| The multi-scale temporal and spatial characteristics and correlation of six major air pollutants(PM2.5,PM10,SO2,NO2,CO and O3)were analyzed utilizing the R language analysis tools based on the monitoring data of the eight environmental monitoring site?state control?from November 2016 to October 2017.Combining the prior knowledge that the main difference of the the air pollution source was the coal pollution between the heating season and non-heating season,the quantitative evaluation method of the contribution rate of coal in Shenyang in winter was researched to provide scientific basis and technical support for the scientific and systematic treatment of air pollution.The research of the spatial-temporal correlation characteristics of air pollutants and quantitative evaluation of pollution sources in Shenyang were as follows:?1?The characteristics of the major air pollutants under multi-scale temporal and spatial scales were analyzed.By analyzing the monthly change characteristics of main air pollution in Shenyang,it was found that the monthly change tendency of PM2.5,PM10,SO2,NO2 and CO was similar but the concentration of the major pollution in the heating season was obviously higher than the non-heating season.Especially,the characteristics change of the O3 month average concentration was exactly the opposite.The primary air pollutants and their proportions in different urban areas of Shenyang during the heating season and non-heating season were compared and can be found that the primary air pollutants of the heating season were mainly PM10 and SO2,and the proportion of SO2 in the main urban area as the primary air pollutant was significantly higher than the surrounding urban areas.The primary air pollutants of the non-heating season were mainly O3 and PM10,and the proportion of various pollutants in different urban regions was relatively stable.On the contrary of the hour average concentration changing disciplinarian of the air pollutants during the heating season and the non-heating season,it was shown that the time point of the low concentration and high concentration during the heating season and non-heating season have higher consistency.That means the process of their change has a high degree of similarity.?2?The Apriori algorithm and R language toolkit were utilized to analyze the spatial and temporal correlations of the major air pollutants in different urban areas during the heating season and non-heating season.The serious PM2.5 pollution were always occurred simultaneously with other pollutants and the pollution effect will be doubled even if the concentration of some pollutants did not meet the standards.The PM2.5 pollution was more likely to occur with a high concentration of PM10,SO2 and NO2.The PM10 concentration level of the single pollutant was the key effect to occur the PM2.5 pollution.During the heating season,the probability of occurrence of PM10and PM2.5serious pollution in the main urban was higher than the surrounding urban.In the non-heating season,the probability of concurrence of PM2.5 pollution with multiple air pollutants in the main urban area was significantly lower than the surrounding urban.?3?The contribution rate of coal pollution n winter were quantified and evaluated.Based on the prior knowledge of the obviously differences of the coal pollution between heating season and non-heating season,The comparative analysis of the correlation of major air pollutants during the heating season and non-heating season were shown that the strong correlation rules of PM2.5,PM10,SO2,NO2 and CO were similar,but there was with quite difference of the concentration level.So it was proved that the coal pollution exists outstanding contribution rate in winter season.The similar distribution characteristics were verified and proved by the discrete Fréchet distance.Finally,utilizing the background difference method to quantify and evaluate the contribution rate of winter coal pollution in the different urban areas.The contribution of coal pollution in winter season for PM2.5,PM10,SO2,NO2 and CO was quite higher.The contribution rate for SO2 was 76.29%,followed by CO with the contribution of 56.94%,the PM2.5 was 46.68%;.The contribution in the main urban areas was significantly higher than the surrounding urban areas.This means that the impact of coal for the atmospheric environment was larger and the greater the population density of the main urban.?4?The analysis system of the air pollutant monitoring data that based on LINUX operating system,MySQL database and R language was designed.For the practical application,the system architecture was composed of public cloud,private cloud and application side.The flow restriction of input and output of the data were designed around the requirement to reduce the system development cost,improving system stability and ensuring data security.The Baidu cloud server was employed to storage and manage data and the private cloud was built for host application that can analyze data for user to access data.The Shiny-Server that was a web serer can automatically run R scripts was utilized to enables the applications of data analytic visualization of client side only with the shown on the mainstream browsers. |
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