Chemical mass balance modeling (CMB) was applied to determine the PM10 sources and their contributions. PM10 samples were collected in Lecce (40.338N, 18.108E, a town of South Italy), during two monitoring campaigns performed on July 2005 and February 2006. Nine source profiles and average mass concentration of the following chemical parameters: elemental carbon (EC), organic carbon (OC), chlorine (Cl-), nitrate (NO3-), sulfate (SO42-), sodium (Na+), ammonium (NH4+), potassium (K+), magnesium (Mg2+), calcium (Ca2+), aluminum (Al), silicon (Si), titanium (Ti), vanadium (V), manganese (Mn), iron (Fe), copper (Cu), lead (Pb), and zinc (Zn) were used to run the CMB model. The results obtained by application of CMB8.2 are shown. The contributions to PM10 show that dominant contributor was traffic with 37% followed by petroleum industry with 19% and field burning with 16%. Minor source contributions were marine aerosol (1%), ammonium sulfate production (4%), ammonium nitrate production (11%), oil-fired power plant (0.1%), gypsum handling (10%) and crustal (2%). Moreover, the Absolute Principal Component Scores (APCS) model was applied to the PM10 samples collected in order to find a correlation between the two source profile sets. With APCS model five source profiles were found and a good correlation (correlation coefficient bigger than 0.8) between crustal, marine, industrial profiles of CMB model and the corresponding ones of APCS model was found.

Application of CMB Model to PM10 Data Collected in a Site of South Italy: Results and Comparison with APCS Model

DE GENNARO, GIANLUIGI;
2010

Abstract

Chemical mass balance modeling (CMB) was applied to determine the PM10 sources and their contributions. PM10 samples were collected in Lecce (40.338N, 18.108E, a town of South Italy), during two monitoring campaigns performed on July 2005 and February 2006. Nine source profiles and average mass concentration of the following chemical parameters: elemental carbon (EC), organic carbon (OC), chlorine (Cl-), nitrate (NO3-), sulfate (SO42-), sodium (Na+), ammonium (NH4+), potassium (K+), magnesium (Mg2+), calcium (Ca2+), aluminum (Al), silicon (Si), titanium (Ti), vanadium (V), manganese (Mn), iron (Fe), copper (Cu), lead (Pb), and zinc (Zn) were used to run the CMB model. The results obtained by application of CMB8.2 are shown. The contributions to PM10 show that dominant contributor was traffic with 37% followed by petroleum industry with 19% and field burning with 16%. Minor source contributions were marine aerosol (1%), ammonium sulfate production (4%), ammonium nitrate production (11%), oil-fired power plant (0.1%), gypsum handling (10%) and crustal (2%). Moreover, the Absolute Principal Component Scores (APCS) model was applied to the PM10 samples collected in order to find a correlation between the two source profile sets. With APCS model five source profiles were found and a good correlation (correlation coefficient bigger than 0.8) between crustal, marine, industrial profiles of CMB model and the corresponding ones of APCS model was found.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/48416
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 10
social impact