Quantification of self pollution from two diesel school buses using three independent methods

We monitored two Seattle school buses to quantify the buses’ self pollution using the dual tracers (DT), lead vehicle (LV), and chemical mass balance (CMB) methods. Each bus drove along a residential route simulating stops, with windows closed or open. Particulate matter (PM) and its constituents were monitored in the bus and from a LV. We collected source samples from the tailpipe and crankcase emissions using an on-board dilution tunnel. Concentrations of PM₁, ultrafine particle counts, elemental and organic carbon (EC/OC) were higher on the bus than the LV. The DT method estimated that the tailpipe and the crankcase emissions contributed 1.1 and 6.8 μg m^?3 of PM_2.5 inside the bus, respectively, with significantly higher crankcase self pollution (SP) when windows were closed. Approximately two-thirds of in-cabin PM_2.5 originated from background sources. Using the LV approach, SP estimates from the EC and the active personal DataRAM (pDR) measurements correlated well with the DT estimates for tailpipe and crankcase emissions, respectively, although both measurements need further calibration for accurate quantification. CMB results overestimated SP from the DT method but confirmed crankcase emissions as the major SP source. We confirmed buses’ SP using three independent methods and quantified crankcase emissions as the dominant contributor.     

Measuring in-cabin school bus tailpipe and crankcase PM2.5: a new dual tracer method

Exposures of occupants in school buses to on-road vehicle emissions, including emissions from the bus itself, can be substantially greater than those in outdoor settings. A dual tracer method was developed and applied to two school buses in Seattle in 2005 to quantify in-cabin fine particulate matter (PM2.5) concentrations attributable to the buses' diesel engine tailpipe (DPMtp) and crankcase vent (PMck) emissions. The new method avoids the problem of differentiating bus emissions from chemically identical emissions of other vehicles by using a fuel-based organometallic iridium tracer for engine exhaust and by adding deuterated hexatriacontane to engine oil. Source testing results showed consistent PM:tracer ratios for the primary tracer for each type of emissions. Comparisons of the PM:tracer ratios indicated that there was a small amount of unburned lubricating oil emitted from the tailpipe; however, virtually no diesel fuel combustion products were found in the crankcase emissions. For the limited testing conducted here, although PMck emission rates (averages of 0.028 and 0.099 g/km for the two buses) were lower than those from the tailpipe (0.18 and 0.14 g/km), in-cabin PMck concentrations averaging 6.8 microg/m3 were higher than DPMtp (0.91 microg/m3 average). In-cabin DPMtp and PMck concentrations were significantly higher with bus windows closed (1.4 and 12 microg/m3, respectively) as compared with open (0.44 and 1.3 microg/m3, respectively). For comparison, average closed- and open-window in-cabin total PM2.5 concentrations were 26 and 12 microg/m3, respectively. Despite the relatively short in-cabin sampling times, very high sensitivities were achieved, with detection limits of 0.002 microg/m3 for DPMtp and 0.05 microg/m3 for PMck.     

Relative importance of school bus-related microenvironments to children's pollutant exposure

Real-time concentrations of black carbon, particle-bound polycyclic aromatic hydrocarbons, nitrogen dioxide, and fine particulate counts, as well as integrated and real-time fine particulate matter (PM2.5) mass concentrations were measured inside school buses during long commutes on Los Angeles Unified School District bus routes, at bus stops along the routes, at the bus loading/unloading zone in front of the selected school, and at nearby urban "background" sites. Across all of the pollutants, mean concentrations during bus commutes were higher than in any other microenvironment. Mean exposures (mean concentration times time spent in a particular microenvironment) in bus commutes were between 50 and 200 times greater than those for the loading/unloading microenvironment, and 20-40 times higher than those for the bus stops, depending on the pollutant. Although the analyzed school bus commutes represented only 10% of a child's day, on average they contributed one-third of a child's 24-hr overall black carbon exposure during a school day. For species closely related to vehicle exhaust, the within- cabin exposures were generally dominated by the effect of surrounding traffic when windows were open and by the bus's own exhaust when windows were closed. Low-emitting buses generally exhibited high concentrations only when traveling behind a diesel vehicle, whereas high-emitting buses exhibited high concentrations both when following other diesel vehicles and when idling without another diesel vehicle in front of the bus. To reduce school bus commute exposures, we recommend minimizing commute times, avoiding caravanning with other school buses, using the cleanest buses for the longest bus routes, maintaining conventional diesel buses to eliminate visible emissions, and transitioning to cleaner fuels and advanced particulate control technologies as soon as possible.     

