Causal Inference and Machine Learning in Climate Studies: Predicting Carbon Emissions and Assessing The Impact of Volcanic Eruptions

Climate change has been of global concerns, on which carbon emissions have a significant impact. Predicting carbon emissions precisely is crucial and the application of machine learning provides an effective and efficient tool to tackle the social science problems of this kind. In this paper, we demonstrated that machine learning is powerful in assisting social workers to draw inference from data. We firstly took Whether Volcanic Eruptions Impact Carbon Concentration in the Atmosphere as a case study and structured this long-time question into a machine learning problem. Secondly, we demonstrated the way to integrate machine learning techniques into social science studies. This study aims to enlighten fellow social scientists, especially those who are in the environmental science field, on how to use machine learning in their studies, and how to accurately interpret the results. We successfully built the model of volcanic eruptions impact on climate change, based on casual inference methodology.