Abstract

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.

Highlights

  • Carbon emissions have been a topical issue within the international community [1]

  • To address the inadequacies in existing research, this study extends it in the following ways: (1) in contrast to previous carbon emission indicators, calculations are made according to the carbon emissions per region

  • There exist obvious spatial difference between Carbon density (CD) and industrial pollution emission levels. Variations in both indicators appear in some provinces

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Summary

Introduction

Carbon emissions have been a topical issue within the international community [1]. China is the world’s largest energy consumer and it has been the world’s largest carbon emitter [2]. In 2007, China’s carbon emissions exceeded those of the United States of America [3]. In the 21st century, the growth of global carbon emission intensity has been mainly driven by China [4]. Under the pressure of international emission reduction targets and the need to improve domestic environmental quality, a series of emission reduction commitments have been put forward by China’s national government. Res. Public Health 2018, 15, 2343; doi:10.3390/ijerph15112343 www.mdpi.com/journal/ijerph

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