Assessing the Impact of Wildfire Smoke Transport Through Chemical Transport Modeling, Satellite Retrievals, and Ground-Based Observations of Ozone in Rural Nevada
Yi Ji*, Xiaodan Zhang, Abiola S. Lawal, Heather A. Holmes and Cesunica E. Ivey,
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引用次数: 0
Abstract
Wildfires emit a large amount of ozone precursors, nitrogen oxides, and particulate matter into the troposphere and sometimes the stratosphere. With the increasing wildfire events in recent years, the western U.S. regions may experience challenges with higher-than-normal air pollution levels during the fire season (June-October). Therefore, determining the ozone enhancement pattern from wildfire smoke is crucial to understanding the influence of wildfire plume transport on a subregional basis. This study investigates the impact of the 2013 Rim Fire on ozone levels in rural Nevada, employing a combination of ground-based monitors, satellite remote sensing, and atmospheric modeling. The research focuses on understanding how wildfire smoke affects ozone concentrations in the downwind regions. Findings indicate significant ozone enhancements on smoke days compared to nonsmoke days, highlighting the contribution of wildfire emissions to regional air quality deterioration. The study demonstrates that the chemical transport model underestimated ozone levels downwind of wildfire plumes, likely due to uncertainties in smoke emissions estimates and differences in chemical mechanisms across model versions. Satellite observations of nitrogen dioxide and formaldehyde underline the link between wildfire emissions and increased ozone production. The comprehensive approach combining ground-based monitoring, remote sensing, and advanced modeling provides deeper insights into the dynamics of wildfire smoke and its effects on air quality, emphasizing the need for integrated strategies to manage the impacts of wildfires on regional air quality.
This study reveals wildfire smoke significantly elevated ozone levels in downwind areas, with models underestimating impacts. Integrated monitoring, remote sensing data, and modeling underscore the need for improved wildfire emission representation.