Atmospheric particulate matter (PM) effect on the growth of Solanum lycopersicum cv. Roma plants

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

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

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