Journal of Meteorological Research

, Volume 31, Issue 6, pp 1045–1061 | Cite as

Optical and radiative properties of aerosols during a severe haze episode over the North China Plain in December 2016

  • Yu Zheng
  • Huizheng Che
  • Leiku Yang
  • Jing Chen
  • Yaqiang Wang
  • Xiangao Xia
  • Hujia Zhao
  • Hong Wang
  • Deying Wang
  • Ke Gui
  • Linchang An
  • Tianze Sun
  • Jie Yu
  • Xiang Kuang
  • Xin Li
  • Enwei Sun
  • Dapeng Zhao
  • Dongsen Yang
  • Zengyuan Guo
  • Tianliang Zhao
  • Xiaoye Zhang
Special Collection on the Heavy and Persistent Haze-Fog Episodes in Winter 2016 in the Beijing-Tianjin-Hebei Area of China
  • 52 Downloads

Abstract

The optical and radiative properties of aerosols during a severe haze episode from 15 to 22 December 2016 over Beijing, Shijiazhuang, and Jiaozuo in the North China Plain were analyzed based on the ground-based and satellite data, meteorological observations, and atmospheric environmental monitoring data. The aerosol optical depth at 500 nm was < 0.30 and increased to > 1.4 as the haze pollution developed. The Ångström exponent was > 0.80 for most of the study period. The daily single-scattering albedo was > 0.85 over all of the North China Plain on the most polluted days and was > 0.97 on some particular days. The volumes of fine and coarse mode particles during the haze event were approximately 0.05–0.21 and 0.01–0.43 μm3, respectively—that is, larger than those in the time without haze. The daily absorption aerosol optical depth was about 0.01–0.11 in Beijing, 0.01–0.13 in Shijiazhuang, and 0.01–0.04 in Jiaozuo, and the average absorption Ångström exponent varied between 0.6 and 2.0. The aerosol radiative forcing at the bottom of the atmosphere varied from –23 to –227,–34 to –199, and –29 to –191 W m–2 for the whole haze period, while the aerosol radiative forcing at the top of the atmosphere varied from –4 to –98, –10 to –51, and –21 to –143 W m–2 in Beijing, Shijiazhuang, and Jiaozuo, respectively. Satellite observations showed that smoke, polluted dust, and polluted continental components of aerosols may aggravate air pollution during haze episodes. The analysis of the potential source contribution function and concentration-weighted trajectory showed that the contribution from local emissions and pollutants transport from upstream areas were 190–450 and 100–410 μg m–3, respectively.

