Abstract:

Heavily polluting enterprises are the main sources of pollution and carbon emissions in China. Investigating the spatiotemporal differentiation characteristics and driving factors of the synergistic effects of pollution and carbon reduction in these enterprises is crucial for further promoting the coordinated governance of pollution and carbon reduction in heavy-pollution enterprises, achieving the goal of "dual carbon" and sustainable economic development. For this purpose, 100 A-share listed companies in China's heavy-pollution industry from 2008 to 2022 were selected as the sample. The Spatiotemporal Geographically Weighted Regression (GTWR) model and kriging spatial interpolation were used to analyze the spatiotemporal differentiation characteristics of the coordinated governance of pollution and carbon emission reduction of heavily polluting enterprises. Additionally, the dual fixed-effects model was employed to analyze the driving factors of the synergistic effects of pollution and carbon reduction in heavy-pollution enterprises and further reveal the heterogeneity of these factors based on the regression results of the GTWR. The results showed the following. (1) From a temporal perspective, since 2008, the synergistic effects of pollution and carbon emission reductions in China's heavily polluting industries have generally exhibited an upward trend, with the mean value increasing from 0.476 in 2008 to 0.490 in 2022. (2) In terms of spatial characteristics, the synergistic effects in the eastern, central, and western regions are 0.413‒0.810, 0.395‒0.662, and 0.187‒0.550, respectively. Initially, the synergistic effect in the eastern and central regions was higher than that in other regions. However, as the collaborative governance of pollution and carbon reduction progressed, differences among the regions gradually diminished. (3) Energy consumption is significantly negatively correlated with the synergistic effect of pollution and carbon reduction in heavy-pollution enterprises, whereas total factor productivity and green technological innovation are significantly positively correlated with the synergistic effect. The driving effects of energy consumption and total factor productivity were more pronounced in the eastern region, whereas the role of green technological innovation was more prominent in the western region. The intensity of environmental regulation and public environmental attention played moderating roles in the driving factors of pollution and carbon emission reduction. This study not only expands the research perspective on the synergistic effect of pollution and carbon reduction in heavy pollution enterprises but also provides insight for China to promote the reduction in pollution and carbon emissions in these enterprises.

Key words: heavily polluting enterprises, pollution and carbon reduction synergy, coupling coordination degree, GTWR model, spatiotemporal differentiation characteristics, driving factors

摘要：

重污染企业是中国污染排放和碳排放的主要来源，探究这些企业减污降碳协同效应的时空分异特征及其驱动因素，对于深入推进重污染企业减污降碳的协同治理，实现“双碳”目标和经济可持续发展至关重要。选取2008－2022年中国重污染行业100家A股上市公司为样本，利用时空地理加权回归（GTWR）模型和克里金空间插值法分析重污染企业减污降碳协同治理的时空分异特征。同时，利用双固定效应模型剖析了重污染企业减污降碳协同效应的驱动因素，并基于GTWR的回归结果进一步揭示这些因素的作用异质性。结果表明，1）从时间特征来看，自2008年以来，中国重污染细分行业减污降碳协同效应总体呈上升趋势，协同效应的均值由2008年的0.476提高到2022年的0.490。2）从空间特征看，样本期内东、中、西部地区的协同效应分别介于0.413－0.810、0.395－0.662、0.187－0.550。东部和中部地区的协同效应起初高于其他地区，但随着减污降碳协同治理的推进，各地区的差异逐渐缩小。3）能源消耗量与重污染企业减污降碳协同效应显著负相关，而全要素生产率和绿色技术创新则与协同效应显著正相关。特别是在东部地区，能源消耗量和全要素生产率的驱动作用更明显，而在西部地区，绿色技术创新的作用更突出。环境规制强度和公众环境关注度对减污降碳的驱动因素起到了调节作用。该研究不仅拓展了重污染企业减污降碳协同效应的研究视角，还为中国推进重污染企业减污降碳提供了政策启示。

关键词: 重污染企业, 减污降碳协同, 耦合协调度, GTWR模型, 时空分异特征, 驱动因素