High-resolution geoelectrical characterization and monitoring of natural fluids emission systems to understand possible gas leakages from geological carbon storage reservoirs.

Gas leakage from deep geologic storage formations to the Earth's surface is one of the main hazards in geological carbon sequestration and storage. Permeable sediment covers together with natural pathways, such as faults and/or fracture systems, are the main factors controlling surface leakages. Therefore, the characterization of natural systems, where large amounts of natural gases are released, can be helpful for understanding the effects of potential gas leaks from carbon dioxide storage systems. In this framework, we propose a combined use of high-resolution geoelectrical investigations (i.e. resistivity tomography and self-potential surveys) for reconstructing shallow buried fracture networks in the caprock and detecting preferential gas migration pathways before it enters the atmosphere. Such methodologies appear to be among the most suitable for the research purposes because of the strong dependence of the electrical properties of water-bearing permeable rock, or unconsolidated materials, on many factors relevant to CO2 storage (i.e. porosity, fracturing, water saturation, etc.). The effectiveness of the suggested geoelectrical approach is tested in an area of natural gas degassing (mainly CH4) located in the active fault zone of the Bolle della Malvizza (Southern Apennines, Italy), which could represent a natural analogue of gas storage sites due to the significant thicknesses (hundreds of meters) of impermeable rock (caprock) that is generally required to prevent carbon dioxide stored at depth from rising to the surface. The obtained 3D geophysical model, validated by the good correlation with geochemical data acquired in the study area and the available geological information, provided a structural and physical characterization of the investigated subsurface volume. Moreover, the time variations of the observed geophysical parameters allowed the identification of possible migration pathways of fluids to the surface.

Fe and As geochemical self-removal dynamics in mineral waters: evidence from the Ferrarelle groundwater system (Riardo Plain, Southern Italy).

A theoretical pattern for Fe and As co-precipitation was tested directly in a groundwater natural system. Several monitoring wells were sampled to identify the different endmembers that govern the hydrodynamics of the Ferrarelle Groundwater System in the Riardo Plain (Southern Italy). In agreement with recent investigations, we found a mix of a deep and a shallow component in different proportions, resulting in a specific chemical composition of groundwater in each well depending on the percentages of each component. The shallow component was characterized by EC ~ 430 µS/cm, Eh ~ 300 mV, Fe ~ 0.06 µmol/L and As ~ 0.01-0.12 µmol/L, while the deep component was characterized by EC ~ 3400 µS/cm, Eh ~ 170 mV, Fe ~ 140 µmol/L and As ~ 0.59 µmol/L. A general attenuation of As and Fe concentration that was not due to a simple dilution effect was observed in the mixing process. The oxidation of Fe(II) to Fe(III) produces solid precipitates which adsorb As from solution and then co-precipitate. The reactions pattern of Fe(II) oxidation and As adsorption gave a linear function between [As] and [Fe], where the angular coefficient depends on the [O2]/[H+] ratio. Chemical data obtained from our samples showed a very good agreement with this theoretical relationship. The investigated geochemical dynamics represented a natural process of attenuation of Fe and As, two undesirable elements that usually affect groundwater quality in volcanic aquifers in central-southern Italy, which are exploited to supply drinking water.

Tracing groundwater circulation in a valuable mineral water basin with geochemical and isotopic tools: the case of FERRARELLE, Riardo basin, Southern Italy.

The Riardo basin hosts groundwater exploited for the production of high quality, naturally sparkling, bottled water (e.g., Ferrarelle water), and circulating in a system constituted by highly fractured Mesozoic carbonates, overlain by more impervious volcanic rocks of the Roccamonfina complex. The two formations are locally in hydraulic connection and dislocated by deep-rooted faults. The study aimed at elucidating groundwater origin and circulation, using isotopic tracers (δ18O, δ2H, δ11B and 87Sr/86Sr) coupled to groundwater dating (Tritium, CFCs and SF6). Besides recharge by local precipitation over the Riardo hydrogeological basin, stable isotope ratios in water indicated an extra-basin recharge, likely from the elevated surrounding carbonate reliefs (e.g., Maggiore and Matese Mts.). The mineralization process, promoted by the deep CO2 flux, controls the B and Sr contents. However, their isotopic ratios did not allow discriminating between circulation in the volcanic and in the carbonate aquifers, as in the latter the isotopic composition differed from the original marine signature. Groundwater model ages ranged from ~ 30 years for the volcanic endmember to > 70 years for the deep, mineralized end-member, with longer circuits recharged at higher elevations. Overall, the results of this study were particularly relevant for mineral water exploitation. A recharge from outside the hydrogeological basin could be evidenced, especially for the more mineralized and valuable groundwater, and an active recent recharge was detected for the whole Riardo system. Both findings will contribute to the refinement of the hydrogeological model and water budget, and to a sustainable development of the resource.

