Wavelets-based clustering of air quality monitoring sites
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This paper aims at providing a variance/covariance profile of a set of 36 monitoring stations measuring ozone (O 3) and nitrogen dioxide (NO 2) hourly concentrations, collected over the period 2005–2013, in Portugal mainland. The resulting individual profiles are embedded in a wavelet decomposition-based clustering algorithm in order to identify groups of stations exhibiting similar profiles. The results of the cluster analysis identify three groups of stations, namely urban, suburban/urban/rural, and a third group containing all but one rural stations. The results clearly indicate a geographical pattern among urban stations, distinguishing those located in Lisbon area from those located in Oporto/North. Furthermore, for urban stations, intra-diurnal and daily time scales exhibit the highest variance. This is due to the more relevant chemical activity occurring in high NO 2 emissions areas which are responsible for high variability on daily profiles. These chemical processes also explain the reason for NO 2 and O 3 being highly negatively cross-correlated in suburban and urban sites as compared with rural stations. Finally, the clustering analysis also identifies sites which need revision concerning classification according to environment/influence type.
KeywordsAir quality monitoring stations Ozone Nitrous oxide Wavelets Classification Clustering
This work was supported by Portuguese Funds through FCT - Foundation for Science and Technology, in the context of the projects UID/CEC/00127/2013 and Incentivo/EEI/UI0127/2014 (IEETA/UA, Instituto de Engenharia Electrónica e Informática de Aveiro, www.ieeta.pt) and UID/MAT/04106/2013 (CIDMA/UA, Centro de I&D em Matemática e Aplicações, www.cidma.mat.ua.pt). S. Gouveia acknowledges the postdoctoral grant by FCT (ref. SFRH/BPD/87037/2012), financed through POPH - QREN programme (European Social Fund and Nacional funds). Andres M. Alonso acknowledges the support of CICYT (Spain) Grants ECO2011-25706 and ECO2012-38442. The authors also gratefully acknowledge to the Portuguese Environmental Agency for providing the air quality monitoring data.
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Conflict of interests
The authors declare that they have no conflict of interest.
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