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Author:

Chen, Y. (Chen, Y..) | Yang, L. (Yang, L..) | Peng, H. (Peng, H..) | Zhang, X. (Zhang, X..) | Zhang, S. (Zhang, S..) | Lu, H. (Lu, H..) | Yao, L. (Yao, L..) | Xia, J. (Xia, J..)

Indexed by:

EI Scopus SCIE

Abstract:

This study constructs a comprehensive framework for exploring the relevance between green development level and environmental footprint in three typical mega-urban agglomerations of Yangtze River Economic Belt (YREB) of China. This framework consists of the three-dimensional ecological footprint (EF3D), carbon footprint (CF), cloud model, and Environmental Kuznets Curve (EKC). Results reveal that there exist an increased EF3D and a decreased ecological carrying capacity in the YREB, with annual change rates of 4.45% and −0.46%, respectively. According to ecological footprint depth, 24.61, 17.59, and 30.89 times of current local land area are required for supporting regional development in the YREB upstream, midstream, and downstream urban agglomerations, respectively. There is an increased tendency in CF, especially in the midstream urban agglomeration with an increased rate of 5.25%. Carbon pressure is mostly contributed by crude oil (34.47%) and raw coal (31.55%). Moreover, green development level in the YREB shows an increased tendency with an annual rate of 0.5%, and that in the downstream urban agglomeration is generally greater than other areas. The relevance between green development level and environmental footprint is mainly inverted U-shaped or inverted N-shaped EKC types. CF in the YREB and its upstream urban agglomeration begins to decline when green development levels are 3.44 in 2020 and 3.26 in 2020, respectively. EF3D in the midstream urban agglomeration starts to fall when green development level reaches 3.36 in 2019. EF3D from cultivated land and fossil fuel land has a positive impact on the improvement of relevance. Overall, the developed framework can be applied to areas where there is a conflict between economic development and environmental protection. Furthermore, dynamic prediction of green development level and environmental footprint as well as their correlation mechanism under different scenarios are still required for enhancing environmental sustainability and promoting regional coordinated development. © 2024 Elsevier Ltd

Keyword:

Mega-urban agglomerations Carbon footprint Environmental footprint Environmental sustainability Green development level

Author Community:

  • [ 1 ] [Chen Y.]School of Economics and Management, Hebei University of Technology, Tianjin, 300401, China
  • [ 2 ] [Chen Y.]Beijing-Tianjin-Hebei Development Research Center, Hebei University of Technology, Tianjin, 300401, China
  • [ 3 ] [Yang L.]School of Economics and Management, Hebei University of Technology, Tianjin, 300401, China
  • [ 4 ] [Peng H.]School of Economics and Management, Hebei University of Technology, Tianjin, 300401, China
  • [ 5 ] [Peng H.]Institute of Circular Economy, Beijing University of Technology, Beijing, 100124, China
  • [ 6 ] [Peng H.]Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, China
  • [ 7 ] [Zhang X.]School of Economics and Management, Hebei University of Technology, Tianjin, 300401, China
  • [ 8 ] [Zhang S.]School of Economics and Management, Hebei University of Technology, Tianjin, 300401, China
  • [ 9 ] [Lu H.]Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
  • [ 10 ] [Yao L.]School of Economics and Management, Hebei University of Technology, Tianjin, 300401, China
  • [ 11 ] [Xia J.]Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
  • [ 12 ] [Xia J.]State Key Laboratory of Water Resources & Hydropower Engineering Sciences, Wuhan University, Wuhan, 430000, China

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Source :

Journal of Cleaner Production

ISSN: 0959-6526

Year: 2024

Volume: 436

1 1 . 1 0 0

JCR@2022

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 9

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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