Course syllabus - Real-time Analysis in Environmental Engineering

Objectives

The objective of the course is to provide in-depth knowledge and understanding of essential principles of selected state-of-the-art real-time analytical methods in environmental engineering. The knowledge is applied to characterization of various substances and processes by optical sensors followed by analysis and interpretation of data using chemometric methods that include artificial intelligence (AI) and machine learning algorithms. The obtained models and results are then applied for control and optimization of environmental and energy processes.

Learning outcomes

1. Describe essential principles of selected state-of-the-art methods for real-time analysis in environmental engineering. ​
2. Demonstrate the ability to characterize selected substances and processes in environmental engineering. ​
3. Analyse and interpret data obtained by a given real-time analytical technique or combination of techniques. ​
4. Develop a multivariate model enabling real-time analysis in a given material flow and for process monitoring. ​
5. Evaluate how to apply the information acquired from real-time analysis in process and environmental monitoring, control and optimization. ​
6. Evaluate how selected real-time analytical techniques are currently applied in different sectors and propose potential future applications.
7. Critically evaluate how the real-time analytical techniques can contribute to sustainable development.

Course content

The course mainly addresses the following:
 - State-of-the-art real-time analytical spectroscopic methods.
- Chemometrics (data processing and interpretation) using artificial intelligence (AI) and machine learning algorithms.
- Implementation of real-time analytical techniques for process and environmental monitoring, control and optimization.

Tuition

Web-based teaching and assignments

Specific requirements

120 credits including 90 credits in engineering and/or natural science, of which 15 credits on advanced level, and 7.5 credits mathematics. In addition Swedish course B/Swedish course 3 and English course B/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.

Examination

Home examination (HEM1), 1.5 credits, grades Excellent (A), Very good (B), Good (C), Satisfactory (D), Sufficient (E), Insufficient, complementary work possible (Fx), Insufficient (F), (Learning outcomes: 1, 2, 6, 7)
Project (PRO1), 6 credits, grades Excellent (A), Very good (B), Good (C), Satisfactory (D), Sufficient (E), Insufficient, complementary work possible (Fx), Insufficient (F), (Learning outcomes: 2, 3, 4, 5, 6, 7)

A student who has a certificate from MDU regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2020/1655). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.

Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.

Grade

Excellent, Very good, Good, Satisfactory, Sufficient, Insufficient, complementary work possible, Insufficient