Characterization of in-use light-duty gasoline vehicle emissions by remote sensing in Beijing: impact of recent control measures

China's national government and Beijing city authorities have adopted additional control measures to reduce the negative impact of vehicle emissions on Beijing's air quality. An evaluation of the effectiveness of these measures may provide guidance for future vehicle emission control strategy development. In-use emissions from light-duty gasoline vehicles (LDGVs) were investigated at five sites in Beijing with remote sensing instrumentation. Distance-based mass emission factors were derived with fuel consumption modeled on real world data. The results show that the recently implemented aggressive control strategies are significantly reducing the emissions of on-road vehicles. Older vehicles are contributing substantially to the total fleet emissions. An earlier program to retrofit pre-Euro cars with three-way catalysts produced little emission reduction. The impact of model year and driving conditions on the average mass emission factors indicates that the durability of vehicles emission controls may be inadequate in Beijing.     

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.     

Developing a High-Resolution Vehicular Emission Inventory by Integrating an Emission Model and a Traffic Model: Part 2—A Case Study in Beijing

Abstract

A grid-based, bottom-up method has been proposed by combining a vehicle emission model and a travel demand model to develop a high-resolution vehicular emission inventory for Chinese cities. Beijing is used as a case study in which the focus is on fuel consumption and emissions from hot-stabilized activities of light-duty gasoline vehicles (LGVs) in 2005. The total quantity of emissions, emission intensity, and spatial distribution of emissions at 1- by 1-km resolution are presented and compared with results from other inventory methods commonly used in China. The results show that the total daily fuel consumption and vehicular emissions of carbon dioxide, carbon monoxide, hydrocarbons, and oxides of nitrogen from LGVs in the Beijing urban area in 2005 were 1.95 × 10⁷ L, 4.28 × 10⁴ t, 1.97 × 10³ t, 0.28 × 10³ t, and 0.14 × 10³ t, respectively. Vehicular fuel consumption and emissions show spatial variations that are consistent with the traffic characteristics. The grid-based inventory developed in this study reflects the influence of traffic conditions on vehicle emissions at the microscale and may be applied to evaluate the effectiveness of traffic-related measures on emission control in China.     

Characteristics of Real-World Vehicular Emissions in Chinese Cities

Abstract

On-board emission measurements were performed on 49 light-duty gasoline vehicles in seven cities of China. Vehicle-specific power mode distribution and emission characteristics were analyzed based on the data collected. The results of our study show that there were significant differences in different types of roads. The emission factors and fuel consumption rates on arterial roads and residential roads were approximately 1.4–2 times those on freeways. The carbon monoxide, hydrocarbon, and nitrogen oxides emission factors of Euro II vehicles were on average 86.2, 88.2, and 64.5% lower than those of carburetor vehicles, respectively. The new vehicle emission standards implemented in China had played an important role in reducing individual vehicle emissions. More comprehensive measures need to be considered to reduce the total amount of emissions from vehicles.     

Real-World Vehicle Emissions: A Summary of the Ninth Coordinating Research Council On-Road Vehicle Emissions Workshop

ABSTRACT

In April 1999, the Coordinating Research Council sponsored a workshop focusing on our understanding of real-world emissions from motor vehicles. This summary presents the latest information on in-use light- and heavy-duty vehicle tailpipe and evaporative emissions, the effects of fuels on emissions, field programs designed to understand the contribution of mobile sources to emission inventories, efforts to evaluate and improve mobile source emission models, progress of vehicle inspection/ maintenance programs, and topics for future research. While significant progress has been made in understanding in-use vehicle emissions, further improvements are necessary. Moreover, the impact of current and future changes in emission control technologies and control programs will have to be monitored for effectiveness and incorporated into the emission factor models.     

Modeling In-Use Vehicle Emissions and the Effects of Inspection and Maintenance Programs

Different ways for modeling the impact of vehicle emission inspection and maintenance programs on fleet hydrocarbon emissions are examined. A dynamic model is developed for forecasting fleet emissions in which individual vehicle performance is modeled as a stochastic process and vehicle emissions are tracked over time. Emissions inspection and repair are incorporated into the model, allowing for the stochastic aspects of both testing and repair. This model is compared to EPA’s model for evaluating the impact of vehicle emissions inspection and maintenance. We find that the way vehicle emission equipment deterioration overtime is modeled is important for forecasting emissions from the fleet and for assessing the success of inspection and maintenance programs. For inspection programs, we find that factors such as the proportion of vehicles tested, and repair effectiveness and duration have the greatest impact on emission reductions. The ability of different emission testing regimes to identify polluting vehicles has less impact on a program’s overall potential for emissions reduction. Policy recommendations for I&M testing and predictions of emission reduction credits from these tests will depend in important ways on the methods used in the underlying emissions models.     

The impact of transportation control measures on emission reductions during the 2008 Olympic Games in Beijing,China

Traffic congestion and air pollution were two major challenges for the planners of the 2008 Olympic Games in Beijing. The Beijing municipal government implemented a package of temporary transportation control measures during the event. In this paper, we report the results of a recent research project that investigated the effects of these measures on urban motor vehicle emissions in Beijing. Bottom–up methodology has been used to develop grid-based emission inventories with micro-scale vehicle activities and speed-dependent emission factors. The urban traffic emissions of volatile organic compounds (VOC), carbon monoxide (CO), nitrogen oxides (NO_x) and particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀) during the 2008 Olympics were reduced by 55.5%, 56.8%, 45.7% and 51.6%, respectively, as compared to the grid-based emission inventory before the Olympics. Emission intensity was derived from curbside air quality monitoring at the North 4th Ring Road site, located about 7 km from the National Stadium. Comparison between the emission intensity before and during the 2008 Olympics shows a reduction of 44.5% and 49.0% in daily CO and NO_x emission from motor vehicles. The results suggest that reasonable traffic system improvement strategies along with vehicle technology improvements can contribute to controlling total motor vehicle emissions in Beijing after the Olympic Games.     

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.     

Evaluating Speed Differences between Passenger Vehicles and Heavy Trucks for Transportation-Related Emissions Modeling

Abstract

Heavy-duty trucks make up only 3% of the on-road vehicle fleet, yet they account for >7% of vehicle miles traveled in the United States. They also contribute a significant proportion of regulated ambient emissions. Heavy vehicles emit emissions at different rates than passenger vehicles. They may also behave differently on‐road, yet may be treated similarly to passenger vehicles in emissions modeling. Input variables to the MOBILE software, such as average vehicle speed, are typically specified the same for heavy trucks as for passenger vehicles. Although not frequently considered in modeling emissions, speed differences between passenger vehicles and heavy trucks may influence emissions, because emission rates are correlated to average speed. Differences were evaluated by collecting average and spot speeds for heavy trucks and passenger vehicles on arterials and spot speeds on freeways in Des Moines, IA, and Minneapolis/St. Paul, MN. Speeds were compared by study site. Space mean speeds for heavy trucks were lower than passenger vehicle speeds for all of the arterials with differences ranging from 0.8 to 19 mph. Spot speeds for heavy trucks were also lower at all of the arterial and freeway locations with differences ranging from 0.8 to 6.1 mph. The impact that differences in on‐road speeds had on emissions was also evaluated using MOBILE version 6.2. Misspecification of average truck speed is the most significant at lower and higher speed ranges.     

Airshed Model Evaluation of Reactivity Adjustment Factors Calculated with the Maximum Incremental Reactivity Scale for Transitional-Low Emission Vehicles

Abstract

The California Air Resources Board recently adopted regulations for light- and medium-duty vehicles that require reductions in the ozone-forming potential or “reactivity,” rather than the mass, of nonmethane organic gas (NMOG) emissions. The regulations allow sale of all alternatively fueled vehicles (AFVs) that meet NMOG exhaust emission standards equivalent in reactivity to those set for vehicles fueled with conventional gasoline. Reactivity adjustment factors (RAFs), the ratio of the reactivity (per gram) of the AFV exhaust to that of the conventionally fueled vehicle (CFV), are used to correct the stringent exhaust emission standards. Complete chemical speciation of the exhaust and conversion of each NMOG species to an appropriate mass of ozone using the maximum incremental reactivity (MIR) scale of Carter determines the RAF. The MIR approach defines reactivity where NMOG control is the most effective strategy in reducing ozone concentrations, and assumes it is not important to define reactivity at other conditions, i.e., where NO_x is the limiting precursor.

This study used the Carnegie/California Institute of Technology airshed model to evaluate whether the RAF-adjusted AFV emissions result in ozone impacts equivalent to those of CFV emissions. A matrix of two ozone episodes in the South Coast Air Basin (SoCAB) of California, two base emission inventories, and exhaust emissions from three alternative fuels that meet the first level of the low emission vehicle standards bounds the expected range of conditions. Although very good agreement was found previously for individual NMOG species,² this study noted deviations of up to ±15 percent from the equal ozone impacts for any vehicle/fuel combination required by the California regulations. These deviations appear to be attributable to differences in spatial and temporal patterns of emissions between vehicle fleets, rather than a problem with the MIR approach. The first formally adopted RAF, a value of 0.41 for 85 percent methanol/15 percent gasoline-fueled vehicles, includes a 10 percent increase based on the airshed modeling. The correction to the RAF is different for other fuels and may be different for air basins other than the SoCAB.     

