Revalorización energética de los residuos sólidos municipales generados en la ciudad de Sincelejo
La gestión de Residuos Sólidos Municipales (RSM) representa un desafío mundial que requiere soluciones sostenibles e innovadoras, particularmente en las ciudades con rápido crecimiento. Con el fin de optimizar la valorización energética y minimizar el impacto ambiental, esta tesis doctoral diseña un...
- Autores:
-
Otero Meza, Daniel David
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2025
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/13944
- Acceso en línea:
- https://hdl.handle.net/11323/13944
- Palabra clave:
- Residuos sólidos municipales
Valorización energética
Análisis de decisión multicriterio
Sostenibilidad
Municipal solid waste
Waste-to-energy
Multi-criteria decision-making
Sustainability
- Rights
- closedAccess
- License
- Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
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RCUC2 |
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REDICUC - Repositorio CUC |
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| dc.title.none.fl_str_mv |
Revalorización energética de los residuos sólidos municipales generados en la ciudad de Sincelejo |
| title |
Revalorización energética de los residuos sólidos municipales generados en la ciudad de Sincelejo |
| spellingShingle |
Revalorización energética de los residuos sólidos municipales generados en la ciudad de Sincelejo Residuos sólidos municipales Valorización energética Análisis de decisión multicriterio Sostenibilidad Municipal solid waste Waste-to-energy Multi-criteria decision-making Sustainability |
| title_short |
Revalorización energética de los residuos sólidos municipales generados en la ciudad de Sincelejo |
| title_full |
Revalorización energética de los residuos sólidos municipales generados en la ciudad de Sincelejo |
| title_fullStr |
Revalorización energética de los residuos sólidos municipales generados en la ciudad de Sincelejo |
| title_full_unstemmed |
Revalorización energética de los residuos sólidos municipales generados en la ciudad de Sincelejo |
| title_sort |
Revalorización energética de los residuos sólidos municipales generados en la ciudad de Sincelejo |
| dc.creator.fl_str_mv |
Otero Meza, Daniel David |
| dc.contributor.advisor.none.fl_str_mv |
Cabello Eras, Juan José Salcedo Mendoza, Jairo Guadalupe |
| dc.contributor.author.none.fl_str_mv |
Otero Meza, Daniel David |
| dc.contributor.jury.none.fl_str_mv |
Contreras Lozano, Karen Balbis Morejón, Milen Bermejo Altamar, Fabio |
| dc.subject.proposal.spa.fl_str_mv |
Residuos sólidos municipales Valorización energética Análisis de decisión multicriterio Sostenibilidad |
| topic |
Residuos sólidos municipales Valorización energética Análisis de decisión multicriterio Sostenibilidad Municipal solid waste Waste-to-energy Multi-criteria decision-making Sustainability |
| dc.subject.proposal.eng.fl_str_mv |
Municipal solid waste Waste-to-energy Multi-criteria decision-making Sustainability |
| description |
La gestión de Residuos Sólidos Municipales (RSM) representa un desafío mundial que requiere soluciones sostenibles e innovadoras, particularmente en las ciudades con rápido crecimiento. Con el fin de optimizar la valorización energética y minimizar el impacto ambiental, esta tesis doctoral diseña una herramienta metodológica para la evaluación integral y selección de alternativas de aprovechamiento de los RSM, integrando el potencial de diversas tecnologías, la proyección de tasas de disposición y un enfoque multicriterio objetivo. La metodología combina análisis de series de tiempo, específicamente SARIMAX, para proyectar la disposición futura de RSM con rigor estadístico (pruebas de Ljung-Box, KPSS, cointegración de Johansen, Causalidad de Granger), contemplando variables exógenas clave. Asimismo, se aplica un método de decisión multicriterio basado en ENTROPY y TOPSIS, que pondera equitativamente factores técnicos, energéticos, ambientales y económicos. La aplicación de la herramienta en Sincelejo, Colombia, muestra su efectividad al identificar el relleno sanitario con captura de biogás como la opción más sólida, alineada con la aprobación de proyectos análogos por la Convención Marco de las Naciones Unidas sobre el Cambio Climático (UNFCCC). Los resultados confirman que esta solución es la más equilibrada para la ciudad, teniendo en cuenta la disponibilidad de recursos, el potencial de generación de energía, la mitigación de emisiones y la viabilidad económica. Además, la herramienta desarrollada demuestra su adaptabilidad a distintos escenarios y su utilidad para la toma de decisiones informadas, facilitando la transición hacia prácticas de economía circular y contribuyendo a la reducción del cambio climático. En suma, esta investigación aporta una solución práctica para la planificación de la gestión de RSM, fomentando un uso más eficiente de los recursos y promoviendo la sostenibilidad local y regional. |
