W. Scott Wayne

Idle emissions from heavy-duty diesel vehicles: review and recent data.

Abstract Heavy-duty diesel vehicle idling consumes fuel and reduces atmospheric quality, but its restriction cannot simply be proscribed, because cab heat or air-conditioning provides essential driver comfort. A comprehensive tailpipe emissions database to describe idling impacts is not yet available. This paper presents a substantial data set that incorporates results from the West Virginia University transient engine test cell, the E-55/59 Study and the Gasoline/Diesel PM Split Study. It covered 75 heavy-duty diesel engines and trucks, which were divided into two groups: vehicles with mechanical fuel injection (MFI) and vehicles with electronic fuel injection (EFI). Idle emissions of CO, hydrocarbon (HC), oxides of nitrogen (NOx), particulate matter (PM), and carbon dioxide (CO2) have been reported. Idle CO2 emissions allowed the projection of fuel consumption during idling. Test-to-test variations were observed for repeat idle tests on the same vehicle because of measurement variation, accessory loads, and ambient conditions. Vehicles fitted with EFI, on average, emitted [~20 g/hr of CO, 6 g/hr of HC, 86 g/hr of NOx, 1 g/hr of PM, and 4636 g/hr of CO2 during idle. MFI equipped vehicles emitted ~35 g/hr of CO, 23 g/hr of HC, 48 g/hr of NOx, 4 g/hr of PM, and 4484 g/hr of CO2, on average, during idle. Vehicles with EFI emitted less idleCO, HC, and PM, which could be attributed to the efficient combustion and superior fuel atomization in EFI systems. Idle NOx, however, increased with EFI, which corresponds with the advancing of timing to improve idle combustion. Fuel injection management did not have any effect on CO2 and, hence, fuel consumption. Use of air conditioning without increasing engine speed increased idle CO2, NOx, PM, HC, and fuel consumption by 25% on average. When the engine speed was elevated from 600 to 1100 revolutions per minute, CO2 and NOx emissions and fuel consumption increased by >150%, whereas PM and HC emissions increased by ~100% and 70%, respectively. Six Detroit Diesel Corp. (DDC) Series 60 engines in engine test cell were found to emit less CO, NOx, and PM emissions and consumed fuel at only 75%of the level found in the chassis dynamometer data. This is because fan and compressor loads were absent in the engine test cell.

Idle Emissions from Medium Heavy-Duty Diesel and Gasoline Trucks

Abstract Idle emissions data from 19 medium heavy-duty diesel and gasoline trucks are presented in this paper. Emissions from these trucks were characterized using full-flow exhaust dilution as part of the Coordinating Research Council (CRC) Project E-55/59. Idle emissions data were not available from dedicated measurements, but were extracted from the continuous emissions data on the low-speed transient mode of the medium heavy-duty truck (MHDTLO) cycle. The four gasoline trucks produced very low oxides of nitrogen (NOx) and negligible particulate matter (PM) during idle. However, carbon monoxide (CO) and hydrocarbons (HCs) from these four trucks were approximately 285 and 153 g/hr on average, respectively. The gasoline trucks consumed substantially more fuel at an hourly rate (0.84 gal/hr) than their diesel counterparts (0.44 gal/hr) during idling. The diesel trucks, on the other hand, emitted higher NOx (79 g/hr) and comparatively higher PM (4.1 g/hr), on average, than the gasoline trucks (3.8 g/hr of NOx and 0.9 g/hr of PM, on average). Idle NOx emissions from diesel trucks were high for post-1992 model year engines, but no trends were observed for fuel consumption. Idle emissions and fuel consumption from the medium heavy-duty diesel trucks (MHDDTs) were marginally lower than those from the heavy heavy-duty diesel trucks (HHDDTs), previously reported in the literature.

