长江中游城市群耕地利用碳排放“总量-强度”的空间关联特征

熊子昕; 匡兵; 柯楠

doi:10.13961/j.cnki.stbctb.20230216.004

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长江中游城市群耕地利用碳排放“总量-强度”的空间关联特征

试验研究

- 长江中游城市群耕地利用碳排放“总量-强度”的空间关联特征
- Spatial Correlation Characteristics of Amount and Intensity of Carbon Emissions Resulting from Cultivated Land Utilization in an Urban Agglomeration in Middle Reaches of Yangtze River
- 水土保持通报 2023年43卷第3期页码：406-413
- 作者机构：
  
  1. 华中师范大学公共管理学院,湖北,武汉,430079
  2. 华中师范大学自然资源治理研究院,湖北,武汉,430079
  3. 华中科技大学公共管理学院,湖北,武汉,430074
- 作者简介：
- 基金信息：
  
  教育部人文社会科学研究青年项目“乡村振兴战略背景下中国耕地轮作休耕的响应与适应机制研究”(19YJC790054);中央高校基本科研业务费项目(CCNU20QN036)
- DOI：10.13961/j.cnki.stbctb.20230216.004
  中图分类号： X321;F323.211
- 纸质出版：2023
- 稿件说明：
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熊子昕, 匡兵, 柯楠. 长江中游城市群耕地利用碳排放“总量-强度”的空间关联特征[J]. 水土保持通报, 2023,43(3):406-413.

Xiong Zixin, Kuang Bing, Ke Nan. Spatial Correlation Characteristics of Amount and Intensity of Carbon Emissions Resulting from Cultivated Land Utilization in an Urban Agglomeration in Middle Reaches of Yangtze River[J]. Bulletin of Soiland Water Conservation, 2023, 43(3): 406-413.
熊子昕, 匡兵, 柯楠. 长江中游城市群耕地利用碳排放“总量-强度”的空间关联特征[J]. 水土保持通报, 2023,43(3):406-413. DOI： 10.13961/j.cnki.stbctb.20230216.004.

Xiong Zixin, Kuang Bing, Ke Nan. Spatial Correlation Characteristics of Amount and Intensity of Carbon Emissions Resulting from Cultivated Land Utilization in an Urban Agglomeration in Middle Reaches of Yangtze River[J]. Bulletin of Soiland Water Conservation, 2023, 43(3): 406-413. DOI： 10.13961/j.cnki.stbctb.20230216.004.

摘要

[目的] 揭示长江中游城市群耕地利用碳排放“总量—强度”的空间关联特征，为实现高质量发展提供理论和现实指导。[方法] 采用IPCC系数法、总体耦合态势模型和双变量空间自相关法分析相关指标。[结果] ①2010—2013年长江中游城市群耕地利用碳排放总量呈显著上升趋势，年均增率为2.0%；2014—2020年则呈下降趋势，年均降幅为2.6%，且碳排放的市域间差异趋于扩大。②长江中游城市群耕地利用的碳排放强度总体处于波动下降态势，年均降幅达4.9%，但受边际递减效应影响，碳排放强度进一步改善的难度不断加大。③2010—2020年长江中游城市群耕地利用碳排放量与碳排放强度的加权中心距离从0.571 km减少到0.312 km，移动方向夹角总体也呈减小趋势，总体耦合态势不断加强。④2010—2020年长江中游城市群耕地利用碳排放总量与强度存在显著空间正相关，同时存在空间异质性。聚集态势主要表现为武汉城市圈“双高”聚集区和环长株潭城市群“双低”聚集区。[结论] 应采取差异化手段对耕地利用碳排放总量与强度进行分区调控，完善碳排放总量和强度“双控”机制。

Abstract

[Objective] The spatial correlation characteristics of the amount and intensity of carbon emissions resulting from cultivated land utilization in an urban agglomeration in the middle reaches of the Yangtze River were analyzed in order to provide theoretical and practical guidance for achieving regional high-quality development.[Methods] The IPCC coefficient method

the overall coupling analysis model

and the bivariate spatial autocorrelation method were used in this study.[Results] ① The amount of carbon emissions resulting from cultivated land utilization in the study area showed a significant upward trend during 2010-2013

with an average annual growth rate of 2.0%. Carbon emissions showed a downward trend during 2014-2020

with an average annual decline of -2.6%. During the study period

the difference between the carbon emissions of each city tended to expand. ② The intensity of carbon emissions resulting from cultivated land utilization in the study area showed a fluctuating downward trend

with an average annual decline of -4.9%. However

due to the marginal decline effect

it was increasingly difficult to further improve the carbon emission intensity. ③ During the study period

the center-weighted distance between the amount and intensity of carbon emissions resulting from cultivated land utilization in the study area decreased from 0.571 km to 0.312 km. The included angle between their moving directions also showed a general declining trend

and the coupling situation continued to strengthen. ④ From 2010 to 2020

there was a significant spatial positive correlation between the amount and intensity of carbon emissions resulting from cultivated land utilization in the study area

and there was also spatial heterogeneity in this effect. The agglomeration situation was mainly manifested in the "high-high" and "low-low" area

which was represented by the Wuhan urban agglomeration and the Changsha-Zhuzhou-Xiangtan urban agglomeration

respectively.[Conclusion] Different regulation measures should be taken according to the spatial correlation pattern between the amount and intensity of carbon emissions resulting from cultivated land utilization. The "dual control" mechanism for the amount and intensity of carbon emissions resulting from cultivated land utilization is also an important consideration.

