Preprints
https://doi.org/10.5194/acp-2021-1042
https://doi.org/10.5194/acp-2021-1042
 
31 Jan 2022
31 Jan 2022
Status: this preprint is currently under review for the journal ACP.

A method for using stationary networks to observe long term trends of on-road emissions factors of primary aerosol from heavy duty vehicles

Helen Lorraine Fitzmaurice1 and Ronald C. Cohen1,2 Helen Lorraine Fitzmaurice and Ronald C. Cohen
  • 1Department of Earth and Planetary Science, University of California Berkeley, Berkeley, 94720, United States
  • 2Department of Chemistry, University of California Berkeley, Berkeley, 94720, United States

Abstract. Heavy-duty vehicles (HDV) contribute a significant, but decreasing, fraction of primary aerosol emissions in urban areas. Previous studies have shown spatial heterogeneity in compliance with regulation. Consequently, location-specific emissions factors are necessary to describe primary particulate matter (PM) emissions by HDV. Using near-road observations from the Bay Area Air Quality Management District (BAAQMD) network over the 2009–2020 period in combination with Caltrans measurements of vehicle number and type, we determine primary PM2.5 emission factors from HDV on highways in the San Francisco Bay Area. We demonstrate that HDV primary aerosol emission factors derived using this method are in line with observations by other studies, that they decreased a by a factor of ~7 in the past decade, and that they are still 2–3 times higher than would be expected if all HDV were in compliance with California HDV regulations.

Helen Lorraine Fitzmaurice and Ronald C. Cohen

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2021-1042', Anonymous Referee #1, 31 Mar 2022
  • RC2: 'Comment on acp-2021-1042', Anonymous Referee #2, 15 May 2022

Helen Lorraine Fitzmaurice and Ronald C. Cohen

Helen Lorraine Fitzmaurice and Ronald C. Cohen

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Short summary
We develop a novel method for finding Heavy Duty Vehicle (HDV) emission factors (g PM / kg fuel) using regulatory sensor networks and publicly available traffic data. We find that PM emissions factors have decreased by a factor of ~7 in the past decade in the SF Bay Area. Because of the wide availability of similar data sets across the US and globally, this method could be applied to other settings to understand long-term trends and regional differences in HDV emission.
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