十九大以来，农村农业绿色低碳发展不仅是全面推进乡村振兴、促进农业农村现代化进程的必然要求，也是“碳达峰、碳中和”愿景实现的必经之路。但《中华人民共和国气候变化第三次两年更新报告（2023）》显示，我国农业活动产生的温室气体排放量占全国温室气体排放总量的6.1%，现已成为我国第三大温室气体排放源。乡村经济产业和农村居民生活碳排放的急剧上升对农村农业绿色发展、乡村振兴战略目标的实现带来较大阻力，二者既是不可忽视的温室气体排放源，也是蕴含巨大减排与抵消潜力的碳汇系统。因此，本文将基于乡村振兴战略助推农业农村现代化转型发展及固碳减排的现实要求，明确农村碳排放历史变化趋势，探寻农村碳减排的关键点，比较设计乡村全面振兴与农村碳减排均衡发展的最优路径，为有效控制和减少农村碳排放提供建议参考。

       本文以全国31省（市、自治区）（不含港、澳、台地区）为研究对象，基于排放系数法建立农村碳排放测算模型，从农业生产活动（种植业、林业、畜牧业、渔业）四个层次测算我国2012-2021年的农村碳排放总量及强度，并从时序、区域两方面综合分析农村碳排放的历史变化特征，结果表明近10年中，农村净碳排放总量呈现“上升—下降—上升”的三阶段变化特征，碳排放强度呈现明显波动下降趋势，各地区农村碳排放总量及碳排放结构存在较大区别；其次，基于LMDI模型建立农村碳排放影响因素分解模型，依据各影响因素分解贡献值分析其对农村碳排放的作用方向及大小，结果发现农业经济水平与城镇化水平对农村碳排放具有驱动促进作用，农业生产效率、农业产业结构、农村人口规模具有明显抑制作用，这3个因素在全国各地区的碳减排覆盖面和抑制强度方面还存在一定差距；之后，将灰色模型与遗传算法优化的BP神经网络相结合构建农村碳排放趋势预测模型，以情景分析法为基础，设计3种情景模式：历史趋势发展情景、乡村振兴政策规划情景、乡村振兴政策调控情景，对比预测2022-2030年间农村碳排放量的未来变化趋势，结果发现三种情景下农村碳排放总量预测结果存在一定差异，乡村振兴政策规划情景和乡村振兴政策调控情景对于减少农村碳排放具有积极作用，且调控情景下农村碳排放量的下降程度明显快于历史趋势发展情景和规划情景，这表明未来随着乡村振兴政策战略的强化实施与宏观调控的进一步加强，我国农村碳减排的成效将会逐步显现。

       最后，基于我国农村发展实际，从乡村振兴的产业、人才、文化、生态和组织这5个视角出发，设计乡村振兴背景下助力农村碳减排的相应路径。一是产业方面：转变农业发展模式，培育数字农业新质生产力；二是人才方面：提升农民综合素质，培养绿色发展人才；三是文化方面：加强农村文化建设，弘扬绿色生活方式；四是生态方面：加强农村生态文明建设，保护修复农村生态系统；五是组织方面：加强政策引导与组织监管，完善农村碳减排监测体系，助力乡村全面振兴与农村碳减排均衡发展。

      Since the 19th National Congress of the Communist Party of China, the green and low-carbon development of rural agriculture has not only been an inevitable requirement for comprehensively promoting the revitalization of the countryside and the modernization of agriculture and rural areas, but also the necessary path to realize the vision of “carbon peak and carbon neutral”. However, as per the Third Biennial Update Report on Climate Change in the People’s Republic of China (2023), the greenhouse gas emissions from agricultural activities account for 6.1% of the total national greenhouse gas emissions, and has now become the third largest source of greenhouse gas emissions. With the surge of carbon emissions from rural economic industries and residents’ lives, the realization of the strategic objectives of rural agricultural green development and rural regeneration has faced significant resistance. Together with being the unavoidable sources of greenhouse gas emissions, the two also form carbon sink systems that contain enormous potential for emission reduction and offsetting. Therefore, according to the realistic requirements of the rural revitalization strategy to promote the transformation and development of agricultural and rural modernization, this paper clarifies the historical trend of rural carbon emission, explores the key points of rural carbon reduction, comparatively designs the optimal path for balanced development of rural comprehensive revitalization and carbon reduction, and provides recommendations for effectively controlling and reducing rural carbon emissions.

        Taking 31 provinces(excluding Hong Kong, Macao, and Taiwan) as the research object, this paper establishes a rural carbon emission measurement model based on the emission coefficient method, measuring the total amount and intensity of rural carbon emissions from 2012 to 2021 at four levels of agricultural production activities (planting, forestry, animal husbandry, and fishery), and comprehensively analyzes the historical changes of rural carbon emissions from both temporal and regional perspectives. The results show that in the past decade, the net carbon emissions in rural areas have exhibited a three-stage pattern of “rise-fall-rise”, with an obvious fluctuating decline trend in carbon emission intensity, and there are significant differences in the rural carbon emission structure among various regions. Secondly, based on the LMDI model, a decomposition model of rural carbon emissions influencing factors is formed. The contribution value of each influencing factor is analyzed to determine its direction and magnitude of effect on rural carbon emissions, which finds that the development level of the agricultural economy and urbanization promote rural carbon emissions, while agricultural production efficiency, agricultural industrial structure and rural population, still have a gap in the coverage and suppression intensity of carbon emission reduction in all regions of the country. Subsequently, combining the grey model with the back propagation neural network model optimized by genetic algorithm, a rural carbon emission trend prediction model is constructed in this paper, and based on the scenario analysis method, three scenarios are designed: historical trend development scenario, rural revitalization policy planning scenario and rural revitalization policy regulation scenario. The future trends of rural carbon emissions for 2022 to 2030 under each scenario are compared. The results show that there are certain differences in the predicted total amount of rural carbon emissions under the three scenarios. The planning and regulation scenario of rural revitalization policy has a positive effect on reducing rural carbon emissions, with the decline of rural carbon emissions under the regulation scenario being significantly faster than that under the historical trend and planning scenario, which indicates that with the strengthening of the implementation of rural revitalization policy strategy and the further strengthening of macro-control in the future, the effectiveness of rural carbon emission reduction in China will gradually emerge.

        Finally, based on the actual situation of rural development in China, this paper designs corresponding pathways to support rural carbon emission reduction from the perspectives of rural revitalization. (1) From the aspect of industry: transforming the agricultural development mode and cultivating the new productivity in digital agriculture. (2) From the aspect of talent: enhancing the comprehensive quality of farmers and nurturing talents for green development talents. (3) From the aspect of culture: strengthening the rural culture construction and promoting a green lifestyle. (4) From the aspect of ecology: improving rural ecological civilization construction, protecting and repairing the rural ecosystem. (5) From the aspect of organization: reinforcing policy guidance and organizational supervision, improving the monitoring system for rural carbon emission reduction, and assisting the balanced development between comprehensive revitalization and rural carbon emission reduction.

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