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Grant support

This study was financially supported by the Spanish Ministry of Economy, Industry and Competitiveness - Research National Agency (under projects DPI2016-75791-C2-1-Pand RTI2018-100907-A-I00), by FEDER funds and by the Generalitat de Catalunya - AGAUR (under project 2017 SGR 01234). Authors would like to thank the Government of Catalonia for granting access to atmospheric pollutant data from the XVPCA network and the Servei Meteorol`ogic de Catalunya for weather measurements.

Analysis of institutional authors

Fabregat, ACorresponding AuthorVazquez, LAuthorVernet, AAuthor
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Article

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

Publicated to:Environmental Modelling & Software. 139 (104995): 104995- - 2021-05-01 139(104995), DOI: 10.1016/j.envsoft.2021.104995

Authors: Fabregat, Alexandre; Vazquez, Lluis; Vernet, Anton

Affiliations

‎ Univ Rovira & Virgili, Dept Mech Engn, Ave Paisos Catalans 26, Tarragona 43007, Spain - Author

Abstract

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.

Keywords
Air qualityAir quality impactsAtmospheric dispersion modelsAtmospheric movementsBarcelonaClassical approachConcentration (composition)Cruise shipsDispersionEmission inventoriesEmissionsEnergy efficiencyGeneralized boosted regression modelsHarborIdentificationLineMachine learningMaritime activitiesMeteorologyModeling systemNumerical modelPm10Pm2.5Pollutant concentrationPollutant emissionPollutantsPollutionPredictive capabilitiesService industryShipsUrban air pollutionUrban areaUrban atmosphereWaterway transportation

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Environmental Modelling & Software due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2021, it was in position 16/100, thus managing to position itself as a Q1 (Primer Cuartil), in the category Water Resources.

From a relative perspective, and based on the normalized impact indicator calculated from World Citations provided by WoS (ESI, Clarivate), it yields a value for the citation normalization relative to the expected citation rate of: 1.87. This indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: ESI Nov 14, 2024)

This information is reinforced by other indicators of the same type, which, although dynamic over time and dependent on the set of average global citations at the time of their calculation, consistently position the work at some point among the top 50% most cited in its field:

  • Weighted Average of Normalized Impact by the Scopus agency: 2.36 (source consulted: FECYT Feb 2024)
  • Field Citation Ratio (FCR) from Dimensions: 7.37 (source consulted: Dimensions Apr 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-04-24, the following number of citations:

  • WoS: 22
  • Scopus: 30
  • OpenCitations: 25
Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-04-24:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 89.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 89 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 1.25.
  • The number of mentions on the social network X (formerly Twitter): 2 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Fabregat Tomàs, Alexandre) and Last Author (Vernet Peña, Antonio).

the author responsible for correspondence tasks has been Fabregat Tomàs, Alexandre.