Longitudinal emissions evaluation of mixed (cooperative) adaptive cruise control traffic flow and its relationship with stability

ABSTRACT

Cooperative adaptive cruise control (CACC) vehicles need vehicle-to-vehicle (V2 V) communication to achieve CACC function. When a CACC vehicle follows a manual-driven vehicle (MDV) without V2 V communication, it needs degenerate to adaptive cruise control (ACC). By using real experiments, California PATH program indicated that ACC vehicles are apt to be unstable, which may have negative influence on fuel consumption and traffic emissions. Hence, this paper studies the impacts of the mixed CACC-MDV traffic on fuel consumption and emissions, by taking into consideration partial degenerations from stable CACC vehicles to unstable ACC vehicles. To deal with this, microscopic simulations were adopted by using car-following models. Then, an appropriate emission model was used for evaluating the emission impacts under different CACC market penetration rates (MPRs). In order to obtain reliable evaluation results, the models validated by PATH program using real experimental data were employed as the CACC and ACC car-following models. In addition, we also analytically investigated stability of the mixed traffic flow under different CACC MPRs, in order to explore its relationship with the emission impacts. The results show that the fuel consumption and emissions firstly increase and then decrease with the increase of the CACC MPR. This means the mixed traffic under some ranges of CACC MPRs will produce more fuel consumption and emissions, compared with the full MDVs traffic. It indicates that stability situations of the mixed traffic qualitatively influence the impact trend of CACC MPRs on fuel consumption and emissions. Then, V2 V communication equipments on MDVs are not only encouraging but also essential to avoid the deterioration of fuel consumption and emissions of the mixed traffic flow.     

Improved Version of Anion-exchange Resin-based Desulfurization Process for Alkali Metal Sulfates

Abstract

Vehicle gaseous emissions (NO, CO, CO₂, and hydrocarbon [HC]) and driver’s particle exposures (particulate matter <1 μm [PM₁], <2.5 μm [PM_2.5], and<10 μm [PM₁₀]) were measured using a mobile laboratory to follow a wide variety of vehicles during very heavy traffic congestion in Macao, Special Administrative Region, People’s Republic of China, an urban area having one of the highest population densities in the world. The measurements were taken with high time resolution so that fluctuations in the emissions can be seen readily during vehicle acceleration, cruising, deceleration, and idling. The tests were conducted in close proximity to the vehicles, with the inlet of a five-gas analyzer mounted on the front bumper of the mobile laboratory, and the distance between the vehicles was usually within several meters. To measure the driver’s particle exposures, the inlets of the particle analyzers were mounted at the height of the driver’s breathing position in the mobile laboratory, with the driver’s window open. A total of 178 and 113 vehicles were followed individually to determine the gaseous emission factor and the driver’s particle exposures, respectively, for motorcycle, passenger car, taxi, truck, and bus. The gaseous emission factors were used to model the roadside air quality, and good correlations between the modeled and monitored CO, NO₂, and nitrogen oxide (NO_x) verified the reliability of the experiments. Compared with petrol passenger cars and petrol trucks, diesel taxies and diesel trucks emitted less CO but more NO_x. The impact of urban canyons is shown to cause a significant increase in the PM₁ peak. The background concentrations contributed a significant amount of the driver’s particle exposures.     

Diagnosis and Repair of Excessively Emitting Vehicles

Abstract

Between 1991 and 1993, the California Air Resources Board (CARB) selected 1,115 vehicles from all across the South Coast Air Basin to evaluate the effectiveness of the state's existing biennial motor vehicle Inspection/Maintenance (I/M) or Smog Check program. The vehicles were chosen to represent the population of cars that "should fail" properly conducted inspections. The cars were emissions-tested at baseline and sent undercover to licensed I/M garages throughout the basin. Federal Test Procedure (FIT) emissions were measured again for cars that were repaired. In the second year of the study, the vehicles that could be reproduced were tested at the CARB to measure the level of emissions deterioration and any underhood changes in emission control systems. In the third year, the cycle of emissions testing and undercover inspections and repair was repeated.

