高原气象

高原气象 >

2019 , Vol. 38 >Issue 6: 1332 - 1343

DOI: https://doi.org/10.7522/j.issn.1000-0534.2018.00157

论文

京津冀地区一次雾霾过程的污染分布及来源分析

  • 沈新勇 ,
  • 陈逸智 ,
  • 郭春燕 ,
  • 李小凡
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  • 南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心, 江苏 南京 210044;中国科学院大气物理研究所云降水物理与强风暴重点实验室, 北京 100029;内蒙古气象服务中心, 内蒙古 呼和浩特 010051;浙江大学地球科学学院, 浙江 杭州 310027

收稿日期: 2018-06-21

  网络出版日期: 2019-12-28

基金资助

国家重点研发计划项目（2016YFC0203301）；国家自然科学基金项目（41790471，41530427，41775040）；国家重点基础研究发展计划项目（2015CB453201）

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Pollution Distribution and Source Analysis of a Haze Process in Beijing-Tianjin-Hebei Area

  • SHEN Xinyong ,
  • CHEN Yizhi ,
  • GUO Chunyan ,
  • LI Xiaofan
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  • Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China;Key Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;Inner Mongolia Meteorological Service Center, Hohhot, Inner Mongolia 010051, China;School of Earth Sciences, Zhejiang University, Hangzhou, Zhejiang 310027, China

Received date: 2018-06-21

  Online published: 2019-12-28

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摘要

利用气象与化学模块在线耦合的模式WRF-Chem V3.5（Weather Research and Forecasting Model coupled to Chemistry Version 3.5）对2016年11月3-6日的一次京津冀污染过程展开了数值模拟，设计进行了包含人为排放源的实验，运用有效的模拟结果对过程进行分析。结果表明：大气稳定度指数能有效量化反映污染过程中的大气稳定状况，且K指数和TT指数相较其他两种指数的指示效果更为准确，是讨论雾霾发生发展原因的有力依据。本次污染高值中心有三个，分别为北京天津一带、河北东北部以及河北南部。PM2.5、PM10以及SO2污染物水平分布有明显日变化特征，CO和NO2则变化不明显，污染从3日开始发展至6日结束，除NO2外各项污染物都明显受到冷空气的影响，在6日浓度骤降。北京和天津地区的污染是主要来源于河北南部的工业和交通排放的外源型污染，而河北东北部和河北南部的污染则是主要受本地排放影响的内源型污染。污染物主要化学成分为CO，污染物颗粒PM2.5和PM10量级相当且浓度差别不大，均对本次污染有较大贡献。

关键词： WRF-Chem模式; 雾霾; 大气稳定度指数; 分布特征; 后向轨迹

本文引用格式

沈新勇 , 陈逸智 , 郭春燕 , 李小凡 . 京津冀地区一次雾霾过程的污染分布及来源分析[J]. 高原气象, 2019 , 38(6) : 1332 -1343 . DOI: 10.7522/j.issn.1000-0534.2018.00157

Abstract

To investigate the pollution process from 3 to 6 in November 2016 in Beijing, Tianjin and Hebei region, a simulations with anthropogenic emissions are conducted by using WRF-Chem V3.5 (Weather Research and Forecasting Model coupled to Chemistry Version 3.5). The effective simulated results shows that the atmospheric stability index can effectively quantify the atmospheric stable status in the process of pollution, both the K index and the TT index are more accurate than the other two indices. It is a powerful basis for discussing the causes of the occurrence and development of haze. There are three high value centers of pollution. They are Beijing Tianjin area, northeast Hebei and southern Hebei. The horizontal distribution of PM2.5, PM10 and SO2 pollutants has a more obvious diurnal variation, while CO and NO2 are not changed obviously. The pollution begin on 3 and end on 6 in November, all pollutants are obviously affected by the cold air except NO2, and the concentration suddenly drops on 6 in November. The pollution in Beijing and Tianjin is mainly derived from the external pollution of industry and transport in southern Hebei, while the pollution in the northeast of Hebei and southern Hebei is an endogenous pollution mainly affected by local emissions. With the classification of chemical composition, the main pollutants are CO, and with the classification of the particle size of the pollutants, the size of PM2.5 and PM10 are similar and their concentration is not very different, all of which have great contribution to the pollution.

