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  • 标题:Air Treatment Effect Assessment for Improving Vehicle Emission Standards: Counterfactual Analysis Based on Machine Learning
  • 本地全文:下载
  • 作者:Yunan Zhang ; Bilin Xu ; Haroon Rashid
  • 期刊名称:Nature, Environment and Pollution Technology
  • 印刷版ISSN:0972-6268
  • 出版年度:2019
  • 卷号:18
  • 期号:5
  • 页码:1739-1745
  • 语种:English
  • 出版社:Technoscience Publications
  • 摘要:Automobile exhaust has become an important source of urban air pollution. Improving vehicle emission standards is one of the key measures to control air pollution. This paper takes Tianjin’s implementation of the “National V” motor vehicle emission standard as an example. The study found that this policy is an indispensable condition for improving air quality, which helps to reduce carbon monoxide (CO) and nitrogen dioxide (NO 2 ) in the atmosphere, but the effect on the treatment of atmospheric pollutants such as particulate matter (PM2.5) and respirable particulate matter (PM10) is not significant. It can be seen that while continuously improving the emission standards of motor vehicles, it should also cooperate with the improvement of public transportation systems, the development of new energy vehicles and alternative fuels, and the targeted regulation of air pollution control measures in other high-energy-consuming industries.
  • 关键词:Air treatment;Motor vehicle emission;standards;Counterfactual analysis;Machine learning
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