Enhancing fire emissions inventories for acute health effects studies: integrating high spatial and temporal resolution data

Sam D. Faulstich; Matthew J. Strickland; Heather A. Holmes

doi:10.1071/WF24040

RESEARCH ARTICLE (Open Access)

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Enhancing fire emissions inventories for acute health effects studies: integrating high spatial and temporal resolution data

Sam D. Faulstich

^A ^* , Matthew J. Strickland ^B and Heather A. Holmes ^A

+ Author Affiliations

- Author Affiliations

^A Department of Chemical Engineering, University of Utah, Salt Lake City, UT, USA.

^B School of Public Health, University of Nevada, Reno, NV, USA.

^* Correspondence to: sam.faulstich@utah.edu

International Journal of Wildland Fire 34, WF24040 https://doi.org/10.1071/WF24040

Submitted: 2 March 2024 Accepted: 21 January 2025 Published: 20 February 2025

© 2025 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Background

Daily fire progression information is crucial for public health studies that examine the relationship between population-level smoke exposures and subsequent health events. Issues with remote sensing used in fire emissions inventories (FEI) lead to the possibility of missed exposures that impact the results of acute health effects studies.

Aims

This paper provides a method for improving an FEI dataset with readily available information to create a more robust dataset with daily fire progression.

Methods

High temporal and spatial resolution burned area information from two FEI products are combined into a single dataset, and a linear regression model fills gaps in daily fire progression.

Key results

The combined dataset provides up to 71% more PM_2.5 emissions, 69% more burned area, and 367% more fire days per year than using a single source of burned area information.

Conclusions

The FEI combination method results in improved FEI information with no gaps in daily fire emissions estimates.

Implications

The combined dataset provides a functional improvement to FEI data that can be achieved with currently available data.

Keywords: acute health effects studies, burned area, cloud cover, environmental epidemiology, exposure modelling, fire remote sensing, PM_2.5, wildfire smoke exposure, wildfire smoke transport.

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