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乐山市2016年冬季颗粒物重污染过程与输送路径及潜在源区
引用本文:龙启超,陈军辉,廖婷婷,桂柯,何敏,冯小琼,刘思宇.乐山市2016年冬季颗粒物重污染过程与输送路径及潜在源区[J].环境科学研究,2019,32(2):263-272.
作者姓名:龙启超  陈军辉  廖婷婷  桂柯  何敏  冯小琼  刘思宇
作者单位:四川省环保科技工程有限责任公司, 四川 成都 610041;四川省环境保护科学研究院, 四川 成都 610041;四川省环境保护科学研究院,四川 成都,610041;成都信息工程大学大气科学学院, 高原大气与环境四川省重点实验室, 四川 成都 610225;中国气象科学研究院大气成分研究所,北京,100081
基金项目:四川省科技计划项目(No.2017SZ0169)
摘    要:对乐山市2016年12月—2017年2月的大气污染特征及气象条件进行研究分析,并结合HYSPLIT(后向轨迹模式),用聚类方法、PSCF(潜在源贡献因子法)、CWT(浓度权重轨迹分析法)分别模拟了研究期间PM2.5的主要潜在源区.结果表明:研究期间,乐山市以PM2.5污染为主.因风速低、无降水、相对湿度高、边界层高度降低等原因,使乐山市发生了一次持续时间较长的重污染过程(2017年1月1—7日),该过程二次污染物累积特征较为明显;春节期间,因烟花爆竹集中燃放产生的大量污染物使乐山市出现了一次严重污染(2017年1月28日),ρ(PM2.5)日均值达358 μg/m3.乐山市复杂的地形引起的热力差异有利于局地环流的生成与发展,山谷风的存在可能是造成夜间乐山市郊区站点ρ(PM2.5)高于城区站点的主要原因.结合后向轨迹与ρ(PM2.5)日均值分析发现,来自盆地内部的气流(占比为28.57%)对乐山市空气质量产生的影响最大.乐山市东部边界附近、宜宾市西北部、自贡市南部等地对乐山市PM2.5的潜在源贡献(WPSCF)在0.96以上,说明这些地区是研究期间影响乐山市ρ(PM2.5)的重要潜在源区,模型的模拟结果与风向、风速、ρ(PM2.5)监测值插值结果相符.研究显示,乐山市大气污染过程除了与在不利气象条件下污染物的累积有关外,区域污染物的输送贡献也不容忽视. 

关 键 词:大气污染特征  HYSPLIT模型  山谷风  后向轨迹  潜在源区
收稿时间:2018/4/1 0:00:00
修稿时间:2018/5/17 0:00:00

The Severe Pollution Process, Transport Pathways and Potential Sources of Particulate Matter during the Winter of 2016 in Leshan City
LONG Qichao,CHEN Junhui,LIAO Tingting,GUI Ke,HE Min,FENG Xiaoqiong and LIU Siyu.The Severe Pollution Process, Transport Pathways and Potential Sources of Particulate Matter during the Winter of 2016 in Leshan City[J].Research of Environmental Sciences,2019,32(2):263-272.
Authors:LONG Qichao  CHEN Junhui  LIAO Tingting  GUI Ke  HE Min  FENG Xiaoqiong and LIU Siyu
Institution:1.Sichuan Environmental Protection Technology Engineering Co., Ltd., Chengdu 610041, China2.Sichuan Academy of Environmental Sciences, Chengdu 610041, China3.Plateau Atmospheric and Environment Key Laboratory of Sichuan Province, College of Atmosphere Sciences, Chengdu University of Information Technology, Chengdu 610225, China4.Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Abstract:Pollution characteristics and meteorological parameters in Leshan City, China were analyzed from December 2016 to February 2017. Combined with the HYSPLIT model, the main potential sources of PM2.5 were simulated by adopting the clustering method, the Potential Source Contribution Function (PSCF) method and the Concentration Weighted Trajectory (CWT) method. The results showed that during the study period, the air pollution in Leshan City was dominated by fine particulate pollutants. Due to the unfavorable meteorological conditions (low wind speed, no precipitation, high relative humidity and the decreasing boundary layer height), a severe pollution process occurred in Leshan City for a long time (from January 1st 2017 to January 7th, 2017). It was obvious that the secondary pollutants were cumulated in this process. During the Spring Festival, lots of pollutants produced by the concentrated discharge of fireworks and firecrackers led to a serious pollution in Leshan (January 28th, 2017). The average daily concentration of PM2.5 was 358 μg/m3. The thermal difference caused by the complex topography of Leshan City was conducive to the generation and development of local circulation, while the existence of the valley breeze might be the main reason for the higher PM2.5 concentration in the suburban area than in the urban area at night. By combining the backward trajectories with the daily PM2.5 concentrations, it was found that the air flow from the interior of the basin (28.57%) had the greatest impact on the air quality of Leshan City. The WPSCF (weighted potential source contribution function) value was higher than 0.96 at the eastern boundary of Leshan City, in the northwest of Yibin City, and in the south of Zigong City, which indicated that these regions were the major potential sources of PM2.5 for Leshan City in the study period. The simulation results of the model were consistent with the interpolation results of the wind direction, wind speed and daily concentration of PM2.5. The study showed that the pollution process of Leshan City was related with the accumulation of pollutants under adverse meteorological conditions, but the contribution of regional pollutant transport could not be ignored. 
Keywords:pollution characteristics  HYSPLIT model  valley breeze  backward trajectories  potential sources
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