Research On Analysis And Visualization Of Atmospheric Pollutant Data In Tianjin

As an industrial city in China,Tianjin has a total industrial production value of 2.94 trillion yuan in 2016,becoming the first industrial city in the north.At the same time,with the rapid growth of population in Tianjin and the rapid increase in the number of motor vehicles,the level of air pollution in Tianjin has intensified,especially the increase of particulate pollutants such as PM2.5 and PM10,which has caused the smog in Tianjin to increase.The deteriorating air quality in Tianjin has seriously threatened the health of the broad masses of the people,especially the incidence of diseases in the respiratory system.Analysis of the sequential variation and geographical distribution characteristics of atmospheric pollutants in Tianjin has crucial scientific significance for revealing the changes of air quality in Tianjin,and provides data support for the development of targeted and accurate pollution control strategies.Taking Tianjin's main pollutants such as sulfur dioxide,nitrogen dioxide,carbon monoxide,ozone,PM2.5 and PM10 as the research object,based on the data of all national and municipal monitoring points in Tianjin in 2016,the pollution for 2016 is throughout the year.The correlation and analysis of the mass concentration changes were carried out,and the pollutant concentration distribution was visualized in 3D.The main work and conclusions of the paper are as follows:Firstly,the noise data detection and repair model has established,and the obtained raw pollutant concentration data was cleaned.In the process of noise detection and repair,not only the changing trend of the single pollutant's time series but also other gaseous pollution was also considered.The trend of the concentration of the substance was compared,and the detection and correction of the dirty data played a positive role.Secondly,based on data cleaning of the original data,the daily and monthly characteristics of the atmospheric pollutants monitored in Tianjin have statistically analyzed,and the changes of atmospheric pollutants at various points in the day have summarized.The law of change in different months,the application of regression calculations,and the correlation between the daily average concentration values of different pollutants in 2016 was obtained.Thirdly,the concentration values of each pollutant detected by 27 monitoring points in Tianjin were clustered by hierarchical clustering algorithm and K-means clustering algorithm,and the clustering results showed a high degree of consistency.Firstly,this verified the correctness of classification results.Secondly,the areas covered by the monitoring points in the same result class indicate that the contaminant concentration values have a high degree of similarity,which guides the development of targeted regional pollution control strategiesFourthly,an atmospheric pollutant concentration interpolation model has established.The Tianjin city was divided into multiple grids according to the administrative area.The grid pollutant concentration data was interpolated twice,and a three-dimensional visualization model of atmospheric pollutants in Tianjin was established.The spatial distribution of various atmospheric pollutants in Tianjin was presented in three dimensions.