“双碳”目标下黄河下游耕地绿色利用效率、收敛性与影响因素

刘涛; 尚晓菲; 苏原原; 霍静娟

doi:10.13961/j.cnki.stbctb.20230220.004

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“双碳”目标下黄河下游耕地绿色利用效率、收敛性与影响因素

试验研究

- “双碳”目标下黄河下游耕地绿色利用效率、收敛性与影响因素
- Green Utilization Efficiency, Convergence, and Influencing Factors of Cultivated Land in Lower Yellow River Under “Double Carbon” Target
- 水土保持通报 2023年43卷第1期页码：291-299
- 作者机构：
  
  1. 河南理工大学财经学院,河南,焦作,454000
  2. 河南大学中原发展研究院,河南,开封,475001
  3. 河南理工大学物理与电子信息学院,河南,焦作,454000
- 作者简介：
- 基金信息：
  
  国家社科基金青年项目“乡村振兴背景下中国农村闲置资源协同激活问题研究(18CJY030)”(18CJY030);教育部人文社会科学青年基金项目(18YJCZH061)”;河南省高等学校青年骨干教师培养计划(2021GGJS053);河南理工大学“研究和阐释党的十九大精神”专项立项项目(SJDZXZD-01);河南省社会科学规划专项(2022ZT08)。
- DOI：10.13961/j.cnki.stbctb.20230220.004
  中图分类号： F301.24
- 纸质出版：2023
- 稿件说明：
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刘涛, 尚晓菲, 苏原原, 等. “双碳”目标下黄河下游耕地绿色利用效率、收敛性与影响因素[J]. 水土保持通报, 2023,43(1):291-299.

Liu Tao, Shang Xiaofei, Su Yuanyuan, et al. Green Utilization Efficiency, Convergence, and Influencing Factors of Cultivated Land in Lower Yellow River Under “Double Carbon” Target[J]. Bulletin of Soiland Water Conservation, 2023, 43(1): 291-299.
刘涛, 尚晓菲, 苏原原, 等. “双碳”目标下黄河下游耕地绿色利用效率、收敛性与影响因素[J]. 水土保持通报, 2023,43(1):291-299. DOI： 10.13961/j.cnki.stbctb.20230220.004.

Liu Tao, Shang Xiaofei, Su Yuanyuan, et al. Green Utilization Efficiency, Convergence, and Influencing Factors of Cultivated Land in Lower Yellow River Under “Double Carbon” Target[J]. Bulletin of Soiland Water Conservation, 2023, 43(1): 291-299. DOI： 10.13961/j.cnki.stbctb.20230220.004.

摘要

[目的] 分析黄河下游耕地绿色利用效率及其收敛性与影响因素，为黄河下游地区耕地生态保护与高质量发展提供参考。 [方法] 将耕地资源利用过程中产生的耕地面源污染和碳排放等非期望产出和总碳汇同时纳入评价指标体系，利用EBM模型、收敛模型、面板Tobit模型系统分析了2007—2020年黄河下游34个地市耕地绿色利用效率、收敛性与影响因素。[结果] ①黄河下游耕地绿色利用效率整体呈上升趋势，但2020年末仍未达到最优状态。黄河下游地区耕地绿色利用效率存在空间非均衡性，豫南及鲁北耕地绿色利用效率值较高，而郑州、威海等地市的效率值一直偏低。 ②从效率分解看，黄河下游地区耕地绿色利用效率提升的主要动力源于规模效率，阻力来自纯技术效率。 ③从收敛检验看，黄河下游耕地绿色利用效率均存在σ收敛和β收敛，河南省耕地绿色利用效率的地市间差距明显低于山东省，但山东省的收敛速度较之更快。 ④从影响因素看，农作物种植结构与政府财政支农对黄河下游地区耕地绿色利用效率起促进作用，而城乡收入差距、经济发展水平和耕地机械投入强度起抑制作用。[结论] 未来黄河下游不但要提高耕地绿色利用的综合管理水平，加强地市间交流合作，更要在推进耕地绿色利用发展的同时，重点关注各地区耕地绿色利用效率的收敛速度与发展差距之间的协调。

Abstract

[Objective] Green utilization efficiency of cultivated land in the lower Yellow River and its convergence and influencing factors were analyzed in order to provide a reference for ecological protection and high-quality development of cultivated land in the lower Yellow River. [Methods] Undesirable outputs such as surface pollution and carbon emissions from cultivated land

and the carbon sequestration and sink capacity of cultivated land resources were simultaneously incorporated into the evaluation index system. The green utilization efficiency

convergence

and influencing factors of cultivated land in 34 municipalities in the lower Yellow River from 2007 to 2020 were systematically analyzed using the EBM model

the convergence model

and the panel random effects Tobit model. [Results] ① The green utilization efficiency of cultivated land in the lower Yellow River showed an overall upward trend

but still did not reach the optimal state by the end of 2020. The green utilization efficiency of cultivated land in the lower Yellow River was spatially unbalanced. The green utilization efficiency of cultivated land in Southern He’nan and Northern Shandong provinces was high

while that in Zhengzhou

Weihai

and other cities was always low. ② From the perspective of efficiency decomposition

the main driving force for the improvement of green utilization efficiency of cultivated land in the lower Yellow River was scale efficiency

while the resistance came from pure technical efficiency. ③ From the convergence test

both σ convergence and β convergence existed in the green utilization efficiency of farmland in the lower Yellow River. The inter-city gap of cultivated land green utilization efficiency in He’nan Province was obviously lower than in Shandong Province

but the convergence rate in Shandong Province was faster. ④ In terms of influencing factors

crop planting structure and government financial support to agriculture increased green utilization efficiency of cultivated land in the lower Yellow River

while the urban-rural income gap

economic development level

and farmland machinery input intensity decreased green utilization efficiency. [Conclusion] In the future

the lower Yellow River should not only improve the comprehensive management level of the green utilization of cultivatedpland and strengthen inter-city exchanges and cooperation

but should also focus on the coordination between the convergence rate of green utilization efficiency of cultivated land and the development gap in each region while promoting development of the green utilization of cultivated land.

