Traffic road emission estimation through visual programming algorithms and building information models: a case study
Visualitza/Obre
10.1109/ACCESS.2021.3123565
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/368741
Tipus de documentArticle
Data publicació2021
EditorInstitute of Electrical and Electronics Engineers (IEEE)
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement 4.0 Internacional
ProjecteMODELOS ESTRUCTURALES PARA LA GESTION EFICIENTE DE INFRAESTRUCTURAS: SMART BIM MODELS (AEI-BIA2017-86811-C2-1-R)
CALIBRACION DE MODELOS BIM MEDIANTE SENSORES DE BAJO COSTE PARA LA OPTIMIZACION ENERGETICA DE EDIFICIOS (AEI-BIA2017-86811-C2-2-R)
CALIBRACION DE MODELOS BIM MEDIANTE SENSORES DE BAJO COSTE PARA LA OPTIMIZACION ENERGETICA DE EDIFICIOS (AEI-BIA2017-86811-C2-2-R)
Abstract
Emissions from transportation have a severe impact on the current climate crisis. Therefore, the estimation of these pollutants requires precise measurements that integrate both traffic and vehicle fleet information within a specific country or area. However, the current estimation tools continue using vehicle fleet standards based on recommendations or local studies. A problem for the current estimation models arises due to the difficulty of centralizing the large number of vehicle statistics. This article has taken advantage of the capabilities of both visual programming tools and building information modeling (BIM) to centralize databases from different sources, generating a model that integrates current traffic data and vehicle fleet statistics. The proposed platform estimates emissions and the carbon footprint using TIER 1 emission factors recommended by the European Environmental Agency (EEA). This platform has been successfully applied to a case study to estimate the carbon footprint of the B-20 road in Barcelona, using current vehicle restriction scenarios. This case study presents a maximum difference of -2.72% compared with the estimations made by another similar report. This proposed platform more completely automates the communication among the equations and databases required to estimate traffic road emissions.
CitacióCollao, J. [et al.]. Traffic road emission estimation through visual programming algorithms and building information models: a case study. "IEEE access", 2021, vol. 9, p. 150846-150864.
ISSN2169-3536
Versió de l'editorhttps://ieeexplore.ieee.org/document/9591571
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