Geochemical characterization and health risk assessment in two diversified environmental settings (Southern Italy).

An integrated approach using chemical and microbial indicators has been tested in two different sites of the Campania Plain (Southern Italy) with different land use covering and different hydrogeological features in order: (1) to define the water-rock interaction processes, (2) to differentiate sources of pollution in a detailed way (3) to evaluate the degree of water quality in the studied alluvial aquifer and (4) to identify the most worrying elements for human's health. Groundwater have showed a HCO3-Ca signature for both investigated sites, and a progressive enrichment in alkali ions has been highlighted moving from the boundary of the plain toward the coastal areas, due to groundwater interaction with volcanic rocks along the flow path. The application of the Factor Analysis allowed to identify different sources of pollution, which were attributed to (a) leaks in the sewer system for the Agro-Aversano Area and also the spreading of manure as fertilizers in agricultural activities for the Caiazzo Plain. Furthermore, it has been highlighted that the use of major elements, trace elements and microbiological indicators, allows to accurately differentiate contamination processes in progress. In fact, from the results of the Factor Analysis applied in the Agro-Aversano area, no significant statistically relationships between major elements and microbiological indicators of fecal contamination were highlighted, unlike the Caiazzo plain where statistically significant correlations have been found between major and trace elements and microbiological indicators. The use of a Groundwater Quality Index has shown general poor water quality for the majority of analyzed samples due to the high amount of Nitrate and Fecal indicators. The use of a Health Risk Assessment highlighted that Nitrate coupled with Fluoride represent the most important concern for human health compared to the all investigated parameters in both sites.

Predictive modeling of selected trace elements in groundwater using hybrid algorithms of iterative classifier optimizer.

Trace element (TE) pollution in groundwater resources is one of the major concerns in both developing and developed countries as it can directly affect human health. Arsenic (As), Barium (Ba), and Rubidium (Rb) can be considered as TEs naturally present in groundwater due to water-rock interactions in Campania Plain (CP) aquifers, in South Italy. Their concentration could be predicted via some readily available input variables using an algorithm like the iterative classifier optimizer (ICO) for regression, and novel hybrid algorithms with additive regression (AR-ICO), attribute selected classifier (ASC-ICO) and bagging (BA-ICO). In this regard, 244 groundwater samples were collected from water wells within the CP and analyzed with respect to the electrical conductivity, pH, major ions and selected TEs. To develop the models, the available dataset was divided randomly into two subsets for model training (70% of the dataset) and evaluation (30% of the dataset), respectively. Based on the correlation coefficient (r), different input variables combinations were constructed to find the most effective one. Each model's performance was evaluated using common statistical and visual metrics. Results indicated that the prediction of As and Ba concentrations strongly depends on HCO3-, while Na+ is the most effective variable on Rb prediction. Also, the findings showed that the most powerful predictive models were those that used all the available input variables. According to models' performance evaluation metrics, the hybrid ASC-ICO outperformed other hybrid (BA- and AR-ICO) and standalone (ICO) algorithms to predict As and Ba concentrations, while both hybrid ASC- and BA-ICO models had higher accuracy and lower error than other algorithms for Rb prediction.

Baseline for rainwater chemistry and quality as influenced by Nyiragongo volcano permanent plume, East Africa.

