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Publication
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Atmospheric particulate matter (PM) has been associated with increased morbidity and mortality, reduced visibility, and is one of the least understood components of the climate system. We use the Fourier transform infrared (FT-IR) absorbance spectra of atmospheric aerosol (PM2.5) collected on Teflon filters to characterize the aerosol chemical composition using the functional group (FG) representation. Teflon filters have been collected daily at the National Air Pollution Monitoring Network (NABEL) station in Zurich (Switzerland) from the 1st of April 2016 until the 31st of March 2017. We quantify alcohol COH, carboxylic COOH, alkane CH, carbonyl CO, and amine NH functional groups of the ambient samples by fitting individual Gaussian line shapes to spectra. We compare our analysis with collocated black carbon measurements (BC) that have been apportioned to traffic emission and wood burning.
Rainer Beck, Mateusz Suchodol, Harmina Vejayan
Ivo Furno, Alan Howling, Fabio Avino, Rita Agus, Brayden Graham Myers, Lorenzo Ibba, Leonardo Zampieri
Edoardo Charbon, Claudio Bruschini, Andrei Ardelean, Paul Mos, Arin Can Ülkü, Francesco Marsili, Michael Alan Wayne