title: Spatio-temporal models to estimate daily concentrations of fine particulate matter in Montreal: Kriging with external drift and inverse distance-weighted approaches.
abstract: Air pollution is a major environmental and health problem, especially in urban agglomerations. Estimating personal exposure to fine particulate matter (PM2.5) remains a great challenge because it requires numerous point measurements to explain the daily spatial variation in pollutant levels. Furthermore, meteorological variables have considerable effects on the dispersion and distribution of pollutants, which also depends on spatio-temporal emission patterns. In this study we developed a hybrid interpolation technique that combined the inverse distance-weighted (IDW) method with Kriging with external drift (KED), and applied it to daily PM2.5 levels observed at 10 monitoring stations. This provided us with downscaled high-resolution maps of PM2.5 for the Island of Montreal. For the KED interpolation, we used spatio-temporal daily meteorological estimates and spatial covariates as land use and vegetation density. Different KED and IDW daily estimation models for the year 2010 were developed for each of the six synoptic weather classes. These clusters were developed using principal component analysis and unsupervised hierarchical classification. The results of the interpolation models were assessed with a leave-one-station-out cross-validation. The performance of the hybrid model was better than that of the KED or the IDW alone for all six synoptic weather classes (the daily estimate for R(2) was 0.66-0.93 and for root mean square error (RMSE) 2.54-1.89 μg/m(3)).
authors.affiliation: Département de Géographie, Université de Montréal, Montréal, Québec, Canada.
authors.forename: Yuddy
authors.initials: Y
authors.lastname: Ramos
authors.affiliation: Département de Géographie, Université du Québec à Montréal (UQAM), Montréal, Québec, Canada.
authors.forename: Benoît
authors.initials: B
authors.lastname: St-Onge
authors.affiliation: Département des Sciences de la Terre et de l'atmosphère, Université du Québec à Montréal (UQAM), Montréal, Québec, Canada.
authors.forename: Jean-Pierre
authors.initials: JP
authors.lastname: Blanchet
authors.affiliation: Département de Santé Environnementale et de Santé au Travail, Université de Montréal, Montréal, Québec, Canada.|Institut National de Santé Publique du Québec (INSPQ), Montréal, Québec, Canada.
authors.forename: Audrey
authors.initials: A
authors.lastname: Smargiassi
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis*; D004784:Environmental Monitoring / Q000379:methods; D006801:Humans; D008377:Maps as Topic; D008962:Models, Theoretical; D010316:Particle Size; D052638:Particulate Matter / Q000032:analysis*; D025341:Principal Component Analysis; D011792:Quebec; D015203:Reproducibility of Results; D062206:Spatial Analysis; D062211:Spatio-Temporal Analysis; D001335:Vehicle Emissions / Q000032:analysis; D014887:Weather
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter; D001335:Vehicle Emissions