An Approach to Air Pollution Source–Receptor Solution by Angular Distances

Abstract

This study presents the analysis of two series of concentrations of airborne particulate matter (APM) collected in two exploratory campaigns aimed at elucidating the source?receptor problem (SRP) in the metropolitan area of Buenos Aires. Although several techniques have been previously applied to interpret these measurements, we have almost exclusively used here the method of angular distances among objects (ADO) to discuss its advantages as a tool in understanding environmental questions within the source?receptor framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. metropolitan area of Buenos Aires. Although several techniques have been previously applied to interpret these measurements, we have almost exclusively used here the method of angular distances among objects (ADO) to discuss its advantages as a tool in understanding environmental questions within the source?receptor framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. metropolitan area of Buenos Aires. Although several techniques have been previously applied to interpret these measurements, we have almost exclusively used here the method of angular distances among objects (ADO) to discuss its advantages as a tool in understanding environmental questions within the source?receptor framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. ?receptor problem (SRP) in the metropolitan area of Buenos Aires. Although several techniques have been previously applied to interpret these measurements, we have almost exclusively used here the method of angular distances among objects (ADO) to discuss its advantages as a tool in understanding environmental questions within the source?receptor framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed. ?receptor framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed.