Spatial-temporal characteristics and decoupling effect of agricultural carbon emissions in Xuzhou City
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    Abstract:

    [Objective] Agriculture is an important source of carbon that affects climate change, and its emission reduction and carbon sequestration play an important role in achieving the "double carbon" target and building a strong agricultural country. [Methods] The total, intensity and structure of agricultural carbon emissions in Xuzhou City from 2000 to 2020 were measured using the emission coefficient method, and then the decoupling relationship between agricultural economic development was analyzed based on the Tapio decoupling model. [Results] ①The overall trend of agricultural carbon emissions in Xuzhou city is "rapid rise - fluctuating rise - rapid decline", from 1.61×106 t in 2000 to 1.69×106 t in 2020. It is in the shape of an "M". The contribution to agricultural carbon emissions is in the order of arable land use (46.44%), crop cultivation (31.90%) and livestock breeding (21.66%), with chemical fertilizers being the most important carbon source; ②Agricultural carbon emissions in Xuzhou city vary significantly among districts (counties and cities) and have undergone a long-term evolutionary process from rising to falling, with a spatial distribution pattern of "high in the middle and low in the periphery", with Pizhou city being the most prominent; ③Xuzhou''s agricultural carbon emissions and agricultural economic development have generally undergone a process of "weak decoupling - strong negative decoupling - expansion of negative decoupling - strong decoupling", and the main performance since the 13th Five-Year Plan is strong decoupling. [Conclusion] Xuzhou''s agricultural carbon emissions are becoming more and more reasonable as the concept of low-carbon emission reduction continues to deepen, and the agricultural economic development has also achieved certain results.

    Reference
    [1] 周一凡,李彬,张润清.县域尺度下河北省农业碳排放时空演变与影响因素研究[J].中国生态农业学报(中英文),2022,30(04):570-581.
    [2] 林斌,徐孟,汪笑溪.中国农业碳减排政策、研究现状及展望[J].中国生态农业学报(中英文),2022,30(04):500-515.
    [3] 冉光和,王建洪,王定祥.我国现代农业生产的碳排放变动趋势研究[J].农业经济问题,2011,32(02):32-38+110-111.
    [4] 杨世琦,颜鑫.基于生物地球化学循环视角下我国农业碳达峰、碳中和应对策略[J/OL].中国科学院院刊:1-9.
    [5] 田云,张俊飚,李波.中国农业碳排放研究:测算、时空比较及脱钩效应[J].资源科学,2012,34(11):2097-2105.
    [6] 许萍萍,赵言文,陈颢明,等.江苏省农田生态系统碳源/汇、碳足迹动态变化[J].水土保持通报,2018,38(05):238-243.
    [7] 金书秦,林煜,牛坤玉.以低碳带动农业绿色转型:中国农业碳排放特征及其减排路径[J].改革,2021(05):29-37.
    [8] 田云,尹忞昊.中国农业碳排放再测算:基本现状、动态演进及空间溢出效应[J].中国农村经济,2022(03):104-127.
    [9] 赵宇.江苏省农业碳排放动态变化影响因素分析及趋势预测[J].中国农业资源与区划,2018,39(05):97-102.
    [10] 邱怡慧,王璞,苏时鹏.中国农地利用碳排放时空演变特征及驱动因素研究——基于IPCC法与LMDI指数分解模型[J].资源开发与市场,2019,35(05):625-631.
    [11] 刘杨,刘鸿斌.山东省农业碳排放特征、影响因素及达峰分析[J].中国生态农业学报(中英文),2022,30(04):558-569.
    [12] 王莉,刘莹莹,张亚慧,等.河南省农田生态系统碳源/汇时空分布及影响因素分解[J/OL].环境科学学报:1-13.
    [13] 曹俐,王莹,雷岁江.山东省农业碳排放的时空特征与脱钩弹性研究[J].江苏农业科学,2020,48(17):250-256.
    [14] 张中秋,劳燕玲,赵宁俊,等.广东省土地利用-碳减排-经济增长的脱钩关系[J].水土保持通报,2022,42(01):250-258+266.
    [15] 丁宝根,杨树旺,赵玉,等.中国耕地资源利用的碳排放时空特征及脱钩效应研究[J].中国土地科学,2019,33(12):45-54.
    [16] 吴昊玥,黄瀚蛟,陈文宽.中国粮食主产区耕地利用碳排放与粮食生产脱钩效应研究[J].地理与地理信息科学,2021,37(06):85-91.
    [17] 段华平,张悦,赵建波,等.中国农田生态系统的碳足迹分析[J].水土保持学报,2011,25(05):203-208.
    [18] 闵继胜,胡浩.中国农业生产温室气体排放量的测算[J].中国人口·资源与环境,2012,22(07):21-27.
    [19] 陈胜涛,张开华,张岳武.农业碳排放绩效的测量与脱钩效应[J].统计与决策,2021,37(22):85-88.
    [20] 徐玥,王辉,韩秋凤,等.我国耕地碳排放时空特征与影响因素[J].江苏农业科学,2022,50(16):218-226.
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History
  • Received:November 05,2022
  • Revised:April 03,2023
  • Adopted:April 04,2023
  • Online: November 09,2023