Evaluation of Emissions from New and In-Use Transit Buses in Mexico City, Mexico

The West Virginia University Transportable Heavy-Duty Emissions Testing Laboratory was used to evaluate exhaust emissions from nine transit buses from six separate manufacturers, as commissioned by the Mexico City, Mexico, Secretariat of the Environment. The vehicles included a hybrid-drive diesel bus, two buses with lean-burn spark-ignited compressed natural gas (CNG) engines, and six buses powered by conventional diesel engines. Vehicle testing weights (curb weight plus passenger weight) ranged from 26,996 Ib (12,256 kg) to 57,025 Ib (25,889 kg), and passenger capacities ranged from 85 to 161. Two driving cycles, the European Transient Cycle (ETC, also known as the FIGE transient cycle) and a new, three-mode Mexico City Schedule, were used to simulate in-use driving conditions during emissions measurements. Diesel fuels with three different sulfur concentrations (15, 150, and 350 ppm) were also examined, and the lowest-sulfur fuel (15 ppm) was not found to have an appreciable direct effect on emissions....

Pump-to-Wheels Methane Emissions from the Heavy-Duty Transportation Sector

Pump-to-wheels (PTW) methane emissions from the heavy-duty (HD) transportation sector, which have climate change implications, are poorly documented. In this study, methane emissions from HD natural gas fueled vehicles and the compressed natural gas (CNG) and liquefied natural gas (LNG) fueling stations that serve them were characterized. A novel measurement system was developed to quantify methane leaks and losses. Engine related emissions were characterized from twenty-two natural gas fueled transit buses, refuse trucks, and over-the-road (OTR) tractors. Losses from six LNG and eight CNG stations were characterized during compression, fuel delivery, storage, and from leaks. Cryogenic boil-off pressure rise and pressure control venting from LNG storage tanks were characterized using theoretical and empirical modeling. Field and laboratory observations of LNG storage tanks were used for model development and evaluation. PTW emissions were combined with a specific scenario to view emissions as a percent of throughput. Vehicle tailpipe and crankcase emissions were the highest sources of methane. Data from this research are being applied by the authors to develop models to forecast methane emissions from the future HD transportation sector.

Emissions Benefits from Alternative Fuels and Advanced Technology in the U.S. Transit Bus Fleet

Alternative fuels and technologies offer potential for reducing emissions in public transportation. These potentials were explored by determining emissions levels and fuel consumption from the U.S. transit bus fleet and comparison of hypothetical scenarios in which implementation of specific alternative fuels and technologies is considered. Impacts from current transit bus procurements were also evaluated. Emissions benefits above and beyond the natural course of transit bus procurements were examined for new diesel buses running on ULSD fuel, diesel-electric hybrid buses, gasoline-electric hybrid buses, compressed natural gas and biodiesel. According to the analysis, reductions in emissions of CO, NMHC, NOx, PM and CO2, as well as fuel consumption, may be attained, and diesel hybrid buses yield the largest reductions in CO2 emissions and are the only technology to reduce fuel consumption relative to the present fleet. Introducing diesel-electric hybrid buses in 15% of the U.S. transit bus fleet would reduce annual end-use emissions by nearly 1,800 tons of CO, 400 tons of NMHC, 4,400 tons of NOx, 200 tons of PM, 491,400 tons of CO2, and fuel consumption by 50.66 millions of diesel gallons.