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references

宋妍,张明.公众认知与环境治理:中国实现绿色发展的路径探析[J].中国人口·资源与环境,2018,28(8):161-168.

崔许锋,王雨菲,张光宏.面向低碳发展的农业生态效率测度与时空演变分析:基于SBM-ESDA模型[J].农业经济问题,2022,43(9):47-61.

王少剑,黄永源.中国城市碳排放强度的空间溢出效应及驱动因素[J].地理学报,2019,74(6):1131-1148.

吴贤荣,张俊飚,田云,等.中国省域农业碳排放:测算、效率变动及影响因素研究:基于DEA-Malmquist指数分解方法与Tobit模型运用[J].资源科学,2014,36(1):129-138.

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.

李秋萍,李长建,肖小勇,等.中国农业碳排放的空间效应研究[J].干旱区资源与环境,2015,29(4):30-35.

祝宏辉,李晓晓.新疆农业碳排放的脱钩效应及驱动因素分析[J].生态经济,2018,34(9):31-35.

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(6):85-91.

吴昊玥,孟越,黄瀚蛟,等.中国耕地低碳利用绩效测算与时空分异[J].自然资源学报,2022,37(5):1148-1163.

阿依吐尔逊·沙木西,艾力西尔·亚力坤,刘晓曼,等.乌鲁木齐土地利用碳排放强度时空演变研究[J].中国农业资源与区划,2020,41(2):139-146.

夏四友,赵媛,许昕,等.近20年来中国农业碳排放强度区域差异、时空格局及动态演化[J].长江流域资源与环境,2020,29(3):596-608.

王若梅,马海良,王锦.基于水-土要素匹配视角的农业碳排放时空分异及影响因素:以长江经济带为例[J].资源科学,2019,41(8):1450-1461.

王良健,李辉.中国耕地利用效率及其影响因素的区域差异:基于281个市的面板数据与随机前沿生产函数方法[J].地理研究,2014,33(11):1995-2004.

刘蒙罢,张安录,文高辉.长江中下游粮食主产区耕地利用生态效率时空格局与演变趋势[J].中国土地科学,2021,35(2):50-60.

马勇,黄智洵.长江中游城市群生态文明水平测度及时空演变[J].生态学报,2016,36(23):7778-7791.

吴清,马会丽,吴黎,等.长江中游城市群农业经济时空格局演化研究[J].广东农业科学,2016,43(9):152-158.

李俊杰.民族地区农地利用碳排放测算及影响因素研究[J].中国人口·资源与环境,2012,22(9):42-47.

黎孔清,陈俭军,马豆豆.基于STIRPAT和GM(1,1)模型的湖南省农地投入碳排放增长机理及趋势预测[J].长江流域资源与环境,2018,27(2):345-352.

田云,张俊飚,李波.湖北省农地利用碳排放时空特征与脱钩弹性研究[J].长江流域资源与环境,2012,21(12):1514-1519.

李强,高威,魏建飞,等.中国耕地利用净碳汇时空演进及综合分区[J].农业工程学报,2022,38(11):239-249.

匡兵,卢新海,韩璟,等.考虑碳排放的粮食主产区耕地利用效率区域差异与变化[J].农业工程学报,2018,34(11):1-8.

周思宇,郗凤明,尹岩,等.东北地区耕地利用碳排放核算及驱动因素[J].应用生态学报,2021,32(11):3865-3871.

West T O. A synthesis of carbon sequestration, carbon emissions, and net carbon flux in agriculture:Comparing tillage practices in the United States[J]. Agriculture, Ecosystems & Environment, 2002,91(1/2/3):217-232.

Post W M, Kwon K C. Soil carbon sequestration and land-use change:Processes and potential[J]. Global Change Biology, 2000,6(3):317-327.

李波,张俊飚,李海鹏.中国农业碳排放时空特征及影响因素分解[J].中国人口·资源与环境,2011,21(8):80-86.

伍芬琳,李琳,张海林,等.保护性耕作对农田生态系统净碳释放量的影响[J].生态学杂志,2007,26(12):2035-2039.

Yang Chen, Zhan Qingming, Gao Sihang, et al. How do the multi-temporal centroid trajectories of urban heat island correspond to impervious surface changes:A case study in Wuhan, China[J]. International Journal of Environmental Research and Public Health, 2019,16(20):3865.

Yang Zhiwei, Chen Yingbiao, Qian Qinglan, et al. The coupling relationship between construction land expansion and high-temperature area expansion in China's three major urban agglomerations[J]. International Journal of Remote Sensing, 2019,40(17):6680-6699.

Anselin L. Local indicators of spatial association-LISA[J]. Geographical Analysis, 2010,27(2):93-115.

徐冬,黄震方,黄睿.基于空间面板计量模型的雾霾对中国城市旅游流影响的空间效应[J].地理学报,2019,74(4):814-830.

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