Single rainwater samples were collected in the city of Goma (~1,1 million inhabitants), eastern Democratic Republic of the Congo, from January to June 2013 to draw a baseline for rainwater chemical composition and quality as influenced by the permanent plume of Nyiragongo volcano. This was a better period for a baseline as the neighboring Nyamulagira volcano, only 15 km apart, had no important degassing from its central crater, and hence the recorded volcanic influence on the rainwater chemistry was solely from Nyiragongo's lava lake which has been active since May 2002. The baseline for the rainwater chemistry and quality is important for this highly populated region where rainwater is the unique potable water source for the inhabitants of many villages surrounding the volcanoes, and for some of the inhabitants of the city of Goma. Our results show that samples collected at the crater rim of Nyiragongo were more acidic with pH ranging from 3.70 to 3.82, while the majority of rainwater samples collected in downtown Goma city and to the northeastern zone of the volcano had pH close to 5.7; which represents the value for rainwater from unpolluted continental areas (Berner and Berner, 2012). However, the pH was as low as 3.93 to the west of Nyiragongo volcano because the volcanic plume is directed westward by the dominant local wind direction. The western part of the city of Goma as well as the small town of Sake and many villages (e.g. Rusayo, Mubambiro, Kingi, …) are located in this zone, and experience endemic fluorosis caused by high fluoride in the available water. The mean F- in this zone was 0.38 mg/L, while the southern and northeastern zones had mean F- concentrations on 0.44 and 0.01 mg/L respectively; even though concentrations higher than the WHO guidelines were found in few samples from the western zone (1.69 mg/L) and from the southern zone (3.44 mg/L). Compared to data from Cuoco et al. (2012) obtained during the Nyamulagira 2010 eruption, and from Balagizi et al.2017 and Liotta et al., 2017 obtained during the intense degassing of both Nyiragongo and Nyamulagira lava lakes; we have noted similarity in the spatial variation of the pH, but samples from the present study showed notable lower concentrations of major elements. This is the case for fluoride which is strictly of volcanic origin. For the other major elements, anthropogenic sources, mainly the traffic and wind-blown dust; or other non-volcanic natural sources influenced their concentrations. Thus, the anions (Cl- and SO42-) and cations (Na+, K+, Mg2+, and Ca2+) from the present study are either lower compared to that previously reported in the literature for the Virunga, or are both comparable for the zones impacted by anthropogenic activities.

Deep carbon degassing in the Matese massif chain (Southern Italy) inferred by geochemical and isotopic data.

The Italian Apennines are among the most important sources of freshwater for several Italian regions. With evidences of deep CO2-rich fluids intruding into aquifers in the nearby central-southern Apennines, a thorough investigation into the geochemistry of groundwater became critical to ensure the water quality in the area. Here, we show the main hydrogeochemical processes occurring in the Matese Massif (MM) aquifer through the investigation of 98 water samples collected from springs and water wells. All waters were classified as HCO3 type with Ca dominance (from 50% up to 97%) and variable amount of Mg (from 1% up to 49%). A multivariate statistical approach through the application of the factor analysis (FA) highlighted three main hydrogeochemical processes: (i) water-carbonate rock interactions mostly enhanced in peripheral areas of the MM by CO2 deep degassing; (ii) addition of NaCl-rich components linked to recharging process and to water mixing processes of the groundwater with a thermal component relatively rich in Cl, Na, and CO2; (iii) anthropogenic activities influencing groundwater composition at the foothills of MM. Furthermore, the first detailed TDIC, pCO2, and δ13C-TDIC distribution maps of the MM area have been created, which track chemical and isotopic anomalies in several peripheral areas (Pratella, Ailano, and Telese) throughout the region. These maps systematically highlight that the greater the amount of dissolved carbon occurs the heavier the C isotope enrichment, especially in the peripheral areas. Conversely, spring waters emerging at higher altitudes within MM are only slightly mineralized and associated with δ13C-TDIC values mainly characterized by recharging processes with the addition of biogenic carbon during the infiltration process through the soil.

Enhancing nitrate and strontium concentration prediction in groundwater by using new data mining algorithm.

