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...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/4888311 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832562237608296448 |
|---|---|
| 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. |
| format | Article |
| id | doaj-art-0efff70cf18a45e2b5472b8415203090 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| 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 |
| work_keys_str_mv | AT chongmingli modelingintercityco2tradingscenariosinchinacomplexityofurbannetworksintegratingdifferentspatialscales AT nali modelingintercityco2tradingscenariosinchinacomplexityofurbannetworksintegratingdifferentspatialscales AT zuozhang modelingintercityco2tradingscenariosinchinacomplexityofurbannetworksintegratingdifferentspatialscales AT luzhang modelingintercityco2tradingscenariosinchinacomplexityofurbannetworksintegratingdifferentspatialscales AT zhili modelingintercityco2tradingscenariosinchinacomplexityofurbannetworksintegratingdifferentspatialscales AT yanzhongliu modelingintercityco2tradingscenariosinchinacomplexityofurbannetworksintegratingdifferentspatialscales |