The study on separation of meteorological information and emission information of pollution sources in air pollu⁃tant time series is of some important significance to the evaluation of air pollution control measures. Based on the daily air pollution index ( API) and simultaneous surface meteorological observation data during 2001-2010 in Beijing, Tianjin and Shijiazhuang, the Kolmogorov⁃Zurbenko ( KZ) wave filter method was used to break the API time series into short⁃term, seasonal and long⁃term components, and then the stepwise regression was used to set up API baseline and short⁃term com⁃ponents separately and establish linear regression models for meteorological variables of corresponding scales. The residual differences between the baseline and short⁃term components were KZ filtered and series reestablished. And eventually an API time series free of meteorological impacts was worked out. Results of the study show that the long⁃term component of API shows a downward trend in all the three cities from 2002-2009, which may be attributed to changes in emission with the influence of meteorology removed, namely, meteorological adjustment. Comparison of the meteorologicaly adjusted long⁃term trends with unadjusted ones show that unfavorable meteorological conditions often lead to increase by 1-13 in the long⁃term API in the three cities, whereas favorable meteorological conditions account for reduction by 2-6 in the compo⁃nent.%空气污染时间序列中气象信息与污染源排放信息的分离研究对大气污染控制措施效果评估具有重要意义。依据北京市、天津市和石家庄市2001—2010年期间的空气污染指数（ API）逐日数据和同期地面气象观测资料，利用KZ滤波将API时间序列分解为短期分量、季节分量和长期分量，采用逐步回归方法分别建立API基线分量和短期分量与相应尺度气象要素的线性回归模型，通过对残差进行滤波和序列重建，最终得到去除气象影响的API时间序列。分析结果表明：由于污染源排放的变化，京津石3市API长期分量在2002—2009年期间总体呈现下降趋势；不利的气象条件致使京津石3市API长期分量增加1～13，而在气象条件对空气质量改善呈现促进作用的情况下API长期分量减少2～6。
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