Groundwater resources constitute the main source of clean fresh water for domestic use and it is essential for food production in the agricultural sector. Groundwater has a vital role for water supply in the Campanian Plain in Italy and hence a future sustainability of the resource is essential for the region. In the current paper novel data mining algorithms including Gaussian Process (GP) were used in a large groundwater quality database to predict nitrate (contaminant) and strontium (potential future increasing) concentrations in groundwater. The results were compared with M5P, random forest (RF) and random tree (RT) algorithms as a benchmark to test the robustness of the modeling process. The dataset includes 246 groundwater quality samples originating from different wells, municipals and agricultural. It was divided for the modeling process into two subgroups by using the 10-fold cross validation technique including 173 samples for model building (training dataset) and 73 samples for model validation (testing dataset). Different water quality variables including T, pH, EC, HCO3-, F-, Cl-, SO42-, Na+, K+, Mg2+, and Ca2+ have been used as an input to the models. At first stage, different input combinations have been constructed based on correlation coefficient and thus the optimal combination was chosen for the modeling phase. Different quantitative criteria alongside with visual comparison approach have been used for evaluating the modeling capability. Results revealed that to obtain reliable results also variables with low correlation should be considered as an input to the models together with those variables showing high correlation coefficients. According to the model evaluation criteria, GP algorithm outperforms all the other models in predicting both nitrate and strontium concentrations followed by RF, M5P and RT, respectively. Result also revealed that model's structure together with the accuracy and structure of the data can have a relevant impact on the model's results.

A novel hybrid method of specific vulnerability to anthropogenic pollution using multivariate statistical and regression analyses.

Groundwater resources are the main supply of freshwater for human activities. However, in the last fifty years aquifers have become more susceptible to chemical pollution due to human activities. The concept of groundwater vulnerability constitutes a worldwide accepted tool for water protection and planning. However, the existing methods and modified versions do not account for all the hydrogeochemical processes that drive anthropogenic pollution. The hydrogeochemical processes occurring within an aquifer can be determined using multivariate statistical analysis. In this study a specific vulnerability method named SVAP (Specific Vulnerability to Anthropogenic Pollution) is proposed. The index is based on seven quantitative parameters: depth to groundwater, recharge, nitrate losses, hydraulic resistance of the vadose zone, aquifer thickness, hydraulic conductivity of the aquifer, and slope. Weights of anthropogenic factors were determined by factor analysis and used to validate the SVAP methodology. The parameters' classification was selected according to the highest Pearson's correlation coefficient with factor weights and then grouped via a linear combination. The new index was applied in two watersheds: the Florina basin (Greece) and the Garigliano River basin (Italy), both of which possess complex hydrogeochemical regimes. The main hydrogeochemical processes acting in the study areas were identified via factor analysis, which revealed that the anthropogenic pollution in both sites was due mainly to chemical fertilizers and manure. Verification of the SVAP method produced correlation coefficients with nitrate concentrations of 0.75 and 0.62 in Florina and Garigliano, respectively. The proposed SVAP method is more reliable and flexible than standard vulnerability assessment methods and can be easily adapted for complex aquifers.

Evaluating the suitability of urban groundwater resources for drinking water and irrigation purposes: an integrated approach in the Agro-Aversano area of Southern Italy.

Deterioration of groundwater quality due to the introduction of pollutants from natural and anthropic sources has become a major environmental issue. We tested three methodologies in assessing groundwater quality and intrinsic aquifer vulnerability in the Agro-Aversano area (Southern Italy). A geographic information system (GIS)-based groundwater quality index (GQI) was realized to assess groundwater quality for drinking and irrigation use and, in parallel, standard SINTACS was applied to evaluate the intrinsic vulnerability of the aquifer. Nitrate concentrations and sodium absorption ratio (SAR) in groundwater samples were used to verify the reliability of vulnerability data. GQI analysis pointed to a general poor quality of groundwater both for drinking and irrigation use, especially in sub-urban areas. The spatial pattern of water quality from GQI analysis was positively related to nitrate and fluoride concentrations for drinking use and to bicarbonate and sodium concentrations for irrigation use, whose levels exceeded the WHO and FAO recommended thresholds, respectively. Standard SINTACS was found to be inadequate for describing the aquifer state, its results showing no correlation with nitrate concentration or SAR. Because of this inconsistency, we tested a novel approach combining GQI with SINTACS analysis. Results showed positive correlation with nitrate (r = 0.63) and SAR (r = 0.64) contents, thus pointing to combined SINTACS-GQI as a more reliable approach than standard methodologies.

