Modelamiento Geoestadístico de Mediciones de Concentración de Material Particulado (PM10) para la Validación de un Método Simplificado

Particulate matter (PM10) is an atmospheric pollutant capable of causing serious problems in terms of air quality and human health conditions. Therefore, this research presents the analysis of the concentrations of particulate matter (PM10) in the Tababela airport sector in the Metropolitan District of Quito, whose objective is to determine the most appropriate method for measuring the concentration of particulate matter (PM10), through geostatistical analysis of three methods: IDW, Spline and Kriging by means of ArcGIS software, in order to identify the points of highest concentration of PM10 in the study area. Data collection was performed using a home sampler, as well as data obtained from the Quito Metropolitan Network of Atmospheric Monitoring (REMMAQ) located in the Carapungo sector; with these data, the sampling methodology was validated using the linear regression or least squares method, showing the usefulness of the home sampler. The concentration data was collected in 16 strategic points with duplicates each one covering the Collas route, with which maps of the analyzed area were obtained, one for each proposed method, these were validated through the application of the Arctoolbox tool relating the data obtained with respect to the target, it is presented that the uncertainty value indicates a proximity in relation to the real concentration; The Inverse distance weighted (IDW) model was the one that best responded to the behavior of PM10 in the area, thus allowing to obtain the best model that differentiates the points of lower and higher PM10 concentration, unlike the Spline and Kriging models.