北方农业学报 ›› 2024, Vol. 52 ›› Issue (2): 87-96.doi: 10.12190/j.issn.2096-1197.2024.02.10

• 农业生态环境·农业气象 • 上一篇    下一篇

基于灰色预测和脱钩模型的甘肃省农业碳排放预测分析

何丽博, 任苏灵   

  1. 兰州财经大学 统计与数据科学学院,甘肃 兰州 730020
  • 收稿日期:2024-03-07 出版日期:2024-04-20 发布日期:2024-07-24
  • 通讯作者: 任苏灵(1985—),女,副教授,博士,主要从事随机分析及其应用、金融随机分析的研究工作。
  • 作者简介:何丽博(1998—),女,硕士研究生,研究方向为金融随机分析。
  • 基金资助:
    国家自然科学基金青年基金项目(12101279); 甘肃省自然科学基金项目(21JR11RA133); 甘肃省教育厅高等学校创新创业基金项目(2021A-072)

Analysis of agricultural carbon emission prediction in Gansu Province based on gray prediction and decoupling models

HE Libo, REN Suling   

  1. School of Statistics and Data Science,Lanzhou University of Finance and Economics,Lanzhou 730020,China
  • Received:2024-03-07 Online:2024-04-20 Published:2024-07-24

摘要: 【目的】 分析甘肃省2000—2020年农业碳排放总量及其发展演变特性和脱钩效应,为甘肃省绿色低碳农业发展提供参考。【方法】 以农业物资投入碳源为数据样本,基于IPCC碳排放系数法测算了甘肃省2000—2020年的农业碳排放量,利用灰色预测模型GM(1,1),预测2025—2030年甘肃省农业碳排放量,并对预测结果进行对比分析;利用Tapio脱钩模型来分析农业碳排放与农业经济发展之间的关系。【结果】 2000—2020年甘肃省农业碳排放量表现出先增加后减少的变化趋势,碳源主要是化肥和薄膜,化肥碳排放量占农业碳排放量的比重为31.27%~43.22%,在20年间始终处于最高;2015年农业碳排放量达到最大,为282.513 8万t,2015年后开始逐渐下降,2020年农业碳排放量为228.860 1万t;2000—2020年农业碳排放的脱钩关系多表现为强脱钩或弱脱钩;以近10年数据和近5年数据为样本预测出的农业碳排放量整体均呈现明显的下降趋势,且以近5年的数据为样本进行预测时,模型的预测精度最高;甘肃省农业碳排放量在2025年之前已达到峰值,近5年数据样本预测出的农业碳排放量中,2025年与2020年相比,农业碳排放量将减少17.08%,到2030年该降幅将会达到30.36%,年均减少幅度为13.90万t。【结论】 甘肃省的农业碳排放量持续下降、农业经济整体呈现稳定增长的态势,农业碳排放量在2025年前达到峰值,说明甘肃省近年来的绿色低碳农业已经取得了一定进展,应根据当地的实际情况采取相应的措施,以达到持续推动绿色农业发展、减少高碳排放活动、增加农业碳汇、实现甘肃省农业碳减排的目标。

关键词: 甘肃省, 灰色预测, Tapio脱钩模型, 农业碳排放, 农业经济, 农资投入

Abstract: 【Objective】By analyzing the total amount of carbon emissions from agriculture in Gansu Province during 2000 to 2020 and its development and evolution characteristics,and the decoupling effect as a reference for the development of green and low-carbon agriculture in Gansu Province.【Methods】The agricultural carbon emissions in Gansu Province between 2000 to 2020 were measured based on the IPCC carbon emission coefficient method using agricultural inputs as the carbon source,and using the grey prediction model GM(1,1),the agricultural carbon emissions of different years were selected as samples to predict the agricultural carbon emissions in Gansu Province from 2025 to 2030,and the prediction results were compared and analyzed. The Tapio decoupling model was used to study and analyse the relationship between agricultural carbon emissions and economic development.【Results】Agricultural carbon emissions in Gansu Province from 2000 to 2020 show a trend of increasing and then decreasing.The source of carbon emissions were mainly chemical fertilizers and agricultural films,chemical fertilizer carbon emissions accounted for 31.27% to 43.22% of agricultural carbon emissions,always at the highest level during the 20-year period;agricultural carbon emissions reached a maximum of 2.825 138 million tons in 2015. After 2015,it began to decline gradually,and the agricultural carbon emissions in 2020 were 2.288 601 million tons. The decoupling relationship of agricultural carbon emissions from 2000 to 2020 mostly showed strong decoupling or weak decoupling. Using the data of the last 10 years and the data of the last 5 years as the samples to predict the agricultural carbon emissions as a whole all showed a clear downward trend.The model′s prediction accuracy was the highest when using the data of the last 5 years as the sample for prediction. The agricultural carbon emissions in Gansu Province have reached the peak before 2025,agricultural carbon emissions projected for a sample of the last 5 years of data will be 17.08% lower in 2025 compared to 2020,the rate of reduction will reach 30.36% in 2030,and the average annual reduction rate will be 0.139 million tons.【Conclusion】Gansu Province′s agricultural carbon emissions continue to decline,the agricultural economy shows stable growth,and agricultural carbon emissions will peak before 2025,indicating that Gansu Province has made some progress in green low-carbon agriculture in recent years. Measures should be taken according to the actual local situation in order to achieve the goal of continuously promoting the development of green agriculture,reducing high-carbon emission activities,increasing agricultural carbon sinks,and realizing agricultural carbon emission reduction in Gansu Province.

Key words: Gansu Province, Grey prediction, Tapio decoupling model, Agricultural carbon emissions, Agricultural economy, Agricultural material inputs

中图分类号: 

  • F327