| publishDate |
2025 |
| dc.date.accessioned.none.fl_str_mv |
2025-01-21T22:01:51Z |
| dc.date.available.none.fl_str_mv |
2025 2025-01-21T22:01:51Z |
| dc.date.issued.none.fl_str_mv |
2025 |
| dc.type.none.fl_str_mv |
Trabajo de grado - Doctorado |
| dc.type.coar.none.fl_str_mv |
http://purl.org/coar/resource_type/c_db06 |
| dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
| dc.type.redcol.none.fl_str_mv |
http://purl.org/redcol/resource_type/TD |
| dc.type.version.none.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
| format |
http://purl.org/coar/resource_type/c_db06 |
| status_str |
acceptedVersion |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/11323/13944 |
| url |
https://hdl.handle.net/11323/13944 |
| dc.language.iso.none.fl_str_mv |
spa |
| language |
spa |
| dc.relation.references.none.fl_str_mv |
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Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/closedAccesshttp://purl.org/coar/access_right/c_14cbCabello Eras, Juan JoséSalcedo Mendoza, Jairo GuadalupeOtero Meza, Daniel DavidContreras Lozano, KarenBalbis Morejón, MilenBermejo Altamar, Fabio2025-01-21T22:01:51Z20252025-01-21T22:01:51Z2025https://hdl.handle.net/11323/13944La gestión de Residuos Sólidos Municipales (RSM) representa un desafío mundial que requiere soluciones sostenibles e innovadoras, particularmente en las ciudades con rápido crecimiento. Con el fin de optimizar la valorización energética y minimizar el impacto ambiental, esta tesis doctoral diseña una herramienta metodológica para la evaluación integral y selección de alternativas de aprovechamiento de los RSM, integrando el potencial de diversas tecnologías, la proyección de tasas de disposición y un enfoque multicriterio objetivo. La metodología combina análisis de series de tiempo, específicamente SARIMAX, para proyectar la disposición futura de RSM con rigor estadístico (pruebas de Ljung-Box, KPSS, cointegración de Johansen, Causalidad de Granger), contemplando variables exógenas clave. Asimismo, se aplica un método de decisión multicriterio basado en ENTROPY y TOPSIS, que pondera equitativamente factores técnicos, energéticos, ambientales y económicos. La aplicación de la herramienta en Sincelejo, Colombia, muestra su efectividad al identificar el relleno sanitario con captura de biogás como la opción más sólida, alineada con la aprobación de proyectos análogos por la Convención Marco de las Naciones Unidas sobre el Cambio Climático (UNFCCC). Los resultados confirman que esta solución es la más equilibrada para la ciudad, teniendo en cuenta la disponibilidad de recursos, el potencial de generación de energía, la mitigación de emisiones y la viabilidad económica. Además, la herramienta desarrollada demuestra su adaptabilidad a distintos escenarios y su utilidad para la toma de decisiones informadas, facilitando la transición hacia prácticas de economía circular y contribuyendo a la reducción del cambio climático. En suma, esta investigación aporta una solución práctica para la planificación de la gestión de RSM, fomentando un uso más eficiente de los recursos y promoviendo la sostenibilidad local y regional.The management of Municipal Solid Waste (MSW) presents a global challenge that requires sustainable and innovative solutions, particularly in rapidly growing cities. In order to optimize energy recovery and minimize environmental impact, this doctoral thesis develops a methodological tool for the comprehensive evaluation and selection of MSW utilization alternatives, integrating the potential of various technologies, projected disposal rates, and an objective multicriteria approach. The methodology combines time series analyses, specifically SARIMAX, to project future MSW disposal with statistical rigor (Ljung-Box, KPSS, Johansen cointegration, Granger causality), considering key exogenous