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Sökning: id:"swepub:oai:lup.lub.lu.se:063300a9-7f0b-438b-a017-fa9f08aa6de4" > Spatial-temporal di...

Spatial-temporal differentiation and influencing factors of carbon emission trajectory in Chinese cities - A case study of 247 prefecture-level cities

Yang, Xinlian (författare)
Ningbo University
Jin, Ke (författare)
Ningbo University
Duan, Zheng (författare)
Lund University,Lunds universitet,BECC: Biodiversity and Ecosystem services in a Changing Climate,Centrum för miljö- och klimatvetenskap (CEC),Naturvetenskapliga fakulteten,MERGE: ModElling the Regional and Global Earth system,Institutionen för naturgeografi och ekosystemvetenskap,Centre for Environmental and Climate Science (CEC),Faculty of Science,Dept of Physical Geography and Ecosystem Science
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Gao, Yuhe (författare)
University of Pittsburgh
Sun, Yanwei (författare)
Ningbo University
Gao, Chao (författare)
Ningbo University
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 (creator_code:org_t)
2024
2024
Engelska.
Ingår i: Science of the Total Environment. - 0048-9697. ; 928
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Cities, where human energy activities and greenhouse gas emissions are concentrated, contribute significantly to alleviating the impacts of global climate change. Utilizing the China Carbon Emissions Accounting Database (CEADs) to provide carbon dioxide emission inventories for urban areas in China at the prefecture level, this study closely examines the historical evolution trajectories of carbon emissions across 247 urban units from 2005 to 2019. The logarithmic cubic function model was employed to simulate these trajectories, evaluating urban emission peaks and classifying the different carbon emission trajectories. Further, the Geographical and Temporal Weighted Regression model was employed to explore spatiotemporal traits and essential variables that impact the variations in carbon emissions among four identified trajectory types. Our results showed that Chinese urban carbon emission trajectories can be classified into four categories: a) peaking emissions, b) fluctuating growth, c) continuous growth, and d) passive decline. Specifically, 43 cities, primarily in North China, proactively attained their emission peak post-2010, driven by the reduction in secondary industry and energy intensity. 90 cities, largely industrial hubs in the southeast coast and inland, reached an emission plateau around 2015, exhibiting fluctuating growth due to dependencies on secondary industries. 101 cities, predominantly located in western and central regions, demonstrated a clear upward trend in carbon emissions, propelled by rapid urbanization and heavy industry-oriented economic development. Lastly, 13 cities, typically in the northeastern and southwestern regions, experienced a passive decline in carbon emissions, attributable to resource depletion or economic downturns. It is evident that China's city-level carbon peaking has demonstrated some effectiveness, yet considerable progress is still required.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Miljövetenskap (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Environmental Sciences (hsv//eng)

Nyckelord

Carbon emission trajectory
Influencing factors
Spatial-temporal differentiation
Urbanization

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Yang, Xinlian
Jin, Ke
Duan, Zheng
Gao, Yuhe
Sun, Yanwei
Gao, Chao
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NATURVETENSKAP
NATURVETENSKAP
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Lunds universitet

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