If climate neutrality is a journey, what is our map?

At a time of climate crisis: the critical role of modelling in climate policymaking

To steeply cut greenhouse gas emissions, people will have to make sacrifices such as reducing carbon-intensive activities like driving. Photograph: PA/PA Wire
To steeply cut greenhouse gas emissions, people will have to make sacrifices such as reducing carbon-intensive activities like driving. Photograph: PA/PA Wire

I raise many eyebrows when I tell people that I do modelling for a living. “Energy systems modelling,” I clarify after a pause, usually causing those eyes to glaze over.

I like to think of these models as maps. Decarbonisation is a journey: even though we know the destination – climate neutrality – there are unaccountably many pathways to get there.

If we were sailors back in the Age of Exploration, we would not attempt an ocean crossing without a map, which gathered together all the best evidence available – about the tides, weather and geography – to allow us to plan a route, make best use of our skills and resources, track progress, and adjust the plan as the journey evolves.

Similarly, we are not embarking on this journey to climate neutrality without models to help plan the best pathway.

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The energy systems model we build in UCC, the TIMES-Ireland Model (not named after this newspaper) takes a “big picture” lens to understand how future energy demands, technologies and low-carbon fuel supply may interact and evolve over the coming decades, to depict different pathways to reducing fossil fuel dependence in line with carbon budgets.

Like maps, models are simplifications of a system, and there is no one perfect model. Other systems models focus on different aspects of decarbonisation such as the power system, transport network, building stock, economic activity and farming practices.

This diverse ecosystem of models forms the evidence base for climate policy, necessary to allow policymakers and society to understand different options and the multifaceted impacts on different parts of society and the economy.

As decarbonisation effort accelerates, these models will increasingly come under the spotlight.

To steeply cut greenhouse gas emissions in line with legally-adopted carbon budgets and to do our part to limit global warming, people will have to make sacrifices, such as paying for low-carbon solutions and by reducing carbon-intensive activities like driving, flying and eating red meat.

It is also likely that emissions-intensive parts of the economy will be affected, raising concern for workers and emphasising the need for a just transition.

Now, more than ever, there is an imperative that models underpinning climate policy are well resourced, fit for purpose and transparent, and in particular that they can understand how different parts of society could be negatively impacted.

There is an important parallel here with the models developed by epidemiologists, mathematicians and scientists in the Irish Epidemiological Modelling Advisory Group that informed the Government’s response to the Covid-19 pandemic: these scenarios did not prescribe policy, but were a crucial input to the Government’s decision to impose and lift lockdowns. The public rightly demanded transparency of these models, which evolved with emerging science of Covid-19.

Transparency and integrity can be ensured by making models open source, scientifically peer reviewed and clearly explained. Two-way engagement and capacity development between modellers (cartographers) and model users (map readers) is also necessary. Because just as models can be used to inform and explain, they can also be used to legitimise decisions on the basis of flawed inputs.

For example, energy systems models are rightly criticised for simplifying human behaviour, and not factoring in the potential for rapid change. They typically assume that future energy demands will keep growing like in the past – that people will keep consuming more, driving further and building and heating bigger homes – despite the growing evidence that this is not consistent with safely limiting climate change. For this reason, we have developed a new “Low Energy Demand” scenario, which demonstrates that reducing these carbon-intensive practices makes meeting Ireland’s carbon budgets far more feasible.

Similarly, a transport model can become a self-fulfilling prophecy if it is used to justify building new roads, if its parameters assume that people dislike cycling and taking public transport. By building additional roads, this dissuades people from taking sustainable transport modes.

Indeed, that people are self-interested “rational optimisers” is an assumption underpinning many economic models (ignoring evidence that people often act with solidarity and compassion), but studies have found that after studying this economic theory, students actually become less altruistic than their peers.

This is a cautionary tale: models of a system can become models for a system. Unlike pure engineering or physics, no model that depicts human behaviour, either explicitly or implicitly, is values-neutral.

Furthermore, models should be able to envisage a just transition to the world we want to create, and not simply project the past into the future. In this vein, the epigraph of the Intergovernmental Panel on Climate Change’s landmark report on limiting warming to 1.5 degrees translates roughly as follows: “Your task is not to foresee the future, but to make it happen”.

Hannah Daly is a professor of sustainable energy at UCC