郭海红, 盖凌云. 山东省农业绿色低碳转型评价及驱动因素分析[J]. 中国生态农业学报 (中英文), 2024, 32(2): 240−251. DOI: 10.12357/cjea.20230526
引用本文: 郭海红, 盖凌云. 山东省农业绿色低碳转型评价及驱动因素分析[J]. 中国生态农业学报 (中英文), 2024, 32(2): 240−251. DOI: 10.12357/cjea.20230526
GUO H H, GAI L Y. Evaluation and driving factor analysis of agricultural green and low-carbon transformation in Shandong Province[J]. Chinese Journal of Eco-Agriculture, 2024, 32(2): 240−251. DOI: 10.12357/cjea.20230526
Citation: GUO H H, GAI L Y. Evaluation and driving factor analysis of agricultural green and low-carbon transformation in Shandong Province[J]. Chinese Journal of Eco-Agriculture, 2024, 32(2): 240−251. DOI: 10.12357/cjea.20230526

山东省农业绿色低碳转型评价及驱动因素分析

Evaluation and driving factor analysis of agricultural green and low-carbon transformation in Shandong Province

  • 摘要: 农业绿色低碳发展是实现农业现代化和经济高质量发展的重要途径, 针对农业面源污染严重、农产品质量安全隐患凸显、农业碳排放增加等问题, 山东省推动农业绿色低碳转型势在必行。本研究构建了山东省农业绿色低碳转型水平评价指标体系, 采用熵权法对2011—2021年山东省农业绿色低碳转型水平进行测算, 从整体、经济圈和地市3个层面分析了农业绿色低碳转型水平的时空分异情况, 采用自然断点法对山东省进行分类分析, 通过地理探测器揭示山东省及三大经济圈农业绿色低碳转型的关键驱动因素。研究发现: 1)山东省农业绿色低碳转型的总体水平呈现稳步增长态势, 年均增长率达2.310%。2) 16个地市的农业绿色低碳转型水平均呈明显上升趋势, 青岛、济南连续11年领跑, 而临沂、潍坊、威海连续11年位居16个地市的尾部。3)省会经济圈的农业绿色低碳转型水平一直处于领先水平, 其次为鲁南经济圈, 胶东经济圈的水平则相对较低。4)财政支农政策、农业科技投入、农业产业结构调整是山东省农业绿色低碳转型的关键驱动因素。农业产业结构调整是省会经济圈最重要的驱动因素, 城镇化水平是胶东经济圈最重要的驱动因素, 政策扶持力度是鲁南经济圈最重要的驱动因素, 且各因素交互产生的驱动作用程度高于单因素。基于此, 山东省应以政策引领激发内生动力, 强化头雁的示范带动作用, 因地制宜地探索绿色低碳创新路径。

     

    Abstract: Agricultural green and low-carbon development is essential for achieving agricultural modernization and fostering high-quality economic development. Due to severe agricultural non-point source pollution, prominent quality and safety hazards of agricultural products, and increased agricultural carbon emissions, the agricultural green and low-carbon development should be promoted in Shandong Province. An evaluation index system for assessing the transformation level of agricultural green and low-carbon development in Shandong Province was constructed. The entropy weight method was used to calculate the agricultural green and low-carbon transformation level in Shandong Province from 2011 to 2021. The temporal and spatial differences of agricultural green and low-carbon transformation at overall, regional, and economic circle levels were analyzed. The natural breakpoint method was used to classify the agricultural green and low-carbon transformation levels in Shandong Province. The key driving factors influencing the agricultural green and low-carbon transformation in Shandong Province and its three major economic circles were revealed using geographic detectors. The results indicate that: 1) The overall level of agricultural green and low-carbon transformation in Shandong Province has maintained a steady growth trend, with an average annual growth rate of 2.310%. 2) The agricultural green and low-carbon transformation levels of 16 cities in Shandong Province showed an obvious increasing trend, with Qingdao and Jinan ranking at the top and Linyi, Weifang, and Weihai ranking at the bottom. 3) The agricultural green and low-carbon transformation level in the Provincial Capital Economic Circle was the highest, followed by the Lunan Economic Circle. In contrast, the level of the Jiaodong Economic Circle was relatively low. 4) The agricultural fiscal policy, agricultural technology input, and agricultural structure adjustment were key driving factors of agricultural green and low-carbon transformation in Shandong Province. The agricultural structure adjustment, urbanization level, and agricultural fiscal policy were the most critical driving factors in the Provincial Capital Economic Circle, the Jiaodong Economic Circle, and the Lunan Economic Circle, respectively. Moreover, the degree of driving effect generated by the interaction of various factors was markedly higher than that of single factors. Based on these findings, Shandong Province should leverage policy guidance to stimulate endogenous driving forces, strengthen the demonstration and driving role of leading entities, and explore green and low-carbon innovation paths tailored to local conditions.

     

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