Autor segons l'article: Fabregat, Alexandre; Vazquez, Lluis; Vernet, Anton;
Departament: Enginyeria Química
Autor/s de la URV: Fabregat Tomàs, Alexandre / Vázquez Vilamajó, Luis Enrique / Vernet Peña, Antonio
Paraules clau: Waterway transportation Urban atmosphere Urban area Urban air pollution Ships Service industry Predictive capabilities Pollution Pollutants Pollutant emission Pollutant concentration Pm2.5 Pm10 Numerical model Modeling system Meteorology Maritime activities Machine learning Line Identification Harbor Generalized boosted regression models Energy efficiency Emissions Emission inventories Dispersion Cruise ships Concentration (composition) Classical approach Barcelona Atmospheric movements Atmospheric dispersion models Air quality impacts Air quality
Resum: Maritime activity is known to increase pollutant concentration levels in neighboring cities. In major touristic destinations, the singular need of cruise liners to keep supplying energy to on-board services and amenities while docked, has raised concerns about this industry contribution to pollutant emissions. To estimate the impact of port activities and that exclusively due to cruises, classical approaches would rely on atmospheric dispersion models. Although these tools retain the underlying physics, lack of details on background flow state and emission inventories limits their predictive capabilities. Using historical data on pollutant concentration, meteorology and traffic intensity at specific locations across the city of Barcelona, it was found that predictions of local pollutant concentration by the present Machine Learning tool are more accurate than those provided by the CALIOPEUrban-v1.0 in our test cases. Estimated air quality impact due to cruise ships is shown to be limited in comparison to overall Port effects.
Àrees temàtiques: Zootecnia / recursos pesqueiros Water resources Software Planejamento urbano e regional / demografia Matemática / probabilidade e estatística Interdisciplinar Geociências Environmental sciences Environmental engineering Engineering, environmental Engenharias iv Engenharias iii Engenharias i Economia Ecological modeling Computer science, software, graphics, programming Computer science, software engineering Computer science, interdisciplinary applications Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência política e relações internacionais Ciência da computação Biodiversidade Antropologia / arqueologia
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: alexandre.fabregat@urv.cat anton.vernet@urv.cat lluis.vazquez@urv.cat lluis.vazquez@urv.cat
Identificador de l'autor: 0000-0002-6032-2605 0000-0002-7028-1368 0000-0002-2347-5784 0000-0002-2347-5784
Data d'alta del registre: 2024-08-03
Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
Enllaç font original: https://www.sciencedirect.com/science/article/abs/pii/S1364815221000384
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Environmental Modelling & Software. 139 (104995):
Referència de l'ítem segons les normes APA: Fabregat, Alexandre; Vazquez, Lluis; Vernet, Anton; (2021). Using Machine Learning to estimate the impact of ports and cruise ship traffic on urban air quality: The case of Barcelona. Environmental Modelling & Software, 139(104995), -. DOI: 10.1016/j.envsoft.2021.104995
DOI de l'article: 10.1016/j.envsoft.2021.104995
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2021
Tipus de publicació: Journal Publications
Repositori URV