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.     

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.     

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.     

Size and composition distributions of particulate matter emissions: part 2--heavy-duty diesel vehicles

Particulate matter (PM) emissions from heavy-duty diesel vehicles (HDDVs) were collected using a chassis dynamometer/dilution sampling system that employed filter-based samplers, cascade impactors, and scanning mobility particle size (SMPS) measurements. Four diesel vehicles with different engine and emission control technologies were tested using the California Air Resources Board Heavy Heavy-Duty Diesel Truck (HHDDT) 5 mode driving cycle. Vehicles were tested using a simulated inertial weight of either 56,000 or 66,000 lb. Exhaust particles were then analyzed for total carbon, elemental carbon (EC), organic matter (OM), and water-soluble ions. HDDV fine (< or =1.8 microm aerodynamic diameter; PM1.8) and ultrafine (0.056-0.1 microm aerodynamic diameter; PM0.1) PM emission rates ranged from 181-581 mg/km and 25-72 mg/km, respectively, with the highest emission rates in both size fractions associated with the oldest vehicle tested. Older diesel vehicles produced fine and ultrafine exhaust particles with higher EC/OM ratios than newer vehicles. Transient modes produced very high EC/OM ratios whereas idle and creep modes produced very low EC/OM ratios. Calcium was the most abundant water-soluble ion with smaller amounts of magnesium, sodium, ammonium ion, and sulfate also detected. Particle mass distributions emitted during the full 5-mode HDDV tests peaked between 100-180 nm and their shapes were not a function of vehicle age. In contrast, particle mass distributions emitted during the idle and creep driving modes from the newest diesel vehicle had a peak diameter of approximately 70 nm, whereas mass distributions emitted from older vehicles had a peak diameter larger than 100 nm for both the idle and creep modes. Increasing inertial loads reduced the OM emissions, causing the residual EC emissions to shift to smaller sizes. The same HDDV tested at 56,000 and 66,000 lb had higher PM0.1 EC emissions (+22%) and lower PM0.1 OM emissions (-38%) at the higher load condition.     

Characterization of exhaust particles from military vehicles fueled with diesel,gasoline, and JP-8

Diluted exhaust from selected military aircraft ground-support equipment (AGE) was analyzed for particulate mass, elemental carbon (EC) and organic carbon (OC), SO4(2-), and size distributions. The experiments occurred at idle and load conditions and utilized a chassis dynamometer. The selected AGE vehicles operated on gasoline, diesel, and JP-8. These military vehicles exhibited concentrations, size distributions, and emission factors in the same range as those reported for nonmilitary vehicles. The diesel and JP-8 emission rates for PM ranged from 0.092 to 1.1 g/kg fuel. The EC contributed less and the OC contributed more to the particulate mass than reported in recent studies of vehicle emissions. Overall, the particle size distribution varied significantly with engine condition, with the number of accumulation mode particles and the count median diameter (CMD) increasing as engine load increased. The SO4(2-) analyses showed that the distribution of SO4(2-) mass mirrored the distribution of particle mass.     

Contribution of motor vehicle emissions to organic carbon and fine particle mass in Pittsburgh, Pennsylvania: Effects of varying source profiles and seasonal trends in ambient marker concentrations

We present estimates of the vehicular contribution to ambient organic carbon (OC) and fine particle mass (PM) in Pittsburgh, PA using the chemical mass balance (CMB) model and a large dataset of ambient molecular marker concentrations. Source profiles for CMB analysis are selected using a method of comparing the ambient ratios of marker species with published profiles for gasoline and diesel vehicle emissions. The ambient wintertime data cluster on a hopanes/EC ratio–ratio plot, and therefore can be explained by a large number of different source profile combinations. In contrast, the widely varying summer ambient ratios can be explained by a more limited number of source profile combinations. We present results for a number of different CMB scenarios, all of which perform well on the different statistical tests used to establish the quality of a CMB solution. The results illustrate how CMB estimates depend critically on the marker-to-OC and marker-to-PM ratios of the source profiles. The vehicular contribution in the winter is bounded between 13% and 20% of the ambient OC (274±56–416±72 ng-C m⁻³). However, variability in the diesel profiles creates uncertainty in the gasoline–diesel split. On an OC basis, one set of scenarios suggests gasoline dominance, while a second set indicates a more even split. On a PM basis, all solutions indicate a diesel-dominated split. The summer CMB solutions do not present a consistent picture given the seasonal shift and wide variation in the ambient hopanes-to-EC ratios relative to the source profiles. If one set of source profiles is applied to the entire dataset, gasoline vehicles dominate vehicular OC in the winter but diesel dominates in the summer. The seasonal pattern in the ambient hopanes-to-EC ratios may be caused by photochemical decay of hopanes in the summer or by seasonal changes in vehicle emission profiles.     

