论文

2016年冬季四川盆地一次重度灰霾事件形成机制研究

  • 任鑫冰 ,
  • 杨显玉 ,
  • 文军 ,
  • 王式功
展开
  • 1. 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
    2. 成都平原城市气象与环境四川省野外科学观测研究站,四川 成都 610225
    3. 中国科学院大气物理研究所大气边界层物理和大气化学国家重点实验室,北京 100029
    4. 中国科学院大学地球与行星科学学院,北京 100049

任鑫冰(1998 -), 男, 四川仁寿人, 博士研究生, 主要研究方向为大气边界层物理和化学、 大涡模拟E-mail:

收稿日期: 2023-04-16

  修回日期: 2023-10-09

  网络出版日期: 2023-10-09

基金资助

国家自然科学基金项目(42175174); 成都信息工程大学科技创新能力提升计划项目(KYQN202239); 国家留学基金资助项目(CSC202008510035)

Formation and Evolution Mechanisms of A Severe Haze Event in the Sichuan Basin in Winter 2016

  • Xinbing REN ,
  • Xianyu YANG ,
  • Jun WEN ,
  • Shigong WANG
Expand
  • 1. College of Atmospheric Sciences,Chengdu University of Information Technology / Sichuan Key Laboratory of Plateau Atmosphere and Environment,Chengdu 610225,Sichuan,China
    2. Chengdu Plain Urban Meteorology and Environment Sichuan Provincial Field Scientific Observation and Research Station,Chengdu 610225,Sichuan,China
    3. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC),Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China
    4. College of Earth and Planetary Sciences,University of Chinese Academy of Sciences,Beijing 100049,China

Received date: 2023-04-16

  Revised date: 2023-10-09

  Online published: 2023-10-09

摘要

深入理解重度灰霾污染事件的形成和演化机制对于区域尺度空气质量的管控以及霾污染防治政策的制定具有重要的意义。本文应用中尺度气象模式WRF和区域空气质量模型CMAQ, 结合实际观测数据, 研究了2016年12月23日至2017年1月7日发生在四川盆地成都地区的一次重度灰霾事件。主要分析了在此污染期间气象要素场的时间变化, PM2.5浓度和通风系数的时空变化, 量化了各个物理化学过程对PM2.5的相对贡献以及污染源区的分布, 以研究此次重污染霾事件的形成和演化机制。研究表明: (1)霾事件期间低温和低风速的环境条件为污染物的积累创造了有利条件。(2)盆地北侧的偏北气流和南侧的偏西南气流以及较低的通风系数(大气的湍流扩散能力弱)是污染物积累的主要原因, 成都地区PM2.5浓度在东北气流的作用下达到峰值。污染物的消散主要是因为偏北气流的加强和较高的通风系数(大气的湍流扩散能力强)。(3)此次霾事件中气溶胶过程和排放源的正贡献加强, PM2.5的增加主要在夜间(平流过程和扩散过程的负贡献减弱)且增加幅度更大, 使得PM2.5总体上逐渐增加。(4)PSCF和CWT分析表明, 在此次霾事件期间, 致使成都地区PM2.5浓度升高的主要气流为其东北方向和西南方向的气流, 潜在的污染源区在总体上呈东北-西南向的分布状态。

本文引用格式

任鑫冰 , 杨显玉 , 文军 , 王式功 . 2016年冬季四川盆地一次重度灰霾事件形成机制研究[J]. 高原气象, 2024 , 43(3) : 775 -789 . DOI: 10.7522/j.issn.1000-0534.2023.00082

