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Updated: Jun 11, 2025

Using Generative Art to Convey Past and Future Climate Transitions
Published on: March 31, 2023
Forecasting national CO2 emissions worldwide
Lorenzo Costantini1,2, Francesco Laio3, Manuel Sebastian Mariani4,5
1CENTAI, Turin, Italy. lorenzo.costantini@centai.eu.
Abstract:
Urgent climate action, especially carbon emissions reduction, is required to achieve sustainable goals. Therefore, understanding the drivers of and predicting [Formula: see text] emissions is a compelling matter. We present two global modeling frameworks-a multivariate regression and a Random Forest Regressor (RFR)-to hindcast (until 2021) and forecast (up to 2035) [Formula: see text] emissions across 117 countries as driven by 12 socioeconomic indicators regarding carbon emissions, economic well-being, green and complexity economics, energy use and consumption. Our results identify key driving features to explain emissions pathways, where beyond-GDP indicators rooted in the Economic Complexity field emerge. Considering current countries' development status, divergent emission dynamics appear. According to the RFR, a -6.2% reduction is predicted for developed economies by 2035 and a +19% increase for developing ones (referring to 2020), thus stressing the need to promote green growth and sustainable development in low-capacity contexts.
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