Course syllabus adopted 2026-02-20 by Head of Programme (or corresponding).
Overview
- Swedish nameModellera framtidens klimat: vetenskap, ekonomi, etik och politik
- CodeTRA420
- Credits7.5 Credits
- OwnerTRACKS
- Education cycleSecond-cycle
- DepartmentTRACKS
- GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Course round 1
Teaching language
EnglishApplication code
97140Maximum participants
30 (at least 10% of the seats are reserved for exchange students)Minimum participants
8Open for exchange students
Yes
Credit distribution
Module | Sp1 | Sp2 | Sp3 | Sp4 | Summer | Not Sp | Examination dates |
|---|---|---|---|---|---|---|---|
| 0124 Project 7.5 c Grading: TH | 4 c | 3.5 c |
In programmes
Examiner
- Martin Persson
- Director of Studies, Environmental and Energy Sciences
Course round 3
Teaching language
EnglishApplication code
97192Open for exchange students
No
Credit distribution
Module | Sp1 | Sp2 | Sp3 | Sp4 | Summer | Not Sp | Examination dates |
|---|---|---|---|---|---|---|---|
| 0124 Project 7.5 c Grading: TH | 4 c | 3.5 c |
Examiner
Information missingEligibility
General entry requirements for Master's level (second cycle)Specific entry requirements
Applicants needs to have 90 ECTS at the time for application.English 6/B.
Course specific prerequisites
Letter of motivation.Selection is based on an overall assessment of the applicants' merits and letter of motivation.
Aim
With a core focus on integrated climate assessments the student cohort - through "Integrated Assessment modeling (IAM)" and stakeholder interaction - explore carbon pricing based on a knowledge foundation in climate science, economics, and ethical considerations. The course aims to serve as a learning lab which through practical learning activities - in connection with policymakers and stakeholders (e.g. OECD, SIDA, Volvo). The goal is to facilitate the discussion about the right price of carbon emissions for a transition to a fossil-free society. This dynamic, project-based learning environment strives to, using modeling, cultivate expertise in environmental economics and offers students an opportunity to practice contributing to evidence-based decision making in a real-world context.Learning outcomes (after completion of the course the student should be able to)
- master problems with open solutions spaces which includes being able to handle uncertainties and limited information.
- work and collaborate in interdisciplinary and/or diverse teams
- identify ethical aspects and discuss and judge their consequences in relation to a specific problem.
- show insights about, and deal with, the impact of engineering solutions in a global, economic, environmental and societal context.
- communicate and convey information, problems, methods, and development processes, both orally and in writing
- apply and interpret IAMs, assessing their strengths and limitations in the context of climate change economics and policy analysis including:
- applying core climate physics insights through modifying climate models
- model and interpret key aspects of the economics of climate change: damages, discounting, mitigation costs
- analyze and critique the integration of the natural science description of the climate physics with social science descriptions of the economic system and technological development in IAMs
- critically evaluate the ethical implications of assumptions and parameters in IAMs
- apply AI as a tool for project work and for learning in the transdisciplinary areas of the course as well as reflect on the risks and opportunities with using AI
Content
This course combines climate science, economics as well as ethical and political considerations to explore carbon pricing and emission pathways. Examples of topics included: energy balance models, damage functions, marginal abatement costs and intergenerational justice.Through collaborative projects, students will develop resources aimed at aiding policymakers and stakeholders in making informed decisions. Modelling, in different formats but mainly using IAMs of varying complexity, is a key approach to learning in the course.
Students will develop their capabilities to leverage artificial intelligence for learning and project work.
Drawing from and managing the diverse academic and professional backgrounds of course participants, students will engage in tailored explorations that build upon and complement their previous studies, ensuring a rich, interdisciplinary learning journey.
Organisation
The course is run by a teaching team.The main part of the course is a challenge driven project. Course participants will collaborate in a way that lets each years cohort define a feasible project goal that balances ambitions of learning with the practical creation of an impactful digital resource, such as online calculation tools, addressing the needs of key actors in climate policy. Engaging with an interdisciplinary expert group, students will leverage diverse skills to examine emission pathways, carbon pricing and other instruments that can lead to reduced emissions in an efficient, fair and acceptable way. In other words, students are encouraged to actively lead and affect the direction and execution of the project they take on.
The challenge may range from being of a more applied practical nature to research driven. The project work is performed in one or two project group(s). The course is supplemented by on-demand teaching and learning of the skills necessary for the project. The project team will have one university examiner, a pole of university supervisors and one or a pole of external co-supervisors if applicable.
The course will host about 10 core seminars/workshops on the core topics, methods and project of the course. In addition to these there will be an additional 3 to 4 - teacher led - course activities, to suite the chosen focus of the year's project, the interest and the expertise of the course participants. Course participants will receive formative feedback during the course and may seek feedback/input from designated project supervisors during the project period.
The course is refined each year based on feedback, and improved learning resources are further co-developed. In the same way, the project builds on last years results so that meaningful knowledge building takes place in direct interaction with the projects stakeholders.
Literature
With input from the teaching team, students will develop the ability to identify and acquire relevant literature throughout their projects. A key article for the course is: Hänsel, Martin C., et al. "Climate economics support for the UN climate targets." Nature Climate Change 10.8 (2020): 781-789, which signals the teaching team¿s established position at the knowledge frontier on the main topic of this course. We introduce the course overall objective with the En-ROADS climate solution simulator and then progress to a version of the DICE model for the main analysis and exploration of integrated assessment models. The course's digital resources (articles, video clips, weblinks etc.) will be made available using the Canvas learning platform and through a course specific AI-chatbot.Examination including compulsory elements
The examination consists of a combination of- hand-ins
- oral presentations and groups discussions
- mandatory active participation on final project presentation session
- semi-mandatory active participation on core seminars (6 of 10 needed to pass)
The course uses a Fail/3/4/5 grading system. To obtain a Pass on the whole course you will have to reach a Pass-level on all of the components listed above (or on substituting tasks). To receive a higher grade you will need to have received on average that higher grade for the individual tasks as well as have contributed to a corresponding degree to the collective outputs produced in the course.
The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers about disability study support.