Uncertainties from biomass burning aerosols in air quality models obscure public health impacts in Southeast Asia

Marvin, Margaret R. and Palmer, Paul I. and Yao, Fei and Latif, Mohd Talib and Khan, Md Firoz (2024) Uncertainties from biomass burning aerosols in air quality models obscure public health impacts in Southeast Asia. Atmospheric Chemistry and Physics, 24 (6). pp. 3699-3715. ISSN 1680-7316, DOI https://doi.org/10.5194/acp-24-3699-2024.

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Official URL: https://doi.org/10.5194/acp-24-3699-2024

Abstract

Models suggest that biomass burning causes thousands of premature deaths annually in Southeast Asia due to excessive exposure to particulate matter (PM) in smoke. However, measurements of surface air quality are sparse across the region, and consequently estimates for the public health impacts of seasonal biomass burning, are not well constrained. We use the nested GEOS-Chem model of chemistry and transport (horizontal resolution of 0.25 degrees x 0.3125 degrees ) to simulate atmospheric composition over Southeast Asia during the peak burning months of March and September in the moderate burning year of 2014. Model simulations with GEOS-Chem indicate that regional surface levels of PM 2.5 (fine particulate matter with a diameter <= 2.5 mu m) greatly exceed World Health Organization guidelines during the burning seasons, resulting in up to 10 000 premature deaths in a single month. However, the model substantially underestimates the regional aerosol burden compared to satellite observations of aerosol optical depth (AOD) (20 %-52 %) and ground-based observations of PM (up to 54 %), especially during the early burning season in March. We investigate potential uncertainties limiting the model representation of biomass burning aerosols and develop sensitivity simulations that improve model-measurement agreement in March (to within 31 %) and increase the estimated number of PM 2.5 -related premature deaths that month by almost half. Our modifications have a much smaller impact on the same metrics for September, but we find that this is due to canceling errors in the model. Compared to PM 2.5 simulated directly with GEOS-Chem, PM 2.5 derived from satellite AOD is less sensitive to model uncertainties and may provide a more accurate foundation for public health calculations in the short term, but continued investigation of uncertainties is still needed so that model analysis can be applied to support mitigation efforts. Further reduction of uncertainties can be achieved with the deployment of more aerosol measurements across Southeast Asia.

Item Type: Article
Funders: UK Research & Innovation (UKRI) Natural Environment Research Council (NERC), Department of Environment, Ministry of Natural Resources, Environment and Climate Change, Malaysia
Uncontrolled Keywords: Optical Depth; Organic Aerosol; Emission Factors; Fire Activity; Time-Series; Trace Gases; Peat Fires; PM2.5; Field; Sensitivity
Subjects: Q Science > Q Science (General)
Q Science > QE Geology
S Agriculture > S Agriculture (General)
Divisions: Faculty of Science > Department of Chemistry
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 21 Oct 2024 03:41
Last Modified: 21 Oct 2024 03:41
URI: http://eprints.um.edu.my/id/eprint/45409

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