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Grant support

This study was carried out within AIRTEC-CM (urban air quality and climate change integral assessment) scientific program funded by the Directorate General for Universities and Research of the Greater Madrid Region (S2018/EMT-4329) . The authors acknowledge the contribution and Support of Ricardo Vargas and Jaime S. Gallego from the Madrid Regional Government (Consejeia de Medio Ambiente, Vivienda y Agricultura de la Comunidad de Madrid) .

Analysis of institutional authors

Borge, RafaelCorresponding AuthorJung, DaeunAuthorDe La Paz, DavidAuthorCordero, Jose MariaAuthor

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December 19, 2022
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Assessment of the Madrid region air quality zoning based on mesoscale modelling and k-means clustering

Publicated to:Atmospheric Environment. 287 119258- - 2022-07-11 287(), DOI: 10.1016/j.atmosenv.2022.119258

Authors: Borge, Rafael; Jung, Daeun; Lejarraga, Iciar; de la Paz, David; Cordero, Jose Maria

Affiliations

Univ Politecn Madrid UPM, Dept Chem & Environm Engn, Environm Modelling Lab, Madrid, Spain - Author

Abstract

According to the Air Quality (AQ) Directive (2008/50/EC), European Member States should establish (and revise every five years) their own AQ zones, where the air quality and population exposure are homogeneous. In Madrid, there are currently seven AQ zones, which were determined based on administrative geographic and land use criteria in 2014. However, so far, there has been no standardized methodology to define an objective AQ zoning. In this study, a new methodology is applied to revise the AQ zones of the Madrid region by using the WRF-CMAQ modelling system with 1?km(2) spatial resolution. All the relevant legal indicators of the main pollutants (NO2, O-3, PM10 and PM2.5) were computed from an annual 1-h temporal resolution model run and aggregated at municipality level. Then, seven basic statistics (mean, interquartile range, etc.) are computed for each air quality indicator within each of the 179 municipalities of the Madrid region. A Principal Components Analysis (PCA) is applied to identify the most relevant clustering variables from all these statistics to subsequently apply a k-mean cluster analysis. The definition of the number air quality zones (clusters) is based on three methods: Elbow, Silhouette, and Gap statistic. Following this methodology, five zones for NO2, PM10, and PM2.5 and four zones for O-3 are proposed. To assess the resulting zoning and to compare it with the current one, concentration distributions in each zone are visualized through boxplots. In addition, in order to confirm significant differences among the zones of both zonings, they are examined by two statistical tests: the Kruskal-Wallis and Dunn tests. Finally, the coverage and potential redundancy areas of the 47 existing air quality monitoring stations in the region are analysed for the two alternatives, confirming the suitability of the new air quality zoning proposed.

Keywords

Air monitoringAir pollutantAir qualityAir quality zoneAir quality zonesArticleAssessment methodChemical modelCluster analysisClustering analysisCmaqConcentration (parameter)K means clusteringK-mean clusteringK-means clusteringK-means++ clusteringLand useMadridMadrid regionMeso-scale modelingMethodologyModelingNitrogen dioxideNitrogen oxidesOzoneParticulate matter 10Particulate matter 2.5Pm 10Pm 2.5Pollution exposurePrincipal component analysisQuality controlQuality zonesSpainSpatiotemporal analysisZoningZoning assessment

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Atmospheric Environment 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, 2022, it was in position 21/94, thus managing to position itself as a Q1 (Primer Cuartil), in the category Meteorology & Atmospheric Sciences.

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: 1.09. 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: 1.55 (source consulted: FECYT Feb 2024)
  • Field Citation Ratio (FCR) from Dimensions: 6.01 (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-23, the following number of citations:

  • WoS: 13
  • Scopus: 15
  • Google Scholar: 11

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 2025-07-23:

  • 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: 40 (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:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.

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 (BORGE GARCIA, RAFAEL) and Last Author (CORDERO DÍAZ, JOSÉ MARÍA).

the author responsible for correspondence tasks has been BORGE GARCIA, RAFAEL.