Structural Characterization of the Lactobacillus Plantarum FlmC Protein Involved in Biofilm Formation.

Lactobacillus plantarum is one of the most predominant species in the human gut microbiota of healthy individuals. We have previously characterized some probiotic features of L. plantarum LM3, as the high resistance to different stress, the binding ability toward some extracellular matrix proteins and plasminogen and the immunomodulatory role of the surface expressed adhesin EnoA1. We have also identified the flmA, flmB and flmC genes, coding for putative proteins named FlmA, FlmB and FlmC, whose null mutations partially impaired biofilm development; the L. plantarum LM3⁻6 strain, carrying a deletion in flmC, showed a high rate of autolysis, supporting the hypothesis that FlmC might be involved in cell wall integrity. Here, we report the in-silico characterization of ΔTM-FlmC, a portion of the FlmC protein. The protein has been also expressed, purified and characterized by means of CD spectroscopy, ICP-mass and UHPLC-HRMS. The obtained experimental data validated the predicted model unveiling also the presence of a bound lipid molecule and of a Mg(II) ion. Overall, we provide strong evidences that ΔTM-FlmC belongs to the LytR-CpsA-Psr (LCP) family of domains and is involved in cell envelope biogenesis.

Influence of moisture source dynamics and weather patterns on stable isotopes ratios of precipitation in Central-Eastern Africa.

We report the first δ18O and δ2H data of Virunga rainfall in the Eastern Democratic Republic of the Congo, situated on the limit between Central and Eastern Africa. The dataset is from 13 rain gauges deployed at Mount Nyiragongo and its surroundings sampled monthly between December 2013 and October 2015. The δ18O and δ2H vary from -6.44 to 6.16‰, and -32.53 to 58.89‰ respectively, and allowed us to define a LMWL of δ2H = 7.60δ18O + 16.18. Three main wind directions, i.e. NE, E and SE, were identified in the upper atmosphere corresponding to three major moisture source regions. On the contrary, lower atmospheric winds are weaker in nature and originate mainly from the S and SW, creating a topographically-driven, more local moisture regime. The latter is due to the accumulation in the floor of the rift of water vapor from Lake Kivu forming a layer of isotopically enriched vapor that mediates the isotope enrichment of the falling raindrops. A strong seasonality is observed in both δ18O and δ2H data, and is primarily driven by combined seasonal and spatial variation in the moisture sources. The δ18O and δ2H seasonality is thus correlated to weather patterns, as the latter control the wet to dry season shifting, and vice versa. The key characteristic of seasonality is the variation of monthly precipitation amounts, since the mean monthly air temperature is nearly constant on an annual scale. Two regionally relevant hydrological processes contribute to the isotopic signature: namely moisture uptake from the isotopically enriched surface waters of East African lakes and from the depleted soil-water and plants. Consequently, the proportion of water vapor from each of these reservoirs in the atmosphere drives the enrichment or depletion of δ2H and δ18O in the precipitation. Thus, during wet periods the vapor from soil-plants evapotranspiration dominates yielding isotopically depleted precipitation, contrary to dry periods when vapor from lakes surface evaporation dominates, yielding isotopically enriched precipitation. At the global scale, our dataset reduces gaps in this region that has been poorly studied for δ18O and δ2H in precipitation. At the regional scale, the improved understanding of the ways land cover, moisture source seasonal and spatial dynamics, and atmospheric patterns impact precipitation spatial and temporal variabilities in Central-East African will contribute to the ongoing research on mitigating the impacts of ongoing climate change in Sub-Saharan Africa. The reduction of gaps and uncertainties in δ2H and δ18O of precipitation, and the understanding of their interrelation with weather patterns are essential for a better past, present and future environmental and climatic modelling at both local and regional scales.

Multivariate statistical analysis to characterize/discriminate between anthropogenic and geogenic trace elements occurrence in the Campania Plain, Southern Italy.

