Research On Carbon Emissions Prediction And Reduction Countermeasures Of Shandong Province

With the rapid growth of the economy, people’s living standards continues to improve and energy consumption is also increasing, thereby promoting the rise of carbon emissions. Shandong is a province with rapid economic development and large energy consumption, studying its carbon emissions problem is of vital importance, which can contribute to scientific and rational carbon reduction strategies for Shandong province.This paper analyzes the various factors that affect carbon emissions of Shandong, then select 8 factors including population, urbanization rate, the per capita GDP, the level of industrialization, the tertiary industry in GDP, energy consumption intensity, the proportion of coal consumption, the proportion of oil consumption as independent variables, build the carbon emissions prediction system of Shandong Province. This prediction system consists of 4 prediction methods, which respectively are Secondary Average prediction and Gray Prediction GM (1,1) based on time series prediction, STIRPAT model and Neural Network prediction model based on influencing factors. Then according to optimal weighting method, assign weights to four kinds of prediction methods to reduce systematic error of single prediction to get the optimal prediction results from 2012 to 2015. Prediction results prove that the trend of carbon emissions is up of Shandong Province. Finally, depending on the STIRPAT prediction model and Combined Prediction put forward relevant countermeasures to reduce the carbon emissions of Shandong Province. Depending on the STIRPAT prediction model and Combined Prediction put forward relevant countermeasures to reduce the carbon emissions of Shandong Province. And it’s including to control of population and urbanization rate growth, slowing GDP growth, optimizing the industrial structure and energy consumption structure, improving energy utilization efficiency and the level of energy utilization technology.