济南市采暖季污染指数构建及应用

Development and Application of Pollution Index during Heating Period in Ji’nan

作为东亚冬季气候系统的重要组成部分,西伯利亚高压的存在强烈的影响亚洲东部地区天气系统的变化,阿留申低压的强度和位置异常对北半球的天气、气候异常有重要的影响,它们都是影响中国东部地区空气质量的重要的天气系统,其强度和位置变化,影响中国东部地区大尺度污染物扩散条件,本地水平风速、行星边界层高度、相对湿度等影响局地空气中污染物的生成、累积、传输、扩散、沉降等过程。基于2013—2019年采暖季(11月至次年3月)气象数据及济南市空气质量指数(AQI)数据,通过研究西伯利亚高压、阿留申低压、南部气压距平中心气压值强度的变化,以及本地2 m相对湿度、10 m风速、行星边界层高度等气象因素,结合AQI数据,确定各气象因子阈值范围及权重系数,通过权重求和,建立基于经验预报的济南市采暖季污染指数(PI),两者相关系数达到0.579,为显著相关,随着污染加重,污染指数相应增大,该指数能够反映空气质量变化趋势。以2020年12月出现的两次重污染过程为例,分析不同污染阶段污染指数变化,评估所建公式对济南市空气质量的预报能力,结果表明:12月7—13日重污染过程中,污染指数能够较好的预测本次污染过程的累积及消散过程,11日由于GFS资料中对相对湿度的预报偏差导致预测与实际偏差较大;25—31日污染过程中,污染指数与AQI变化完全一致,预报效果好。污染指数能够较好的反映污染过程的不同阶段,具有较好的提前预报能力,对空气质量预报尤其是重污染期间预报具有较好的指导意义。

As important parts of the winter climate system in East Asia,Siberian high strongly affects the changes of weather system in East Asia,and Aleutian low with intensity and position anomalies has a key impact on the weather and climate anomalies in the Northern Hemisphere.They are both crucial weather systems that affect the air quality in eastern China.Their intensity and position changes affect the diffusion conditions of large-scale pollutants in eastern China,and local horizontal wind speed,planetary boundary layer height and relative humidity influence the formation,accumulation,transport,diffusion and deposition of pollutants in the local air.In this study,based on the meteorological data during heating season(November to March of the next year)and the air quality index(AQI)of Ji’nan from 2013 to 2019,the threshold range and weight coefficient of each meteorological factor were determined by investigating the intensity changes in Siberian high,Aleutian low and central pressure of southern barometric anomaly,local 2-m relative humidity,10-m wind speed and planetary boundary layer height in combination with AQI.Additionally,through weight summation,the pollution index(PI)during heating season of Ji’nan was established based on empirical prediction.Their correlation coefficient reached 0.579,which was a significant correlation.With pollution aggravation,PI increased accordingly,which could reflect the changing trend of air quality.With two heavy pollution processes in December 2020 as examples,the changes in PI at different pollution stages were analyzed,and the forecasting capability of the established formula for air quality in Ji’nan was evaluated.The results showed that during the heavy pollution from December 7 to 13,PI could well forecast the accumulation and dissipation processes.On the 11th,due to the forecast deviation of relative humidity in GFS data,there was a large deviation between the forecast and actual data.During the pollution from 25th to 31st,the changes in PI and AQI were identical,with good forecast effect.Therefore,PI can well reflect different stages of the pollution process,and has a good ability to forecast in advance,which has good guiding significance for air quality forecast,especially in heavy pollution period.