PARAllel FACtor analysis (PARAFAC) is used to interpret natural organic matter (NOM) fluorescence when measured using excitation emission matrix (EEM) spectroscopy. PARAFAC resolves overlapping fluorescence signals into independent spectra representing different chemical components. When fluorescence signals conform to Beers Law, this process can lead to the identification and quantification of independently varying fluorophores. However, many practical and analytical hurdles stand between EEM datasets and their chemical interpretation. This course will provide instruction on best-practice application of PARAFAC to fluorescence datasets using the drEEM toolbox for MATLAB.
This course is offered through the PhD program in Water Environment Technology at the Department of Architecture and Civil Engineering, Chalmers University of Technology. Participants who complete the course including submitting three assignments can obtain official credit (5 ETS points, Pass/Fail grade).
Topics to be covered
1. Flourescence and PARAFAC theory
2. Acquiring, importing av validating flourescence measurements
3. Data organisation
4. Checking, cleaning and preparing datasets
5. Inner filter correction
6. Modelling with PARAF
7. Diagnosing and validating PARAFAC models
1. An introductory MATLAB course or equivalent experience.
Obtaining course credit
To pass the course, you will
need to submit three assignments by final deadline.
This is an online course consisting of recorded lectures and in person discussions on Zoom. Zoom meetings are held on Mondays 8-10 am and repeated at 4-6 pm (Stockholm Time), to enable participation by students in a wide range of time zones.
The course is offered in collaboration with the Technical University of Denmark (DTU).