南京主要大气污染物季节变化及相关气象分析

为研究南京主要大气复合污染物PM_2.5、PM₁₀和O₃四季变化特征及其气象影响因子，利用2013年1月～2015年2月国控点环境监测数据对浓度特征进行统计分析，再利用WRF模式模拟的精细大气边界层气象场，分析气象要素与各污染物的相关性，并建立统计模型.结果表明：PM₁₀、PM_2.5冬高夏低，冬季日均值分别为160.6μg/m³和98.0μg/m³；日变化特征四季基本一致，但秋冬季最强，夏季最弱，且冬季上午峰值比其余三季延后1～2h.各季大气可吸入颗粒物中细粒子占主导，PM_2.5/PM₁₀年均值为0.59；首要污染物为PM_2.5、PM₁₀、O₃的年频率分别为51.5%、26.6%和13.5%，PM_2.5主导四季AQI的变化，尤其是在重污染的情况下，首要污染物为PM_2.5占96%.O₃浓度春末夏初高、秋末冬初低，日变化为单峰式；O₃与边界层高度呈显著正相关，四季相关系数分别为0.500、0.572、0.326、0.323.四季PM₁₀、PM_2.5、O₃_8h_max日值逐步回归方程拟合度为40%～65%.

Seasonal variations in major air pollutants in Nanjing and their meteorological correlation analyses

In order to study the seasonal variations of major air combined pollutants PM_2.5, 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 PM_2.5 and PM₁₀ shifted between wintertime high and summertime low levels in Nanjing with the peaks of daily PM_2.5 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 PM_2.5 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 PM_2.5/PM₁₀ reaching 0.59. The annual frequencies of PM_2.5, 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 PM_2.5 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 PM_2.5, PM₁₀ and O₃_8h_max ranged reasonably over 40%~65% in four seasons.