Modeling Intercity CO2 Trading Scenarios in China: Complexity of Urban Networks Integrating Different Spatial Scales

Today, cities account for the majority of global energy consumption and CO2 emissions. The interaction between cities is critical for regional low-carbon development. At this time, China has turned to the full opening of the carbon trading market as an important policy tool for achieving its ambitio...

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Main Authors: Chongming Li, Na Li, Zuo Zhang, Lu Zhang, Zhi Li, Yanzhong Liu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2022/4888311
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author Chongming Li
Na Li
Zuo Zhang
Lu Zhang
Zhi Li
Yanzhong Liu
author_facet Chongming Li
Na Li
Zuo Zhang
Lu Zhang
Zhi Li
Yanzhong Liu
author_sort Chongming Li
collection DOAJ
description Today, cities account for the majority of global energy consumption and CO2 emissions. The interaction between cities is critical for regional low-carbon development. At this time, China has turned to the full opening of the carbon trading market as an important policy tool for achieving its ambitious emission reduction goals. This paper attempts to explore the spatial relationships among cities from the perspective of carbon trading. A “multiscenarios across different spatial scales” analysis framework applied to the allocation and trading of CO2 emission quotas among cities in China is proposed. Based on this framework, the carbon trading networks of 182 cities in China are specifically simulated under four different scenarios, with a comparative analysis of the networks’ complexity made from different perspectives. The results of the study are as follows: firstly, significant spatial network correlations exist between the cities’ carbon trading under each scenario. Secondly, on a national scale, there are more inner connections in carbon trading networks, with stronger correlations and robustness, while the degree of connection of intercity carbon trading is higher overall on a regional scale. Thirdly, on a national scale, no obvious core nodes exist in the network, while core nodes do exist in the overall network and in each region under the regional scale. Fourthly, cities in the central region have the highest core position overall. Finally, based on the research results, practical guidance in using the framework for achieving carbon reduction, promoting economic growth, and balancing regional development, as well as the important inspiration for policy formulation, is further discussed.
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spelling doaj-art-0efff70cf18a45e2b5472b84152030902025-02-03T01:22:58ZengWileyComplexity1099-05262022-01-01202210.1155/2022/4888311Modeling Intercity CO2 Trading Scenarios in China: Complexity of Urban Networks Integrating Different Spatial ScalesChongming Li0Na Li1Zuo Zhang2Lu Zhang3Zhi Li4Yanzhong Liu5School of Public AdministrationSchool of Public AdministrationSchool of Public AdministrationSchool of Public AdministrationSchool of Public AdministrationCollege of Resource and Environmental EngineeringToday, cities account for the majority of global energy consumption and CO2 emissions. The interaction between cities is critical for regional low-carbon development. At this time, China has turned to the full opening of the carbon trading market as an important policy tool for achieving its ambitious emission reduction goals. This paper attempts to explore the spatial relationships among cities from the perspective of carbon trading. A “multiscenarios across different spatial scales” analysis framework applied to the allocation and trading of CO2 emission quotas among cities in China is proposed. Based on this framework, the carbon trading networks of 182 cities in China are specifically simulated under four different scenarios, with a comparative analysis of the networks’ complexity made from different perspectives. The results of the study are as follows: firstly, significant spatial network correlations exist between the cities’ carbon trading under each scenario. Secondly, on a national scale, there are more inner connections in carbon trading networks, with stronger correlations and robustness, while the degree of connection of intercity carbon trading is higher overall on a regional scale. Thirdly, on a national scale, no obvious core nodes exist in the network, while core nodes do exist in the overall network and in each region under the regional scale. Fourthly, cities in the central region have the highest core position overall. Finally, based on the research results, practical guidance in using the framework for achieving carbon reduction, promoting economic growth, and balancing regional development, as well as the important inspiration for policy formulation, is further discussed.http://dx.doi.org/10.1155/2022/4888311
spellingShingle Chongming Li
Na Li
Zuo Zhang
Lu Zhang
Zhi Li
Yanzhong Liu
Modeling Intercity CO2 Trading Scenarios in China: Complexity of Urban Networks Integrating Different Spatial Scales
Complexity
title Modeling Intercity CO2 Trading Scenarios in China: Complexity of Urban Networks Integrating Different Spatial Scales
title_full Modeling Intercity CO2 Trading Scenarios in China: Complexity of Urban Networks Integrating Different Spatial Scales
title_fullStr Modeling Intercity CO2 Trading Scenarios in China: Complexity of Urban Networks Integrating Different Spatial Scales
title_full_unstemmed Modeling Intercity CO2 Trading Scenarios in China: Complexity of Urban Networks Integrating Different Spatial Scales
title_short Modeling Intercity CO2 Trading Scenarios in China: Complexity of Urban Networks Integrating Different Spatial Scales
title_sort modeling intercity co2 trading scenarios in china complexity of urban networks integrating different spatial scales
url http://dx.doi.org/10.1155/2022/4888311
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