Maximizing the effectiveness of carbon emissions abatement in China across carbon communities

Li Huang, Scott Kelly, Xunpeng Shi, Kangjuan Lv, Xuan Lu and Damien Giurco

Energy Economics, 2022, vol. 106, issue C

Abstract: The invisible and complex transfer of embodied carbon emissions makes the traditional production or consumption approach insufficient to inform emissions abatement actions because carbon communities have emerged during the transmission procedure of embodied carbon emissions. The carbon community—a group of sectors with more intensive embodied carbon emissions trades within the group than outside—provides the missing critical information about carbon abatement beyond the commonly used production and consumption approaches. This research aims to detect the carbon communities and examine the effect of community structure on sectors' direct carbon emissions. Unlike the industrial agglomeration in traditional economics and management studies, where the border is predefined in a geographical or administrative region, the hybrid input-output analysis and network analysis method detects the carbon communities data-driven, focusing on the embodied carbon emissions trades. Moreover, the hierarchical linear model examines the effect of community structure on sectors' direct carbon emissions to inform climate change policy-making and planning. The findings suggest around 19 carbon communities existing in China, which can advise local governments on their external cooperation strategies for a synergy. In addition, the regression results indicate that the increasing size and density of carbon communities can help mitigate sectors' direct carbon emissions.

Keywords: Carbon emissions; Transmission; Network analysis; Input–output analysis; Community; Industrial agglomeration (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:106:y:2022:i:c:s0140988321006368

DOI: 10.1016/j.eneco.2021.105801

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