This paper uses data from the study to explore the relationships between super emitting vehicles (defined here as vehicles whose emissions are several times California certification standards) and diagnostics and repair of their underhood emissions control systems. Also examined is their appearance and improvement during a three-year period that includes two cycles of inspection and repair. An important finding is that once normalized to account for differences in certification standards, the super emitting vehicles do not have a unique signature in terms of their underhood emission control system failure modes, mileage, or age, when compared with the average vehicle expected to fail a Smog Check inspection. However, they are more likely to be identified, diagnosed, and repaired effectively than other vehicles, although they continue to reappear over time.     

Developing a high-resolution vehicular emission inventory by integrating an emission model and a traffic model: Part 2--A case study in Beijing

A grid-based, bottom-up method has been proposed by combining a vehicle emission model and a travel demand model to develop a high-resolution vehicular emission inventory for Chinese cities. Beijing is used as a case study in which the focus is on fuel consumption and emissions from hot-stabilized activities of light-duty gasoline vehicles (LGVs) in 2005. The total quantity of emissions, emission intensity, and spatial distribution of emissions at 1- by 1-km resolution are presented and compared with results from other inventory methods commonly used in China. The results show that the total daily fuel consumption and vehicular emissions of carbon dioxide, carbon monoxide, hydrocarbons, and oxides of nitrogen from LGVs in the Beijing urban area in 2005 were 1.95 x 10(7) L, 4.28 x 10(4) t, 1.97 x 10(3) t, 0.28 x 10(3) t, and 0.14 x 10(3) t, respectively. Vehicular fuel consumption and emissions show spatial variations that are consistent with the traffic characteristics. The grid-based inventory developed in this study reflects the influence of traffic conditions on vehicle emissions at the microscale and may be applied to evaluate the effectiveness of traffic-related measures on emission control in China.     

Effects of Fuel Type,Driving Cycle,and Emission Status on In-Use Vehicle Exhaust Reactivity

ABSTRACT

The introduction of reformulated gasolines significantly reduced exhaust hydrocarbon (HC) mass emissions, but few data are available concerning how these new fuels affect exhaust reactivity. Similarly, while it is well established that high-emitting vehicles contribute a significant portion of total mobile source HC mass emissions, it is also important to evaluate the exhaust reactivity from these vehicles. The objective of this study was to evaluate the relative influence on in-use vehicle exhaust reactivity of three critical factors: fuel, driving cycle, and vehicle emission status. Nineteen in-use vehicles were tested with seven randomly assigned fuel types and two driving cycles: the Federal Test Procedure (FTP) and the Unified Cycle (UC). Total exhaust reactivity was not statistically different between the FTP and UC cycles but was significantly affected by fuel type. On average, the exhaust reactivity for California Phase 2 fuel was the lowest (16 % below the highest fuel type) among the seven fuels tested for cold start emissions. The average exhaust reactivity for high-emitting vehicles was significantly higher for hot stabilized (11%) and hot start (15%) emissions than for low-emitting vehicles. The exhaust reactivities for the FTP and UC cycles for light-end HCs and carbonyls were significantly different for the hot stabilized mode. There was a significant fuel effect on the mean specific reactivity (SR) for the mid-range HCs, but not for light-end HCs or carbonyls, while vehicle emission status affected the mean SR for all three HC compound classes.     

Multispecies remote sensing measurements of vehicle emissions on Sherman Way in Van Nuys,California

As part of the 2010 Van Nuys tunnel study, researchers from the University of Denver measured on-road fuel-specific light-duty vehicle emissions from nearly 13,000 vehicles on Sherman Way (0.4 miles west of the tunnel) in Van Nuys, California, with its multispecies Fuel Efficiency Automobile Test (FEAT) remote sensor a week ahead of the tunnel measurements. The remote sensing mean gram per kilogram carbon monoxide (CO), hydrocarbon (HC), and oxide of nitrogen (NO_x) measurements are 8.9% lower, 41% higher, and 24% higher than the tunnel measurements, respectively. The remote sensing CO/NO_x and HC/NO_x mass ratios are 28% lower and 20% higher than the comparable tunnel ratios. Comparisons with the historical tunnel measurements show large reductions in CO, HC, and NO_x over the past 23 yr, but little change in the HC/NO_x mass ratio since 1995. The fleet CO and HC emissions are increasingly dominated by a few gross emitters, with more than a third of the total emissions being contributed by less than 1% of the fleet. An example of this is a 1995 vehicle measured three times with an average HC emission of 419 g/kg fuel (two-stroke snowmobiles average 475 g/kg fuel), responsible for 4% of the total HC emissions. The 2008 economic downturn dramatically reduced the number of new vehicles entering the fleet, leading to an age increase (>1 model year) of the Sherman Way fleet that has increased the fleet's ammonia (NH₃) emissions. The mean NH₃ levels appear little changed from previous measurements collected in the Van Nuys tunnel in 1993. Comparisons between weekday and weekend data show few fleet differences, although the fraction of light-duty diesel vehicles decreased from the weekday (1.7%) to Saturday (1.2%) and Sunday (0.6%).

