A network analysis of indirect carbon emission flows among different industries in China

被引:38
作者
Du, Qiang [1 ]
Xu, Yadan [2 ]
Wu, Min [2 ]
Sun, Qiang [2 ]
Bai, Libiao [1 ]
Yu, Ming [2 ]
机构
[1] Changan Univ, Sch Econ & Management, Xian 710064, Shaanxi, Peoples R China
[2] Changan Univ, Sch Civil Engn, Xian 710061, Shaanxi, Peoples R China
关键词
Complex network; Input-output analysis; Indirect carbon emission flows; Industry; INPUT-OUTPUT-ANALYSIS; ENERGY-WATER NEXUS; COMPLEX NETWORK; CO2; EMISSIONS; DIOXIDE EMISSIONS; EMBODIED ENERGY; EXERGY FLOW; CONSUMPTION; SECTORS; PERSPECTIVE;
D O I
10.1007/s11356-018-2533-x
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Indirect carbon emissions account for a large ratio of the total carbon emissions in processes to make the final products, and this implies indirect carbon emission flow across industries. Understanding these flows is crucial for allocating a carbon allowance for each industry. By combining input-output analysis and complex network theory, this study establishes an indirect carbon emission flow network (ICEFN) for 41 industries from 2005 to 2014 to investigate the interrelationships among different industries. The results show that the ICEFN was consistent with a small-world nature based on an analysis of the average path lengths and the clustering coefficients. Moreover, key industries in the ICEFN were identified using complex network theory on the basis of degree centrality and betweenness centrality. Furthermore, the 41 industries of the ICEFN were divided into four industrial subgroups that are related closely to one another. Finally, possible policy implications were provided based on the knowledge of the structure of the ICEFN and its trend.
引用
收藏
页码:24469 / 24487
页数:19
相关论文
共 47 条
[21]   Economic input-output models for environmental life-cycle assessment [J].
Hendrickson, C ;
Horvath, A ;
Joshi, S ;
Lave, L .
ENVIRONMENTAL SCIENCE & TECHNOLOGY, 1998, 32 (07) :184A-191A
[22]   Low-Molecular-Weight Heparin and Unfractionated Heparin Decrease Th-1, 2, and 17 Expressions [J].
Huang, Jing-Ning ;
Tsai, Ming-Chin ;
Fang, Shun-Lung ;
Chang, Margaret Dah-Tsyr ;
Wu, Yu-Rou ;
Tsai, Jaw-Ji ;
Fu, Lin-Shien ;
Lin, Heng-Kuei ;
Chen, Yi-Jun ;
Li, Tsai-Wei .
PLOS ONE, 2014, 9 (11)
[23]   Quantitative assessment of carbon dioxide emissions in construction projects: A case study in Shenzhen [J].
Li, Lijuan ;
Chen, Kanghai .
JOURNAL OF CLEANER PRODUCTION, 2017, 141 :394-408
[24]   The rumor diffusion process with emerging independent spreaders in complex networks [J].
Li, Weihua ;
Tang, Shaoting ;
Pei, Sen ;
Yan, Shu ;
Jiang, Shijin ;
Teng, Xian ;
Zheng, Zhiming .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2014, 397 :121-128
[25]   Examining industrial structure changes and corresponding carbon emission reduction effect by combining input-output analysis and social network analysis: A comparison study of China and Japan [J].
Li, Zhaoling ;
Sun, Lu ;
Geng, Yong ;
Dong, Huijuan ;
Ren, Jingzheng ;
Liu, Zhe ;
Tian, Xu ;
Yabar, Helmut ;
Higano, Yoshiro .
JOURNAL OF CLEANER PRODUCTION, 2017, 162 :61-70
[26]   The energy requirements and carbon dioxide emissions of tourism industry of Western China: A case of Chengdu city [J].
Liu, Jun ;
Feng, Tingting ;
Yang, Xi .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2011, 15 (06) :2887-2894
[27]   Breaking news dissemination in the media via propagation behavior based on complex network theory [J].
Liu, Nairong ;
An, Haizhong ;
Gao, Xiangyun ;
Li, Huajiao ;
Hao, Xiaoqing .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2016, 453 :44-54
[28]  
Luo J., 2005, SOCIAL NETWORK ANAL
[29]   Quantifying direct and indirect carbon dioxide emissions of the Chinese tourism industry [J].
Meng, Weiqing ;
Xu, Lingying ;
Hu, Beibei ;
Zhou, Jun ;
Wang, Zhongliang .
JOURNAL OF CLEANER PRODUCTION, 2016, 126 :586-594
[30]   Social networks in the context of community response to disaster: Study of a cyclone-affected community in Coastal West Bengal, India [J].
Misra, Sanchayeeta ;
Goswami, Rupak ;
Mondal, Tandra ;
Jana, Rabindranath .
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2017, 22 :281-296