摘要
对防城港市影响最大的首要空气污染物为PM_(2.5)和O_(3),空气污染日主要集中在秋冬季。空气污染按500 hPa环流形势可分为西北气流型、偏西气流型及西南气流型;按地面气压场可分为冷高压脊型、均压型、高压后部低压前部型。在无境外输入的情况下,PM_(2.5)产生在风速小、气温较低、能见度小、湿度较大并且无降雨或降雨不明显的天气环境里,而O_(3)产生在高温、低湿、日照充足、风速较大和能见度好的天气环境里。在垂直运动方面,中低层的下沉气流利于空气污染物累积。在温度层结分布方面,700~850 hPa的低层存在的逆温层对PM_(2.5)浓度增加非常重要,近地面的逆温层对PM_(2.5)浓度增加的作用要比低层弱,而近地面的逆温层对O_(3)浓度的增加非常重要,但是低层的逆温却不重要。
PM_(2.5)and O_(3)are the most important air pollutants in Fangchenggang City,and the air pollution days are mainly occurred in autumn and winter.According to 500 hPa circulation pattern,air pollution can be divided into northwest air flow pattern,westerly air flow pattern and southwest air flow pattern,and according to the surface pressure field,it can be divided into the cold high-pressure ridge type,uniform pressure field type,high pressure rear and low pressure front type.In the absence of overseas input,PM_(2.5)is produced in the weather environment with low wind speed,low temperature,low visibility,high humidity and no rainfall or no obvious rainfall,while O_(3)is produced in the weather environment with high temperature,low humidity,sufficient sunshine,high wind speed and good visibility.In terms of vertical movement,the downdraft in the middle and low levels is conducive to the accumulation of air pollutants.In terms of temperature stratification distribution,the inversion layer at 700~850 hPa is very important for the increase of PM_(2.5)concentration.The effect of inversion layer near the ground on the increase of PM_(2.5)concentration is weaker than that of the low layer.The inversion layer near the ground is very important for the increase of O_(3)concentration,but the inversion layer at the low layer is not important.
作者
林文桦
赵胜男
陈绍河
黄滢
LIN Wenhua;ZHAO Shengnan;CHEN Shaohe;HUANG Ying(Fangchenggang Meteorological Bureau of Guangxi Zhuang Autonormous Region,Fangchenggang 538001,China)
出处
《中低纬山地气象》
2022年第3期108-113,共6页
Mid-low Latitude Mountain Meteorology
基金
广西区气象局青年人才培养项目(桂气科[2022]QN02):防城港近地面臭氧浓度与气象条件关系研究。
关键词
空气污染
气象分析
天气分型
相关系数
air pollution
meteorological analysis
weather typing
correlation coefficient
