Quantifying O₃ Impacts in Urban Areas Due to Wildfires Using a Generalized Additive Model

Area of Science:

• Atmospheric Chemistry
• Air Quality Modeling
• Environmental Science

Background:

• Wildfires release ozone precursors, but variability in emissions, plume height, and processing complicates Eulerian modeling of ozone production.
• Accurate modeling of ozone (O3) is crucial for air quality management, especially considering the increasing frequency of wildfire events.

Purpose of the Study:

• To develop a statistical approach for characterizing maximum daily 8-hour average ozone (MDA8) under typical non-fire conditions.
• To quantify the impact of wildfire smoke on MDA8 levels in urban areas.
• To evaluate existing methods for attributing ozone to wildfire emissions.

Main Methods:

• Developed a statistical model to predict MDA8 for 8 U.S. cities under non-fire conditions, explaining 35-81% of variance.
• Analyzed model residuals on "smoke days" with elevated particulate matter (PM) and satellite-observed smoke.
• Compared results with a published method that ignores transport patterns.

Main Results:

• Statistical models explained 35-81% of MDA8 variance for typical conditions.
• Wildfire smoke days, though 4.1% of the study period, accounted for 19% of days with MDA8 > 75 ppb.
• Elevated MDA8 levels (3-8 ppb) were observed on smoke days compared to non-smoke days.
• A method ignoring transport patterns overestimated wildfire-attributed ozone, especially for coastal cities.

Conclusions:

• Wildfire smoke significantly contributes to high ozone events, necessitating improved modeling approaches.
• The developed statistical method accurately characterizes non-fire MDA8 and quantifies smoke impacts.
• The approach is applicable to regulatory guidance for excluding data affected by uncontrollable sources like wildfires.