Estimate on spillover effect of environmental pollution between peripheral areas

Ma, Qian; Zhang, Tongbin; Li, Jinkai

doi:10.1080/10042857.2019.1628605

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…is one of the most important carriers for a country's economic development and incubators for innovation, where the exchange of capital, information, and labor within the UAs are more active than those outside [8], especially in China [88,89]. UAs and the transportation network have become China's core points of spatial planning and regional development in the 21st century [81,90].…”

Section: Four Urban Agglomerations Urban Agglomeration (Ua)mentioning

confidence: 99%

Booming with Speed: High-Speed Rail and Regional Green Innovation

Zhu

Lin

Yang

2021

Journal of Advanced Transportation

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Exploiting China’s high-speed rail (HSR) as a quasi-natural experiment, we examine the relationship between the HSR connection and green innovation. The opening of HSR can promote green innovation by facilitating the flow of innovation factors. Using the multiperiod difference-in-differences (DID) model, we find that the regional green innovation performance significantly becomes better following the opening of HSR in the local city. Moreover, in examining the specific mechanisms at work, we find evidence that HSR stimulates green patents through increased labor mobility and research capital mobility. Further analyses show that the facilitating effect of HSR is heterogeneous among cities. Our paper sheds new light on the effects of HSR on social welfare in the case of sustainable economy.

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Section: Four Urban Agglomerations Urban Agglomeration (Ua)mentioning

confidence: 99%

Booming with Speed: High-Speed Rail and Regional Green Innovation

Zhu

Lin

Yang

2021

Journal of Advanced Transportation

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“…Part of the research is to show the empirical results of the spillover effects of various air pollution indicators in different regions. For example, Hoti et al (2005) for the research of atmospheric carbon dioxide concentrations between Asia and South West Pacific shows that the spatial correlation between the two is almost zero; The research of Zheng et al (2018), Fang et al (2019), Li H. et al (2019), andMa et al (2019) shows the spillover effects of PM2.5 concentration, CO2 emission, SO2 emission and other air indicators in different degrees within and between regions.…”

Section: Spillover Effects About Air Qualitymentioning

confidence: 99%

What drives the spatio-temporal distribution and spillover of air quality in China’s three urban agglomerations? Evidence from a two-stage approach

Cui

Ren²,

Wei³

et al. 2022

Front. Ecol. Evol.

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Beijing-Tianjin-Hebei urban agglomeration (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) are the most important economic hinterlands in China, offering high levels of economic development. In 2020, their proportion of China’s total GDP reached 39.28%. Over the 5 years of 2014–2018, the annual maximum air quality index (AQI) of the three major urban agglomerations was greater than 100, thus maintaining a grade III light pollution (100 < AQI < 200) in Chinese air standards. This research thus uses a two-stage empirical analysis method to explore the spatial-temporal dispersal physiognomies and spillover effects of air quality in these three major urban agglomerations. In the first stage, the Kriging interpolation method regionally estimates and displays the air quality monitoring sampling data. The results show that the air quality of these three major urban agglomerations is generally good from 2014 to 2018, the area of good air is gradually expanding, the AQI value is constantly decreasing, the air pollution of YRD is shifting from southeast to northwest, and the air pollution of PRD is increasing. The dyeing industry shows a trend of concentration from northwest to south-central. In the second stage, Moran’s I and Spatial Durbin Model (SDM) explore the spatial autocorrelation and spillover effects of air quality related variables. The results show that Moran’s I values in the spatial autocorrelation analysis all pass the significance test. Moreover, public transport, per capita GDP, science and technology expenditure, and the vegetation index all have a significant influence on the spatial dispersal of air quality in the three urban agglomerations, among which the direct effect of public transport and the indirect effect and total effect of the vegetation index are the most significant. Therefore, the China’s three major urban agglomerations (TMUA) ought to adjust the industrial structure, regional coordinated development, and clean technology innovation.

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The heterogeneous impact of environmental regulation on urban green scale economy: an empirical analysis based on city-level panel data in China

Tian

Feng

2021

Environ Sci Pollut Res

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Estimate on spillover effect of environmental pollution between peripheral areas

Cited by 5 publications

References 13 publications

Booming with Speed: High-Speed Rail and Regional Green Innovation

Booming with Speed: High-Speed Rail and Regional Green Innovation

What drives the spatio-temporal distribution and spillover of air quality in China’s three urban agglomerations? Evidence from a two-stage approach

The heterogeneous impact of environmental regulation on urban green scale economy: an empirical analysis based on city-level panel data in China

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