摘要
为探究空气污染与气象条件的关系,以及基于气象条件的空气污染等级报方法,以开远市为例,利用相关性分析、数值统计预报方法及《空气污染扩散气象条件等级》标准进行了分析。结果表明:(1)开远空气污染具有“冬春高夏秋低”的鲜明特点,影响污染物主要有SO_(2)、PM_(10)、O_(3)、PM_(2.5),其中O_(3)为首要污染物;(2)影响开远市空气质量的气象条件主要有降水、相对湿度和风向。夏季降水的湿清除作用对改善当地空气质量有重要作用,尤其是在调节降低SO_(2)、PM_(10)、CO、PM_(2.5)浓度中作用显著。相对湿度与空气质量呈负相关,影响开远市空气污染扩散的风向主要为南向风;(3)根据《空气污染扩散气象条件等级》标准建立的基于气象条件的空气污染等级预报方程,比数值统计预报方法建立的AQI逐步回归预报方程具有更好的适用性,预测AQI等级对比实测AQI预报等级正确率达79.4%,对开远市空气污染防治具有一定的科学指导意义。
In order to explore the relationship between air pollution and meteorological conditions,as well as the reporting method of air pollution level based on meteorological conditions,Kaiyuan City was taken as an example,analysis was conducted,using correlation analysis,numerical statistics and forecasting methods and the standard of Meteorological Condition level of Air Pollution Difusion.The results showed that:(1)The air pollution in Kaiyuan is characterized by"high in winter and spring,low in summer and autumn".The main pollutants affecting the air pollution are SO_(2),PM_(10),O_(2),and PM_(2.5),of which O,is the primary pollutant;(2)The meteorological conditions affecting the air quality of Kaiyuan City mainly include precipitation,relative humidity and wind direction.The wet removal of summer precipitation plays an important role in improving local air quality,especially in regulating and reducing SO_(2),PM_(10),CO and PM_(2.5) concentrations.The relative humidity is negatively correlated with the air quality,and the wind direction that affects the air pollution diffusion in Kaiyuan City is mainly southward wind;(3)The prediction equation of air pollution level based on meteorological conditions established according to the Standard of Meteorological Conditions for Air Pollution Diffusion is more applicable than the AQI stepwise regression prediction equation established by numerical statistical prediction method.The accuracy rate of the predicted AQI level compared with the measured AQI prediction level is 79.4%,which has certain scientific significance for air pollution prevention and control in Kaiyuan City.
作者
罗小杰
王爱玲
熊丽萍
LUO Xiao-jie;WANG Ai-ling;XIONG Li-ping(Yunnan Honghe Prefecture Meteorological Bureau,Mengzi,Yunnan 661100,China;Yunnan Kaiyuan Meteorological Bureau,Kaiyuan,Yunnan 661600,China)
出处
《四川环境》
2023年第5期54-60,共7页
Sichuan Environment
基金
云南省气象局科研项目(YZ202219)资助。
关键词
气象条件
空气质量
预报方法
Meteorological conditions
air quality
prediction method