Observational Constraints on the Aerosol Optical Depth–Surface PM2.5 Relationship during Alaskan Wildfire Seasons

Tianlang Zhao; Jingqiu Mao; Pawan Gupta; Huanxin Zhang; Jun Wang

doi:10.1021/acsestair.4c00120

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Observational Constraints on the Aerosol Optical Depth–Surface PM2.5 Relationship during Alaskan Wildfire Seasons

Journal article

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Observational Constraints on the Aerosol Optical Depth–Surface PM2.5 Relationship during Alaskan Wildfire Seasons

Tianlang Zhao, Jingqiu Mao, Pawan Gupta, Huanxin Zhang and Jun Wang

ACS ES&T Air, Vol.1(9), pp.1164-1176

09/13/2024

DOI: 10.1021/acsestair.4c00120

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https://pmc.ncbi.nlm.nih.gov/articles/PMC11407303/pdf/ea4c00120.pdfView

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Abstract

Wildfire is one of the main sources of PM2.5 (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 PM2.5 during wildfire season in Alaska. Here we aim at proposing a quick and direct method to estimate surface PM2.5 over Alaska, especially in places exposed to strong wildfire events with limited measurements. We compare the AOD–surface PM2.5 conversion factor (η = PM2.5/AOD; AOD, aerosol optical depth) from the chemical transport model GEOS-Chem (ηGC) and from observations (ηobs). We show that ηGC is biased high compared to ηobs 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 ηGC can be to some extent improved by increasing the injection height of wildfire emissions. We constructed a piecewise function for ηobs across different AOD ranges based on VIIRS-SNPP AOD and PurpleAir surface PM2.5 measurements over Alaska in the 2019 summer and then applied it on VIIRS AOD to derive daily surface PM2.5 over continental Alaska in the 2021 and 2022 summers. The derived satellite PM2.5 shows a good agreement with corrected PurpleAir PM2.5 in Alaska during the 2021 and 2022 summers, suggesting that aerosol vertical distribution likely represents the largest uncertainty in converting AOD to surface PM2.5 concentrations. This piecewise function, η′obs, shows the capability of providing an observation-based, quick and direct estimation of daily surface PM2.5 over the whole of Alaska during wildfires, without running a 3-D model in real time.

Alaska

CALIOP

low-cost sensor

VIIRS

PM2.5

wildfire smoke

Details

Title: Subtitle: Observational Constraints on the Aerosol Optical Depth–Surface PM2.5 Relationship during Alaskan Wildfire Seasons
Creators: Tianlang Zhao - University of Alaska Fairbanks
Jingqiu Mao - University of Alaska Fairbanks
Pawan Gupta - Goddard Space Flight Center
Huanxin Zhang - University of Iowa
Jun Wang - University of Iowa
Resource Type: Journal article
Publication Details: ACS ES&T Air, Vol.1(9), pp.1164-1176
DOI: 10.1021/acsestair.4c00120
ISSN: 2837-1402
eISSN: 2837-1402
Publisher: American Chemical Society
Number of pages: 13
Language: English
Date published: 09/13/2024
Academic Unit: Electrical and Computer Engineering; Civil and Environmental Engineering; Iowa Technology Institute; Physics and Astronomy; Chemical and Biochemical Engineering
Record Identifier: 9984704828602771

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