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The Detroit Diesel Corporation produces two popular diesel fuel engines that have been used in a case-study. The study examines emissions data from two transportable chassis dynamometer laboratories formed and run by the West Virginia University. A subset of this information on heavy-duty vehicles, including buses, has been used for the last seven years.

A method is proposed to predict vehicle emissions over a driving cycle on the basis of the vehicle's 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). [ABSTRACT FROM AUTHOR]

Traditional emissions inventories for trucks and buses have relied on diesel engine emissions certification data, in units of g/bhp-hr, processed to yield a value in g/mile without a detailed accounting of the vehicle activity. Research has revealed a variety of other options for inventory prediction, including the use of emissions factors based upon instantaneous engine power and instantaneous vehicle behavior. The objective of this paper is to provide tabular factors for use with vehicle activity information to describe the instantaneous emissions from each heavyduty vehicle considered. To produce these tables, a large body of data was obtained from the research efforts of the West Virginia University-Transportable Heavy Duty Emissions Testing Laboratories (TransLabs). These data were available as continuous records of vehicle speed (hence also acceleration), vehicle power, and emissions of carbon monoxide (CO), oxides of nitrogen (NO[sub x]), and hydrocarbons (HC). Data for particulate matter (PM) were available only as a composite value for a whole vehicle test cycle, but using a best effort approach, the PM was distributed in time in proportion to the CO. Emissions values, in g/sec, were binned according to the speed and acceleration of a vehicle, and it was shown that the emissions could be predicted with reasonable accuracy by applying this table to the original speed and acceleration data. The test cycle used was found to have a significant effect on the emissions value predicted. Tables were created for vehicles grouped by type (large transit buses, small transit buses, and tractor-trailers) and by range of model year. These model year ranges were bounded by U.S. national changes in emissions standards. The result is that a suite of tables is available for application to emissions predictions for trucks and buses with known activity, or as modeled by TRANSIMS, a vehicle activity simulation model from Los Alamos National Laboratories. [ABSTRACT FROM AUTHOR]

Examines exhaust emissions from engines of the Detroit Diesel Corp. transit buses. Presentation of realistic emission data; Decline of most regulated emissions from engine; Reduction of nitrogen oxide emission.

Presents an atmospheric emissions inventory data for heavy-duty vehicles in the United States. Atmospheric oxides of nitrogen recorded from chassis dynamometer testing of eight vehicles using a variety of transient cycles; Vehicles and cycles used for testing and emissions measured.

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. [ABSTRACT FROM AUTHOR]