Income and energy efficiency to drive future greenhouse gas emissions

A new study published in Nature Climate Change provides a better understanding of future long-term carbon dioxide (CO₂) emissions as a function of the evolution of different socio-economic and technical underlying forces.

CO₂ emissions from energy combustion are the biggest determinant of human-caused climate change, and have been growing over the past decades. In order to grasp where we are heading, it is therefore imperative to have a better understanding of future long-term emissions as a function of the evolution of different socio-economic and technical underlying forces.

Bringing together six different energy-economy-climate models from six different European research institutes including IIASA, the study decomposes the sensitivity of future long-term CO₂ emissions to their major drivers: population, income, energy intensity, fossil resources availability, and low carbon technologies development.

The study confronts three possible future worlds, as delineated by the Shared Socioeconomic Pathways (SSPs), a set of quantitative research scenarios that describe socioeconomic developments that would affect the challenges to mitigating and adapting to climate change. Using advanced statistical approaches, the study disentangles the impacts of each of the drivers in isolation as well as in interaction with the others.

“The results clearly point to income and energy efficiency as key determinants of future emissions,” says Giacomo Marangoni, researcher at FEEM and Politecnico di Milano in Italy and leader of the study. “Projected population seems to matter less in determining future emissions. Fossil fuel and low carbon resources rank in between. These results tend to hold across models, over different time horizons, and also in the presence of a climate policy. The different drivers interact: for example a richer world will lead to lower emission increase if it is a sustainable one, and vice versa. Neglecting these interactions would lead to inaccurate sensitivity rankings.”

Massimo Tavoni—a study coauthor, program coordinator at FEEM and faculty member at Politecnico di Milano—says that the study also helps us think about how to solve climate change. “Economic growth is a political priority and is needed, especially in emerging and developing economies. But there are policies which can make this objective compatible with lower emissions: energy efficiency and disincentives to fossil resources, especially coal, are high priorities. The alternative of high climate change would be far worse.”

The uncertainty ranges spanned by the scenario storylines and the different modelling choices in implementing them have the potential to influence several years of climate policy research to come. The study helps prioritize this research, suggesting that modelling and policy communities could benefit from shifting some of their attention from the traditional energy-supply domain also to elements like energy efficiency and economic wellbeing.

“From a scientific perspective the analysis also helps improve our understanding of how our assumptions on the future evolution of socioeconomic and technological factors influence results of model-based climate change analysis. Analyses like this one should become common practice when exploring different research questions with energy-economy-climate models,” says Volker Krey, a researcher at IIASA who contributed to the study.

Researchers from the following institutions contributed to the research: Fondazione Eni Enrico Mattei (FEEM), Politecnico di Milano, Bocconi University, National Technical University of Athens, International Institute for Applied Systems Analysis (IIASA), PBL Netherlands Environmental Assessment Agency, Utrecht University, Centre International de Recherche sur l'Environnement et le Développement (CIRED), Ecole des Ponts and University College London.

Adapted from text provided by the Fondazione Eni Enrico Mattei  (FEEM)

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Last edited: 01 March 2017