Course syllabus for Modeling climate futures: Science, economics, ethics and policy

Course syllabus adopted 2024-04-10 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 English
  • Application code 97171
  • Minimum participants8
  • Open for exchange studentsYes

Credit distribution

0124 Project 7.5 c
Grading: TH		7.5 c

In programmes

Examiner

Go to coursepage (Opens in new tab)

Eligibility

General entry requirements for bachelor's level (first 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

The course provides a platform to work and solve challenging cross-disciplinary authentic problems from different stakeholders in society such as the academy, industry or public institutions. Additionally, the aim is that students from different educational programs practice working efficiently in multidisciplinary development teams.
With a core focus on integrated climate assessments the student cohort - through modeling 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 develops practical digital tools (or trainings) - for policymakers and stakeholders, like civil servants, policy analysts, climate negotiators, and educators - which facilitate the discussion about the right price of carbon emissions for a transition to a fossil-free society. This dynamic, project-based learning environment stives to cultivate expertise in climate economics and offers students an opportunity to practice contributing to evidence-based decision making in a real-world context, using modeling.

Learning outcomes (after completion of the course the student should be able to)

  1. master problems with open solutions spaces which includes to be able to handle uncertainties and limited information.
  2. work in multidisciplinary teams and collaborate in teams with different compositions
  3. show insights about and deal with the impact of engineering solutions in a global, economic, environment and societal context.
  4. orally and in writing explain and discuss information, problems, methods, design/development processes and solutions
  5. apply and interpret Integrated Assessment Models, assessing their strengths and limitations in the context of climate change economics and policy analysis including:
    1. applying core climate physics insights through modifying climate models
    2. model and interpret key aspects of the economics of climate change: damages, discounting, mitigation costs
    3. 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 IAM models
    4. critically evaluate the ethical implications of assumptions and parameters in integrated assessment models
  6. design and develop user-friendly, digital resources that communicate complex climate scenarios and policy implications to selected non-technical audiences, including policymakers and other key stakeholders
  7. explore and reflect on the risks and opportunities with using AI in the development and for potential use within the digital resource(s) created

Content

This course combines climate science, economics, 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 tools and resources aimed at aiding policymakers and stakeholders in making informed decisions. Modelling, in different formats but mainly using integrated assessment models of varying complexity, is a key approach to learning in the course. The questions of how to and how not to leverage artificial intelligence for learning and project work are explored. 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 year's 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 broad societal to profound 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 the course participants will collectively get to select an additional 3 to 4 - teacher led - course activities (from a list of 10 recommended), 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 on several occasions during the course and may seek feedback/input from designated project supervisors during the project period.

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.

Examination including compulsory elements

The examination consists of a combination of
  • hand-ins on individual as well as group level
  • oral presentations and groups discussions
  • mandatory active participation on final project presentation session
  • semi-mandatory active participation on core seminars (7 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 on educational support due to disability.