1. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing 210044, China;
2. Jiangsu Provincial Environmental Monitoring Center, Nanjing 210029, China;
3. School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, China
In order to study the seasonal variations of major air combined pollutants PM2.5, PM10 and O3 and their influencing factors of meteorology in Nanjing, the major air combined pollutants were seasonally characterized, and the correlations between meteorological factors and air pollutant concentrations were statistically analyzed to develop a statistical model of stepwise regression fitting by using the environmental monitoring data from January 2013 to February 2015 and the fine meteorological fields in the boundary layer produced by the high resolution WRF modeling. The seasonal averages of PM2.5 and PM10 shifted between wintertime high and summertime low levels in Nanjing with the peaks of daily PM2.5 and PM10 up to 160.6μg/m3 and 98.0μg/m3 in winter, and their diurnal changes were distinct from autumn to winter and weak in summer with the similar patterns over four seasons. The daytime peaks of diurnal PM2.5 and PM10 levels in winter delayed 1~2 hours comparing to other three seasons. Fine particles dominated atmospheric particles in all seasons with the annual mean ratio of PM2.5/PM10 reaching 0.59. The annual frequencies of PM2.5, PM10 and O3 being the major pollutants determining the AQI changes were respectively 51.5%, 26.6% and 13.5% in Nanjing, especially the major air pollutant contribution of PM2.5 to heavy haze pollution periods exceeding 96% in Nanjing. The surface levels of O3 oscillated seasonally between a peak in late spring and early summer and a bottom in late autumn and early winter with a unimodal pattern. The surface levels of O3 were positively related to the boundary layer height with the correlation coefficients of 0.500, 0.572, 0.326, 0.323 respectively. The fitting goodness of stepwise regressions for the daily concentrations of PM2.5, PM10 and O3_8h_max ranged reasonably over 40%~65% in four seasons.
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