Registration
Because this course is part of a joint degree between Leiden University and TU Delft, students (also guest and exchange) have to be enrolled to both universities.
All students have to enroll for the course via Brightspace (before the start of the course) and for the exam via uSis, Leiden University. For more information see this website.
Students who are not enrolled for the MSc Industrial Ecology have to ask permission from the study advisor of Industrial Ecology to join this course, at least one month before start of the course.
Exchange students can only enroll for this course if their home university has an Exchange agreement with both Leiden University and TU Delft. Exchange students have to ask permission from the study advisor of
Industrial Ecology as soon as possible, preferably six months before the start of the course.
Description
In this course, students systematically study Environmentally-extended Input-Output Analysis (EEIOA). EEIOA is a standard methodology for assessing environmental footprints (e.g. carbon footprints) and analyzing the production and consumption structures within one or across economies. Economic and environmental analyses are inherently integrated for EEIOA.
The course is divided into two parts. The first part introduces the fundamental concepts and quantifications of EEIOA, such as the monetary and physical input-output tables and environmental footprint calculations for nations. The second part of the course introduces several advanced EEIOA techniques and illustrates how they have been used for analyzing sustainability issues, such as the socio-economic and environmental effects of international trade, and the main drivers of changing environmental pressures imposed by human activities (e.g. CO2 emissions).
The course follows a hands-on approach. Each new lecture is accompanied by an individual assignment, in which students do exercises related to the new content and develop and apply python programming skills. As a 10-EC course, the weekly study load is about 10 hours.
Learning objectives
After completing this course, students are expected to:
1. Understand the structures and key components of supply-use tables (SUTs), input-output (IO) tables, and main IO datasets.
2. Model, in Python, and analyze the economic and environmental effects of production and consumption activities and potential policies across supply chains.
3. Articulate the state-of-the-art EEIOA methods introduced in the course and their applications in sustainability research and real-world decision-making.
4. Develop and present a quantitative study using EEIOA, interpreting its main results and potential limitations.
Teaching methods/mode of instruction
In most weeks there is a single lecture to introduce the week’s new material (i.e. lecturing, 45×3=135 minutes). In the weekly Q&A session (60 minutes), theoretical and computational questions that are related to the exercises assigned in the prior week are addressed. There are 1-2 expert panel discussions on non-academic applications and opportunities of EEIOA.
Type of assessment
40% of the final grade will result from the weekly assignments, 30% from a mid-term exam, corresponding to learning objectives 1&3. The other 30% will result from a final group project to be completed at the end of the course, corresponding to learning objectives 2-4. The final assignment consists of a quantitative study in which a set of the EEIOA methods learned during the course are applied to address sustainability-related questions in a meaningful way. The specific format of the assignment is clarified during the course, as it depends on the number of students enrolled.
Course materials/reading list
The textbook for the course is ‘Input-output Analysis – Foundations and Extensions’ by Ronald E. Miller and Peter D. Blair. Reading materials (e.g. sections, chapters from the textbook or scientific papers) will be assigned for the students to go through before each lecture. The list of reading materials is available in the Manual of the course. Course materials also include lecture slides, IO datasets, and code.
Registration
Because this course is part of a joint degree between Leiden University and TU Delft, students (also guest and exchange) have to be enrolled to both universities.
All students have to enroll for the course via Brightspace (before the start of the course) and for the exam via uSis, Leiden University. For more information see this website.
Students who are not enrolled for the MSc Industrial Ecology have to ask permission from the study advisor of Industrial Ecology to join this course, at least one month before start of the course.
Exchange students can only enroll for this course if their home university has an Exchange agreement with both Leiden University and TU Delft. Exchange students have to ask permission from the study advisor of
Industrial Ecology as soon as possible, preferably six months before the start of the course.
Other remarks
We strongly recommend using the anaconda package (https://www.anaconda.com/) as the python development environment. It’s freely available for Windows, macOS, and Linux and comes with a code editor (Spyder). Likely you have been using the Anaconda package during the Earth System Science and Analysis course in Q1 of the academic year.