Relative Importance of School Bus-Related Microenvironments to Children’s Pollutant Exposure

Abstract

Real‐time concentrations of black carbon, particle‐bound polycyclic aromatic hydrocarbons, nitrogen dioxide, and fine particulate counts, as well as integrated and real‐time fine particulate matter (PM_2.5) mass concentrations were measured inside school buses during long commutes on Los Angeles Unified School District bus routes, at bus stops along the routes, at the bus loading/unloading zone in front of the selected school, and at nearby urban “background” sites. Across all of the pollutants, mean concentrations during bus commutes were higher than in any other microenvironment. Mean exposures (mean concentration times time spent in a particular microenvironment) in bus commutes were between 50 and 200 times greater than those for the loading/unloading microenvironment, and 20–40 times higher than those for the bus stops, depending on the pollutant. Although the analyzed school bus commutes represented only 10% of a child’s day, on average they contributed one‐third of a child’s 24‐hr overall black carbon exposure during a school day. For species closely related to vehicle exhaust, the within‐cabin exposures were generally dominated by the effect of surrounding traffic when windows were open and by the bus’s own exhaust when windows were closed. Low‐emitting buses generally exhibited high concentrations only when traveling behind a diesel vehicle, whereas high‐emitting buses exhibited high concentrations both when following other diesel vehicles and when idling without another diesel vehicle in front of the bus. To reduce school bus commute exposures, we recommend minimizing commute times, avoiding caravanning with other school buses, using the cleanest buses for the longest bus routes, maintaining conventional diesel buses to eliminate visible emissions, and transitioning to cleaner fuels and advanced particulate control technologies as soon as possible.     

Prediction of PM10 concentrations at urban traffic intersections using semi-empirical box modelling with instantaneous velocity and acceleration

At urban traffic intersections, vehicles frequently stop with idling engines during the red-light period and speed up rapidly during the green-light period. The changes of driving patterns (i.e., idle, acceleration, deceleration and cruising patterns) generally produce uncertain emission. Additionally, the movement of pedestrians and the influence of wind further result in the random dispersion of pollutants. It is, therefore, too complex to simulate the effects of such dynamics on the resulting emission using conventional deterministic causal models.For this reason, a modified semi-empirical box model for predicting the PM₁₀ concentrations on roadsides is proposed in this paper. The model constitutes three parts, i.e., traffic, emission and dispersion components. The traffic component is developed using a generalized force traffic model to obtain the instantaneous velocity and acceleration when vehicles move through intersections. Hence the distribution of vehicle emission in street canyon during the green-light period is calculated. Then the dispersion component is investigated using a semi-empirical box model combining average wind speed, box height and background concentrations. With these considerations, the proposed model is applied and evaluated using measured data at a busy traffic intersection in Mong Kok, Hong Kong. In order to test the performance of the model, two situations, i.e., the data sets within a sunny day and between two sunny days, were selected to examine the model performance. The predicted values are generally well coincident with the observed data during different time slots except several values are overestimated or underestimated. Moreover, two types of vehicles, i.e., buses and petrol cars, are separately taken into account in the study. Buses are verified to contribute most to the emission in street canyons, which may be useful in evaluating the impact of vehicle emissions on the ambient air quality when there is a significant change in a specific vehicular population.     

