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北京市空气污染与气象条件的关系及其预报 被引量:2

Study on the relationship between air pollution and meteorological conditions in Beijing and their forecasting
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摘要 利用北京市2015-2017年逐日、逐小时w(PM2.5)、w(SO2)和w(O3)资料,及同期NCEP/NCAR的高分辨率全球预报系统数值预报产品,计算了相关空气污染气象参数,研究了北京市空气污染物质量浓度与气象条件的关系.采用逐步回归方法,建立了北京市空气污染物w(PM2.5)、w(SO2)和w(O3)的预报方程,并对预报结果进行了检验.结果表明,稳定能量和涡度与w(PM2.5)、w(SO2)以正相关为主,与w(O3)以负相关为主.低层平均风速和边界层厚度与w(PM2.5)、w(SO2)以负相关为主,与w(O3)以正相关为主.地面露点温度与w(PM2.5)、w(SO2)和w(O3)以正相关为主;在优选空气污染气象参数的基础上,利用逐小时空气污染物质量浓度资料和逐步回归方法,筛选了最佳预报因子,建立了北京市逐3 h的0~72 h短期精细化空气污染物质量浓度预报模型,能够拟合w(PM2.5)、w(SO2)和w(O3)随边界层气象条件的变化趋势. w(PM2.5),w(SO2)and w(O3)on day-by-day and hour-by-hour bases in Beijing from 2015 to 2017 were used,and also the high spatial resolution data of the same period from the National Center for Environmental Prediction/National Center for Atmospheric Research global forecast system numerical forecast products,and the related meteorological parameters of air pollution were calculated.The relationship between air pollutant mass concentrations and meteorological conditions in Beijing was studied,a stepwise regression method was used to establish the prediction equations for the air pollutant w(PM2.5),w(SO2),w(O3)in Beijing and the prediction results were tested.The research results showed that the stable energy and vorticity were mainly positively correlated with w(PM2.5)and w(SO2),while negatively correlated with w(O3).The lower average wind speed and boundary layer thickness were mainly negatively correlated with w(PM2.5)and w(SO2),and mostly positively correlation with w(O3).There was a positive correlation between the dew point temperature and the mass concentration of w(PM2.5),w(SO2)and w(O3).Based on the optimization of the meteorological parameters of air pollution and via the hourly air pollutant mass concentration data and stepwise regression methods,the best predictors were selected,and a three-hour,0-72 hour short-term refined air pollutant mass concentration forecast model was established for Beijing.It can fit the trend that w(PM2.5),w(SO2)and w(O3)with the change of boundary layer meteorological conditions.
作者 尚子溦 康延臻 杜晖 王式功 Shang Zi-wei;Kang Yan-zhen;Du Hui;Wang Shi-gong(Meteorological Bureau of Lanzhou,Lanzhou 730000,China;College of Atmospheric Sciences,Lanzhou University,Lanzhou 730000,China;School of Atmospheric Sciences,Chengdu Information Engineering University,Chengdu 610225,China)
出处 《兰州大学学报(自然科学版)》 CAS CSCD 北大核心 2020年第3期380-387,共8页 Journal of Lanzhou University(Natural Sciences)
基金 国家自然科学基金项目(91644226) 国家基础科技条件平台建设项目(NCMI-SBS17-201807,NCMI-SJS15-201707) 兰州市科学技术局项目(2018-4-57)
关键词 空气污染 空气污染气象参数 逐步回归 预报方程 air pollution meteorological parameters of air pollution stepwise regression forecast equation
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