Journal article

Silicone v1.0.0: an open-source Python package for inferring missing emissions data for climate change research

Robin D Lamboll, Zebedee RJ Nicholls, Jarmo S Kikstra, Malte Meinshausen, Joeri Rogelj

GEOSCIENTIFIC MODEL DEVELOPMENT | COPERNICUS GESELLSCHAFT MBH | Published : 2020

Abstract

Integrated assessment models (IAMs) project future anthropogenic emissions which can be used as input for climate models. However, the full list of climate-relevant emissions is lengthy and most IAMs do not model all of them. Here we present Silicone, an open-source Python package which infers anthropogenic emissions of unmodelled species based on other reported emissions projections. For example, it can infer nitrous oxide emissions in one scenario based on carbon dioxide emissions from that scenario plus the relationship between nitrous oxide and carbon dioxide emissions found in other scenarios. Infilling broadens the range of IAMs available for exploring projections of future climate cha..

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Grants

Awarded by European Union


Funding Acknowledgements

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 820829 (CONSTRAIN).