| China is a high value area of global PM2.5 pollution,the Yangtze River Delta region is a very representative region.Chinese government proposed to tackle smog and continue to promote the construction of ecological civilization on the session of NPC and CPPCC in 2016.And the concentration of PM2.5.5 was incorporated into the binding index for the first time in the"13th Five-Year plan”.According to the environmental bulletin of Shanghai for three consecutive years,PM2.5 had become the main pollutant of air pollution in Shanghai in recent years.In this paper,wavelet analysis was applied to analyse the concentration of PM2.5 in Shanghai.By changing the number of large and disorganized data into multi-level decomposition,we could obtain the obvious periodic characteristics and forecast the change of future PM2.5 concentration in shanghai.The PM2.5 data of the ten national controlling monitoring stations was analyzed by surfer and cluster analysis in order to further analyze the spatial distribution characteristics of PM2.5.In addition,the correlation analysis was used to study the influence of air pollutants and meteorological conditions on PM2.5 concentration.Principal component analysis was used to study the main factors influencing the source,composition and transformation process of PM2.5.The results could provide technical support in the short-term forecast and prevention of large-scale outbreak of haze events.The main results of this paper were as follows:?1?The annual average concentration of PM2.5 reached 53.6?g/m3which decreased 14%comparing with the benchmark year in 2013.The monthly variation of PM2.5 presented a“U”type distribution.The average monthly maximum concentration was 82.9?g/m3 occurred in January and the minimum concentration was 33.89?g/m3 occurred in September.Seasonal change magnitudes of PM2.5 pollution presented the sequence of winter>spring>autumn>summer.?2?The morlet wavelet analysis showed that when the time scale was10,23,51,98,207,the periodic variation of PM2.5 concentration was the strongest.The results showed that the prediction of the PM2.5 concentration trend was accurate.?3?The data of PM2.5 concentration of each air quality monitoring site in Shanghai was plotted and clustered by surfer software and SPSS statistical analysis software.The results showed that these sites could be classified into five categories according to PM2.5 pollution degree,the classifications were related to the location in the ring roads,meteorological conditions and human activities.?4?By calculating the correlation matrix of every AQI monitoring index,there was maximum correlation between PM2.5 and PM10.Person correlation coefficient of PM2.5 and PM100 was 0.919.At the same time,CO,NO2 and SO2 also showed a significant correlation with PM2.5.There was a negative correlation between PM2.5 and ozone,but the correlation was not significant.By analyzing the partial correlation of meteorological conditions and PM2.5 concentrations,the results showed significant correlation.?5?The main factors influencing the concentration of PM2.5 were calculated and analyzed by principal component analysis.The results showed that CO?NO2?PM10 and SO2 were the most important factors influencing the concentration of PM2.5 and the concentration could be largely predicted by the established model. |
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