In-use fuel economy of hybrid-electric school buses in Iowa

Although it is much safer and more fuel-efficient to transport children to school in buses than in private vehicles, school buses in the United States still consume 822 million gal of diesel fuel annually, and school transportation costs can account for a significant portion of resource-constrained school district budgets. Additionally, children in diesel-powered school buses may be exposed to higher levels of particulates and other pollutants than children in cars. One solution to emission and fuel concerns is use of hybrid-electric school buses, which have the potential to reduce emissions and overall lifecycle costs compared with conventional diesel buses. Hybrid-electric technologies are available in the passenger vehicle market as well as the transit bus market and have a track record indicating fuel economy and emissions benefits. This paper summarizes the results of an in-use fuel economy evaluation for two plug-in hybrid school buses deployed in two different school districts in Iowa. Each school district selected a control bus with a route similar to that of the hybrid bus. Odometer readings, fuel consumption, and maintenance needs were recorded for each bus. The buses were deployed in 2008 and data were collected through May 2010. Fuel consumption was calculated for each school district. In Nevada, IA, the overall average fuel economy was 8.23 mpg for the hybrid and 6.35 mpg for the control bus. In Sigourney, IA, the overall average fuel economy was 8.94 mpg for the hybrid and 6.42 mpg for the control bus. The fuel consumption data were compared for the hybrid and control buses using a Wilcoxon signed rank test. Results indicate that fuel economy for the Nevada hybrid bus was 29.6% better than for the Nevada control bus, and fuel economy for the Sigourney hybrid bus was 39.2% higher than for the Sigourney control bus. Both differences were statistically significant.     

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.     

Carbon monoxide modeling from transportation sources.

Street canyon module and gaussian line source module of a regional-scale dispersion model Indic Airviro were used to simulate ambient carbon monoxide (CO) concentrations due to traffic flow at two roadside monitoring locations in Singapore. The fleet average emission factors for each vehicle category was estimated from US EPA MOBILE 5 A guidelines as a function of speed, vehicle deterioration rates and model years. 1-h CO concentrations and worst case 8-h levels have been simulated and compared with measured readings. This study used model-simulated rooftop concentration levels from non-localized sources as background levels at the two sites. The resulting CO concentrations correlate well with actual measured levels and provide a unique approach to predict the impact of CO from transportation.     

Soil Suspension/Dispersion Modeling Methods for Estimating Health-Based Soil Cleanup Levels of Hexavalent Chromium at Chromite Ore Processing Residue Sites

Abstract

The primary health concern associated with exposures to chromite ore processing residue (COPR)-affected soils is inhalation of hexavalent chromium [Cr(VI)] particulates. Site-specific soil alternative remediation standards (ARSs) are set using soil suspension and dispersion models to be protective of the theoretical excess cancer risk associated with inhalation of soil suspended by vehicle traffic and wind. The purpose of this study was to update a previous model comparison study that identified the 1995 AP-42 particulate emission model for vehicle traffic over un-paved roads and the Fugitive Dust Model (FDM) as the most appropriate model combination for estimating site-specific ARSs. Because the AP-42 model has been revised, we have updated our past evaluation. Specifically, the 2006 AP-42 particulate emissions model; the Industrial Source Complex–Short Term model, version 3 (ISCST3); and the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) air dispersion models were evaluated, and the results were compared with those from the previously used modeling approaches. Two sites with and two sites without vehicle traffic were evaluated to determine if wind erosion is a significant source of emissions. For the two sites with vehicle traffic, both FDM and ISCST3 produced total suspended particulate (TSP) estimates that were, on average, within a factor of 2 of measured; whereas AERMOD produced estimates that were as much as 5-fold higher than measured. In general, the estimated TSP concentrations for FDM were higher than those for ISCST3. For airborne Cr(VI), the ISCST3 model produced estimates that were only 2- to 8-fold of the measured concentrations, and both FDM and AERMOD estimated airborne Cr(VI) concentrations that were approximately 4- to 14-fold higher than measured. Results using the 1995 AP-42 model were closer to measured than those from the 2006 AP-42 model. Wind erosion was an insignificant contributor to particulate emissions at COPR sites.     

