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Global database of cement production assets and upstream suppliers
Cement producers and their investors are navigating evolving risks and opportunities as the sector’s climate and sustainability implications become more prominent. While many companies now disclose greenhouse gas emissions, the majority from carbon-intensive industries appear to delegate emissions t...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575953/ https://www.ncbi.nlm.nih.gov/pubmed/37833339 http://dx.doi.org/10.1038/s41597-023-02599-w |
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author | Tkachenko, Nataliya Tang, Kevin McCarten, Matthew Reece, Steven Kampmann, David Hickey, Conor Bayaraa, Maral Foster, Peter Layman, Courtney Rossi, Cristian Scott, Kimberly Yoken, Dave Christiaen, Christophe Caldecott, Ben |
author_facet | Tkachenko, Nataliya Tang, Kevin McCarten, Matthew Reece, Steven Kampmann, David Hickey, Conor Bayaraa, Maral Foster, Peter Layman, Courtney Rossi, Cristian Scott, Kimberly Yoken, Dave Christiaen, Christophe Caldecott, Ben |
author_sort | Tkachenko, Nataliya |
collection | PubMed |
description | Cement producers and their investors are navigating evolving risks and opportunities as the sector’s climate and sustainability implications become more prominent. While many companies now disclose greenhouse gas emissions, the majority from carbon-intensive industries appear to delegate emissions to less efficient suppliers. Recognizing this, we underscore the necessity for a globally consolidated asset-level dataset, which acknowledges production inputs provenance. Our approach not only consolidates data from established sources like development banks and governments but innovatively integrates the age of plants and the sourcing patterns of raw materials as two foundational variables of the asset-level data. These variables are instrumental in modeling cement production utilization rates, which in turn, critically influence a company’s greenhouse emissions. Our method successfully combines geospatial computer vision and Large Language Modelling techniques to ensure a comprehensive and holistic understanding of global cement production dynamics. |
format | Online Article Text |
id | pubmed-10575953 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105759532023-10-15 Global database of cement production assets and upstream suppliers Tkachenko, Nataliya Tang, Kevin McCarten, Matthew Reece, Steven Kampmann, David Hickey, Conor Bayaraa, Maral Foster, Peter Layman, Courtney Rossi, Cristian Scott, Kimberly Yoken, Dave Christiaen, Christophe Caldecott, Ben Sci Data Data Descriptor Cement producers and their investors are navigating evolving risks and opportunities as the sector’s climate and sustainability implications become more prominent. While many companies now disclose greenhouse gas emissions, the majority from carbon-intensive industries appear to delegate emissions to less efficient suppliers. Recognizing this, we underscore the necessity for a globally consolidated asset-level dataset, which acknowledges production inputs provenance. Our approach not only consolidates data from established sources like development banks and governments but innovatively integrates the age of plants and the sourcing patterns of raw materials as two foundational variables of the asset-level data. These variables are instrumental in modeling cement production utilization rates, which in turn, critically influence a company’s greenhouse emissions. Our method successfully combines geospatial computer vision and Large Language Modelling techniques to ensure a comprehensive and holistic understanding of global cement production dynamics. Nature Publishing Group UK 2023-10-13 /pmc/articles/PMC10575953/ /pubmed/37833339 http://dx.doi.org/10.1038/s41597-023-02599-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Tkachenko, Nataliya Tang, Kevin McCarten, Matthew Reece, Steven Kampmann, David Hickey, Conor Bayaraa, Maral Foster, Peter Layman, Courtney Rossi, Cristian Scott, Kimberly Yoken, Dave Christiaen, Christophe Caldecott, Ben Global database of cement production assets and upstream suppliers |
title | Global database of cement production assets and upstream suppliers |
title_full | Global database of cement production assets and upstream suppliers |
title_fullStr | Global database of cement production assets and upstream suppliers |
title_full_unstemmed | Global database of cement production assets and upstream suppliers |
title_short | Global database of cement production assets and upstream suppliers |
title_sort | global database of cement production assets and upstream suppliers |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575953/ https://www.ncbi.nlm.nih.gov/pubmed/37833339 http://dx.doi.org/10.1038/s41597-023-02599-w |
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