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ArchABM: An agent-based simulator of human interaction with the built environment. CO(2) and viral load analysis for indoor air quality
Recent evidence suggests that SARS-CoV-2, which is the virus causing a global pandemic in 2020, is predominantly transmitted via airborne aerosols in indoor environments. This calls for novel strategies when assessing and controlling a building’s indoor air quality (IAQ). IAQ can generally be contro...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8579709/ https://www.ncbi.nlm.nih.gov/pubmed/34785852 http://dx.doi.org/10.1016/j.buildenv.2021.108495 |
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author | Martinez, Iñigo Bruse, Jan L. Florez-Tapia, Ane M. Viles, Elisabeth Olaizola, Igor G. |
author_facet | Martinez, Iñigo Bruse, Jan L. Florez-Tapia, Ane M. Viles, Elisabeth Olaizola, Igor G. |
author_sort | Martinez, Iñigo |
collection | PubMed |
description | Recent evidence suggests that SARS-CoV-2, which is the virus causing a global pandemic in 2020, is predominantly transmitted via airborne aerosols in indoor environments. This calls for novel strategies when assessing and controlling a building’s indoor air quality (IAQ). IAQ can generally be controlled by ventilation and/or policies to regulate human–building-interaction. However, in a building, occupants use rooms in different ways, and it may not be obvious which measure or combination of measures leads to a cost- and energy-effective solution ensuring good IAQ across the entire building. Therefore, in this article, we introduce a novel agent-based simulator, ArchABM, designed to assist in creating new or adapt existing buildings by estimating adequate room sizes, ventilation parameters and testing the effect of policies while taking into account IAQ as a result of complex human–building interaction patterns. A recently published aerosol model was adapted to calculate time-dependent carbon dioxide (CO(2)) and virus quanta concentrations in each room and inhaled CO(2) and virus quanta for each occupant over a day as a measure of physiological response. ArchABM is flexible regarding the aerosol model and the building layout due to its modular architecture, which allows implementing further models, any number and size of rooms, agents, and actions reflecting human–building interaction patterns. We present a use case based on a real floor plan and working schedules adopted in our research center. This study demonstrates how advanced simulation tools can contribute to improving IAQ across a building, thereby ensuring a healthy indoor environment. |
format | Online Article Text |
id | pubmed-8579709 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85797092021-11-12 ArchABM: An agent-based simulator of human interaction with the built environment. CO(2) and viral load analysis for indoor air quality Martinez, Iñigo Bruse, Jan L. Florez-Tapia, Ane M. Viles, Elisabeth Olaizola, Igor G. Build Environ Article Recent evidence suggests that SARS-CoV-2, which is the virus causing a global pandemic in 2020, is predominantly transmitted via airborne aerosols in indoor environments. This calls for novel strategies when assessing and controlling a building’s indoor air quality (IAQ). IAQ can generally be controlled by ventilation and/or policies to regulate human–building-interaction. However, in a building, occupants use rooms in different ways, and it may not be obvious which measure or combination of measures leads to a cost- and energy-effective solution ensuring good IAQ across the entire building. Therefore, in this article, we introduce a novel agent-based simulator, ArchABM, designed to assist in creating new or adapt existing buildings by estimating adequate room sizes, ventilation parameters and testing the effect of policies while taking into account IAQ as a result of complex human–building interaction patterns. A recently published aerosol model was adapted to calculate time-dependent carbon dioxide (CO(2)) and virus quanta concentrations in each room and inhaled CO(2) and virus quanta for each occupant over a day as a measure of physiological response. ArchABM is flexible regarding the aerosol model and the building layout due to its modular architecture, which allows implementing further models, any number and size of rooms, agents, and actions reflecting human–building interaction patterns. We present a use case based on a real floor plan and working schedules adopted in our research center. This study demonstrates how advanced simulation tools can contribute to improving IAQ across a building, thereby ensuring a healthy indoor environment. Elsevier Ltd. 2022-01 2021-11-10 /pmc/articles/PMC8579709/ /pubmed/34785852 http://dx.doi.org/10.1016/j.buildenv.2021.108495 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Martinez, Iñigo Bruse, Jan L. Florez-Tapia, Ane M. Viles, Elisabeth Olaizola, Igor G. ArchABM: An agent-based simulator of human interaction with the built environment. CO(2) and viral load analysis for indoor air quality |
title | ArchABM: An agent-based simulator of human interaction with the built environment. CO(2) and viral load analysis for indoor air quality |
title_full | ArchABM: An agent-based simulator of human interaction with the built environment. CO(2) and viral load analysis for indoor air quality |
title_fullStr | ArchABM: An agent-based simulator of human interaction with the built environment. CO(2) and viral load analysis for indoor air quality |
title_full_unstemmed | ArchABM: An agent-based simulator of human interaction with the built environment. CO(2) and viral load analysis for indoor air quality |
title_short | ArchABM: An agent-based simulator of human interaction with the built environment. CO(2) and viral load analysis for indoor air quality |
title_sort | archabm: an agent-based simulator of human interaction with the built environment. co(2) and viral load analysis for indoor air quality |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8579709/ https://www.ncbi.nlm.nih.gov/pubmed/34785852 http://dx.doi.org/10.1016/j.buildenv.2021.108495 |
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