Correlation analysis of regional carbon emission intensity and green industry development-A case study of Chengdu-Chongqing region

区域碳排放强度与绿色产业发展相关性分析——以成渝地区为例

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Abstract

Industrial structure markedly affects the level of carbon emissions generated in a region. It is imperative to study the industrial structure of the Chengdu-Chongqing region to obtain information to achieve regional high-quality development by promoting low-carbon development. We selected 16 cities in Chengdu-Chongqing area as the research object in this study. The total carbon emissions (CE), carbon intensity (CI) and per capita carbon emissions (PCE) were calculated for each city. The green industry development (GI) evaluation indexes were then extracted, and the comprehensive evaluation value was determined using the entropy weight-TOPSIS model (EWM-TOPSIS). The green industry development was used as the core explanatory variable to construct a system representing the dynamic relationship between green industry development and carbon intensity using the quantile regression (QR) model. The results of the study showed that: (1) the total carbon emissions of Chengdu-Chongqing region increased whereas the carbon intensity decreased from 2010 to 2020. (2) The green industry development evaluation results showed that Chengdu-Chongqing had unevenly distributed green industry development during the study period, and Chengdu and Chongqing cities had higher green industry development values than other cities. (3) The green industry development of the region had a significant negative effect on carbon intensity at low quantile and a significant positive effect on carbon intensity at high quantile. Energy supply (ES) was positively correlated with the carbon intensity of the region at 1 % level of significance, whereas urbanization rate (U) and power consumption (PEC) were negatively correlated with the carbon intensity at 1 % level of significance. We comprehensively evaluated the development of green industry and introduced it as a core explanatory variable into the quantile regression model to explore the relationship between regional carbon emission intensity and industrial development. The results provide a reference for designing strategies to promote high-quality development in the cities in the Chengdu-Chongqing region.

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