Summer and winter nonmethane hydrocarbon emissions from on-road motor vehicles in the Midwestern United States

On-road vehicle emission rates of nonmethane hydrocarbons (NMHCs) were measured in two tunnels in Milwaukee, WI, in summer 2000 and winter 2001. Seasonal ambient temperatures in the Midwestern United States vary more widely than in locations where most studies of NMHC emissions from vehicle fleets have been conducted. Ethanol is the added fuel oxygenate in the area, and, thus, emissions measured here are of interest as other regions phase out methyl tertiary butyl ether and increase the use of ethanol. Total emissions of NMHCs in three types of tunnel tests averaged 4560 +/- 800 mg L(-1) fuel burned (average +/- standard error). To investigate the impact of cold start on vehicle emissions, samples were collected as vehicles exited a parking structure in subzero temperatures. NMHC emissions in the subzero cold-start test were 8830 +/- 190 mg L(-1) fuel-nearly double the tunnel emissions. Comparison of ambient data for the Milwaukee area with tunnel emissions showed the impact of seasonal differences in fuels and emissions on the urban atmosphere. Composition of fuel samples collected from area gas stations in both seasons was correlated with vehicle emissions; the predominant difference was increased winter emissions of lighter hydrocarbons present in winter gasoline. A chemical mass balance model was used to determine the contributions of whole gasoline and gasoline headspace vapors to vehicle emissions in the tunnel and cold-start tests, which were found to vary with season. Results of the mass balance model also indicate that partially combusted components of gasoline are a major contributor to emissions of aromatic compounds and air toxic compounds, including benzene, toluene, xylenes, napthalene, and 1,3-butadiene, whereas air toxics hexane and 2,2,4-trimethylpentane are largely attributed to gasoline and headspace vapors.     

机动车尾气VOCs排放特征及减排措施研究

分析了机动车尾气挥发性有机物(VOCs)的排放特征,发现尾气VOCs排放具有明显的日变化和季节变化特征。不同区域不同车型机动车尾气VOCs成分谱略有差异,轻型汽油车尾气VOCs中芳香烃和烷烃含量较高,柴油车烷烃含量较高。尾气排放受机动车保有量、行驶里程、维护保养水平、行驶速度和燃油标准、排放标准等因素影响。从优先控制汽油车、加快机动车更新、采取本地化减排措施、加强多元管理措施、提高科研水平等方面提出了针对性的减排措施。     

Cold-start emissions of modern passenger cars at different low ambient temperatures and their evolution over vehicle legislation categories

The emissions of modern gasoline and diesel passenger cars are reduced by catalysts except in cold-starting. Since catalysts require a certain temperature (typically above 300 °C) to work to full efficiency, emissions are significantly higher during the warm-up phase of the car. The duration of this period and the emissions produced depend on the ambient temperature as well as on the initial temperature of the car's propulsion systems.The additional emissions during a warm-up phase, known as “cold-start extra emissions” (CSEEs) for emission inventory modelling, are mostly assessed by emission measurements at an ambient temperature of 23 °C. However, in many European countries average ambient temperatures are below 23 °C. This necessitates emission measurements at lower temperatures in order to model and assess cold-start emissions for real-world temperature conditions.This paper investigates the influence of regulated pollutants and CO₂ emissions of recent gasoline and diesel car models (Euro-4 legislation) at different ambient temperatures, 23, ?7 and ?20 °C. We present a survey and model of the evolution of cold-start emissions as a function of different car generations (pre-Euro-1 to Euro-4 legislations). In addition the contribution of CSEEs to total fleet running emissions is shown to highlight their increasing importance.For gasoline cars, it turns out that in average real-world driving the majority of the CO (carbon monoxide) and HC (hydrocarbon) total emissions are due to cold-start extra emissions. Moreover, the cold-start emissions increase considerably at lower ambient temperatures. In contrast, cold-start emissions of diesel cars are significantly lower than those of gasoline cars. Furthermore, the transition from Euro-3 to Euro-4 gasoline vehicles shows a trend for a smaller decline for cold-start extra emissions than for legislative limits. Particle and NO_x emission of cold-starts are less significant.     

Trends in onroad transportation energy and emissions

Globally, 1.3 billion on-road vehicles consume 79 quadrillion BTU of energy, mostly gasoline and diesel fuels, emit 5.7 gigatonnes of CO₂, and emit other pollutants to which approximately 200,000 annual premature deaths are attributed. Improved vehicle energy efficiency and emission controls have helped offset growth in vehicle activity. New technologies are diffusing into the vehicle fleet in response to fuel efficiency and emission standards. Empirical assessment of vehicle emissions is challenging because of myriad fuels and technologies, intervehicle variability, multiple emission processes, variability in operating conditions, and varying capabilities of measurement methods. Fuel economy and emissions regulations have been effective in reducing total emissions of key pollutants. Real-world fuel use and emissions are consistent with official values in the United States but not in Europe or countries that adopt European standards. Portable emission measurements systems, which uncovered a recent emissions cheating scandal, have a key role in regulatory programs to ensure conformity between “real driving emissions” and emission standards. The global vehicle fleet will experience tremendous growth, especially in Asia. Although existing data and modeling tools are useful, they are often based on convenience samples, small sample sizes, large variability, and unquantified uncertainty. Vehicles emit precursors to several important secondary pollutants, including ozone and secondary organic aerosols, which requires a multipollutant emissions and air quality management strategy. Gasoline and diesel are likely to persist as key energy sources to mid-century. Adoption of electric vehicles is not a panacea with regard to greenhouse gas emissions unless coupled with policies to change the power generation mix. Depending on how they are actually implemented and used, autonomous vehicles could lead to very large reductions or increases in energy consumption. Numerous other trends are addressed with regard to technology, emissions controls, vehicle operations, emission measurements, impacts on exposure, and impacts on public health.