Abstract

Studying the formation and evolution mechanism of heavy pollution haze events is beneficial to control the regional scale air quality and to formulate the prevention policies of severe haze pollution.Based on the WRF-CMAQ model and actual observation data, a severe haze event which occurred in Chengdu of Sichuan Basin from December 23, 2016 to January 7, 2017 was reproduced.The distribution of temporal and spatial variations of PM2.5 concentration and ventilation coefficient, the physical and chemical processes and the distribution of potential pollution source areas were analyzed to study the formation and evolution mechanism of this severe pollution haze event.Major results were as follows: (1) The environmental conditions of low temperature and low wind speed during the haze event created favorable conditions for the accumulation of pollutants.(2) The northerly airflow in the north of the basin, the southwesterly airflow in the south and the lower ventilation coefficient value (weak turbulent diffusion capability of atmosphere) were the main reasons for the accumulation of pollutants.The PM2.5 concentration in Chengdu reached the peak under the influence of the northeast airflow.The dissipation of pollutants was mainly because of the strengthening of the northerly airflow and the higher ventilation coefficient value (strong turbulent diffusion capability of atmosphere).(3) The positive contribution of the aerosol process and emission sources in this haze event was strengthened.And the increase in PM2.5 was mainly at night (the negative contribution of the advection process and the weak diffusion process) and the magnitude of the increase was greater relative to the decrease, resulting in an overall gradual increase in PM2.5.(4) PSCF and CWT analysis showed that the airflows with high PM2.5 concentration in Chengdu mainly came from its northeast and southwest directions during this haze event, and the potential pollution source areas were generally distributed in a northeast-southwest band.