Soil suspension/dispersion modeling methods for estimating health-based soil cleanup levels of hexavalent chromium at chromite ore processing residue sites

The primary health concern associated with exposures to chromite ore processing residue (COPR)-affected soils is inhalation of hexavalent chromium [Cr(VI)] particulates. Site-specific soil alternative remediation standards (ARSs) are set using soil suspension and dispersion models to be protective of the theoretical excess cancer risk associated with inhalation of soil suspended by vehicle traffic and wind. The purpose of this study was to update a previous model comparison study that identified the 1995 AP-42 particulate emission model for vehicle traffic over unpaved roads and the Fugitive Dust Model (FDM) as the most appropriate model combination for estimating site-specific ARSs. Because the AP-42 model has been revised, we have updated our past evaluation. Specifically, the 2006 AP-42 particulate emissions model; the Industrial Source Complex-Short Term model, version 3 (ISCST3); and the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) air dispersion models were evaluated, and the results were compared with those from the previously used modeling approaches. Two sites with and two sites without vehicle traffic were evaluated to determine if wind erosion is a significant source of emissions. For the two sites with vehicle traffic, both FDM and ISCST3 produced total suspended particulate (TSP) estimates that were, on average, within a factor of 2 of measured; whereas AERMOD produced estimates that were as much as 5-fold higher than measured. In general, the estimated TSP concentrations for FDM were higher than those for ISCST3. For airborne Cr(VI), the ISCST3 model produced estimates that were only 2- to 8-fold of the measured concentrations, and both FDM and AERMOD estimated airborne Cr(VI) concentrations that were approximately 4- to 14-fold higher than measured. Results using the 1995 AP-42 model were closer to measured than those from the 2006 AP-42 model. Wind erosion was an insignificant contributor to particulate emissions at COPR sites.     

Modeling the impacts of traffic emissions on air toxics concentrations near roadways

The dispersion formulation incorporated in the U.S. Environmental Protection Agency's AERMOD regulatory dispersion model is used to estimate the contribution of traffic-generated emissions of select VOCs – benzene, 1,3-butadiene, toluene – to ambient air concentrations at downwind receptors ranging from 10-m to 100-m from the edge of a major highway in Raleigh, North Carolina. The contributions are computed using the following steps: 1) Evaluate dispersion model estimates with 10-min averaged NO data measured at 7 m and 17 m from the edge of the road during a field study conducted in August, 2006; this step determines the uncertainty in model estimates. 2) Use dispersion model estimates and their uncertainties, determined in step 1, to construct pseudo-observations. 3) Fit pseudo-observations to actual observations of VOC concentrations measured during five periods of the field study. This provides estimates of the contributions of traffic emissions to the VOC concentrations at the receptors located from 10 m to 100 m from the road. In addition, it provides estimates of emission factors and background concentrations of the VOCs, which are supported by independent estimates from motor vehicle emissions models and regional air quality measurements. The results presented in the paper demonstrate the suitability of the formulation in AERMOD for estimating concentrations associated with mobile source emissions near roadways. This paper also presents an evaluation of the key emissions and dispersion modeling inputs necessary for conducting assessments of local-scale impacts from traffic emissions.     

