A Bayesian approach for the assessment of shallow and deep aquifers susceptibility to point sources contamination in the Province of Milan, Italy

In densely populated areas, urban and industrial activities are responsible for groundwater quality deterioration due to point sources contamination (Kuroda and Fukushi, 2008). In the Province of Milan (Northern Italy), the available water-quality data indicate the occurrence of high PCE+TCE and chromium concentrations in the unconfined shallow as well as in the confined deep aquifers. To cope with this problem, statistical methods can represent reliable tools to provide key information for groundwater management and protection

An Enhanced Approach to the Spatial and Statistical Analysis of Factors Influencing Spring Distribution on a Transboundary Karst Aquifer

Karst aquifers are indispensable, yet vulnerable, resources; therefore, they require a comprehensive protection strategy. Since springs are the terminal points of the karst flow systems, knowledge of their distribution is a key element for the better understanding of groundwater flow, availability and vulnerability. The present study aims to introduce a data-driven analysis by the application of a spatial statistical technique (Weights of Evidence (WofE)) for the evaluation of factors influencing spring distribution in karst areas. A workflow was developed for investigating two questions: where will the springs locate, and where will the permanent springs evolve? This workflow has the potential for application to unconfined karst areas. This enhanced approach was applied to an unconfined transboundary aquifer, the G\uf6m\uf6r\u2013Torna Karst (HU and SK). The roles of five factors was statistically investigated: terrain elevation, distance to faults, distance of the carbonate\u2013non-carbonate rock contact, distance to sinkholes, and precipitation distribution. The validation procedures confirmed the effectiveness of the approach. The resulting predictive maps are useful for decision-makers to delineate areas holding potential karst springs and to address water availability problems and protection measures. In addition, the WofE technique improved the comprehension of the geological conditions favourable for the formation of the springs

A Bayesian approach for the assessment of shallow and deep aquifers susceptibility to point sources contamination in the Province of Milan, Italy

In densely populated areas, urban and industrial activities are responsible for groundwater quality deterioration due to point sources contamination (Kuroda and Fukushi, 2008). In the Province of Milan (Northern Italy), the available water-quality data indicate the occurrence of high PCE+TCE and chromium concentrations in the unconfined shallow as well as in the confined deep aquifers. To cope with this problem, statistical methods can represent reliable tools to provide key information for groundwater management and protection

Implementation of satellite-based data for improving predictions of arsenic contamination in groundwater in the Red River Delta in Vietnam

Natural arsenic contamination of groundwater aquifers is globally widespread, and particularly poses a problem in regions where groundwater is the main source of drinking and cooking water. Arsenic poisoning can lead to a myriad of serious health effects such as diseases of blood vessels, diabetes and cancers. The aquifers of the Red River Delta in Vietnam are highly contaminated with arsenic and it has been estimated that in this area, around 3 million people are affected by high arsenic concentrations (> 10 \ub5g/L, WHO guideline value; Winkel et al., 2011). Previously, predictions of arsenic contamination in the Red River Delta were established via geospatial modelling using arsenic measurements, as well as surface and 3D-geology. Based on these predictions, probability maps of arsenic at specific depths were created. By comparing these depthresolved probabilities to measured arsenic concentrations, a drawdown of arsenic-enriched waters from Holocene aquifers to previously uncontaminated Pleistocene aquifers was observed. This finding indicated that arsenic contamination has been exacerbated by excessive groundwater pumping rates (Winkel et al., 2011). Furthermore, in a study conducted in the Mekong delta, it was hypothesized that groundwater extraction causes interbedded clays to compact, thereby releasing water containing dissolved arsenic that is subsequently transported to deeper aquifers (Erban et al., 2013). Such human-induced changes cannot be captured by the previous predictive models based on natural predictive parameters mentioned above, leading to erroneous predictions of the arsenic content in areas affected by urbanization, especially in deeper aquifers. To improve predictions in human-affected regions we are using satellite data and remote sensing techniques that enable detection of changes of urban and suburban extents (Nghiem et al., 2009) and vertical build-up (Mathews et al., 2019). Those data and techniques in combination with geochemical and environmental data can help in i) resolving mechanisms behind arsenic mobilization in aquifers due to increased pumping rates and ii) making predictions of arsenic contamination more accurate, especially in areas characterized by increased groundwater pumping

Spatial statistical assessment of groundwater PCE (Tetrachloroethylene) diffuse contamination in urban areas

Contamination by chlorinated solvents is typically associated with point sources, which are able to release high concentrations and to generate well defined plumes. Nevertheless, in urban settings (especially in functional urban areas\u2014FUAs), multiple-point sources are frequently present, consisting of a series of unidentifiable small sources clustered within large areas, generating a diffuse, anthropogenic contamination. This situation results in the coexistence of single plumes with higher contaminant concentrations, and larger areas where the concentration is lower but still higher than the maximum admissible concentration limits. This paper proposes a methodology devised to cope with the diffuse contamination by chlorinated solvents within shallow aquifers due to multiple-point sources in FUAs. The approach is based on a Bayesian model that helps to spatially evaluate the likelihood of having active multiple-point sources, and to relate their impact on the shallow aquifer to the hydrogeological features of the area. Moreover, the approach allows testing of the efficiency of the monitoring network to properly characterize the contamination in the aquifer. The consistency of the results of the analysis was also checked for the Milan FUA (Italy) by a comparison to a previous study, performed through an inverse numerical modelling approach within a Monte Carlo statistical framework to identify the areas with the highest likelihood to host potential multiple-point sources

Protein profiling in hepatocellular carcinoma by label-free quantitative proteomics in two west african populations.

Background Hepatocellular Carcinoma is the third most common cause of cancer related death worldwide, often diagnosed by measuring serum AFP; a poor performance stand-alone biomarker. With the aim of improving on this, our study focuses on plasma proteins identified by Mass Spectrometry in order to investigate and validate differences seen in the respective proteomes of controls and subjects with LC and HCC. Methods Mass Spectrometry analysis using liquid chromatography electro spray ionization quadrupole time-of-flight was conducted on 339 subjects using a pooled expression profiling approach. ELISA assays were performed on four significantly differentially expressed proteins to validate their expression profiles in subjects from the Gambia and a pilot group from Nigeria. Results from this were collated for statistical multiplexing using logistic regression analysis. Results Twenty-six proteins were identified as differentially expressed between the three subject groups. Direct measurements of four; hemopexin, alpha-1-antitrypsin, apolipoprotein A1 and complement component 3 confirmed their change in abundance in LC and HCC versus control patients. These trends were independently replicated in the pilot validation subjects from Nigeria. The statistical multiplexing of these proteins demonstrated performance comparable to or greater than ALT in identifying liver cirrhosis or carcinogenesis. This exercise also proposed preliminary cut offs with achievable sensitivity, specificity and AUC statistics greater than reported AFP averages. Conclusions The validated changes of expression in these proteins have the potential for development into high-performance tests usable in the diagnosis and or monitoring of HCC and LC patients. The identification of sustained expression trends strengthens the suggestion of these four proteins as worthy candidates for further investigation in the context of liver disease. The statistical combinations also provide a novel inroad of analyses able to propose definitive cut-offs and combinations for evaluation of performance