Tackling Climate Change with System Dynamics
Figure by Mahdis Mousavi Unsplash
Understanding climate change and crafting effective responses is one of the most complex challenges of our time. Climate impacts ripple through multiple sectors—energy, agriculture, urban infrastructure—and human responses themselves feed back into this intricate web, sometimes with unintended consequences. Traditional models often fall short in capturing these deep interconnections and dynamic feedbacks.
The Horizon Europe project KNOWING addresses this complexity head-on using System Dynamics, a powerful modelling approach designed to unravel how different climate risks, mitigation measures, and adaptation strategies interact over time. By embracing feedback loops and stock-and-flow dynamics, System Dynamics allows researchers and decision-makers to explore how actions in one area may reinforce or counteract effects elsewhere, illuminating pathways toward climate resilience that account for the full system’s behavior.
In the following interview, Martin Zach from the AIT Austrian Institute of Technology—the lead of KNOWING’s modelling work package—explains how System Dynamics works, why it matters for climate action, and how it supports the project’s mission to design integrated and adaptive climate strategies.
SCC: In the KNOWING research project you try to find the best possible actions to tackle climate change. Your method of choice is called „System Dynamics“. What is System Dynamics and what makes this method so important to this project?
Zach: It’s a method to make complex systems and their behaviour over time easier to understand. Complexity is characterised by multiple causal links within a system, everything is connected to everything. This makes it difficult to apply our traditional types of models that are very accurate but address only certain parts of the system, also called sectors. Climate change brings about a variety of hazards, each of them affecting multiple sectors. Human responses to these impacts are contributing further to the complexity of the overall system.
Air conditioning is a form of maladaptation
Just consider a simple and frequently discussed example: Extreme heat days lead to dramatically increased energy demand for residential air conditioning and more and more people deciding to install often inefficient A/C systems in their homes. This does not only endanger the whole energy system, in the sense of increased risk of overload and blackouts affecting various other sectors, but also results in an increased amount of energy generation from non-renewable sources, and consequently, extra emissions of green-house gases, contributing to further increase of global temperature in the long run.
Such interactions between the involved sectors, as well as the long-term dynamics of the overall system, have to be modelled in a systematic way.
SCC: So, how does system dynamics work?
Zach: There are two basic concepts which enable us to model any large and complex system: Feedback loops, which can be reinforcing or balancing, and the introduction of Stock and Flow variables.
Understanding System Dynamics
Video: System Dynamics give a possibility to see if we really contribute towards our climate goals. Or if we might compromise mitigation by maladaptation. ©SCC
A stock variable is something that can only change over time due to in- and out-flows. Basic stock variables we may think of in the context of KNOWING will be the CO2 in the atmosphere, land use, energy of various sources, or the sea level. But also the population in a certain area and various socioeconomic variables will be represented as stock variables.
Due to the multiple causal links in our model we will have a lot of feedback loops: Almost each responsive action resulting from climate change impacts will influence various variables across sectors, ending up with some kind of feedback, reinforcing or balancing, to the driver variables.
SCC: How can you depict climate change and all the factors important to it?
Zach: The example given before on the air conditioning would represent a reinforcing feedback loop. Of course, this simple example might not be the most significant contribution, but analysing the climate impact contexts „urban heat waves“, „flooding“, and „agriculture“ in more detail over the next months we assume to identify a lot of such reinforcing feedback loops, also often called vicious circles. Some of them might dominate the long-term system behaviour, at least under certain conditions.
Vicious circles become virtous circles
The good news is that such vicious circles, once they have been identified, can be broken up by corresponding policy interventions, and even transformed into virtuous circles. Reinforcing feedback loops in complex systems are not necessarily something bad, they can also be used for supporting our path towards mitigation goals. In recent literature this is also referred to as positive tipping points.
SCC: What will you achieve with the System Dynamics Model in the KNOWING research project?
Zach: One of the primary goals of KNOWING is a modelling framework helping to understand and quantify the interactions between impacts and risks of climate change, mitigation pathways and adaptation strategies. Further, based on that framework, we will identify mitigation pathways along optimised combinations of interventions in different sectors, reconciling adaptation and mitigation. System dynamics is providing the appropriate tool set to achieve these goals, supported by the results of detailed sector models, which contain much more specific information and disaggregated data, customised for a specific pilot region.
About Martin Zach
Martin Zach has a PhD in Physics and gained several decades of experience in research and development projects, ranging from high-energy physics, ICT, management of complex systems to connected and automated mobility and climate change. He joined a multi-disciplinary team at the AIT Austrian Institute of Technology in 2019, developing system dynamics models for impact analysis and using them for backcasting (starting from desirable visions). In the research project KNOWING, Martin is leading the work package for developing the modelling framework, with a system dynamics model as its core.
About KNOWING
KNOWING is a Horizon Europe project that develops tools, models and participatory formats to support climate-transformation. By combining scientific analysis with local knowledge and stakeholder input, the project supports regions and sectors to understand climate risks, assess options, and design effective, inclusive pathways for change.
