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Economic footprint of California wildfires in 2018

Abstract

Recent increases in the frequency and scale of wildfires worldwide have raised concerns about the influence of climate change and associated socioeconomic costs. In the western United States, the hazard of wildfire has been increasing for decades. Here, we use a combination of physical, epidemiological and economic models to estimate the economic impacts of California wildfires in 2018, including the value of destroyed and damaged capital, the health costs related to air pollution exposure and indirect losses due to broader economic disruption cascading along with regional and national supply chains. Our estimation shows that wildfire damages in 2018 totalled $148.5 (126.1–192.9) billion (roughly 1.5% of California’s annual gross domestic product), with $27.7 billion (19%) in capital losses, $32.2 billion (22%) in health costs and $88.6 billion (59%) in indirect losses (all values in US$). Our results reveal that the majority of economic impacts related to California wildfires may be indirect and often affect industry sectors and locations distant from the fires (for example, 52% of the indirect losses—31% of total losses—in 2018 were outside of California). Our findings and methods provide new information for decision makers tasked with protecting lives and key production sectors and reducing the economic damages of future wildfires.

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Fig. 1: Air pollution due to fire emissions from July to December in California.
Fig. 2: Fire-related damages from the 2018 wildfires in California.
Fig. 3: Impacts of wildfires on specific industry sectors in California.

Data availability

Ground-level PM2.5 measurements for 2018 were obtained from US Environmental Protection Agency’s Air Quality System (https://www.epa.gov/outdoor-air-quality-data/); MAIAC AOD was downloaded from NASA Earthdata portal (https://search.earthdata.nasa.gov/); North American Land Data Assimilation Systems, elevation at 30 m spatial resolution is from the National Elevation Dataset (NED, http://ned.usgs.gov); forest cover, shrub cover and cultivated land cover at 30 m spatial resolution is from the 2011 National Land Cover Database (NLCD, http://www.mrlc.gov); road lengths of major roads, highways and interstate highways was extracted from ESRI StreetMap USA (Environmental Systems Research Institute); the population data are from 2017 LandScan data (https://landscan.ornl.gov/downloads/2017); wildland fire information is from the National Interagency Fire Center (National Large Incident Year-to-Date Report 2018), CAL FIRE (https://www.fire.ca.gov/); the county-level input–output table and trade-flow data between counties are from IMPLAN (https://implan.com/data/).

Code availability

The simulation code for the indirect economic costs can be accessed at https://github.com/DaopingW/Disaster-Footprint-Model. The minimal input for the code is the multiregional input–output table. The sample code and test data for the minimal inputs are also provided.

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Acknowledgements

We acknowledge the heroic efforts and sacrifices of the men and women who have fought California wildfires in recent years. This study was supported by the National Natural Science Foundation of China (41921005) and National Key R&D Program of China (2016YFA0602604). D.W. acknowledges support from the Fundamental Research Funds for the Central Universities (CXJJ-2020-301). D.G. acknowledges support from the National Natural Science Foundation of China (91846301 and 41629501), the UK Natural Environment Research Council (NE/N00714X/1 and NE/P019900/1), the Economic and Social Research Council (ES/L016028/1) and British Academy (NAFR2180103). S.S. acknowledges support from the National Natural Science Foundation of China (71922015 and 71773075). S.J.D. and M.M.K. acknowledge support from the US National Science Foundation and US Department of Agriculture (INFEWS grant EAR-1639318).

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Authors

Contributions

D.G. and S.J.D. designed the study. D.W., S.Z., G.G. and M.M.K. performed the analysis. D.G., S.J.D. and D.W. interpreted the results. D.W., S.J.D. and T.L. prepared the figures. D.W., S.J.D., D.G., S.Z. and G.G. prepared the manuscript. D.W., S.Z., G.G., T.L. and H.Z. prepared the supplementary information. D.G. coordinated and Q.Z., and P.G. supervised the project. Q.Z., S.S. and P.G. participated in the writing of the manuscript.

Corresponding author

Correspondence to Dabo Guan.

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The authors declare no competing interests.

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Peer review information Nature Sustainability thanks the anonymous reviewers for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–11, Tables 1 and 5, and references.

Supplementary Data 1

Supplementary Table 2: Damages of 2018 wildfires on 58 counties and RUS. Supplementary Table 3: Damages of 2018 wildfires on 80 industrial sectors and households. Supplementary Table 4: 80 industrial sectors in the multiregional input–output table.

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Wang, D., Guan, D., Zhu, S. et al. Economic footprint of California wildfires in 2018. Nat Sustain 4, 252–260 (2021). https://doi.org/10.1038/s41893-020-00646-7

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