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author:

Guo, Shihong (Guo, Shihong.) [1] | Chen, Liqiang (Chen, Liqiang.) [2]

Indexed by:

SSCI Scopus

Abstract:

Improving air quality across mainland China is an urgent policy challenge, while rapidly increasing use of vehicles poses a great menace to the urban population and air quality. Public transportation has received increasing attention as emissions- friendly transport options, but whether the urban rail transit system has a significant effect on curbing air pollution has been unclear, and there is a lack of explicit case studies in mainland China. Therefore, the effects of the opening of the Beijing Metro on air pollutants emissions in Beijing were quantified through a regression discontinuity design. Beijing has seen a brisk growth in its rail transit infrastructure and a downward trend of air pollution index since 2005. The regression results show that the operation of the rail transit system was observed to have a significant effect on reducing most of the air pollutants concentrations (PM2.5, PM10, SO2, NO2, and CO) but had little effect on ozone pollution. The results obtained were highly robust across a variety of tests. This study contributes to empirical evidence on the air pollutants associated with the opening of rail transit and traffic-related pollution control policy making in Beijing.

Keyword:

Community:

  • [ 1 ] [Guo, Shihong]Tsinghua Univ, Sch Publ Policy & Management, Wu Shunde Bldg,Tsinghua Campus, Beijing, Peoples R China
  • [ 2 ] [Chen, Liqiang]Fuzhou Univ, Sch Econ & Management, Fuzhou, Fujian, Peoples R China

Reprint 's Address:

  • [Guo, Shihong]Tsinghua Univ, Sch Publ Policy & Management, Wu Shunde Bldg,Tsinghua Campus, Beijing, Peoples R China

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Source :

GROWTH AND CHANGE

ISSN: 0017-4815

Year: 2019

Issue: 1

Volume: 50

Page: 130-144

1 . 2 3 5

JCR@2019

2 . 9 0 0

JCR@2023

ESI Discipline: SOCIAL SCIENCES, GENERAL;

ESI HC Threshold:95

Cited Count:

WoS CC Cited Count: 11

SCOPUS Cited Count: 14

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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