| In order to understand the factors which affect the quality concentration of PM2.5, the restricting factors of PM2.5 concentrations and find the effective ways to reduce the quality concentration of PM2.5 in Harbin, we studied the factors affecting the quality concentration of PM2.5 based on the daily average data of the air pollutants and meteorological factors in winter, 2014.Study the main influence factors of PM2.5 concentrations in Harbin, and obtain some achievements.1 Analysis the environmental protection bureau released the data, the result shows that PM2.5 concentrations showed a trend of fluctuations rise, along with seasonal changes in Harbin,2013. Through the data analysis of The Environmental Protection Agency (EPA) in Harbin, the quality concentration of PM2.5 displayed a fluctuating upward trend seasonally before 2013. In 2013 the number of days on which the air quality in Harbin exceeds the standard was 171 days. In those days,87 days are in winter, because the primary pollutant is PM2.5. In January 2014, the number of days on which the air quality exceeds the standard was 25 days, including 29 days for the primary pollutant of fine particulate matter (PM2.5),25 days on which the air quality exceeds the average standard daily, the average standard monthly was 130 μg/m3 and the air quality exceeds the secondary standard yearly by 2.71 times. The number of days in February on which the air quality exceeds the standard was 22 days, including 24 days for the primary pollutant of fine particulate matter (PM2.5),22 days on which the air quality exceeds the average standard daily, the average standard monthly was 120 μg/m3 and the air quality exceeds the secondary standard yearly by 2.43 times. The number of days in March on which the air quality exceeds the standard was 4 days, including 15 days for the primary pollutant of fine particulate matter (PM2.5),4 days on which the air quality exceeds the average standard daily, the average standard monthly was 60μg/m3 and the air quality exceeds the secondary standard yearly by 0.71 time.2 Correlation analysis, principal component analysis and path analysis method are applied, these methods are mainly used to study the daily data of air environmental quality of sulfur dioxide, nitrogen dioxide, carbon monoxide, ozone, PM10, PM2.5 in Harbin, on January and February 2014 in Harbin. The results show that PM2.5 is related positive significantly to sulfur dioxide, nitrogen dioxide, PM10, carbon monoxide. Combining with the result of correlation analysis, established a principal component regression model between PM2.5 and sulfur dioxide, nitrogen dioxide, PM10, carbon monoxide. Path analysis is used on the model, the results show that the carbon monoxide is the maximum direct effect of PM2.5. The direct effects from sulfur dioxide, nitrogen dioxide, PM10 are relatively small, but the indirect effects of PM2.5 through carbon monoxide is relatively large.3 Correlation analysis, the PLS1 and size analysis method are applied to studied the direct impact of the main air pollutant on the concentration of PM2.5, the indirect effects through other air pollutants and synergy between air pollutants based on the data of the main air pollutants Harbin in January 2014 (a total of 31 days). The results showed that PM2.5 is related significantly to sulfur dioxide, nitrogen dioxide, PM10, carbon monoxide. The correlation between the ozone and PM2.5 is not significant. There is serious multi-colinearity between sulfur dioxide, nitrogen dioxide, PM10 and carbon monoxide. Based on the results of correlation analysis, a PLS1 model is established for sulfur dioxide, nitrogen dioxide, PM10 and carbon monoxide influencing the quality concentration of PM2.5. The results show that goodness-of-fit of the PLS1 model is good and is 0.852. Path analysis is used on the PLS1 model, the results show that the direct effect of sulfur dioxide, nitrogen dioxide, PM10 and carbon monoxide on quality of PM2.5 concentration are 0.005,0.142,0.140,1.191, carbon monoxide is the maximum direct affect the quality of PM2.5. The indirect impact of sulfur dioxide, nitrogen dioxide, PM10 through carbon monoxide on the quality of PM2.5 are 0.706, 1.011,1.118, is greater than their effects. The total decision coefficient of sulfur dioxide, nitrogen dioxide, PM10 and carbon monoxide on quality of PM2.5 concentration changes is 85.9%.4 Correlation analysis, PLS1 and path analysis is used to study the direct effect, indirect effect through other meteorological factors and the synergy between meteorological factors on the change of quality of PM2.5 concentration based on the data in Harbin in January 2014, a total of 31 days.The meteorological factors data include speed, temperature, humidity and air pressure.The results show that PM2.5 is related significantly to wind speed, humidity, and wind speed is the strongest correlation between PM2.5. There is no significantly correlation between PM2.5 and temperature, pressure. Establish a PLS1 model of wind speed, temperature, humidity, air pressure on quality of PM2.5 concentration. Path analysis on the PLS1 model, the results show that the main meteorological factors affect the quality of PM2.5 concentration change is wind speed. The direct effect of wind speed on PM2.5 concentration and the indirect effect of temperature, humidity, air pressure through wind speed on PM2.5 concentration is greater than their direct effect. The increase of wind speed is beneficial to the spread of fine particulate matter, reduce haze days. The remaining factors on PM2.5 mass concentration change is greater than the comprehensive meteorological factors, the influence of meteorological factors is not the main factors influencing the quality of PM2.5 concentration.5 Three methods are applied to understand the factors which affect the quality concentration of PM2.5 in Harbin, based on the daily average data of the air pollutants and meteorological factors in January,2014. Use correlation analysis method to study the correlative relationship between the quantity concentration of PM2.5 and main air pollutants, meteorological factors. The results show that the PM2.5 is related significantly to sulfur dioxide, nitrogen dioxide, PM10, carbon monoxide, wind speed, humidity. The correlation between the one hour average concentration of ozone, the eight hours average concentration of ozone and PM2.5 is not significant. At the same time, there is serious multi-colinearly between nitrogen dioxide, PM10 and carbon monoxide. Based on the results of correlation analysis, a numerical model is built for the factors influencing the quality concentration of PM2.5. The results show that goodness-of-fit of PLS1 model is 0.905 and is good. Use path analysis to study the direct impact of the explanatory variables on the dependent variable, the indirect impact of the other explanatory variables on the dependent variable, the synergy of the explanatory variables on the dependent variable. The results show that the direct effect on the changes in concentration of PM2.5 is up to 1.007. The indirect effects from sulfur dioxide, nitrogen dioxide, PM10, wind speed, humidity on the quality concentration of PM2.5 is greater than their direct effects. The synergy of the explanatory variables reached 90.5%. |
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