浙江省农业碳排放影响因素分析与预测研究  

Analysis and forecasting research on influencing factors of agricultural carbon emissions in Zhejiang Province

作　　者：韩争 丁宁[1] 郑光华[1] 徐江荣[1] HAN Zheng;DING Ning;ZHENG Guanghua;XU Jiangrong(School of Sciences,Hangzhou Dianzi University,Hangzhou 310018,China)

机构地区：[1]杭州电子科技大学理学院,浙江杭州310018

出　　处：《杭州电子科技大学学报（自然科学版）》2024年第3期43-50,共8页Journal of Hangzhou Dianzi University：Natural Sciences

基　　金：浙江省自然科学基金(LQ21E060005)。

摘　　要：碳排放引起的气候变化是全球重点关注的问题,农业是温室气体主要源头之一,准确测算和预测农业碳排放对于实现“双碳”目标具有重要意义。文章采用排放因子法测算农业碳排放,利用STIRPAT扩展模型定性与定量分析碳排放影响因素,构建SVR模型预测2022-2035年碳排放总量。结果表明,2001-2021年浙江省农业碳排放总量呈下降趋势,牲畜粪便发酵对农业碳排放贡献最大,占比45.2%;在各影响因素中,种植结构、城镇化率和富裕水平为增碳因素,人口规模、畜牧业规模为抑碳因素;在2022-2035年的7种预测情景中,综合优化情景下的农业碳排放下降显著,较2021减少35.2%,而其他6种情景可以为农业碳减排提供不同方向的参考。Climate change caused by carbon emissions is a key global concern,and as agriculture is one of the main sources of greenhouse gases,accurate measurement and prediction of carbon emissions from agriculture is of great significance in achieving the dual-carbon target.This paper adopts the emission factor method to measure agricultural carbon emissions,uses the STIRPAT extended model to qualitatively and quantitatively analyze the carbon emission influencing factors,and constructs the SVR model to predict the total amount of carbon emissions from 2022 to 2035.The results show that the total agricultural carbon emissions in Zhejiang Province show a decreasing trend from 200l to 202l,and livestock manure fermentation makes the largest contribution to agricultural carbon emissions,accounting for 45.2%;among the influencing factors,cropping structure,urbanisation rate and prosperity level are the carbon-increasing factors,and population size and livestock size are the carbon-suppressing factors.In the seven prediction scenarios from 2022 to 2035,agricultural carbon emissions under the comprehensive optimization scenario decrease significantly by 35.2%compared with 202l,while the other six scenarios can provide references for reducing agricultural carbon emissions in different directions.

关 键 词：浙江省 碳排放 STIRPAT SVR 因素分解 预测研究 

分 类 号：X322[环境科学与工程—环境工程]