Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA

David J Diner; Stacey W Boland; Michael Brauer; Carol Bruegge; Kevin A Burke; Russell Chipman; Larry Di Girolamo; Michael J Garay; Sina Hasheminassab; Edward Hyer; Michael Jerrett; Veljko Jovanovic; Olga V Kalashnikova; Yang Liu; Alexei I Lyapustin; Randall V Martin; Abigail Nastan; Bart D Ostro; Beate Ritz; Joel Schwartz; Jun Wang; Feng Xu

doi:10.1117/1.JRS.12.042603

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Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA

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Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA

David J Diner, Stacey W Boland, Michael Brauer, Carol Bruegge, Kevin A Burke, Russell Chipman, Larry Di Girolamo, Michael J Garay, Sina Hasheminassab, Edward Hyer, …

Journal of applied remote sensing, Vol.12(4), pp.042603-042603

10/01/2018

DOI: 10.1117/1.JRS.12.042603

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Abstract

Inhalation of airborne particulate matter (PM) is associated with a variety of adverse health outcomes. However, the relative toxicity of specific PM types-mixtures of particles of varying sizes, shapes, and chemical compositions-is not well understood. A major impediment has been the sparse distribution of surface sensors, especially those measuring speciated PM. Aerosol remote sensing from Earth orbit offers the opportunity to improve our understanding of the health risks associated with different particle types and sources. The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard NASA's Terra satellite has demonstrated the value of near-simultaneous observations of backscattered sunlight from multiple view angles for remote sensing of aerosol abundances and particle properties over land. The Multi-Angle Imager for Aerosols (MAIA) instrument, currently in development, improves on MISR's sensitivity to airborne particle composition by incorporating polarimetry and expanded spectral range. Spatiotemporal regression relationships generated using collocated surface monitor and chemical transport model data will be used to convert fractional aerosol optical depths retrieved from MAIA observations to near-surface PM10, PM2.5, and speciated PM2.5. Health scientists on the MAIA team will use the resulting exposure estimates over globally distributed target areas to investigate the association of particle species with population health effects.

Remote Sensing

particulate matter

aerosols

human health

Details

Title: Subtitle: Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA
Creators: David J Diner - aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Stacey W Boland - aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Michael Brauer - bUniversity of British Columbia, School of Population and Public Health, Vancouver, British Columbia, Canada
Carol Bruegge - aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Kevin A Burke - aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Russell Chipman - cUniversity of Arizona, College of Optical Sciences, Tucson, Arizona, United States
Larry Di Girolamo - dUniversity of Illinois Urbana-Champaign, Department of Atmospheric Science, Urbana, Illinois, United States
Michael J Garay - aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Sina Hasheminassab - eSouth Coast Air Quality Management District, Diamond Bar, California, United States
Edward Hyer - fNaval Research Laboratory, Marine Meteorology Division, Monterey, California, United States
Michael Jerrett - gUniversity of California Los Angeles, Fielding School of Public Health, Los Angeles, California, United States
Veljko Jovanovic - aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Olga V Kalashnikova - aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Yang Liu - hEmory University, Rollins School of Public Health, Atlanta, Georgia, United States
Alexei I Lyapustin - iNASA Goddard Space Flight Center, Climate and Radiation Laboratory, Greenbelt, Maryland, United States
Randall V Martin - kSmithsonian Astrophysical Observatory, Cambridge, Massachusetts, United States
Abigail Nastan - aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Bart D Ostro - lUniversity of California Davis, Air Quality Research Center, Davis, California, United States
Beate Ritz - gUniversity of California Los Angeles, Fielding School of Public Health, Los Angeles, California, United States
Joel Schwartz - mHarvard University, Department of Epidemiology, Boston, Massachusetts, United States
Jun Wang - nUniversity of Iowa, College of Engineering, Iowa City, Iowa, United States
Feng Xu - aJet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States
Resource Type: Journal article
Publication Details: Journal of applied remote sensing, Vol.12(4), pp.042603-042603
DOI: 10.1117/1.JRS.12.042603
ISSN: 1931-3195
eISSN: 1931-3195
Publisher: Society of Photo-Optical Instrumentation Engineers
Grant note: National Aeronautics and Space Administration (NASA) (https://doi.org/10.13039/100000104)
Language: English
Date published: 10/01/2018
Academic Unit: Electrical and Computer Engineering; Civil and Environmental Engineering; Physics and Astronomy; Chemical and Biochemical Engineering
Record Identifier: 9984104811702771

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