Carbon emission flow in the power industry and provincial CO2 emissions: Evidence from cross-provincial secondary energy trading in China

Wang, Feng; Shackman, Joshua D.; Liu, Xin

doi:10.1016/j.jclepro.2017.05.007

Cited by 50 publications

(29 citation statements)

References 33 publications

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“…Air pollution and the increase of an income gap are by-products of China's economic growth and major concerns of the public. The emission characteristics of China's provinces and cities are closely related to their different economic development and income levels, so the formulation and implementation of relevant policies should be proceeded with caution [71]. Fortunately, based on the results of this study, the policy ideas around solving these issues is not contradictory.…”

Section: Testing Environmental Kuznets Curves With Urban-rural Inequalitymentioning

confidence: 88%

Impact of Income Inequality on Urban Air Quality: A Game Theoretical and Empirical Study in China

Wang

Yang

Shackman

et al. 2021

IJERPH

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Income inequality and environmental pollution are of great concern in China. It is important to better understand whether the narrowing of income inequality and environmental improvement contradict each other. The study aims to investigate the linkage between income inequality and environmental pollution. To illustrate the interplay between different income groups on environmental issues, we apply a mixed-strategy game. Based on the game-theoretic analytical result, the probability of residents supporting clean energy and environmental protection decreases as income inequality widens and increases as inequality narrows. This empirical study is based on the proportion of coal consumption and urban air pollution data from 113 key environmental protection cities and regions in China. The air quality data are from the National Environmental Air Quality Monitoring Network published in the China Statistical Yearbook from 2014–2018. Convincing results show that regions with higher income inequality suffer severe smog and related pollution and that economies with narrow income disparity experience significant improvements in smog and pollution control, with the expansion of the proportion of clean energy use. The results also provide no evidence of the impact of per capita income on pollution. We studied the relationship between individuals of different wealth levels within an economy, within a repeated-game setting. The finding suggests that the distribution of growth impacts pollution. Imposing higher taxes on air polluters while transferring the revenue to the lower-income group is suggested.

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Section: Testing Environmental Kuznets Curves With Urban-rural Inequalitymentioning

confidence: 88%

Impact of Income Inequality on Urban Air Quality: A Game Theoretical and Empirical Study in China

Wang

Yang

Shackman

et al. 2021

IJERPH

Self Cite

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“…In the 21st century, global warming has become the most important challenge as an international environmental problem for mankind [1]. Greenhouse gas is considered to be the main cause of global warming, especially carbon dioxide [2].…”

Section: Introductionmentioning

confidence: 99%

How Do the Population Structure Changes of China Affect Carbon Emissions? An Empirical Study Based on Ridge Regression Analysis

et al. 2021

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This study focuses on the impact of population structure changes on carbon emissions in China from 1995 to 2018. This paper constructs the multiple regression model and uses the ridge regression to analyze the relationship between population structure changes and carbon emissions from four aspects: population size, population age structure, population consumption structure, and population employment structure. The results showed that these four variables all had a significant impact on carbon emissions in China. The ridge regression analysis confirmed that the population size, population age structure, and population employment structure promoted the increase in carbon emissions, and their contribution ratios were 3.316%, 2.468%, 1.280%, respectively. However, the influence of population consumption structure (−0.667%) on carbon emissions was negative. The results showed that the population size had the greatest impact on carbon emissions, which was the main driving factor of carbon emissions in China. Chinese population will bring huge pressure on the environment and resources in the future. Therefore, based on the comprehensive analysis, implementing the one-child policy will help slow down China’s population growth, control the number of populations, optimize the population structure, so as to reduce carbon emissions. In terms of employment structure and consumption structure, we should strengthen policy guidance and market incentives, raising people’s low-carbon awareness, optimizing energy-consumption structure, improving energy efficiency, so as to effectively control China’s carbon emissions.

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“…Although ecological and meteorological conditions (e.g., forest coverage, wind speed, atmospheric pressure) can influence this process, they are usually beyond policymakers' control in the short run, shifting policymakers' attention to the aforementioned economic driving factors of SO 2 emissions from a spatial perspective. To examine factors of air pollutant emissions across regions in China, a common way is to divide the whole provincial dataset into western China, eastern China and central China for a comparison purpose (Zhou and Liu, 2016;Wang et al, 2017;Ahmad et al, 2021a). However, this cannot investigate the global and local relationships between factors and emissions simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Spatial heterogeneity and economic driving factors of SO2 emissions in China: Evidence from an eigenvector based spatial filtering approach

Shi

Chang

et al. 2021

Ecological Indicators

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Sulfur dioxide (SO 2 ) emissions have been a great challenge in China over the last few decades due to their serious impact on the environment and human health. In this paper, a random effect eigenvector spatial filtering (RE-ESF) approach without and with non-spatially varying coefficients (SNVC) is identified to examine spatial heterogeneity and economic driving factors of SO 2 emissions in China from 2011 to 2017. Using the Moran eigenvectors to extract information on spatial dependence, the main findings of the RE-ESF approach are as follows: First, after comparing different approaches for dealing with spatial dependence, it is found that the RE-ESF approach demonstrates the best fit to the dataset. Second, the global investigation shows that SO 2 emissions are negatively determined by economic growth and government expenditure for environment protection, but are positively determined by road freight transport, coal consumption and oil consumption. Third, the local investigation indicates that the spatially varying coefficients of economic growth and coal consumption range from 0.1401 to 0.2732 with the median value of 0.2478 and from 0.2406 to 0.3611 with the median value of 0.3210, respectively, revealing significant spatial heterogeneity of SO 2 emissions driven by economic growth and coal consumption. These findings provide meaningful insights into centralized and province-specific policies for reducing SO 2 emissions.

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Carbon emission flow in the power industry and provincial CO2 emissions: Evidence from cross-provincial secondary energy trading in China

Cited by 50 publications

References 33 publications

Impact of Income Inequality on Urban Air Quality: A Game Theoretical and Empirical Study in China

Impact of Income Inequality on Urban Air Quality: A Game Theoretical and Empirical Study in China

How Do the Population Structure Changes of China Affect Carbon Emissions? An Empirical Study Based on Ridge Regression Analysis

Spatial heterogeneity and economic driving factors of SO2 emissions in China: Evidence from an eigenvector based spatial filtering approach

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