Decoupling and decomposition analysis of residential building carbon emissions from residential income: Evidence from the provincial level in China
Decoupling and decomposition analysis of residential building carbon emissions from residential income: Evidence from the provincial level in China
复制标题
住宅建筑碳排放与居民收入的解耦分解分析：来自中国省级的证据
DOI：
10.1016/j.eiar.2020.106487
复制
发表时间：
2021-01-01
影响因子：
7.9
通讯作者：
Ren, Hong
中科院分区：
文献类型：
--
作者：
Huo, Tengfei;Ma, Yuling;Ren, Hong
住宅建筑碳排放与居民收入脱钩对碳减排乃至全球气候变化具有重要意义。然而，它们之间脱钩关系的性质仍不清楚。本文采用Tapio脱钩模型，研究了2000 - 2015年中国30个省份的居民建筑碳排放（TC）、人均碳排放（PC）、居民碳强度（FC）和人均收入（PCI）之间的脱钩关系。然后，利用对数平均Divisa指数（LMDI）模型对省级层面的居民建筑碳强度与PCI的脱钩度进行分解，确定决定这种关系的主要因素。结果表明，在整个时间段内，我国30个省份的FC与PCI的主要脱钩趋势由弱脱钩状态向强脱钩状态转变，而TC和PC与PCI的脱钩仍有较大的空间。消费支出对FC与消费支出的脱钩具有主要的抑制作用，而居民能源强度对二者的脱钩具有主要的促进作用。这些研究结果为国际政策制定者制定有针对性的节能减碳政策，协调收入与碳排放之间的关系提供了有价值的参考，其结果也可应用于其他经济体，并在更大程度上适用于其他污染物。
Decoupling residential building carbon emissions from residential income has great significance for carbon mitigation and even global climate change. However, the nature of the decoupling relationship between them is still unclear. This study adopts the Tapio decoupling model to explore the decoupling relationship among residential building carbon emissions (TC), per capita carbon emissions (PC), residential carbon intensity (FC) and per capita income (PCI) across 30 Chinese provinces from 2000 to 2015. Then, the Logarithmic Mean Divisa Index (LMDI) model is used to decompose the decoupling of residential building carbon intensity and PCI at the provincial level to determine the main factors determining this relationship. Results show that the main decoupling trend between FC and PCI in 30 provinces transformed from weak decoupling state to strong decoupling state during the whole period, while there is still extensive room for TC and PC to decouple with PCI. PCI has the major inhibiting effect on the decoupling between FC and PCI, while residential energy intensity (EI) has the primarily promoting effect on the decoupling. These findings provide valuable references for international policymakers in formulating precisely targeted energy-saving and carbon-reducing policies to coordinate the relationship between income and carbon emissions, and the results also can be applied to other economies and, to a greater extent, other pollutants.