Developing a Heavy-Duty Vehicle Activity Database to Estimate Start and Idle Emissions

Chen Zhang, Karen Ficenec, Andrew Kotz, Kenneth Kelly, Darrell Sonntag, Carl Fulper, Jessica Brakora, Tiffany Mo, Sudheer Ballare

Research output: Contribution to journalArticlepeer-review

2 Scopus Citations


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.

Original languageAmerican English
Article numberArticle No. 103251
Number of pages19
JournalTransportation Research Part D: Transport and Environment
StatePublished - Apr 2022

Bibliographical note

Publisher Copyright:
© 2022

NREL Publication Number

  • NREL/JA-5400-80717


  • Emissions
  • Engine idle activity
  • Engine starts
  • Heavy duty vehicles
  • On-road data


Dive into the research topics of 'Developing a Heavy-Duty Vehicle Activity Database to Estimate Start and Idle Emissions'. Together they form a unique fingerprint.

Cite this