In-Use Fuel Economy of Hybrid-Electric School Buses in Iowa

ABSTRACT

Although it is much safer and more fuel-efficient to transport children to school in buses than in private vehicles, school buses in the United States still consume 822 million gal of diesel fuel annually, and school transportation costs can account for a significant portion of resource-constrained school district budgets. Additionally, children in diesel-powered school buses may be exposed to higher levels of particulates and other pollutants than children in cars. One solution to emission and fuel concerns is use of hybrid-electric school buses, which have the potential to reduce emissions and overall lifecycle costs compared with conventional diesel buses. Hybrid-electric technologies are available in the passenger vehicle market as well as the transit bus market and have a track record indicating fuel economy and emissions benefits. This paper summarizes the results of an in-use fuel economy evaluation for two plug-in hybrid school buses deployed in two different school districts in Iowa. Each school district selected a control bus with a route similar to that of the hybrid bus. Odometer readings, fuel consumption, and maintenance needs were recorded for each bus. The buses were deployed in 2008 and data were collected through May 2010. Fuel consumption was calculated for each school district. In Nevada, IA, the overall average fuel economy was 8.23 mpg for the hybrid and 6.35 mpg for the control bus. In Sigourney, IA, the overall average fuel economy was 8.94 mpg for the hybrid and 6.42 mpg for the control bus. The fuel consumption data were compared for the hybrid and control buses using a Wilcoxon signed rank test. Results indicate that fuel economy for the Nevada hybrid bus was 29.6% better than for the Nevada control bus, and fuel economy for the Sigourney hybrid bus was 39.2% higher than for the Sigourney control bus. Both differences were statistically significant.

IMPLICATIONS The results of the research presented in this paper can be readily used by school districts and policy-makers who are interested in purchasing hybrid school buses. Very little information about actual on-road fuel consumption or costs is available. Because the cost of a hybrid bus can be significantly more than the cost of a conventional bus, the information provided in this paper can be very useful for an agency to determine the costs and benefits of a hybrid bus. The information is also useful to researchers who are studying hybrid school and transit buses.     

大型城市客车加速模拟工况排放特性的实验研究

通过对258辆大型城市客车进行加速模拟工况排放测试,研究了城市客车的排放特性,比较了压缩天然气(CNG)车辆与汽油车辆的排放特性,分析了车辆车龄与排放的关系、发动机燃油供给方式与排放的关系,以及车辆总质量与排放的关系。研究结果表明：燃用CNG的车辆其CO、NOx排放较汽油低许多,尤其是CO,但HC排放较汽油高;电喷车辆的CO、NOx排放比化油器车低,但HC排放值高于化油器车;车龄增长,车辆的CO、NOx排放值增大,但HC变化不明显;车辆总质量增加,排放呈下降趋势。     

An evaluation of the estimation of road traffic emission factors from tracer studies

Road traffic emission factors (EFs) are one of the main sources of uncertainties in emission inventories; it is necessary to develop methods to reduce these uncertainties to manage air quality more efficiently. Recently an alternative method has been proposed to estimate the EFs. In that work the emission factors were estimated from a long term tracer study developed in Ho Chi Minh City (HCMC) Vietnam. A passive tracer was continuously emitted from a finite line source placed in one side of an urban street canyon. Simultaneously, the resulting tracer concentrations were monitored at the other side of the street. The results of this experiment were used to calculate the dispersion factors and afterwards, these dispersion factors were used to estimate the EFs. In this paper we use the Computational Fluids Dynamics (CFD) model WinMISKAM to critically evaluate the proposed methodology.In a first step, we use the results of the tracer study to validate the CFD model. Results show that the model is able to simulate quite well the tracer dispersion in most of the cases. The model is then used to evaluate the effect of varying the source configuration and to correct the EFs. A comparison with available studies shows that the corrected EFs are within the range of the EFs reported in other studies. Finally, the CFD model is used to find a source configuration that better represents the vehicle emissions and that may be used in future studies to estimate the EFs more accurately. Results show that a 200 m line placed in the center of the street would represent very well the vehicle emissions. This work shows that it is possible to accurately estimate the EFs from tracer studies.     

