacPM). MicroFacPM that was evaluated in Tuscarora Mountain Tunnel, Pennsylvania Turnpike, PA shows good agreement between measured and modeled emissions. MicroFacPM application is presented to the vehicle traffic on the main approach road to the Ambassador Bridge, which is one of the most important international border entry points in North America, connecting Detroit, MI, with Windsor, Ontario, Canada. An increase in border security has forced heavy-duty diesel vehicles to line up for several kilometers through the city of Windsor causing concern about elevated concentrations of ambient PM. MicroFacPM has been developed to model vehicle-generated PM (fine [PM2.5] and coarse < or = 10 microm [PM10]) from the on-road vehicle fleet, which in this case includes traffic at very low speeds (10 km/h). The Windsor case study gives vehicle generated PM2.5 sources and their breakdown by vehicle age and class. It shows that the primary sources of vehicle-generated PM2.5 emissions are the late-model heavy-duty diesel vehicles. We also applied CALINE4 and AERMOD in conjunction with MicroFacPM, using Canadian traffic and climate conditions, to describe the vehicle-generated PM2.5 dispersion near this roadway during the month of May in 2003.     

On-road measurement of fine particle and nitrogen oxide emissions from light- and heavy-duty motor vehicles

An updated assessment of fine particle emissions from light- and heavy-duty vehicles is needed due to recent changes to the composition of gasoline and diesel fuel, more stringent emission standards applying to new vehicles sold in the 1990s, and the adoption of a new ambient air quality standard for fine particulate matter (PM_2.5) in the United States. This paper reports the measurement of emissions from vehicles in a northern California roadway tunnel during summer 1997. Separate measurements were made of uphill traffic in two tunnel bores: one bore carried both light-duty vehicles and heavy-duty diesel trucks, and the second bore was reserved for light-duty vehicles. Ninety-eight percent of the light-duty vehicles were gasoline-powered. In the tunnel, heavy-duty diesel trucks emitted 24, 37, and 21 times more fine particle, black carbon, and sulfate mass per unit mass of fuel burned than light-duty vehicles. Heavy-duty diesel trucks also emitted 15–20 times the number of particles per unit mass of fuel burned compared to light-duty vehicles. Fine particle emissions from both vehicle classes were composed mostly of carbon; diesel-derived particulate matter contained more black carbon (51±11% of PM_2.5 mass) than did light-duty fine particle emissions (33±4%). Sulfate comprised only 2% of total fine particle emissions for both vehicle classes. Sulfate emissions measured in this study for heavy-duty diesel trucks are significantly lower than values reported in earlier studies conducted before the introduction of low-sulfur diesel fuel. This study suggests that heavy-duty diesel vehicles in California are responsible for nearly half of oxides of nitrogen emissions and greater than three-quarters of exhaust fine particle emissions from on-road motor vehicles.     

An investigation on the physical,chemical and ecotoxicological characteristics of particulate matter emitted from light-duty vehicles

Particulate matter (PM) emitted from three light-duty vehicles was studied in terms of its physicochemical and ecotoxicological character using Microtox^® bioassay tests. A diesel vehicle equipped with an oxidation catalyst emitted PM which consisted of carbon species at over 97%. PM from a diesel vehicle with a particle filter (DPF) consisted of almost equal amounts of carbon species and ions, while a gasoline vehicle emitted PM consisting of ～90% carbon and ～10% ions. Both the DPF and the gasoline vehicles produced a distinct nucleation mode at 120 km/h. The PM emitted from the DPF and the gasoline vehicles was less ecotoxic than that of conventional diesel, but not in direct proportion to the emission levels of the different vehicles. These results indicate that PM emission reductions are not equally translated into ecotoxicity reductions, implying some deficiencies on the actual environmental impact of emission control technologies and regulations.