Examination arrangement

Course content

This course introduces the physical foundation of sustainability science. Material Flow Analysis (MFA) is a tool based on mass and energy balance principles that is used to analyze how humans satisfy 5their needs and wants by using resources from the environment and emit wastes to the environment: the anthropogenic (or socio-economic) metabolism. Analyses of the anthropogenic metabolism help industry and policy makers to understand the systemic and interconnected context of problems such as resource depletion, criticality of supply, and climate change. Well-intended sustainability interventions often have large unintended consequences. MFA is used to analyze the causalities of such problem shifts and how they can be mitigated: mathematical models and scenarios are used to test how resource use and emissions change under different conditions of consumer behavior, technology, and geopolitics. Hence, MFA models and scenarios are increasingly used by governments and businesses to test alternative strategies for circular economy, climate change mitigation, or security of supply with critical resources. The students learn how to map, model, simulate, and interpret systems using various methodological elements. These include: i) terminology, system definition, and indicator selection; ii) mathematical representation of systems; iii) mathematical representation of uncertainty, sensitivity analysis, and data reconciliation; iv) introduction to dynamic modeling; and v) use of Python and STAN software for MFA modeling. Methodology lectures are supplemented with background lectures, which introduce the students to large resource challenges related to the human activities "to nourish", "to clean", "to transport and communicate", and "to reside and work". In group exercises, the students employ MFA methodology in practical examples related to these human activities. The course includes guest lectures from industry and government and an excursion.

Lectures on the principles of dMFA and stock dynamics are complemented with introductory information on the use of Python and Jupyter Notebooks and practical exercises. In the exercises, the students work in groups of two to develop their own models and scenarios for vehicle and building stocks and interpret the results from a climate policy perspective. The students will present their intermediate and final work in a seminar. The course involves guest lectures from industry and government and an excursion.

Learning outcome

Knowledge: The students will obtain knowledge about:

- the main challenges and strategies for the socio-economic metabolism related to the basic human activities (to nourish, to clean, to transport and communicate, to reside and work);

- the theory of the socio-economic metabolism and its examination in space and time through material flow analysis (MFA).

Skills: The students will be able to:

- explain the role of key substances and materials in today's societal metabolism and their potential interactions with the environment;

- define MFA systems, and to describe a system as a mathematical model in order to test the impact of data uncertainties and to develop simple scenarios (forecasting, backcasting, analyzing implications of interventions);

- point out and reflect on strengths, limitations, and specific areas of application of different MFAs (including other industrial ecology tools that build on them), and to interpret the results in terms of their policy implications (e.g., judge the effectiveness of different interventions).

General competence: The students will:

- familiarize with the use of system approaches for solving complex problems;

- become aware of the similarities and differences between MFA and other industrial ecology tools, the types of questions they can address, and their limitations;

- learn to effectively communicate complex information with practitioners (including visual representation).

Learning methods and activities

Interactive background (2h/week) and methodology (1h/week) lectures. Five exercises are conducted in groups of 2 or 3 with the option to ask questions during exercise sessions (4h/week). The course will be taught in English and the exercises and examination papers will be given in English only.

Further on evaluation

The final grade of the course is composed of a grade given for the assignments (counts 40% to the final grade) and a written exam (counts 60% to the final grade). Assignments and written exam are graded on a scale from A-F. Assignments and exam both need to be passed individually for an overall passing grade (letter grade E or higher). If there is a re-sit examination, the examination form may be changed from written to oral. For re-take of an examination, all assessments during the course must be re-taken.

Recommended previous knowledge

Some prior exposure to Python and Jupyter Notebooks is of advantage, but not required. This course is part of the MSc. Industrial Ecology curriculum and therefore synergizes particularly well with TEP4223 (Life Cycle Assessment), TEP4300 (Climate Change Mitigation), and TEP4221 (Python for Sustainability Analysis) or equivalent but is not dependent on any prior knowledge from these.

Required previous knowledge

None.

Course materials

Brunner and Rechberger (2017): Handbook of Material Flow Analysis, CRC Press, Boca Raton, FL

The Handbook and additional course materials will be distributed electronically on Blackboard during the semester.

Credit reductions