Comment on acp-2022-138

Abstract

Wildfires, and the resulting smoke, are an increasing problem in many regions of the world. However, identifying the contribution of smoke to pollutant loadings in urban regions can be challenging at lower concentrations due to the presence of the usual array of anthropogenic pollutants. Here we propose a method using the difference in PM to CO emission ratios between smoke and typical urban pollution. For smoke, emission ratios of PM2.5 to CO are between 200–300 µg m−3 ppb−1, whereas typical urban sources have an emission ratio that is lower by a factor of 4–10. This gives rise to the possibility of using this ratio as an indicator of smoke extent. We use observations a regulatory surface monitoring sites in Sparks, NV, for the period of May–September 2018–2021. During this time, there were many smoke-influenced periods from numerous California wildfires that burned during this period. Using a PM / CO ratio of 30, we can split the data into smoke-influenced and no-smoke periods. We then develop a Monte Carlo simulation, tuned to local conditions, to derive a set of PM2.5 / CO values that can be used to identify smoke influence in urban areas. From the simulation, we find that a smoke enhancement ratio of 140 µg m−3 ppb−1 best fits the observations, which is significantly lower than the ratio observed in fresh smoke plumes. The most likely explanation for this difference is greater loss of PM2.5 during dilution and transport to warmer surface layers. We find that the PM2.5 / CO ratio in urban areas is an excellent indicator of smoke and should prove to be useful to identify biomass burning influence on the policy relevant concentrations of both PM2.5 and O3. Using the results of our Monte Carlo simulation, this ratio can also quantify the influence of smoke on urban PM2.5.