Greenhouse gas emissions evaluation.

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This studentship will develop machine learning and data analysis techniques for inferring greenhouse gas emissions from in situ and satellite measurement datasets. With these methods, we aim to learn about carbon cycle feedbacks and improve transparency and accuracy of national emissions reports. Our work has been central to ensuring the continuing success of international environmental agreements such as the Montreal Protocol, by understanding the drivers of changing concentrations of greenhouse gases and ozone depleting substances, and identifying anomalous regional emissions.