The EU Water Framework Directive (EU-WFD) requires Member States to implement measures that reduce groundwater pollution resulting from the impact of human activity (article 4). In this context, it is essential to determine the contamination not related to widespread pollution, but significantly affected by still active human influence [1] in order to reverse the sustained upward trend in pollution concentration (article 4). In the Lombardy Plain area (Northern Italy), in particular in the Functional Urban Area (FUA) of Milan (about 1000 km2), the groundwater quality status is influenced not only by soil vulnerability, which is high due to the subsoil characteristic in this area, but also by the high density of industries and anthropic activities. The chlorinated solvents are one of the main contaminants and have been monitored and studied for several years. The great number of available analysis, coming from the several monitoring networks existing in the town, was a precious source of information and the cluster analysis was a useful tool to identify pollution hotspots in the main Aquifer of the study area. Although this technique has already been applied to investigate groundwater quality characteristics ([2]; [3], [4]), it is the first time it is applied to identify pollution hotspots in order to implement a transport numerical model. Cluster Analysis was proven to be extremely useful not only to identify PCE pollution hotspots and dataset outlier values, but also to classify the groundwater quality temporal profiles within spatial clusters. In the last phase of the study, the numerical model results could indicate the area extension of the plumes, not related to widespread pollution, but related only to the contamination hotspot sources.

USE OF CLUSTER ANALYSIS TO IDENTIFY TETRACHLOROETHYLENE POLLUTION HOTSPOTS FOR THE TRANSPORT NUMERICAL MODEL IMPLEMENTATION IN URBAN FUNCTIONAL AREA

ALBERTI, LUCA;AZZELLINO, ARIANNA;COLOMBO, LORIS;LOMBI, SILVIA
2016-01-01

Abstract

The EU Water Framework Directive (EU-WFD) requires Member States to implement measures that reduce groundwater pollution resulting from the impact of human activity (article 4). In this context, it is essential to determine the contamination not related to widespread pollution, but significantly affected by still active human influence [1] in order to reverse the sustained upward trend in pollution concentration (article 4). In the Lombardy Plain area (Northern Italy), in particular in the Functional Urban Area (FUA) of Milan (about 1000 km2), the groundwater quality status is influenced not only by soil vulnerability, which is high due to the subsoil characteristic in this area, but also by the high density of industries and anthropic activities. The chlorinated solvents are one of the main contaminants and have been monitored and studied for several years. The great number of available analysis, coming from the several monitoring networks existing in the town, was a precious source of information and the cluster analysis was a useful tool to identify pollution hotspots in the main Aquifer of the study area. Although this technique has already been applied to investigate groundwater quality characteristics ([2]; [3], [4]), it is the first time it is applied to identify pollution hotspots in order to implement a transport numerical model. Cluster Analysis was proven to be extremely useful not only to identify PCE pollution hotspots and dataset outlier values, but also to classify the groundwater quality temporal profiles within spatial clusters. In the last phase of the study, the numerical model results could indicate the area extension of the plumes, not related to widespread pollution, but related only to the contamination hotspot sources.
International Multidisciplinary scientific Geoconference On Science and Technologies in Geology, Exploration and Mining
978-619-7105-55-1
Statistic analysis
groundwater quality
pollution hotspot
numerical transport model
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1003315
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