大型工业城市碳排放影响因素分析及趋势预测——基于PLS-STIRPAT模型的实证研究

Influencing Factor Analysis and Trend Forecasting of Large Industrial Cities’ Carbon Emissions：Based On the PLS-STIRPAT Model

摘要:

选取天津市作为大型工业城市的代表,利用PLS方法对影响天津市1995年-2012年的碳排放因素进行实证分析,构建STIRPAT模型将碳排放量分解为人口数量、富裕度、能源强度、城市化率、煤炭消费比例、FDI、二产及三产占GDP的比率八个因素,并利用灰色模型预测天津市2020年能源强度。研究结果显示：人口数量和第二产业比率是影响天津市碳排放最主要的两项因素,能源强度和第三产业比率抑制天津市碳排放量的增加,且天津市目前不存在环境库兹涅兹曲线；利用GM(1,1)预测可以得出,2020年天津市能源强度为2005年的44.19%,降幅达到55.81%,优于全国的减排标准。

Abstract:

The paper selects Tianjin as a representative of large industrial cities, and PLS method is used to study the factors that impact on the Tianjin carbon emissions based on the data from 1995 to 2012, build the STIRPAT model which decomposed carbon emissions into population, affluence, energy intensity, urbanization, the proportion of coal consumption, FDI, secondary industry and tertiary industry accounted for GDP, the gray GM(1,1) model is used to forecast the carbon emission strength of Tianjin in 2015 and 2020. The result of study shows that population and proportion of the tertiary industry were the most important driving forces impact the carbon emissions, and the environment Kuznets curve didn’t exist in Tianjin. By using the GM(1,1) the 2020 Tianjin city carbon emission strength is predicted to be 44.19% in 2005 and drop to 55.81%, far better than the national emission standards.