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

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

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.     

Effects of improved spatial and temporal modeling of on-road vehicle emissions

Numerous emission and air quality modeling studies have suggested the need to accurately characterize the spatial and temporal variations in on-road vehicle emissions. The purpose of this study was to quantify the impact that using detailed traffic activity data has on emission estimates used to model air quality impacts. The on-road vehicle emissions are estimated by multiplying the vehicle miles traveled (VMT) by the fleet-average emission factors determined by road link and hour of day. Changes in the fraction of VMT from heavy-duty diesel vehicles (HDDVs) can have a significant impact on estimated fleet-average emissions because the emission factors for HDDV nitrogen oxides (NOx) and particulate matter (PM) are much higher than those for light-duty gas vehicles (LDGVs). Through detailed road link-level on-road vehicle emission modeling, this work investigated two scenarios for better characterizing mobile source emissions: (1) improved spatial and temporal variation of vehicle type fractions, and (2) use of Motor Vehicle Emission Simulator (MOVES2010) instead of MOBILE6 exhaust emission factors. Emissions were estimated for the Detroit and Atlanta metropolitan areas for summer and winter episodes. The VMT mix scenario demonstrated the importance of better characterizing HDDV activity by time of day, day of week, and road type. More HDDV activity occurs on restricted access road types on weekdays and at nonpeak times, compared to light-duty vehicles, resulting in 5-15% higher NOx and PM emission rates during the weekdays and 15-40% lower rates on weekend days. Use of MOVES2010 exhaust emission factors resulted in increases of more than 50% in NOx and PM for both HDDVs and LDGVs, relative to MOBILE6. Because LDGV PM emissions have been shown to increase with lower temperatures, the most dramatic increase from MOBILE6 to MOVES2010 emission rates occurred for PM2.5 from LDGVs that increased 500% during colder wintertime conditions found in Detroit, the northernmost city modeled.     

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.     

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.     

The impact of municipal solid waste management on greenhouse gas emissions in the United States

Technological advancements, environmental regulations, and emphasis on resource conservation and recovery have greatly reduced the environmental impacts of municipal solid waste (MSW) management, including emissions of greenhouse gases (GHGs). This study was conducted using a life-cycle methodology to track changes in GHG emissions during the past 25 years from the management of MSW in the United States. For the baseline year of 1974, MSW management consisted of limited recycling, combustion without energy recovery, and landfilling without gas collection or control. This was compared with data for 1980, 1990, and 1997, accounting for changes in MSW quantity, composition, management practices, and technology. Over time, the United States has moved toward increased recycling, composting, combustion (with energy recovery) and landfilling with gas recovery, control, and utilization. These changes were accounted for with historical data on MSW composition, quantities, management practices, and technological changes. Included in the analysis were the benefits of materials recycling and energy recovery to the extent that these displace virgin raw materials and fossil fuel electricity production, respectively. Carbon sinks associated with MSW management also were addressed. The results indicate that the MSW management actions taken by U.S. communities have significantly reduced potential GHG emissions despite an almost 2-fold increase in waste generation. GHG emissions from MSW management were estimated to be 36 million metric tons carbon equivalents (MMTCE) in 1974 and 8 MMTCE in 1997. If MSW were being managed today as it was in 1974, GHG emissions would be approximately 60 MMTCE.     

Real-world in-use activity, fuel use, and emissions for nonroad construction vehicles: a case study for excavators

A study design was developed and demonstrated for deployment of a portable emission measurement system (PEMS) for excavators. Excavators are among the most commonly used vehicles in construction activities. The PEMS measured nitric oxide, carbon monoxide, hydrocarbons, carbon dioxide, and opacity-based particulate matter. Data collection, screening, processing, and analysis protocols were developed to assure data quality and to quantify variability in vehicle fuel consumption and emissions rates. The development of data collection procedures was based on securing the PEMS while avoiding disruption to normal vehicle operations. As a result of quality assurance, approximately 90% of the attempted measurements resulted in valid data. On the basis of field data collected for three excavators, an average of 50% of the total nitric oxide emissions was associated with 29% of the time of operation, during which the average engine speed and manifold absolute pressure were significantly higher than corresponding averages for all data. Mass per time emission rates during non-idle modes (i.e., moving and using bucket) were on average 7 times greater than for the idle mode. Differences in normalized average rates were influenced more by intercycle differences than intervehicle differences. This study demonstrates the importance of accounting for intercycle variability in real-world in-use emissions to develop more accurate emission inventories. The data collection and analysis methodology demonstrated here is recommended for application to more vehicles to better characterize real-world vehicle activity, fuel use, and emissions for nonroad construction equipment.     

