Satellite-Based Spatiotemporal Trends in PM2.5 Concentrations: China, 2004-2013.

• Type of Material: Article
• Authors: Zongwei Ma, Emory University; Xuefei Hu, Emory University; Andrew M. Sayer, Universities Space Research Association; Robert Levy, NASA Goddard Space Flight Center; Qiang Zhang, Tsinghua University; Yingang Xue, Changzhou Environmental Monitoring Center; Shilu Tong, Queensland University of Technology; Jun Bi, Nanjing University; Lei Huang, Nanjing University; Yang Liu, Emory University
• Language: English
• Date: 2016-02
• Publisher: National Institute of Environmental Health Sciences (NIEHS)
• Publication Version: Final Published Version
• Copyright Statement: Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, “Reproduced with permission from Environmental Health Perspectives”); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
• Final Published Version (URL): http://dx.doi.org/10.1289/ehp.1409481
• Title of Journal or Parent Work: Environmental Health Perspectives
• ISSN: 0091-6765
• Volume: 124
• Issue: 2
• Start Page: 184
• End Page: 192
• Grant/Funding Information: The work of L.H. and J.B. was partially supported by the Key Program of the Chinese National Natural Science Foundation (71433007) and the National High-tech R&D Program (863 Program) of China (2013AA06A309).; The work of Z.M. was supported by the China Scholarship Council (CSC).; This publication was made possible by U.S. Environmental Protection Agency (EPA) grant R834799.; The work of Y.L. was partially supported by the NASA Applied Sciences Program (grant NNX11AI53G).
• Research Categories: Health Sciences, Public Health; Environmental Sciences; Statistics

Abstract

BACKGROUND: Three decades of rapid economic development is causing severe and widespread PM2.5 (particulate matter ≤ 2.5 μm) pollution in China. However, research on the health impacts of PM2.5 exposure has been hindered by limited historical PM2.5 concentration data. OBJECTIVES: We estimated ambient PM2.5 concentrations from 2004 to 2013 in China at 0.1° resolution using the most recent satellite data and evaluated model performance with available ground observations. METHODS: We developed a two-stage spatial statistical model using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) and assimilated meteorology, land use data, and PM2.5 concentrations from China's recently established ground monitoring network. An inverse variance weighting (IVW) approach was developed to combine MODIS Dark Target and Deep Blue AOD to optimize data coverage. We evaluated model-predicted PM2.5 concentrations from 2004 to early 2014 using ground observations. RESULTS: The overall model cross-validation R2 and relative prediction error were 0.79 and 35.6%, respectively. Validation beyond the model year (2013) indicated that it accurately predicted PM2.5 concentrations with little bias at the monthly (R2 = 0.73, regression slope = 0.91) and seasonal (R2 = 0.79, regression slope = 0.92) levels. Seasonal variations revealed that winter was the most polluted season and that summer was the cleanest season. Analysis of predicted PM2.5 levels showed a mean annual increase of 1.97 μg/m3 between 2004 and 2007 and a decrease of 0.46 μg/m3 between 2008 and 2013. CONCLUSIONS: Our satellite-driven model can provide reliable historical PM2.5 estimates in China at a resolution comparable to those used in epidemiologic studies on the health effects of long-term PM2.5 exposure in North America. This data source can potentially advance research on PM2.5 health effects in China.