Dioxin and inorganic micropollutants contamination analysis: a statistical multi-method approach

Current development of the society is characterized by a continuous and progressive transformation of the agricultural and industrial production. These processes are accomplished through the use of organic and inorganic contaminants and, often, their release in the environment may generate pollution and toxicity for plants, animals as well as humans when overcome certain concentration thresholds. Among the organic contaminants, dioxins are one of the twelve classes of stable and persistent organic pollutants (Persistent Organic Pollutants - POPs), internationally recognized by UNEP (United Nations Environment Programme) to be toxic for both the environment and humans1 . However, over all the species of dioxins only 7 are highly toxic. Their chemical-physical characteristics are according to their chlorination's degree. Among all the 75 congeners, the most toxic isomers are the ones with chlorine in positions 2, 3, 7, and 8, and, in particular, the 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)2 , which owns a lesser chlorination degree while, on the contrary, the octachlorodibenzo-p-dioxins (OCDD), have a higher chlorination degree and a lower toxicity. There are different types of inorganic pollutants; between them heavy metals, as well as the above mentioned organic contaminants, can present problems of toxicity in addition to long persistence time. Among them Al, Fe, Ba, Be, Cd, Co, Cr, Hg, Mo, Ni, Pb, Cu, Sn, Ti, Ta, V, Zn together with to certain metalloids with similar properties to those of heavy metals such as As, Bi and Se. The present study takes into consideration topsoil samples from an site in the surroundings of a former chemical industry. Some authors investigated concentrations of As, Cd, Cu and Zn in agricultural soil originating from applications of pesticides, animal manures and fertilizers3,4. Other studies considered the heavy metals and organic pollutant combination in agricultural soils near emission sources (e.g. solid waste incinerators, urban sites or chemical industries)5 . The aim of this study was to use a statistical multi-method approach to analyse relationship existing between organic and inorganic micropollutants detected in the above-mentioned soil samples, in order to formulate a statistically valid model for the mathematical representation of the results that could also be used for predictive purposes.