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A dynamic risk assessment model to assess the impact of the coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry

The novel coronavirus (COVID-19) is highly detrimental, and its death distribution peculiarity has severely affected people’s health and the operations of businesses. COVID-19 has wholly undermined the global economy, including inflicting significant damage to the ever-emerging biomass supply chain;...

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Autor principal: Sajid, Zaman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8363463/
https://www.ncbi.nlm.nih.gov/pubmed/34413696
http://dx.doi.org/10.1016/j.rser.2021.111574
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author Sajid, Zaman
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description The novel coronavirus (COVID-19) is highly detrimental, and its death distribution peculiarity has severely affected people’s health and the operations of businesses. COVID-19 has wholly undermined the global economy, including inflicting significant damage to the ever-emerging biomass supply chain; its sustainability is disintegrating due to the coronavirus. The biomass supply chain must be sustainable and robust enough to adapt to the evolving and fluctuating risks of the market due to the coronavirus or any potential future pandemics. However, no such study has been performed so far. To address this issue, investigating how COVID-19 influences a biomass supply chain is vital. This paper presents a dynamic risk assessment methodological framework to model biomass supply chain risks due to COVID-19. Using a dynamic Bayesian network (DBN) formalism, the impacts of COVID-19 on the performance of biomass supply chain risks have been studied. The proposed model has been applied to the biomass supply chain of a U.S.-based Mahoney Environmental® company in Washington, USA. The case study results show that it would take one year to recover from the maximum damage to the biomass supply chain due to COVID-19, while full recovery would require five years. Results indicate that biomass feedstock gate availability (FGA) is 2%, due to pandemic and lockdown conditions. Due to the availability of vaccination and gradual business reopenings, this availability increases to 92% in the second year. Results also indicate that the price of fossil-based fuel will gradually increase after one year of the pandemic; however, the market prices of fossil-based fuel will not revert to pre-coronavirus conditions even after nine years. K-fold cross-validation is used to validate the DBN. Results of validation indicate a model accuracy of 95%. It is concluded that the pandemic has caused risks to the sustainability of biomass feedstock, and the current study can help develop risk mitigation strategies.
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spelling pubmed-83634632021-08-15 A dynamic risk assessment model to assess the impact of the coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry Sajid, Zaman Renew Sustain Energy Rev Article The novel coronavirus (COVID-19) is highly detrimental, and its death distribution peculiarity has severely affected people’s health and the operations of businesses. COVID-19 has wholly undermined the global economy, including inflicting significant damage to the ever-emerging biomass supply chain; its sustainability is disintegrating due to the coronavirus. The biomass supply chain must be sustainable and robust enough to adapt to the evolving and fluctuating risks of the market due to the coronavirus or any potential future pandemics. However, no such study has been performed so far. To address this issue, investigating how COVID-19 influences a biomass supply chain is vital. This paper presents a dynamic risk assessment methodological framework to model biomass supply chain risks due to COVID-19. Using a dynamic Bayesian network (DBN) formalism, the impacts of COVID-19 on the performance of biomass supply chain risks have been studied. The proposed model has been applied to the biomass supply chain of a U.S.-based Mahoney Environmental® company in Washington, USA. The case study results show that it would take one year to recover from the maximum damage to the biomass supply chain due to COVID-19, while full recovery would require five years. Results indicate that biomass feedstock gate availability (FGA) is 2%, due to pandemic and lockdown conditions. Due to the availability of vaccination and gradual business reopenings, this availability increases to 92% in the second year. Results also indicate that the price of fossil-based fuel will gradually increase after one year of the pandemic; however, the market prices of fossil-based fuel will not revert to pre-coronavirus conditions even after nine years. K-fold cross-validation is used to validate the DBN. Results of validation indicate a model accuracy of 95%. It is concluded that the pandemic has caused risks to the sustainability of biomass feedstock, and the current study can help develop risk mitigation strategies. Elsevier Ltd. 2021-11 2021-08-14 /pmc/articles/PMC8363463/ /pubmed/34413696 http://dx.doi.org/10.1016/j.rser.2021.111574 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
Sajid, Zaman
A dynamic risk assessment model to assess the impact of the coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry
title A dynamic risk assessment model to assess the impact of the coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry
title_full A dynamic risk assessment model to assess the impact of the coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry
title_fullStr A dynamic risk assessment model to assess the impact of the coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry
title_full_unstemmed A dynamic risk assessment model to assess the impact of the coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry
title_short A dynamic risk assessment model to assess the impact of the coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry
title_sort dynamic risk assessment model to assess the impact of the coronavirus (covid-19) on the sustainability of the biomass supply chain: a case study of a u.s. biofuel industry
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8363463/
https://www.ncbi.nlm.nih.gov/pubmed/34413696
http://dx.doi.org/10.1016/j.rser.2021.111574
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