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Environmental science and pollution research international
Nov, 2023;30 (51): 111459-111480.

Spatiotemporal evolution trend and decoupling type identification of transport carbon emissions from economic development in China.

Qian Cui, Zhixiang Zhou, Dongjie Guan, Lilei Zhou, Ke Huang, Yuqian Xue
Author Information
  1. Qian Cui: College of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing, 400074, People's Republic of China.
  2. Zhixiang Zhou: College of Civil and Transportation Engineering, Shenzhen University, Room A507, Shenzhen, 518060, People's Republic of China. zhixiangzhou@szu.edu.cn. ORCID
  3. Dongjie Guan: School of Smart City, Chongqing Jiaotong University, Chongqing, 400074, People's Republic of China.
  4. Lilei Zhou: School of Civil Engineering, Chongqing Jiaotong University, Chongqing, 400074, People's Republic of China.
  5. Ke Huang: College of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing, 400074, People's Republic of China.
  6. Yuqian Xue: College of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing, 400074, People's Republic of China.
PMID: 37814052 DOI: 10.1007/s11356-023-29857-z

Abstract

Carbon emissions are a major concern in China, and transportation is an important part of it. In this paper, data on China's 30 provinces' transport carbon emissions from 2005 to 2019 were selected to construct a spatial autocorrelation model and identified the decoupling types, which revealed the relationship between transport carbon emissions and economic development. This study suggests a regulation strategy for provincial transport carbon emissions in China based on the contribution rates of transport carbon emission variables. According to the findings, transport carbon emissions of China indicated a slow rise from 2005 to 2019, the annual growth rate has fluctuated downward, and petroleum products have been the most major source. The geographical correlation of transport carbon emissions has gradually improved, and the transport carbon emission intensity has become more significant. Differences in the transport carbon emission intensity slightly increased, which were significantly regionally correlated. There were seven forms of decoupling between yearly provincial transport carbon emissions and economic development, with weak decoupling accounting for the largest proportion, 45.24%. Decoupling was achieved in 83.33% of the provinces in the period of 2005-2019. As a consequence of factor decomposition, the energy intensity, transport intensity, and economic structure played an overall inhibitory role, while the carbon emission intensity, economic scale, and population played promoting roles. The economic scale was the most important influencing factor.

Keywords

Contribution rates of influencing factors Economic decoupling Spatiotemporal evolution Transport carbon emissions

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Grants

  1. 42171298/National Natural Science Foundation of China
  2. 42201333/National Natural Science Foundation of China
  3. 20FJYB035/Late Project of National Social Science Foundation in China

MeSH Term

Economic Development
Carbon
Carbon Dioxide
China
Transportation

Chemicals

Carbon
Carbon Dioxide
Journal Article

Word Cloud

Created with Highcharts 10.0.0carbontransportemissionseconomicdecouplingintensityChinaemissiondevelopmentmajorimportant20052019provincialratesfactorplayedscaleinfluencingSpatiotemporalevolutionCarbonconcerntransportationpartpaperdataChina's30provinces'selectedconstructspatialautocorrelationmodelidentifiedtypesrevealedrelationshipstudysuggestsregulationstrategybasedcontributionvariablesAccordingfindingsindicatedslowriseannualgrowthratefluctuateddownwardpetroleumproductssourcegeographicalcorrelationgraduallyimprovedbecomesignificantDifferencesslightlyincreasedsignificantlyregionallycorrelatedsevenformsyearlyweakaccountinglargestproportion4524%Decouplingachieved8333%provincesperiod2005-2019consequencedecompositionenergystructureoverallinhibitoryrolepopulationpromotingrolestrendtypeidentificationContributionfactorsEconomicTransport

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