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1.
Kecorius, S. et al.: Development of a cost-effective adsorption dryer for high-quality aerosol sampling. Aerosol Air Qual. Res. 24:230057 (2024)
2.
Petric, V.* et al.: Ensemble machine learning, deep learning, and time series forecasting: Improving prediction accuracy for hourly concentrations of ambient air pollutants. Aerosol Air Qual. Res. 24:230317 (2024)
3.
Popovicheva, O.* et al.: Spring aerosol in the urban atmosphere of a megacity: Analytical and statistical assessment for source impacts. Aerosol Air Qual. Res. 20, 702-719 (2020)
4.
Bukowiecki, N.* et al.: Effect of large-scale biomass burning on aerosol optical properties at the GAW regional station pha din, Vietnam. Aerosol Air Qual. Res. 19, 1172-1187 (2019)
5.
Liu, X. et al.: Analysis of PAHs associated with PM10 and PM2.5 from different districts in Nanjing. Aerosol Air Qual. Res. 19, 2294-2307 (2019)
6.
Kirchner, M. et al.: Ambient air levels of organochlorine pesticides at three high alpine monitoring stations: Trends and dependencies on geographical origin. Aerosol Air Qual. Res. 16, 738-751 (2016)
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