Estimating the global abundance of ground level presence of particulate matter (PM2.5)

  • David J. Lary | david.lary@utdallas.edu Hanson Center for Space Science, University of Texas at Dallas, Dallas, United States.
  • Fazlay S. Faruque GIS and Remote Sensing Program, University of Mississippi Medical Center, Jackson, United States.
  • Nabin Malakar Hanson Center for Space Science, University of Texas at Dallas, Dallas, United States.
  • Alex Moore Hanson Center for Space Science, University of Texas at Dallas, Dallas, United States.
  • Bryan Roscoe Hanson Center for Space Science, University of Texas at Dallas, Dallas, United States.
  • Zachary L. Adams Hanson Center for Space Science, University of Texas at Dallas, Dallas, United States.
  • York Eggelston Machine Data Learning Llc, Baltimore, United States.

Abstract

With the increasing awareness of the health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground level airborne particulate matter with a diameter of 2.5 microns or less (PM2.5). Here we use a suite of remote sensing and meteorological data products together with groundbased observations of particulate matter from 8,329 measurement sites in 55 countries taken 1997-2014 to train a machinelearning algorithm to estimate the daily distributions of PM2.5 from 1997 to the present. In this first paper of a series, we present the methodology and global average results from this period and demonstrate that the new PM2.5 data product can reliably represent global observations of PM2.5 for epidemiological studies.

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Published
2014-12-01
Info
Issue
Section
Original Articles
Keywords:
PM2.5, machine-learning, remote sensing
Statistics
  • Abstract views: 3400

  • PDF: 1418
How to Cite
Lary, D. J., Faruque, F. S., Malakar, N., Moore, A., Roscoe, B., Adams, Z. L., & Eggelston, Y. (2014). Estimating the global abundance of ground level presence of particulate matter (PM2.5). Geospatial Health, 8(3), S611-S630. https://doi.org/10.4081/gh.2014.292