Do Rail Transits Improve Local Air Quality? Take Chengdu-Nanchang for Example Xueyuan Wang Zhejiang Gongshang University Yuping Wang Zhejiang Gongshang University Zhijian Zhang ( [email protected] ) Zhejiang Gongshang University Jingwei Li Zhejiang Gongshang University Research Article Keywords: Urban Rail Transit, Air Pollution, Regression Discontinuity Designs, Chengdu-Nanchang Posted Date: April 27th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-320209/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License 1 Do Rail Transits Improve Local Air Quality? Take Chengdu-Nanchang for Example 2 Xueyuan Wang, Yuping Wang, Zhijian Zhang *, Jingwei Li 3 The affiliation and address of the authors: 4 School of Economics, Zhejiang Gongshang University, 18 Xuezheng Road, Hangzhou 310018, 5 China. 6 The e-mail address, telephone and fax numbers of the corresponding author: 7 [email protected] (Z. Zhang), 0086-187-58107661, 0086-571-28008035 8 The e-mail address, telephone and fax numbers of the coauthor: 9 [email protected] (X. Wang), 0086-135-88493453, 0086-571-28008035 10 [email protected] (Y. Wang), 0086-153-81165378, 0086-571-28008035 11 [email protected] (J. Li), 0086-188-88929759, 0086-571-2800803 12 Do rail transits improve local air quality? Take Chengdu-Nanchang for example 13 Abstract 14 Many cities in China have invested the city’s rail transit system to reduce urban air pollution and 15 traffic congestion. Earlier studies rarely compare the effects of rail transit on urban air quality in 16 different cities, providing little guidance to urban planners in solving traffic congestion and air 17 quality. By using the rail transit lines in Chengdu and Nanchang as case studies, this paper 18 attempts to examine the effect of rail transit on air pollution. Data were collected from 18 19 monitoring stations distributed along the chosen rail transit lines in both cities during the period 20 2014 to 2016 and analyzed using the regression discontinuity design to address the potential 21 endogenous location of subway stations. The results show that subway opening in Nanchang has a 22 better reductions from automobile exhaust than that in Chengdu, specifically, carbon monoxide 23 pollution, one key tailpipe pollutant, experienced a 10.23% greater reduction after Nanchang 24 Metro Line 1 opened. On the contrary, the point estimate for carbon monoxide in Chengdu is 25 22.42% and statistically significant at the 1% level. Nanchang Metro Line 1 does play an 26 important role in road traffic externalities, but the benefit was not huge enough to change the 27 overall air quality. On the contrary, the opening of the Chengdu Metro Line 4 is unlikely to yield 28 improvements in air quality. 29 Keywords 30 Urban Rail Transit; Air Pollution; Regression Discontinuity Designs; Chengdu-Nanchang 31 1. Introduction 32 Traffic is a major contributor to ambient air pollution. Based on the world air quality report 33 published by IQAir AirVisual in 2019, the top 50 most polluted cities are from East and South 34 Asian countries, such as India, Pakistan, Bangladesh, Indonesia, and fourteen of them were 35 located in China, including Hotan, Kashgar, Shangqiu, Anyang, Handan, Shijiazhuang, Xianyang, 36 Xingtai, Puyang, Shihezi, Laiwu, Luoyang, Hebi, Linfen. Ghaziabad, located in India, experienced 37 the highest level of PM2.5 concentration in 2019. PM2.5 is widely regarded as most harmful to 38 human health, originating from a range of sources, for example, vehicle engines, industry, fires 39 and coal burning. Air pollution is responsible for the premature death of 4.2 million people 40 worldwide in 2016, of which 40 percent occurred in China. And the evidence shows that vehicular 41 emissions contribute to around 33% to 57% of ambient air pollution (Chen et al. 2020). The 42 environmental effect of traffic may hardly negligible, traffic congestion and subsequent air 43 pollution present policymakers with pressing challenges. 44 The most commonly adopted policy measures for improvements in terms of traffic pollution are 45 routinely focusing on limiting transportation demand, such as imposing road pricing (Gibson and 46 Carnovale 2015), parking controls (Melia and Clark 2018), driving restrictions (Melia and Clark 47 2018；Zhang et al. 2020；Zhang et al. 2017) and traffic calming (Akbari and Haghighi 2020), or 48 increasing transportation supply, including increasing capacities of transportation facilities and 49 investments. This paper focuses on another policy: urban rail transit. 