Advertisement

Journal of Meteorological Research

, Volume 32, Issue 1, pp 81–98 | Cite as

Differences in Meteorological Conditions between Days with Persistent and Non-Persistent Pollution in Beijing, China

  • Ting You
  • Renguang Wu
  • Gang Huang
Regular Articles

Abstract

We compared the regional synoptic patterns and local meteorological conditions during persistent and non-persistent pollution events in Beijing using US NCEP–Department of Energy reanalysis outputs and observations from meteorological stations. The analysis focused on the impacts of high-frequency (period < 90 days) variations in meteorological conditions on persistent pollution events (those lasting for at least 3 days). Persistent pollution events tended to occur in association with slow-moving weather systems producing stagnant weather conditions, whereas rapidly moving weather systems caused a dramatic change in the local weather conditions so that the pollution event was short-lived. Although Beijing was under the influence of anomalous southerly winds in all four seasons during pollution events, notable differences were identified in the regional patterns of sea-level pressure and local anomalies in relative humidity among persistent pollution events in different seasons. A region of lower pressure was present to the north of Beijing in spring, fall, and winter, whereas regions of lower and higher pressures were observed northwest and southeast of Beijing, respectively, in summer. The relative humidity near Beijing was higher in fall and winter, but lower in spring and summer. These differences may explain the seasonal dependence of the relationship between air pollution and the local meteorological variables. Our analysis showed that the temperature inversion in the lower troposphere played an important part in the occurrence of air pollution under stagnant weather conditions. Some results from this study are based on a limited number of events and thus require validation using more data.

Keywords

persistent and non-persistent pollution events regional synoptic patterns local meteorological conditions temperature inversion stability index Beijing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgments

We appreciate the comments of the two anonymous reviewers. The NCEP–DOE reanalysis 2 data were obtained from ftp://ftp.cdc.noaa.gov/.

