基于STIRPAT模型的南京市农业碳排放驱动因素分析及趋势预测

Driving Factors and Trends Prediction of Urban Agricultural Carbon Emissions in Nanjing based on STIRPAT

摘要:

本文应用STIRPAT模型对影响南京市2000年—2015年农业碳排放驱动因素进行分析，并结合灰色模型GM（1,1）预测了南京市2016年—2025年农业碳排放量。研究结果显示：2000—2015年南京市农业碳排放量呈下降趋势，年均增长率为-3.07%；农村人口、富裕度、技术水平、能源效率、农村居民人均可支配收入、林业面积、城镇化率每发生1%的变动分别会引起南京市农业碳排放0.26%、0.11%、0.06%、0.31%、-0.07%、-0.06%、-0.09%的变化。根据GM（1,1）模型预测，南京市农业碳排放逐年下降，从2016年的57.96万吨下降到2025年的45.41万吨。研究得出南京市为进一步降低农业碳排放量，实现低碳农业发展，应调整农业产业结构、推行绿色农业生产方式，降低农业能源消耗，并加大政策扶持力度。

Abstract:

The factors which affecting agricultural carbon emissions in Nanjing from 2000 to 2015 were analyzed by STIRPAT model, and the agricultural carbon emissions in Nanjing from 2016 to 2025 were predicted by gray model GM (1, 1). The results show that agricultural carbon emissions are decreasing in the agricultural carbon emissions in Nanjing from 2000 to 2015, with an average annual growth rate of -3.07%. Rural population, wealth, technical level, the energy efficiency, the per capita disposable income of rural residents, the area of forestry, the urbanization rate each change 1% will increase 0.26%, 0.11%, 0.06%, 0.31%, -0.07%,-0.06% and -0.09% carbon emission from urban agricultural respectively. According to the GM (1,1) prediction model, it can be concluded that the agricultural carbon emission in Nanjing decreased year by year, from 57.96×104tons in 2016 to 45.41×104 tons in 2025. Therefore, in order to reduce agricultural carbon emissions and achieve low-carbon agriculture, Nanjing should adjust the structure of agricultural industry, implement green production mode, reduce agricultural energy consumption and increase policy support efforts.