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Promoting low-carbon land use: from theory to practical application through exploring new methods

Author

Listed:
  • Xiaowei Chuai

    (Nanjing University
    Nanjing University
    Ministry of Natural Resources)

  • Hongbo Xu

    (Zhejiang Academy of Surveying and Mapping)

  • Zemiao Liu

    (Nanjing University)

  • Ai Xiang

    (Nanjing University)

  • Yuting Luo

    (Nanjing University)

  • Wanliu Mao

    (Zhejiang Academy of Surveying and Mapping)

  • Tong Wang

    (Nanjing University)

  • Xin Ye

    (Nanjing University)

  • Lijuan Miao

    (Nanjing University of Information Science & Technology)

  • Rongqin Zhao

    (North China University of Water Resource and Electric Power)

  • Fengtai Zhang

    (Chongqing University of Technology)

Abstract

Cities are main carbon emissions generators. Land use changes can not only affect terrestrial ecosystems carbon, but also anthropogenic carbon emissions. However, carbon monitoring at a spatial level is still coarse, and low-carbon land use encounters the challenge of being unable to adjust at the patch scale. This study addresses these limitations by using land-use data and various auxiliary data to explore new methods. The approach involves developing a high-resolution carbon monitoring model and investigating a patch-scale low-carbon land use model by integrating high carbon sink/source images with the Future Land Use Simulation model. Between 2000 and 2020, the results reveal an increasing trend in both carbon emissions and carbon sinks in the Shangyu district. Carbon sinks can only offset approximately 3% of the total carbon emissions. Spatially, the north exhibits net carbon emissions, while the southern region functions more as a carbon sink. A total of 14.5% of the total land area witnessed a change in land-use type, with the transfer-out of cropland constituting the largest area at 96.44 km2, accounting for 50% of the total transferred area. Land-use transfer resulted in an annual increase of 77.72 × 104 t in carbon emissions between 2000 and 2020. Through land-use structure optimisation, carbon emissions are projected to increase by only 7154 t C/year from 2000 to 2030, significantly lower than the amount between 2000 and 2020. Further low-carbon land optimisation at the patch scale can enhance the carbon sink by 129.59 t C/year. The conclusion drawn is that there is considerable potential to reduce carbon emissions through land use control. The new methods developed in our study can effectively contribute to high-resolution carbon monitoring in spatial contexts and support low-carbon land use, promoting the application of low-carbon land use from theory to practice. This will provide technological guidance for land use planning, city planning, and so forth.

Suggested Citation

  • Xiaowei Chuai & Hongbo Xu & Zemiao Liu & Ai Xiang & Yuting Luo & Wanliu Mao & Tong Wang & Xin Ye & Lijuan Miao & Rongqin Zhao & Fengtai Zhang, 2024. "Promoting low-carbon land use: from theory to practical application through exploring new methods," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03192-1
    DOI: 10.1057/s41599-024-03192-1
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    References listed on IDEAS

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    1. Bhanage Vinayak & Han Soo Lee & Shirishkumar Gedem, 2021. "Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model," Sustainability, MDPI, vol. 13(2), pages 1-22, January.
    2. Lishan Ran & David E. Butman & Tom J. Battin & Xiankun Yang & Mingyang Tian & Clément Duvert & Jens Hartmann & Naomi Geeraert & Shaoda Liu, 2021. "Substantial decrease in CO2 emissions from Chinese inland waters due to global change," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    3. Lu, Heli & Liu, Guifang, 2014. "Spatial effects of carbon dioxide emissions from residential energy consumption: A county-level study using enhanced nocturnal lighting," Applied Energy, Elsevier, vol. 131(C), pages 297-306.
    4. Han Huang & Yang Zhou & Mingjie Qian & Zhaoqi Zeng, 2021. "Land Use Transition and Driving Forces in Chinese Loess Plateau: A Case Study from Pu County, Shanxi Province," Land, MDPI, vol. 10(1), pages 1-15, January.
    5. Rui Lu & Anne Gauthier & Gert Stulp, 2023. "Fertility preferences in China in the twenty-first century," Journal of Population Research, Springer, vol. 40(2), pages 1-30, June.
    6. Cai, Bofeng & Guo, Huanxiu & Ma, Zipeng & Wang, Zhixuan & Dhakal, Shobhakar & Cao, Libin, 2019. "Benchmarking carbon emissions efficiency in Chinese cities: A comparative study based on high-resolution gridded data," Applied Energy, Elsevier, vol. 242(C), pages 994-1009.
    7. Shilong Piao & Jingyun Fang & Philippe Ciais & Philippe Peylin & Yao Huang & Stephen Sitch & Tao Wang, 2009. "The carbon balance of terrestrial ecosystems in China," Nature, Nature, vol. 458(7241), pages 1009-1013, April.
    8. Chunhua Zhang & Weimin Ju & Jing Chen & Mei Zan & Dengqiu Li & Yanlian Zhou & Xiqun Wang, 2013. "China’s forest biomass carbon sink based on seven inventories from 1973 to 2008," Climatic Change, Springer, vol. 118(3), pages 933-948, June.
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