Authors’ Reply

ABSTRACT

Exposures of occupants in school buses to on-road vehicle emissions, including emissions from the bus itself, can be substantially greater than those in outdoor settings. A dual tracer method was developed and applied to two school buses in Seattle in 2005 to quantify in-cabin fine particulate matter (PM_2.5) concentrations attributable to the buses' diesel engine tailpipe (DPM_tp) and crankcase vent (PM_ck) emissions. The new method avoids the problem of differentiating bus emissions from chemically identical emissions of other vehicles by using a fuel-based organometallic iridium tracer for engine exhaust and by adding deuterated hexatriacontane to engine oil. Source testing results showed consistent PM:tracer ratios for the primary tracer for each type of emissions. Comparisons of the PM:tracer ratios indicated that there was a small amount of unburned lubricating oil emitted from the tailpipe; however, virtually no diesel fuel combustion products were found in the crankcase emissions. For the limited testing conducted here, although PM_ck emission rates (averages of 0.028 and 0.099 g/km for the two buses) were lower than those from the tailpipe (0.18 and 0.14 g/km), in-cabin PM_ck concentrations averaging 6.8 μg/m³ were higher than DPM_tp (0.91 μg/m³ average). In-cabin DPM_tp and PM_ck concentrations were significantly higher with bus windows closed (1.4 and 12 μg/m³, respectively) as compared with open (0.44 and 1.3 μg/m³, respectively). For comparison, average closed- and open-window in-cabin total PM_2.5 concentrations were 26 and 12 μg/m³, respectively. Despite the relatively short in-cabin sampling times, very high sensitivities were achieved, with detection limits of 0.002 μg/m³ for DPM_tp and 0.05 μg/m³ for PM_ck.

IMPLICATIONS PM_2.5 measurements in two Seattle school buses showed average concentrations of 26 and 12 μg/m³ with windows closed and open, respectively. Virtually all PM_2.5 was car bonaceous. Tracer measurements showed that bus self-pollution contributed approximately 50% of total PM_2.5 concentrations with windows closed and 15% with windows open, with over three-quarters of these contributions attributed to crankcase emissions. Maintaining ventilation in buses clearly reduces total PM_2.5 exposures and that from the buses' own emissions. The dual tracer method now offers researchers a new technique for explicit identification of single source contributions in settings with multiple sources of carbonaceous emissions.     

Sensitivity analysis and evaluation of microFacCO: a microscale motor vehicle emission factor model for CO emissions

This paper presents a sensitivity analysis of a microscale emission factor model (MicroFacCO) for predicting real-time site-specific motor vehicle CO emissions to input variables, as well as a limited field study evaluation of the model. The sensitivity analysis has shown that MicroFacCO emission estimates are very sensitive to vehicle fleet composition, speed, and ambient temperature. For the present U.S. traffic fleet, the CO emission rate (g/mi) is increased by more than 500% at 5 mph in comparison with a speed greater than 40 mph and by approximately 67% at ambient temperatures of 45 degrees F and > or = 95 degrees F in comparison with an ambient temperature of 75 degrees F. The input variable "emission failure standard rate" is more sensitive to estimating emission rates in the 1990s than in the 2000s. The estimation of emission rates is not very sensitive to relative humidity. MicroFacCO can also be applied to examine the contribution of emission rates per vehicle class and model year. The model evaluation is presented for tunnel studies at five locations. In general, this evaluation study found good agreement between the measured and the modeled emissions. These analyses and evaluations have identified the need for additional studies to update the high-speed (>35 mph) air conditioning (A/C) correction factor and to add effects due to road grades. MicroFacCO emission estimates are very sensitive to the emission standard failure rate. Therefore, the model performance can be greatly improved by using a local emission standard failure rate.     

