RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2025, Vol. 34 >> Issue (3): 546-557.doi: 10.11870/cjlyzyyhj202503007

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Effects of Land Use Change on Spatio-temporal Pattern of Carbon Source/Sink in Poyang Lake Basin

HUANG Yuan-ting1,ZHONG Ye-xi2,BI Man-yu3   

  1. (Geography and Environment of Jiangxi Normal Unversity, Nanchang 330000,China)
  • Online:2025-03-20 Published:2025-03-20

Abstract: In order to promote low-carbon sustainable development and achieve carbon peaking and carbon neutrality goals, it is important to estimate regional carbon storage and carbon emissions. This study took Poyang Lake Basin as an example. Land use data for 1990, 2000, 2010, and 2020 were selected. The InVEST model was used to estimate carbon sequestration. The carbon emission coefficient method combined with the energy consumption algorithms was used to estimate carbon sources. The spatial-temporal pattern of carbon sources/sinks under different land use changes was analyzed. The results indicated: (1) The Poyang Lake Basin was primarily composed of cropland and forestland. Over the past 30 years, there had been a significant reduction in both cropland and forestland, while construction land had markedly increased. (2) From 1990 to 2020, the carbon storage in the Poyang Lake Basin first slightly increased and then gradually decreased, with significant spatial heterogeneity—lower around the lake area and higher in the surrounding regions. The growth in carbon storage mainly stemmed from the conversion of cropland to forestland, grassland to forestland, and water bodies to cropland, while the conversion out of cropland and forestland led to a substantial reduction in carbon storage. (3) Between 1990 and 2020, the net carbon emissions initially increased slowly and then increased rapidly. Construction land was the primary source of carbon emissions, which were mainly distributed in the economically developed areas around the lake and in the southern regions, with Nanchang being the most prominent. (4) The carbon footprint pressure index showed a significant increasing trend. Nanchang, Xinyu, Pingxiang, and Yingtan were categorized as high-pressure cities, while Ganzhou, Fuzhou, Ji'an, and Shangrao were identified as low-pressure cities.

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