Keywords

haze episodes aerosols optical properties radiative forcing North China Plain 

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References

  1. Bergstrom, R. W., 1973: Extinction and absorption coefficients of the atmospheric aerosol as a function of particle size. Beitr. Phys. Atmos., 46, 223–234.Google Scholar
  2. Blando, J. D., and B. J. Turpin, 2000: Secondary organic aerosol formation in cloud and fog droplets: A literature evaluation of plausibility. Atmos. Environ., 34, 1623–1632, doi: 10.1016/S1352-2310(99)00392-1.CrossRefGoogle Scholar
  3. Che, H., G. Shi, A. Uchiyama, et al., 2008: Intercomparison between aerosol optical properties by a PREDE skyradiometer and CIMEL sunphotometer over Beijing, China. Atmos. Chem. Phys., 8, 3199–3214, doi: 10.5194/acp-8-3199-2008.CrossRefGoogle Scholar
  4. Che, H., X. Xia, J. Zhu, et al., 2014: Column aerosol optical properties and aerosol radiative forcing during a serious haze–fog month over North China Plain in 2013 based on ground-based sunphotometer measurements. Atmos. Chem. Phys., 14, 2125–2138, doi: 10.5194/acp-14-2125-2014.CrossRefGoogle Scholar
  5. Che, H. Z., G. Y. Shi, X. Y. Zhang, et al., 2005: Analysis of 40 years of solar radiation data from China, 1961–2000. Geophys. Res. Lett., 32, L06803, doi: 10.1029/2004GL022322.CrossRefGoogle Scholar
  6. Che, H. Z., X. Y. Zhang, Y. Li, et al., 2007: Horizontal visibility trends in China 1981–2005. Geophys. Res. Lett., 34, L24706, doi: 10.1029/2007GL031450.CrossRefGoogle Scholar
  7. Che, H. Z., X. Y. Zhang, H. B. Chen, et al., 2009: Instrument calibration and aerosol optical depth validation of the China Aerosol Remote Sensing Network. J. Geophys. Res., 114, D03206, doi: 10.1029/2008JD011030.CrossRefGoogle Scholar
  8. Draxler, R. R., and G. D. Hess, 1998: An overview of the HYSPLIT_4 modelling system for trajectories, dispersion, and deposition. Aust. Meteor. Mag., 47, 295–308.Google Scholar
  9. Dubovik, O., B. Holben, T. F. Eck, et al., 2002: Variability of absorption and optical properties of key aerosol types observed in worldwide locations. J. Atmos. Sci., 59, 590–608, doi: 10.1175/1520-0469(2002)059<0590:VOAAOP>2.0.CO;2.CrossRefGoogle Scholar
  10. Eck, T. F., B. N. Holben, O. Dubovik, et al., 2005: Columnar aerosol optical properties at AERONET sites in central eastern Asia and aerosol transport to the tropical mid-Pacific. J. Geophys. Res., 110, D06202, doi: 10.1029/2004JD005274.CrossRefGoogle Scholar
  11. Eck, T. F., B. N. Holben, J. S. Reid, et al., 2012: Fog-and cloud-induced aerosol modification observed by the Aerosol Robotic Network (AERONET). J. Geophys. Res., 117, D07206, doi: 10.1029/2011JD016839.CrossRefGoogle Scholar
  12. Fu, G. Q., W. Y. Xu, R. F. Yang, et al., 2014: The distribution and trends of fog and haze in the North China Plain over the past 30 years. Atmos. Chem. Phys., 14, 11949–11958, doi: 10.5194/acp-14-11949-2014.CrossRefGoogle Scholar
  13. Giles, D. M., B. N. Holben, T. F. Eck, et al., 2012: An analysis of AERONET aerosol absorption properties and classifications representative of aerosol source regions. J. Geophys. Res., 117, D17203, doi: 10.1029/2012JD018127.CrossRefGoogle Scholar
  14. Gui, K., H. Che, Q. L. Chen, et al., 2016: Aerosol optical properties based on ground and satellite retrievals during a serious haze episode in December 2015 over Beijing. Atmosphere, 7, 70, doi: 10.3390/atmos7050070.CrossRefGoogle Scholar
  15. Gyawali, M., W. P. Arnott, K. Lewis, et al., 2009: In situ aerosol optics in Reno, NV, USA during and after the summer 2008 California wildfires and the influence of absorbing and nonabsorbing organic coatings on spectral light absorption. Atmos. Chem. Phys., 9, 8007–8015, doi: 10.5194/acp-9-8007-2009.CrossRefGoogle Scholar
  16. Hansen, J., M. Sato, and R. Ruedy, 1997: Radiative forcing and climate response. J. Geophys. Res., 10, 6831–6864, doi: 10.1029/96JD03436.CrossRefGoogle Scholar
  17. He, X., C. C. Li, A. K. H. Lau, et al., 2009: An intensive study of aerosol optical properties in Beijing urban area. Atmos. Chem. Phys., 9, 8903–8915, doi: 10.5194/acp-9-8903-2009.CrossRefGoogle Scholar
  18. Hennigan, C. J., M. H. Bergin, J. E. Dibb, et al., 2008: Enhanced secondary organic aerosol formation due to water uptake by fine particles. Geophys. Res. Lett., 35, L18801, doi: 10.1029/2008GL035046.CrossRefGoogle Scholar
  19. Holben, B. N., T. F. Eck, I. Slutsker, et al., 1998: AERONET-A federated instrument network and data archive for aerosol characterization. Remote Sens. Environ., 66, 1–16, doi: 10.1016/S0034-4257(98)00031-5.CrossRefGoogle Scholar
  20. Hsu, Y. K., T. M. Holsen, and P. K. Hopke, 2003: Comparison of hybrid receptor models to locate PCB sources in Chicago. Atmos. Environ., 37, 545–562, doi: 10.1016/S1352-2310(02)00886-5.CrossRefGoogle Scholar
  21. Jing, J. S., R. J. Zhang, J. Tao, et al., 2011: Observations of aerosol optical properties in the Beijing urban area in summer. Atmos. Oceanic Sci. Lett., 4, 338–343, doi: 10.1080/16742834.2011.11446953.CrossRefGoogle Scholar
  22. Kotchenruther, R. A., and P. V. Hobbs, 1998: Humidification factors of aerosols from biomass burning in Brazil. J. Geophys. Res., 103, 32081–32089, doi: 10.1029/98JD00340.CrossRefGoogle Scholar
  23. Li, Z., X. Gu, L. Wang, et al., 2013: Aerosol physical and chemical properties retrieved from ground-based remote sensing measurements during heavy haze days in Beijing winter. Atmos. Chem. Phys., 13, 10171–10183, doi: 10.5194/acp-13-10171-2013.CrossRefGoogle Scholar
  24. Omar, A. H., D. M. Winker, M. A. Vaughan, et al., 2009: The CALIPSO automated aerosol classification and LiDAR ratio selection algorithm. J. Atmos. Oceanic Technol., 26, 1994–2014, doi: 10.1175/2009JTECHA1231.1.CrossRefGoogle Scholar
  25. Polissar, A. V., P. K. Hopke, and J. M. Harris, 2001: Source regions for atmospheric aerosol measured at Barrow, Alaska. Environ. Sci. Technol., 35, 4214–4226, doi: 10.1021/es0107529.CrossRefGoogle Scholar
