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.
Subscribe to Journal
Get full journal access for 1 year
only $8.25 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
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/).
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.
Abatzoglou, J. T. & Williams, A. P. Impact of anthropogenic climate change on wildfire across western US forests. Proc. Natl Acad. Sci. USA 113, 11770–11775 (2016).
Dennison, P. E., Brewer, S. C., Arnold, J. D. & Moritz, M. A. Large wildfire trends in the western United States, 1984–2011. Geophys. Res. Lett. 41, 2928–2933 (2014).
Holden, Z. A. et al. Decreasing fire season precipitation increased recent western US forest wildfire activity. Proc. Natl Acad. Sci. USA 115, E8349 (2018).
Kitzberger, T., Falk, D. A., Westerling, A. L. & Swetnam, T. W. Direct and indirect climate controls predict heterogeneous early-mid 21st century wildfire burned area across western and boreal North America. PLoS ONE 12, e0188486 (2017).
Latif, M. T. et al. Southeast Asian forest fires (1997/1998): El Niño as a driver of regional impacts. Air Pollut. Epis. 6, 191–225 (2017).
Balch, J. K. et al. Human-started wildfires expand the fire niche across the United States. Proc. Natl Acad. Sci. USA 114, 2946–2951 (2017).
Radeloff, V. C. et al. Rapid growth of the US wildland–urban interface raises wildfire risk. Proc. Natl Acad. Sci. USA 115, 3314–3319 (2018).
Zhuang, J., Payyappalli, V. M., Behrendt, A. & Lukasiewicz, K. Total Cost of Fire in the United States (Fire Protection Research Foundation, 2017).
Shi, H. et al. Modeling study of the air quality impact of record-breaking Southern California wildfires in December 2017. J. Geophys. Res. Atmos. 124, 6554–6570 (2019).
Reid Colleen, E. et al. Critical review of health impacts of wildfire smoke exposure. Environ. Health Perspect. 124, 1334–1343 (2016).
Inoue, H. & Todo, Y. Firm-level propagation of shocks through supply-chain networks. Nat. Sustain. 2, 841–847 (2019).
Rose, A., Benavides, J., Chang, S. E., Szczesniak, P. & Lim, D. The regional economic impact of an earthquake: direct and indirect effects of electricity lifeline disruptions. J. Reg. Sci. 37, 437–458 (1997).
Johnston Fay, H. et al. Estimated global mortality attributable to smoke from landscape fires. Environ. Health Perspect. 120, 695–701 (2012).
2018 National Year-to-Date Report on Fires and Acres Burned (National Interagency Fire Center, 2018).
Faust, E. & Steuer, M. Climate change increases wildfire risk in California. Munich RE (26 March 2019); https://go.nature.com/35nKs2b
Randerson, J. T., Van Der Werf, G. R., Giglio, L., Collatz, G. J. & Kasibhatla, P. S. Global Fire Emissions Database Version 4.1 (GFEDv4) (ORNL Distributed Active Archive Center, 2017); https://doi.org/10.3334/ORNLDAAC/1293
Sacks, J. D. et al. The environmental benefits mapping and analysis program—community edition (BenMAP–CE): a tool to estimate the health and economic benefits of reducing air pollution. Environ. Model. Softw. 104, 118–129 (2018).
Hallegatte, S. An adaptive regional input–output model and its application to the assessment of the economic cost of Katrina. Risk Anal. 28, 779–799 (2008).
Hallegatte, S. Modeling the role of inventories and heterogeneity in the assessment of the economic costs of natural disasters. Risk Anal. 34, 152–167 (2014).
Guan, D. et al. Global supply-chain effects of COVID-19 control measures. Nat. Hum. Behav. 4, 577–587 (2020).
Shen, E., Oliver, A. & Dabirian, S. Final Socioeconomic Report Appendices to the 2016 Air Quality Management Plan (South Coast Air Quality Management District, 2017); https://go.nature.com/3ePpwEj
Davidson, K., Hallberg, A., McCubbin, D. & Hubbell, B. Analysis of PM2.5 using the environmental benefits mapping and analysis program (BenMAP). J. Toxicol. Environ. Health A 70, 332–346 (2007).
Benefits and Costs of the Clean Air Act 1990–2020, the Second Prospective Study (US Environmental Protection Agency, 2011); https://go.nature.com/3f3muwp
Jazebi, S., León, F. D. & Nelson, A. Review of wildfire management techniques—part I: causes, prevention, detection, suppression, and data analytics. IEEE Trans. Power Deliv. 35, 430–439 (2020).
Roberts, D. California’s deliberate blackouts were outrageous and harmful. They’re going to happen again. Vox (24 October 2019); https://go.nature.com/3lpnL34
Smith, A. E. & Gans, W. Enhancing the characterization of epistemic uncertainties in PM2.5 risk analyses. Risk Anal. 35, 361–378 (2015).
