Estimating Wildfire Smoke Concentrations During the October 2017 California Fires Through BME Space/Time Data Fusion of Observed, Modeled, and Satellite-Derived PM2.5

Details

• Personal Author:
  Cleland SE ; Jia Y ; O'Neill S ; Raffuse S ; Reid S ; Serre ML ; West JJ
• Description:
  Exposure to wildfire smoke causes adverse health outcomes, suggesting the importance of accurately estimating smoke concentrations. Geostatistical methods can combine observed, modeled, and satellite-derived concentrations to produce accurate estimates. Here, we estimate daily average ground-level PM2.5 concentrations at a 1 km resolution during the October 2017 California wildfires, using the Constant Air Quality Model Performance (CAMP) and Bayesian Maximum Entropy (BME) methods to bias-correct and fuse three concentration datasets: permanent and temporary monitoring stations, a chemical transport model (CTM), and satellite-derived estimates. Four BME space/time kriging and data fusion methods were evaluated. All BME methods produce more accurate estimates than the standalone CTM and satellite products. Adding temporary station data increases the R2 by 36%. The data fusion of observations with the CAMP-corrected CTM and satellite-derived concentrations provides the best estimate (R2 = 0.713) in fire-impacted regions, emphasizing the importance of combining multiple datasets. We estimate that approximately 65,000 people were exposed to very unhealthy air (daily average PM2.5 >/= 150.5 microg/m3). [Description provided by NIOSH]
• Subjects:
  Air Pollutants, Occupational Air Pollution Dust Environmental Exposure Environmental Monitoring Fires Occupational Health Particulate Matter Safety Wildfires
• Keywords:
  Airborne Particulates Air Contaminants Air Quality Monitoring Analytical Methods Environmental Exposure Environmental Monitoring Exposure Assessment Geostatistics Particulate Dust
• ISSN:
  0013-936X
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  California ; North Carolina ; OSHA Region 10 ; OSHA Region 4 ; OSHA Region 9 ; Washington
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  54
• Issue:
  21
• NIOSHTIC Number:
  nn:20062007
• Citation:
  Environ Sci Technol 2020 Nov; 54(21):13439-13447
• Contact Point Address:
  Marc L. Serre, Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina 27599, United States
• Email:
  marc_serre@unc.edu
• Federal Fiscal Year:
  2021
• Performing Organization:
  University of North Carolina, Chapel Hill
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Environmental Science and Technology
• End Date:
  20270630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:1c2581759ee0612843fae36b5ee84a50e69b97d02ef0494db235c3c291a61110cbb30a8b8f7bf315dcb068506857e1f0f0018abef42e1b75ac7a1404ba6d3c28
• Download URL:
  https://stacks.cdc.gov/view/cdc/225334/cdc_225334_DS1.pdf
• File Type:
  [PDF - 3.19 MB ]