References

  1. Beaver, S., A. Palazoglu, A. Singh, et al., 2010: Identification of weather patterns impacting 24-h average fine particulate matter pollution. Atmos. Environ., 44, 1761–1771, doi: 10.1016/j.atmosenv.2010.02.001.CrossRefGoogle Scholar
  2. Berico, M., A. Luciani, and M. Formignani, 1997: Atmospheric aerosol in an urban area—measurements of TSP and PM10 standards and pulmonary deposition assessments. Atmos. Environ., 31, 3659–3665, doi: 10.1016/S1352-2310(97)00204-5.CrossRefGoogle Scholar
  3. Buchanan, C. M., I. J. Beverland, and M. R. Heal, 2002: The influence of weather-type and long-range transport on airborne particle concentrations in Edinburgh, UK. Atmos. Environ., 36, 5343–5354, doi: 10.1016/S1352-2310(02)00579-4.CrossRefGoogle Scholar
  4. Chen, H. P., and H. J. Wang, 2015: Haze days in North China and the associated atmospheric circulations based on daily visibility data from 1960 to 2012. J. Geophys. Res. Atmos., 120, 5895–5909, doi: 10.1002/2015JD023225.CrossRefGoogle Scholar
  5. Chen, Z. H., S. Y. Cheng, J. B. Li, et al., 2008: Relationship between atmospheric pollution processes and synoptic pressure patterns in northern China. Atmos. Environ., 42, 6078–6087, doi: 10.1016/j.atmosenv.2008.03.043.CrossRefGoogle Scholar
  6. Cheng, Y., K. F. Ho, S. C. Lee, et al., 2006: Seasonal and diurnal variations of PM1.0, PM2.5 and PM10 in the roadside environment of Hong Kong. China Particuology, 4, 312–315, doi: 10.1016/S1672-2515(07)60281-4.CrossRefGoogle Scholar
  7. Choi, Y. S., C. H. Ho, D. L. Chen, et al., 2008: Spectral analysis of weekly variation in PM10 mass concentration and meteorological conditions over China. Atmos. Environ., 42, 655–666, doi: 10.1016/j.atmosenv.2007.09.075.CrossRefGoogle Scholar
  8. Dawson, J. P., P. J. Adams, and S. N. Pandis, 2007: Sensitivity of PM2.5 to climate in the eastern US: A modeling case study. Atmos. Chem. Phys., 7, 4295–4309, doi: 10.5194/acp-7-4295-2007.CrossRefGoogle Scholar
  9. 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
  10. Fung, W. Y., and R. Wu, 2014: Relationship between intraseasonal variations of air pollution and meteorological variables in Hong Kong. Annals of GIS, 20, 217–226, doi: 10.1080/19475683.2014.945480.CrossRefGoogle Scholar
  11. He, S. S., B. T. Zhao, and Z. Y. Yu, 2014: Development and comparison of national ambient air quality standards in China. Environ. Monitor. China, 30, 50–55, doi: 10.3969/j.issn.1002-6002.2014.04.009.(in Chinese)Google Scholar
  12. Hu, X. M., Y. Zhang, M. Z. Jacobson, et al., 2008: Coupling and evaluating gas/particle mass transfer treatments for aerosol simulation and forecast. J. Geophys. Res. Atmos., 113, D11208, doi: 10.1029/2007JD009588.CrossRefGoogle Scholar
  13. Jacob, D. J., and D. A. Winner, 2009: Effect of climate change on air quality. Atmos. Environ., 43, 51–63, doi: 10.1016/j.atmosenv.2008.09.051.CrossRefGoogle Scholar
  14. Ji, D. S., Y. S. Wang, L. L. Wang, et al., 2012: Analysis of heavy pollution episodes in selected cities of northern China. Atmos. Environ., 50, 338–348, doi: 10.1016/j.atmosenv.2011.11.053.CrossRefGoogle Scholar
  15. Kanamitsu, M., W. Ebisuzaki, J. Woollen, et al., 2002: NCEP–DOE AMIP-II reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 1631–1643, doi: 10.1175/BAMS-83-11-1631.CrossRefGoogle Scholar
  16. Kaur, S., M. J. Nieuwenhuijsen, and R. N. Colvile, 2007: Fine particulate matter and carbon monoxide exposure concentrations in urban street transport microenvironments. Atmos. Environ., 41, 4781–4810, doi: 10.1016/j.atmosenv.2007.02.002.CrossRefGoogle Scholar
  17. Liu, X. G., J. Li, Y. Qu, et al., 2013: Formation and evolution mechanism of regional haze: A case study in the megacity Beijing, China. Atmos. Chem. Phys., 13, 4501–4514, doi: 10.5194/acp-13-4501-2013.CrossRefGoogle Scholar
  18. Lyu, B. L., B. Zhang, and Y. Q. Bai, 2016: A systematic analysis of PM2.5 in Beijing and its sources from 2000 to 2012. Atmos. Environ., 124, 98–108, doi: 10.1016/j.atmosenv.2015.09.031.CrossRefGoogle Scholar
  19. Molina, L. T., S. Madronich, J. S. Gaffney, et al., 2010: An overview of the MILAGRO 2006 Campaign: Mexico City emissions and their transport and transformation. Atmos. Chem. Phys., 10, 8697–8760, doi: 10.5194/acp-10-8697-2010.CrossRefGoogle Scholar
  20. Pope III, C. A., M. Ezzati, and D. W. Dockery, 2009: Fine-particulate air pollution and life expectancy in the United States. N. Engl. J. Med., 360, 376–386, doi: 10.1056/NEJMsa0805646.CrossRefGoogle Scholar
  21. Pu, W. W., X. J. Zhao, X. F. Shi, et al., 2015: Impact of long-range transport on aerosol properties at a regional background station in northern China. Atmos. Res., 153, 489–499, doi: 10.1016/j.atmosres.2014.10.010.CrossRefGoogle Scholar
  22. Sun, Y. L., G. S. Zhuang, Y. Wang, et al., 2004: The air-borne particulate pollution in Beijing—concentration, composition, distribution and sources. Atmos. Environ., 38, 5991–6004, doi: 10.1016/j.atmosenv.2004.07.009.CrossRefGoogle Scholar
  23. Tian, G. J., Z. Qiao, and X. L. Xu, 2014: Characteristics of particulate matter (PM10) and its relationship with meteorological factors during 2001–2012 in Beijing. Environ. Pollut., 192, 266–274, doi: 10.1016/j.envpol.2014.04.036.CrossRefGoogle Scholar
  24. Twomey, S., 1974: Pollution and the planetary albedo. Atoms. Environ., 8, 1251–1256, doi: 10.1016/0004-6981(74)90004-3.CrossRefGoogle Scholar
  25. Wang, F., D. S. Chen, S. Y. Cheng, et al., 2010: Identification of regional atmospheric PM10 transport pathways using HYSPLIT, MM5-CMAQ and synoptic pressure pattern analysis. Environ. Modell. Softw., 25, 927–934, doi: 10.1016/j.envsoft.2010.02.004.CrossRefGoogle Scholar
  26. Wang, X. K., and W. Z. Lu, 2006: Seasonal variation of air pollution index: Hong Kong case study. Chemosphere, 63, 1261–1272, doi: 10.1016/j.chemosphere.2005.10.031.CrossRefGoogle Scholar
  27. Wilson, A. M., J. C. Salloway, C. P. Wake, et al., 2004: Air pollution and the demand for hospital services: A review. Environ. Int., 30, 1109–1118, doi: 10.1016/j.envint.2004.01.004.CrossRefGoogle Scholar
  28. Ye, X. X., Y. Song, X. H. Cai, et al., 2016: Study on the synoptic flow patterns and boundary layer process of the severe haze events over the North China Plain in January 2013. Atmos. Environ., 124, 129–145, doi: 10.1016/j.atmosenv.2015.06.011.CrossRefGoogle Scholar
  29. You, T., R. Wu, G. Huang, et al., 2017: Regional meteorological patterns for heavy pollution events in Beijing. J. Meteor. Res., 31, 597–611, doi: 10.1007/s13351-017-6143-1.CrossRefGoogle Scholar
  30. Zhang, H. L., Y. G. Wang, J. L. Hu, et al., 2015: Relationships between meteorological parameters and criteria air pollutants in three megacities in China. Environ. Res., 140, 242–254, doi: 10.1016/j.envres.2015.04.004.CrossRefGoogle Scholar
  31. Zhang, L., T. Wang, M. Y. Lyu, et al., 2015: On the severe haze in Beijing during January 2013: Unraveling the effects of meteorological anomalies with WRF-Chem. Atmos. Environ., 104, 11–21, doi: 10.1016/j.atmosenv.2015.01.001.CrossRefGoogle Scholar
  32. Zhang, R. H., Q. Li, and R. N. Zhang, 2013: Meteorological conditions for the persistent severe fog and haze event over eastern China in January 2013. Sci. China Earth Sci., 57, 26–35, doi: 10.1007/s11430-013-4774-3.Google Scholar
  33. Zhang, X.-Y., J.-Y. Sun, Y.-Q. Wang, et al., 2013: Factors contributing to haze and fog in China. Chinese Sci. Bull., 58, 1178–1187, doi: 10.1360/972013-150. (in Chinese)CrossRefGoogle Scholar
  34. Zhang, Y., A. J. Ding, H. T. Mao, et al., 2016: Impact of synoptic weather patterns and inter-decadal climate variability on air quality in the North China Plain during 1980–2013. Atmos. Environ., 124, 119–128, doi: 10.1016/j.atmosenv.2015.05.063.CrossRefGoogle Scholar
  35. Zhao, S. P., Y. Yu, D. Y. Yin, et al., 2016: Annual and diurnal variations of gaseous and particulate pollutants in 31 provincial capital cities based on in situ air quality monitoring data from China National Environmental Monitoring Center. Environ. Int., 86, 92–106, doi: 10.1016/j.envint.2015.11.003.CrossRefGoogle Scholar

Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Center for Monsoon System Research, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  2. 2.College of Atmospheric SciencesChengdu University of Information TechnologyChengduChina
  3. 3.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  4. 4.Laboratory for Regional Oceanography and Numerical ModelingQingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  5. 5.Joint Center for Global Change StudiesBeijingChina
  6. 6.University of Chinese Academy of SciencesBeijingChina

Personalised recommendations