Journal of Northern Agriculture ›› 2024, Vol. 52 ›› Issue (2): 87-96.doi: 10.12190/j.issn.2096-1197.2024.02.10

• Agroecology environment·Agrometeorology • Previous Articles     Next Articles

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

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

CLC Number: 

  • F327