Evaluating speed differences between passenger vehicles and heavy trucks for transportation-related emissions modeling

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.     

Future methane emissions from the heavy-duty natural gas transportation sector for stasis,high, medium,and low scenarios in 2035

Today’s heavy-duty natural gas–fueled fleet is estimated to represent less than 2% of the total fleet. However, over the next couple of decades, predictions are that the percentage could grow to represent as much as 50%. Although fueling switching to natural gas could provide a climate benefit relative to diesel fuel, the potential for emissions of methane (a potent greenhouse gas) from natural gas–fueled vehicles has been identified as a concern. Since today’s heavy-duty natural gas–fueled fleet penetration is low, today’s total fleet-wide emissions will be also be low regardless of per vehicle emissions. However, predicted growth could result in a significant quantity of methane emissions. To evaluate this potential and identify effective options for minimizing emissions, future growth scenarios of heavy-duty natural gas–fueled vehicles, and compressed natural gas and liquefied natural gas fueling stations that serve them, have been developed for 2035, when the populations could be significant. The scenarios rely on the most recent measurement campaign of the latest manufactured technology, equipment, and vehicles reported in a companion paper as well as projections of technology and practice advances. These “pump-to-wheels”(PTW) projections do not include methane emissions outside of the bounds of the vehicles and fuel stations themselves and should not be confused with a complete wells-to-wheels analysis. Stasis, high, medium, and low scenario PTW emissions projections for 2035 were 1.32%, 0.67%, 0.33%, and 0.15% of the fuel used. The scenarios highlight that a large emissions reductions could be realized with closed crankcase operation, improved best practices, and implementation of vent mitigation technologies. Recognition of the potential pathways for emissions reductions could further enhance the heavy-duty transportation sectors ability to reduce carbon emissions.

Implications: Newly collected pump-to-wheels methane emissions data for current natural gas technologies were combined with future market growth scenarios, estimated technology advancements, and best practices to examine the climate benefit of future fuel switching. The analysis indicates the necessary targets of efficiency, methane emissions, market penetration, and best practices necessary to enable a pathway for natural gas to reduce the carbon intensity of the heavy-duty transportation sector.     

Idle emissions from heavy-duty diesel and natural gas vehicles at high altitude

Idle emissions of total hydrocarbon (THC), CO, NOx, and particulate matter (PM) were measured from 24 heavy-duty diesel-fueled (12 trucks and 12 buses) and 4 heavy-duty compressed natural gas (CNG)-fueled vehicles. The volatile organic fraction (VOF) of PM and aldehyde emissions were also measured for many of the diesel vehicles. Experiments were conducted at 1609 m above sea level using a full exhaust flow dilution tunnel method identical to that used for heavy-duty engine Federal Test Procedure (FTP) testing. Diesel trucks averaged 0.170 g/min THC, 1.183 g/min CO, 1.416 g/min NOx, and 0.030 g/min PM. Diesel buses averaged 0.137 g/min THC, 1.326 g/min CO, 2.015 g/min NOx, and 0.048 g/min PM. Results are compared to idle emission factors from the MOBILE5 and PART5 inventory models. The models significantly (45-75%) overestimate emissions of THC and CO in comparison with results measured from the fleet of vehicles examined in this study. Measured NOx emissions were significantly higher (30-100%) than model predictions. For the pre-1999 (pre-consent decree) truck engines examined in this study, idle NOx emissions increased with model year with a linear fit (r2 = 0.6). PART5 nationwide fleet average emissions are within 1 order of magnitude of emissions for the group of vehicles tested in this study. Aldehyde emissions for bus idling averaged 6 mg/min. The VOF averaged 19% of total PM for buses and 49% for trucks. CNG vehicle idle emissions averaged 1.435 g/min for THC, 1.119 g/min for CO, 0.267 g/min for NOx, and 0.003 g/min for PM. The g/min PM emissions are only a small fraction of g/min PM emissions during vehicle driving. However, idle emissions of NOx, CO, and THC are significant in comparison with driving emissions.     

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 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.     

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.     

