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Article

Can Environmental Quality Improvement and Emission Reduction Targets Be Realized Simultaneously? Evidence from China and A Geographically and Temporally Weighted Regression Model

School of Management, China University of Mining and Technology, Xuzhou 221116, China
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Int. J. Environ. Res. Public Health 2018, 15(11), 2343; https://doi.org/10.3390/ijerph15112343
Received: 26 September 2018 / Revised: 13 October 2018 / Accepted: 15 October 2018 / Published: 24 October 2018
(This article belongs to the Special Issue Circular Economy from Process to Policy)
The reductions of industrial pollution and greenhouse gas emissions are important actions to create an ecologically stable civilization. However, there are few reports on the interaction and variation between them. In this study, the vertical and horizontal scatter degree method is used to calculate a comprehensive index of industrial pollution emissions. Then based on carbon density, a geographically and temporally weighted regression (GTWR) model is developed to examine the interaction between industrial pollution emissions and carbon emissions. The results specify that there exists spatial autocorrelation for carbon density in China. Overall, the average effect of industrial pollution emissions on carbon density is positive. This indicates that industrial pollution emissions play a driving role in carbon density on the whole, while there are temporal and spatial differences in the interactions at the provincial level. According to the Herfindahl index, neither time nor space can be neglected. Moreover, according to the traditional division of eastern, central and western regions in China, the situation in 30 provinces is examined. Results show that there is little difference in the parameter-estimated results between neighboring provinces. In many provinces, the pull effect of industrial pollution emissions on carbon density is widespread. Thus, carbon emissions could be reduced by controlling industrial pollution emissions in more than 60% of regions. In a few other regions, such as Shanghai and Heilongjiang, the industrial pollution emissions do not have a pull effect on carbon density. But due to spatial and temporal heterogeneity, the effects are different in different regions at different times. It is necessary to consider the reasons for the changes combined with other factors. Finally, the empirical results support pertinent suggestions for controlling future emissions, such as optimizing energy mix and reinforcing government regulation. View Full-Text
Keywords: industrial pollution emissions; vertical and horizontal scatter degree method; carbon density; GTWR industrial pollution emissions; vertical and horizontal scatter degree method; carbon density; GTWR
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MDPI and ACS Style

Dong, F.; Wang, Y.; Zhang, X. Can Environmental Quality Improvement and Emission Reduction Targets Be Realized Simultaneously? Evidence from China and A Geographically and Temporally Weighted Regression Model. Int. J. Environ. Res. Public Health 2018, 15, 2343. https://doi.org/10.3390/ijerph15112343

AMA Style

Dong F, Wang Y, Zhang X. Can Environmental Quality Improvement and Emission Reduction Targets Be Realized Simultaneously? Evidence from China and A Geographically and Temporally Weighted Regression Model. International Journal of Environmental Research and Public Health. 2018; 15(11):2343. https://doi.org/10.3390/ijerph15112343

Chicago/Turabian Style

Dong, Feng, Yue Wang, and Xiaojie Zhang. 2018. "Can Environmental Quality Improvement and Emission Reduction Targets Be Realized Simultaneously? Evidence from China and A Geographically and Temporally Weighted Regression Model" International Journal of Environmental Research and Public Health 15, no. 11: 2343. https://doi.org/10.3390/ijerph15112343

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