基于出口贸易因素驱动下江苏省碳排放预测研究

Study on carbon Emission Prediction of Jiangsu Province driven by Export Trade factors

采用KAYA的模型对2000—2015年江苏省各年度碳排放量进行测算,并在此基础上利用回归分析的方法计算出江苏省碳排放量与出口贸易额以及万元GDP碳排放之间的定量关系,之后采用灰色预测模型和广义神经网络的方法对江苏未来的碳排量进行预测。研究发现,基于出口贸易因素驱动下的广义神经网络模型对江苏省碳排放的预测值与实际数值拟合度最好,江苏省的碳排放总量极有可能在2020年前后达到峰值。最后基于研究结果提出相关政策建议。

Using the KAYA model to estimate the carbon emissions of Jiangsu Province from 2000 to 2015.On this basis,the quantitativerelationship between the carbon emissions of Jiangsu Province and export trade volume and 10,000 yuan GDP carbon emissions is calculatedby regression analysis.Then the grey prediction model and the generalized neural network method are used to predict the future carbonemission of Jiangsu.The generalized neural network model based on the export trade factor is the best fit between the predicted valueand the actual value of carbon emissions in Jiangsu Province.The total amount of carbon emissions in Jiangsu Province is likely to reach itspeak around 2020.Finally,the relevant policy recommendations are put forward based on the results of the study.