21/03/2017, 11:00 — 12:00 — Room P3.10, Mathematics Building
Alexandra Monteiro, CESAM, Department of Environment and Planning, University of Aveiro
Air quality science: putting statistics to work
Several statistical tools have been used to analyse air quality data with different purposes. This talk will highlight some of these examples and how the different statistical tools can be bring an added value for this scientific environmental area. First, changes in pollutant concentrations were examined and clustered by means of quantile regression, which allows to analyse the trends not only in the mean but in the overall data distribution. The clustering procedure has shown/indicated where the largest trends are found, in terms of space (location) and quantiles. Secondly, the resulting individual variance/covariance profiles of a set of air quality hourly time series are embedded in a wavelet decomposition-based clustering algorithm in order to identify groups of stations exhibiting similar profiles. The results clearly indicate a geographical pattern among different type of stations and allowed to identify sites which need revision concerning classification according to environment/ influence type. Both exercises were particular important for air quality management practices, in particular regarding the design of the national monitoring network.