Key words： WRF-Chem model; smog; atmospheric stabilit; distribution charact; backward trajectory

参考文献

[1]Ackermann I J, Hass H, Memmesheimer M, et al, 1998. Modal aerosol dynamics model for Europe:Development and first applications[J]. Atmospheric environment, 32(17):2981-2999.
[2]Fuzzi S, Castillo R A, Jiusto J E, et al, 1984. Chemical composition of radiation fog water at Albany, New York, and its relationship to fog microphysics[J]. Journal of Geophysical Research Atmospheres, 89(D5):7159-7164.
[3]Grell G A, Freitas S R, 2013. A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling[J]. Atmospheric Chemistry and Physics Discussions, 13:23845-23893.
[4]Hong S Y, Noh Y, Dudhia J, 2006. A new vertical diffusion package with an explicit treatment of entrainment processes[J]. Monthly Weather Review, 134:2318-2341.
[5]Iacono M J, Delamere J S, Mlawer E J, et al, 2008. Radiative forcing by long-lived greenhouse gases:Calculations with the AER radiative transfer models[J]. Journal of Geophysical Research:Atmospheres, 113(D13):D13103. DOI:10.1029/2008JD009944.
[6]Morrison H, Thompson G, Tatarskii V, 2009. Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line:Comparison of one-and two-moment schemes[J]. Monthly Weather Review, 137:991-1007.
[7]Pleijel H, 2009. Air pollution and climate change, Two sides of the same coin[M]. Stockholm:Swedish Environmental Protection Agency, 76-83.
[8]Saide P E, Carmichael G R, Spak S N, et al, 2011. Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF-Chem CO tracer model[J]. Atmospheric Environment, 45(16):2769-2780.
[9]Stockwell W R, Middleton P, Chang J S, et al, 1990. The second generation regional acid deposition model chemical mechanism for regional air quality modeling[J]. Journal of Geophysical Research:Atmospheres, 95(D10):16343-16367.
[10]Wild O, Zhu X, Prather M J, 2000. Fast-J:Accurate simulation of in-and below-cloud photolysis in tropospheric chemical models[J]. Journal of Atmospheric Chemistry, 37:245-282.
[11]Wu P Y, Ding H, Liu Y J, 2017. Atmospheric circulation and dynamic mechanism for persistent haze events in the Beijing-Tianjin-Hebei region[J]. Advances in Atmospheric Sciences, 34(4), 429-440.
[12]Ying I T, 2005.Atmospheric visibility trends in an urban area in Taiwan 1961-2003[J]. Atmospheric Environment, 39(30):5555-5567.
