“双碳”目标下中国农业碳生产率提升的组态路径研究
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1.河南工业大学;2.河南农业大学;3.生态环境部环境规划院

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F205

基金项目:

教育部人文社会科学研究青年基金项目“水多重属性视角下华北平原县域农业用水效率时空分异及驱动机制”(23YJCZH215);河南省高等学校重点科研项目“科技创新支撑黄河流域生态保护和高质量发展问题研究”(24A630018)


A Study on the Configuration Path of Improving Agricultural Carbon Productivity in China under the "Carbon Peaking and Carbon Neutrality " Goals
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    摘要:

    提高农业碳生产率是实现农业低碳绿色发展的必由之路。研究构建了农业碳生产率提升的组态路径分析框架,选取中国2006-2020年31个省份为样本,在考虑碳排放因子区域差异的基础上,对省级尺度农业碳排放总量、碳生产率进行测度,运用模糊集定性比较分析方法解析影响农业碳生产率的复杂因果机制及多元提升路径。结果表明:(1)我国农业碳生产率整体呈上升趋势,呈东部明显高于中西部的分布格局,省间农业碳生产率差异明显;(2)产生高农业碳生产率的组态类型为:区域经济驱动型、农业技术驱动型、种植结构-区域经济驱动型、种植结构-劳动力素质驱动型;(3) 抑制农业碳生产率提升的组态类型包括种植结构抑制型、产业结构-城镇化率抑制型和产业结构-区域经济抑制型;(4)种植结构一直是农业碳生产率高的核心驱动力,城镇化率和农业政策支持力度的驱动作用随时间演变有所弱化,而区域经济和劳动力素质对提升农业高碳生产率的作用有所增强。

    Abstract:

    Improving agricultural carbon productivity as a way to achieve low-carbon green development in agriculture has received widespread attention, but existing studies have focused on the impact of a single factor on agricultural carbon productivity, and few have explored the synergistic effects of multiple factors on agricultural carbon productivity. A sample of 31 provinces in China from 2006 to 2020 was selected to measure the total agricultural carbon emissions and carbon productivity at the provincial scale based on regional differences in carbon emission factors, and a single-factor and multi-factor analysis framework based on the configuration perspective was constructed to analyze the complex causal mechanisms and multiple enhancement paths affecting agricultural carbon productivity using fuzzy set qualitative comparative analysis. The results show that the overall trend of agricultural carbon productivity in China is increasing. The distribution pattern of agricultural carbon productivity is significantly higher in the east than in the middle and west, and the difference of agricultural carbon productivity between provinces is obvious. The configuration types that generate high agricultural carbon productivity are: regional economy driven type, agricultural technology driven type, planting structure-regional economy driven type, and planting structure-labor quality driven type. The configuration types that inhibit the improvement of agricultural carbon productivity include planting structure inhibition type, industrial structure-urbanization rate inhibition type, and industrial structure-regional economic level inhibition type. The planting structure has always been the core driving force for high agricultural carbon productivity. The driving effect of urbanization rate and agricultural policy support on agricultural carbon productivity has weakened over time. The role of regional economy and labor quality in improving agricultural high carbon productivity has been enhanced.

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赵彦飞,王丽,李桢.“双碳”目标下中国农业碳生产率提升的组态路径研究[J].,2025,(2).

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  • 收稿日期:2024-03-21
  • 最后修改日期:2025-03-07
  • 录用日期:2024-05-20
  • 在线发布日期: 2025-08-20
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