A machine learning method to estimate PM concentrations across China with remote sensing, meteorological and land use information.

Journal: The Science of the total environment
Published Date: Apr 25, 2018

Abstract

BACKGROUND: Machine learning algorithms have very high predictive ability. However, no study has used machine learning to estimate historical concentrations of PM (particulate matter with aerodynamic diameter ≤ 2.5 μm) at daily time scale in China at a national level.

Authors

  • Gongbo Chen
    Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
  • Shanshan Li
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Luke D Knibbs
    Department of Epidemiology and Biostatistics, School of Public Health, The University of Queensland, Brisbane, Australia.
  • N A S Hamm
    Geospatial Research Group and School of Geographical Sciences, Faculty of Science and Engineering, University of Nottingham, Ningbo, China.
  • Wei Cao
    Collaborative Innovation Center for Green Chemical Manufacturing and Accurate Detection, Key Laboratory of Interfacial Reaction & Sensing Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, PR China.
  • Tiantian Li
    China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, People's Republic of China.
  • Jianping Guo
    Department of Cardiology, Brigham and Women's Hospital, Boston, Massachusetts.
  • Hongyan Ren
    Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
  • Michael J Abramson
    Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
  • Yuming Guo
    Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia. Electronic address: yuming.guo@monash.edu.

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