Articles producció científica> Enginyeria Química

Using Machine Learning to estimate the impact of ports and cruise ship traffic on urban air quality: The case of Barcelona

  • Datos identificativos

    Identificador: imarina:9216310
    Autores:
    Fabregat, AlexandreVazquez, LluisVernet, Anton
    Resumen:
    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.
  • Otros:

    Autor según el artículo: Fabregat, Alexandre; Vazquez, Lluis; Vernet, Anton;
    Departamento: Enginyeria Química
    Autor/es de la URV: Fabregat Tomàs, Alexandre / Vázquez Vilamajó, Luis Enrique / Vernet Peña, Antonio
    Palabras clave: 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
    Resumen: 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.
    Áreas temáticas: 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
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: alexandre.fabregat@urv.cat anton.vernet@urv.cat lluis.vazquez@urv.cat lluis.vazquez@urv.cat
    Identificador del autor: 0000-0002-6032-2605 0000-0002-7028-1368 0000-0002-2347-5784 0000-0002-2347-5784
    Fecha de alta del registro: 2024-08-03
    Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
    Enlace a la fuente original: https://www.sciencedirect.com/science/article/abs/pii/S1364815221000384
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Environmental Modelling & Software. 139 (104995):
    Referencia 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 del artículo: 10.1016/j.envsoft.2021.104995
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2021
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Computer Science, Interdisciplinary Applications,Computer Science, Software Engineering,Computer Science, Software, Graphics, Programming,Ecological Modeling,Engineering, Environmental,Environmental Engineering,Environmental Sciences,Software,Water Resources
    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
    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
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