PM2.5 in China: Measurements, sources, visibility and health effects, and mitigation

David Y.H. Pui, Sheng Chieh Chen, Zhili Zuo

Research output: Contribution to journalReview articlepeer-review

461 Scopus citations

Abstract

Concern over the health effects of fine particles in the ambient environment led the U.S. Environmental Protection Agency to develop the first standard for PM2.5 (particulate matter less than 2.5 μm) in 1997. The Particle Technology Laboratory at the University of Minnesota has helped to establish the PM2.5 standard by developing many instruments and samplers to perform atmospheric measurements. In this paper, we review various aspects of PM2.5, including its measurement, source apportionment, visibility and health effects, and mitigation. We focus on PM2.5 studies in China and where appropriate, compare them with those obtained in the U.S. Based on accurate PM2.5 sampling, chemical analysis, and source apportionment models, the major PM2.5 sources in China have been identified to be coal combustion, motor vehicle emissions, and industrial sources. Atmospheric visibility has been found to correlate well with PM 2.5 concentration. Sulfate, ammonium, and nitrate carried by PM 2.5, commonly found in coal burning and vehicle emissions, are the dominant contributors to regional haze in China. Short-term exposure to PM 2.5 is strongly associated with the increased risk of morbidity and mortality from cardiovascular and respiratory diseases in China. The strategy for PM2.5 mitigation must be based on reducing the pollutants from the two primary sources of coal-fired power plants and vehicle emissions. Although conventional Particulate Emission Control Devices (PECD) such as electrostatic precipitators in Chinese coal-fired power plants are generally effective for large particles, most of them may not have high collection efficiency of PM2.5. Baghouse filtration is gradually incorporated into the PECD to increase the PM2.5 collection efficiency. By adopting stringent vehicle emissions standard such as Euro 5 and 6, the emissions from vehicles can be gradually reduced over the years. An integrative approach, from collaboration among academia, government, and industries, can effectively manage and mitigate the PM2.5 pollution in China.

Original languageEnglish (US)
Pages (from-to)1-26
Number of pages26
JournalParticuology
Volume13
Issue number1
DOIs
StatePublished - Apr 2014

Bibliographical note

Funding Information:
This review/perspective paper provided the background for the Einstein Professorship Lecture given by David Y.H. Pui in China during May–July, 2013. We appreciated the helpful discussions with Prof. Junji Cao of the Institute of Earth Environment of the Chinese Academy of Sciences, Prof. Jingxian Liu of the China Northeastern University, Prof. Guangbiao Zhou of the Institute of Zoology of the Chinese Academy of Sciences, Dr. William E. Wilson, formerly Senior Physical Science Advisor, National Center for Environmental Assessment, U.S. Environmental Protection Agency (USEPA), and former students/colleagues Prof. Da-Ren Chen of the Virginia Commonwealth University (U.S.), Prof. Chuen-Jinn Tsai of the National Chiao Tung University (Taiwan, China), Prof. Jing Wang of ETH Zurich (Switzerland), and Dr. Christof Asbach of Institut fuer Energie- und Umwelttechnik e.V. (Germany). The authors thank the support of members of the Center for Filtration Research (CFR) at the University of Minnesota: 3M Corporation, Boeing Commercial Airplanes, Cummins Filtration Inc., Donaldson Company, Inc., Entegris, Inc., Ford Motor Co., W.L. Gore & Associates, Inc., Hollingsworth & Vose Company, MANN + HUMMEL GMBH, MSP Corporation, Samsung Electronics Co., Ltd., Shigematsu Works Co., Ltd., and TSI Inc., and the affiliate member National Institute for Occupational Safety and Health (NIOSH).

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

Keywords

  • Atmospheric particle size distribution
  • Baghouse filtration
  • Coal-fired power plant
  • Integrative approach
  • Particle emission control devices (PECD)
  • Source apportionment models

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