期刊
SCIENCE OF THE TOTAL ENVIRONMENT
卷 580, 期 -, 页码 197-209出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.scitotenv.2016.11.188
关键词
Emission inventory; Air pollution prevention and control action plan; CMAQ; PM2.5 concentration
资金
- MEP's Special Funds for Research on Public Welfare [201409002]
- Strategic Priority Research Program of the Chinese Academy of Sciences [XDB05020300]
- National Natural Science Foundation of China [21625701]
- Airborne: Pollution, Climate Change, and New Visions of Sustainability in China
In order to cope with heavy haze pollution in China, the Air Pollution Prevention and Control Action Plan including phased goals of the fine particulate matter (PM2.5) was issued in 2013. In this study, China's emission inventories in the baseline 2012 and the future scenarios of 2017 and 2020 have been developed based on this Action Plan. Beijing-Tianjin-Hebei (Jing-Jin-Ji) region, one of the most polluted regions in China, was taken as a case to assess the impact of phased emission control measures on PM2.5 concentration reduction using WRF-CMAQ model system. With the implementation of the Action Plan, the emissions of sulfur dioxide (SO2), nitrogen oxides (NOx), PM2.5, non-methane volatile organic compound (NMVOC), and ammonia (NH3) in 2017 will decrease by36%, 31%, 30%,12%, and 10% from the 2012 levels in Jing-Jin-Ji, respectively. In 2020, the emissions of SO2, NOx, PM2.5, NMVOC, and NH3 will decrease by 40%, 44%, 40%, 22%, and 3% from the 2012 levels in Jing-Jin-Ji, respectively. Consequently, the ambient annual PM2.5 concentration under the scenarios of 2017 and 2020 will be 28.3% and 37.8% lower than those in 2012, respectively. The Action Plan provided an effective approach to alleviate PM2.5 pollution level in Jing-Jin-Ji region. However, emission control of NMVOC and NH3 should be paid more attention and be strengthened in future. Meanwhile, emission control of NOx, SO2, NH3 and NMVOC synergistically are highly needed in the future because multiple pollutants impact on PM2.5 and O-3 concentrations nonlinearly. (C) 2016 Elsevier B.V. All rights reserved.
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