Tracking Inter-Regional Carbon Flows: A Hybrid Network Model

被引:99
作者
Chen, Shaoqing [1 ]
Chen, Bin [1 ]
机构
[1] Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat & Pollut Con, Beijing 100875, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金; 高等学校博士学科点专项科研基金;
关键词
INPUT-OUTPUT-ANALYSIS; ECOLOGICAL NETWORK; INTERNATIONAL-TRADE; CO2; EMISSIONS; DISTRIBUTED CONTROL; GLOBAL CHANGE; TIME-SERIES; ENERGY; CONSUMPTION; PERSPECTIVE;
D O I
10.1021/acs.est.5b06299
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The mitigation of anthropogenic carbon emissions: has moved beyond the local scale because they diffuse across boundaries, and the consumption that triggers emissions has become regional and global. A precondition of effective mitigation is to explicitly assess inter-regional transfer of emissions. This study presents a hybrid network model to track inter-regional carbon flows by combining network analysis and input-output analysis. The direct, embodied, and controlled emissions associated with regions are quantified for assessing various types of carbon flow. The network,oriented metrics called "controlled emissions" is proposed to cover the amount of carbon emissions that can be mitigated within a region by adjusting its consumption. The case study of the Jing-Jin-Ji Area suggests that CO2 emissions embodied in products are only partially controlled by a region from a network perspective. Controlled carbon accounted for about 70% of the total embodied carbon flows, while household consumption only controlled about 25% of Beijing's emissions, much lower than its proportion of total embodied carbon. In addition to quantifying emissions, the model can pinpoint the dominant processes and sectors of emissions transfer across regions. This technique is promising for searching efficient pathways of coordinated emissions control across various regions connected by trade.
引用
收藏
页码:4731 / 4741
页数:11
相关论文
共 87 条
[1]  
[Anonymous], BEIJ STAT YB
[2]  
Astrom K. J., 2012, Introduction to stochastic control theory
[3]   enaR: AnR package for Ecosystem Network Analysis [J].
Borrett, Stuart R. ;
Lau, Matthew K. .
METHODS IN ECOLOGY AND EVOLUTION, 2014, 5 (11) :1206-1213
[4]   Global non-linear effect of temperature on economic production [J].
Burke, Marshall ;
Hsiang, Solomon M. ;
Miguel, Edward .
NATURE, 2015, 527 (7577) :235-+
[5]   Three-scale input-output modeling for urban economy: Carbon emission by Beijing 2007 [J].
Chen, G. Q. ;
Guo, Shan ;
Shao, Ling ;
Li, J. S. ;
Chen, Zhan-Ming .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2013, 18 (09) :2493-2506
[6]   Low-carbon building assessment and multi-scale input-output analysis [J].
Chen, G. Q. ;
Chen, H. ;
Chen, Z. M. ;
Zhang, Bo ;
Shao, L. ;
Guo, S. ;
Zhou, S. Y. ;
Jiang, M. M. .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2011, 16 (01) :583-595
[7]   Nonzero-Sum Relationships in Mitigating Urban Carbon Emissions: A Dynamic Network Simulation [J].
Chen, Shaoqing ;
Chen, Bin ;
Su, Meirong .
ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2015, 49 (19) :11594-11603
[8]   Assessing the cumulative environmental impact of hydropower construction on river systems based on energy network model [J].
Chen, Shaoqing ;
Chen, Bin ;
Fath, Brian D. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2015, 42 :78-92
[9]   Urban energy consumption: Different insights from energy flow analysis, input-output analysis and ecological network analysis [J].
Chen, Shaoqing ;
Chen, Bin .
APPLIED ENERGY, 2015, 138 :99-107
[10]   Urban ecosystem modeling and global change: Potential for rational urban management and emissions mitigation [J].
Chen, Shaoqing ;
Chen, Bin ;
Fath, Brian D. .
ENVIRONMENTAL POLLUTION, 2014, 190 :139-149