Creation and Evaluation of a Medium Heavy-Duty Truck Test Cycle

The California Air Resources Board (ARB) developed a Medium Heavy-Duty Truck (MHDT) schedule by selecting and joining microtrips from real-world MHDT. The MHDT consisted of three modes; namely, a Lower Speed Transient, aHigher Speed Transient, and a Cruise mode. The maximum speeds of these modes were 28.9, 58.2 and 66.0 mph, respectively. Each mode represented statistically selected truck behavior patterns in California. The MHDT is intended to be applied to emissions characterization of trucks (14,001 to 33,0001b gross vehicle weight) exercised on a chassis dynamometer. This paper presents the creation of the MHDT and an examination of repeatability of emissions data from MHDT driven through this schedule. Two trucks were procured to acquire data using the MHDT schedule. The first, a GMC truck with an 8.2-liter Isuzu engine and a standard transmission, was tested at laden weight (90% GVW, 17,5501b) and at unladen weight (50% GVW, 9,7501b). The second, a Freightliner with a 7.2-liter Caterpillar engine and an automatic transmission, was tested only at 13,000lb (50% GVW). The test runs were performed using the West Virginia University (WVU) medium-duty chassis dynamometer, located in Riverside, CA. Vehicle inertia was mimicked using a flywheel set, and tire and wind drag were mimicked using an eddy current power absorber. The truck exhaust was ducted to a full-scale dilution tunnel, with HEPA filtered dilution air, and a flow rate of approximately 1,500scfm. Particulate matter (PM) mass was found gravimetrically, using filtration, while carbon dioxide (CO 2 ), carbon monoxide (CO), oxides of nitrogen (NO x ) and hydrocarbons (HC) were measured using research grade analyzers. Data were computed in units of g/cycle, g/mile, g/ahp-hr, g/gallon and g/minute, and were examined most carefully in units of g/mile. Preliminary runs showed that the GMC truck did deviate from the target trace when tested at laden weight, and the completed distance for the MHDT Lower Speed Transient mode varied from 0.906 to 0.954 miles. Laden data from the GMC truck demonstrated that emissions were repeatable for all three modes of the MHDT schedule. Averaged GMC truck results for all laden runs of the Lower Speed Transient mode were 8.99g/mile NO x and 0.26g/mile PM results for the Higher Speed Transient mode were 6.50g/mile NO x and 0.20g/mile PM and for the Cruise mode were 4.73g/mile NO x and 0.09g/mile PM. Unladen data from the GMC truck also showed acceptable repeatability, with emissions of NO x that were about 87% of the laden values. The Freightliner, with an automatic transmission, produced 16.39g/mile NO x and 0.33g/mile PM on the Lower Speed Transient mode, 12.59g/mile NOX and 0.25g/mile PM on the Higher Speed Transient mode, 7.93g/mile NO x and 0.14g/mile PM on the Cruise mode and 7.57g/mile NO x and 0.19g/mile PM on the UDDS (Test D). when three runs of thee same mode were run back-to-back, the standard deviation of NO x values for six sequences of runs were under 4% of the average for all three modes on both the manual transmission truck at laden test weight and the automatic transmission truck at unladen weight. CO 2 variation was under 4% as well, except in one instance. In two of the six sequences PM variability exceeded 10%. The researchers concluded that the MHDT was suitable for characterizing the emissions from trucks in future inventory research. Data also showed that emissions from a mode were unaffected by whichever mode was run previously.

Expressing cycles and their emissions on the basis of properties and results from other cycles.

A method is proposed to predict vehicle emissions over a driving cycle on the basis of the vehicles emissions measured over other driving cycles and the properties of these cycles. These properties include average velocity, average inertial power, and average acceleration. This technique was demonstrated and verified using data from the Coordinating Research Council (CRC) E-55/59 emissions inventory program using the statistical properties of the cycles used for measurement in E-55/59. These cycles were Idle mode, Creep mode, Cruise mode, and Transient mode of the 5-Mode CARB H-HDDT, and their intensive properties were average velocity, average acceleration, and average inertial power. The predicted emissions were from the vehicle driven over the U.S. heavy-duty urban dynamometer driving schedule (UDDS). The emissions data were collected from 56 heavy-duty trucks operating at a test weight of 56000 lbs. The predicted emissions data for the UDDS can be expressed as a linear combination of emissions from Idle, Transient, and Cruise modes, and the weighting factors for the linear combination can be determined without prior knowledge of the UDDS emissions themselves. Different combinations of cycles were employed to predict UDDS emissions, and the combination of Idle, Transient, and Cruise modes was found to be the most suitable. For the 56 heavy-duty trucks, the coefficient of determination (R2) in predicting carbon dioxide (CO2) was 0.80, oxides of nitrogen (NOx) was 0.89, and total particulate matter (PM) was 0.71. The average errors between the predicted and measured cycle emissions were 4.2%, 7.8%, and 46.8%, respectively. As with most emissions modeling tools, CO2 and NOx were better predicted than PM. The generic use of the technique was further demonstrated by predicting the emissions expected to arise from operation over the European Transient Cycle (ETC).