Shallow aquifers are the most accessible reservoirs of potable groundwater; nevertheless, they are also prone to various sources of pollution and it is usually difficult to distinguish between human and natural sources at the watershed scale. The area chosen for this study (the Campania Plain) is characterized by high spatial heterogeneities both in geochemical features and in hydraulic properties. Groundwater mineralization is driven by many processes such as, geothermal activity, weathering of volcanic products and intense human activities. In such a landscape, multivariate statistical analysis has been used to differentiate among the main hydrochemical processes occurring in the area, using three different approaches of factor analysis: (i) major elements, (ii) trace elements, (iii) both major and trace elements. The elaboration of the factor analysis approaches has revealed seven distinct hydrogeochemical processes: i) Salinization (Cl-, Na+); ii) Carbonate rocks dissolution; iii) Anthropogenic inputs (NO3-, SO42-, U, V); iv) Reducing conditions (Fe2+, Mn2+); v) Heavy metals contamination (Cr and Ni); vi) Geothermal fluids influence (Li+); and vii) Volcanic products contribution (As, Rb). Results from this study highlight the need to separately apply factor analysis when a large data set of trace elements is available. In fact, the impact of geothermal fluids in the shallow aquifer was identified from the application of the factor analysis using only trace elements. This study also reveals that the factor analysis of major and trace elements can differentiate between anthropogenic and geogenic sources of pollution in intensively exploited aquifers.

Dynamics of natural contamination by aluminium and iron rich colloids in the volcanic aquifers of Central Italy.

The dynamics of natural contamination by Al and Fe colloids in volcanic aquifers of central-southern Italy were investigated. Localized perched aquifers, and their relative discharges, are strongly affected by the presence of massive suspended solids, which confer a white-lacteous coloration to the water. This phenomenon occasionally caused the interruption of water distribution due to the exceeding of Al and Fe concentrations in aquifers exploited for human supply. The cause was ascribed to water seepage from perched aquifers. Water discharges affected by such contamination was investigated for the Rocca Ripesena area (north-eastern sector of Vulsini Volcanic District) and for the Rianale Stream Valley (Roccamonfina Volcanic Complex). Hydrogeological survey of both areas confirmed the presence of perched aquifers not previously considered due to their low productivity. Pluviometric data and chemical parameters were periodically monitored. Water mineralization decreased with increasing rainfall, conversely Al and Fe concentrations increased. Statistical analysis confirmed the dependence of all the chemical variables on rock leaching, with the sole exception of Al and Fe which were imputed to colloids mobilization from local, strongly pedogenized pyroclastic material. The similarities in hydrogeological settings and mobilization dynamics in both areas suggest that the Al and Fe colloidal contamination should be more abundant than currently known in quaternary volcanic areas.

Impact of volcanic plume emissions on rain water chemistry during the January 2010 Nyamuragira eruptive event: implications for essential potable water resources.

On January 2, 2010 the Nyamuragira volcano erupted lava fountains extending up to 300 m vertically along an ~1.5 km segment of its southern flank cascading ash and gas on nearby villages and cities along the western side of the rift valley. Because rain water is the only available potable water resource within this region, volcanic impacts on drinking water constitutes a major potential hazard to public health within the region. During the 2010 eruption, concerns were expressed by local inhabitants about water quality and feelings of physical discomfort (e.g. nausea, bloating, indigestion, etc.) after consuming rain water collected after the eruption began. We present the elemental and ionic chemistry of drinking water samples collected within the region on the third day of the eruption (January 5, 2010). We identify a significant impact on water quality associated with the eruption including lower pH (i.e. acidification) and increases in acidic halogens (e.g. F(-) and Cl(-)), major ions (e.g. SO(4)(2-), NH(4)(+), Na(+), Ca(2+)), potentially toxic metals (e.g. Al(3+), Mn(2+), Cd(2+), Pb(2+), Hf(4+)), and particulate load. In many cases, the water's composition significantly exceeds World Health Organization (WHO) drinking water standards. The degree of pollution depends upon: (1) ash plume direction and (2) ash plume density. The potential negative health impacts are a function of the water's pH, which regulates the elements and their chemical form that are released into drinking water.