Soil heavy metal contamination in an industrial area: analysis of the data collected during a decade.

Soil contamination by heavy metals has become a serious problem mainly because, above certain concentrations, all metals have adverse effects on human health. In particular, the accumulation of heavy metals in agricultural soils leads to elevated uptake by crops and affects food quality and safety. In this paper, we present the results of a study carried out over a decade for evaluating the impact of a new industrial settlement in an area geared to agriculture and livestock and far from urban sites. We focus our study on the bioavailable fraction of Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn in soil samples. Heavy metal concentrations in soil are analysed with both univariate and multivariate statistical procedures. The main goal of this paper is the development of a statistical procedure, based on a mix of multivariate analysis, able to compare field surveys carried out during different years and to characterize spatial and temporal changes in soil heavy metals concentrations.

Apportioning PM1 in a contrasting receptor site in the Mediterranean region: Aerosol sources with an updated sulfur speciation.

A multi-parametric experimental campaign was performed in Agri Valley (Basilicata, southern Italy) from July 2017 to January 2018. The investigated area, though basically rural and devoted to agricultural activities, hosts a huge on-shore oil reservoir, i.e. Centro Olio Val d'Agri (COVA), bringing substantial environmental modifications and impacts to the district landscape. Daily concentrations of PM1 aerosol samples, Equivalent Black Carbon and number size distributions were evaluated. Chemical aerosol speciation based on elemental and ion analyses were carried out and source apportionment by Positive Matrix Factorization (PMF) was applied to reconstruct PM1 source profile. The most significant emission sources found are torches from the oil treatment facility (37 % w/w), an unresolved factor constituted by soil resuspension, Saharan dust, and biomass burning (24 % w/w), ammonium sulphate (23 % w/w), emissions from the oil desulfurization (Claus process) (13 % w/w), and traffic + road dust (3 % w/w). SEM analysis on PM1 single particles allowed to confirm the finding from PMF including the occurrence of elemental sulfur associated with the Claus process. The novelty of the present study consists in the identification of this latter fingerprint.

Trace elements and human health risks assessment of finer aerosol atmospheric particles (PM1).

The present study investigated PM1 (aerosol particles with an aerodynamic diameter ≤ 1.0 µm) mass concentrations and sixteen (Al, Ca, Cd, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Pb, S, Ti, and Zn) PM1-related trace elements. PM1 samples were collected in an anthropized area of international attention close to oil/gas pre-treatment plants in Agri Valley (Southern Italy). The PM1 mass concentrations varied from 3 to 16 µg/m3. The decreasing pattern of the trace element concentrations was S > Ca > Na > K ≈ Mg ≈ Fe> Al > Li > Cr > Zn > Ti> Cu > Ni ≈ Mn > Pb ≈ Cd. Anthropogenic local emissions such as biomass burning, vehicular traffic, and industrial sources mainly related to oil/gas pre-treatment plants were identified by the principal component analysis. Further, air mass back-trajectory analyses suggest an important contribute to the long-range transport on PM1 at Agri Valley. The carcinogenic (Cd, Cr(VI), Ni, and Pb) and non-carcinogenic (Cd, Cr(VI), Cu, Mn, Ni, Pb, and Zn) health risks both for children and for adults were assessed using the United State Environmental Protection Agency (USEPA) methods considering inhalation, ingestion, and dermal contact pathway. Chromium (VI) posed the highest carcinogenic risk for both children and adults. The integrated carcinogenic risks were respectively 3.45 × 10-5 and 1.38 × 10-4 for children and adults indicating that attention should be paid for carcinogenic health effects. Nickel posed the highest non-carcinogenic risk for children through inhalation pathway. The integrated non-carcinogenic risk showed a value higher than 1 highlighting that Cd, Cr(VI), Cu, Mn, Ni, Pb, and Zn may cause cumulative non-carcinogenic health effect for children from inhalation exposure.

Biomonitoring of atmospheric pollution: a novel approach for the evaluation of natural and anthropogenic contribution to atmospheric aerosol particles.

The investigation of the potential natural and anthropogenic contribution to atmospheric aerosol particles by using lichen-bag technique was performed in the Agri Valley (Basilicata region, southern Italy). This is an area of international concern since it houses one of the largest European on-shore reservoirs and the biggest oil/gas pre-treatment plant (i.e., Centro Olio Val d'Agri (COVA)) within an anthropized context. In particular, the concentrations of 17 trace elements (Al, Ca, Cd, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, S, Ti, and Zn) were measured in lichen bags exposed in 59 selected monitoring points over periods of 6 months (from October 2011 to April 2012) and 12 months (from October 2011 to October 2012). The general origin of the main air masses affecting the sampling site during the study period was assessed by the back trajectories clustering calculated using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The results allowed the identification and characterization of the crustal material, smoke, sea salt, sulfate, and anthropogenic trace element contributions to the atmospheric aerosol particles in the study area. Finally, the application of the trend surface analysis (TSA) allowed the study of the spatial distribution of the considered contributions highlighting the existence of a continuous broad variation of these contributions in the area of interest.

Metal levels in fodder, milk, dairy products, and tissues sampled in ovine farms of Southern Italy.

We measured Cd, Cr, Hg, Mn, and Pb levels in samples of fodder, milk, dairy products, and tissues collected from 12 ovine farms in the regions of Campania and Calabria (Southern Italy). The areas in which the farms are located show different levels of anthropogenic pressure. The main purpose of this study is the identification and the analysis of relationships among metal concentrations observed in samples representative of different links in the food chain. Particularly, we apply univariate, bivariate, and multivariate statistical techniques to identify the correlation structure of our data set and to evaluate the influence of anthropogenic activity. We discuss the results, focusing the analysis on the spatial and the temporal patterns of metal concentrations.