From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

Journal: Proceedings of the National Academy of Sciences of the United States of America
PMID: 34155113

Abstract

The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational data during COVID-19, to predict surface-level NO, O, and fine particle concentration in the Los Angeles megacity. Our model exhibits high fidelity in reproducing pollutant concentrations in the Los Angeles Basin and identifies major factors controlling each species. During the strictest lockdown period, traffic reduction led to decreases in NO and particulate matter with aerodynamic diameters <2.5 μm by -30.1% and -17.5%, respectively, but a 5.7% increase in O Heavy-duty truck emissions contribute primarily to these variations. Future traffic-emission controls are estimated to impose similar effects as observed during the COVID-19 lockdown, but with smaller magnitude. Vehicular electrification will achieve further alleviation of NO levels.

Authors

  • Jiani Yang
    Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125.
  • Yifan Wen
    School of Environment, Tsinghua University, Beijing 100084, China.
  • Yuan Wang
    State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro-Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China.
  • Shaojun Zhang
    School of Environment, Tsinghua University, Beijing 100084, China; yuan.wang@caltech.edu zhsjun@tsinghua.edu.cn seinfeld@caltech.edu.
  • Joseph P Pinto
    Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599.
  • Elyse A Pennington
    Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125.
  • Zhou Wang
    Department of Geography, University of Mainz, 55099 Mainz, Germany.
  • Ye Wu
    Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Stanley P Sander
    Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109.
  • Jonathan H Jiang
    Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109.
  • Jiming Hao
    State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
  • Yuk L Yung
    Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125.
  • John H Seinfeld
    Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125; yuan.wang@caltech.edu zhsjun@tsinghua.edu.cn seinfeld@caltech.edu.

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