Pollution from particulate matter, PM10/2.5, is nowadays a relevant problem, either for public Administration or researchers. The present study aims to investigate the temporal and spatial variability of this pollutant in Tuscany and to study the different nature (primary or secondary) of the PM10/2.5. PM10 are emitted and generated by many different sources. The analysis of the raw data measured in the last three years by Tuscany Air Quality Network (in particular for the PM10 and also for other pollutants related to them), allows to better understand the nature of pollution events and the correlation with meteorological and site characteristics. Seasonal and daily pollution trends are studied for several sites: a statistical study and a mathematical algorithm, set up to identify the characteristic trends, as well as chemical analysis, help to identify the main sources. In particular, the study of the hourly averaged PM10 data allows to characterize the different stations and the time of the day when acute episodes take place. These results can contribute to define more sound criteria for the classification of the stations for air quality definition.
Fine Particulate Matter Pollution of Air in Tuscany
TOGNOTTI, LEONARDO
2003-01-01
Abstract
Pollution from particulate matter, PM10/2.5, is nowadays a relevant problem, either for public Administration or researchers. The present study aims to investigate the temporal and spatial variability of this pollutant in Tuscany and to study the different nature (primary or secondary) of the PM10/2.5. PM10 are emitted and generated by many different sources. The analysis of the raw data measured in the last three years by Tuscany Air Quality Network (in particular for the PM10 and also for other pollutants related to them), allows to better understand the nature of pollution events and the correlation with meteorological and site characteristics. Seasonal and daily pollution trends are studied for several sites: a statistical study and a mathematical algorithm, set up to identify the characteristic trends, as well as chemical analysis, help to identify the main sources. In particular, the study of the hourly averaged PM10 data allows to characterize the different stations and the time of the day when acute episodes take place. These results can contribute to define more sound criteria for the classification of the stations for air quality definition.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.