Boundary layer perspective assessment of air pollution status in Wuhan city from 2013 to 2017

  • Yassin Mbululo
  • Jun QinEmail author
  • Zhengxuan Yuan
  • Fatuma Nyihirani
  • Xiang Zheng


This study used daily air pollution data (PM2.5, PM10, SO2, NO2, CO, and O3) from nine monitoring stations in Wuhan city to calculate the air quality index (AQI) from 2013 to 2017. Together with this data, L-band sounding data, ground meteorological data, and air mass back trajectories were also used to describe the dynamics of atmospheric boundary layer (ABL) during pollution process. Analysis of the results shows that, even though the city is still polluted, the number of polluted days was decreasing. Ranking the years in terms of pollution status shows that the year 2013 was the most polluted year while the year 2017 was the cleanest year. Average annual limit of PM10, PM2.5, and NO2 during these 5 years were 1.3~1.8, 1.5~2.7, and 1.2~1.5 times higher than the annual average acceptable limit, respectively. The average ratio of PM2.5/PM10 for 5 years was 0.67 which signifies that a significant portion of PM2.5 accounted for the total mass of PM10. Moreover, the condition of ABL during the pollution process shows the dominance of strong ground inversion and weak to calm winds. These conditions are not favorable for horizontal and vertical mixing of air pollutants and prevent dilution of pollutants with clean air. Mean cluster analysis of air mass back trajectory shows that pollutants of local origin were more important than the trans-boundary movement of air pollutants. This indicates that the observed pollution in Wuhan was more of local origin.


Air pollution Air quality index Air pollutants Atmospheric boundary layer PM2.5 



The authors gratefully acknowledge the support of this research by the National Key Research and Development Program of China (2016YFA0602002 and 2017YFC0212603). Thanks to NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and/or READY website ( used in this study. Last but not least, we would like to express our sincere appreciation to the editorial board and two anonymous reviewers for their constructive comments, corrections and suggetions. 

Supplementary material

10661_2019_7206_MOESM1_ESM.docx (17 kb)
ESM 1 (DOCX 16 kb)


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Environmental StudiesChina University of GeosciencesWuhanChina
  2. 2.Department of Geography and Environmental Studies, Solomon Mahlangu College of Science and EducationSokoine University of AgricultureMorogoroTanzania
  3. 3.Centre for Environment, Poverty and Sustainable DevelopmentMzumbe UniversityMorogoroTanzania

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