Positive Economic Growth And Environmental Pollution

Nowadays, people pay more and more attention to the environment problems, and the relationship between economy growth and chemical pollution has become hot point to the scholars both at home and abroad. Starting with the Environmental Kuznets curves and utilizing econometric models, the paper analyze the concrete correlation between CO₂ emission and economy growth of china 1980-2004 from energy consumption point. Through the analyzing and comparison of the CO₂ emission EKCs of coal, natural gas, petroleum and fossil fuel, then it put forward some counter measures to deal with the coordinated growth of energy consumption and economy.From the results we found that the CO₂ emission EKCs of our country present weak Environmental Kuznets curves features, and the relationship curves of CO₂ emission of different energy consumption and average GDP are diverse from each other which has something to do with the actual situation of china. Some researches had found that china's CO₂ emission EKCs conform to the peak theory, which means that in china the majority of CO₂ emission come from energy consumption. Making further analyses, we found that the relationship curves between energy consumption intensity and the average GDP, the emission intensity of CO₂ discharged from fossil fuel and coal and the average GDP are extremely the same, illustrating that the most CO₂ emission produced by energy consumption come from fossil fuel, and the coal play a leading role among the fossil fuel. The conclusion reveal the relations of our country's economy growth, CO₂ emission and the energy consumption constructions from a new visual angle, and make production of evidences to energy consumption and environment policies.Considering data's spatial dependence, this text deal with the EKCs using the matherd of spatial econometrics. We put the spatial lag term WLnY into the econometric model which refers to the average CO₂ emission of china and other 20 countries or areas around. A comparison of the ordinary regression model and the spatial autocorrelation model was made to reach a conclusion of the spatial effects, and we found that all the coefficients' notable level are rising when adding the spatial lag term.Then, we made a series of spatial effect tests to the results of the two equations, and found that the outcomes of the ordinary regression equation have the stronger spatial dependence and reject the hypothesis of having not spatial effect. On the other hand, the outcomes of the spatial autocorrelation equation have passed all the tests, which mean that it has not spatial dependence at all. The concrete result shows that the spatial effect of the CO₂ emission of Asia is sure existed, and the forward spatial dependence has been rising. The conclusion draws one's attention to that we should not only consider about the factors ourselves but also the conditions around us. The innovation of this text is using the spatial econometrics, and it also advises the scholars not to ignore the data dependence when considering EKCs.