Modelling background air pollution exposure in urban environments: Implications for epidemiological research

• Tipo: Artigo em Revista Científica Internacional
• Data: 2018

Autores

Gómez-Losada, Á. (Autor) Outra; Pires, JCM (Autor) FEUP; Pino-Mejías, R. (Autor) Outra

Revista

Título: ENVIRONMENTAL MODELLING & SOFTWARE

Vol. 106

Páginas: 13-21

ISSN: 1364-8152

Editora: Elsevier

Indexação

ISI Web of Knowledge - 14 Citações

Scopus - 21 Citações

INSPEC

Outras Informações

ID Authenticus: P-00P-06X

DOI: 10.1016/j.envsoft.2018.02.011

Abstract (EN): Background pollution represents the lowest levels of ambient air pollution to which the population is chronically exposed, but few studies have focused on thoroughly characterizing this regime. This study uses clustering statistical techniques as a modelling approach to characterize this pollution regime while deriving reliable information to be used as estimates of exposure in epidemiological studies. The background levels of four key pollutants in five urban areas of Andalusia (Spain) were characterized over an 11-year period (2005e2015) using four widely-known clustering methods. For each pollutant data set, the first (lowest) cluster representative of the background regime was studied using finite mixture models, agglomerative hierarchical clustering, hidden Markov models (hmm) and k-means. Clustering method hmm outperforms the rest of the techniques used, providing important estimates of exposures related to background pollution as its mean, acuteness and time incidence values in the ambient air for all the air pollutants and sites studied.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 9