Examining the Effects of Parameterized Changes in Biomass Burning NO x Emissions on Forecasted Air Quality

Abstract Climate change has led to an increase in the number and size of wildfires in western North America, and their emissions of particulate matter and reactive trace gases threaten to offset otherwise improving air quality. Most air quality models do not dynamically update the chemical composition of biomass burning emissions with each model time step. However, laboratory, field, and satellite remote sensing observations indicate that the chemical composition of wildfire emissions changes with evolving combustion conditions (i.e., flaming vs. smoldering). We have previously shown that the Tropospheric Monitoring Instrument (TROPOMI) can be used to observe day‐to‐day changes in the chemical composition of wildfire emissions, during the transition from flaming to smoldering combustion. Here, we present the use of the Hourly Wildfire Potential index (HWP) to predict the impact of meteorological changes on wildfire activity, combined with TROPOMI observations of enhanced nitrogen dioxide emissions compared with that of carbon monoxide (/CO), to parameterize how biomass burning nitrogen oxide () emissions change with evolving combustion conditions. We implemented this parameterization in the High‐Resolution Rapid Refresh model coupled with Chemistry (HRRR‐Chem), developed by National Oceanic and Atmospheric Administration's Global Systems Laboratory. HRRR‐Chem is an experimental, high‐resolution chemical transport model with 3 × 3 horizontal grid spacing over the contiguous US, based on the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem). We compared modeled smoke and trace gases with airborne measurements to evaluate our model. Overall, we found that modifying biomass burning emissions based on HWP significantly improved predicted ozone concentrations in smoke plumes.