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The development of input-monitoring system on biofuel economics and social welfare analysis
Biofuel production relies on stable supply of biomass which would be significantly influenced by climate-induced impacts. Since the actual agricultural outputs are relatively unpredictable in the face of uncertain environmental conditions and can only be realized in the harvest season, providing use...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10358576/ https://www.ncbi.nlm.nih.gov/pubmed/35975579 http://dx.doi.org/10.1177/00368504221118350 |
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author | Kung, Chih-Chun Zheng, Binbo Li, Hailing Kung, Shan-Shan |
author_facet | Kung, Chih-Chun Zheng, Binbo Li, Hailing Kung, Shan-Shan |
author_sort | Kung, Chih-Chun |
collection | PubMed |
description | Biofuel production relies on stable supply of biomass which would be significantly influenced by climate-induced impacts. Since the actual agricultural outputs are relatively unpredictable in the face of uncertain environmental conditions and can only be realized in the harvest season, providing useful information regarding the stability of biomass supply to the downstream biofuel industry is crucial. This study firstly illustrates a theoretical framework to explore the resultant market equilibrium and optimal conditions of agricultural and bioenergy production in the face of highly uncertain environmental risks and then employs a two-stage stochastic programming model to investigate the optimal biofuel development and associated economic and environmental effects. The results show that total welfare may not always increase because the loss of other agricultural commodities induced by climate impacts may be greater than the gains received by biofuel production and emission reduction. This study provides insights into the area where artificial intelligence monitoring system can be implemented to analyze the input data associated with agricultural activities and help the biofuel industry to improve its production possibilities. |
format | Online Article Text |
id | pubmed-10358576 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-103585762023-08-09 The development of input-monitoring system on biofuel economics and social welfare analysis Kung, Chih-Chun Zheng, Binbo Li, Hailing Kung, Shan-Shan Sci Prog Applying Artificial Intelligence Techniques to Encourage Economic Growth and Maintain Sustainable Societies Biofuel production relies on stable supply of biomass which would be significantly influenced by climate-induced impacts. Since the actual agricultural outputs are relatively unpredictable in the face of uncertain environmental conditions and can only be realized in the harvest season, providing useful information regarding the stability of biomass supply to the downstream biofuel industry is crucial. This study firstly illustrates a theoretical framework to explore the resultant market equilibrium and optimal conditions of agricultural and bioenergy production in the face of highly uncertain environmental risks and then employs a two-stage stochastic programming model to investigate the optimal biofuel development and associated economic and environmental effects. The results show that total welfare may not always increase because the loss of other agricultural commodities induced by climate impacts may be greater than the gains received by biofuel production and emission reduction. This study provides insights into the area where artificial intelligence monitoring system can be implemented to analyze the input data associated with agricultural activities and help the biofuel industry to improve its production possibilities. SAGE Publications 2022-08-17 /pmc/articles/PMC10358576/ /pubmed/35975579 http://dx.doi.org/10.1177/00368504221118350 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Applying Artificial Intelligence Techniques to Encourage Economic Growth and Maintain Sustainable Societies Kung, Chih-Chun Zheng, Binbo Li, Hailing Kung, Shan-Shan The development of input-monitoring system on biofuel economics and social welfare analysis |
title | The development of input-monitoring system on biofuel economics and social welfare analysis |
title_full | The development of input-monitoring system on biofuel economics and social welfare analysis |
title_fullStr | The development of input-monitoring system on biofuel economics and social welfare analysis |
title_full_unstemmed | The development of input-monitoring system on biofuel economics and social welfare analysis |
title_short | The development of input-monitoring system on biofuel economics and social welfare analysis |
title_sort | development of input-monitoring system on biofuel economics and social welfare analysis |
topic | Applying Artificial Intelligence Techniques to Encourage Economic Growth and Maintain Sustainable Societies |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10358576/ https://www.ncbi.nlm.nih.gov/pubmed/35975579 http://dx.doi.org/10.1177/00368504221118350 |
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