参考文献

null
Ashbaugh L L Malm W C Sadeh W Z1985.A residence time probability analysis of sulfur concentrations at grand Canyon National Park[J].Atmospheric Environment19(8): 1263-1270.DOI: 10.1016/0004-6981(85)90256-2 .
null
Boylan J W Russell A G2006.PM and light extinction model performance metrics, goals, and criteria for three-dimensional air quality models[J].Atmospheric Environment40(26): 4946-4959.DOI: 10.1016/j.atmosenv.2005.09.087 .
null
Cai W Li K Liao H, et al, 2017.Weather conditions conducive to Beijing severe haze more frequent under climate change[J].Nature Climate Change7(4): 257-262.DOI: 10.1038/nclimate3249 .
null
Cao Y Q Zhang W Wang W J2018.Spatial-temporal characteristics of haze and vertical distribution of aerosols over the Yangtze River Delta of China[J].Journal of Environmental Sciences66(4): 12-19, DOI: 10.1016/j.jes.2017.05.039 .
null
Chang D Song Y Liu B2009.Visibility trends in six megacities in China 1973-2007[J].Atmospheric Research94(2): 161-167.DOI: 10.1016/j.atmosres.2009.05.006 .
null
Chen Y Xie S D2013.Long-term trends and characteristics of visibility in two megacities in Southwest China: Chengdu and Chongqing[J].Journal of the Air & Waste Management Association63(9): 1058-1069.DOI: 10.1080/10962247.2013.791348 .
null
Ding A J Huang X Nie W, et al, 2016.Enhanced haze pollution by black carbon in megacities in China[J].Geophysical Research Letters43(6): 2873-2879, DOI: 10.1002/2016gl067745 .
null
Huang X Song Y Zhao C, et al, 2014.Pathways of sulfate enhancement by natural and anthropogenic mineral aerosols in China[J].Journal of Geophysical Research: Atmospheres119(14): 14165-14179.DOI: 10.1002/2014JD022301 .
null
Guenther A B Jiang X Heald C L, et al, 2012.The model of emissions of gases and aerosols from nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions[J].Geoscientific Model Development5(6): 1471-1492.DOI: 10.5194/gmd-5-1471-2012 .
null
IPCC, 2014.Climate Change 2014.Synthesis Report.Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[R].IPCC, Geneva, Switzerland, 151.
null
Jones A M Harrison R M Baker J, et al, 2010.The wind speed dependence of the concentrations of airborne particulate matter and NOX [J].Atmospheric Environment44(13): 1682-1690.DOI: 10.1016/j.atmosenv.2010.01.007 .
null
Karaca F Anil I Alagha O2009.Long-range potential source contributions of episodic aerosol events to PM10 profile of a megacity[J].Atmospheric Environment43 (36): 5713-5722.DOI: 10. 1016/j.atmosenv.2009.08.005 .
null
Kong S F Li L Li X X, et al, 2015.The impacts of firework burning at the Chinese Spring Festival on air quality: insights of tracers, source evolution and aging processes[J].Atmospheric Chemistry and Physics15(4): 2167-2184.DOI: 10.5194/acp-15-2167-2015 .
null
Lei Y Zhang Q He K B, et al, 2011.Primary anthropogenic aerosol emission trends for China, 1990-2005[J].Atmospheric Chemistry and Physics11(3): 931-954.DOI: 10.5194/acp-11-931-2011 .
null
Li D P Liu J G Zhang J S, et al, 2017.Identification of long-range transport pathways and potential sources of PM2.5 and PM10 in Beijing from 2014 to 2015[J].Journal of Environmental Sciences, 56: 214-229.DOI: 10.1016/j.jes.2016.06.035 .
null
Liao T Wang S Ai J, et al, 2017.Heavy pollution episodes, transport pathways and potential sources of PM2.5 during the winter of 2013 in Chengdu (China)[J].Science of the Total Environment584-585: 1056.DOI: 10.1016/j.scitotenv.2017.01.160 .
null
Liu S Hu M Slanina S, et al, 2008.Size distribution and source analysis of ionic compositions of aerosols in polluted periods at Xinken in Pearl River Delta (PRD) of China[J].Atmospheric Environment42(25): 6284-6295, DOI: 10.1016/j.atmosenv.2007.12.035 .
null
Ma Y J Ye J H Xin J Y, et al, 2020.The stove, dome, and umbrella effects of atmospheric aerosol on the development of the planetary boundary layer in hazy regions[J].Geophysical Research Letters47(13): e2020GL087373.DOI: 10.1029/2020GL087373 .
null
Ma Y J Xin J Y Wang Z F, et al, 2022.How do aerosols above the residual layer affect the planetary boundary layer height?[J] Science of the Total Environment, 814: 151953, DOI: 10.1016/j.scitotenv.2021.151953 .
null
