摘要
利用气象观测资料、南昌市PM2.5资料并结合HYSPLIT轨迹模型,对2013年12月4—10日江西省中北部地区一次典型、持续性灰霾天气过程进行了分析,综合讨论了灰霾天气发生过程中的天气形势、风速、能见度、低层相对湿度、层结稳定度等气象要素和物理量特征,分析了PM2.5浓度等环境要素的变化特征以及导致此次灰霾天气的污染源。结果表明:1)此次灰霾天气过程的500 h Pa高度层平均环流形势为"两槽一脊"型,江西省受西北偏西气流控制;弱冷空气、静稳天气是灰霾天气得以形成和发展的主要天气背景场。2)较小的近地面风速和较大的相对湿度以及中低层逆温层的存在均是此次灰霾形成和维持的重要条件,且此次灰霾天气过程中能见度分别与近地面风速和相对湿度、PM2.5浓度呈正、反相位关系,湿度升高、污染物浓度较高、风速较低的气象条件容易形成低能见度。3)灰霾天气气溶胶颗粒物浓度的升高可能是由本地污染源和甘肃省、内蒙古自治区一带以及四川省东南部污染源共同造成的;前期整体出现在2 km以下,随着时间的推移,浓度升高。
A long-lasting haze event in Jiangxi dur ing 4-10 December 2013 was analyzed by using meteorological observational data,air quality data and HYSPLIT trajectory model. The meteorological factors including the weather situation,wind speed,visibility,relative humidity as well as stratification stability,the PM2.5concentrations and the pollution sources leading to the haze were comprehensively studied in this paper. The results showed that：1） The 500 h Pa circulation pattern was two troughs-one ridge and in which Jiangxi was controlled by northwest airflow. The weak cold air and statically stable weather was the main weather background field to the formation and development of the haze. 2） Low wind speed,high humidity and inversion layer at mid-low lever,were important to the formation and maintenance of the sever haze event. During the haze,visibility had a negative relationship with PM2.5and relative humidity while it had a positive relationship with wind speed and the decrease of visibility was often associated with the increase of humidity,the higher concentration of pollutions and low wind speed. 3） Local pollution and the pollutions from Gansu,Inner Mongolia as well as the southeast part of Sichuan contributed to the increase of concentrations of aerosol particles in north-central Jiangxi. Pollutions mainly occurred below 2.0 km in the former stage of the haze,and the height increased as the time went on.
出处
《气象与减灾研究》
2015年第2期40-46,共7页
Meteorology and Disaster Reduction Research
基金
国家自然科学基金项目(编号:41265003)
关键词
霾
天气背景
影响因子
轨迹模拟
north-central Jiang
haze
influencing factors
trajectory model
