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Analysis of institutional authors

Morillo McCorresponding AuthorMartínez-Cuevas S.AuthorGarcía-Aranda C.AuthorMolina I.AuthorQuerol JjAuthorMartinez E.Author

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June 6, 2022
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Spatial analysis of the particulate matter (PM10) an assessment of air pollution in the region of Madrid (Spain): spatial interpolation comparisons and results

Publicated to: International Journal of Environmental Studies. 81 (4): 1501-1511 - 2024-01-01 81(4), DOI: 10.1080/00207233.2022.2072585

Authors:

Morillo MC; Martínez-Cuevas S; García-Aranda C; Molina I; Querol JJ; Martínez E
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Affiliations

Universidad Politécnica de Madrid - Author
Universidad Politécnica de MadridETSI Topografía - Author

Abstract

This paper reports a comparison of different spatial and statistical models to predict the concentrations of the particulate matter (PM10), measured by the environmental stations of the Community of Madrid (Spain). Three methods were compared: Inverse Distance Weighting (IDW), Ordinary Kriging (OK) and Empirical Bayesian Kriging (EBK). The most accurate spatial interpolation method was the EBK. An interpolation map obtained by applying the EBK geostatistical method is presented to identify the areas with the highest pollution of PM10.].
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Keywords

InterpolationKrigingPm10PollutionSpatialStatistics

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal International Journal of Environmental Studies due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position , thus managing to position itself as a Q2 (Segundo Cuartil), in the category Geography, Planning and Development.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-25:

  • Scopus: 4
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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 2026-04-25:

  • 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: 10 (PlumX).

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:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/92847/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 30
  • Downloads: 1
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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 (MORILLO BALSERA, M DEL CARMEN) and Last Author (MARTINEZ IZQUIERDO, M.ESTIBALIZ).

the author responsible for correspondence tasks has been MORILLO BALSERA, M DEL CARMEN.

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Contextual narrative

This research compares various spatial and statistical models for predicting PM10 concentrations in Madrid, specifically evaluating Inverse Distance Weighting, Ordinary Kriging, and Empirical Bayesian Kriging. The findings indicate that Empirical Bayesian Kriging is the most accurate method, and an interpolation map highlighting areas of highest PM10 pollution is provided.

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