Quantitative Relationship Between Atmospheric Particulate Concentration And Visibility

With the rapid development of China’s economic and social and motor vehicle ownership increases sharply, resulting in particulate matter (PMio) and total suspended particles (TSP) pollution has not been effective control, under the condition of beijing-tianjin-hebei, the Yangtze river delta, the pearl river delta areas such as fine particulate matter (PM2.5) pollution is aggravating, the ash haze phenomena occur frequently.The occurrence of haze obviously characterized by low visibility.And reflected by the visibility of a sensory pollution levels closer to the ordinary people, thus the visibility of Shandong province as a technical reference indicator to assess environmental air quality. But visibility can accurate evaluation of the environmental air quality, so far there is no scientific discourse.Through the establishment of ambient air particulate matter concentrations and the quantitative relationship between the atmospheric visibility, can explain scientific environmental air quality and visibility of the differences, and help to study atmospheric haze, urban visibility assessment, prediction and improvement has important theoretical significance.This paper treated Shandong province as the study area. SPSS19.0based on on-line automatic monitoring data, applications, statistical analysis of particle concentration and atmospheric visibility variation characteristics, and studies the quantitative relations between the concentration of particulate matter and visibility. The research content and the main conclusions are summarized as follows:(1)Dezhou and Jinan days of PM10over standard were164d,218d, respectively,44.93%,44.93%of the total; Qingdao and Yantai PM10condition better, days of over standard can be controlled to about10%. Dezhou and Jinan days of PM2.5over standard were250d,210d, respectively68.5.%,57.73%of the total; Qingdao and Yantai over standard days were69d,18.90%of the total. Particulate matter mass concentration is obvious diurnal change rule of bimodal, including peak appeared at08:00and22:00respectively, may be related to the residents’daily life habits and the city meteorological conditions. Four city particulate matter (PM10and PM2.5) concentration variation characteristics are basic same, maximum in January. Particulate matter concentrations seasonal changes, the order of the mean season is winter> spring> autumn> summer. Four urban particulate matter pollution condition of Yantai city is best, followed by Qingdao, Dezhou and Jinan is worse.(2)Visibility in Yantai, Qingdao best times less, Dezhou and Jinan. Dezhou, Jinan, Qingdao, Yantai visibility of30km or more days respectively,22d,27d,95d,163d, total observation of the number of days respectively6.0%,7.4%,26.0%,7.4%; Visibility10km or less days respectively in196d,144d,88d,18d, accounted for53.7%of total observation days,39.5%,24.1%,39.5%.Dezhou visibility diurnal variation characteristics significantly, visibility minimum appear around08:00, the maximum16:00or so. Low visibility frequency of Dezhou and Jinan monitoring sites appear significantly higher than Qingdao and Yantai monitoring sites. Visibility month variation of the four cities is basically the same, the maximum average in January. Visibility seasonal changes significantly. Season average size of the order is autumn> spring> summer> winter. City of Shandong province as a whole, better visibility conditions, coastal cities are better than inland city, quite different things.(3)The correlation between visibility and PM2.5and PM10, RH, has negative correlation with wind speed, temperature, atmospheric pressure are low correlation. Therefore, PM2.5and PM10and RH are the main factors influencing the atmospheric visibility.(4) Particle concentration and visibility regression models with multiple correlation coefficients R all above0.6, the sample fitting is better, can reflect the variety regulation of visibility to accept; P values were less than0.05, the variables show significant difference, statistically significant. In RH<70%,70%<RH<80%two small segment model calculation values, and in80%<RH<90%segment model calculation value is larger; In RH<70%,70%<RH<80%and80%<RH<90%sections of the average error of33.2%,2.1%and9.7%respectively.(5) In70%<RH<80%section,"Blue sky, starry" differences between index and air environmental quality index."Blue sky, starry" can only be environmental air quality reference indicators.