The measurement and influencing factors of carbon transfers embodied in inter-provincial trade in China

被引:33
|
作者
Wang, Wenzhi [1 ]
Hu, Yong [1 ]
机构
[1] Zhejiang Gongshang Univ, Hangzhou, Peoples R China
关键词
Multi-regional input-output model; Logarithmic mean divisia index; Carbon transfer; Inter-provincial trade in China; INPUT-OUTPUT-ANALYSIS; GROWING CO2 EMISSIONS; DIOXIDE EMISSIONS; DECOMPOSITION ANALYSIS; DRIVING FORCES; ENERGY; CONSUMPTION; DRIVERS; IMPACT;
D O I
10.1016/j.jclepro.2020.122460
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Based on a measurement model for carbon transfers in bilateral trade between regions and an improved log-mean Divisia index decomposition method, this study estimates carbon transfers caused by inter-provincial demand and inter-provincial exports for 2007, 2010, and 2012 and investigates the main factors that affect net carbon transfers between provinces. The results show the following. First, in 2007-2012, the average carbon emissions caused by inter-provincial demand and inter-provincial exports account for about 35.4% and 8% of total production-based carbon emissions, respectively, which indicates that carbon transfers between provinces are widespread. Second, total carbon transfers caused by inter-provincial demand keep increasing, and in 2012, 19 provinces show net carbon outflows, and provinces located in the northern and central regions receive most net carbon inflows. By contrast, net carbon outflows induced by inter-provincial export keep decreasing and are concentrated in eight provinces in the Beijing-Tianjin, eastern, and southern coastal areas. Third, the scale and structural effects increase net carbon transfers between provinces in 2007-2010 and 2010-2012, respectively, whereas the technological effect reduces net carbon transfers between provinces in 2007-2012. Our empirical results suggest that carbon emissions and inter-provincial carbon transfers can be reduced effectively through inter-provincial cooperation and narrowing provincial differences in emissions reduction technology. (C) 2020 Elsevier Ltd. All rights reserved.
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页数:14
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