Analysis of Spatial Carbon Metabolism by ENA: A Case Study of Tongzhou District, Beijing

Yongchao Qu, Jian Zhang, Chongyuan Xu, Yichao Gao, Shanwen Zheng () and Meiling Xia
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Yongchao Qu: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Jian Zhang: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Chongyuan Xu: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Yichao Gao: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Shanwen Zheng: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Meiling Xia: Beijing Tsinghua TongHeng Urban Planning & Design Institute, Beijing 100085, China

Land, 2022, vol. 11, issue 9, 1-17

Abstract: Carbon metabolism research has attracted worldwide attention as an important way to cope with climate change, promote carbon emission reduction, increase carbon sequestration, and support low-carbon city construction. Ecological network analysis (ENA) plays an important role in network analysis and simulation of carbon metabolism. However, current studies largely focus on single elements or local processes while rarely analyzing the spatial coupling between land use and carbon metabolism. Therefore, taking Tongzhou District as an example, based on the data of land use change and energy consumption, this study constructed an analysis framework based on ENA to explore the comprehensive impact of land use changes on carbon metabolism. The results show the following: (1) From 2014 to 2020, the total carbon emissions increased year by year. Carbon emissions of other construction land (OCL) were dominant, while the carbon sequestration capacity of forest land (FL) increased by 236%. The positive carbon metabolic density remained relatively stable, while the negative carbon metabolic density decreased year by year. (2) The negative carbon flow was concentrated in the transfer of other land to OCL, accounting for 40.2% of the total negative “carbon flow.” The positive carbon flow was primarily from the transfer of other land to FL. (3) From 2014 to 2016, the spatial ecological relationships of carbon flow were dominated by exploitation and control. From 2016 to 2018, competition relationships intensified due to the expansion of the field; from 2016 to 2018, exploitation and control relationships, competition relationships, and mutualism relationships increased significantly and were evenly distributed. This study provides decision-making guidance for the subsequent formulation of government carbon emission reduction policies.

Keywords: carbon metabolism; carbon flow; ENA; spatial and temporal characteristics; Tongzhou District (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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