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IMPROVEMENT OF THE DIMENSION OF AN AIR QUALITY MONITORING NETWORK BY MEANS OF MULTIVARIATE STATISTICAL METHODS

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MARCH 2020   -  Volume: 95 -  Pages: 149-153

DOI:

https://doi.org/10.6036/9250

Authors:

MARTA DOVAL MIÑARRO - JOSE ALBERTO EGEA LARROSA - GINESA NAVARRO COBACHO

Disciplines:

  • Environmental technology and engineering (CONTROL DE LA CONTAMINACION ATMOSFERICA )

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Key words:
calidad del aire, redes de vigilancia atmosférica, análisis de componentes principales, análisis cluster, monitoring networks, redundancies, principal component analysis, cluster analysis
Article type:
COLABORACION/COLLABORATION DAMR
Section:
COLLABORATIONS

Two multivariate statistical methods (principal component analysis and cluster analysis) have been used in this work to assess potential redundancies in stations and measurements of the air quality monitoring network of the Región de Murcia (Spain). The results show that there are no redundancies, not even in areas with more stations than required by the legislation. This highlights that current criteria for assigning stations to a particular area (based on population numbers) must be complemented with criteria that consider, among others, its industrial or touristic activity. The described methodology is applicable to other existing networks.

Keywords: monitoring networks, redundancies, principal component analysis, cluster analysis

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