Implications: Without specific policies to the contrary, fossil fuels are likely to continue to be the major source of on-road vehicle energy consumption. Fuel economy and emission standards are generally effective in achieving reductions per unit of vehicle activity. However, the number of vehicles and miles traveled will increase. Total energy use and emissions depend on factors such as fuels, technologies, land use, demographics, economics, road design, vehicle operation, societal values, and others that affect demand for transportation, mode choice, energy use, and emissions. Thus, there are many opportunities to influence future trends in vehicle energy use and emissions.     

An empirical method for predicting exhaust emissions of regulated pollutants from future vehicle technologies

A methodology is presented for estimating emissions of passenger cars and light commercial vehicles complying with future European Union emission standards, which introduces appropriate reductions over the emission factors of existing vehicle technologies. For three-way catalyst gasoline vehicles, future real-world emissions are assumed to decrease by the same ratio as emission standards. Additionally, distinction is made between emissions during the thermally stabilised emission control system operation and emissions during the cold-start phase, where reductions are mainly due to the decreasing light-off time of future catalyst technologies. In case of diesel vehicles, some of the emission standards, such as 1993 CO, did not represent the actual emission level of vehicles at the time. Therefore, reductions brought over the 1993 emission factor are based both on relevant emission standards reductions and on technological considerations. In a second step, the derived emission factors are corrected to account for vehicle age and fuel quality effects. Vehicle age is introduced in the calculation via emission degradation functions of the total vehicle-accumulated mileage. The impact of improved fuels on the emissions of existing and future vehicle technologies is also modelled by applying correction factors depending on fuel specifications. A number of examples are given by applying the methodology on forecast activity data for different European countries to illustrate the expected effects of future vehicle technologies and fuels.     

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.     

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.     

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.     

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.     

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

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

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

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

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

Emission Factors for High-Emitting Vehicles Based on On-Road Measurements of Individual Vehicle Exhaust with a Mobile Measurement Platform

ABSTRACT

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 μm (PM_2.5) 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), PM_2.5, 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 PM_2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM_2.5, and NO_x tended to cluster among the same vehicles.

IMPLICATIONS This study presents the characterization of on-road vehicle emissions in Wilmington, CA, by sampling individual vehicle plumes. Approximately 5% of the vehicles were high emitters, whose emissions were more than 5 times the fleet-average values. These high emitters were responsible for 30% and more than 50% of the average emission factors of LDGVs and HDDVs, respectively. It is likely that as the overall fleet becomes cleaner due to more stringent regulations, a small fraction of the fleet may contribute a growing and disproportionate share of the overall emissions. Therefore, long-term changes in on-road emissions need to be monitored.     

A Fuel-Based Motor Vehicle Emission Inventory

Abstract

A fuel-based methodology for calculating motor vehicle emission inventories is presented. In the fuel-based method, emission factors are normalized to fuel consumption and expressed as grams of pollutant emitted per gallon of gasoline burned. Fleet-average emission factors are calculated from the measured on-road emissions of a large, random sample of vehicles. Gasoline use is known at the state level from sales tax data, and may be disaggregated to individual air basins. A fuel-based motor vehicle CO inventory was calculated for the South Coast Air Basin in California for summer 1991. Emission factors were calculated from remote sensing measurements of more than 70,000 in-use vehicles. Stabilized exhaust emissions of CO were estimated to be 4400 tons/day for cars and 1500 tons/day for light-duty and medium- duty trucks, with an estimated uncertainty of ±20% for cars and ±30% for trucks. Total motor vehicle CO emissions, including incremental start emissions and emissions from heavy-duty vehicles were estimated to be 7900 tons/day. Fuelbased inventory estimates were greater than those of California's MVEI 7F model by factors of 2.2 for cars and 2.6 for trucks. A draft version of California's MVEI 7G model, which includes increased contributions from high-emitting vehicles and off-cycle emissions, predicted CO emissions which closely matched the fuel-based inventory. An analysis of CO mass emissions as a function of vehicle age revealed that cars and trucks which were ten or more years old were responsible for 58% of stabilized exhaust CO emissions from all cars and trucks.