Metadata-Version: 2.1
Name: silicone
Version: 1.1.0
Summary: Automated filling of detail in reported emission scenarios
Home-page: https://github.com/GranthamImperial/silicone
Author: Robin Lamboll, Zebedee Nicholls, Jarmo Kikstra, Gaurav Ganti
Author-email: r.lamboll@imperial.ac.uk, zebedee.nicholls@climate-energy-college.org, kikstra@iiasa.ac.at, gaurav.ganti@climateanalytics.org
License: 3-Clause BSD License
Project-URL: Bug Reports, https://github.com/GranthamImperial/silicone/issues
Project-URL: Documentation, https://silicone.readthedocs.io/en/latest
Project-URL: Source, https://github.com/GranthamImperial/silicone
Keywords: emissions,automation,filling,detail,climate
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/x-rst
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Silicone
========

.. sec-begin-index


Silicone is a Python package which can be used to infer emissions from other emissions data.
It is intended to 'infill' integrated assessment model (IAM) data so that their scenarios
quantify more climate-relevant emissions than are natively reported by the IAMs themselves.
It does this by comparing the incomplete emissions set to complete data from other sources.
It uses the relationships within the complete data to make informed infilling estimates of
otherwise missing emissions timeseries.
For example, it can add emissions of aerosol precurors based on carbon dioxide emissions
and infill nitrous oxide emissions based on methane, or split HFC emissions pathways into
emissions of different specific HFC gases.


.. sec-end-index

License
-------

.. sec-begin-license

Silicone is free software under a BSD 3-Clause License, see
`LICENSE <https://github.com/GranthamImperial/silicone/blob/master/LICENSE>`_.

.. sec-end-license

.. sec-begin-funders

Funders
-------
This project has received funding from the European Union Horizon 2020 research and
innovation programme under grant agreement No 820829 (CONSTRAIN) and No 641816 (CRESCENDO).

.. sec-end-funders

