Theories and Tools for Climate Policy Exploration
(yet another grant application)
I've just submitted a grant proposal about "Theories and Tools for Climate Policy Exploration" to FORMAS (a government research council for sustainable development). If funded, it would mean a team consisting of me, Nicola Botta, a post-doc, and two student research assistants will start working on this by the end on 2026.
PopSci description (shortened):
The climate crisis demands urgent action. But which actions are best?
Decision makers face tough trade-offs:
Policy A lowers emissions at home but increases reliance on imports.
Policy B cuts emissions long-term but raises unemployment short-term.
Policy C boosts jobs now but increases emissions in the near term.
None of these choices are simple. A policy that looks good locally may increase global emissions, or its effects may depend on what other countries do. And sometimes policies cancel each other out.
The key point: climate policy is full of hard trade-offs. Technology can’t decide them — but it can help us (and policy-makers) understand them better.
That’s the goal of our new project (proposal): building open-source computational tools that let decision makers explore climate policies under uncertainty, weigh different values, and see trade-offs clearly.
PopSci description (shortened):
The climate crisis demands urgent action. But which actions are best?
Decision makers face tough trade-offs:
Policy A lowers emissions at home but increases reliance on imports.
Policy B cuts emissions long-term but raises unemployment short-term.
Policy C boosts jobs now but increases emissions in the near term.
None of these choices are simple. A policy that looks good locally may increase global emissions, or its effects may depend on what other countries do. And sometimes policies cancel each other out.
The key point: climate policy is full of hard trade-offs. Technology can’t decide them — but it can help us (and policy-makers) understand them better.
That’s the goal of our new project (proposal): building open-source computational tools that let decision makers explore climate policies under uncertainty, weigh different values, and see trade-offs clearly.
Abstract:
The latest IPCC report clearly shows that avoiding unmanageable consequences of climate change requires a profound transformation in how we produce, transport, and consume energy, goods, and services. Yet, the report provides limited guidance on which concrete climate policies can promote and sustain such a transformation over the coming decades. Designing fair carbon taxes, effective emission-trading schemes, or regulatory interventions is inherently challenging, and poorly anticipated measures can even increase emissions in the short term.
A transformation towards a fossil-fuel-free society must itself be sustainable: it must achieve climate targets while safeguarding the prosperity of future generations. Doing so requires decision processes that are open, iterative, and rigorous, integrating climate science, empirical data, domain expertise, and insights from stylized decision problems. Even very simple stylized problems, such as the Prisoner’s dilemma, illustrate fundamental challenges in climate policy, including free-riding or delayed action, and highlight how different assumptions and uncertainties shape possible outcomes.
This project develops and applies computational methods for multi-objective decision problems under uncertainty, with an emphasis on rigor, transparency, and correctness. Our methodology builds on formal specifications, domain-specific languages, and verified algorithms that enable decision makers and advisors to explore the consequences of different assumptions and trade-offs systematically. In particular, the project focuses on three research questions:
WP1: How can stylized decision processes be formally encoded and reasoned about?
WP2: How can preferences and conflicting objectives be expressed and optimized reliably?
WP3: How can alternative policies be explored in a manner that is rigorous, reproducible, and trustworthy?
The project will produce open-source tools for specifying and computing solutions to multi-objective decision problems under uncertainty. These tools will make all underlying assumptions explicit, ensure correctness by construction, and provide a systematic way to understand trade-offs between competing objectives. By enabling domain experts and policy advisors to reason clearly about these trade-offs, the project aims to support more informed and accountable climate policy decisions, contributing to climate action (SDG 13), sustainable cities (SDG 11), and quality education (SDG 4).
The latest IPCC report clearly shows that avoiding unmanageable consequences of climate change requires a profound transformation in how we produce, transport, and consume energy, goods, and services. Yet, the report provides limited guidance on which concrete climate policies can promote and sustain such a transformation over the coming decades. Designing fair carbon taxes, effective emission-trading schemes, or regulatory interventions is inherently challenging, and poorly anticipated measures can even increase emissions in the short term.
A transformation towards a fossil-fuel-free society must itself be sustainable: it must achieve climate targets while safeguarding the prosperity of future generations. Doing so requires decision processes that are open, iterative, and rigorous, integrating climate science, empirical data, domain expertise, and insights from stylized decision problems. Even very simple stylized problems, such as the Prisoner’s dilemma, illustrate fundamental challenges in climate policy, including free-riding or delayed action, and highlight how different assumptions and uncertainties shape possible outcomes.
This project develops and applies computational methods for multi-objective decision problems under uncertainty, with an emphasis on rigor, transparency, and correctness. Our methodology builds on formal specifications, domain-specific languages, and verified algorithms that enable decision makers and advisors to explore the consequences of different assumptions and trade-offs systematically. In particular, the project focuses on three research questions:
WP1: How can stylized decision processes be formally encoded and reasoned about?
WP2: How can preferences and conflicting objectives be expressed and optimized reliably?
WP3: How can alternative policies be explored in a manner that is rigorous, reproducible, and trustworthy?
The project will produce open-source tools for specifying and computing solutions to multi-objective decision problems under uncertainty. These tools will make all underlying assumptions explicit, ensure correctness by construction, and provide a systematic way to understand trade-offs between competing objectives. By enabling domain experts and policy advisors to reason clearly about these trade-offs, the project aims to support more informed and accountable climate policy decisions, contributing to climate action (SDG 13), sustainable cities (SDG 11), and quality education (SDG 4).