Substances in the atmosphere can originate from a myriad of source like industrial emissions, power generation, fossil fuel combustion, dust, forest, residential fires and forest fires. Predicting the fate and impacts of these substances in the atmosphere requires understanding their chemical, physical and optical transformation processes; this task is complicated by the fact that thousands of different types of molecules in different complexes can be found in one place, and can be distributed among several phases (gas, solid, liquid).
Work at LAPI includes the development of mechanistic models and numerical tools to characterize these complex interactions. Models are evaluated in conjunction with advanced measurement campaigns conducted in the field and experiments conducted in controlled laboratory environments. Statistical models are further used to reduce and understand the high dimensional space of measurements and simulations of atmospheric variables, and used to build predictive models of chemical composition where the mechanical predictive ability is still incomplete.
- Multiphase equilibria and aerosol acidity
- Characterization of atmospheric brown carbon
- Functional group evolution of organic aerosols
- New methods for measurement of chemical composition
Ruggeri, G. and Takahama, S. (2016) Technical Note: Development of chemoinformatic tools to enumerate functional groups in molecules for organic aerosol characterization, Atmos. Chem. Phys., 16, 4401–4422, https://doi.org/10.5194/acp-16-4401-2016.
Ruggeri et coll. (2016) Comparaison de modèle-mesure de l’abondance des groupes fonctionnels dans la formation d’aérosols organiques secondaires α-pinène et 1,3,5-triméthylbenzène, Atmos. Chem. Phys., 16, 8729–8747, doi: 10.5194 / acp-16-8729-2016
Takahama, S. et Ruggeri, G. (2017) Note technique: Relier les mesures de groupes fonctionnels aux types de carbone pour améliorer les comparaisons modèle-mesure de la composition des aérosols organiques, Atmos. Chem. Phys., 17, 4433–4450, https://doi.org/10.5194/acp-17-4433-2017.
Arangio, A., Delval, C., Ruggeri, G., Dudani, N., Yazdani, A., Takahama, S. (2019) Electrospray Film Deposition for Solvent-Elimination Infrared Spectroscopy, Appl. Spectrosc., 73 (6), 638-652, https://doi.org/10.1177/0003702818821330.