Abstract: The analysis data include the PM₁₀ (particulate matter with aero-dynamic diameter smaller than 10 μm) mass concentration, AWS (automatic weather station) data and radio-sounding data at Beijing Observatory in November 2007, to find out the relationship between PM₁₀ mass concentration and bulk Richardson number. The result got by statistical analysis software SPSS 15. 0 shows that there is strong correlation between PM₁₀ mass concentration and surface meteorological factors, as well as bulk Richardson number in atmospheric stable stratification condition in Beijing area. The linear correlation between PM₁₀ mass concentration and wind speed ( r= - 0. 65, α= 0. 01) is significant, and the same as that PM₁₀ mass concentration and relative humidity (r = 0. 69, α= 0. 01). There is a nonlinear relationship like logarithm ( R = 0. 42) between PM₁₀ mass concentration and bulk Richardson number of ground to 450m layer. Besides, some independent sample tests also suggest that the regression model simulates the PM₁₀ mass concentration well when using the radio-sounding data.

Key words: Beijing, PM₁₀ mass concentration, bulk Richardson number, nonlinear relationship, logarithmic form

摘要： 为了研究总体理查逊数对可吸入颗粒物 PM₁₀ ( particulate matter with aero-dynamic diameter smaller than 10 μm) 质量浓度的影响, 对2007年11月北京南郊观象台的PM₁₀质量浓度资料、地面气象自动站资料和常规无线电探空资料进行了分析。统计分析软件采用 SPSS15.0( Statistical Package for Social Sciences 15. 0) 。分析结果表明,在北京地区以稳定层结为主的条件下, PM₁₀质量浓度与地面气象要素和总体理查逊数存在很好的规律性。PM₁₀质量浓度与风速和相对湿度显著相关, 相关系数分别为 - 0. 65 和 0. 69, 通过 α= 0. 01 显著性检验; PM₁₀质量浓度与地面至450m层的总体理查逊数存在显著的对数形式非线性关系, 决定系数 R2= 0.42。非线性回归方程的独立样本预测检验显示回归模型可以用于根据无线电探空资料对PM₁₀质量浓度进行预测。

关键词: 北京, PM₁₀质量浓度, 总体理查逊数, 非线性关系, 对数形式