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Industrial carbon emission intensity: A comprehensive dataset of European regions

The dataset has been developed within the framework of the EU EIT-Climate Kic Flagship Project “Re-Industrialise” and it includes data of Carbon Emission Intensity (CEI) from industrial sources for the European Regions. CEI is considered as a proxy for analysing the Industrial Sustainability Transit...

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Autores principales: Mura, Matteo, Longo, Mariolina, Toschi, Laura, Zanni, Sara, Visani, Franco, Bianconcini, Silvia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113706/
https://www.ncbi.nlm.nih.gov/pubmed/34013002
http://dx.doi.org/10.1016/j.dib.2021.107046
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author Mura, Matteo
Longo, Mariolina
Toschi, Laura
Zanni, Sara
Visani, Franco
Bianconcini, Silvia
author_facet Mura, Matteo
Longo, Mariolina
Toschi, Laura
Zanni, Sara
Visani, Franco
Bianconcini, Silvia
author_sort Mura, Matteo
collection PubMed
description The dataset has been developed within the framework of the EU EIT-Climate Kic Flagship Project “Re-Industrialise” and it includes data of Carbon Emission Intensity (CEI) from industrial sources for the European Regions. CEI is considered as a proxy for analysing the Industrial Sustainability Transition pathways and is calculated as the ratio between CO2 equivalent emissions (CO2(e)) and Gross Domestic Product (GDP) of the industrial sector over a nine-year timespan, i.e. from 2008 to 2016. CO2(e) data at plant level have been retrieved from EU Emission Trading System (EU ETS) register and aggregated at different geographical scales, corresponding to the nested structure of NUTS (Nomenclature of Territorial Units for Statistics), proposed by EUROSTAT. Industrial GDP data have been selected from EUROSTAT database to match the industrial sectors covered by EU ETS.
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spelling pubmed-81137062021-05-18 Industrial carbon emission intensity: A comprehensive dataset of European regions Mura, Matteo Longo, Mariolina Toschi, Laura Zanni, Sara Visani, Franco Bianconcini, Silvia Data Brief Data Article The dataset has been developed within the framework of the EU EIT-Climate Kic Flagship Project “Re-Industrialise” and it includes data of Carbon Emission Intensity (CEI) from industrial sources for the European Regions. CEI is considered as a proxy for analysing the Industrial Sustainability Transition pathways and is calculated as the ratio between CO2 equivalent emissions (CO2(e)) and Gross Domestic Product (GDP) of the industrial sector over a nine-year timespan, i.e. from 2008 to 2016. CO2(e) data at plant level have been retrieved from EU Emission Trading System (EU ETS) register and aggregated at different geographical scales, corresponding to the nested structure of NUTS (Nomenclature of Territorial Units for Statistics), proposed by EUROSTAT. Industrial GDP data have been selected from EUROSTAT database to match the industrial sectors covered by EU ETS. Elsevier 2021-04-10 /pmc/articles/PMC8113706/ /pubmed/34013002 http://dx.doi.org/10.1016/j.dib.2021.107046 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Mura, Matteo
Longo, Mariolina
Toschi, Laura
Zanni, Sara
Visani, Franco
Bianconcini, Silvia
Industrial carbon emission intensity: A comprehensive dataset of European regions
title Industrial carbon emission intensity: A comprehensive dataset of European regions
title_full Industrial carbon emission intensity: A comprehensive dataset of European regions
title_fullStr Industrial carbon emission intensity: A comprehensive dataset of European regions
title_full_unstemmed Industrial carbon emission intensity: A comprehensive dataset of European regions
title_short Industrial carbon emission intensity: A comprehensive dataset of European regions
title_sort industrial carbon emission intensity: a comprehensive dataset of european regions
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113706/
https://www.ncbi.nlm.nih.gov/pubmed/34013002
http://dx.doi.org/10.1016/j.dib.2021.107046
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