Cargando…
Life cycle inventory data generation by process simulation for conventional, feedstock recycling and power-to-X technologies for base chemical production
The article presents the methodology and applicable data for the generation of life cycle inventory for conventional and alternative processes for base chemical production by process simulation. Addressed base chemicals include lower olefins, BTX aromatics, methanol, ammonia and hydrogen. Assessed p...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818931/ https://www.ncbi.nlm.nih.gov/pubmed/35146084 http://dx.doi.org/10.1016/j.dib.2022.107848 |
_version_ | 1784645942185558016 |
---|---|
author | Keller, Florian Mamani Soliz, Patricio Seidl, Ludwig Georg Lee, Roh Pin Meyer, Bernd |
author_facet | Keller, Florian Mamani Soliz, Patricio Seidl, Ludwig Georg Lee, Roh Pin Meyer, Bernd |
author_sort | Keller, Florian |
collection | PubMed |
description | The article presents the methodology and applicable data for the generation of life cycle inventory for conventional and alternative processes for base chemical production by process simulation. Addressed base chemicals include lower olefins, BTX aromatics, methanol, ammonia and hydrogen. Assessed processes include conventional chemical production processes from naphtha, LPG, natural gas and heavy fuel oil; feedstock recycling technologies via gasification and pyrolysis of refuse derived fuel; and power-to-X technologies from hydrogen and CO(2). Further, process variations with additional hydrogen input are covered. Flowsheet simulation in Aspen Plus is applied to generate datasets with conclusive mass and energy balance under uniform modelling and assessment conditions with available validation data. Process inventory data is generated with no regard to the development stage of the respective technology, but applicable process data with high technology maturity is prioritized for model validation. The generated inventory data can be applied for life cycle assessments. Further, the presented modelling and balancing framework can be applied for inventory data generation of similar processes to ensure comparability in life cycle inventory data. |
format | Online Article Text |
id | pubmed-8818931 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88189312022-02-09 Life cycle inventory data generation by process simulation for conventional, feedstock recycling and power-to-X technologies for base chemical production Keller, Florian Mamani Soliz, Patricio Seidl, Ludwig Georg Lee, Roh Pin Meyer, Bernd Data Brief Data Article The article presents the methodology and applicable data for the generation of life cycle inventory for conventional and alternative processes for base chemical production by process simulation. Addressed base chemicals include lower olefins, BTX aromatics, methanol, ammonia and hydrogen. Assessed processes include conventional chemical production processes from naphtha, LPG, natural gas and heavy fuel oil; feedstock recycling technologies via gasification and pyrolysis of refuse derived fuel; and power-to-X technologies from hydrogen and CO(2). Further, process variations with additional hydrogen input are covered. Flowsheet simulation in Aspen Plus is applied to generate datasets with conclusive mass and energy balance under uniform modelling and assessment conditions with available validation data. Process inventory data is generated with no regard to the development stage of the respective technology, but applicable process data with high technology maturity is prioritized for model validation. The generated inventory data can be applied for life cycle assessments. Further, the presented modelling and balancing framework can be applied for inventory data generation of similar processes to ensure comparability in life cycle inventory data. Elsevier 2022-01-20 /pmc/articles/PMC8818931/ /pubmed/35146084 http://dx.doi.org/10.1016/j.dib.2022.107848 Text en © 2022 The Author(s). Published by Elsevier Inc. 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 Keller, Florian Mamani Soliz, Patricio Seidl, Ludwig Georg Lee, Roh Pin Meyer, Bernd Life cycle inventory data generation by process simulation for conventional, feedstock recycling and power-to-X technologies for base chemical production |
title | Life cycle inventory data generation by process simulation for conventional, feedstock recycling and power-to-X technologies for base chemical production |
title_full | Life cycle inventory data generation by process simulation for conventional, feedstock recycling and power-to-X technologies for base chemical production |
title_fullStr | Life cycle inventory data generation by process simulation for conventional, feedstock recycling and power-to-X technologies for base chemical production |
title_full_unstemmed | Life cycle inventory data generation by process simulation for conventional, feedstock recycling and power-to-X technologies for base chemical production |
title_short | Life cycle inventory data generation by process simulation for conventional, feedstock recycling and power-to-X technologies for base chemical production |
title_sort | life cycle inventory data generation by process simulation for conventional, feedstock recycling and power-to-x technologies for base chemical production |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818931/ https://www.ncbi.nlm.nih.gov/pubmed/35146084 http://dx.doi.org/10.1016/j.dib.2022.107848 |
work_keys_str_mv | AT kellerflorian lifecycleinventorydatagenerationbyprocesssimulationforconventionalfeedstockrecyclingandpowertoxtechnologiesforbasechemicalproduction AT mamanisolizpatricio lifecycleinventorydatagenerationbyprocesssimulationforconventionalfeedstockrecyclingandpowertoxtechnologiesforbasechemicalproduction AT seidlludwiggeorg lifecycleinventorydatagenerationbyprocesssimulationforconventionalfeedstockrecyclingandpowertoxtechnologiesforbasechemicalproduction AT leerohpin lifecycleinventorydatagenerationbyprocesssimulationforconventionalfeedstockrecyclingandpowertoxtechnologiesforbasechemicalproduction AT meyerbernd lifecycleinventorydatagenerationbyprocesssimulationforconventionalfeedstockrecyclingandpowertoxtechnologiesforbasechemicalproduction |