Abstract

Abstract. Wildfires and their 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 low concentrations due to the presence of the usual array of anthropogenic pollutants. Here we propose a method using the difference in PM2.5 to CO emission ratios between smoke and typical urban pollution. For temperate wildfires, the mean emission ratio of PM2.5 to CO is in the range of 0.14–0.18 g PM2.5 g CO−1, whereas typical urban emissions have a PM2.5 to CO emissions ratio that is lower by a factor of 2–20. This gives rise to the possibility of using this ratio as an indicator of wildfire smoke. We use observations at a regulatory surface monitoring site in Sparks, NV, for the period of May–September 2018–2021. There were many smoke-influenced periods from numerous California wildfires that burned during this period. Using a PM2.5 / CO threshold of 30.0 µgm-3ppm-1, we can split the observations 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 µgm-3ppm-1 best fits the observations, which is significantly lower than the ratio observed in fresh smoke plumes (e.g., 200–300 µgm-3ppm-1). The most likely explanation for this difference is 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.

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