Application of receptor models to airborne particulate matter

The human activities in their various aspects cause a change in the natural air quality. This change results more marked in very populated and in high industrialized areas. Some pollutants emitted are typical of a particular activity. Each source of pollution is identified by its profile in the composition of the emissions in the environment. Multivariate receptor models can be used in order to apportion pollutants to the different sources assessing the contribution of each source to the total pollution. This paper deals with the application of Absolute Principal Component Scores (APCS) receptor model to data obtained from the automatic network of air quality monitoring in the city of Bari (South Italy). The parameters monitored by automatic networks, as bihourly values, are PM10, NOx, CO, Benzene, Toluene, Xilene. The data shown in this paper concerning 1 month almost of sampling in different monitoring stations of Bari Municipality during the period of time from January 2005 to April 2006. Moreover preliminary results obtained applying the APCS model to daily PM2.5 samples collected during SITECOS PRIN project are shown. The results concerning data collected in corso Cavour (Bari) during the month of October 2005. The results obtained by APCS receptor model seem to suggest a poor contribution of the "vehicular traffic source" and a relevant contribution of the "secondary particulate source" to particulate matter concentrations.