Forecasting national CO₂ emissions worldwide.

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 app

SUBMITTER: Costantini L 

PROVIDER: S-EPMC11439049 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature