| The data of particles mass concentration, including Black Carbon (BC), PM2.5and PM10, together with surface meteorological factors in Suzhou, from July2009to May2010, were used. Based on that, we conducted the correlation analysis between visibility and particles mass concentration, and meteorological elements, including relative humidity, wind speed, wind direction and air temperature. The results indicated that the visibility negatively correlates with mass concentrations of BC, PM2.5and PM10. The correlation coefficients are-0.465,-0.359and-0.238resepectively. At low relative humidity(<60%) situation, the correlation coefficients are-0.675、-0.411and-0.364, while the correlation coefficients between visibility and air temperature, wind velocity, relative humidity are0.132,0.188and-0.632respectively. In conclusion,(1) the visibility correlates best with BC mass concentration among the three kinds of particles under study,(2) the lower the relative humidity is, the better particles mass concentration correlates with visibility. A linear regression model based on BC,PM10and relative humidity was built, the result of which is not good enough. Based on the linear model, we built a more complicated regression model, in which the multiple correlation coefficient is0.865and the coefficient of determination is0.749.NJU-CAQPS (air quality forecast system developed by Nanjing University Atmospheric Physics and Environment Group) coupled with SBDART (Santa Barbara DISORT Atmospheric Radiative Transfer) was used to simulate the distribution and variation of particles mass concentration and meteorological elements. During daytime, there was an obviously heat increase in boundary layer due to the short wave radiative effect of aerosols, which strengthened urban heat island circulation and decreased particles mass concentration and lead to higher heating rate in the upper layers and lower heating rate in the lower. At night, the effect of aerosols were to warm up the lower boundary layer. |
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