  26. Quan, J., Q. Zhang, H. He, et al., 2011: Analysis of the formation of fog and haze in North China Plain (NCP). Atmos. Chem. Phys., 11, 8205–8214, doi: 10.5194/acp-11-8205-2011.CrossRefGoogle Scholar
  27. Quan, J. N., X. X. Tie, Q. Zhang, et al., 2014: Characteristics of heavy aerosol pollution during the 2012–2013 winter in Beijing, China. Atmos. Environ., 88, 83–89, doi: 10.1016/j.atmosenv.2014.01.058.CrossRefGoogle Scholar
  28. Russell, P. B., R. W. Bergstrom, Y. Shinozuka, et al., 2010: Absorption Angstrom Exponent in AERONET and related data as an indicator of aerosol composition. Atmos. Chem. Phys., 10, 1155–1169, doi: 10.5194/acp-10-1155-2010.CrossRefGoogle Scholar
  29. Stohl, A., 1996: Trajectory statistics—A new method to establish source-receptor relationships of air pollutants and its applica-tion to the transport of particulate sulfate in Europe. Atmos. Environ., 30, 579–587, doi: 10.1016/1352-2310(95)00314-2.CrossRefGoogle Scholar
  30. Sun, Y. L., G. S. Zhuang, A. H. Tang, et al., 2006: Chemical characteristics of PM2.5 and PM10 in haze–fog episodes in Beijing. Environ. Sci. Technol., 40, 3148–3155, doi: 10.1021/es051533g.CrossRefGoogle Scholar
  31. Tao, M. H., L. F. Chen, Z. F. Wang, et al., 2014: A study of urban pollution and haze clouds over northern China during the dusty season based on satellite and surface observations. Atmos. Environ., 82, 183–192, doi: 10.1016/j.atmosenv.2013.10.010.CrossRefGoogle Scholar
  32. Wang, Q., M. Shao, Y. Zhang, et al., 2009: Source apportionment of fine organic aerosols in Beijing. Atmos. Chem. Phys., 9, 8573–8585, doi: 10.5194/acp-9-8573-2009.CrossRefGoogle Scholar
  33. Wang, Y., G. S. Zhuang, Y. L. Sun, et al., 2006: The variation of characteristics and formation mechanisms of aerosols in dust, haze, and clear days in Beijing. Atmos. Environ., 40, 6579–6591, doi: 10.1016/j.atmosenv.2006.05.066.CrossRefGoogle Scholar
  34. Wang, Y. Q., X. Y. Zhang, and R. R. Draxler, 2009: TrajStat: GISbased software that uses various trajectory statistical analysis methods to identify potential sources from long-term air pollution measurement data. Environmental Modelling & Software, 24, 938–939.CrossRefGoogle Scholar
  35. Wang, Y. S., L. Yao, L. L. Wang, et al., 2014: Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China. Sci. China Earth Sci., 57, 14–25, doi: 10.1007/s11430-013-4773-4.CrossRefGoogle Scholar
  36. Watson, J. G., 2002: Visibility: science and regulation. J. Air Waste Manage. Assoc., 52, 628–713, doi: 10.1080/10473289.2002.10470813.CrossRefGoogle Scholar
  37. Watson, J. G., J. C. Chow, F. W. Lurmann, et al., 1994: Ammonium nitrate, nitric acid, and ammonia equilibrium in wintertime Phoenix, Arizona. Air & Waste, 44, 405–412.CrossRefGoogle Scholar
  38. Wehner, B., W. Birmili, F. Ditas, et al., 2008: Relationships between submicrometer particulate air pollution and air mass history in Beijing, China, 2004–2006. Atmos. Chem. Phys., 8, 6155–6168, doi: 10.5194/acp-8-6155-2008.CrossRefGoogle Scholar
  39. Xia, X., H. Chen, and W. Zhang, 2007a: Analysis of the dependence of column-integrated aerosol properties on long-range transport of air masses in Beijing. Atmos. Environ., 41, 7739–7750, doi: 10.1016/j.atmosenv.2007.06.042.CrossRefGoogle Scholar
  40. Xia, X., H. Chen, P. Goloub, et al., 2007b: A compilation of aerosol optical properties and calculation of direct radiative forcing over an urban region in northern China. J. Geophys. Res., 112, D12203, doi: 10.1029/2006JD008119.CrossRefGoogle Scholar
  41. Xin, Y. J., G. C. Wang, and L. Chen, 2016: Identification of longrange transport pathways and potential sources of PM10 in Tibetan Plateau uplift area: Case study of Xining, China in 2014. Aerosol and Air Quality Research, 16, 1044–1054, doi: 10.4209/aaqr.2015.05.0296.CrossRefGoogle Scholar
  42. Yan, R. C., S. C. Yu, Q. Y. Zhang, et al., 2015: A heavy haze episode in Beijing in February of 2014: Characteristics, origins and implications. Atmos. Pollut. Res., 6, 867–876, doi: 10.5094/APR.2015.096.CrossRefGoogle Scholar
  43. Yang, M., S. G. Howell, J. Zhuang, et al., 2009: Attribution of aerosol light absorption to black carbon, brown carbon, and dust in China-interpretations of atmospheric measurements during EAST-AIRE. Atmos. Chem. Phys., 9, 2035–2050, doi: 10.5194/acp-9-2035-2009.CrossRefGoogle Scholar
  44. Yu, X. N., B. Zhu, Y. Yin, et al., 2011: A comparative analysis of aerosol properties in dust and haze–fog days in a Chinese urban region. Atmos. Res., 99, 241–247, doi: 10.1016/j.atmosres.2010.10.015.CrossRefGoogle Scholar
  45. Yu, X. N., R. Kumar, R. Lü, et al., 2016: Changes in column aerosol optical properties during extreme haze–fog episodes in January 2013 over urban Beijing. Environ. Pollut., 210, 217–226, doi: 10.1016/j.envpol.2015.12.021.CrossRefGoogle Scholar
  46. Zhang, J. K., Y. Sun, Z. R. Liu, et al., 2013: Characterization of submicron aerosols during a serious pollution month in Beijing (2013) using an aerodyne high-resolution aerosol mass spectrometer. Atmos. Chem. Phys. Discuss., 13, 19009–19049, doi: 10.5194/acpd-13-19009-2013.CrossRefGoogle Scholar
  47. Zhang, R., J. Jing, J. Tao, et al., 2013: Chemical characterization and source apportionment of PM2.5 in Beijing: Seasonal perspective. Atmos. Chem. Phys., 13, 7053–7074, doi: 10.5194/acp-13-7053-2013.CrossRefGoogle Scholar
  48. Zheng, Y., H. Z. Che, T. L. Zhao, et al., 2016: Aerosol optical properties over Beijing during the world athletics championships and victory day military parade in August and September 2015. Atmosphere, 7, 47, doi: 10.3390/atmos7030047.CrossRefGoogle Scholar
  49. Zhu, J., H. Z. Che, X. G. Xia, et al., 2014: Column-integrated aerosol optical and physical properties at a regional background atmosphere in North China Plain. Atmos. Environ., 84, 54–64, doi: 10.1016/j.atmosenv.2013.11.019.CrossRefGoogle Scholar

Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Yu Zheng
    • 1
    • 2
  • Huizheng Che
    • 2
  • Leiku Yang
    • 3
  • Jing Chen
    • 4
  • Yaqiang Wang
    • 2
  • Xiangao Xia
    • 5
    • 6
  • Hujia Zhao
    • 2
  • Hong Wang
    • 2
  • Deying Wang
    • 2
  • Ke Gui
    • 2
  • Linchang An
    • 2
    • 7
  • Tianze Sun
    • 2
  • Jie Yu
    • 2
    • 8
  • Xiang Kuang
    • 1
  • Xin Li
    • 1
  • Enwei Sun
    • 1
  • Dapeng Zhao
    • 1
  • Dongsen Yang
    • 1
  • Zengyuan Guo
    • 9
  • Tianliang Zhao
    • 1
  • Xiaoye Zhang
    • 2
  1. 1.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/Key Laboratory for Aerosol–Cloud–Precipitation of China Meteorological AdministrationNanjing University of Information Science & TechnologyNanjingChina
  2. 2.State Key Laboratory of Severe Weather/Institute of Atmospheric Composition of China Meteorological AdministrationChinese Academy of Meteorological SciencesBeijingChina
  3. 3.School of Surveying and Land Information EngineeringHenan Polytechnic UniversityJiaozuoChina
  4. 4.Shijiazhuang Meteorological BureauShijiazhuangChina
  5. 5.Laboratory for Middle Atmosphere and Global Environment Observation, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  6. 6.University of Chinese Academy of SciencesBeijingChina
  7. 7.National Meteorological CenterChina Meteorological AdministrationBeijingChina
  8. 8.Institute of Meteorological Science of Jilin ProvinceChangchunChina
  9. 9.Key Laboratory for Earth System Modeling of Ministry of Education, Department of Earth System Science, and Joint Center for Global Change StudiesTsinghua UniversityBeijingChina

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