Articles | Volume 22, issue 12
https://doi.org/10.5194/nhess-22-4039-2022
https://doi.org/10.5194/nhess-22-4039-2022
Research article
 | 
20 Dec 2022
Research article |  | 20 Dec 2022

Statistical modelling of air quality impacts from individual forest fires in New South Wales, Australia

Michael A. Storey and Owen F. Price

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Cited articles

Biau, G. and Scornet, E.: A random forest guided tour, TEST, 25, 197–227, https://doi.org/10.1007/s11749-016-0481-7, 2016. 
Boer, M. M., Resco de Dios, V., and Bradstock, R. A.: Unprecedented burn area of Australian mega forest fires, Nat. Clim. Change, 10, 171–172, https://doi.org/10.1038/s41558-020-0716-1, 2020. 
Borchers-Arriagada, N., Bowman, D. M. J. S., Price, O., Palmer, A. J., Samson, S., Clarke, H., Sepulveda, G., and Johnston, F. H.: Smoke health costs and the calculus for wildfires fuel management: a modelling study, Lancet Planetary Health, 5, e608–e619, https://doi.org/10.1016/s2542-5196(21)00198-4, 2021. 
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Short summary
Models are needed to understand and predict pollutant output from forest fires so fire agencies can reduce smoke-related risks to human health. We modelled air quality (PM2.5) based on fire area and weather variables. We found fire area and boundary layer height were influential on predictions, with distance, temperature, wind speed and relative humidity also important. The models predicted reasonably accurately in comparison to other existing methods but would benefit from further development.
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