A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector

Autores
Verrengia, María de los Milagros; Vecchietti, Aldo Rodomiro
Año de publicación
2022
Idioma
inglés
Tipo de recurso
parte de libro
Estado
versión publicada
Descripción
This article presents a mathematical model of the soybean´s supply chain for Argentina where the different stakeholders and the material flows among them are represented. The transport used in this sector are trucks, trains, and river ships. The objective is to analyze the emissions of greenhouse gases (GHG) generated by the transportation in this sector using electric trucks as an alternative to biodiesel ones. The model generated is a mixed multi-period / multi-objective linear integer model, destined at minimizing operating and GHG emissions cost. The accuracy of the model is compared against two statistical studies made by the Transport Agency of Argentina in 2014 and 2017 regarding the soybean transportation. The results show a good fit with those reports. Two scenarios are compared, in the first one only biodiesel trucks are used for transportation, while in the second one trains, barges and electric trucks are included. Results show the tradeoff between investment costs and reduction of emissions where it is possible to achieve a 60% GHG decrease, which is far to compensate for the investment cost.
Trabajo presentado en el 32nd European Symposium on Computer Aided Process Engineering – ESCAPE-32 y publicado en Computer Aided Chemical Engineering (Vol. 51).
Fil: Vecchietti, Aldo Rodomiro. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.
Fil: Verrengia, María de los Milagros. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.
Peer Reviewed
Materia
Soybean
Supply chain
Emissions
Transportation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
Attribution 4.0 International
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/13177
Acceder
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network_name_str Repositorio Institucional Abierto (UTN)
spelling A soybean supply chain model to analyze the greenhouse gas emissions of the transport sectorVerrengia, María de los MilagrosVecchietti, Aldo RodomiroSoybeanSupply chainEmissionsTransportationThis article presents a mathematical model of the soybean´s supply chain for Argentina where the different stakeholders and the material flows among them are represented. The transport used in this sector are trucks, trains, and river ships. The objective is to analyze the emissions of greenhouse gases (GHG) generated by the transportation in this sector using electric trucks as an alternative to biodiesel ones. The model generated is a mixed multi-period / multi-objective linear integer model, destined at minimizing operating and GHG emissions cost. The accuracy of the model is compared against two statistical studies made by the Transport Agency of Argentina in 2014 and 2017 regarding the soybean transportation. The results show a good fit with those reports. Two scenarios are compared, in the first one only biodiesel trucks are used for transportation, while in the second one trains, barges and electric trucks are included. Results show the tradeoff between investment costs and reduction of emissions where it is possible to achieve a 60% GHG decrease, which is far to compensate for the investment cost. Trabajo presentado en el 32nd European Symposium on Computer Aided Process Engineering – ESCAPE-32 y publicado en Computer Aided Chemical Engineering (Vol. 51).Fil: Vecchietti, Aldo Rodomiro. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.Fil: Verrengia, María de los Milagros. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.Peer ReviewedComputer Aided Chemical Engineering (Book Series)2025-06-05T18:48:59Z2022-05-12info:eu-repo/semantics/bookPartinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_3248info:ar-repo/semantics/parteDeLibropdfapplication/pdfVerrengia, M.M., & Vecchietti, A.R. (2022). A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector. En: Computer Aided Chemical Engineering (Vol. 51, pp. 1327–1332). Elsevier. https://doi.org/10.1016/B978-0-323-95879-0.50222-8https://hdl.handle.net/20.500.12272/13177https://doi.org/10.1016/B978-0-323-95879-0.50222-8engSITCAFE0008418TCModelado de la Cadena de Suministro de da Industria de da Soja en Argentina con Técnicas de Programación Matemática y Ciencia de Datosinfo:eu-repo/semantics/openAccessAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/Los autoresCreativeCommonsreponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-09-24T12:45:09Zoai:ria.utn.edu.ar:20.500.12272/13177instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:45:10.187Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector
title A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector
spellingShingle A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector
Verrengia, María de los Milagros
Soybean
Supply chain
Emissions
Transportation
title_short A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector
title_full A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector
title_fullStr A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector
title_full_unstemmed A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector
title_sort A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector
dc.creator.none.fl_str_mv Verrengia, María de los Milagros
Vecchietti, Aldo Rodomiro
author Verrengia, María de los Milagros
author_facet Verrengia, María de los Milagros
Vecchietti, Aldo Rodomiro
author_role author
author2 Vecchietti, Aldo Rodomiro
author2_role author
dc.subject.none.fl_str_mv Soybean
Supply chain
Emissions
Transportation
topic Soybean
Supply chain
Emissions
Transportation
dc.description.none.fl_txt_mv This article presents a mathematical model of the soybean´s supply chain for Argentina where the different stakeholders and the material flows among them are represented. The transport used in this sector are trucks, trains, and river ships. The objective is to analyze the emissions of greenhouse gases (GHG) generated by the transportation in this sector using electric trucks as an alternative to biodiesel ones. The model generated is a mixed multi-period / multi-objective linear integer model, destined at minimizing operating and GHG emissions cost. The accuracy of the model is compared against two statistical studies made by the Transport Agency of Argentina in 2014 and 2017 regarding the soybean transportation. The results show a good fit with those reports. Two scenarios are compared, in the first one only biodiesel trucks are used for transportation, while in the second one trains, barges and electric trucks are included. Results show the tradeoff between investment costs and reduction of emissions where it is possible to achieve a 60% GHG decrease, which is far to compensate for the investment cost.
Trabajo presentado en el 32nd European Symposium on Computer Aided Process Engineering – ESCAPE-32 y publicado en Computer Aided Chemical Engineering (Vol. 51).
Fil: Vecchietti, Aldo Rodomiro. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.
Fil: Verrengia, María de los Milagros. CONICET-UTN. Instituto de desarrollo y diseño (INGAR); Argentina.
Peer Reviewed
description This article presents a mathematical model of the soybean´s supply chain for Argentina where the different stakeholders and the material flows among them are represented. The transport used in this sector are trucks, trains, and river ships. The objective is to analyze the emissions of greenhouse gases (GHG) generated by the transportation in this sector using electric trucks as an alternative to biodiesel ones. The model generated is a mixed multi-period / multi-objective linear integer model, destined at minimizing operating and GHG emissions cost. The accuracy of the model is compared against two statistical studies made by the Transport Agency of Argentina in 2014 and 2017 regarding the soybean transportation. The results show a good fit with those reports. Two scenarios are compared, in the first one only biodiesel trucks are used for transportation, while in the second one trains, barges and electric trucks are included. Results show the tradeoff between investment costs and reduction of emissions where it is possible to achieve a 60% GHG decrease, which is far to compensate for the investment cost.
publishDate 2022
dc.date.none.fl_str_mv 2022-05-12
2025-06-05T18:48:59Z
dc.type.none.fl_str_mv info:eu-repo/semantics/bookPart
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_3248
info:ar-repo/semantics/parteDeLibro
format bookPart
status_str publishedVersion
dc.identifier.none.fl_str_mv Verrengia, M.M., & Vecchietti, A.R. (2022). A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector. En: Computer Aided Chemical Engineering (Vol. 51, pp. 1327–1332). Elsevier. https://doi.org/10.1016/B978-0-323-95879-0.50222-8
https://hdl.handle.net/20.500.12272/13177
https://doi.org/10.1016/B978-0-323-95879-0.50222-8
identifier_str_mv Verrengia, M.M., & Vecchietti, A.R. (2022). A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector. En: Computer Aided Chemical Engineering (Vol. 51, pp. 1327–1332). Elsevier. https://doi.org/10.1016/B978-0-323-95879-0.50222-8
url https://hdl.handle.net/20.500.12272/13177
https://doi.org/10.1016/B978-0-323-95879-0.50222-8
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv SITCAFE0008418TC
Modelado de la Cadena de Suministro de da Industria de da Soja en Argentina con Técnicas de Programación Matemática y Ciencia de Datos
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
Los autores
CreativeCommons
eu_rights_str_mv openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
Los autores
CreativeCommons
dc.format.none.fl_str_mv pdf
application/pdf
dc.publisher.none.fl_str_mv Computer Aided Chemical Engineering (Book Series)
publisher.none.fl_str_mv Computer Aided Chemical Engineering (Book Series)
dc.source.none.fl_str_mv reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
_version_ 1877230895053668352
score 13.24418

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