关键词

Keywords

references

Han Haibin, Zhang Xiaoyu. Static and dynamic cultivated land use efficiency in China: A minimum distance to strong efficient frontier approach [J]. Journal of Cleaner Production, 2020,246(10):1-15.

Hou Xianhui, Liu Jingming, Zhang Daojun, et al. Impact of urbanization on the eco-efficiency of cultivated land utilization: A case study on the Yangtze River Economic Belt, China [J]. Journal of Cleaner Production, 2019,238(20):1-9.

陶园,徐静,任贺靖,等.黄河流域农业面源污染时空变化及因素分析[J].农业工程学报,2021,37(4):257-264.

盖兆雪,孙萍,张景奇.环境约束下的粮食主产区耕地利用效率时空演变特征[J].经济地理,2017,37(12):163-171.

秦钟,王璐,张春霞,等.基于Malmquist指数法的珠三角耕地生产效率研究[J].生态科学,2019,38(6):125-130.

姜晗,杨皓然,吴群.东部沿海经济区耕地利用效率的时空格局分异及影响因素研究[J].农业现代化研究,2020,41(2):321-330.

崔宁波,王欣媛,于尊.东北粮食主产区耕地生态效率评价及影响因素分析[J].生态经济,2021,37(7):104-110.

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.

黄祥芳.面源污染视角下江西省耕地利用效率研究[J].中国农业资源与区划,2018,39(12):177-183.

Xie Hualin, Chen Qianru, Wang Wei, et al. Analyzing the green efficiency of arable land use in China [J]. Technological Forecasting and Social Change, 2018,133(8):15-28.

Lin H C, Hülsbergen K J. A new method for analyzing agricultural land-use efficiency, and its application in organic and conventional farming systems in southern Germany [J]. European Journal of Agronomy, 2017,83(2):15-27.

Kühling I, Broll G, Trautz D. Spatio-temporal analysis of agricultural land-use intensity across the Western Siberian grain belt [J]. Science of the Total Environment, 2016,544(3):271-280.

匡兵,范翔宇,卢新海.中国耕地利用绿色转型效率的时空分异特征及其影响因素[J].农业工程学报,2021,37(21):269-277.

孙嘉阳,张惠中,张文信,等.山东省耕地利用效率时空差异及其影响因素分析[J].山东农业大学学报(自然科学版),2021,52(5):853-859.

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区域差异与空间收敛[J].自然资源学报,2022,37(2):477-493.

Tone K, Tsutsui M. An epsilon-based measure of efficiency in DEA： A third pole of technical efficiency [J]. European Journal of Operational Research, 2010,207(3):1554-1563.

王许亮,王恕立.服务业能源生产率变迁及收敛性分析: 基于全球40个经济体细分行业数据的经验研究[J].数量经济技术经济研究,2018,35(1):42-59.

Miller S M, Upadhyay M P. Total factor productivity and the convergence hypothesis [J]. Journal of Macroeconomics,2002,24(2):267-286.

Tobin J. Estimation of relationships for limited dependent variables [J]. Econometrica, 1958,26(1):24-36.

刘蒙罢,胡贤辉,文高辉.环境约束下的洞庭湖平原耕地利用效率动态演变特征分析[J].中国农业资源与区划,2022,43(4):108-118.

马林燕,张仁慧,潘子纯,等.中国省际耕地利用生态效率时空格局演变及影响因素分析: 基于2000—2019年面板数据[J].中国土地科学,2022,36(3):74-85.

张利国,鲍丙飞,潘丹.鄱阳湖生态经济区粮食生产技术效率时空演变及环境协调性探究[J].经济地理,2016,36(11):116-123.

方永丽,曾小龙.中国省际农业生态效率评价及其改进路径分析[J].农业资源与环境学报,2021,38(1):135-142.

柯楠,卢新海,匡兵,等.碳中和目标下中国耕地绿色低碳利用的区域差异与影响因素[J].中国土地科学,2021,35(8):67-76.

杨果,陈瑶.中国农业源碳汇估算及其与农业经济发展的耦合分析[J].中国人口·资源与环境,2016,26(12):171-176.

汪亚琴,姚顺波,侯孟阳,等.基于地理探测器的中国农业生态效率时空分异及其影响因素[J].应用生态学报,2021,32(11):4039-4049.

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.

辛岭,刘衡,胡志全.我国农业农村现代化的区域差异及影响因素分析[J].经济纵横,2021(12):101-114.

罗冲,姜博,张文琦,等.东北地区耕地利用效率时空差异及其影响因素分析[J].中国农业资源与区划,2017,38(10):38-44.

曾龙,付振奇.中国城乡收入差距对农业生产率的影响: 基于农村劳动力转移与农村居民收入的双重视角[J].江汉论坛,2021(11):15-24.

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