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    Academic Journals

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• A new machine-learning-based analysis for improving satellite-retrieved atmospheric composition data: OMI SO.sub.2 as an example.

  Authors:Can Li, Joanna Joiner, Fei Liu, Nickolay A. Krotkov, Vitali Fioletov, and Chris McLindenFrom:Atmospheric Measurement Techniques (Vol. 15, Issue 18) Peer-Reviewed

  Sept. 27, 2022457 words Article Despite recent progress, satellite retrievals of anthropogenic SO.sub.2 still suffer from relatively low signal-to-noise ratios. In this study, we demonstrate a new machine learning data analysis method to improve the...

• Towards vertical wind and turbulent flux estimation with multicopter uncrewed aircraft systems.

  Authors:Norman Wildmann and Tamino WetzFrom:Atmospheric Measurement Techniques (Vol. 15, Issue 18) Peer-Reviewed

  Sept. 27, 2022232 words Brief article Vertical wind velocity and its fluctuations are essential parameters in the atmospheric boundary layer (ABL) to determine turbulent fluxes and scaling parameters for ABL processes. The typical instrument to measure...

• Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison.

  Authors:Marta Via, Gang Chen, Francesco Canonaco, Kaspar R. Daellenbach, Benjamin Chazeau, Hasna Chebaicheb, et al.From:Atmospheric Measurement Techniques (Vol. 15, Issue 18) Peer-Reviewed

  Sept. 27, 2022450 words Article Particulate matter (PM) has become a major concern in terms of human health and climate impact. In particular, the source apportionment (SA) of organic aerosols (OA) present in submicron particles (PM.sub.1) has gained...