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Published December 1, 2020 | Published
Journal Article Open

Air quality impact of the Northern California Camp Fire of November 2018


The Northern California Camp Fire that took place in November 2018 was one of the most damaging environmental events in California history. Here, we analyze ground-based station observations of airborne particulate matter that has a diameter <2.5 µm (PM_(2.5)) across Northern California and conduct numerical simulations of the Camp Fire using the Weather Research and Forecasting model online coupled with chemistry (WRF-Chem). Simulations are evaluated against ground-based observations of PM_(2.5), black carbon, and meteorology, as well as satellite measurements, such as Tropospheric Monitoring Instrument (TROPOMI) aerosol layer height and aerosol index. The Camp Fire led to an increase in Bay Area PM_(2.5) to over 50 µg m⁻³ for nearly 2 weeks, with localized peaks exceeding 300 µg m⁻³. Using the Visible Infrared Imaging Radiometer Suite (VIIRS) high-resolution fire detection products, the simulations reproduce the magnitude and evolution of surface PM_(2.5) concentrations, especially downwind of the wildfire. The overall spatial patterns of simulated aerosol plumes and their heights are comparable with the latest satellite products from TROPOMI. WRF-Chem sensitivity simulations are carried out to analyze uncertainties that arise from fire emissions, meteorological conditions, feedback of aerosol radiative effects on meteorology, and various physical parameterizations, including the planetary boundary layer model and the plume rise model. Downwind PM2.5 concentrations are sensitive to both flaming and smoldering emissions over the fire, so the uncertainty in the satellite-derived fire emission products can directly affect the air pollution simulations downwind. Our analysis also shows the importance of land surface and boundary layer parameterization in the fire simulation, which can result in large variations in magnitude and trend of surface PM_(2.5). Inclusion of aerosol radiative feedback moderately improves PM_(2.5) simulations, especially over the most polluted days. Results of this study can assist in the development of data assimilation systems as well as air quality forecasting of health exposures and economic impact studies.

Additional Information

© Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. Received: 03 Jun 2020 – Discussion started: 08 Jul 2020 – Revised: 20 Sep 2020 – Accepted: 30 Sep 2020 – Published: 01 Dec 2020. This study was supported by the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. We thank Kristal R. Verhulst, Yi Yin, Don Longo, Gonzalo Ferrada, and Saulo Freitas for their support and discussion. Code availability: WRF-Chem model code is available for download via the WRF website (https://www2.mmm.ucar.edu/wrf/users/downloads.html, last access: June 2018). Data availability: US Environmental Protection Agency Air Quality System Data Mart (internet database) is available for download (https://www.epa.gov/airdata, last access: June 2019). NCDC data are available for download via the NCEI website (https://www.ncei.noaa.gov/metadata/geoportal/rest/metadata/item/gov.noaa.ncdc:C00684/html#, last access: June 2019). TROPOMI data are available for download via the Copernicus Open Access Hub website (https://scihub.copernicus.eu/, last access: October 2019). ERA5 data are available for download via the Copernicus Climate Data Store website (https://cds.climate.copernicus.eu/, last access: March 2019). FINN emission data are available for download via the NCAR Atmospheric Chemistry Observations and Modeling website (http://bai.acom.ucar.edu/Data/fire, last access: January 2020). Author contributions: YW, JHS, and JHJ conceived and designed the research. YW and BR performed the WRF-Chem simulations. BR, YW, and JHS performed the data analyses and produced the figures. BZ provided technical support for fire emission preparation. ZCZ helped satellite data analyses. BR, YW, and JHS wrote the paper. All authors contributed to the scientific discussions and preparation of the manuscript. The authors declare that they have no conflict of interest. This study has been supported by the AQ-SRTD project at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA, and the NASA ACMAP, CCST, and TASNPP programs. Review statement: This paper was edited by Joshua Fu and reviewed by two anonymous referees.

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