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Impact of air pollution control policies on future PM2.5 concentrations and their source contributions in China.
Cai, Siyi; Ma, Qiao; Wang, Shuxiao; Zhao, Bin; Brauer, Michael; Cohen, Aaron; Martin, Randall V; Zhang, Qianqian; Li, Qinbin; Wang, Yuxuan; Hao, Jiming; Frostad, Joseph; Forouzanfar, Mohammad H; Burnett, Richard T.
Afiliação
  • Cai S; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
  • Ma Q; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China; School of Energy and Power Engineering, Shandong University, Jinan, 250061, China.
  • Wang S; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China. Electronic address: shxwang@tsinghua.
  • Zhao B; Joint Institute for Regional Earth System Science and Engineering, Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, 90095, USA.
  • Brauer M; School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia V6T1Z3, Canada.
  • Cohen A; Health Effects Institute, Boston, MA, 02110, USA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98195, USA.
  • Martin RV; Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, B3H 4R2, Canada.
  • Zhang Q; National Satellite Meteorological Center, Beijing, 100089, China.
  • Li Q; Joint Institute for Regional Earth System Science and Engineering, Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, 90095, USA.
  • Wang Y; Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA.
  • Hao J; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China.
  • Frostad J; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98195, USA.
  • Forouzanfar MH; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98195, USA.
  • Burnett RT; Health Canada, Ottawa, ON, K1A 0K9, Canada.
J Environ Manage ; 227: 124-133, 2018 Dec 01.
Article em En | MEDLINE | ID: mdl-30172931
ABSTRACT
To investigate the impact of air pollutant control policies on future PM2.5 concentrations and their source contributions in China, we developed four future scenarios for 2030 based on a 2013 emission inventory, and conducted air quality simulations for each scenario using the chemical transport model GEOS-Chem (version 9.1.3). Two energy scenarios i.e., current legislation (CLE) and with additional measures (WAM), were developed to project future energy consumption, reflecting, respectively, existing legislation and implementation status as of the end of 2012, and new energy-saving policies that would be released and enforced more stringently. Two end-of-pipe control strategies, i.e., current control technologies (until 2017) and more stringent control technologies (until 2030), were also developed. The combinations of energy scenarios and end-of-pipe control strategies constitute four emission scenarios (2017-CLE, 2030-CLE, 2017-WAM, and 2030-WAM) evaluated in simulations. PM2.5 concentrations at national level were estimated to be 57 µg/m3 in the base year 2013, and 58 µg/m3, 42 µg/m3, 42 µg/m3, and 30 µg/m3 under the 2017-CLE, 2030-CLE, 2017-WAM, and 2030-WAM scenarios in 2030, respectively. Large PM2.5 reductions between 2013 and 2030 were estimated for heavily polluted regions (Sichuan Basin, Middle Yangtze River, North China). The energy-saving policies show similar effects to the end-of-pipe emission control measures, but the relative importance of these two groups of policies varies in different regions. Absolute contributions to PM2.5 concentrations from most major sources declined from 2017-CLE to 2030-WAM. With respect to fractional contributions, most coal-burning sectors (including power plant, industrial and residential coal burning) increased from 2017-CLE to 2030-WAM, due to larger reductions from non-coal sources, including transportation and biomass open burning. Residential combustion and open burning had much lower fractional contribution to ambient PM2.5 concentrations in the 2017-WAM/2030-WAM compared to the 2017-CLE/2030-CLE scenarios. Fractional contributions from transportation were reduced dramatically in 2030-CLE and 2030-WAM compared to 2017-CLE/2017-WAM, due to the enforcement of stringent end-of-pipe emission controls. Across all scenarios, coal combustion remained the single largest contributor to PM2.5 concentrations in 2030. Reducing PM2.5 emissions from coal combustion remains a strategic priority for air quality management in China.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Poluição do Ar País/Região como assunto: Asia Idioma: En Revista: J Environ Manage Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Poluição do Ar País/Região como assunto: Asia Idioma: En Revista: J Environ Manage Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China