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

Wildfires emit O precursors but there are large variations in emissions, plume heights, and photochemical processing. These factors make it challenging to model O production from wildfires using Eulerian models. Here we describe a statistical approach to characterize the maximum daily 8-h average O (MDA8) for 8 cities in the U.S. for typical, nonfire, conditions. The statistical model represents between 35% and 81% of the variance in MDA8 for each city. We then examine the residual from the model under conditions with elevated particulate matter (PM) and satellite observed smoke ("smoke days"). For these days, the residuals are elevated by an average of 3-8 ppb (MDA8) compared to nonsmoke days. We found that while smoke days are only 4.1% of all days (May-Sept) they are 19% of days with an MDA8 greater than 75 ppb. We also show that a published method that does not account for transport patterns gives rise to large overestimates in the amount of O from fires, particularly for coastal cities. Finally, we apply this method to a case study from August 2015, and show that the method gives results that are directly applicable to the EPA guidance on excluding data due to an uncontrollable source.