Selected article for: "air pollution and spatial scale"

Author: Goldberg, Daniel L.; Anenberg, Susan C.; Kerr, Gaige Hunter; Mohegh, Arash; Lu, Zifeng; Streets, David G.
Title: TROPOMI NO(2) in the United States: A Detailed Look at the Annual Averages, Weekly Cycles, Effects of Temperature, and Correlation With Surface NO(2) Concentrations
  • Cord-id: g3ntkwip
  • Document date: 2021_4_2
  • ID: g3ntkwip
    Snippet: Observing the spatial heterogeneities of NO(2) air pollution is an important first step in quantifying NO(X) emissions and exposures. This study investigates the capabilities of the Tropospheric Monitoring Instrument (TROPOMI) in observing the spatial and temporal patterns of NO(2) pollution in the continental United States. The unprecedented sensitivity of the sensor can differentiate the fine‐scale spatial heterogeneities in urban areas, such as emissions related to airport/shipping operatio
    Document: Observing the spatial heterogeneities of NO(2) air pollution is an important first step in quantifying NO(X) emissions and exposures. This study investigates the capabilities of the Tropospheric Monitoring Instrument (TROPOMI) in observing the spatial and temporal patterns of NO(2) pollution in the continental United States. The unprecedented sensitivity of the sensor can differentiate the fine‐scale spatial heterogeneities in urban areas, such as emissions related to airport/shipping operations and high traffic, and the relatively small emission sources in rural areas, such as power plants and mining operations. We then examine NO(2) columns by day‐of‐the‐week and find that Saturday and Sunday concentrations are 16% and 24% lower respectively, than during weekdays. We also analyze the correlation of daily maximum 2‐m temperatures and NO(2) column amounts and find that NO(2) is larger on the hottest days (>32°C) as compared to warm days (26°C–32°C), which is in contrast to a general decrease in NO(2) with increasing temperature at moderate temperatures. Finally, we demonstrate that a linear regression fit of 2019 annual TROPOMI NO(2) data to annual surface‐level concentrations yields relatively strong correlation (R (2) = 0.66). These new developments make TROPOMI NO(2) satellite data advantageous for policymakers and public health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations.

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