Exploring the nonlinear association between environmental regulation and carbon intensity in China: The mediating effect of green technology

Yang, Guanglei; Zha, Donglan; Wang, Xiaojuan; Chen, Qian

doi:10.1016/j.ecolind.2020.106309

Cited by 100 publications

(38 citation statements)

References 48 publications

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“…Governments can increase the production costs and pollution control costs of enterprises through market-incentive environmental regulation, such as levying environmental taxes and emission trading systems to reduce pollution emissions [19,27,28]. Moreover, some scholars have studied the impact of environmental regulation on environmental pollution through industrial structure [29], foreign direct investment [7] and technological innovation [27,30,31]. However, Sinn [32] has questioned the effectiveness of environmental supervision policies.…”

Section: Literature Reviewmentioning

confidence: 99%

How Promotion Incentives and Environmental Regulations Affect China’s Environmental Pollution?

Liu

Zhang

Xu³

et al. 2021

Sustainability

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As for the academics and policymakers, more attention has been given to the issue on how to reduce environmental pollution through the cooperation of environmental regulation and local officials’ promotion incentives. With the use of a city-level panel data of 266 Chinese cities from 2005 to 2016, this study preliminary explores the impacts of environmental regulations, local officials’ promotion incentives, and their interaction terms on urban environmental pollution at national and regional levels by using the spatial Durbin model. The results indicate that the impacts of environmental regulations and local officials’ promotion incentives on urban environmental pollution have achieved the desired goal with the other’s cooperation, and their interaction term’s coefficients on urban environmental pollution are significantly negative. Moreover, spatial heterogeneity is established, and the uneven development of urban environmental pollution among different regions deserves more attention. In order to effectively reduce the level of urban environmental pollution in China, the government should focus on such solutions as enhancing the implementation and supervision efficiency of environmental regulation, optimizing the performance appraisal system of local officials, improving the synergistic effects of environmental regulations and local officials’ promotion incentives, and establishing a multi-scale spatial cooperation mechanism based on both geographical and economic correlations.

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Section: Literature Reviewmentioning

confidence: 99%

How Promotion Incentives and Environmental Regulations Affect China’s Environmental Pollution?

Liu

Zhang

Xu³

et al. 2021

Sustainability

View full text Add to dashboard Cite

show abstract

“…As mentioned previously, many influencing factors affect environmental pollution, including urbanization (Xu et al, 2019), transportation (Zhao et al, 2018), environmental regulation (Yang et al, 2020;Zhao et al, 2020). Second, construction of various models of empirical studies on pollution.…”

Section: Measuredmentioning

confidence: 99%

Analyzing China’s provincial pollution and its influencing factors: A spatial analysis

Wang

Zhou

2021

Preprint

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In-depth analyses of the spatial heterogeneity in pollution, and the causes of differences are of great importance for contributing to provide reference for reduction policies. However, a spatial analysis of the existence and mechanism of China’s pollution is still ignored. Using the province-level data of thirty provinces in China over 2005–2017, this paper constructs a spatial Durbin model (SDM) to empirically address the existence and spatial transmission mechanism of pollution. The main results are as follows: first, China’s pollution shows significant characteristics of spatial dependence and clustering from global and local perspectives, indicating that the existence of spatial autocorrelation in pollution across regions. Second, both per capita GDP and urbanization have positive impacts on pollution, but the impacts of environmental regulation and FDI are insignificant. Third, urbanization not only directly influences pollution, but also indirectly influences pollution. Our analysis provides valuable information for developing policies to effectively alleviate pollution.

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“…The form of varying temporal trends in EFI besides the declining type is mainly contributed by the varying trends of carbon EFI. The carbon intensity trends are mostly dependent on the economic development and industrial structure, and green technology, which has a significant impact on carbon intensity [47]. The counties of the linear declining type and most of the inverted-N type are of steady carbon EFI evolution, and normally showed a steadily declining trend, i.e., Binhai County, Dongtai, Funing County and Huan'an District.…”

Section: Temporal Changes In Efi For Jiangsu's Countiesmentioning

confidence: 99%

Spatial and Temporal Evaluation of Ecological Footprint Intensity of Jiangsu Province at the County-Level Scale

Liu

2020

IJERPH

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Due to the high ecological pressure that exists in the process of rapid economic development in Jiangsu Province, it is necessary to evaluate its ecological footprint intensity (EFI). This article focuses on ecological footprint intensity analysis at the county scale. We used county-level data to evaluate the spatial distributions and temporal trends of the ecological footprint intensity in Jiangsu’s counties from 1995 to 2015. The temporal trends of counties are divided into five types: linear declining type, N-shape type, inverted-N type, U-shape type and inverted-U shape type. It was discovered that the proportions of the carbon footprint intensity were maintained or increased in most counties. Exploratory spatial data analysis shows that there was a certain regularity of the EFI spatial distributions, i.e., a gradient decrease from north to south, and there was a decline in the spatial heterogeneity of EFI in Jiangsu’s counties over time. The global Moran’s index (Moran’s I) and local spatial association index (LISA) are used to analyze both the global and local spatial correlation of EFIs among counties of Jiangsu Province. The high-high and low-low agglomeration effects were the most common, and there were assimilation impacts of counties with strong agglomeration on adjacent units over time. The results implied the utility of differentiated EFI reduction control measures and promotion of low-low agglomeration and suppression of high-high agglomeration in EFI-related ecology policy.

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Exploring the nonlinear association between environmental regulation and carbon intensity in China: The mediating effect of green technology

Cited by 100 publications

References 48 publications

How Promotion Incentives and Environmental Regulations Affect China’s Environmental Pollution?

How Promotion Incentives and Environmental Regulations Affect China’s Environmental Pollution?

Analyzing China’s provincial pollution and its influencing factors: A spatial analysis

Spatial and Temporal Evaluation of Ecological Footprint Intensity of Jiangsu Province at the County-Level Scale

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