Atmospheric Chemistry and Physics (Aug 2023)

High-resolution air quality simulations of ozone exceedance events during the Lake Michigan Ozone Study

  • R. B. Pierce,
  • M. Harkey,
  • A. Lenzen,
  • L. M. Cronce,
  • J. A. Otkin,
  • J. A. Otkin,
  • J. L. Case,
  • D. S. Henderson,
  • Z. Adelman,
  • T. Nergui,
  • C. R. Hain

DOI
https://doi.org/10.5194/acp-23-9613-2023
Journal volume & issue
Vol. 23
pp. 9613 – 9635

Abstract

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We evaluate two high-resolution Lake Michigan air quality simulations during the 2017 Lake Michigan Ozone Study campaign. These air quality simulations employ identical chemical configurations but use different input meteorology. The AP-XM configuration follows the U.S. Environmental Protection Agency (EPA)-recommended modeling practices, whereas the YNT_SSNG employs different parameterization schemes and satellite-based inputs of sea surface temperatures, green vegetative fraction, and soil moisture and temperature. Overall, we find a similar performance in the model simulations of hourly and maximum daily average 8 h (MDA8) ozone, with the AP-XM and YNT_SSNG simulations showing biases of −11.42 and −13.54 ppbv (parts per billion by volume), respectively, during periods when the observed MDA8 was greater than 70 ppbv. However, for the two monitoring sites that observed high-ozone events, the AP-XM simulation better matched observations at Chiwaukee Prairie, and the YNT_SSNG simulation better matched observations at the Sheboygan Kohler-Andrae (KA) State Park. We find that the differences between the two simulations are largest for column amounts of ozone precursors, particularly NO2. Across three high-ozone events, the YNT_SSNG simulation has a lower NO2 column bias (0.17×1015 mol cm−2) compared to the AP-XM simulation (0.31×1015 mol cm−2). The YNT_SSNG simulation also has an advantage in that it better captures the structure of the boundary layer and lake breeze during the 2 June high-ozone event, although the timing of the lake breeze is about 3 h too early at Sheboygan. Our results are useful for informing an air quality modeling framework for the Lake Michigan area.