Abstract: As a traditional industrial and agricultural province, in order to identify the main factors affecting carbon emissions in Liaoning province under the background of continuous adjustment of energy structure and gradual improvement of agricultural mechanization level, the main energy consumption carbon emission was calculated based on the energy consumption data of 2012—2021. Then, the estimation model of energy consumption carbon emission was constructed by STIRPAT model, and the main reasons affecting the carbon emissions of energy consumption were analyzed. The result showed that coal was still the most important energy source consumed in Liaoning province, accounting for about 55% of the total energy consumption. The total carbon emissions of energy consumption showed a significant increasing trend. However, the carbon emission intensity tends to decline. The total amount decreased by 11.3 kt CO2/100 million yuan in 10 years. Nine factors, including the output value of the secondary industry, the agricultural carbon emission efficiency, the agricultural economic development level, the output value of the primary industry, the population, the per capita GDP, the urbanization rate, the agricultural mechanization degree, and the energy processing and conversion efficiency, mainly affected the carbon emission. A carbon emission prediction model based on STIRPAT was constructed with an average relative error -4.91%, which indicated a good accuracy. From the model, population change had negative effects on the total energy carbon emission, however, Per capita GDP, the output value of the secondary industry, the agricultural economic development level, and the degree of agricultural mechanization had a positive impact. Therefore, in order to restrain the rapid increase of energy carbon emissions in Liaoning Province, it is necessary to control the population, optimize the industrial structure, keep the per capita GDP growth rate, the output value of the secondary industry and the degree of agricultural mechanization at a reasonable level.

Key words: agricultural mechanization, energy carbon emissions, STIRPAT model, influencing factors, energy saving and emission reduction

摘要： 辽宁省是传统的工业和农业大省，在能源结构持续调整和农业机械化水平逐渐提高的背景下，为制定科学合理的减排措施，必须探明其碳排放主要来源。为此，采用排放因子法计算2012—2021年主要能源消耗碳排放量，利用STIRPAT模型构建辽宁省能源消耗碳排放测算模型，分析影响能源消耗碳排放的主导因素。结果发现，煤炭是辽宁省消耗的最主要能源，占总能耗的55%左右；能源消耗碳排放总量整体呈明显增加趋势，而碳排放强度呈下降趋势，10年间降低11.3 kt CO2/亿元；第二产业产值、农业碳排放效率、农业经济发展水平、第一产业产值、人口、人均GDP、城镇化率、农业机械化程度、能源加工转换效率是影响辽宁省碳排放的主要因素；基于STIRPAT模型构建辽宁省碳排放测算模型，通过验证发现平均相对误差为-4.91%，准确度较好；对模型分析发现人口变化对辽宁省能源碳排放呈负向影响，而人均GDP、第二产业产值、农业经济发展水平、农业机械化程度对辽宁省能源碳排放呈正向影响。因此为抑制辽宁省能源碳排放量的快速增加，需要控制人口数量，优化产业结构，保持人均GDP增速，第二产业产值和农业机械化程度在一个合理的水平。

关键词: 农业机械化, 能源碳排放, STIRPAT模型, 影响因素, 节能减排