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The city of Bodø in Norway was one of the case studies in the PROVIDE project. Photo: Gerd Eichmann/Wikimedia Commons. CC BY 4.0: https://creativecommons.org/licenses/by-sa/4.0/

How much co₂ can be emitted to avoid local impacts?

Would local decision-makers be more likely to act on climate change if they knew the maximum amount of co₂ that could be emitted to avoid critical climate risk in their community? Yes, argue researchers who propose a new approach that links climate risk thresholds at local level to emission pathways.

Publishing date
17.2.2025
Key scientists

Helena Gonzales Lindberg

Impacts of climate change are increasingly being felt locally around the world, and local decision-makers need relevant information to make decisions for adaptation planning.

“It is critical that local decision-makers have information and knowledge that is founded in local realities that they can act on. We believe research must also be provided in a format that can easily be integrated into local planning and policy work and help communication on climate action”, says professor Jana Sillmann, research director at CICERO and one of the 16 authors behind the study published in Nature Geoscience.

In the paper the researchers, all part of the PROVIDE project, propose an end-user focused approach they call the reversed impact chain where they link local risk thresholds exceedance directly to global emissions benchmarks. In the reversed impact chain, scientists model the climate effects (such as daily temperatures) to the cause (emissions). Instead of comparing how impacts evolve in abstract emissions scenarios in the future, the proposed approach allows decision-makers to focus on climate impact such as heat wave intensity and storm surge levels and how those impacts would affect society.

They use three concrete examples to illustrate how this approach can work:

  • critical levels of health-related heat risk in Berlin
  • fire weather in Portugal
  • glacier mass loss in high mountain Asia.

Avoiding heat-related death and disease in Berlin in the future

What emission reductions are required to avoid a 50 percent increase in hot summer days with expected health impacts in Berlin? This was the question the researchers wanted to answer with their reversed impact chain approach. Analysis of heat-related mortality in Berlin suggests that days with average temperatures above 28 °C considerably increase heat mortality. Particularly elderly people, children and people with chronic illnesses and those in low-income households are affected.

At higher levels of global mean temperatures caused by climate change, the likelihood of hot days in Berlin increases which in turn leads to an increase in heat-related mortality. The researchers find that if the relative increase in days with 28°C averaged temperatures in Berlin should be limited to 50% in 2100 a total of 880 Gt of co₂ can be emitted until 2100.

Adaptation measures, such as greening of the city e.g. by planting more trees and ensuring sufficient green spaces, could reduce the city-average temperatures and thus increase the co₂ budget without exceed the critical threshold for health.

“Linking locally avoided impacts to emission goals could be a useful way to make the National Emission Targets more tangible to people”, said Sillmann.

Similarly, the researchers found that 440 Gt co₂ could be emitted until 2100 should Portugal stay within the 15 percent probability of 50 days with extreme fire weather and 850 Gt could be emitted for 80 percent confidence that at least 50 percent of the 2020 glacier mass would remain in High Mountain Asia.

The paper also lays out another concrete example from the urban context that can provide a concrete starting point for the reversal of the impact chain approach: A hard adaptation limit could be if a local tree species cannot live in a higher global warming level and therefore cannot be used as a nature-based urban adaptation option.

 

- Motivation for both adaptation and mitigation

The researchers note that presenting climate change information in this more tangible way for practitioners does require simplifications and assumptions and that the method might not yet be applicable for all climate impact drivers yet (e.g. tropical cyclones and convective storms).

In any case, the researchers argue that the reversed impact chain can help to make the consequences of different emissions scenarios more logically tangible and thus provide a new tool for communication at local level.

“We hope this approach can motivate local action, both for adaptation and mitigation, at the same time as it can help bridge the gap between science and policy implementation,” said Sillmann.

Focusing on avoidable climate risks can be more effective

As part of the PROVIDE project, Helena Gonzales Lindberg, senior researcher at Nordland Research Institute, conducted a case study on the Northern Norwegian city of Bodø where they have looked at how municipal planners plan for an unknown future.

“Local planners in Bodø municipality mainly work according to precautionary models”, explained Lindberg. “Although they sometimes target adaptation to a worst-case scenario, this is not always practically possible nor locally useful as there are risks of overspending when “planning too much” for events that might not happen.”

In Bodø, adapting to future climate risks has commonly been dealt with as unavoidable consequences of climate change. However, when discussing climate impacts, the local planners in Bodø noted that it can be more fruitful and effective to emphasise avoidable impacts and what the municipality can do locally to deal with them. An example of a climate risk is that peripheral parts of the municipality become totally isolated due to avalanches or slush slides. To focus on what can be done to avoid such events or prevent them from having severe consequences provides new perspectives to both planners and researchers for how to discuss and implement local adaptation measures. It also provides a new vocabulary to talk about local climate change impacts that are more pro-active and potentially more relevant to decision-makers. 

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101003687.