Xiao, Q., Chang, H. H., Geng, G. & Liu, Y. An ensemble machine-learning model to predict historical PM2.5 concentrations in China from satellite data. Environ. Sci. Technol. 52, 13260–13269 (2018).
Stowell, J. D. et al. Associations of wildfire smoke PM2.5 exposure with cardiorespiratory events in Colorado 2011–2014. Environ. Int. 133, 105151 (2019).
Lyapustin, A., Martonchik, J., Wang, Y., Laszlo, I. & Korkin, S. Multiangle implementation of atmospheric correction (MAIAC): 1. radiative transfer basis and look-up tables. J. Geophys. Res. Atmos. https://doi.org/10.1029/2010JD014985 (2011).
Lyapustin, A. et al. Multiangle implementation of atmospheric correction (MAIAC): 2. aerosol algorithm. J. Geophys. Res. Atmos. https://doi.org/10.1029/2010JD014986 (2011).
Chen, H., Goldberg, M. S. & Villeneuve, P. J. A systematic review of the relation between long-term exposure to ambient air pollution and chronic diseases. Rev. Environ. Health 23, 243–297 (2008).
Kampa, M. & Castanas, E. Human health effects of air pollution. Environ. Pollut. 151, 362–367 (2008).
Pascal, M. et al. Assessing the public health impacts of urban air pollution in 25 European cities: results of the Aphekom project. Sci. Total Environ. 449, 390–400 (2013).
Driscoll, C. T. et al. US power plant carbon standards and clean air and health co-benefits. Nat. Clim. Change 5, 535–540 (2015).
Zhu, S., Horne, J. R., Mac Kinnon, M., Samuelsen, G. S. & Dabdub, D. Comprehensively assessing the drivers of future air quality in California. Environ. Int. 125, 386–398 (2019).
Jones, B. A., Thacher, J. A., Chermak, J. M. & Berrens, R. P. Wildfire smoke health costs: a methods case study for a Southwestern US ‘mega-fire’. J. Environ. Econ. Policy 5, 181–199 (2016).
Jones, B. A. & Berrens, R. P. Application of an original wildfire smoke health cost benefits transfer protocol to the western US, 2005–2015. Environ. Manage. 60, 809–822 (2017).
Rose, A. N., McKee, J. J., Urban, M. L. & Bright, E. A. LandScan (Oak Ridge National Laboratory, 2018).
Marrison, H., Penn, S. & Roman, H. Review of Baseline Incidence Rate Estimates for Use in 2016 Socioeconomic Assessment (Industrial Economics, 2016); https://go.nature.com/36tSOEt
Literature Review of Air Pollution-Related Health Endpoints and Concentration–Response Functions for Particulate Matter: Results and Recommendations (Industrial Economics, 2016); https://go.nature.com/35n6cLg
Literature Review of Air Pollution-Related Health Endpoints and Concentration–Response Functions for Ozone, Nitrogen Dioxide, and Sulfur Dioxide: Results and Recommendations (Industrial Economics, 2016); https://go.nature.com/38xDWaY
Jerrett, M. et al. Spatial analysis of air pollution and mortality in California. Am. J. Respir. Crit. Care Med. 188, 593–599 (2013).
Krewski, D. et al. Extended follow-up and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality. Res. Rep. Health Eff. Inst. 140, 5–136 (2009).
Roman, H., Marrison, H. & Robinson, L. Review of Morbidity Valuation Estimates for Use in 2016 Socioeconomic Assessment (Industrial Economics, 2016); https://go.nature.com/2UmrmmF
Roman, H. & Robinson, L. Review of Mortality Risk Reduction Valuation Estimates for 2016 Socioeconomic Assessment (Industrial Economics, 2016); https://go.nature.com/32xA8mj
Robinson, L. A. & Hammitt, J. K. Valuing reductions in fatal illness risks: implications of recent research. Health Econ. 25, 1039–1052 (2016).
Allstate says losses from California fires $670M, CEO wants to address climate change. Insurance Journal (13 December 2018); https://go.nature.com/2GWG3K4
$8.6B worth of homes at high or extreme risk from California fires. Insurance Journal (16 November 2018); https://go.nature.com/3lnyCdK
Miller, R. E. & Blair, P. D. Input-Output Analysis: Foundations and Extensions 2nd edn (Cambridge Univ. Press, 2009).
Koks, E. E. & Thissen, M. A multiregional impact assessment model for disaster analysis. Economic Syst. Res. 28, 429–449 (2016).
Mintz, D. Technical Assistance Document for the Reporting of Daily Air Quality—the Air Quality Index (AQI) (US Environmental Protection Agency, 2018).
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).
The authors declare no competing interests.
Peer review information Nature Sustainability thanks the anonymous reviewers for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Figs. 1–11, Tables 1 and 5, and references.
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.
About this article
Cite this article
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
Consumption- and Income-Based Sectoral Emissions of Polycyclic Aromatic Hydrocarbons in China from 2002 to 2017
Environmental Science & Technology (2021)
SSRN Electronic Journal (2020)