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Weather conditions conducive to Beijing severe haze more frequent under climate change

Nature Climate Change volume 7, pages 257–262 (2017)Cite this article

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Abstract

The frequency of Beijing winter severe haze episodes has increased substantially over the past decades1,2,3,4, and is commonly attributed to increased pollutant emissions from China’s rapid economic development5,6. During such episodes, levels of fine particulate matter are harmful to human health and the environment, and cause massive disruption to economic activities3,4,7,8,9,10,11,12,13,14,15,16, as occurred in January 201317,18,19,20,21. Conducive weather conditions are an important ingredient of severe haze episodes3,21, and include reduced surface winter northerlies3,21, weakened northwesterlies in the midtroposphere, and enhanced thermal stability of the lower atmosphere1,3,16,21. How such weather conditions may respond to climate change is not clear. Here we project a 50% increase in the frequency and an 80% increase in the persistence of conducive weather conditions similar to those in January 2013, in response to climate change. The frequency and persistence between the historical (1950–1999) and future (2050–2099) climate were compared in 15 models under Representative Concentration Pathway 8.5 (RCP8.5)22. The increased frequency is consistent with large-scale circulation changes, including an Arctic Oscillation upward trend23,24, weakening East Asian winter monsoon25,26, and faster warming in the lower troposphere27,28. Thus, circulation changes induced by global greenhouse gas emissions can contribute to the increased Beijing severe haze frequency.

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Figure 1: Observed Beijing (116.4° E, 39.9° N) winter severe haze weather conditions and their representation by a haze weather index (HWI).
Figure 2: Time series of 2009–2015 normalized observed boreal winter daily PM2.5 (μg m−3) and normalized daily weather conditions near Beijing.
Figure 3: Future changes of Beijing winter severe haze weather conditions based on climate models.
Figure 4: Simulated winter severe haze weather conditions near Beijing (116.4° E, 39.9° N).
Figure 5: Simulated multi-model ensemble mean state changes in boreal winter mean circulation.

References

  1. Niu, F., Li, Z. Q., Li, C., Lee, K. H. & Wang, M. Y. Increase of wintertime fog in China: potential impacts of weakening of the eastern Asian monsoon circulation and increasing aerosol loading. J. Geophys. Res. 115, D00K20 (2010).

    Article  Google Scholar 

  2. Ding, Y. H. & Liu, Y. J. Analysis of long-term variations of fog and haze in China in recent 50 years and their relations with atmospheric humidity. Sci. China Earth Sci. 57, 36–46 (2014).

    Article  Google Scholar 

  3. Chen, H. & Wang, H. Haze days in north China and the associated atmospheric circulations based on daily visibility data from 1960 to 2012. J. Geophys. Res. 120, 5895–5909 (2015).

    Google Scholar 

  4. Wang, H. J., Chen, H. P. & Liu, J. Arctic sea ice decline intensified haze pollution in eastern China. Atmos. Ocean. Sci. Lett. 8, 1–9 (2015).

    Google Scholar 

  5. Guo, J. et al. Spatiotemporal variation trends of satellite-based aerosol optical depth in China during 1980–2008. Atmos. Environ. 45, 6802–6811 (2011).

    Article  CAS  Google Scholar 

  6. Zhou, Y. et al. The impact of transportation control measures on emission reductions during the 2008 Olympic Games in Beijing, China. Atmos. Environ. 44, 285–293 (2010).

    Article  CAS  Google Scholar 

  7. Bai, N., Khazaei, M., van Eeden, S. F. & Laher, I. The pharmacology of particulate matter air pollution-induced cardiovascular dysfunction. Pharmacol. Ther. 113, 16–29 (2007).

    Article  CAS  Google Scholar 

  8. Kan, H. et al. Differentiating the effects of fine and coarse particles on daily mortality in Shanghai, China. Environ. Int. 33, 376–384 (2007).

