The Research on Prediction and Control of Carbon Emission for Jiangsu Province

With the rapid economic development in recent years, increasing energy consumption, as well as the relatively low energy efficiency and the coal-focused energy consumption structure, causes the carbon emission of Jiangsu Province increase continued. Predicting the trend of carbon emission and analyzing the impact factors of carbon emission is extremely important for mitigation strategy and the development of low carbon economy. This paper analyzes the impact factors of carbon emission and establishes an improved BP neural network model according to the statistical data in 1995 similar to 2007. Through comparing this model with the principal component regression model, the result shows that the improved BP neural network has better predictive effect. So carbon emission in next three years is predicted through the model, it's predicted that the carbon emission is increasing. Finally, in 2010, for example, controlling for other factors constant, the influence of energy efficiency, industrial structure and energy consumption to carbon emission is analyzed, it will provide the basic for the development of low-carbon economic for Jiangsu province.