| Resumo: | This study aims to apply principal component analysis (PCA) to identify monitoring sites with similar variations of PM10 concentrations in the London Air Quality Monitoring Network. This statistical methodology was applied to hourly average concentrations measured at 27 monitoring sites during the period from January 2000 to December 2009. The monitoring sites were selected according their efficiency in the study period (greater than 75% for each year). It was observed that the hourly average PM10 concentrations were decreasing along the selected period at almost all monitoring sites. PCA was performed for each year, selecting the number of principal components (PCs) that had at least 95% of the original data variance. Analysing the frequency with which each pair of monitoring sites gave a significant contribution to the same PC, nine city areas with specific PM10 behaviour were identified. Thus, monitoring sites with redundant measurements during the studied period were identified, being possible to remove them to decrease the costs relative to their maintenance or replace them to increase the monitored area.
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