Selection of carbon emissions control industries in China: An approach based on complex networks control perspective

Ying Hu, Yang Yu and Abbas Mardani

Technological Forecasting and Social Change, 2021, vol. 172, issue C

Abstract: To achieve the goal of reaching the peak of carbon emissions by 2030, in the absence of conditions to implement carbon emissions target control of the whole industry at this stage, it is important to select carbon emissions control industries. Carbon emissions will transfer amongst industries with the flow of production factors, forming a complex linkage network structure. Based on the theory of controllability complex networks, we built a carbon emissions control industry selection model and proposed an exactly controllable minimum control industry set search algorithm for minimising carbon emissions reduction cost (MCMCS algorithm) to select the carbon emissions control industries of China's inter-industry carbon emissions transfer network in 2017. The results show that most of the carbon emissions control industries avoid high-degree industries, most of which are less affected by upstream industries, and have greater impact on downstream high-degree industries and intermediary industries through carbon emissions transfer. Setting carbon emissions reduction targets for these industries for direct control will indirectly control the high-degree industries with high-emission reduction cost, great control difficulty, and great economic impact in the short term, and they can make the whole carbon emissions transfer network achieve the expected carbon emissions control target in a limited time.

Keywords: Inter-industry carbon emissions transfer; Carbon emissions control industries; Carbon emissions transfer network; Complex networks control (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521004625

DOI: 10.1016/j.techfore.2021.121030

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