Carbon Emission Risk from Land Use in Typical Regions of Middle and Lower Yangtze River—A Case Study at Jiujiang City, Jianxi Province

Liu Chunying; Tan Siyuan; WangJunbo; Liu Li

doi:10.13961/j.cnki.stbctb.20230220.003

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Carbon Emission Risk from Land Use in Typical Regions of Middle and Lower Yangtze River—A Case Study at Jiujiang City, Jianxi Province

- Carbon Emission Risk from Land Use in Typical Regions of Middle and Lower Yangtze River—A Case Study at Jiujiang City, Jianxi Province
- Bulletin of Soiland Water Conservation Vol. 43, Issue 1, Pages: 341-349(2023)
- 作者机构：
  
  1. 江西财经大学旅游与城市管理学院,江西,南昌,330032
  2. 赣州市住房公积金管理中心,江西,赣州,341000
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.20230220.003
  CLC： X24;F301
- Published：2023
- 稿件说明：
移动端阅览
Liu Chunying, Tan Siyuan, WangJunbo, et al. Carbon Emission Risk from Land Use in Typical Regions of Middle and Lower Yangtze River—A Case Study at Jiujiang City, Jianxi Province[J]. Bulletin of Soiland Water Conservation, 2023, 43(1): 341-349.
DOI：

Liu Chunying, Tan Siyuan, WangJunbo, et al. Carbon Emission Risk from Land Use in Typical Regions of Middle and Lower Yangtze River—A Case Study at Jiujiang City, Jianxi Province[J]. Bulletin of Soiland Water Conservation, 2023, 43(1): 341-349. DOI： 10.13961/j.cnki.stbctb.20230220.003.

摘要

[目的] 定量测算江西省九江市土地利用碳排放，揭示其时空演变特征，并估算土地利用碳排放风险，为九江市构建绿色低碳土地利用方式提供科学参考。[方法] 采用土地利用碳排放系数法测度2000—2020年九江市土地利用碳排放和时空变化规律，并从网格化的视角，利用碳排放风险指数识别各县区碳排放风险，基于对数平均迪式指数(LMDI)模型，分析土地利用碳排放的影响因素。[结果] 2000—2020年九江市土地利用净碳排放量呈递增趋势，年均增幅为13.75%，建设用地是主要碳源，占碳排放量的90%以上，林地是主要碳汇。九江市净碳排放量呈现“东北高，西南低”的空间分布特征，森林覆盖率好的武宁县、修水县一直处于碳汇功能，濂溪区、浔阳区、湖口县、瑞昌市的碳排放量占九江市净碳排放量的95%以上。九江市土地利用碳排放风险整体偏低，并呈现“东北高，西南低”的分布特征，长江沿岸县区濂溪区、浔阳区和柴桑区处于高度碳排放风险区。经济发展水平是碳排放增加的主要因素，能源消费强度则是抑制碳排放的关键因素。[结论] 2000—2020年九江市土地利用碳排放大幅增加，应控制新增碳源用地，优化土地利用结构，并积极探索低碳绿色能源利用体系，着力推进长江经济带绿色低碳发展的“九江模式”建设。

Abstract

[Objective] The land use carbon emissions in Jiujiang City

Jiangxi Province were quantitatively measured

and its temporal and spatial evolution characteristics

and the risk of land use carbon emissions were determined in order to provide a scientific reference for the construction of green and low-carbon land use methods in Jiujiang City. [Methods] Land use carbon emissions

and their temporal and spatial variation characteristics in Jiujiang City from 2000 to 2020 were measured by the carbon emission coefficient method. The carbon emission risk of each county was identified by the carbon emission risk index based on grid perspective. The factors influencing land use carbon emissions were analyzed based on the logarithmic mean divisia index (LMDI) model. [Results] Net carbon emissions from land use in Jiujiang City have been increasing at an average annual rate of 13.75% during 2000—2020. Construction land was the main carbon source

accounting for more than 90% of the carbon emissions

whereas forest land was the main carbon sink. Additionally

net carbon emissions in Jiujiang City presented a spatial distribution pattern of “high in northeast and low in southwest”. Wuning County and Xiushui County have good forest coverage and have always been carbon sinks. Lianxi District

Xunyang District

Hukou County

and Ruichang City

with more construction land

had the largest net carbon emissions and accounted for more than 95% of carbon emissions in Jiujiang City. Moreover

the carbon emission risk from land use in Jiujiang City was generally low

and showed a distribution pattern of “high in northeast and low in southwest”. High carbon emission risk areas were Lianxi District

Xunyang District

and Chaisang District

all along the Yangtze River. Economic development level was the main factor increasing carbon emissions

while energy consumption intensity was the key factor curbing carbon emissions. [Conclusion] Carbon emissions from land use have increased significantly during 2000—2020. New carbon source land use should be controlled

land use structure should be optimized

a low-carbon

green-energy utilization system should be actively constructed

and “Jiujiang model” construction of green and low-carbon development should be promoted in the Yangtze River Economic Belt.

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