河南农业碳排放驱动效应及情景预测研究  

Research on the Driving Effect and Scenario Prediction of Agricultural Carbon Emission in Henan Province

作　　者：李青霞 史维良 LI Qingxia;SHI Weiliang(School of Statistics,Xi'an University of Finance and Economics,Xi'an 710100,China)

机构地区：[1]西安财经大学统计学院,西安710100

出　　处：《科技与经济》2025年第2期46-50,共5页Science & Technology and Economy

摘　　要：为推动河南农业绿色发展,促进低碳绿色转型,基于河南2001—2021年种植业和畜牧业相关数据,利用IPCC法测算农业碳排放量,并通过LMDI模型对其分析驱动因素,再结合SVR模型和情景预测分析法预测2022—2030年河南农业碳排放量。结果显示:碳排放量呈“先上升后下降”趋势,在2015年达到峰值,其中农用物资投入的碳排放贡献率最高;经济水平是碳排放的正向驱动要素,而生产效率则是最主要的负向驱动因素;碳排放量在未来仍将持续走低。最后,从提高农资投入利用效率、提升农业生产效率方面提出建议。Based on data of planting and animal husbandry in Henan Province from 2001 to 2021,the total agricultural carbon emission was calculated by the IPCC method in order to promote the green development of the agriculture in Henan Province and facilitate low-carbon and green transformation.The driving factors were analyzed by the LMDI model,and carbon emissions from 2022 to 2030 were predicted by combining the SVR model with scenario prediction analysis.The results indicate that total carbon emissions exhibited an“up-and-down”trend,peaking in 2015,with agricultural material inputs contributing the highest carbon emission rate.The economic level serves as a positive driving factor for carbon emissions,while production efficiency is the most significant negative driver.Carbon emissions are projected to continue declining in the future.Finally,suggestions are proposed for enhancing agricultural material efficiency and agricultural production efficiency.

关 键 词：河南 农业碳排放 LMDI模型 SVR模型 情景预测 

分 类 号：F323.22[经济管理—产业经济]