Identify the significant contributors of regional CO emissions in the context of the operation of high-speed railway-illustrated by the case of Hunan Province.
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2020
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Abstract
High-speed rail (HSR) is one of the essential innovations in the field of transportation in the latter half of the twentieth century. In China, the rapid development of HSR has received increasing attention and resulted in a boost of tourism, with significant impact on the development of cities that operates HSR. To accurately comprehend how will the operation of HSR influence the regional CO emissions, this paper applies the modified STIRPAT model, combining with real data on high-speed rail passenger flow volume of the Beijing-Guangzhou high-speed rail Hunan section. The results show that (1) the high-speed rail operation is also a significant impact factor for regional CO emissions. (2) Considering the operation of HSR, the ranking of contribution rate of driving factors for regional CO emissions is as follows: GDP per capita, energy consumption per unit of GDP, arrival volume of high-speed rail, originated volume of high-speed rail, the proportion of coal in the energy mix, proportion of the tertiary industry, and population. (3) Surprisingly, the numerical research result shows that the operation of HSR for the cities may promote regional CO emissions, while the increase in urban population and the optimization of energy structure have a reducing effect on regional carbon emissions. There is a transfer effect of the operation of HSR and region development, which results in the rising of regional CO emissions. Thus, it is urgent to research on the decoupling of economic growth from CO emissions. The findings could be conducive for the government and railway company to evaluate and administrate the operation of high-speed rail and adequately deal with the relationships between the high-speed railway and regional development.
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| Reference Key |
gan2020identifyenvironmental
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| Authors | Gan, Mi;Jiang, Qingchen;Zhu, Daoli; |
| Journal | Environmental science and pollution research international |
| Year | 2020 |
| DOI |
10.1007/s11356-020-07866-6
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