Carbon Balance Matching Relationships and Spatiotemporal Evolution Patterns in China’s National-Level Metropolitan Areas

In the urgent context of global climate change and carbon neutrality goals, effective carbon balance regulation is critical for achieving temperature control targets. Metropolitan areas encounter significant challenges in carbon emission reduction, energy transition advancement, and enhancement of s...

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Main Authors: Mengqi Liu, Yang Yu, Maomao Zhang, Pengtao Wang, Nuo Shi, Yichen Ren, Di Zhang
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Land
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Online Access:https://www.mdpi.com/2073-445X/14/4/800
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author Mengqi Liu
Yang Yu
Maomao Zhang
Pengtao Wang
Nuo Shi
Yichen Ren
Di Zhang
author_facet Mengqi Liu
Yang Yu
Maomao Zhang
Pengtao Wang
Nuo Shi
Yichen Ren
Di Zhang
author_sort Mengqi Liu
collection DOAJ
description In the urgent context of global climate change and carbon neutrality goals, effective carbon balance regulation is critical for achieving temperature control targets. Metropolitan areas encounter significant challenges in carbon emission reduction, energy transition advancement, and enhancement of sequestration capabilities. However, traditional carbon balance analysis methods have limitations in capturing dynamic changes and guiding precise regulation. Therefore, this study developed a dynamic–static classification system for carbon balance based on the Ecological Support Coefficient (ESC) and the Economic Contributive Coefficient (ECC). This system examined carbon emissions and carbon sequestration in China’s 14 national-level metropolitan areas from 2000 to 2020. The results showed that: (1) Carbon emissions showed an increasing trend, exhibiting a spatial distribution with higher levels in the north, moderate levels in the central region, and the lowest levels in the southeast. In contrast, carbon sequestration exhibited a spatial pattern with higher levels in the east, moderate levels in the central region, and lower levels in the west. (2) Static classification revealed that the ECC and ESC of metropolitan areas in the central and northern regions were relatively weaker than those in other regions. Dynamic classification further showed an upward trend in the economic and ecological capabilities of these central and northern metropolitan areas. In contrast, metropolitan areas along the coast and within the Yangtze River Economic Belt needed to optimize their economic–ecological coordination efficiency. Although southern coastal metropolitan areas demonstrated robust economic vitality, they encountered significant ecological support pressures. (3) Economic development level and ecological environmental quality were the predominant factors in metropolitan area classification. Regions with a higher ECC tended to exhibit an enhanced ESC, while regions with a stronger ESC prioritized economic growth. This classification system provided a solid scientific basis for formulating differentiated low-carbon transformation strategies, thereby supporting high-quality development in China’s metropolitan areas while maintaining a dynamic balance between economic and ecologic objectives. Moreover, it offered both theoretical foundations and practical guidance for optimizing sustainable development pathways in similar metropolitan areas globally.
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spelling doaj-art-332dc05ad0c74e10becaeb11ab9bdecc2025-08-20T03:13:58ZengMDPI AGLand2073-445X2025-04-0114480010.3390/land14040800Carbon Balance Matching Relationships and Spatiotemporal Evolution Patterns in China’s National-Level Metropolitan AreasMengqi Liu0Yang Yu1Maomao Zhang2Pengtao Wang3Nuo Shi4Yichen Ren5Di Zhang6School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, ChinaSchool of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, ChinaCollege of Public Administration, Huazhong University of Science and Technology, Wuhan 430079, ChinaSchool of Tourism, Xi’an International Studies University, Xi’an 710128, ChinaSchool of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, ChinaSchool of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, ChinaSchool of Asian and African Studies, Xi’an International Studies University, Xi’an 710128, ChinaIn the urgent context of global climate change and carbon neutrality goals, effective carbon balance regulation is critical for achieving temperature control targets. Metropolitan areas encounter significant challenges in carbon emission reduction, energy transition advancement, and enhancement of sequestration capabilities. However, traditional carbon balance analysis methods have limitations in capturing dynamic changes and guiding precise regulation. Therefore, this study developed a dynamic–static classification system for carbon balance based on the Ecological Support Coefficient (ESC) and the Economic Contributive Coefficient (ECC). This system examined carbon emissions and carbon sequestration in China’s 14 national-level metropolitan areas from 2000 to 2020. The results showed that: (1) Carbon emissions showed an increasing trend, exhibiting a spatial distribution with higher levels in the north, moderate levels in the central region, and the lowest levels in the southeast. In contrast, carbon sequestration exhibited a spatial pattern with higher levels in the east, moderate levels in the central region, and lower levels in the west. (2) Static classification revealed that the ECC and ESC of metropolitan areas in the central and northern regions were relatively weaker than those in other regions. Dynamic classification further showed an upward trend in the economic and ecological capabilities of these central and northern metropolitan areas. In contrast, metropolitan areas along the coast and within the Yangtze River Economic Belt needed to optimize their economic–ecological coordination efficiency. Although southern coastal metropolitan areas demonstrated robust economic vitality, they encountered significant ecological support pressures. (3) Economic development level and ecological environmental quality were the predominant factors in metropolitan area classification. Regions with a higher ECC tended to exhibit an enhanced ESC, while regions with a stronger ESC prioritized economic growth. This classification system provided a solid scientific basis for formulating differentiated low-carbon transformation strategies, thereby supporting high-quality development in China’s metropolitan areas while maintaining a dynamic balance between economic and ecologic objectives. Moreover, it offered both theoretical foundations and practical guidance for optimizing sustainable development pathways in similar metropolitan areas globally.https://www.mdpi.com/2073-445X/14/4/800carbon emissionscarbon balance zoningnational metropolitan areasecological support coefficienteconomic contributive coefficient
spellingShingle Mengqi Liu
Yang Yu
Maomao Zhang
Pengtao Wang
Nuo Shi
Yichen Ren
Di Zhang
Carbon Balance Matching Relationships and Spatiotemporal Evolution Patterns in China’s National-Level Metropolitan Areas
Land
carbon emissions
carbon balance zoning
national metropolitan areas
ecological support coefficient
economic contributive coefficient
title Carbon Balance Matching Relationships and Spatiotemporal Evolution Patterns in China’s National-Level Metropolitan Areas
title_full Carbon Balance Matching Relationships and Spatiotemporal Evolution Patterns in China’s National-Level Metropolitan Areas
title_fullStr Carbon Balance Matching Relationships and Spatiotemporal Evolution Patterns in China’s National-Level Metropolitan Areas
title_full_unstemmed Carbon Balance Matching Relationships and Spatiotemporal Evolution Patterns in China’s National-Level Metropolitan Areas
title_short Carbon Balance Matching Relationships and Spatiotemporal Evolution Patterns in China’s National-Level Metropolitan Areas
title_sort carbon balance matching relationships and spatiotemporal evolution patterns in china s national level metropolitan areas
topic carbon emissions
carbon balance zoning
national metropolitan areas
ecological support coefficient
economic contributive coefficient
url https://www.mdpi.com/2073-445X/14/4/800
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