Miao S G Chen F LeMone M A, et al, 2009.An observational and modeling study of characteristics of urban heat island and boundary layer structures in Beijing[J].Journal of Applied Meteorology and Climatology48(3): 484-501.DOI: 10.1175/2008JAMC1909.1 .
null
Polissar A V Hopke P K Harrwas J M2001.Source regions for atmospheric aerosol measured at Barrow, Alaska[J].Environmental Science & Technology35 (21): 4214-4226.DOI: 10.1021/es0107529 .
null
Qian Y Yan H P Berg L K, et al, 2016.Assessing impacts of PBL and surface layer schemes in simulating the surface-atmosphere interactions and precipitation over the tropical ocean using observations from AMIE/DYNAMO[J].Journal of Climate29(22): 8191-8210.DOI: 10.1175/JCLI-D-16-0040.1 .
null
Stohl A Kromp-kolb H1994.Origin of ozone in Vienna and surroundings, Austria[J].Atmospheric Environment28 (7): 1255-1266.DOI: 10.1016/1352-2310(94)90272-0 .
null
Stohl A1996.Trajectory statistics-a new method to establish source-receptor relationships of air pollutants and its application to the transport of particulate sulfate in Europe[J].Atmospheric Environment30(4): 579-587.DOI: 10.1016/1352-2310(95)00314-2 .
null
Stohl A1998.Computation, accuracy and applications of trajectories: a review and bibliography[J].Atmospheric Environment32(6): 947-966.DOI: 10.1016/S1352-2310(97)00457-3 .
null
Sun Y L Wang Z F Fu P Q, et al, 2013: The impact of relative humidity on aerosol composition and evolution processes during wintertime in Beijing, China[J].Atmospheric Environment, 77: 927-934, DOI: 10.1016/j.atmosenv.2013.06.019 .
null
Tie X X Wu D Brasseur G2009.Lung cancer mortality and exposure to atmospheric aerosol particles in Guangzhou, China[J].Atmospheric Environment43(14): 2375-2377, DOI: 10.1016/j.atmosenv.2009.01.036 .
null
Ula? ? M Tayan? M Yenigün O, et al, 2006.Analysis of major photochemical pollutants with meteorological factors for high ozone days in Istanbul, Turkey[J].Water, Air, and Soil Pollution, 175: 335-359.DOI: 10.1007/s11270-006-9142-x .
null
Wang Q Y Cao J J Shen Z X, et al, 2013.Chemical characteristics of PM2.5 during dust storms and air pollution events in Chengdu, China[J].Particuology11(1): 70-77.DOI: 10.1016/j.partic.2012.08.001 .
null
Wang Y Zhuang G S Zhang X Y, et al, 2006a.The ion chemistry, seasonal cycle, and sources of PM2.5 and TSP aerosol in Shanghai[J].Atmospheric Environment40(16): 2935-2952.DOI: 10. 1016/j.atmosenv.2005.12.051 .
null
Wang Y Q Zhang X Y Arimoto R2006b.The contribution from distant dust sources to the atmospheric particulate matter loadings at Xi’an, China during spring[J].Science of the Total Environment368(2-3): 875-883.DOI: 10.1016/j.scitotenv.2006. 03. 040 .
null
Wang Y Q2014a.MeteoInfo: GIS software for meteorological data visualization and analysis[J].Meteorological Applications21(2): 360-368.DOI: 10.1002/met.1345 .
null
Wang Y S Yao L Wang L L, et al, 2014b.Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China[J].Science China Earth Sciences57(1): 14-25, DOI: 10.1007/s11430-013-4773-4 .
null
Wang Y X Zhang Q Q Jiang J K, et al, 2014c.Enhanced sulfate formation during China’s severe winter haze episode in January 2013 missing from current models[J].Journal of Geophysical Research: Atmospheres119(17): 10425-410440.DOI: 10.1002/2013JD021426 .
null
Wang L L Liu Z R Sun Y, et al, 2015.Long-range transport and regional sources of PM2.5 in Beijing based on long-term observations from 2005 to 2010[J].Atmospheric Research, 157: 37-48.DOI: 10.1016/j.atmosres.2014.12.003 .
null
Wang J D Zhao B Wang S X, et al, 2017.Particulate matter pollution over China and the effects of control policies[J].Science of the Total Environment584-585: 426-447.DOI: 10.1016/j.scitotenv.2017.01.027 .
null
Wu D Tie X X Li C C, et al, 2005.An extremely low visibility event over the Guangzhou region: A case study[J].Atmospheric Environment39(35): 6568-6577.DOI: 10.1016/j.atmosenv. 2005.07.061 .
null
Wu D Bi X Y Deng X J, et al, 2007.Effect of atmospheric haze on the deterioration of visibility over the Pearl River Delta[J].Journal of Meteorological Research21(2): 215-223.DOI: CNKI: SUN: QXXW.0.2007-02-008 .
null
Xin Y G Wang G C Chen L2016.Identification of long-range transport pathways and potential sources of PM10 in Tibetan plateau uplift area: case study of Xining, China in 2014[J].Aerosol Air Quality Research16(4): 1044-1054.DOI: 10.4209/aaqr. 2015.05.0296 .