50 According to data from the China Statistical Yearbook, over the period from 1998 to 2018, GDP 51 per capita increased by nearly 10 times, per capita disposable income of national residents 52 increased by about 7 times, and vehicle ownership increased by 48 times in China. China’s reform 53 and opening-up, the rapid growth of its economy has led to plenty of problems (Mbizvo et al. 2019) 54 including urban traffic congestion (Akbari and Haghighi 2020), adverse health consequences 55 (Brook and Rajagopalan 2012；Currie and Neidell 2018；Heinrich and Slama 2007) and air 56 pollution (Ibarra-Espinosa et al. 2020). To reverse the trend of nationwide environmental 57 deterioration, Chinese government made the decision to transform its economic pattern to a new 58 one featured with technology innovation since the Ninth Five-Year Plan by supporting the 59 implement of the Air Pollution Control Action Plan and setting detail emission reduction target for 60 each Five-Year Plan (Wang et al. 2019). Chinese government has also been investing heavily in 61 transportation infrastructure. As of 2019, a total of 46 cities in mainland China have opened urban 62 rail lines, with 5680.84 km in total route length. The rapid subway expansion is still ongoing at the 63 national level: the network consists of another 266 subway lines, serving a total of 3,872 subway 64 stations with a total length of 6282.6 km. The remarkable development of China’s transportation 65 infrastructure in the past 10 years has caused the profound changes in the economic structure and 66 the developmental pattern. 67 Recently major cities in China have been investing heavily in green infrastructure to mitigate air 68 pollution. However, existing studies rarely compare the effects of rail transit on air quality in 69 different cities. This paper examines the impact of rail transit on air quality by leveraging hourly 70 weather data collected from Chengdu and Nanchang during the period of 2014-2016. The 71 literatures in subway infrastructure incorporates two countervailing forces, one possible channel 72 that may affect traffic pollution is the possibility that households near the subway stations may 73 substitute for their driving after the rail transit opened, this traffic diversion effect may relieve 74 traffic congestion and thus alleviate air pollution (Mohring 1972). The other possible channel is 75 the improved traffic conditions may provide some people near the subway stations with more 76 potential choices, and induce additional travel demand using private cars (Vickrey 1969) and the 77 phenomenon of separation of workplace and residence. This traffic creation effect would result in 78 the increase of the traffic volume in the streets and the prolongation of peak-hours and thus 79 aggravate local air pollution. 80 This analysis is relevant to currently high-profile discussions about whether the opening of rail 81 transit has positive effects on air quality in different cities. Our empirical analysis leverages 82 discontinuity in the concentration of air pollutant to control for possible confounding factors. The 83 data on air quality come from published hourly air quality index from the U.S. National Climatic 84 Data Center. The central empirical challenge in scrutinizing the effects of rail transit on air quality 85 is identification concern. First, in measuring variations in rail transit, confounding with other 86 factors affecting air pollution, have no way to give sound results (Chen and Whalley 2012；Li et al. 87 2019). For example, subway stations are likely to be located in areas with high population growth, 88 hence induce the demand of travel and deterioration in air pollution. Second, it is a mistake to 89 confound the variation in the demand for public transit with other covariables that affect air 90 quality (Rivers et al. 2017). The demand for public transport is associated with the overall price, 91 income, speed and frequency elasticities (Toro-González et al. 2020). Public transportation is not a 92 sufficiently good alternative for those who travel a lot (Lalive et al. 2018) and the demand for 93 public transport decreases given an increase in per capita income (Toro-González et al. 2020). 94 Using the regression discontinuity design based on the combinations of weather controls (i.e. 95 temperature, wind speed, volume, precipitation), air pollution (CO, NO2, PM2.5, SO2, O3, PM10), 96 time fixed effect and station fixed effect, we find that the opening of rail transit in different cities 97 may have different effects on local air pollutants. The findings of this paper are contrary to much 98 of the existing literature on the relationship between rail transit and air quality. Our first finding 99 shows that carbon monoxide experienced a greater reduction in Nanchang relative to 100 concentrations calculated from the Chengdu monitoring stations after the subway line opened. 101 Second, the opening of Nanchang Metro Line 1 leads to two contradictory results. On the one 102 hand, the expansion of Nanchang’s subway network could lead some commuters living near the 103 subway stations to prefer to subways. This traffic diversion effect may be conducive to alleviate 104 people’s travel pressure, and thus reduce automobile exhausted gas pollution. On the other hand, a 105 completely new subway line’s opening could offer more convenient mobility options and induce 106 additional travel demand, resulting in a traffic creation effect.