摘要
为探究相对湿度及大气气溶胶等影响因子对成都大气能见度的影响,并得出它们之间的函数关系。利用2014~2018年成都市气象观测站及环境监测站的能见度、相对湿度等气象因子及PM2.5、PM10等大气污染物数据进行变化趋势及相关性分析。结果表明:成都地区年平均能见度呈明显的上升趋势,其主要原因与PM2.5及PM10年平均浓度的持续性降低有关。能见度与相对湿度的线性相关系数最高,其次是PM2.5。当相对湿度小于85%时,能见度与PM2.5、PM10主要呈指数函数相关,当相对湿度大于85%时,能见度与PM2.5、PM10主要呈逆函数相关。随着相对湿度的增加,能见度受相对湿度的影响逐渐增大,能见度与PM2.5、PM10的非线性相关性逐渐减小。能见度与相对湿度主要呈三次函数关系,其次是幂函数,两者相关系数相差极小。运用相对湿度、PM2.5、PM10与能见度数据得出大气能见度的拟合方程,经验证,该方程能较好的反映成都地区能见度的变化规律,且冬季拟合度最高,春季其次,可进一步用于成都地区低能见度的预测研究。
In order to explore the influence of relative humidity and atmospheric aerosols on the visibility of Chengdu atmosphere,and obtain the functional relationship between them,In this paper,visibility,relative humidity and other meteorological factors as well as PM2.5,PM10 and other atmospheric pollutant data of meteorological observation stations and environmental monitoring stations in Chengdu city from 2014 to 2018 were used for variation trend and correlation analysis.The results showed that the annual average visibility in Chengdu area has a clear upward trend,the main reason of which was related to the continuous decrease of the average annual concentration of PM2.5 and PM10.Visibility has the highest linear correlation coefficient with relative humidity,followed by PM2.5.When relative humidity is less than 85%,visibility is mainly correlated with PM2.5 and PM10 in an exponential function.When relative humidity is greater than 85%,visibility is mainly correlated with PM2.5 and PM10 in an inverse function.With the increase of relative humidity,the visibility gradually increased under the influence of relative humidity,and the nonlinear correlation between visibility and PM2.5 and PM10 gradually decreases.Visibility and relative humidity are mainly in a cubic function relationship,followed by a power function.The correlation coefficient between the two is extremely small.Using the relative humidity,PM2.5,PM10 and visibility data to obtain a fitting equation for atmospheric visibility.It was proved that the equation could better reflect the change law of visibility in Chengdu,and the fitting degree was the highest in winter,followed by spring,which could be further used in the prediction of the low visibility in Chengdu area.
作者
苏靖晰
王永忠
王圣堂
陈红敏
SU Jing-xi;WANG Yong-zhong;WANG Sheng-tang;CHEN Hong-min(Civil Aviation Flight University of China,College of Air Traffic Management,Guanghan,Sichuan 318307,China)
出处
《四川环境》
2020年第6期66-73,共8页
Sichuan Environment
基金
中国民用航空飞行学院研究生科研创新项目(X2018-39)。
关键词
大气能见度
相对湿度
气溶胶粒子
大气污染物
非线性拟合
atmospheric visibility
relative humidity
aerosol particles
atmospheric pollutants
nonlinear fitting