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Define, process and describe the intersectoral embedded carbon flow network in China

This article focuses on defining the intersectoral embedded carbon flow network as a matrix to mimic the complex economic-energy-environment symbiotic system in China. We propose a set of synthetical methodologies, which combines life cycle assessment (LCA) and social network analysis (SNA) in the i...

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Detalles Bibliográficos
Autores principales: Wu, Kaiyao, Yang, Tinggan, Wei, Xiaoyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6812374/
https://www.ncbi.nlm.nih.gov/pubmed/31667101
http://dx.doi.org/10.1016/j.mex.2019.08.003
Descripción
Sumario:This article focuses on defining the intersectoral embedded carbon flow network as a matrix to mimic the complex economic-energy-environment symbiotic system in China. We propose a set of synthetical methodologies, which combines life cycle assessment (LCA) and social network analysis (SNA) in the input–output framework. The nodes and relations between nodes in the network are delicately designed such that these relations, which represent the carbon intensity of total intersectoral input between sectors, can be comparable among sectors and over time. Subsequently, based on longitudinal data of input–output tables in China, we derive, sequentialize and dichotomize matrices in order to apply the SNA method to describe the evolution of the intersectoral embedded carbon flow network. The SNA methods used include network visualization, triad census, cohesion metrics, position metrics and core–periphery modeling. Our synthetical methodologies provide a potential systematic solution to carbon reduction in China and help policy makers determine policy priorities rationally. • By constructing an intersectoral embedded carbon flow network matrix, we provide an easily explicable map to aid in the investigation and research in human derived CO(2) emissions embedded in the network. • By describing the longitudinal network matrices with SNA, the evolution of the complex economic-energy-environment symbiotic system in China can be mapped out, such as an example illustrated in Wu et al. [1].