Emissions from Diesel-Fueled Heavy-Duty Vehicles in Southern California

Few real-worid data exist to describe the contribution of diesel vehicles to the emissions inventory, although it is widely acknowledged that diesel vehicles are a significant contributor to oxides of nitrogen (NO x ) andparticulate matter (PM) in Southern California. New data were acquired during the Gasoline/Diesel PM Split Study, designed to collect emissions data for source profiling of PM emissions from diesel- and gasoline-powered engines in the South Coast (Los Angeles) Air Basin in 2001. Regulated gases, PM and carbon dioxide (CO 2 ) were measured from 34 diesel vehicles operating in the Southern California area. Two were transit buses, 16 were trucks over 33,000 Ibs. in weight, 8 were 14,001 Ibs. to 33,000 Ibs. in weight and 8 were under 14,001 Ibs. in weight. The vehicles were also grouped by model year for recruiting and data analysis. Emissions were measured in Riverside, CA, using West Virginia Universitys (WVU) Transportable Medium-Duty and Heavy-Duty Vehicle Emissions Testing Laboratories. The trucks were all exercised through a CSHVR, a Highway cycle, and an Idle period. In addition, selected vehicles were tested under cold start idle, cold start CSHVR, and the Urban Dynamometer Driving Schedule (UDDS). All data were computed in units of g/mile except for idle tests, which were recorded in g/cycle. Repeat runs on the same test schedule demonstrated that data were consistent from run to run. This paper presents the data for the trucks over 33,000 Ib. in weight. Data for these trucks showed conclusively that PM levels are higher for older vehicles: this may be due to vehicle age, but more likely is associated with the improved technology for later model years and implied compliance with later standards. In contrast, emissions of oxides of nitrogen (NO x ) have not fallen in the same way with respect to model year. The data provide new insight into real-world diesel truck emissions and will provide information for emissions source profiles for PM source apportionment in Los Angeles. The data reported in this presentation are a portion of the GasolinelDiesel PM Split Study, sponsored by the U.S. Department of Energys Office of FreedomCAR and Vehicle Technologies through the National Renewable Energy Laboratory.

Integrated Bus Information System: Vehicle Procurement Resource for Transit

West Virginia University, under contract to the Federal Transit Administration, has developed two tools to evaluate the pollutant emissions, greenhouse gases, and fuel economy of transit buses: a searchable database of transit vehicle emission data and a transit fleet emission inventory model. These tools, complemented by a transit vehicle life-cycle cost model developed by West Virginia University, Battelle, and Transit Resource Center for the Transportation Research Board, provide an interactive, approachable, and reliable method for users, primarily transit agencies, to evaluate overall fleet emissions and fuel consumption for optimization of fleet configuration and operation. These tools will be made available through an online website called the Integrated Bus Information System (IBIS). This paper describes development of the transit fleet inventory model and comparison with the U.S. Environmental Protection Agency (EPA) MOBILE6 and MOVES (motor vehicle emission simulator) emission inventory models. The IBIS model was developed from extensive chassis dynamometer data from several reference vehicles. Polynomial models were built through linear regression. These backbone models characterized the effects of driving activity on vehicle emissions and fuel consumption. Comparison of predicted emissions showed good agreement for hydrocarbon, carbon monoxide, and oxides of nitrogen emissions and acceptable agreement for particulate matter emissions. The EPA MOBILE6 model assumed constant values as a function of duty cycle for carbon dioxide emissions and fuel economy. The West Virginia University IBIS model and EPA MOVES model displayed similar trends for carbon dioxide emissions, but MOVES predicted substantially lower carbon dioxide levels.

Creation of Life-Cycle Cost Tool for Transit Buses to Evaluate Hybrid Electric Bus Technologies in Real-World Operation

Hybrid buses offer the potential for fuel savings for transit operators and are expected to become important components of bus fleets around the world in the coming decade. This paper describes how a spreadsheet tool for a life-cycle cost (LCC) model for transit buses was developed to assist transit agencies in forecasting life-cycle operating and capital costs when choosing among various bus technologies, including hybrids. The tool is a key deliverable in a project sponsored by TCRP to assess hybrid electric bus performance in real-world operation. Forty hybrid electric buses were evaluated at four U.S. transit agencies, along with comparable conventional diesel and compressed natural gas buses. The LCC tool was created to cover key capital- and operating-cost factors that are based on the real-world data collected. The model is extremely flexible, and the user can override nearly all the data so that the model can be used in the future as costs and technologies change. This paper focuses on the models structure, describes the case study buses, and illustrates an example of LCC calculation by using the model. More information about the project and its other results and deliverables can be found in TCRP Report 132.