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Evaluation of Hydrocarbon Soil Pollution Using E-Nose

The possibility of detecting low levels of soil pollution by petroleum fuel using an electronic nose (e-nose) was studied. An attempt to distinguish between pollution caused by petrol and diesel oil, and its relation to the time elapsed since the pollution event was simultaneously performed. Ten ara...

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Detalles Bibliográficos
Autores principales: Bieganowski, Andrzej, Józefaciuk, Grzegorz, Bandura, Lidia, Guz, Łukasz, Łagód, Grzegorz, Franus, Wojciech
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111446/
https://www.ncbi.nlm.nih.gov/pubmed/30061490
http://dx.doi.org/10.3390/s18082463
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author Bieganowski, Andrzej
Józefaciuk, Grzegorz
Bandura, Lidia
Guz, Łukasz
Łagód, Grzegorz
Franus, Wojciech
author_facet Bieganowski, Andrzej
Józefaciuk, Grzegorz
Bandura, Lidia
Guz, Łukasz
Łagód, Grzegorz
Franus, Wojciech
author_sort Bieganowski, Andrzej
collection PubMed
description The possibility of detecting low levels of soil pollution by petroleum fuel using an electronic nose (e-nose) was studied. An attempt to distinguish between pollution caused by petrol and diesel oil, and its relation to the time elapsed since the pollution event was simultaneously performed. Ten arable soils, belonging to various soil groups from the World Reference Base (WRB), were investigated. The measurements were performed on soils that were moistened to field capacity, polluted separately with both hydrocarbons, and then allowed to dry slowly over a period of 180 days. The volatile fingerprints differed throughout the course of the experiment, and, by its end, they were similar to those of the unpolluted soils. Principal component analysis (PCA) and artificial neural network (ANN) analysis showed that the e-nose results could be used to detect soil contamination and distinguish between pollutants and contamination levels.
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spelling pubmed-61114462018-08-30 Evaluation of Hydrocarbon Soil Pollution Using E-Nose Bieganowski, Andrzej Józefaciuk, Grzegorz Bandura, Lidia Guz, Łukasz Łagód, Grzegorz Franus, Wojciech Sensors (Basel) Article The possibility of detecting low levels of soil pollution by petroleum fuel using an electronic nose (e-nose) was studied. An attempt to distinguish between pollution caused by petrol and diesel oil, and its relation to the time elapsed since the pollution event was simultaneously performed. Ten arable soils, belonging to various soil groups from the World Reference Base (WRB), were investigated. The measurements were performed on soils that were moistened to field capacity, polluted separately with both hydrocarbons, and then allowed to dry slowly over a period of 180 days. The volatile fingerprints differed throughout the course of the experiment, and, by its end, they were similar to those of the unpolluted soils. Principal component analysis (PCA) and artificial neural network (ANN) analysis showed that the e-nose results could be used to detect soil contamination and distinguish between pollutants and contamination levels. MDPI 2018-07-30 /pmc/articles/PMC6111446/ /pubmed/30061490 http://dx.doi.org/10.3390/s18082463 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bieganowski, Andrzej
Józefaciuk, Grzegorz
Bandura, Lidia
Guz, Łukasz
Łagód, Grzegorz
Franus, Wojciech
Evaluation of Hydrocarbon Soil Pollution Using E-Nose
title Evaluation of Hydrocarbon Soil Pollution Using E-Nose
title_full Evaluation of Hydrocarbon Soil Pollution Using E-Nose
title_fullStr Evaluation of Hydrocarbon Soil Pollution Using E-Nose
title_full_unstemmed Evaluation of Hydrocarbon Soil Pollution Using E-Nose
title_short Evaluation of Hydrocarbon Soil Pollution Using E-Nose
title_sort evaluation of hydrocarbon soil pollution using e-nose
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111446/
https://www.ncbi.nlm.nih.gov/pubmed/30061490
http://dx.doi.org/10.3390/s18082463
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