南宁地区秋季一次连续灰霾过程的污染特征及成因分析

Characteristics and formation mechanism from a serious haze event in autumn of Nanning

以南宁市秋季某次连续灰霾过程为例,利用单站地面激光雷达数据,结合地面气溶胶观测数据、气象资料和HYSPLIT轨迹模式分析此次灰霾的边界层高度、气溶胶垂直分布特征及成因。南宁市此次灰霾过程PM2.5日均浓度值连续9天超标。灰霾持续期间,边界层高度波动范围0.4～0.8km,不利于污染物的扩散。地面监测的颗粒物浓度与激光雷达反演的边界层高度呈负相关关系,12：00—17：00时段内,地面PM2.5与边界层高度相关系数r=-0.671,激光雷达反演的边界层高度较好地反映了颗粒物的扩散条件。PM2.5浓度与近地面消光系数呈正相关关系,12：00—17：00时段PM2.5浓度与近地面消光系数相关系数r=0.986,说明激光雷达所反演的消光系数可以较好地反映PM2.5污染程度。此次连续灰霾期间最强消光系数出现在下午14：00,为0.7km-1,高度在2.0km左右;其次是中午12：00,为0.4km-1,高度在1.0～1.2km;消光系数较弱的时段为下午16：00,峰值约为0.25km-1,高度在1.5～2.0km。结合气象条件和HYSPLIT轨迹模式分析,南宁市此次连续灰霾天气是由区域传输叠加本地污染源排放,加上不良的气象条件共同影响造成的。

A serious haze event in Nanning was analyzed.Planetary Boundary Layer （ PBL） and vertical distribu-tion of the extinction coefficient during the haze period are performed by MPL-4B-IDS -532.Based on ground aerosol measurements, meteorological data and HYSPLIT trajectory model analysis, the characteristics and forma-tion mechanism of this pollution episode were analyzed.Daily average concentration of PM2.5 exceeded the stand-ard in nine consecutive days.The PBL performed by lidar was negatively corrected with the ground particulate matter measurement.Correlation coefficient between PBL and PM2.5 was r=-0.671 during 12：00-17：00 of day-time, which indicated that the PBL could reflect the diffusion conditions of PM better.The extinction coefficient was positively corrected with ground PM2.5, with correlation r=0.986 during 12：00-17：00 of daytime,suggesting that extinction coefficient could reflect the pollution level of PM2.5.During the period of haze, the most strong ex-tinction coefficient occurred at 14：00 PM, followed by the extinction coefficient at 12：00 PM, with extinction co-efficient 0.7 km-1 at the height of 2.0 km and 0.4 km-1 at the height of 1.0-1.2 km, respectively.Weaker ex-tinction coefficient was at 16：00 PM, about 0.25 km-1 at a height of 1.5-2.0 km.According to meteorological conditions and the HYSPLIT trajectory model analysis, the continuous haze in Nanning was caused by local pollu-tion emissions coupled with regional transport, as well as the poor weather conditions.