Exploring Soil Pollution Patterns Using Self-Organizing Maps
The geochemical composition of bedrock is the key feature determining elemental concentrations in soil, followed by anthropogenic factors that have less impact. Concerning the latter, harmful effects on the trophic chain are increasingly affecting people living in and around urban areas. In the stud...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Toxics |
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| Online Access: | https://www.mdpi.com/2305-6304/10/8/416 |
| _version_ | 1797441609306996736 |
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| author | Ilaria Guagliardi Aleksander Maria Astel Domenico Cicchella |
| author_facet | Ilaria Guagliardi Aleksander Maria Astel Domenico Cicchella |
| author_sort | Ilaria Guagliardi |
| collection | DOAJ |
| description | The geochemical composition of bedrock is the key feature determining elemental concentrations in soil, followed by anthropogenic factors that have less impact. Concerning the latter, harmful effects on the trophic chain are increasingly affecting people living in and around urban areas. In the study area of the present survey, the municipalities of Cosenza and Rende (Calabria, southern Italy), topsoil were collected and analysed for 25 elements by inductively coupled plasma mass spectrometry (ICP-MS) in order to discriminate the different possible sources of elemental concentrations and define soil quality status. Statistical and geostatistical methods were applied to monitoring the concentrations of major oxides and minor elements, while the Self-Organizing Maps (SOM) algorithm was used for unsupervised grouping. Results show that seven clusters were identified—(I) Cr, Co, Fe, V, Ti, Al; (II) Ni, Na; (III) Y, Zr, Rb; (IV) Si, Mg, Ba; (V) Nb, Ce, La; (VI) Sr, P, Ca; (VII) As, Zn, Pb—according to soil elemental associations, which are controlled by chemical and mineralogical factors of the study area parent material and by soil-forming processes, but with some exceptions linked to anthropogenic input. |
| first_indexed | 2024-03-09T12:25:36Z |
| format | Article |
| id | doaj.art-40bed30fe65c4652859ff6e80499fe92 |
| institution | Directory Open Access Journal |
| issn | 2305-6304 |
| language | English |
| last_indexed | 2024-03-09T12:25:36Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Toxics |
| spelling | doaj.art-40bed30fe65c4652859ff6e80499fe922023-11-30T22:35:06ZengMDPI AGToxics2305-63042022-07-0110841610.3390/toxics10080416Exploring Soil Pollution Patterns Using Self-Organizing MapsIlaria Guagliardi0Aleksander Maria Astel1Domenico Cicchella2National Research Council of Italy—Institute for Agricultural and Forest Systems in Mediterranean (CNR-ISAFOM), Via Cavour 4/6, 87036 Rende, ItalyEnvironmental Chemistry Research Unit, Institute of Biology and Earth Sciences, Pomeranian University in Słupsk, 22a Arciszewskiego Str., 76-200 Słupsk, PolandDepartment of Science and Technology, University of Sannio, 82100 Benevento, ItalyThe geochemical composition of bedrock is the key feature determining elemental concentrations in soil, followed by anthropogenic factors that have less impact. Concerning the latter, harmful effects on the trophic chain are increasingly affecting people living in and around urban areas. In the study area of the present survey, the municipalities of Cosenza and Rende (Calabria, southern Italy), topsoil were collected and analysed for 25 elements by inductively coupled plasma mass spectrometry (ICP-MS) in order to discriminate the different possible sources of elemental concentrations and define soil quality status. Statistical and geostatistical methods were applied to monitoring the concentrations of major oxides and minor elements, while the Self-Organizing Maps (SOM) algorithm was used for unsupervised grouping. Results show that seven clusters were identified—(I) Cr, Co, Fe, V, Ti, Al; (II) Ni, Na; (III) Y, Zr, Rb; (IV) Si, Mg, Ba; (V) Nb, Ce, La; (VI) Sr, P, Ca; (VII) As, Zn, Pb—according to soil elemental associations, which are controlled by chemical and mineralogical factors of the study area parent material and by soil-forming processes, but with some exceptions linked to anthropogenic input.https://www.mdpi.com/2305-6304/10/8/416soilpotentially harmful elementscontaminationmultidimensional spatial analysisCalabria |
| spellingShingle | Ilaria Guagliardi Aleksander Maria Astel Domenico Cicchella Exploring Soil Pollution Patterns Using Self-Organizing Maps Toxics soil potentially harmful elements contamination multidimensional spatial analysis Calabria |
| title | Exploring Soil Pollution Patterns Using Self-Organizing Maps |
| title_full | Exploring Soil Pollution Patterns Using Self-Organizing Maps |
| title_fullStr | Exploring Soil Pollution Patterns Using Self-Organizing Maps |
| title_full_unstemmed | Exploring Soil Pollution Patterns Using Self-Organizing Maps |
| title_short | Exploring Soil Pollution Patterns Using Self-Organizing Maps |
| title_sort | exploring soil pollution patterns using self organizing maps |
| topic | soil potentially harmful elements contamination multidimensional spatial analysis Calabria |
| url | https://www.mdpi.com/2305-6304/10/8/416 |
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