Climate change: a study published in PNAS proposes a new integrated approach to assessing the effectiveness, fairness and sustainability of climate policies
‘We can provide a more realistic and useful picture of how climate policies can be developed on multiple scales, increasing their effectiveness,’ says Francesco Lamperti, full professor at the Sant'Anna School of Advanced Studies in Pisa and author of the study
How can we tackle the complex challenges of climate change? One possible answer comes from a study published in the journal Proceedings of the National Academy of Sciences (PNAS), whose authors include several scholars from the Sant'Anna School of Advanced Studies in Pisa. Through the innovative and integrated use of scientific models from different disciplines, the study proposes a system capable of offering more realistic and comprehensive analyses of climate policies, overcoming the limitations of each approach taken separately.
The study, coordinated by Delft University of Technology, paves the way for new integrated paradigms for analysing the relationships between climate, economy, ecosystems and society, helping to steer climate policies towards fairer and more effective solutions capable of responding to the complexity of the current climate crisis, proposing solutions that can combine different decision-making scales.
"No single model is capable of capturing the complexity of climate-economy-energy dynamics. Through careful coupling of models with different strengths, we can provide a more realistic and useful picture of how climate policies develop across multiple scales" says Francesco Lamperti, full professor at the Institute of Economics of the Sant'Anna School of Advanced Studies and author of the study.
Combining models for better analysis of climate impacts and climate policies
Climate policy faces increasingly complex challenges that span multiple human decision-making scales in nature-society systems. Contemporary climate policy models, while valuable and increasingly versatile in managing spatial and temporal scales, struggle to represent socio-economic decisions that interact at multiple levels.
For example, local policymakers and actors on the ground cannot identify with the global scenarios used by these decision support models. As a result, Lamperti continues, "there is a wide gap between what is agreed at COPs and how climate policies can actually be implemented, whether they will be accepted by the population, and what knock-on effects (financial, interregional, etc.) they might generate".
For this reason, emissions reductions are not happening at the necessary speed and scale, while climate change-related floods and forest fires continue to break records year after year.
The study published in PNAS focuses on how to combine models from different disciplines with different temporal, spatial and decision-making scales, such as the integrated assessment models (IAMs) used in IPCC scenarios and agent-based models (ABMs). Model coupling plays a key role in analysing the efficiency, equity and consistency of policies, taking into account the interactions between individual behaviour, macroeconomic dynamics, productive sectors and decision-making processes.
"This approach - Lamperti emphasises - is essential to give momentum to climate policy and to ensure that policy makers at different levels (from local to regional, from national to European) have information that is targeted and relevant to their decisions, but at the same time consistent with the overall evolution of the system".
The study focuses on three examples in which different models are intertwined, allowing the study of dynamics that would otherwise be overlooked: i) the use of global decarbonisation trajectories for short-term macro-financial stability analysis, ii) the analysis of the effect of adaptation decisions by households on macroeconomic dynamics and employment, iii) the inclusion of political and voting preferences – and their variety – in determining international climate negotiations.
In particular, the examples of successful model coupling presented in the Perspective summarise the knowledge developed by several ERC teams: SCALAR (led by T. Filatova at TU Delft), RIPPLE (led by G. Marangoni at TU Delft), FIND (led by F. Lamperti at the Scuola Superiore Sant'Anna in Pisa, IT) and SPHINX (led by T. Filatova at TU Delft).
