Air quality monitoring networks are important tools in management and evaluation of air quality. Classifying monitoring stations via homogeneous clusters allows identification of similarities in pollution, of representative sites, and of spatial patterns. Instead of summaries by statistical indicators, we propose to consider the air pollutant concentrations as functional data. We then classify using functional cluster analysis, where Partitioning Around Medoids (PAM) algorithm is embedded. The proposed data analysis approach is applied to the air quality monitoring network in Piemonte (Northern Italy); we consider the three more critical pollutants: NO2 , PM10, and O3.

Analysis of air quality monitoring networks by functional clustering

IGNACCOLO, Rosaria;GHIGO, Stefania;
2008-01-01

Abstract

Air quality monitoring networks are important tools in management and evaluation of air quality. Classifying monitoring stations via homogeneous clusters allows identification of similarities in pollution, of representative sites, and of spatial patterns. Instead of summaries by statistical indicators, we propose to consider the air pollutant concentrations as functional data. We then classify using functional cluster analysis, where Partitioning Around Medoids (PAM) algorithm is embedded. The proposed data analysis approach is applied to the air quality monitoring network in Piemonte (Northern Italy); we consider the three more critical pollutants: NO2 , PM10, and O3.
2008
19
672
686
R. Ignaccolo; S. Ghigo; E. Giovenali
File in questo prodotto:
File Dimensione Formato  
2008 IgnaccoloGhigoGiovenali ENV.pdf

Accesso riservato

Tipo di file: POSTPRINT (VERSIONE FINALE DELL’AUTORE)
Dimensione 480.42 kB
Formato Adobe PDF
480.42 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/34494
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 61
  • ???jsp.display-item.citation.isi??? 59
social impact