Exhaust temperature profiles for application of passive diesel particulate filters to solid waste collection vehicles in California

To reduce public exposure to diesel particulate matter (DPM), the California Air Resources Board has begun adoption of a series of rules to reduce these emissions from in-use heavy-duty vehicles. Passive diesel particulate filter (DPF) after-treatment technologies are a cost-effective method to reduce DPM emissions and have been used on a variety of vehicles worldwide. Two passive DPFs were interim-verified in California and approved federally for use in most 1994--2002 engine families for vehicles meeting min engine exhaust temperature requirements for successful filter regeneration. Some vehicles, however, may not be suited to passive DPFs because of lower engine exhaust temperatures. The purpose of this study was to determine the applicability of two types of passive DPFs to solid waste collection vehicles, the group of vehicles for which California recently mandated in-use DPM reductions. We selected 60 collection vehicles to represent the four main types of collection vehicle duty cycles--rolloffs, and front-end, rear, and side loaders--and collected second-by-second engine exhaust temperature readings for one week from each vehicle. As a group, the collection vehicles exhibited low engine exhaust temperatures, making the application of passive DPFs to these vehicles difficult. Only 35% of tested vehicles met the temperature requirements for one passive DPF, whereas 60% met the temperature requirements for the other. Engine exhaust temperatures varied by vehicle type. Side and front-end loaders met the engine exhaust temperature requirements in the greatest number of cases with approximately 50-90% achieving the required regeneration temperatures. Only 8-25% of the rear loader and roll-off collection vehicles met the engine exhaust temperature requirements. Solid waste collection vehicles represent a diverse fleet with a variety of duty cycles. Low engine exhaust temperatures will need to be addressed for successful use of passive DPFs in this application.     

Nitrous oxide emissions from light duty vehicles

Nitrous oxide (N₂O) emissions measurements were made on light duty gasoline and light duty diesel vehicles during chassis dynamometer testing conducted at the Environment Canada and California Air Resources Board vehicle emissions laboratories between 2001 and 2007. Per phase and composite FTP emission rates were measured. A subset of vehicles was also tested using other driving cycles to characterize emissions as a function of different driving conditions. Vehicles were both new (<6500 km) and in-use (6500–160,000 km) and were tested on low sulfur gasoline (<30 ppm) or low sulfur diesel (<300 ppm). Measurements from selected published studies were combined with these new measurements to give a test fleet of 467 vehicles meeting both US EPA and California criteria pollutant emissions standards between Tier 0 and Tier 2 Bin 3 or SULEV. Aggregate distance-based and fuel-based emission factors for N₂O are reported for each emission standard and for each of the different test cycles. Results show that the distinction between light duty automobile and light duty truck is not significant for any of the emission standards represented by the test fleet and the distinction between new and aged catalyst is significant for vehicles meeting all emission standards but Tier 2. This is likely due to the relatively low mileage accumulated by the Tier 2 vehicles in this study as compared to the durability requirement of the standard. The FTP composite N₂O emission factors for gasoline vehicles meeting emission standards more stringent than Tier 1 are substantially lower than those currently used by both Canada and the US for the 2005 inventories. N₂O emission factors from test cycles other than the FTP illustrate the variability of emission factors as a function of driving conditions. N₂O emission factors are shown to strongly correlate with NMHC/NMOG emission standards and less strongly with NO_X and CO emission standards. A review of several published reports on the effect of gasoline sulfur content on N₂O emissions suggests that additional research is needed to adequately quantify the increase in N₂O emissions as a function of fuel sulfur.     

Exhaust Temperature Profiles for Application of Passive Diesel Particulate Filters to Solid Waste Collection Vehicles in California

Abstract

To reduce public exposure to diesel particulate matter (DPM), the California Air Resources Board has begun adoption of a series of rules to reduce these emissions from in-use heavy-duty vehicles. Passive diesel particulate filter (DPF) after-treatment technologies are a cost-effective method to reduce DPM emissions and have been used on a variety of vehicles worldwide. Two passive DPFs were interim-verified in California and approved federally for use in most 1994–2002 engine families for vehicles meeting min engine exhaust temperature requirements for successful filter regeneration. Some vehicles, however, may not be suited to passive DPFs because of lower engine exhaust temperatures. The purpose of this study was to determine the applicability of two types of passive DPFs to solid waste collection vehicles, the group of vehicles for which California recently mandated in-use DPM reductions. We selected 60 collection vehicles to represent the four main types of collection vehicle duty cycles—roll-offs, and front-end, rear, and side loaders—and collected second-by-second engine exhaust temperature readings for one week from each vehicle. As a group, the collection vehicles exhibited low engine exhaust temperatures, making the application of passive DPFs to these vehicles difficult. Only 35% of tested vehicles met the temperature requirements for one passive DPF, whereas 60% met the temperature requirements for the other. Engine exhaust temperatures varied by vehicle type. Side and front-end loaders met the engine exhaust temperature requirements in the greatest number of cases with ～50–90% achieving the required regeneration temperatures. Only 8–25% of the rear loader and roll-off collection vehicles met the engine exhaust temperature requirements. Solid waste collection vehicles represent a diverse fleet with a variety of duty cycles. Low engine exhaust temperatures will need to be addressed for successful use of passive DPFs in this application.     