null
Yang F He K Ye B, et al, 2005.One-year record of organic and elemental carbon in fine particles in downtown Beijing and Shanghai[J].Atmospheric Chemistry and Physics5(6): 1449-1457.DOI: 10.5194/acp-5-1449-2005 .
null
Yang Y J Zheng Z F Yim S Y L, et al, 2020.PM2.5 Pollution modulates wintertime Urban-Heat-Island intensity in the Beijing-Tianjin-Hebei Megalopolis, China[J].Geophysical Research Letters47(1): e2019GL084288, DOI: 10.1029/2019gl084288 .
null
Zachary M Yin L Zacharia M2018.Application of PSCF and CWT to identify potential sources of aerosol optical depth in ICIPE Mbita[J].Open Access Library Journal5(4): 1-12.DOI: 10.4236/oalib.1104487 .
null
Zeng S L Zhang Y2017.The effect of meteorological elements on continuing heavy air pollution: a case study in the Chengdu Area during the 2014 Spring Festival[J].Atmosphere8(4): 71.DOI: 10.3390/atmos8040071 .
null
Zhang B2011.A simulation study on the structure of the urban boundary layer and the diffusion of SO2 pollutants over Shenyang[D].Peking University, Beijing, China, pp.92-97.
null
Zhang M Wang X M Chen J M, et al, 2010.Physical characterization of aerosol particles during the Chinese New Year’s firework events[J].Atmospheric Environment44(39): 5191-5198.DOI: 10.1016/j.atmosenv.2010.08.048 .
null
Zhang Z L Wang J Chen L H, et al, 2014.Impact of haze and air pollution-related hazards on hospital admissions in Guangzhou, China[J].Environmental Science & Pollution Research21(6): 4236-4244, DOI: 10.1007/s11356-013-2374-6 .
null
Zhao D D Xin J Y Gong C S, et al, 2021.The impact threshold of the aerosol radiative forcing on the boundary layer structure in the pollution region[J].Atmospheric Chemistry and Physics21(7): 5739-5753, DOI: 10.5194/acp-21-5739-2021 .
null
Zhao S P Yu Y Yin D Y, et al, 2018.Spatial patterns and temporal variations of six criteria air pollutants during 2015 to 2017 in the city clusters of Sichuan Basin, China[J].Science of the Total Environment, 624: 540-557, DOI: 10.1016/j.scitotenv.2017. 12.172 .
null
Zheng B Tong D Li M, et al, 2018.Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions[J] Atmospheric Chemistry and Physics18(19): 14095-14111.DOI: 10.5194/acp-18-14095-2018 .
null
Zhu T Shang J Zhao D F2011a.The roles of heterogeneous chemical processes in the formation of an air pollution complex and gray haze[J].Science China Chemistry, 54: 145-153.DOI: 10. 1007/s11426-010-4181-y .
null
Zhu L Huang X Shi H, et al, 2011b.Transport pathways and potential sources of PM10 in Beijing[J].Atmospheric Environment45 (3): 594-604.DOI: 10.1016/j.atmosenv.2010.10.040 .
null
陈源, 谢绍东, 罗彬, 2016.成都市大气细颗粒物组成和污染特征分析(2012-2013年)[J].环境科学学报36(3): 1021-1031.DOI: 10.13671/j.hjkxxb.2015.0501.Chen Y
null
Xie S D Luo B2016.Composition and pollution characteristics of fine particles in Chengdu from 2012 to 2013[J].Acta Scientiae Circumstantiae36(3): 1021-1031.DOI: 10.13671/j.hjkxxb. 2015.0501 .
null
戴永立, 陶俊, 林泽健, 等, 2013.2006-2009年我国超大城市霾天气特征及影响因子分析[J].环境科学34(8): 2925-2932.DOI: CNKI: SUN: HJKZ.0.2013-08-000.Dai Y L
null
Tao J Lin Z J, et al, 2013.Characteristics of haze and its impact factors in four megacities in China during 2006-2009[J].Environmental Science34(8): 2925-2932.DOI: CNKI: SUN: HJKZ.0.2013-08-000 .
null
李世广, 蒋厦, 佟洪金, 等, 2013.基于空气质量模型CMAQ的成渝经济区(四川)PM2.5浓度数值模拟研究[J].四川环境32(): 109-113.
null
Li S G Jiang X Dong H J, et al, 2013.Study on the numerical simulation of PM2.5 in Chengdu-Chongqing economic zone based on air quality model system CMAQ[J].Sichuan Environment32(): 109-113.
null
刘培川, 罗彬, 张巍, 等, 2018.基于WRF模式的成都地区边界层污染气象特征研究[J].四川环境37(3): 48-55.DOI: 10. 3969/j.issn.1001-3644.2018.03.010.Liu P C
null
Luo B Zhang W, et al, 2018.Research on pollution meteorological characteristics of boundary layer in Chengdu area based on WRF model[J].Sichuan Environment37(3): 48-55.DOI: 10.3969/j.issn. 1001-3644.2018.03.010 .
null
张颖, 刘志红, 吕晓彤, 等, 2016.四川盆地一次污染过程的WRF模式参数化方案最优配置[J].环境科学学报36(8): 28192826.DOI: 10.13671/j.hjkxxb.2016.0009.Zhang Y
null
Liu Z H X T, et al, 2016.Optimal configuration of parameterized schemes in WRF model during a pollution episode in Sichuan Basin[J].Acta Scientiae Circumstantiae36(8): 28192826.DOI: 10.13671/j.hjkxxb.2016.0009 .
文章导航

/