Implications: On-road remote sensing emission measurements of light-duty vehicles on Sherman Way in Van Nuys, California, show large historical emission reductions for CO and HC emissions despite an older fleet arising from the 2008 economic downturn. Fleet CO and HC emissions are increasingly dominated by a few gross emitters, with a single 1995 vehicle measured being responsible for 4% of the entire fleet's HC emissions. Finding and repairing and/or scrapping as little as 2% of the fleet would reduce on-road tailpipe emissions by as much as 50%. Ammonia emissions have locally increased with the increasing fleet age.     

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.     

Real-World Vehicle Emissions: A Summary of the Tenth Coordinating Research Council On-Road Vehicle Emissions Workshop

ABSTRACT

The Coordinating Research Council (CRC) held its tenth workshop in March 2000, focusing on results from the most recent real-world vehicle emissions research. In this paper, we summarize the presentations from researchers who are engaged in improving our understanding of the contribution of mobile sources to emission inventories. Participants in the workshop discussed efforts to improve mobile source emission models and emission inventories, results from gas- and particle-phase emissions studies from spark-ignition and diesel-powered vehicles, new methods for measuring mobile source emissions, improvements in vehicle emission control systems (ECSs), and evaluation of motor vehicle inspection/maintenance (I/M) programs, as well as topics for future research.     

The Formation of Mg3Ca(S04)4 during the Sulfation Reaction of Dolomite

Abstract

Inspection and maintenance programs for motor vehicles in the United States increasingly use loaded mode mass emissions testing (IM240). A method was developed to predict mass emission rates and mass emission changes, particularly from repair benefits, using a low-cost, portable four-gas non-dispersive infrared (NDIR) vehicle exhaust gas analyzer. A single vehicle was tested several times with the analyzer while on the dynamometer and undergoing successive repairs. Excellent correlations for CO and HC were observed. Five vehicles were measured using an on-road driving loop before and after emissions-related repairs, while another three vehicles were tested with no repairs performed. The on-road concentration data used to guide the repair process were converted to grams per gallon; when divided by estimated miles per gallon, this gave grams per mile emissions for comparison to IM240. Correlation coefficients (r²) of 0.87 for CO and 0.76 for HC were achieved for the 13 tests. The linear correlations between IM240 and emissions measured by this method would allow repair facilities to perform a relatively inexpensive test for diagnostic purposes and to estimate repair effectiveness without the need for a dynamometer.     

Toxic Emissions from Mobile Sources: A Total Fuel-Cycle Analysis for Conventional and Alternative Fuel Vehicles

ABSTRACT

Mobile sources are among the largest contributors of four hazardous air pollutants—benzene, 1,3-butadiene, acetal-dehyde, and formaldehyde—in urban areas. At the same time, federal and state governments are promoting the use of alternative fuel vehicles as a means to curb local air pollution. As yet, the impact of this movement toward alternative fuels with respect to toxic emissions has not been well studied. The purpose of this paper is to compare toxic emissions from vehicles operating on a variety of fuels, including reformulated gasoline (RFG), natural gas, ethanol, methanol, liquid petroleum gas (LPG), and electricity. This study uses a version of Argonne National Laboratory's Greenhouse Gas, Regulated Emissions, and Energy Use in Transportation (GREET) model, appropriately modified to estimate toxic emissions. The GREET model conducts a total fuel-cycle analysis that calculates emissions from both downstream (e.g., operation of the vehicle) and upstream (e.g., fuel production and distribution) stages of the fuel cycle. We find that almost all of the fuels studied reduce 1,3-buta-diene emissions compared with conventional gasoline (CG). However, the use of ethanol in E85 (fuel made with 85% ethanol) or RFG leads to increased acetaldehyde emissions, and the use of methanol, ethanol, and compressed natural gas (CNG) may result in increased formaldehyde emissions. When the modeling results for the four air toxics are considered together with their cancer risk factors, all the fuels and vehicle technologies show air toxic emission reduction benefits.