variables. In addition, a multicriteria decision-making method based on ENTROPY and TOPSIS is applied, equally weighting technical, energy-related, environmental, and economic factors. The application of this tool in Sincelejo, Colombia, demonstrates its effectiveness by identifying a sanitary landfill with biogas capture as the most robust option, in line with the approval of similar projects by the United Nations Framework Convention on Climate Change (UNFCCC). The results confirm that this solution is the most balanced for the city, considering resource availability, energy generation potential, emissions mitigation, and economic feasibility. Moreover, the developed tool proves adaptable to diverse scenarios and valuable for informed decision-making, facilitating a shift toward circular economy practices and contributing to climate change mitigation. In sum, this research provides a practical solution for MSW management planning, promoting more efficient resource use and advancing local and regional sustainability.Lista de tablas y figuras 10-- tablas 10-- Figuras 11-- Introducción 13--Capítulo I. Métodos de Selección de Alternativas MSWtE: Estatus y Retos 24-- Introducción 24-- Vigilancia Científica 26-- Análisis de concurrencias de palabras claves 26-- Revisión sistemática 36-- Limitaciones de métodos de selección 47-- Conclusiones de capitulo 51--Capítulo II. Rutas Tecnológicas de Valorización Energética de Residuos Sólidos Municipales 54-- Introducción 54--Características categóricas de los residuos sólidos municipales 56-- Características fisicoquímicas de los residuos sólidos municipales 60--Tecnologías de valorización energética de residuos sólidos municipales 66-- Incineración 68-- Digestión anaerobia 71-- Gasificación 72-- Relleno Sanitario con captura de biogás 74--Potencial de valorización de las rutas 77-- Potencial Técnico 77--Potencial energético 80--Potencial económico 83-- Potencial ambiental 88-- Conclusiones del capítulo 91-- Capítulo III. Análisis de Series de Tiempo de Residuos Sólidos Municipales 93--Introducción93-- Datos de disposición de residuos sólidos municipales103--Características de las series de tiempo de disposición de residuos sólidos municipales105--Descomposición de series de tiempo 111--Características relevantes de las series de tiempo 115--Modelo de serie de tiempo estacional 119--Entrenamiento y validación de modelos 120--Conclusiones del capítulo121--Capítulo IV. Selección de Alternativas de Valorización Energética de Residuos Sólidos Municipales 122--Introducción 122--Criterios para la evaluación de alternativas 124--Criterios técnicos 124--Criterios energéticos 126-- Criterios económicos 130-- Criterios ambientales 133-- Selección de un método de análisis de decisión multicriterio 135-- Clasificación de alternativas 138--Estructura general de la herramienta de selección de alternativas 141--Conclusiones del capítulo 143--Capítulo V. Evaluación Integral y Selección de Alternativas de Valorización Energética de RSM: caso de Sincelejo 145--Introducción 145--Sistema de gestión de residuos sólidos municipales de Sincelejo 147--Tratamiento actual de los residuos sólidos municipales 147--Composición de los residuos sólidos municipales 150--Proyección de tasas de disposición de residuos sólidos municipales 152--Clasificación de alternativas 160--Conclusiones del capítulo 169--Limitaciones Principales y Recomendaciones 172--Conclusiones 174-- Referencias 176--Doctor(a) en Ingenieria EnergéticaDoctorado202 Páginasapplication/pdfspaCorporación Universidad de la CostaPosgradosIngenieria ElectrícaBarranquilla, ColombiaDoctorado en Ingenieria EnergéticaCorporación Universidad de la CostaRevalorización energética de los residuos sólidos municipales generados en la ciudad de SincelejoTrabajo de grado - Doctoradohttp://purl.org/coar/resource_type/c_db06info:eu-repo/semantics/doctoralThesishttp://purl.org/redcol/resource_type/TDinfo:eu-repo/semantics/acceptedVersionSincelejoAbdella Ahmed, A. K., Ibraheem, A. M., & Abd-Ellah, M. K. (2022). Forecasting of municipal solid waste multi-classification by using time-series deep learning depending on the living standard. Results in Engineering, 16. https://doi.org/10.1016/j.rineng.2022.100655Abushammala, M. F. M., & Qazi, W. A. (2021). Financial feasibility of waste-to-energy technologies for municipal solid waste management in Muscat, Sultanate of Oman. Clean Technologies and Environmental