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An ongoing climate change poses increasing challenges to the public interest. At the same time, digital transformation fosters the development and application of a multitude of different machine learning (ML) models. This work contains a scientific review of recent applications of ML models in the estimation and modelling of greenhouse gas emissions. We provide an overview of the main challenges and the performances of implemented methods and possibilities for future directions.