A Comparative Life Cycle Assessment and Costing of Lighting Systems for Environmental Design and Construction of Sustainable Roads
The management of the life cycle of the transport network is one of the main challenges of sustainable mobility. Roads and highways cause significant damage to the ecosystem. Specifically, lighting systems contribute to climate change, energy consumption, and human health effects. In this context, t...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/146449 |
| Acceso en línea: | https://hdl.handle.net/11441/146449 https://doi.org/10.3390/buildings13040983 |
| Access Level: | acceso abierto |
| Palabra clave: | Life cycle assessment Life cycle costing Eco-efficiency Roads Environmental cost-effectiveness Road light Alternative lighting |
| Sumario: | The management of the life cycle of the transport network is one of the main challenges of sustainable mobility. Roads and highways cause significant damage to the ecosystem. Specifically, lighting systems contribute to climate change, energy consumption, and human health effects. In this context, this work proposes the combination of life cycle assessment (LCA) with life cycle costing (LCC) to analyze the eco-efficiency of the life cycle of a road, including evaluation of the relative contribution of the lighting system to the total impact. Four scenarios were included in the model: (S1) high-pressure sodium lamps with ballast powered from the grid; (S2) halogen lamps powered from the grid; (S3) light-emitting diode lamps powered from the grid; and (S4) light-emitting diode lamps powered from a standalone photovoltaic system. The life cycle stages of raw material extraction, construction, use, maintenance, and end of road life were included in the analysis. The results show that scenarios S3 and S1 are the most eco-efficient relative to the less favorable S2 scenario (80% and 74% lower, respectively). Scenarios with the least environmental impact are the most economically viable. |
|---|