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Spatial heterogeneity analysis of CO 2 emissions in China’s thermal power industry: GWR model

机译:中国热电行业CO 2 排放的空间异质性分析:GWR模型

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The thermal power industry is a major contributor to China's CO_(2)emissions, and its absolute emissions are still increasing year by year. Hence, this paper introduced a geographically weighted regression model to explore the spatial heterogeneity of different driving factors for this industry's CO_(2)emissions. The empirical results show that standard coal consumption is a decisive factor affecting thermal power industry's CO_(2)emissions, and its response to the western region is at the forefront. The average utilization hours of thermal power equipment in the central region exert a profound impact, while the western region devotes a lot to the installed capacity, and these two variables have great potential for CO_(2)emission mitigation. However, the urbanization level and per capita electricity consumption have a slight effect on CO_(2)emissions. These findings furnish constructive reference and policy implications to achieve emission abatement targets of different regions.
机译:热电行业是中国CO_(2)排放的主要贡献者,其绝对排放仍然越来越多。 因此,本文介绍了地理加权回归模型,探讨了该行业CO_(2)排放的不同驱动因素的空间异质性。 经验结果表明,标准煤炭消费是影响热电行业CO_(2)排放的决定性因素,其对西部地区的反应是最前沿。 中央区域的热电设备的平均利用时间发挥了深远的影响,而西部地区致力于装机容量,这两个变量具有很大的潜力,对CO_(2)排放缓解。 然而,城市化水平和人均电力消耗对CO_(2)排放有轻微影响。 这些调查结果提供了建设性的参考和政策影响,以实现不同地区的排放减排目标。

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