Forecasting emissions through Kaya identity using Neural Ordinary Differential Equations

• URL: http://arxiv.org/abs/2201.02433v1
• Date: Fri, 7 Jan 2022 12:34:01 GMT
• Title: Forecasting emissions through Kaya identity using Neural Ordinary Differential Equations
• Authors: Pierre Browne, Aranildo Lima, Rossella Arcucci, C\'esar Quilodr\'an-Casas
• Abstract summary: We use a Neural ODE model to predict the evolution of several indicators related to carbon emissions on a country-level. We conclude that this machine-learning approach can be used to produce a wide range of results and give relevant insight to policymakers.
• Score: 3.4901787251083163
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Starting from the Kaya identity, we used a Neural ODE model to predict the evolution of several indicators related to carbon emissions, on a country-level: population, GDP per capita, energy intensity of GDP, carbon intensity of energy. We compared the model with a baseline statistical model - VAR - and obtained good performances. We conclude that this machine-learning approach can be used to produce a wide range of results and give relevant insight to policymakers

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