    Article  Google Scholar 

  9. Araujo, J. A. et al. Ambient particulate pollutants in the ultrafine range promote early atherosclerosis and systemic oxidative stress. Circ. Res. 102, 589–596 (2008).

    Article  CAS  Google Scholar 

  10. Pope, C. A. III & Dockery, D. W. Health effects of fine particulate air pollution: lines that connect. J. Air. Waste Manage. Assoc. 56, 709–742 (2006).

    Article  CAS  Google Scholar 

  11. Wang, X. P. & Mauzerall, D. L. Evaluating impacts of air pollution in China on public health: implications for future air pollution and energy policies. Atmos. Environ. 40, 1706–1721 (2006).

    Article  CAS  Google Scholar 

  12. Xu, P., Chen, Y. F. & Ye, X. J. Haze, air pollution, and health in China. Lancet 382, 2067 (2013).

    Article  Google Scholar 

  13. Qian, Y., Leung, L. R., Ghan, S. J. & Giorgi, F. Regional climate effects of aerosols over China: modeling and observation. Tellus B 55, 914–934 (2003).

    Article  Google Scholar 

  14. Liao, H., Chang, W. Y. & Yang, Y. Climatic effects of air pollutants over China: a review. Adv. Atmos. Sci. 32, 115–139 (2015).

    Article  Google Scholar 

  15. Li, Z. et al. East Asian studies of tropospheric aerosols and their impact on regional climate (EAST-AIRC): an overview. J. Geophys. Res. 116, D00K34 (2011).

    Google Scholar 

  16. Li, Q., Zhang, R. & Wang, Y. Interannual variation of the wintertime fog–haze days across central and eastern China and its relation with East Asian winter monsoon. Int. J. Climatol. 36, 346–354 (2016).

    Article  Google Scholar 

  17. Huang, R. J. et al. High secondary aerosol contribution to particulate pollution during haze events in China. Nature 514, 218–222 (2014).

    Article  CAS  Google Scholar 

  18. Ji, D. et al. The heaviest particulate air-pollution episodes occurred in northern China in January, 2013: insights gained from observation. Atmos. Environ. 92, 546–556 (2014).

    Article  CAS  Google Scholar 

  19. Quan, J. et al. Characteristics of heavy aerosol pollution during the 2012–2013 winter in Beijing, China. Atmos. Environ. 88, 83–89 (2014).

    Article  CAS  Google Scholar 

  20. Yang, Y. et al. Formation mechanism of continuous extreme haze episodes in the megacity Beijing, China, in January 2013. Atmos. Res. 155, 192–203 (2015).

    Article  CAS  Google Scholar 

  21. Zhang, R. H., Li, Q. & Zhang, R. N. Meteorological conditions for the persistent severe fog and haze event over eastern China in January 2013. Sci. China Earth Sci. 57, 26–35 (2014).

    Article  Google Scholar 

  22. Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

    Article  Google Scholar 

  23. Shindell, D. T. et al. Simulation of recent northern winter climate trends by greenhouse-gas forcing. Nature 399, 452–455 (1999).

    Article  CAS  Google Scholar 

  24. Fyfe, J. C., Boer, G. J. & Flato, G. M. The Arctic and Antarctic oscillations and their projected changes under global warming. J. Geophys. Res. 26, 1601–1604 (1999).

    Google Scholar 

  25. Hori, M. E. & Ueda, H. Impact of global warming on the East Asian winter monsoon as revealed by nine coupled atmosphere-ocean GCMs. Geophys. Res. Lett. 33, L03713 (2006).

    Google Scholar 

  26. Xu, M., Xu, H. & Ma, J. Responses of the East Asian winter monsoon to global warming in CMIP5 models. Int. J. Climatol. 36, 2139–2155 (2016).