Policy, 23(7), 2011–2023. https://doi.org/10.1007/s10098-021-02099-8Adenuga, O. T., Mpofu, K., & Modise, K. R. (2020). An approach for enhancing optimal resource recovery from different classes of waste in South Africa: Selection of appropriate waste to energy technology. Sustainable Futures, 2. https://doi.org/10.1016/j.sftr.2020.100033Adu, W. K., Appiahene, P., & Afrifa, S. (2023). VAR, ARIMAX and ARIMA models for nowcasting unemployment rate in Ghana using Google trends. Journal of Electrical Systems and Information Technology, 10(1), 12. https://doi.org/10.1186/s43067-023-00078-1Afrane, S., Ampah, J. D., Jin, C., Liu, H., & Aboagye, E. M. (2021). Techno-economic feasibility of waste-to-energy technologies for investment in Ghana: A multicriteria assessment based on fuzzy TOPSIS approach. Journal of Cleaner Production, 318. https://doi.org/10.1016/j.jclepro.2021.128515Ahmad, S. I., Ho, W. S., Hassim, M. H., Elagroudy, S., Abdul Kohar, R. A., Bong, C. P. C., Hashim, H., & Rashid, R. (2020). Development of quantitative SHE index for waste to energy technology selection. Energy, 191. https://doi.org/10.1016/j.energy.2019.116534Alao, M. A., Ayodele, T. R., Ogunjuyigbe, A. S. O., & Popoola, O. M. (2020). Multi-criteria decision based waste to energy technology selection using entropy-weighted TOPSIS technique: The case study of Lagos, Nigeria. Energy, 201. https://doi.org/10.1016/j.energy.2020.117675Alao, M. A., Popoola, O. M., & Ayodele, T. R. (2021). 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SUSTAINABILITY, 9(9). https://doi.org/10.3390/su9091568Residuos sólidos municipalesValorización energéticaAnálisis de decisión multicriterioSostenibilidadMunicipal solid wasteWaste-to-energyMulti-criteria decision-makingSustainabilityPublicationORIGINAL1102833229 (1).pdf1102833229 (1).pdfapplication/pdf5243492https://repositorio.cuc.edu.co/bitstreams/fe28330d-52f7-4766-8a62-18ec6870222d/downloadeb0be8f03cf8869a95876b23fb32429eMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-815543https://repositorio.cuc.edu.co/bitstreams/b1923b45-de84-4628-9e4c-aef63c5956ff/download73a5432e0b76442b22b026844140d683MD52TEXT1102833229 (1).pdf.txt1102833229 (1).pdf.txtExtracted texttext/plain102098https://repositorio.cuc.edu.co/bitstreams/58d09e74-ed77-4198-8872-305e049f82bb/downloaded9dc529a7a76f8f14d23ff55c61e05cMD53THUMBNAIL1102833229 (1).pdf.jpg1102833229 (1).pdf.jpgGenerated 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ara ejercer estos derechos sobre la Obra tal y como se indica a continuación:</p>
    <ol type="a">
      <li>Reproducir la Obra, incorporar la Obra en una o más Obras Colectivas, y reproducir la Obra incorporada en las Obras Colectivas.</li>
      <li>Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.</li>
      <li>Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.</li>
    </ol>
    <p>Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).</p>
  </li>
  <br/>
  <li>
    Restricciones.
    <p>La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:</p>
    <ol type="a">
      <li>Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).</li>
      <li>Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.</li>
      <li>Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.</li>
      <li>
        Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:
        <ol type="i">
          <li>Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.</li>
          <li>Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
        </ol>
      </li>
      <li>Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
    </ol>
  </li>
  <br/>
  <li>
    Representaciones, Garantías y Limitaciones de Responsabilidad.
    <p>A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Limitación de responsabilidad.
    <p>A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Término.
    <ol type="a">
      <li>Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.</li>
      <li>Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.</li>
    </ol>
  </li>
  <br/>
  <li>
    Varios.
    <ol type="a">
      <li>Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.</li>
      <li>Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.</li>
      <li>Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.</li>
      <li>Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.</li>
    </ol>
  </li>
  <br/>
</ol>
 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