长江流域资源与环境 >> 2018, Vol. 27 >> Issue (02): 300-.doi: DOI:10.11870/cjlyzyyhj201802013

• 农业发展 • 上一篇    下一篇

基于STIRPAT和GM(1,1)模型的湖南省农地投入碳排放增长机理及趋势预测

黎孔清1,陈俭军2,马豆豆2   

  1. (1.南京农业大学人文与社会发展学院,江苏 南京 210095;2.南京农业大学经济管理学院,江苏 南京 210095)
  • 出版日期:2018-02-20

Growth Mechanism and Trend Forecast of Carbon Emission from Farmland #br# Inputs in Hunan Province Based on Stirpat and GM (1,1) Model

LI Kong-qing1, CHEN Jian-jun2 , MA Dou-dou2   

  1.  
    (1. College of Humanities and Social Development, Nanjing Agricultural University, Nanjing, 210095, China;
    2. College of Economics and Management, Nanjing Agricultural University, Nanjing, 210095, China)
  • Online:2018-02-20

摘要:

探索农地投入的碳排放特征、增长机理及趋势预测,并提出减排对策对农业发展向低碳绿色转型具有重要意义。研究采用回归分析法、STIRPAT和GM(1,1)模型解析湖南省农地投入碳排放增长机理并做出趋势预测。结果表明: 2000~2014年湖南省农地投入碳排放量呈上升趋势,年均增长率为3.25%,各类碳源中化肥累计的碳排放量最大,其次是农药;此外翻耕、农药、农膜、柴油、灌溉、化肥累计碳排放年均增长量分别为0.68%、3.22%、7.47%、6.42%、2.57%、3.25%。农业人口、人均农业GDP、机械化水平、农业生产效率、农业产业结构显著影响农地碳排放,各因素每发生1%的变动会相应带来农地碳排放量约0.20%、0.95%、0.12%、0.98%和0.93%的变化。通过GM(1,1)模型对2016~2020年湖南省农地投入碳排放量进行预测,碳排放量呈持续上升趋势,2020年预计达到430.43万t。最后根据研究结果提出促进农地投入碳减排的政策建议。
 

Abstract:

Exploring the characteristics, influencing factors and trend forecast of carbon emission from farmland inputs, and putting forward the policy proposal to promote the carbon reduction of farmland inputs has great significance to the transformation of low carbon and green agriculture. In this paper, the growth mechanism and the trend forecast of carbon emission from farmland inputs in Hunan Province were studied by Regression Analysis, STIRPAT and GM (1,1) model. The results show that the annual growth rate of carbon emission from farmland inputs in Hunan Province increased 3.25% from 2000 to 2014. The total carbon output of chemical fertilizers in various carbon sources was the highest, followed by pesticide; The average annual growth rate of total carbon emissions from tillage, pesticide, agricultural film, diesel, irrigation and chemical fertilizer was 0.68%, 3.22%, 7.47%, 6.42%, 2.57% and 3.25% respectively. The agricultural population, per capita agricultural GDP, mechanization level, agricultural production efficiency, and agricultural industry structure significantly affected the carbon emissions from farmland inputs, and each change of 1% will bring about 0.20%, 0.95%, 0.12%, 0.98% and 0.93% change in carbon emissions from farmland inputs. The GM (1,1) model was used to forecast the carbon emissions from farmland inputs in Hunan Province from 2016 to 2020, and the carbon emission was rising continuously, which is expected to 430.43 million tons in 2020. Finally, according to the conclusions of the study, it puts forward some policy suggestions to promote the carbon reduction of farmland inputs.
Key words:farmland inputs; carbon emissions; STIRPAT Model; GM (1,1); Hunan Province

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