    Article  Google Scholar 

  27. Jacob, D. J. & Winner, D. A. Effect of climate change on air quality. Atmos. Environ. 43, 51–63 (2009).

    Article  CAS  Google Scholar 

  28. Horton, D. E., Skinner, C. B., Singh, D. & Diffenbaugh, N. S. Occurrence and persistence of future atmospheric stagnation events. Nat. Clim. Change 4, 698–703 (2014).

    Article  Google Scholar 

  29. Zhang, R. et al. Chemical characterization and source apportionment of PM2.5 in Beijing: seasonal perspective. Atmos. Chem. Phys. 13, 7053–7074 (2013).

    Article  Google Scholar 

  30. Xu, M. et al. Steady decline of East Asian monsoon winds, 1969–2000: evidence from direct ground measurements of wind speed. J. Geophys. Res. 111, D24111 (2006).

    Article  Google Scholar 

  31. Kalnay, E. et al. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc. 3, 437–471 (1996).

    Article  Google Scholar 

  32. Jiang, J. et al. Particulate matter distributions in China during a winter period with frequent pollution episodes (January 2013). Aerosol Air Qual. Res. 15, 494–503 (2015).

    Article  CAS  Google Scholar 

  33. Mukherjee, A. & Toohey, D. W. A study of aerosol properties based on observations of particulate matter from the US Embassy in Beijing, China. Earth’s Future 4, 381–395 (2016).

    Article  CAS  Google Scholar 

  34. San Martini, F. M., Hasenkopf, C. A. & Roberts, D. C. Statistical analysis of PM2.5 observations from diplomatic facilities in China. Atmos. Environ. 110, 174–185 (2015).

    Article  Google Scholar 

  35. Wang, J. F., Hu, M. G., Xu, C. D., Christakos, G. & Zhao, Y. Estimation of air citywide pollution in Beijing. PLoS ONE 8, e53400 (2013).

    Article  CAS  Google Scholar 

  36. Zheng, S., Pozzer, A., Cao, C. X. & Lelieveld, J. Long-term (2001–2012) concentrations of fine particulate matter (PM2.5) and the impact on human health in Beijing, China. Atmos. Chem. Phys. 15, 5715–5725 (2015).

    Article  CAS  Google Scholar 

  37. Lorenz, E. N. Empirical Orthogonal Functions and Statistical Weather Prediction Statistical Forecast Project Report 1 (MIT Department of Meteorology, 1956).

    Google Scholar 

  38. Austin, P. C. Bootstrap methods for developing predictive models. Am. Stat. 58, 131–137 (2004).

    Article  Google Scholar 

Download references

Acknowledgements

W.C. is supported by a Greencard Professor of the Ocean University of China, the Australian Climate Change Science Program, and a CSIRO Office of Chief Executive Science Leader award. H.L. is supported by the National Basic Research Program of China (973 program, Grant No. 2014CB441202) and the National Natural Science Foundation of China under grant 91544219.

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Authors and Affiliations

  1. Physical Oceanography Laboratory/CIMSST, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Yushan Road, Qingdao 266003, China

    Wenju Cai & Lixin Wu

  2. CSIRO Oceans and Atmosphere, Aspendale, Victoria 3195, Australia

    Wenju Cai

  3. Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

    Ke Li

  4. University of Chinese Academy of Sciences, Beijing 100049, China

    Ke Li

  5. School of Environmental Science and Engineering/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China

    Hong Liao

  6. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University for Information Science and Technology, Nanjing 210044, China

    Huijun Wang

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  1. Wenju Cai
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Contributions

W.C. and H.L. conceived the study. W.C. and H.L. directed the analysis, and W.C. wrote the first draft of the paper with K.L. K.L. performed the analysis. All authors contributed to interpreting results, discussion of the associated dynamics, and improvement of this paper.

Corresponding author

Correspondence to Hong Liao.

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Cai, W., Li, K., Liao, H. et al. Weather conditions conducive to Beijing severe haze more frequent under climate change. Nature Clim Change 7, 257–262 (2017). https://doi.org/10.1038/nclimate3249

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