中文摘要：

利用2005年9月-2006年9月北京市大气颗粒物分级（不同粒径）监测资料和同期分时段气象观测数据，采用非参数分析（Spearman秩相关系数）法对北京市3种粒径大气颗粒物在不同季节的浓度水平与气象因素的影响进行了研究．结果表明：不同季节影响颗粒物质量浓度的气象因素各不相同；春季P（PM2.5），P（PM2.5-10）和P（PM10）都与气压呈显著负相关；夏季颗粒物质量浓度受降水影响很大；秋、冬季P（PM2.5）和P（PM10）均与日照时数呈显著负相关；冬季P（PM2.5），ρ（PM2.5-10）和ρ（PM10）均与平均风速呈显著负相关，与气温、相对湿度呈显著正相关．细粒子和粗粒子质量浓度对气象因素变化的响应程度也有较大区别．春、夏季地面平均风速对粗粒子质量浓度的影响比细粒子显著，ρ（PM2.5）／ρ（PM10）随风速增加而增大；秋季日照时数对细粒子质量浓度的影响比粗粒子更显著，P（PM2.5）／ρ（PM10）随日照时数增加而减小；冬季相对湿度对粗粒子质量浓度的影响比细粒子显著，ρ（PM2.5）/ρ（PM10）随相对湿度增加而减小．

英文摘要：

Based on monitoring data of particulate matter （PM） and meteorological data from September 2005 to September 2006 in Beijing, the influence of meteorological conditions on concentration levels of PM with different size ranges was investigated for four seasons using nonparameter statistical analysis such as Spearman correlation matrix. The results showed that PM concentrations were significantly correlated with one or more meteorological parameters in different seasons. PM2.5 , PM2.5-10 and PM10 had strongly negative correlation with surface atmospheric pressure in spring. PM concentrations were influenced greatly by rainfall in summer. PM2.5 and PM10 had significantly negative correlation with solar radiation in autumn and winter. The concentrations of PM with three size ranges in winter were significantly and negatively correlated with wind speed, but positively correlated with ambient temperature as well as relative humidity. The concentrations of both fine particles （PM2.5 ） and coarse particles （PM2.5-10） were influenced by meteorological conditions, but to different extents. The concentrations of coarse particles in dusty spring and humid summer were more significantly correlated with wind speed than those of fine particles, so the PM2 5/PM10 increased with stronger wind. In autumn, the concentrations of fine particles were more significantly correlated with solar radiation than those of coarse particles, so the PM2.5/PM10 reduced when solar radiation lasted longer. The coneentrations of coarse particles in winter were more significantly correlated with humidity than fine particles. With increasing humidity, the PM2.5/PM10 got lower.