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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.

Polycyclic aromatic hydrocarbons (PAHs) are known to exert mutagenic and carcinogenic effects. Research on extracted organic matter (EOM) from environmental mixtures has indicated several mechanisms of intracellular damage in living organisms. The toxic effect of environmental pollutants is usually assessed on cell systems or in single species. We used the model organism Caenorhabditis elegans to compare the effect of synthetic PAHs with that of the EOM from environmental mixtures. The biological effect was measured by monitoring the expression level of some crucial genes, sensitive parameters of the organism's response. The results indicate the ability of C. elegans to counteract damage by mounting a stress-response only in the presence of EOM. On the other hand the exposure of C. elegans to a mixture of synthetic PAHs determines the silencing of the transcriptional machinery, thus preventing the synthesis of proteins that are important for both the damage repair mechanism and survival itself. The results strongly indicate that the study of environmental toxicant effects at the molecular level may provide information on their mechanism of action. Copyright © 2011 John Wiley & Sons, Ltd.

The chemical composition of PM10 and PM2.5 samples collected during two seasonal monitoring campaigns at residential, urban and industrial Apulia Region- sites was investigated. Ionic fraction, carbonaceous compounds and Polycyclic Aromatic Hydrocarbons were determined for all samples. High correlations among PM data collected in the investigated sites suggested the regional character of particulate matter. It was also confirmed by five days back trajectories analysis. Moreover, no significant seasonal trend in PM mass concentration was observed in the investigated sites. These results, relevant for the area under investigations, were not observed in the North of Italy and Europe and allow to conclude that PM10 and PM2.5 cannot be considered ‘good’ indicators for the evaluation of local anthropic contributions to air quality. On the contrary, the high levels of Polycyclic Aromatic Hydrocarbons found in Taranto sampling sites suggested that PAHs can be a better indicator for this purpose. This result is also relevant in order to weigh the importance of industrial area and to suggest right policy control to decision makers.

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.

This study shows the direct effect of atmospheric particulate matter on plant growth. Tomato ( Solanum lycopersicum L.) plants were grown for 18 d directly on PM10 collected on quartz fiber filters. Organic and elemental carbon and polycyclic aromatic hydrocarbons (PAHs) contents were analyzed on all the tested filters. The toxicity indicators (i.e., seed germination, root elongation, shoot and/or fresh root weight, chlorophyll and carotenoids content) were quantified to study the negative and/or positive effects in the plants via root uptake. Substantial differences were found in the growth of the root apparatus with respect to that of the control plants. A 17–58% decrease of primary root elongation, a large amount of secondary roots and a decrease in shoot (32%) and root (53–70%) weights were found. Quantitative analysis of the reactive oxygen species (ROS) indicated that an oxidative burst in response to abiotic stress occurred in roots directly grown on PM10, and this detrimental effect was also confirmed by the findings on the chlorophyll content and chlorophyll-to-carotenoid ratio.

Particulate matter (PM) is a very complex mixture of many inorganic and organic compounds of primary and secondary origin and this is the main reason why the desired reduction of its concentration and the identification of its many sources constitute a very difficult task. It is widely recognised that atmospheric particles are responsible for adverse effects on the ecosystem, the climate and the health of human beings (Pope & Dockery, 2006). Epidemiological studies have shown a consistent association of the mass concentration of urban air thoracic particles (PM10 particles with an aerodynamic diameter smaller than 10 μm), and its sub-fraction fine particles (PM2.5 particles with an aerodynamic diameter smaller than 2.5 μm), with mortality and morbidity among cardio-respiratory patients (WHO, 2005). Recent studies indicate that PM10 is associated to respiratory responses while PM2.5 may contribute to cardiovascular diseases (Wyzga, 2002). The chemical characteristics of the particulate fractions and biological mechanisms responsible for these adverse health effects are still unknown as well as the aerosol parameters (mass, particle size, surface area, etc) involved in the health impacts (Hauck et al., 2004). In addition, there is an indication that the increase in the atmospheric aerosol burden delays the global warming attributed to the increase in greenhouse gasses (GHG: CO2, CH4, N2O, halocarbons). Whether the increase in GHGs since preindustrial times is producing a warming of 2.3 Wm,anthropogenic contributions to aerosols (primarily sulphate, organic carbon, black carbon, nitrate and dust) together produce a cooling effect, with a total direct radiative forcing of -0.5 Wm2 and an indirect cloud albedo forcing of -0.7 Wm (IPCC, 2007). In recent years many studies have been carried out to determine the chemical composition of atmospheric particulate matter (Vecchi et al., 2007). Most of these studies were devoted to the identification of the main particle sources, with the purpose to identify viable strategies for their reduction. In this chapter we focus the attention mostly on the ionic component of