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北京地区2019年2~3月供暖结束前后两次污染过程特征分析
摘要点击 3129  全文点击 868  投稿时间:2020-08-17  修订日期:2020-10-26
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中文关键词  PM2.5污染  气象条件  二次生成  同化模拟  城市供暖
英文关键词  PM2.5 pollution  meteorological condition  secondary generation  assimilation simulation  city heating
作者单位E-mail
尹晓梅 京津冀环境气象预报预警中心, 北京 100089 yinxiaomei2010@163.com 
蒲维维 京津冀环境气象预报预警中心, 北京 100089 wwpu@ium.cn 
王继康 国家气象中心, 北京 100081  
刘湘雪 京津冀环境气象预报预警中心, 北京 100089  
乔林 京津冀环境气象预报预警中心, 北京 100089  
中文摘要
      以2019年2~3月北京两次污染过程为例,针对气象要素及污染物浓度进行特征分析,利用后向轨迹及WRF-CAMx模式,分析供暖结束前后的污染物演变规律,并探讨气象条件、区域输送及二次转化等对污染过程的影响.结果表明,2月21~24日(过程1)和3月18~20日(过程2)平均ρ(PM2.5)差异不大,分别为100.1 μg·m-3和97.2 μg·m-3,但过程1平均峰值偏高、日变化明显、过程发展迅速和有两个峰值阶段,且为区域性污染,而过程2更倾向于北京局地污染.两次过程逐时ρ(SO2)均不超16 μg·m-3,供暖燃煤治理效果显著,但过程1的SO2存在夜间次峰值,体现供暖排放影响.过程1的ρ(CO)较高,尤其是2月21~22日前后ρ(CO)/ρ(SO2)升高,且区域中南部城市及北京南部背景站污染高于城区,表明过程1扩散条件不利,且第一个峰值主要受区域输送影响.过程2的ρ(PM2.5)/ρ(CO)偏高,表明二次生成PM2.5占比略大;ρ(NO2)/ρ(CO)、ρ(SO2)/ρ(CO)和ρ(SO42-)/ρ(PM2.5)偏大,SOR与过程1持平,表明过程1更有利于气体相态转化,过程2受工业燃煤影响更大.但将过程1分阶段分析显示,过程1第二阶段与过程2的PM2.5二次生成指征相似,均高于过程1第一阶段,即过程1第二个峰值与过程2主要与本地排放和化学转化相关.WRF-CMAx对污染物演变趋势有较好的再现能力.同化试验对PM2.5趋势模拟显著提升,提高了与观测的相关性,但模拟值偏低;对NO2的模拟2月偏低、3月偏高,对SO2模拟明显偏高有一定纠正;此外,过程2中北京污染物浓度对河北的敏感性相对过程1偏低,即过程1受区域输送影响更大.模式对污染暴发性增长的模拟亟待提升,污染物种类对减排的响应及大气氧化剂和气溶胶性质相关的反馈等可能是影响模拟效果的重要原因,需进一步研究.
英文摘要
      The characteristics of meteorological conditions and pollutant concentrations were analyzed based on two pollution episodes before and after city heating in Beijing during February to March of 2019. The backward trajectory and WRF-CAMx models were used to analyze the evolution of pollutants before and after city heating, and the influences of meteorological conditions, regional transport, and secondary transformation on the episodes were discussed. There was little difference in the average ρ(PM2.5) between February 21-24 (episode 1) and March 18-20 (episode 2), with concentrations of 100.1 μg·m-3 and 97.2 μg·m-3, respectively. However, compared with that of episode 2, in episode 1 the average peak value was higher with two peak stages, the diurnal variation was clearer, and the process developed much more rapidly. Moreover, episode 1 was regional pollution, while episode 2 was more related to local pollution in Beijing. The SO2 concentrations in both episodes were not higher than 16 μg·m-3, thereby indicating the effectiveness of coal-burning treatment and other measures. In addition, two peaks occurred in the diurnal fluctuation of SO2 in episode 1, whereas only one peak occurred for episode 2. In episode 1, the CO concentration was high and the ratio of ρ(CO)/ρ(SO2) increased around February 22-23 (phase 1); moreover, the pollutant concentrations in the central and southern areas of the Beijing-Tianjin-Hebei region and those in the background sites located in the southern part of the Beijing plain were higher than those in the urban area, thereby indicating that the diffusion conditions of episode 1 were unfavorable and the first PM2.5 peak was mainly affected by regional transport. A high ratio of ρ(PM2.5)/ρ(CO) in episode 2 suggested a slightly larger proportion of secondary generation for PM2.5, whereas higher ratios of ρ(NO2)/ρ(CO), ρ(SO2)/ρ(CO), and ρ(SO42-)/ρ(PM2.5) in episode 2 and the similar SOR value to that of episode 1 demonstrated that episode 1 was more advantageous for gas phase transformation and episode 2 was more affected by the coal industry. Phased analysis of episode 1 showed that the indicators of second generation for PM2.5 in phase 2 (around February 23-24) of episode 1 and episode 2 were similar, and both were higher than that in phase 1 of episode 1, which implied that the second PM2.5 peaks of episode 1 and episode 2 were mainly related to local emissions and chemical conversion. Both WRF-CAMx with and without assimilation experiments could better reproduce the temporal variation in pollutants, and the correlation between the simulation and observations increased but with lower values after assimilation. The model performance for the PM2.5 trend simulation significantly increased with data assimilation, and the simulated lower NO2 in February and higher NO2 in March as well as the overestimated SO2 were also improved. In addition, the pollutant concentration simulation in Beijing was more sensitive to that of Hebei in episode 1, which suggested that episode 1 was more affected by regional transport. The simulation ability for the rapid growth of pollutants needs to be promoted, and the response of pollutant types to emission reduction and the feedback related to the atmospheric oxidant and aerosol properties may be important for the simulation effect, which all require further study.

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