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Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province

BACKGROUND: Ground waters are an important resource of water supply for human health and activities. Groundwater uses and applications are often related to its composition, which is increasingly influenced by human activities. In fact the water quality of groundwater is affected by many factors incl...

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Autores principales: Ielpo, Pierina, Cassano, Daniela, Lopez, Antonio, Pappagallo, Giuseppe, Uricchio, Vito Felice, De Napoli, Pasquale Abbruzzese
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3395135/
https://www.ncbi.nlm.nih.gov/pubmed/22594440
http://dx.doi.org/10.1186/1752-153X-6-S2-S5
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author Ielpo, Pierina
Cassano, Daniela
Lopez, Antonio
Pappagallo, Giuseppe
Uricchio, Vito Felice
De Napoli, Pasquale Abbruzzese
author_facet Ielpo, Pierina
Cassano, Daniela
Lopez, Antonio
Pappagallo, Giuseppe
Uricchio, Vito Felice
De Napoli, Pasquale Abbruzzese
author_sort Ielpo, Pierina
collection PubMed
description BACKGROUND: Ground waters are an important resource of water supply for human health and activities. Groundwater uses and applications are often related to its composition, which is increasingly influenced by human activities. In fact the water quality of groundwater is affected by many factors including precipitation, surface runoff, groundwater flow, and the characteristics of the catchment area. During the years 2004-2007 the Agricultural and Food Authority of Apulia Region has implemented the project “Expansion of regional agro-meteorological network” in order to assess, monitor and manage of regional groundwater quality. The total wells monitored during this activity amounted to 473, and the water samples analyzed were 1021. This resulted in a huge and complex data matrix comprised of a large number of physical-chemical parameters, which are often difficult to interpret and draw meaningful conclusions. The application of different multivariate statistical techniques such as Cluster Analysis (CA), Principal Component Analysis (PCA), Absolute Principal Component Scores (APCS) for interpretation of the complex databases offers a better understanding of water quality in the study region. RESULTS: Form results obtained by Principal Component and Cluster Analysis applied to data set of Foggia province it’s evident that some sampling sites investigated show dissimilarities, mostly due to the location of the site, the land use and management techniques and groundwater overuse. By APCS method it’s been possible to identify three pollutant sources: Agricultural pollution 1 due to fertilizer applications, Agricultural pollution 2 due to microelements for agriculture and groundwater overuse and a third source that can be identified as soil run off and rock tracer mining. CONCLUSIONS: Multivariate statistical methods represent a valid tool to understand complex nature of groundwater quality issues, determine priorities in the use of ground waters as irrigation water and suggest interactions between land use and irrigation water quality.
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spelling pubmed-33951352012-07-16 Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province Ielpo, Pierina Cassano, Daniela Lopez, Antonio Pappagallo, Giuseppe Uricchio, Vito Felice De Napoli, Pasquale Abbruzzese Chem Cent J Proceedings BACKGROUND: Ground waters are an important resource of water supply for human health and activities. Groundwater uses and applications are often related to its composition, which is increasingly influenced by human activities. In fact the water quality of groundwater is affected by many factors including precipitation, surface runoff, groundwater flow, and the characteristics of the catchment area. During the years 2004-2007 the Agricultural and Food Authority of Apulia Region has implemented the project “Expansion of regional agro-meteorological network” in order to assess, monitor and manage of regional groundwater quality. The total wells monitored during this activity amounted to 473, and the water samples analyzed were 1021. This resulted in a huge and complex data matrix comprised of a large number of physical-chemical parameters, which are often difficult to interpret and draw meaningful conclusions. The application of different multivariate statistical techniques such as Cluster Analysis (CA), Principal Component Analysis (PCA), Absolute Principal Component Scores (APCS) for interpretation of the complex databases offers a better understanding of water quality in the study region. RESULTS: Form results obtained by Principal Component and Cluster Analysis applied to data set of Foggia province it’s evident that some sampling sites investigated show dissimilarities, mostly due to the location of the site, the land use and management techniques and groundwater overuse. By APCS method it’s been possible to identify three pollutant sources: Agricultural pollution 1 due to fertilizer applications, Agricultural pollution 2 due to microelements for agriculture and groundwater overuse and a third source that can be identified as soil run off and rock tracer mining. CONCLUSIONS: Multivariate statistical methods represent a valid tool to understand complex nature of groundwater quality issues, determine priorities in the use of ground waters as irrigation water and suggest interactions between land use and irrigation water quality. BioMed Central 2012-05-02 /pmc/articles/PMC3395135/ /pubmed/22594440 http://dx.doi.org/10.1186/1752-153X-6-S2-S5 Text en Copyright ©2012 Ielpo et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Ielpo, Pierina
Cassano, Daniela
Lopez, Antonio
Pappagallo, Giuseppe
Uricchio, Vito Felice
De Napoli, Pasquale Abbruzzese
Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province
title Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province
title_full Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province
title_fullStr Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province
title_full_unstemmed Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province
title_short Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province
title_sort source apportionment of groundwater pollutants in apulian agricultural sites using multivariate statistical analyses: case study of foggia province
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3395135/
https://www.ncbi.nlm.nih.gov/pubmed/22594440
http://dx.doi.org/10.1186/1752-153X-6-S2-S5
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