Air Quality Analysis And Forecast In Changsha

This paper investigates the correlation among six AQI indicators(PM2.5,SO2,NO2.PM 10,CO,O3)of Changsha,Hunan province.Then through establishing GARCH model and Grey GM model to predict the PM2.5.SO2 and NO2 in Changsha.This paper is divided into five chapters.In Chapter 1,we mainly introduce the background,significance of this study,and then introduce the main contents and innovations of the research.In Chapter 2,we analyze the correlation between six AQI indicators through the Grey Relational Analysis and the Multiple Regression Analysis.First,we manage the missing data and make the data normalization,then test the correlation.And we extract the principal component Fi and F2 through Principal Component Analysis.Then we get the regression equation by using the Multiple Regression Analysis in order to analyze the dependency relationship among PM2.5 and other monitoring indicators.In Chapter 3,we use the time series GARCH Model to forecast the PM2.5 of Changsha.After making stationary test and ARCH effect test on the data,we build GARCH(1,1)model and make one-week delay numerical prediction in the first half of 2017 in Changsha.The result shows that the error is between 0.1 to 0.6.In Chapter 4,we use Grey GM model to forecast PM2.5,SO2 and NO2 of Changsha.First,we collect the annual average concentration of PM2.5.SO2 and NO2 from 2008 to 2017.Then establishing GM(1,1)model to make a five-year delay prediction of Changsha’s annual average air quality.The last,we provide some policy references for air polluion control.In Chapter 5,we analyze the causes of air pollution in Changsha and provide some measures to prevent air pollution.