Evaluation Study On The System Of City Energy-saving Emission Reduction Policies In China

The twenty-first century is full challenges as well as opportunities. With the society developing at today’s high speed, we face serious problems such as energy crisis, greenhouse effect and pollution in environment in addition to natural disasters. With sustainability of China’s economy questioned, energy-saving emission reduction become a more and more important way for sustainable development. In this situation, our city introduced various energy-saving emission reduction policies, the performance results of the effects of the energy-saving emission reduction to promote the overall. In this context, this forecast study on our city regarding energy-saving emission reduction performance tries to provide a useful reference for our city to promote energy-saving emission reduction.After analyzing relevant energy-saving emission reduction evaluation both domestic and abroad, it is realized that existing research results are not suitable for the performance analysis of the policy. It starts from the requirement of public policy evaluation theory, to classify cities’energy-saving emission reduction policies. It then builds the evaluation space model. And it established a evaluation index system, too. As the requirements of such analysis, Fuzzy comprehensive evaluation method and artificial neural network are adopted as the evaluation method. Finally, the performance of China’s city energy-saving emission reduction policies are expected goal of analysis.In constructing a classification system for the nation’s city energy-saving emission reduction policies, we refined the policy content analysis of collected category factor, screened classification standards for those that are best fit for city energy-saving emission reduction policies, and hope to build a base for further research on policy evaluation.Since policy implementation have various target, we collected and analyzed a large amount of energy-saving and emission reduction evaluation results. Based on these, were fined and determined correlation dimensions to use for the evaluation. Finally, we choices for the evaluation dimensions. In the end, we constructed a widely applicable multi-dimension evaluation space model expected performance for emission reduction policies system for city energy-saving.This paper established the evaluation index system to evaluate the performance of China’s city energy-saving emission reduction policies in economic growth and structural adjustment dimension. This came from the need to evaluate the expected performance requirements of those energy-saving emission reduction policies. It was guided by the 11th Five Year Plan and the 12th Five Year Plan that included a comprehensive energy reduction program. Then, this paper chose the fuzzy comprehensive evaluation method and artificial neural network to achieve the goal of classification and overall evaluation of China’s city energy-saving emission reduction policiesAfter building this evaluation space model model, with established the index system, we then selected evaluation methods and used Chengdu and Hangzhou as target city, using fuzzy comprehensive evaluation method, expected performance of seven kinds of energy saving and emission reduction policy values. And we used DPS software with artificial neural network to synthetise the distribution of space situation of classification evaluation of the sample city. Then, we obtained the overall evaluation results of energy-saving emission reduction policy system of samples city.Finally, with the results of the evaluation, recommendation is provided regarding city energy-saving emission reduction policies given that both economic growth and structural adjustment are both taken into consideration.