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Exploring the drivers to energy-related carbon emissions changes at China’s provincial levels

机译：探索中国省级能源相关碳排放变化的驱动力

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摘要

This paper proposes an alternative method to decompose carbon emissions changes using distance functions estimated by data envelopment analysis. The proposed approach can measure the effects of technical efficiency change and technical change, the effects of substitution among inputs, and the effects of GDP composition change on the changes in carbon emissions. We apply this method to decompose the carbon emissions at China’s provincial levels. For the 30 provinces as a whole during the 11th Five-Year Plan period (2006–2010), empirical results demonstrated that economic growth and the potential carbon factor changes were the largest contributors to carbon emissions increase, while the good output technical changes and energy usage technical changes were the largest components to carbon emissions reduction. The structure effects represented by GDP composition change was a mild contributor to carbon emissions reduction for most provinces. We found that the substitution effects among inputs existed and contributed to carbon emissions increase for most provinces, but their impacts were limited and differed across provinces. The impacts of the good output technical efficiency change and energy usage technical efficiency changes were extremely limited and different across provinces. The empirical results are beneficial to China’s central and local governments to make regional adaptive policies to carbon emissions reduction.
机译：本文提出了一种使用数据包络分析估计的距离函数分解碳排放变化的替代方法。所提出的方法可以衡量技术效率变化和技术变化的影响，投入之间的替代影响以及GDP组成变化对碳排放量变化的影响。我们采用这种方法分解了中国各省的碳排放量。对“十一五”期间（2006-2010年）的30个省整体进行的经验结果表明，经济增长和潜在的碳因子变化是碳排放增加的最大因素，而良好的产出技术变化和能源用法技术变化是减少碳排放的最大因素。 GDP构成变化所代表的结构效应在大多数省份中对碳排放量的减少起到了温和的作用。我们发现，在大多数省份中，投入之间存在替代效应，并导致碳排放增加，但各省的影响有限且存在差异。良好的产出技术效率变化和能源使用技术效率变化的影响极为有限，并且各省之间存在差异。实证结果有利于中国的中央和地方政府制定区域适应性政策以减少碳排放。

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