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Multiscale Modeling of Background Ozone: Research Needs to Inform and Improve Air Quality Management
Citation:
Hogrefe, C., B. Henderson, G. Tonnesen, R. Mathur, AND R. Matichuk. Multiscale Modeling of Background Ozone: Research Needs to Inform and Improve Air Quality Management. EM Magazine. Air and Waste Management Association, Pittsburgh, PA, , 1-6, (2020).
Impact/Purpose:
Accurately quantifying background ozone is important for many air quality management applications. This article for the Air & Waste Management Associations EM publication provides the authors’ perspective on research needs at both the regional and global scale to improve model-based estimates of background ozone.
Description:
For many decades, ground-level ozone has been recognized as a pollutant causing adverse human health effects and damage crops and ecosystems. Scientific understanding about the ambient concentrations at which such damages occur has evolved, triggering several revisions to the National Ambient Air Quality Standard (NAAQS) for ozone that gradually reduced critical thresholds. Grid-based photochemical air quality modeling systems (AQM) have long been used to develop air quality management strategies for areas exceeding the ozone NAAQS. Viewed from an air quality management perspective, the magnitude of locally controllable anthropogenic emissions relative to background ozone (BG O3) levels (i.e., ozone from non-local anthropogenic sources and natural sources) has generally decreased over time. This increases emphasis on representing the processes controlling BG O3 and characterizing its temporal and spatial fluctuations, especially for ozone exceedance events. Improving the representation of BG O3 in AQM improves their fidelity, which increases our confidence in the models’ ability to differentiate BG O3 from controllable sources. Improved differentiation promotes effective controls on anthropogenic sources. In this article, we provide our perspective on improving the characterization of BG O3 in AQM and discuss examples of using such information in air quality management.
