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Study On A City Air Quality Assessment And Forecast In Jilin Province

Posted on:2014-02-24Degree:MasterType:Thesis
Country:ChinaCandidate:B F SunFull Text:PDF
GTID:2231330395497003Subject:Environmental Engineering
Abstract/Summary:PDF Full Text Request
Recently,our country especially in northern areas,the air pollution is even worseand the fog day is increasing,this threats our safety.Air quality assessment andprediction has been the focus of environment management.In this paper,we combinethe natural environment of the city in Jilin Province,the condition of air environmentand the air quality from2001to2010,using the EIA method and mathematicalmodel to assessment and prediction.This paper calculated the single pollution indexand the comprehensive pollution index,pollution load coefficient,basing on the resultof the calculation and the application of fuzzy mathematical model,we give thetotally assessment of the city in Jilin Province.Grey prediction model is a widely usedmodel,in this paper we apply it in the Air quality prediction,by establishing the GM(1,1)prediction model and calculating the average relative error,after checked anderror probability to evaluate the accuracy of the model.After checking,we believethat the accuracy of the model is good and then we analysis the Pollutant emissions inthe future ten years.We choose the common pollutants for assessment andprediction,including the SO2、NO2、CO and PM10,to explain the air qualitycondition and the future air quality trends of the city.According to the result,wefound that the major air pollutant is SO2、NO2、CO and PM10and the pollution islightly,and the pollution is increasing in the ten years,we should pay more attentionon it.On the other hand,the result of the Grey prediction model shows SO2、NO2、COwill increase in the future ten years and the SO2、NO2will not under the nationalstandards.The PM10will decrease because we strictly control it and always under thenational standards.
Keywords/Search Tags:air quality, assessment and prediction, fuzzy mathematical model, Grey Prediction Model
PDF Full Text Request
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