Articles | Volume 22, issue 13
Research article
05 Jul 2022
Research article |  | 05 Jul 2022

Dramatic changes in atmospheric pollution source contributions for a coastal megacity in northern China from 2011 to 2020

Baoshuang Liu, Yanyang Wang, He Meng, Qili Dai, Liuli Diao, Jianhui Wu, Laiyuan Shi, Jing Wang, Yufen Zhang, and Yinchang Feng

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Cited articles

Alexander, B., Sherwen, T., Holmes, C. D., Fisher, J. A., Chen, Q., Evans, M. J., and Kasibhatla, P.: Global inorganic nitrate production mechanisms: comparison of a global model with nitrate isotope observations, Atmos. Chem. Phys., 20, 3859–3877,, 2020. 
Begum, B. A., Biswas, S. K., and Hopke, P. K.: Key issues in controlling air pollutants in Dhaka, Bangladesh, Atmos. Environ., 45, 7705–7713,, 2011. 
Beloconi, A., Probst-Hensch, N. M., and Vounatsou, P.: Spatio-temporal modelling of changes in air pollution exposure associated to the COVID-19 lockdown measures across Europe, Sci. Total Environ., 787, 147607,, 2021. 
Bi, X., Dai, Q., Wu, J., Zhang, Q., Zhang, W., Luo, R., Cheng, Y., Zhang, J., Wang, L., Yu, Z., Zhang, Y., Tian, Y., and Feng, Y.: Characteristics of the main primary source profiles of particulate matter across China from 1987 to 2017, Atmos. Chem. Phys., 19, 3223–3243,, 2019. 
Bie, S. J., Yang, L. X., Zhang, Y., Huang, Q., Li, J. S., Zhao, T., Zhang, X. F., Wang, P. C., and Wang, W. X.: Source appointment of PM2.5 in Qingdao Port, East of China, Sci. Total Environ., 755, 142456,, 2021. 
Short summary
Understanding effectiveness of air pollution regulatory measures is critical for control policy. Machine learning and dispersion-normalized approaches were applied to decouple meteorologically deduced variations in Qingdao, China. Most pollutant concentrations decreased substantially after the Clean Air Action Plan. The largest emission reduction was from coal combustion and steel-related smelting. Qingdao is at risk of increased emissions from increased vehicular population and ozone pollution.
Final-revised paper