Dynamic spatial spillover effect of urbanization on environmental pollution in China considering the inertia characteristics of environmental pollution

Liu, Xiaorui; Sun, Tao; Ren, Yi

doi:10.1016/j.scs.2019.101903

Cited by 135 publications

(50 citation statements)

References 59 publications

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“…This further proves that urbanization only inhibits the decoupling between certain pollutants and economic growth, but not completely. This is consistent with the research conclusions of [37]. Although extensive urbanization in some areas of China has increased the economic growth rate, it has also caused some environmental pollution.…”

Section: Analysis Of Regression Estimation Results Of Spatial Panel Modelsupporting

confidence: 92%

Can Clean Energy Consumption Promote the Decoupling Between Economic Growth and Environmental Pollution? – Spatial Empirical Analysis Based on China

Hong¹,

Wang²,

Deng³

2021

Pol. J. Environ. Stud.

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High hopes are placed on the production and use of clean energy during the decoupling between economic growth and environmental pollution. This article uses the decoupling model to study the temporal and spatial coupling characteristics of economic growth and environmental pollution in different regions of China. On this basis, a spatial measurement model is used to quantitatively evaluate the effects of clean energy consumption on the decoupling of economic growth and environmental pollution. The results show that during the study period, the areas where economic growth and environmental pollution generally showed strong decoupling gradually increased, and the areas showing coupling gradually decreased. Moreover, the decoupling state has obvious spatial heterogeneity and spatial aggregation characteristics. Clean energy consumption can significantly promote the decoupling of economic growth and environmental pollution. In addition, the analysis of direct effects shows that clean energy consumption has a significant negative effect on the decoupling of regional economic growth from SO 2 emissions and DS (dust and smoke) emissions. But the indirect effect and total effect are not obvious. It further proves that clean energy consumption has no significant effect on promoting the decoupling of surrounding areas and all areas except the local area.

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Section: Analysis Of Regression Estimation Results Of Spatial Panel Modelsupporting

confidence: 92%

Can Clean Energy Consumption Promote the Decoupling Between Economic Growth and Environmental Pollution? – Spatial Empirical Analysis Based on China

Hong¹,

Wang²,

Deng³

2021

Pol. J. Environ. Stud.

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“…This study further advances the assessment of the impact of demographic and socio-economic parameters on the spread of COVID-19 cases and deaths across Europe by adopting spatial regression-based approaches. Spatial regressions models have been used extensively in many epidemiological studies ranges across the scale ( Guo, Wu, & Chen, 2020 ; Guo, Yang et al, 2020 ; Liu, Sun, & Feng, 2020 ; Liu, Zhang, Jin, & Liu, 2020 ; Zhao, Zhan, Yao, & Yang, 2020 ). Diuk-Wasser, Brown, Andreadis, and Fish (2006)) evaluated the spatial distribution of mosquito vectors for West Nile virus in Connecticut, the USA using logistic regression models.…”

Section: Introductionmentioning

confidence: 99%

Examining the association between socio-demographic composition and COVID-19 fatalities in the European region using spatial regression approach

Sannigrahi

Pilla

Basu

et al. 2020

Sustainable Cities and Society

273

215

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Highlights The spatial association between socio-demographic composition and COVID-19 deaths and cases were evaluated. Four spatial regression models were implemented for spatial regression modelling. Socio-demographic composition significantly impacting the overall casualties caused by COVID-19. The spatially predicted COVID-19 cases and deaths were found highly consistent with actual estimates.

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“…These problems pose numerous risks to public health [ 8 ]. The environmental problems caused by urbanization and industrialization urgently require solutions [ 9 , 10 ]. Bennett and Satterfield [ 11 ] suggested that in many environmental protection initiatives, the main approach to solving environmental problems should be the establishment of a strong local environmental governance system, and Cheng and Li [ 12 ] discussed the impact of environmental governance policies on the industrial environment.…”

Section: Introductionmentioning

confidence: 99%

Improvement Path for Resource-Constrained Cities Identified Using an Environmental Co-Governance Assessment Framework Based on BWM-mV Model

Wang

Huang

et al. 2021

IJERPH

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Global warming and extreme weather have increased most people’s awareness of the problem of environmental destruction. In the domain of sustainable development, environmental governance has received considerable scholarly attention. However, protecting and improving the environment requires not only substantial capital investment but also cooperation among stakeholders. Therefore, based on the network structure of stakeholders, the best–worst method (BWM) and modified Vlsekriterijumska Optimizacija I Kompromisno Resenje method were combined to form an environmental co-governance assessment framework that can be used to evaluate the effects of various policies and identify strategies for further improvement through data analysis (henceforth the BWM-mV model). This mechanism is not only useful for evaluating the effectiveness of environmental governance policies but also for generating suggestions to enhance these policies. Hence, the BWM-mV model is particularly suitable for local governments with limited resources in time, money, or labor. Pingxiang City Government is currently subject to such limitations and was therefore selected as the subject of an empirical case study. The results of this study revealed that the aspects (i.e., criteria) the Pingxiang City Government should urgently improve on pertain to a high-quality information communication platform (C13) and smooth joint decision-making by stakeholders (C24).

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Dynamic spatial spillover effect of urbanization on environmental pollution in China considering the inertia characteristics of environmental pollution

Cited by 135 publications

References 59 publications

Can Clean Energy Consumption Promote the Decoupling Between Economic Growth and Environmental Pollution? – Spatial Empirical Analysis Based on China

Can Clean Energy Consumption Promote the Decoupling Between Economic Growth and Environmental Pollution? – Spatial Empirical Analysis Based on China

Examining the association between socio-demographic composition and COVID-19 fatalities in the European region using spatial regression approach

Improvement Path for Resource-Constrained Cities Identified Using an Environmental Co-Governance Assessment Framework Based on BWM-mV Model

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