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Changes in Wuhan’s Carbon Stocks and Their Spatial Distributions in 2050 under Multiple Projection Scenarios

  • Yujie Zhang
  • , Xiaoyu Wang
  • , Lei Zhang
  • , Hongbin Xu
  • , Taeyeol Jung
  • , Lei Xiao
  • Kyungpook National University
  • South China University of Technology
  • Inner Mongolia Academy of Forestry Sciences
  • State Key Laboratory of Subtropical Building and Urban Science
  • Guangzhou Key Laboratory of Landscape Architecture

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Urbanization in the 21st century has reshaped carbon stock distributions through the expansion of cities. By using the PLUS and InVEST models, this study predicts land use and carbon stocks in Wuhan in 2050 using three future scenarios. Employing local Moran’s I, we analyze carbon stock clustering under these scenarios, and the Getis–Ord Gi* statistic identifies regions with significantly higher and lower carbon-stock changes between 2020 and 2050. The results reveal a 2.5 Tg decline in Wuhan’s carbon stock from 2000 to 2020, concentrated from the central to the outer city areas along the Yangtze River. By 2050, the ecological conservation scenario produced the highest carbon stock prediction, 77.48 Tg, while the economic development scenario produced the lowest, 76.4 Tg. High-carbon stock-change areas cluster in the north and south, contrasting with low-change area concentrations in the center. This research provides practical insights that support Wuhan’s sustainable development and carbon neutrality goals.

Original languageEnglish
Article number6684
JournalSustainability (Switzerland)
Volume16
Issue number15
DOIs
StatePublished - Aug 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  3. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  4. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • PLUS-InVEST model
  • Wuhan
  • carbon storage
  • land use
  • local spatial autocorrelation
  • scenario simulation

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