Source apportionment of particulate matter (PM2.5) in an urban area using dispersion,receptor and inverse modelling

Air pollution emission inventories are the basis for air quality assessment and management strategies. The quality of the inventories is of great importance since these data are essential for air pollution impact assessments using dispersion models. In this study, the quality of the emission inventory for fine particulates (PM_2.5) is assessed: first, using the calculated source contributions from a receptor model; second, using source apportionment from a dispersion model; and third, by applying a simple inverse modelling technique which utilises multiple linear regression of the dispersion model source contributions together with the observed PM_2.5 concentrations. For the receptor modelling the chemical composition of PM_2.5 filter samples from a measurement campaign performed between January 2004 and April 2005 are analysed. Positive matrix factorisation is applied as the receptor model to detect and quantify the various source contributions. For the same observational period and site, dispersion model calculations using the Air Quality Management system, AirQUIS, are performed. The results identify significant differences between the dispersion and receptor model source apportionment, particularly for wood burning and traffic induced suspension. For wood burning the receptor model calculations are lower, by a factor of 0.54, but for the traffic induced suspension they are higher, by a factor of 7.1. Inverse modelling, based on regression of the dispersion model source contributions and the PM_2.5 concentrations, indicates similar discrepancies in the emissions inventory. In order to assess if the differences found at the one site are generally applicable throughout Oslo, the individual source category emissions are rescaled according to the receptor modelling results. These adjusted PM_2.5 concentrations are compared with measurements at four independent stations to evaluate the updated inventory. Statistical analysis shows improvement in the estimated concentrations for PM_2.5 at all sites. Similarly, inverse modelling is applied at these independent sites and this confirms the validity of the receptor model results.     

Black carbon and polycyclic aromatic hydrocarbon emissions from vehicles in the United States-Mexico border region: pilot study

The investigators developed a system to measure black carbon (BC) and particle-bound polycyclic aromatic hydrocarbon (PAH) emission factors during roadside sampling in four cities along the United States-Mexico border, Calexico/Mexicali and El Paso/Juarez. The measurement system included a photoacoustic analyzer for BC, a photoelectric aerosol sensor for particle-bound PAHs, and a carbon dioxide (CO2) analyzer. When a vehicle with measurable emissions passed the system probe, corresponding BC, PAH, and CO2 peaks were evident, and a fuel-based emission factor was estimated. A picture of each vehicle was also recorded with a digital camera. The advantage of this system, compared with other roadside methods, is the direct measurement of particulate matter components and limited interference from roadside dust. The study revealed some interesting trends: Mexican buses and all medium-duty trucks were more frequently identified as high emitters of BC and PAH than heavy-duty trucks or passenger vehicles. In addition, because of the high daily mileage of buses, they are good candidates for additional study. Mexican trucks and buses had higher average emission factors compared with U.S. trucks and buses, but the differences were not statistically significant. Few passenger vehicles had measurable BC and PAH emissions, although the highest emission factor came from an older model passenger vehicle licensed in Baja California.     

Fine urban and precursor emissions control for diesel urban transit buses

Particulate emission from diesel engines is one of the most important pollutants in urban areas. As a result, particulate emission control from urban bus diesel engines using particle filter technology is being evaluated at several locations in the US. A project entitled "Clean Diesel Air Quality Demonstration Program" has been initiated by the New York City Metropolitan Transit Authority (MTA) under the supervision of New York State Department of Environmental Conservation and with active participation from Johnson Matthey, Corning, Equilon, Environment Canada and RAD Energy. Under this program, several MTA transit buses with DDC Series 50 engines were equipped with Continuously Regenerating Technology (CRTTM) particulate filter systems and have been operated with ultra low sulfur diesel (<30 ppm S) in transit service in Manhattan since February 2000. These buses were evaluated over a 9-month period for durability and maintainability of the particulate filter. In addition, an extensive emissions testing program was carried out using transient cycles on a chassis dynamometer to evaluate the emissions reductions obtained with the particle filter. In this paper, the emissions testing data from the Clean Diesel Air Quality Demonstration Program are discussed in detail.