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

Abstract

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 (PM2.5) 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 PM2.5, 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 PM2.5 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 PM2.5 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 andmore » 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 PM2.5 . Inclusion of aerosol radiative feedback moderately improves PM2.5 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.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [1]
  1. California Institute of Technology (CalTech), Pasadena, CA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Univ. of California, Los Angeles, CA (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE; National Aeronautics and Space Administration (NASA)
OSTI Identifier:
1735695
Report Number(s):
PNNL-SA-157124
Journal ID: ISSN 1680-7324
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 20; Journal Issue: 23; Journal ID: ISSN 1680-7324
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Rooney, Brigitte, Wang, Yuan, Jiang, Jonathan H., Zhao, Bin, Zeng, Zhao-Cheng, and Seinfeld, John H.. Air quality impact of the Northern California Camp Fire of November 2018. United States: N. p., 2020. Web. https://doi.org/10.5194/acp-20-14597-2020.
Rooney, Brigitte, Wang, Yuan, Jiang, Jonathan H., Zhao, Bin, Zeng, Zhao-Cheng, & Seinfeld, John H.. Air quality impact of the Northern California Camp Fire of November 2018. United States. https://doi.org/10.5194/acp-20-14597-2020
Rooney, Brigitte, Wang, Yuan, Jiang, Jonathan H., Zhao, Bin, Zeng, Zhao-Cheng, and Seinfeld, John H.. Tue . "Air quality impact of the Northern California Camp Fire of November 2018". United States. https://doi.org/10.5194/acp-20-14597-2020. https://www.osti.gov/servlets/purl/1735695.
@article{osti_1735695,
title = {Air quality impact of the Northern California Camp Fire of November 2018},
author = {Rooney, Brigitte and Wang, Yuan and Jiang, Jonathan H. and Zhao, Bin and Zeng, Zhao-Cheng and Seinfeld, John H.},
abstractNote = {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 (PM2.5) 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 PM2.5, 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 PM2.5 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 PM2.5 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 PM2.5 . Inclusion of aerosol radiative feedback moderately improves PM2.5 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.},
doi = {10.5194/acp-20-14597-2020},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 23,
volume = 20,
place = {United States},
year = {2020},
month = {12}
}

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