Observational Constraints on the Aerosol Optical Depth-Surface PM 2.5 Relationship during Alaskan Wildfire Seasons.

Wildfire is one of the main sources of PM 2.5 (particulate matter with aerodynamic diameter < 2.5 μm) in the Alaskan summer. The complexity in wildfire smokes, as well as limited coverage of ground measurements, poses a big challenge to estimate surface PM 2.5 during wildfire season in Alaska. Here we aim at proposing a quick and direct method to estimate surface PM 2.5 over Alaska, especially in places exposed to strong wildfire events with limited measurements. We compare the AOD-surface PM 2.5 conversion factor (η = PM 2.5 /AOD; AOD, aerosol optical depth) from the chemical transport model GEOS-Chem (η GC ) and from observations (η obs ). We show that η GC is biased high compared to η obs under smoky conditions, largely because GEOS-Chem assigns the majority of AOD (67%) within the planetary boundary layer (PBL) when AOD > 1, inconsistent with satellite retrievals from CALIOP. The overestimation in η GC can be to some extent improved by increasing the injection height of wildfire emissions. We constructed a piecewise function for η obs across different AOD ranges based on VIIRS-SNPP AOD and PurpleAir surface PM 2.5 measurements over Alaska in the 2019 summer and then applied it on VIIRS AOD to derive daily surface PM 2.5 over continental Alaska in the 2021 and 2022 summers. The derived satellite PM 2.5 shows a good agreement with corrected PurpleAir PM 2.5 in Alaska during the 2021 and 2022 summers, suggesting that aerosol vertical distribution likely represents the largest uncertainty in converting AOD to surface PM 2.5 concentrations. This piecewise function, η' obs , shows the capability of providing an observation-based, quick and direct estimation of daily surface PM 2.5 over the whole of Alaska during wildfires, without running a 3-D model in real time.