Repositorio Institucional de Documentos

000151038 001__ 151038
000151038 005__ 20251017144629.0
000151038 0247_ $$2doi$$a10.1007/s42979-022-01105-0
000151038 0248_ $$2sideral$$a128720
000151038 037__ $$aART-2022-128720
000151038 041__ $$aeng
000151038 100__ $$0(orcid)0000-0002-7073-219X$$aIlarri, S.$$uUniversidad de Zaragoza
000151038 245__ $$aTraffic and Pollution Modelling for Air Quality Awareness: An Experience in the City of Zaragoza
000151038 260__ $$c2022
000151038 5060_ $$aAccess copy available to the general public$$fUnrestricted
000151038 5203_ $$aAir pollution due to the presence of small particles and gases in the atmosphere is a major cause of health problems. In urban areas, where most of the population is concentrated, traffic is a major source of air pollutants (such as nitrogen oxides or NO x and carbon monoxide or CO). Therefore, for smart cities, carrying out an adequate traffic monitoring is a key issue, since it can help citizens to make better decisions and public administrations to define appropriate policies. Thus, citizens could use these data to make appropriate mobility decisions. In the same way, a city council can exploit the collected data for traffic management and for the establishment of suitable traffic policies throughout the city, such as restricting the traffic flow in certain areas. For this purpose, a suitable modelling approach that provides the estimated/predicted values of pollutants at each location is needed. In this paper, an approach followed to model traffic flow and air pollution dispersion in the city of Zaragoza (Spain) is described. Our goal is to estimate the air quality in different areas of the city, to raise awareness and help citizens to make better decisions; for this purpose, traffic data play an important role. In more detail, the proposal presented includes a traffic modelling approach to estimate and predict the amount of traffic at each road segment and hour, by combining historical measurements of real traffic of vehicles and the use of the SUMO traffic simulator on real city roadmaps, along with the application of a trajectory generation strategy that complements the functionalities of SUMO (for example, SUMO’s calibrators). Furthermore, a pollution modelling approach is also provided, to estimate the impact of traffic flows in terms of pollutants in the atmosphere: an R package called Vehicular Emissions INventories (VEIN) is used to estimate the amount of NO x generated by the traffic flows by taking into account the vehicular fleet composition (i.e., the types of vehicles, their size and the type of fuel they use) of the studied area. Finally, considering this estimation of NO x, a service capable of offering maps with the prediction of the dispersion of these atmospheric pollutants in the air has been established, which uses the Graz Lagrangian Model (GRAL) and takes into account the meteorological conditions and morphology of the city. The results obtained in the experimental evaluation of the proposal indicate a good accuracy in the modelling of traffic flows, whereas the comparison of the prediction of air pollutants with real measurements shows a general underestimation, due to some limitations of the input data considered. In any case, the results indicate that this first approach can be used for forecasting the air pollution within the city.
000151038 536__ $$9info:eu-repo/grantAgreement/ES/AEI-FEDER/TIN2016-78011-C4-3-R$$9info:eu-repo/grantAgreement/ES/AEI/PID2020-113037RB-I00$$9info:eu-repo/grantAgreement/EC/CEF Telecom/2017-EU-IA-0167/EU/Understanding Traffic Flows to Improve Air quality/TRAFAIR$$9info:eu-repo/grantAgreement/ES/DGA/T64-20R
000151038 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000151038 592__ $$a0.6$$b2022
000151038 593__ $$aComputer Graphics and Computer-Aided Design$$c2022$$dQ2
000151038 593__ $$aComputational Theory and Mathematics$$c2022$$dQ2
000151038 593__ $$aComputer Science Applications$$c2022$$dQ2
000151038 593__ $$aComputer Networks and Communications$$c2022$$dQ2
000151038 593__ $$aComputer Science (miscellaneous)$$c2022$$dQ2
000151038 593__ $$aArtificial Intelligence$$c2022$$dQ3
000151038 594__ $$a4.3$$b2022
000151038 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000151038 700__ $$0(orcid)0000-0001-6008-1138$$aTrillo-Lado, R.$$uUniversidad de Zaragoza
000151038 700__ $$0(orcid)0000-0002-7767-3057$$aMarrodán, L.$$uUniversidad de Zaragoza
000151038 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000151038 7102_ $$15005$$2790$$aUniversidad de Zaragoza$$bDpto. Ing.Quím.Tecnol.Med.Amb.$$cÁrea Tecnologi. Medio Ambiente
000151038 773__ $$g3 (2022), 281 [33 pp.]$$pSN comput. sci.$$tSN Computer Science$$x2662-995X
000151038 8564_ $$s7101751$$uhttps://zaguan.unizar.es/record/151038/files/texto_completo.pdf$$yVersión publicada
000151038 8564_ $$s2517103$$uhttps://zaguan.unizar.es/record/151038/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000151038 909CO $$ooai:zaguan.unizar.es:151038$$particulos$$pdriver
000151038 951__ $$a2025-10-17-14:25:43
000151038 980__ $$aARTICLE

El sistema ha encontrado un error mientras gestionaba su petición.

Los administradores del sistema han sido avisados.

En caso de duda, póngase en contacto con deposita@unizar.es