Soil parameters affecting the levels of potentially harmful metals in Thessaly area, Greece: a robust quadratic regression approach of soil pollution predictionSoil parameters affecting the levels of potentially harmful metals in Thessaly area, Greece: a robust quadratic regression approach of soil pollution prediction
Peer-Reviewed Journal Publication
Δημοσίευση σε Περιοδικό με Κριτές
2022-11-102022enThe behavior and possible contamination risk due to the presence of potentially harmful metals (PHM) were studied based on 2250 soil samples that were collected in a 5-year period (2013–2017) from the plain of Thessaly (prefectures of Karditsa, Trikala, and Larissa). The vertical distribution of metals was also investigated from sample profiles at three depths 0–30, 30–60, and 60–90cm. The soils of the sampling belong to four taxonomy soil orders that are dominant in the studied area (Alfisols, Inceptisols, Endisols, and Vertisols). In a novel approach, robust quadratic regression analysis on multiple variables was used to define prediction models of the concentrations of two metals: Fe which is an essential metal and the toxic Cd. Linear and quadratic regression formulae were estimated based on the iteratively reweighted least squares robust regression approach in an effort to eliminate the impact of the outliers. These formulae define how several soil properties affect the distribution of the considered metals in each soil order. The evaluation of the estimated regression equations based on the R2 metric indicates that they constitute a useful, reliable, and valuable tool for managing, describing, and predicting the pollution in the studied area.http://creativecommons.org/licenses/by/4.0/Environmental Science and Pollution Research292029544–29561
Golia Evangelia E.
Diakoloukas Vasileios
Διακολουκας Βασιλειoς
Springer
Heavy metals
Quadratic regression
Iteratively reweighted least squares robust regression
Alfisols
Inceptisols
Endisols
Vertisols