[13]Zhang Q, Streets D G, Carmichael G R, et al, 2009. Asian emissions in 2006 for the NASA INTEX-B mission[J]. Atmospheric Chemistry and Physics, 9:5131-5153.
[14]Zhang Y, Olsen S C, Dubey M K, 2010a. WRF/Chem simulated springtime impact of rising Asian emissions on air quality over the US.[J]. Atmospheric Environment, 44(24):2799-2812.
[15]Zhang Y, Wen X Y, Jang C J, 2010b. Simulating chemistry-aerosol-cloud-radiation-climate feedbacks over the continental U. S. using the online-coupled Weather Research Forecasting Model with chemistry (WRF/Chem)[J]. Atmospheric Environment, 44(29):3568-3582.
[16]曹伟华, 李青春, 2012.北京地区雾霾气候特征及影响因子分析[C].南京: 中国灾害防御协会风险分析专业委员会第五届年会论文集.
[17]董雪玲, 2004.大气可吸入颗粒物对环境和人体健康的危害[J].资源产业, 6(5):50-53.
[18]冯民学, 周俊驰, 曾明剑, 等, 2012.基于对流参数的洋口港地区雷暴预报方法研究[J].气象, 38(12):1515-1522.
[19]侯梦玲, 王宏, 赵天良, 等, 2017.京津冀一次重度雾霾天气能见度及边界层关键气象要素的模拟研究[J].大气科学, 2017(6):1177-1190.
[20]花丛, 张恒德, 张碧辉, 2016.2013-2014冬半年北京重污染天气气象传输条件分析及预报指数初建[J].气象, 42(3):314-321.
[21]李菲, 吴兑, 谭浩波, 等, 2012.广州地区旱季一次典型灰霾过程的特征及成因分析[J].热带气象学报, 2012(1):113-120.
[22]刘琳, 王玲玲, 白永清, 等, 2017.应用WRF/Chem模拟河南冬季大气颗粒物的区域输送特征[J].环境科学学报, 37(5):1843-1854.
[23]刘梅, 严文莲, 张备, 等, 2014.2013年1月江苏雾霾天气持续和增强机制分析[J].气象, 40(7):835-843.
[24]马学款, 张碧辉, 桂海林, 等, 2017. APEC前后北京几次静稳天气边界层特征对比分析[J].气象, 43(11):1364-1373.
[25]麦健华, 邓涛, 于玲玲, 等, 2016.中山市旱季霾特征及数值模拟分析[J].环境科学学报, 36(6):2170-2179.
[26]庞杨, 韩志伟, 朱彬, 等, 2013.利用WRF-Chem模拟研究京津冀地区夏季大气污染物的分布和演变[J].大气科学学报, 36(6):674-682.
[27]任芝花, 余予, 韩瑞, 等, 2018.自动与人工观测霾日、雾日序列连续性分析[J].高原气象, 37(3):863-871. DOI:10.7522/j.issn.1000-0534.2018.00007.
[28]沈新勇, 梅海霞, 王卫国, 等, 2015.双参数微物理方案的冰相过程模拟及冰核数浓度的影响试验[J].大气科学, 39(1):83-99.
[29]唐宜西, 张小玲, 熊亚军, 等, 2013.北京一次持续霾天气过程气象特征分析[J].气象与环境学报, 29(5):12-19.
[30]魏建苏, 孙燕, 严文莲, 等, 2010.南京霾天气的特征分析和影响因子初探[J].气象科学, 30(6):868-873.
[31]翁之梅, 李丽平, 杨万裕, 等, 2016.浙江省冬季不同霾过程的后向气流轨迹及环流特征[J].气象, 42(2):183-191.
[32]吴兑, 廖碧婷, 吴蒙, 等, 2014.环首都圈霾和雾的长期变化特征与典型个例的近地层输送条件[J].环境科学学报, 34(1):1-11.
[33]夏冬, 吴志权, 莫伟强, 等, 2013.一次热带气旋外围下沉气流造成的珠三角地区连续灰霾天气过程分析[J].气象, 39(6):759-767.
[34]肖辉, 银燕, 2011.污染气溶胶对山西一次降水过程影响的数值模拟[J].大气科学, 35(2):235-246.
[35]于兴娜, 马佳, 朱彬, 等, 2015.南京北郊秋冬季相对湿度及气溶胶理化特性对大气能见度的影响[J].环境科学, 2015(6):1919-1925.
[36]张人禾, 李强, 张若楠, 2014.2013年1月中国东部持续性强雾霾天气产生的气象条件分析[J].中国科学(地球科学), 44(1):27-36.
[37]张悦, 樊曙先, 李皓, 等, 2016.气溶胶辐射效应在华东地区一次雾霾过程中的作用[J].气象学报, 74(3):465-478.
[38]赵玲, 李树岭, 王安娜, 等, 2013. K指数在黑龙江省晴雨预报中的应用[J].气象与环境学报, 29(6):145-149.
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