• 姬艺珍,郭伟,胡正华,王雁,闫世明,葛艳斌,王小兰.基于积累速率的汾渭平原秋冬季PM2.5污染特征及影响因素分析[J].环境科学学报,2021,41(9):3673-3682

  • 基于积累速率的汾渭平原秋冬季PM2.5污染特征及影响因素分析
  • The pollution characteristics and influencing factors of PM2.5 in autumn and winter seasons in Fenwei Plain based on accumulation rate
  • 基金项目:山西省面上自然科学基金项目(No.201901D111465);山西省面上青年基金项目(No.201801D221333;201801D221334);山西省气象局重点项目(No.SXKZDDW20205203)
  • 作者
  • 单位
  • 姬艺珍
  • 1. 山西省气象科学研究所, 太原 030002;2. 南京信息工程大学气象灾害预报预警与评估协同创新中心, 应用气象学院, 南京 210044;3. 天水市气象局, 天水 741018
  • 郭伟
  • 山西省气象科学研究所, 太原 030002
  • 胡正华
  • 南京信息工程大学气象灾害预报预警与评估协同创新中心, 应用气象学院, 南京 210044
  • 王雁
  • 山西省气象科学研究所, 太原 030002
  • 闫世明
  • 山西省气象科学研究所, 太原 030002
  • 葛艳斌
  • 山西省气象局机关服务中心, 太原 030002
  • 王小兰
  • 山西省气象科学研究所, 太原 030002
  • 摘要:为研究汾渭平原各城市PM2.5污染特征及影响因素,利用2015—2019年汾渭平原11市秋冬季污染物逐时浓度,基于日变化分析构建了各城市慢速积累和快速积累的评价指标,量化了各城市的积累水平.结果表明:汾渭平原各城市PM2.5积累水平差异显著,积累速率最快的城市是宝鸡,最慢的是三门峡;快速积累阈值最高的是临汾,最低的是三门峡.结合各地积累速率值的分布特征,11地市的积累水平可分为较强(宝鸡、临汾、吕梁、晋中)、中等(咸阳、渭南、铜川、运城、洛阳)和较弱(西安、三门峡)3种.积累速率多随浓度的增高呈上升趋势,其中吕梁和临汾最为显著,而西安增幅最小.从年变化来看,各地快速积累占比从2017年或2018年开始减少,从月变化来看,12月和1月为快速积累出现最多的月份.二次污染物和区域传输对PM2.5积累速率均有影响,发生快速积累时,前体物SO2和NO2的浓度明显升高,二次反应显著;对临汾和西安的后向轨迹分析表明,西偏南方向气流的增加更易引起当地PM2.5的快速积累.
  • Abstract:To study the pollution characteristics and influencing factors of PM2.5 in Fenwei Plain, the hourly data of air quality in autumn and winter of 11 cities during the year of 2015—2019 were used to construct the evaluation indicators of slow and rapid accumulation, and quantify the accumulation level of each city. The results showed that there were significant differences in PM2.5 accumulation levels among cities in the Fenwei Plain. Baoji had the fastest accumulation rate, while Sanmenxia had the slowest rate. Linfen and Sanmenxia had the highest and lowest threshold of rapid accumulation, respectively. Based on the distribution characteristics of the accumulation rate, the accumulation level of the 11 cities can be divided into 3 types: strong (Baoji, Linfen, Lvliang, Jinzhong), medium (Xianyang, Weinan, Tongchuan, Yuncheng, Luoyang), and weak groups (Xi'an, Sanmenxia). The accumulation rate of most cities showed an upward trend with the increase of concentration, especially in Lvliang and Linfen, with Xi'an showing the lowest variation. From the view of annual changes, the proportion of rapid accumulation process in various cities decreased from 2017 or 2018, while from the view of monthly changes, the rapid accumulation occurs primarily in December and January. Secondary aerosol and regional transport had significant impact on the accumulation rate of PM2.5. When rapid accumulation occurred, SO2 and NO2 concentrations were obviously increased, suggesting the secondary formation of air pollutants was significant. The backward trajectory analyses in Linfen and Xi'an demonstrated that the increase of airflow in the southwest direction is more likely to cause the rapid accumulation of local PM2.5.

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