Developing a heavy-duty vehicle activity database to estimate start and idle emissions

Heavy-duty vehicle start and idling activities were characterized from two datasets to improve emission estimates in the MOtor Vehicle Emission Simulator (MOVES): 1. Fleet DNA from the National Renewable Energy Laboratory (NREL) and 2. A dataset collected by the University of California, Riverside f...

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Veröffentlicht in:Transportation research. Part D, Transport and environment Transport and environment, 2022-04, Vol.105, p.103251, Article 103251
Hauptverfasser: Zhang, Chen, Ficenec, Karen, Kotz, Andrew, Kelly, Kenneth, Sonntag, Darrell, Fulper, Carl, Brakora, Jessica, Mo, Tiffany, Ballare, Sudheer
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Sprache:eng
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Zusammenfassung:Heavy-duty vehicle start and idling activities were characterized from two datasets to improve emission estimates in the MOtor Vehicle Emission Simulator (MOVES): 1. Fleet DNA from the National Renewable Energy Laboratory (NREL) and 2. A dataset collected by the University of California, Riverside for the California Air Resources Board. The combined dataset includes 564 commercial vehicles, over 23,000 vehicle days of operation and covers seven of the nine heavy-duty source types defined by MOVES. The start and idle activities are characterized and illustrated across MOVES source types, vocations, fleets, days, and hours. This study provides the most comprehensive analysis yet made publicly available to characterize start and idle activity for heavy-duty vehicles within the United States. The results also show there is significant uncertainty in the average heavy-duty idle and start activity due to the large variation in activity across fleets and vocations, and sparsity of nation-wide vehicle population data by vocation.
ISSN:1361-9209
1879-2340
DOI:10.1016/j.trd.2022.103251