【摘要】 为了解中国种植业碳排放情况并对种植业碳减排提出针对性的措施，文章对中国2000-2020年的种植业碳排放进行了测度，并基于LMDI模型，对碳排放驱动因素展开了研究。灌溉碳排放量为种植业碳排放第二大来源且一直处于增长态势，故基于STIRPAT模型，设置了7种不同的情景组合，并对不同情景下灌溉碳排放达峰情况进行了预测。结果表明：（1）2000-2020年中国种植业碳排放总量先增加后减少，在2015年实现了达峰，峰值为10 732.6万t。（2）种植业生产效率、农业产业结构、国家产业结构、农村地区人口对种植业碳减排为正效应，国家经济发展水平、农村人口流失水平则表现为负效应。（3）生态和经济协同发展情景下，2030年灌溉碳排放可以实现达峰，对应值为1 981.8万t。最后，就中国种植业碳减排提出了促进种植业低碳机械化发展、深化种植业低碳技术性改革、保持城镇化率平稳增长等建议。更多还原

【Abstract】 In order to understand the carbon emission of planting industry in China and put forward targeted measures for the carbon emission reduction of planting industry, the carbon emissions of the planting industry in China from 2000 to 2020 were measured, and the driving factors of carbon emissions were studied based on the LMDI model. Irrigation carbon emission is the second largest source of carbon emission from the planting industry and has been growing. Therefore, based on the STIRPAT model, seven different scenarios were set. The peak of irrigation carbon emission under different scenarios was predicted. Results showed that from 2000 to 2020, the total carbon emission of China’s planting industry first increased and then decreased. The carbon emission of planting industry reached a peak in 2015, with a peak of 107.326 million tons. Planting production efficiency, agricultural industrial structure, national industrial structure, and rural population have positive effects on planting carbon emission reduction, while national economic development level and rural population loss level have negative effects. Under the scenario of coordinated ecological and economic development, irrigation carbon emissions can reach the peak in 2030, with the corresponding value of 19.818 million tons. Finally, some suggestions were put forward to promote the development of low-carbon mechanization of planting industry, deepen the low-carbon technical reform of planting industry, and maintain the steady growth of urbanization rate.更多还原