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To meet the continuous growth of urbanised areas with the ever-increasing demand for safe water supplies, the implementation of new scientifically based methodologies can represent a key support for preventing groundwater quality deterioration. In this study, a new combined approach based on the application of the Weights of Evidence and the Null-Space Monte Carlo particle back-tracking methods was set up to assess tetrachloroethylene (PCE) contamination due to Point Sources in the densely urbanised north-eastern sector of the Milano FUA (Functional Urban Area). This combined approach offers the advantage of further enhancing the power of each individual technique by integrating both the advective transport mechanism, neglected by the Weights of Evidence, and the influence of specific factors, such as the land use variation, not considered by the Null-Space Monte Carlo particle tracking. To accurately test and explore the performance of this new approach, the analysis was carried out based on the simulation of synthetic PCE plumes using a groundwater numerical model already implemented in a previous study. The Weights of Evidence method revealed that the areas characterised by a groundwater depth lower than 17 m, a groundwater velocity higher than 2.6 × 10 -6  m/s, a recharge higher than 0.26 m/y and a significant variation of the industrial activities extent are the most susceptible to groundwater pollution. The Null-Space Monte Carlo particle back-tracking has proved to be effective in delineating the potential source zones and contaminant travel path. The proposed approach can offer additional insights for the protection of groundwater resource. The end-product provides crucial information on the zones that require to be prioritised for investigations and can be easily understood by non-expert decision-makers constituting an advanced tool for enhancing groundwater protection strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Groundwater status in highly urbanized areas is particularly affected by anthropogenic influence due to diffuse pollution deriving from many sources. This makes very often challenging to determine whether the observed groundwater conditions are the result of localized pollutant sources (PS-Point Sources). In the EU legislative framework it is accepted that, when Natural Background Levels (NBLs) of undesirable elements are proven to be higher than specific Groundwater Quality Standards (GQSs), NBLs should be assumed as GQSs. No procedure is instead defined when anthropogenic Diffuse Pollution Background levels (DBPLs) are higher than GQSs and make unfeasible any remediation strategy. Among the many contaminants affecting groundwater, the chlorinated solvents, tetrachloroethylene (PCE), trichloroethylene (TCE) and trichloromethane (TCM) among the organics and hexavalent chromium, among the inorganics, having been widely used in several industries all over Europe, are very often the most prevalent contaminants in soil and groundwater. Aim of this paper is to discuss a multivariate statistical approach to address the issue of identification of anthropogenic Diffuse Pollution Background Levels. With such aim, an area of about 1600 km 2 , including the Functional Urban Area of Milan, was considered and 10 independent geochemical datasets, provided by local and regional agencies, and covering the period 2003-2014 were merged into a single database after homogenization and multiple quality checks. A total of 618,258 chemical analyses from 3477 sampling wells were considered, being all samples collected and analyzed through internally consistent protocols. The analysis enabled to identify five main clusters, having specific hydrogeological characteristics, different temporal profiles and pollutant background concentration levels, which were also found to respond differently to meteo-climatic changes. This study offers a robust knowledge basis for drafting a diffuse pollution management plan of the area., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The Lombardy Region in Italy is one of the most urbanized and industrialized areas in Europe. The presence of countless sources of groundwater pollution is therefore a matter of environmental concern. The sources of groundwater contamination can be classified into two different categories: 1) Point Sources (PS), which correspond to areas releasing plumes of high concentrations (i.e. hot-spots) and 2) Multiple-Point Sources (MPS) consisting in a series of unidentifiable small sources clustered within large areas, generating an anthropogenic diffuse contamination. The latter category frequently predominates in European Functional Urban Areas (FUA) and cannot be managed through standard remediation techniques, mainly because detecting the many different source areas releasing small contaminant mass in groundwater is unfeasible. A specific legislative action has been recently enacted at Regional level (DGR IX/3510-2012), in order to identify areas prone to anthropogenic diffuse pollution and their level of contamination. With a view to defining a management plan, it is necessary to find where MPS are most likely positioned. This paper describes a methodology devised to identify the areas with the highest likelihood to host potential MPS. A groundwater flow model was implemented for a pilot area located in the Milan FUA and through the PEST code, a Null-Space Monte Carlo method was applied in order to generate a suite of several hundred hydraulic conductivity field realizations, each maintaining the model in a calibrated state and each consistent with the modelers' expert-knowledge. Thereafter, the MODPATH code was applied to generate back-traced advective flowpaths for each of the models built using the conductivity field realizations. Maps were then created displaying the number of backtracked particles that crossed each model cell in each stochastic calibrated model. The result is considered to be representative of the FUAs areas with the highest likelihood to host MPS responsible for diffuse contamination., (Copyright © 2017 Elsevier B.V. All rights reserved.)

A laboratory approach was adopted in this study to explore the potential of 37 Cl-CSIA in combination with 13 C-CSIA and Biological Molecular Tools (BMTs) to estimate the occurrence of monochloroenzene (MCB) aerobic biodegradation. A new analytical method for 37 Cl-CSIA of MCB was developed in this study. This methodology using a GC-IRMS allowed to determine δ 37 Cl values within an internal error of ±0.3‰. Samples from a heavily MCB contaminated site were collected and MCB aerobic biodegradation microcosms with indigenous cultures in natural and enhanced conditions were set up. The microcosms data show a negligible fractionation for 13 C associated to MCB mass decrease of >95% over the incubation time. Conversely, an enrichment factor of -0.6±0.1‰ was estimated for 37 Cl, which is a reflection of a secondary isotope effect. Moreover, the dual isotope approach showed a pattern for aerobic degradation which differ from the theoretical trend for reductive dehalogenation. Quantitative Polymerase Chain Reaction (qPCR) results showed a significant increase in todC gene copy number with respect to its initial levels for both natural attenuation and biostimulated microcosms, suggesting its involvement in the MCB aerobic degradation, whereas phe gene copy number increased only in the biostimulated ones. Indeed, 37 Cl fractionation in combination with the dual carbon‑chlorine isotope approach and the todC gene copy number represent valuable indicators for a qualitative assessment of MCB aerobic biodegradation in the field., (Copyright © 2017 Elsevier B.V. All rights reserved.)