Use of a vehicle-modelling tool for predicting CO2 emissions in the framework of European regulations for light goods vehicles

The reduction of CO₂ emissions and fuel consumption from road transportation constitutes an important pillar of the EU commitment for implementing the Kyoto Protocol. Efforts to monitor and limit CO₂ emissions from vehicles can effectively be supported by the use of vehicle modelling tools. This paper presents the application of such a tool for predicting CO₂ emissions of vehicles under different operating conditions and shows how the results from simulations can be used for supporting policy analysis and design aiming at further reductions of the CO₂ emissions. For this purpose, the case of light duty goods (N1 category) vehicle CO₂ emissions control measures adopted by the EU is analysed. In order to understand how certain design and operating aspects affect fuel consumption, a number of N1 vehicles were simulated with ADVISOR for various operating conditions and the numerical results were validated against chassis dynamometer tests. The model was then employed for analysing and evaluating the new EU legislative framework that addresses CO₂ emissions from this vehicle class. The results of this analysis have shown the weaknesses of the current regulations and revealed new potential in CO₂ emissions control. Finally the TREMOVE model was used for simulating a possible scenario for reducing CO₂ emissions at fleet level.     

Ammonia emissions from a representative in-use fleet of light and medium-duty vehicles in the California South Coast Air Basin

We used Fourier Transform Infrared Spectroscopy (FTIR) to measure tailpipe ammonia emissions from a representative fleet of 41 light and medium-duty vehicles recruited in the California South Coast Air Basin. A total of 121 chassis dynamometer emissions tests were conducted on these vehicles and the test results were examined to determine the effects of several key variables on ammonia emissions. Variables included vehicle type, driving cycle, emissions technology, ammonia precursor emissions (i.e. CO and NOx) and odometer readings/model year as a proxy for catalyst age. The mean ammonia emissions factor was 46 mg km^?1 (σ = 48 mg km^?1) for the vehicle fleet. Average emission factors for specific vehicle groups are also reported in this study. Results of this study suggest vehicles with the highest ammonia emission rates possess the following characteristics: medium-duty vehicles, older emissions technologies, mid-range odometer readings, and higher CO emissions. In addition, vehicles subjected to aggressive driving conditions are likely to be higher ammonia emitters. Since the vehicles we studied were representative of recent model year vehicles and technologies in urban airsheds, the results of our study will be useful for developing ammonia emissions inventories in Los Angeles and other urban areas where California-certified vehicles are driven. However, efforts should also be made to continue emissions testing on in-use vehicles to ensure greater confidence in the ammonia emission factors reported here.     

Feasibility of Landfill Gas as a Liquefied Natural Gas Fuel Source for Refuse Trucks

Abstract

The purpose of this paper is to develop a methodology to evaluate the feasibility of using landfill gas (LFG) as a liquefied natural gas (LNG) fuel source for heavy-duty refuse trucks operating on landfills. Using LFG as a vehicle fuel can make the landfills more self-sustaining, reduce their dependence on fossil fuels, and reduce emissions and greenhouse gases. Acrion Technologies Inc. in association with Mack Trucks Inc. developed a technology to generate LNG from LFG using the CO₂ WASH process. A successful application of this process was performed at the Eco Complex in Burlington County, PA. During this application two LNG refuse trucks were operated for 600 hr each using LNG produced from gases from the landfill. The methodology developed in this paper can evaluate the feasibility of three LFG options: doing nothing, electricity generation, and producing LNG to fuel refuse trucks. The methodology involved the modeling of several components: LFG generation, energy recovery processes, fleet operations, economic feasibility, and decision-making. The economic feasibility considers factors such as capital, maintenance, operational, and fuel costs, emissions and tax benefits, and the sale of products such as surplus LNG and food-grade carbon dioxide (CO₂).

Texas was used as a case study. The 96 landfills in Texas were prioritized and 17 landfills were identified that showed potential for converting LFG to LNG for use as a refuse truck fuel. The methodology was applied to a pilot landfill in El Paso, TX. The analysis showed that converting LFG to LNG to fuel refuse trucks proved to be the most feasible option and that the methodology can be applied for any landfill that considers this option.     

Further validation of artificial neural network-based emissions simulation models for conventional and hybrid electric vehicles

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO2] and oxides of nitrogen [NO(x)]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO2 and NO(x) in the case of a class-8 truck but were more accurate as the truck weight increased.