研究报告

  • 肖致美,蔡子颖,李鹏,徐虹,刘彬,郑乃源,唐邈,陈魁,邓小文.2020年春节期间天津市重污染天气污染特征分析[J].环境科学学报,2020,40(12):4442-4452

  • 2020年春节期间天津市重污染天气污染特征分析
  • Characterization of heavy air pollution events during the 2020 Spring Festival in Tianjin
  • 基金项目:天津市科技计划项目(No.18ZXSZSF00160)
  • 作者
  • 单位
  • 肖致美
  • 天津市生态环境监测中心, 天津 300191
  • 蔡子颖
  • 天津市环境气象中心, 天津 300074
  • 李鹏
  • 天津市生态环境监测中心, 天津 300191
  • 徐虹
  • 天津市生态环境监测中心, 天津 300191
  • 刘彬
  • 天津市生态环境监测中心, 天津 300191
  • 郑乃源
  • 天津市生态环境监测中心, 天津 300191
  • 唐邈
  • 天津市生态环境监测中心, 天津 300191
  • 陈魁
  • 天津市生态环境监测中心, 天津 300191
  • 邓小文
  • 天津市生态环境监测中心, 天津 300191
  • 摘要:为了解春节期间重污染天气污染特征,基于城区点位2020年1月高时间分辨率的在线监测数据,开展天津市春节期间重污染分析.结果表明:区域污染物输送叠加本地污染物排放和不利气象条件导致春节重污染的发生,重污染期间天津市平均风速为0.97 m·s-1,平均相对湿度为70%左右,边界层高度为210 m,水平和垂直扩散条件均较差.春节重污染期间,天津市PM2.5、SO2、NO2和CO平均浓度分别为219、14、46 μg·m-3和1.9 mg·m-3,与春节前重污染相比,春节重污染期间污染程度有所降低,尤其是NO2浓度下降明显.PM2.5浓度空间分布表明,天津远郊区依然存在烟花爆竹燃放情况.春节重污染期间,城区PM2.5中主要化学组分为二次无机离子(NO3-、SO42-和NH4+)、OC、K+和Cl-,平均浓度分别为96.4、22.5、9.5和8.9 μg·m-3,在PM2.5中占比分别为41.3%、9.7%、4.1%和3.8%.与春节前重污染相比,受移动源减少、工业企业排放降低、工地停工影响,春节重污染期间NO3-、SO42-、NH4+、EC和Ca2+浓度及其在PM2.5中占比明显下降;受烟花爆竹燃放影响,OC、K+、Cl-和Mg2+浓度及其在PM2.5中占比均上升.与清洁天气相比,春节重污染期间PM2.5中二次无机化学转化明显增强.PMF解析结果表明,春节重污染期间,天津市城区PM2.5的主要来源为二次无机盐、燃煤和工业、烟花爆竹及生物质燃烧、机动车和扬尘,贡献分担率分别为40.1%、30.6%、20.6%、6.9%和1.8%.与春节前重污染相比,春节重污染期间二次无机盐、机动车和扬尘贡献率分别下降25.5%、62.9%、71.4%,燃煤和工业贡献率上升51.5%,烟花爆竹及生物质燃烧源显著上升.无论是重污染还是非重污染,常态化还是特殊时期,二次无机盐、燃煤和工业排放始终是天津市PM2.5最主要的来源,产业结构和能源结构的调整始终是天津大气污染防治的主要方向.
  • Abstract:Characterization of heavy air pollution periods (HAP) during the 2020 Spring Festival (SF) were investigated based on high-resolution online monitoring data observed at an urban site in downtown of Tianjin. Results show that the HAP during the SF were caused by the combination of regional transported pollutants, local source emissions and poor horizontal and vertical diffusion conditions, with average wind speed of 0.97 m·s-1, average relative humidity of 70%, and the extremely low boundary layer height of only 210 m. Concentrations of PM2.5, SO2, NO2 and CO observed for the HAP during the SF were 219, 14, 46 μg·m-3 and 1.9 mg·m-3, respectively. Compared with HAP before the SF, the air pollutants concentration decreased in HAP during the SF, especially for NO2. Spatial distribution of PM2.5 concentration indicates that the fireworks activities still existed in the outskirts of Tianjin. During the heavy pollution episode observed in the SF, the major chemical components of PM2.5 were secondary inorganic ions (NO3-, SO42- and NH4+), followed by OC, K+ and Cl-, with average concentration of 96.4 μg·m-3 (41.3% in PM2.5 mass), 22.5 μg·m-3 (9.7%), 9.5 μg·m-3 (4.1%) and 8.9 μg·m-3 (3.8%), respectively. Compared with the heavy pollution period before the SF, the concentrations and mass fraction of secondary inorganic ions, EC and Ca2+ decreased significantly during the SF as likely the result of the reductions of non-essential industries and traffic flow, and the stop of construction activities. While the fireworks display activities were responsible for the increase of OC, K+, Cl- and Mg2+. Additionally, the high values of sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) suggest the enhanced secondary formation of sulfate and nitrate during the SF HAP in Tianjin. Positive matrix factorization was applied to the PM2.5 speciate dataset to estimate source contributions. The five identified sources were secondary inorganic aerosol, industrial and coal combustion, fireworks and biomass burning, vehicle emissions and dust, accounted for 40.1%, 30.6%, 20.6%, 6.9% and 1.8% of PM2.5 mass on average, respectively. Contributions of secondary inorganic aerosol, vehicle emissions and dust in the SF were decreased by 25.5%, 62.9% and 58.7% with respect to their contributions before the SF, respectively. In addition to the sharply increased contribution of fireworks and biomass burning in the SF, industrial and coal combustion emissions also elevated by 51.5%. As for Tianjin, this work highlights the fact the secondary inorganic aerosol, industrial and coal combustion emissions are the major sources of PM2.5 as it is not only for the common "business as usual" days but also for periods involved in unusual events. Thus, focus should be played on the adjustment of industrial structure and energy structure to further improve air quality in Tianjin.

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