With the aim of assess the pollutant load from the Volturno River into the Mediterranean Sea, the amount of some heavy metals (As, Hg, Cd, Cr, Cu, Ni, Pb and Zn) was determined in water dissolved phase (DP), suspended particulate matter (SPM) and sediment samples. Total heavy metal concentrations were in the range 0.20-65.67 μg L −1 (mean value of 12.95 μg L −1 ) for DP, 1.37-601.77 μg L −1 (mean value of 105.39 μg L −1 ) for SPM and 14.62-157.33 mg kg −1 (mean value of 55.24 mg kg −1 ) for sediments. The total heavy metals input are evaluated in about 620.39 kg year −1 , suggesting that the river could be an important source of heavy metals in the Tyrrhenian Sea. The ecological risk characterisation was assessed based on the National Water Quality Criteria, by comparison with criterion concentration for chronic and acute toxicity (CCC and CMC), and sediment quality guidelines. Hg and Cd showed higher values than CMC and CCC for most water samples. The Index of Geoaccumulation (I geo ), Contamination Factor, Contamination degree, Pollution Load Index (PLI) and Potential Ecological Risk Index were evaluated. According to I geo and PLI, the Volturno River was uncontaminated or moderately polluted by heavy metals.
In the last years, the quantity of information and statistics about waste management are more and more consistent but so far, few studies are available in this field. The goal of this paper is of producing a modelbased Composite Indicator of ''good'' Waste Management, in order to provide a useful tool of support for EU countries' policy-makers and institutions.Composite Indicators (CIs), usually, are multidimensional concepts with a hierarchical structure characterized by the presence of a set of specific dimensions, each one corresponding to a subsets of manifest variables. Thus, we propose a CI for Waste Management in Europe by using a hierarchical model-based approach with positive loadings. This approach guarantees to comply with all the good properties on which a composite indicator should be based and to detect the main dimensions (i.e., aspects) of the Waste Management phenomenon.In other terms, this paper provides a hierarchically aggregated index that best describes the Waste Management in EU with its main features by identifying the most important high order (i.e., hierarchical) relationships among subsets of manifest variables. All the parameters are estimated according to the maximum likelihood estimation method (MLE) in order to make inference on the parameters and on the validity of the model.
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