Using Visible and Near infrared reflectance spectroscopy for the prediction of soil heavy metals in the Environmental Crisis Area of Taranto (Southern Italy)
| Autor: | Natalia Leone, Ciro Galeone, Valeria Ancona, Carmine Massarelli, Pietro Coturno Daniela Valeria Miniero, Vito Uricchio, Vera Corbelli, Antonio Pasquale Leone |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | RemTech Europe 2019, Ferrara, 18-20/09/2019 info:cnr-pdr/source/autori:Natalia Leone, Ciro Galeone, Valeria Ancona, Carmine Massarelli, Pietro Coturno Daniela Valeria Miniero, Vito Uricchio, Vera Corbelli, Antonio Pasquale Leone/congresso_nome:RemTech Europe 2019/congresso_luogo:Ferrara/congresso_data:18-20%2F09%2F2019/anno:2019/pagina_da:/pagina_a:/intervallo_pagine |
| Popis: | Soil contamination by heavy metals has become a severe and widespread environmental problem in the World, especially in the more developed and industrialized Countries. Heavy metals can occur naturally in soils, but often occur at enhanced levels due to anthropogenic activities such as mine tailings, disposal of high metal wastes, emissions from the rapidly expanding industrial areas, leaded gasoline and paints, land application of fertilizers, animal manures, sewage sludge, pesticides, wastewater irrigation, coal combustion residues, spillage of petrochemicals, and atmospheric deposition. When released into the soil, heavy metals can be adsorbed on to soil particle, broken down through chemical reactions, or leached to groundwater. Due to the fact that heavy metals cannot be decomposed like organic contaminants through chemical or biological processes, they are considered as stable and durable contaminants. Soil contamination by heavy metals has been proved to be a major environmental threat in the so-called Environmental Crisis Area of Taranto (Apulia Region, Southern Italy), of about 564 km2, including the SIN (Site of National Interest) of Taranto and in a wider surrounding area. Soil reclamation of heavy metals needs careful analysis in order to define their concentrations and spatial distribution. Conventional laboratory analyses, although usefully and practically irreplaceable for detailed investigations, are costly and time-consuming, thus not very suitable when large numbers of soil samples need to be analysed. Thus, there is a need to assess alternative, rapid and cost-effective methods for the characterization of these contaminants, to use as substitutive or integrative of conventional laboratory analysis. In recent years, reflectance spectroscopy, i.e. the ratio of the electromagnetic radiation reflected by a soil surface to that which impinges on it, in the visible-Near Infrared (vis-NIR) domain (350-2500 nm), has proved to be a promising technique for the efficient detection and monitoring of various soil contaminants as well as other soil properties. It is based on the principle that the characteristics of radiation reflected from a material are a function of the chemical and physical properties of the material, thus, observations on soil reflectance can provide information on its properties. Within the framework of the activities planned by the Government Commissioner for the urgent interventions of environmental remediation and rehabilitation of Taranto, a preliminary study was carried out to assess the capability of vis-NIR spectroscopy, combined with multivariate statistical methods, for the prediction of the concentration of fifteen heavy metals (Be, V, Cr, Co, Ni, Cu, Zn, As, Se, Cd, Sr, Sb, Hg, Tl, Pb) on 408 surface and sub-surface soil samples collected with the study area. The diffuse vis-NIR reflectance was measured in the laboratory on the air-dried and 2 mm-sieved soil samples, using a high-resolution FieldSpec Pro spectroradiometer. The measured vis-NIR reflectance spectra were quantitatively related to soil heavy metals using Partial Least Square Regression method (PLSR). PLSR was used to calibrate the spectral data with the reference (laboratory) soil data using two-thirds of the available samples for calibration and the remaining third to independently validate them. Spectral pre-processing methods (first and second derivatives, wavelet detrending) and spectra pre-treatment (mean centre), were employed after smoothing with median filtering, to improve the robustness and performance of the calibration models. Leave-one-out cross-validation was then used to determine the number of factors to retain in the calibration models. To select the optimal cross-validated calibration model, the root mean squared error (RMSE) of predictions was computed. To evaluate the accuracy of models the relative percent deviation (RPD), i.e., the ratio of the standard deviation of analysed data (i.e., the soil properties) to root means square error (RMSE), was considered. Very good predictions were obtained for Thallium, Tl (RPD = 2.04 for calibration and 1.88 for validation) and Chromium, Cr, (RPD = 2.03 and 1.91), and that for Beryllium, Be, was good (RPD = 1.83 and 1.89), whereas prediction for Vanadio, V, was fair (RPD = 1.68 and 1.55). Prediction for the remaining heavy metals was poor. The results of a recent investigation demonstrated that Be, V and Tl are the heavy metals with the greatest impact on soil contamination (as evaluated with reference to the so-called "concentration threshold of contamination" set by law for urban and agricultural areas) in the study area. Therefore, following the outcomes of our preliminary investigation, vis-NIR reflectance spectroscopy can be considered as a promising, innovative technique for the characterisation and monitoring of heavy metals, at least those of greater attention, within the study area, although further insights need to be carried out. |
| Databáze: | OpenAIRE |
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