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

Fitzmaurice, Helen L.; Cohen, Ronald C.

doi:https://doi.org/10.5194/acp-22-15403-2022

Articles | Volume 22, issue 23

https://doi.org/10.5194/acp-22-15403-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-22-15403-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 23

Research article

|

05 Dec 2022

Research article |

| 05 Dec 2022

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

Helen L. Fitzmaurice and Ronald C. Cohen

Supplement

https://doi.org/10.5194/acp-22-15403-2022-supplement

Data sets

Brake and Tire Wear Emissions from Onroad Vehicles in MOVES3 EPA https://nepis.epa. gov/Exe/ZyPDF.cgi?Dockey=P1010M43.pdf

ERA5-Land hourly data from 1981 to present J. Muñoz Sabater https://doi.org/10.24381/cds.e2161bac

Performance Measurement System California Department of Transportation https://pems.dot.ca.gov

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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 particulate matter emission factors have decreased by a factor of ~ 9 in the past decade in the San Francisco Bay area. Because of the wide availability of similar data sets across the USA and globally, this method could be applied to other settings to understand long-term trends and regional differences in HDV emissions.