基于改进BP神经网络的河北省碳排放量增长影响因素分析

Analysis on the influential factors of carbon emission growth based on the improved BP neural network in Hebei

根据河北省1995—2010年能源消耗量和碳排放系数计算碳排放量,确定人口数量、GDP、第二产业比重、能源结构、技术进步及能源价格为碳排放量的主要影响因素,运用改进的BP神经网络方法计算这些因素对碳排放量的影响力系数,评价各因素对碳排放量的影响程度。结果表明:与碳排放量具有正相关关系的因素为GDP、第二产业比重、人口数量和能源价格,其影响力系数分别为1.12、0.92、0.42和0.12,这说明GDP增加是导致碳排放增加最重要的因素,第二产业比重提高是导致碳排放增加的次级因素;与碳排放量具有负相关关系的因素为能源结构和技术进步,其影响力系数分别为-0.47和-0.26,能源结构多元化是降低碳排放量的主要因素,技术进步也是降低碳排放不可忽略的因素。为此,河北省应采取降低第二产业比重、增加第三产业比重、改进能源结构、降低煤炭消耗比重、提升技术进步水平等措施来降低碳排放量。

The paper is aimed as introducing our analysis on the in fluential factors of carbon emission growth based on the improved BP neural network in Hebei. For this research purpose, we have calcu lated the total amount of carbon emissions in the province in accor dance with the energy consumption and the carbon emission coeffi cient from 1995 to 2010, which has been done by taking the number of population, the total GDP, the proportion of secondary industry, the energy constitution, the technological progress and the energy consumption cost as main influential factors on the carbon emissions. In doing so, we have also worked out the influential coefficients of the above said factors on the carbon emissions via the improved BP neu ral network. The results of our analysis show that, the degree of in fluential factors, the total GDP, the proportion of the secondary in dustry, the number of population and the energy cost can all be ex pressed in a positive correlation equation with the total amount of car bon emissions and the energy consumption cost as 1.12, 0.92, 0.42 and 0.12 respectively, which implies that the GDP increase serves as the chief influential factor that leads to increased carbon emissions whereas the proportion increase of the secondary industry is the sec ondary factor leading to the increase of the emission. Though the en ergy structures and the technological progress may have a negative correlation with the increase of carbon emission amount, the respec tive values can be given as 0.47 and 0.26. Since energy struc ture serves as the chief influential factor on the reduction of the car bon emissions and the improvement of the technological progress, it should never be ignored if we want to reduce the carbon emissions. Therefore, it is of great urgency to take measures to reduce the pro portion of the secondary industry production, but to make greater ef forts in increasing the ratio of the tertiary industry, while improving the energy structure, reducing the ratio of coal consumption by pro moting the technological progress in order to reduce the total amount of carbon emissions in the Province.