极端气温事件下空气污染物浓度变化特征分析方法研究  

Analysis on Variation Characteristics of Air Pollutant Concentration under Extreme Temperature

作　　者：闫永刚 姚彩霞[1] 杨帆 闫锦涛 Yan Yonggang;Yao Caixia;Yang Fan;Yan Jintao(Shanxi Meteorological Station, Taiyuan 030006, China;China Agricultural University, Beijing 100193, China)

机构地区：[1]山西省气象台,山西太原030006 [2]中国农业大学,北京100193

出　　处：《环境科学与管理》2022年第2期135-138,共4页Environmental Science and Management

摘　　要：为精准把握极端气温与污染物浓度之间的关系,以山西省为例,提出极端气温事件下空气污染物浓度变化特征分析方法。选取多个气象站,确定数据来源,利用Apriori数据挖掘算法获取气象数据;获取气象要素时间序列和自然序列存在的关联系数,得出气温变化是否明显,计算气象倾斜率,表明污染物浓度变化的态势。实验分析结果表明:山西省近几十年来,随暖夜与暖昼现象的增多,SO_(2)与PM_(10)的浓度降低,但在冷昼与冷夜的多发地区,SO_(2)与PM_(10)的浓度相对升高,而NO_(2)的变化特征并不受极端气温影响。This study takes Shanxi Province as an example to analyze the relationship between extreme temperature and pollutant concentration.It proposed an analysis method for the variation characteristics of air pollutant concentration under extreme temperature events.It selected multiple meteorological stations,determined the data source,and obtained meteorological data by using Apriori data mining algorithm.The correlation coefficient between the time series of meteorological elements and the natural series were obtained to determine whether the temperature change is obvious.The meteorological tilt rate is calculated to study the trend of pollutant concentration change.The experimental results show that in recent decades,with the increase of warm night and warm day,the concentrations of SO_(2)and PM_(10)decrease.But in the areas with frequent cold day and cold night,the concentrations of SO_(2)and PM_(10)increase relatively,while the variation characteristics of NO_(2)are not affected by extreme temperature.

关 键 词：极端气温事件 空气污染物 浓度变化特征 数据挖掘 

分 类 号：X67[环境科学与工程]