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M-GRCT: A Dynamic Circular Economy Model for the Optimal Design of Waste Management Systems in Low-Income Municipalities

This article introduces M-GRCT, a circular economy decision support model for the design of recyclable waste management systems in low-income municipalities. The model allows for performing calculations on a set of two scenarios integrating a sociocultural dynamics assessment, this being a character...

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Detalles Bibliográficos
Autores principales: Vargas-Terranova, Camilo-A., Rodrigo-Ilarri, Javier, Rodrigo-Clavero, María-Elena, Rozo-Arango, Miguel-A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8910470/
https://www.ncbi.nlm.nih.gov/pubmed/35270375
http://dx.doi.org/10.3390/ijerph19052681
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author Vargas-Terranova, Camilo-A.
Rodrigo-Ilarri, Javier
Rodrigo-Clavero, María-Elena
Rozo-Arango, Miguel-A.
author_facet Vargas-Terranova, Camilo-A.
Rodrigo-Ilarri, Javier
Rodrigo-Clavero, María-Elena
Rozo-Arango, Miguel-A.
author_sort Vargas-Terranova, Camilo-A.
collection PubMed
description This article introduces M-GRCT, a circular economy decision support model for the design of recyclable waste management systems in low-income municipalities. The model allows for performing calculations on a set of two scenarios integrating a sociocultural dynamics assessment, this being a characteristic feature of this type of municipalities. The model also integrates the analysis of the remaining variables usually addressed in solid waste management schemes while considering topics such as reduction of the carbon footprint due to activities such as the transport of recyclable waste, the generation of leachates, the generation of greenhouse gases and the promotion of an increase in the number of associated recyclers and selective routes. The economic evaluation of the different implementation scenarios is supported by a dynamic tool called DATA4 (a macro-type array accompanied by two control panels programmed in Visual Basic and dashboards by Power BI). M-GRCT constitutes a tool for the promotion of good environmental practices and the identification of strategies for the promotion of local development mechanisms. Results provided by the model contrast with those obtained by traditional linear economy approaches. An illustrative example of the application of the M-GRCT model is shown. The model was used to simulate the municipal solid waste managing system of the municipality of Guateque (Colombia). The results show the importance of integrating both economic and environmental costs to optimally allocate governmental and private resources when the recycling rate is expected to increase in the next 10 years.
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spelling pubmed-89104702022-03-11 M-GRCT: A Dynamic Circular Economy Model for the Optimal Design of Waste Management Systems in Low-Income Municipalities Vargas-Terranova, Camilo-A. Rodrigo-Ilarri, Javier Rodrigo-Clavero, María-Elena Rozo-Arango, Miguel-A. Int J Environ Res Public Health Article This article introduces M-GRCT, a circular economy decision support model for the design of recyclable waste management systems in low-income municipalities. The model allows for performing calculations on a set of two scenarios integrating a sociocultural dynamics assessment, this being a characteristic feature of this type of municipalities. The model also integrates the analysis of the remaining variables usually addressed in solid waste management schemes while considering topics such as reduction of the carbon footprint due to activities such as the transport of recyclable waste, the generation of leachates, the generation of greenhouse gases and the promotion of an increase in the number of associated recyclers and selective routes. The economic evaluation of the different implementation scenarios is supported by a dynamic tool called DATA4 (a macro-type array accompanied by two control panels programmed in Visual Basic and dashboards by Power BI). M-GRCT constitutes a tool for the promotion of good environmental practices and the identification of strategies for the promotion of local development mechanisms. Results provided by the model contrast with those obtained by traditional linear economy approaches. An illustrative example of the application of the M-GRCT model is shown. The model was used to simulate the municipal solid waste managing system of the municipality of Guateque (Colombia). The results show the importance of integrating both economic and environmental costs to optimally allocate governmental and private resources when the recycling rate is expected to increase in the next 10 years. MDPI 2022-02-25 /pmc/articles/PMC8910470/ /pubmed/35270375 http://dx.doi.org/10.3390/ijerph19052681 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Vargas-Terranova, Camilo-A.
Rodrigo-Ilarri, Javier
Rodrigo-Clavero, María-Elena
Rozo-Arango, Miguel-A.
M-GRCT: A Dynamic Circular Economy Model for the Optimal Design of Waste Management Systems in Low-Income Municipalities
title M-GRCT: A Dynamic Circular Economy Model for the Optimal Design of Waste Management Systems in Low-Income Municipalities
title_full M-GRCT: A Dynamic Circular Economy Model for the Optimal Design of Waste Management Systems in Low-Income Municipalities
title_fullStr M-GRCT: A Dynamic Circular Economy Model for the Optimal Design of Waste Management Systems in Low-Income Municipalities
title_full_unstemmed M-GRCT: A Dynamic Circular Economy Model for the Optimal Design of Waste Management Systems in Low-Income Municipalities
title_short M-GRCT: A Dynamic Circular Economy Model for the Optimal Design of Waste Management Systems in Low-Income Municipalities
title_sort m-grct: a dynamic circular economy model for the optimal design of waste management systems in low-income municipalities
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8910470/
https://www.ncbi.nlm.nih.gov/pubmed/35270375
http://dx.doi.org/10.3390/ijerph19052681
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