内蒙古自治区种植业碳排放驱动因素及预测分析

  • 摘要: 农业是碳排放的重要来源之一,而种植业碳排放是其关键组成部分,具有显著的区域差异。基于2000—2022年内蒙古种植业相关数据,采用IPCC因子系数法系统测算了农资投入及农田土壤碳排放量,并结合LMDI分解模型分析了生产效率、产业结构、经济水平与农业人口四类因素对碳排放的动态影响。此外,利用STIRPAT模型的岭回归分析对内蒙古种植业碳排放趋势进行了预测。研究结果表明,2000—2022年间,内蒙古种植业碳排放总量由242.98万吨增至568.09万吨,年均增长率为3.94%,呈现出“增长—回调—反弹”的波动特征。在农资投入碳排放中,化肥施用占比接近一半,农膜使用的年均增长率达到5.4%。在农田土壤碳排放方面,玉米因种植面积扩大成为主要碳排放源,其占比由50.8%上升至83.3%;大豆排放占比维持在10%—20%之间;小麦与薯类碳排放减少约65%。LMDI分解结果显示,经济水平对碳排放增长的贡献率高达284.01%,是主要驱动因素;生产效率和农业人口的贡献率分别为-137.85%和-41.67%,表明二者有效抑制了碳排放;而产业结构优化的减排贡献较小,仅为-4.49%。基于STIRPAT模型与岭回归分析构建三种情景,基准情景下2030年碳排放量为659.02万吨,低碳情景为619.21万吨,强化减排情景则进一步降至561.24万吨。为实现内蒙古种植业碳减排,应重点推进化肥减量、技术升级与绿色低碳生产方式的推广。

     

    Abstract: Agriculture is one of the major sources of carbon emissions, with crop cultivation being a key component that exhibits significant regional differences. Based on data from 2000 to 2022, this study systematically measured carbon emissions from agricultural inputs and farmland soils in Inner Mongolia using the IPCC emission factor method. It further applied the LMDI decomposition model to analyze the dynamic impacts of production efficiency, industrial structure, economic level, and agricultural population on carbon emissions. In addition, ridge regression based on the STIRPAT model was used to forecast the carbon emission trends of crop cultivation in Inner Mongolia.The results show that from 2000 to 2022, total carbon emissions from crop cultivation in Inner Mongolia increased from 2.43 million tons to 5.68 million tons, with an average annual growth rate of 3.94%, displaying a “growth–adjustment–rebound” fluctuation pattern. Among agricultural input emissions, fertilizer use accounted for nearly half, while the annual growth rate of plastic film use reached 5.4%. Regarding farmland soil emissions, corn became the primary emission source due to the expansion of its planting area, with its share rising from 50.8% to 83.3%. Soybean emissions remained between 10% and 20%, while wheat and tuber crop emissions declined by about 65%.LMDI decomposition results indicate that economic growth contributed 284.01% to the increase in carbon emissions, making it the dominant driving factor. In contrast, production efficiency and agricultural population contributed -137.85% and -41.67%, respectively, demonstrating their significant inhibitory effects. The contribution of industrial structure optimization was relatively small at -4.49%.Based on the STIRPAT model and ridge regression analysis, three scenarios were constructed. Under the baseline scenario, carbon emissions are projected to reach 6.59 million tons by 2030; under the low-carbon scenario, 6.19 million tons; and under the enhanced mitigation scenario, 5.61 million tons. To achieve carbon reduction in crop cultivation in Inner Mongolia, efforts should focus on fertilizer reduction, technological upgrading, and the promotion of green and low-carbon production practices.

     

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