Traffic Road Emission Estimation Through Visual Programming Algorithms and Building Information Models: A Case Study

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 us...

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Autores principales:	Jorge Collao, Haiying Ma, Jose Antonio Lozano-Galant, Jose Turmo
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Building information modeling (BIM) COPERT emissions impact assessing green house gases (GHG) Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/1509a6f228ea49b99d5061c737609d41
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spelling	oai:doaj.org-article:1509a6f228ea49b99d5061c737609d412021-11-18T00:06:01ZTraffic Road Emission Estimation Through Visual Programming Algorithms and Building Information Models: A Case Study2169-353610.1109/ACCESS.2021.3123565https://doaj.org/article/1509a6f228ea49b99d5061c737609d412021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9591571/https://doaj.org/toc/2169-3536Emissions 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.Jorge CollaoHaiying MaJose Antonio Lozano-GalantJose TurmoIEEEarticleBuilding information modeling (BIM)COPERTemissions impact assessinggreen house gases (GHG)Electrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 150846-150864 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Building information modeling (BIM) COPERT emissions impact assessing green house gases (GHG) Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Building information modeling (BIM) COPERT emissions impact assessing green house gases (GHG) Electrical engineering. Electronics. Nuclear engineering TK1-9971 Jorge Collao Haiying Ma Jose Antonio Lozano-Galant Jose Turmo Traffic Road Emission Estimation Through Visual Programming Algorithms and Building Information Models: A Case Study
description	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.
format	article
author	Jorge Collao Haiying Ma Jose Antonio Lozano-Galant Jose Turmo
author_facet	Jorge Collao Haiying Ma Jose Antonio Lozano-Galant Jose Turmo
author_sort	Jorge Collao
title	Traffic Road Emission Estimation Through Visual Programming Algorithms and Building Information Models: A Case Study
title_short	Traffic Road Emission Estimation Through Visual Programming Algorithms and Building Information Models: A Case Study
title_full	Traffic Road Emission Estimation Through Visual Programming Algorithms and Building Information Models: A Case Study
title_fullStr	Traffic Road Emission Estimation Through Visual Programming Algorithms and Building Information Models: A Case Study
title_full_unstemmed	Traffic Road Emission Estimation Through Visual Programming Algorithms and Building Information Models: A Case Study
title_sort	traffic road emission estimation through visual programming algorithms and building information models: a case study
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/1509a6f228ea49b99d5061c737609d41
work_keys_str_mv	AT jorgecollao trafficroademissionestimationthroughvisualprogrammingalgorithmsandbuildinginformationmodelsacasestudy AT haiyingma trafficroademissionestimationthroughvisualprogrammingalgorithmsandbuildinginformationmodelsacasestudy AT joseantoniolozanogalant trafficroademissionestimationthroughvisualprogrammingalgorithmsandbuildinginformationmodelsacasestudy AT joseturmo trafficroademissionestimationthroughvisualprogrammingalgorithmsandbuildinginformationmodelsacasestudy
_version_	1718425208220549120

Traffic Road Emission Estimation Through Visual Programming Algorithms and Building Information Models: A Case Study

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