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Carbon emission and economic development trade-offs for optimizing land-use allocation in the Yangtze River Delta, China

journal contribution
posted on 2024-11-03, 09:03 authored by Wei Li, Zhenjie Chen, Manchun Li, Han Zhang, Mingye Li, Xiaoqian Qiu, Chen Zhou
Reconciling carbon emissions and GDP development is a challenge for most Chinese cities in the sustainable development process. Taking the Yangtze River Delta of China as an example, this study calculated carbon-emission inventories for five typical years and assigned anthropogenic carbon emissions to land-use types. A multi-objective particle swarm algorithm was used to consider three functions of land-use allocation: maximizing GDP, minimizing carbon emissions, and maximizing suitability. Thereafter, the technique for order of preference by similarity to ideal solution (TOPSIS) method was combined to find the optimal solution for carbon emission and economic development trade-offs. It is observed that Jiangsu has the largest carbon emissions in the Yangtze River Delta region; energy consumption is the main source of the carbon emissions, and industrial land is the most carbon intensive region. The land-use allocation obtained by multi-objective optimization with the TOPSIS evaluation method increases GDP and reduces carbon emissions, which is worthy of reference for land planners. Land use optimization from the perspective of balancing carbon emissions and economic development can provide a useful reference for the rational use of land resources and socio-economic sustainable development.

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Related Materials

  1. 1.
    DOI - Is published in 10.1016/j.ecolind.2023.109950
  2. 2.
    ISSN - Is published in 1470160X

Journal

Ecological Indicators

Volume

147

Number

109950

Start page

1

End page

14

Total pages

14

Publisher

Elsevier BV

Place published

Netherlands

Language

English

Copyright

© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).

Former Identifier

2006122503

Esploro creation date

2023-05-31

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