The problem of identifying arsenic anomalies in the basin of Sahand dam through risk-based 'soft modelling'

Metabolic Derangement by Arsenic: a Review of the Mechanisms

Studies have implicated arsenic exposure in various pathological conditions, including metabolic disorders, which have become a global phenomenon, affecting developed, developing, and under-developed nations. Despite the huge risks associated with arsenic exposure, humans remain constantly exposed to it, especially through the consumption of contaminated water and food. This present study provides an in-depth insight into the mechanistic pathways involved in the metabolic derangement by arsenic. Compelling pieces of evidence demonstrate that arsenic induces metabolic disorders via multiple pathways. Apart from the initiation of oxidative stress and inflammation, arsenic prevents the phosphorylation of Akt at Ser473 and Thr308, leading to the inhibition of PDK-1/Akt insulin signaling, thereby reducing GLUT4 translocation through the activation of Nrf2. Also, arsenic downregulates mitochondrial deacetylase Sirt3, decreasing the ability of its associated transcription factor, FOXO3a, to bind to the agents that support the genes for manganese superoxide dismutase and PPARg co-activator (PGC)-1a. In addition, arsenic activates MAPKs, modulates p53/ Bcl-2 signaling, suppresses Mdm-2 and PARP, activates NLRP3 inflammasome and caspase-mediated apoptosis, and induces ER stress, and ox-mtDNA-dependent mitophagy and autophagy. More so, arsenic alters lipid metabolism by decreasing the presence of 3-hydroxy-e-methylglutaryl-CoA synthase 1 and carnitine O-octanoyl transferase (Crot) and increasing the presence of fatty acid-binding protein-3 mRNA. Furthermore, arsenic promotes atherosclerosis by inducing endothelial damage. This cascade of pathophysiological events promotes metabolic derangement. Although the pieces of evidence provided by this study are convincing, future studies evaluating the involvement of other likely mechanisms are important. Also, epidemiological studies might be necessary for the translation of most of the findings in animal models to humans.

Using a soft computing OSPRC risk framework to analyze multiple contaminants from multiple sources; a case study from Khoy Plain, NW Iran

Water shortage in arid and semi-arid areas like Iran makes groundwater contamination a crucial issue. In the Khoy aquifer, NW Iran, contaminants (e.g., arsenic (As), nitrate (NO₃^-), lead (Pb), and zinc (Zn)) may originate from both geological and anthropogenic sources. The objectives of the study are to (1) employ soft modeling framework to abstract available hydrogeochemical information into a perceptual model and (2) build a conceptual model using the risk cells (RCs) by applying the following two steps: (i) study Origin-Source-Pathways-Receptor-Consequence (OSPRC) as a risk system; and (ii) apply "soft modeling" as a set of diverse and classical tools including graphical representations, geological surveys, and multivariate statistical analysis to validate the information by evaluating their convergence or divergence behaviors among different tools used for investigating the groundwater contaminants. According to the perceptual model, the Khoy aquifer contains four RCs. RC4 (southern of plain) and RC2 (northern of the plain) contain high levels of As, while RC2 contains high amounts of Zn. In RC1 (northern of plain) and RC3 (middle of plain), a high concentration of Pb is detected, while in RC3 and RC4, there is a high concentration of NO₃^-. It was found that a soft modeling approach can only identify the dominant hydrogeochemical processes for each RC as a descriptive model, rather than the use of quantitative models if sufficient data are available.

Recent advancements in toxicology, modern technology for detection, and remedial measures for arsenic exposure: review

Arsenic toxicity has become a major global health concern for humans and animals due to extensive environmental and occupational exposure to arsenic-contaminated water, air, soil, and plant and animal origin food. It has a wide range of detrimental effects on animals, humans, and the environment. As a result, various experimental and clinical studies were undertaken and are undergoing to understand its source of exposures, pathogenesis, identify key biomarkers, the medical and economic impact on affected populations and ecosystems, and their timely detection and control measures. Despite these extensive studies, no conclusive information for the prevention and control of arsenic toxicity is available, owing to complex epidemiology and pathogenesis, including an imprecise approach and repetitive work. As a result, there is a need for literature that focuses on recent studies on the epidemiology, pathogenesis, detection, and ameliorative measures of arsenic toxicity to assist researchers and policymakers in the practical future planning of research and community control programs. According to the preceding viewpoint, this review article provides an extensive analysis of the recent progress on arsenic exposure to humans through the environment, livestock, and fish, arsenic toxicopathology, nano-biotechnology-based detection, and current remedial measures for the benefit of researchers, academicians, and policymakers in controlling arsenic eco-toxicology and directing future research. Arsenic epidemiology should therefore place the greatest emphasis on the prevalence of different direct and indirect sources in the afflicted areas, followed by control strategies.

Would delineation of nitrate vulnerable zones be improved by introducing a new parameter representing the risk associated with soil permeability in the Land Use-Intrinsic Vulnerability Procedure?

Most methods for mapping groundwater vulnerability are based on the excessively simplistic approach that aquifer recharge is produced by vertical infiltration. The novel Land Use-Intrinsic Vulnerability (LU-IV) procedure assesses groundwater vulnerability to nitrate pollution over the entire territory, including aquifers catchment areas. In this research, it was analysed if the delineation of nitrate vulnerable zones (NVZs) would be improved by introducing a new parameter representing the risk associated with soil permeability (parameter S) in the procedure. Different versions of parameter S were tested: S_HC (risk associated with soil hydraulic conductivity), S_St+G+S (risk associated with the stone, gravel and sand fraction of the soil) and S_C (risk associated with the clay fraction). The study was undertaken in the catchment areas of the Oja and Tirón alluvial aquifers (Spain). The efficacy of the following six models was compared: Model 1 (original LU-IV procedure), Model 2 (LU-IV' procedure using parameter S_HC), Model 3 (LU-IV' procedure using parameter S_St+G+S), Model 4 (LU-IV' procedure using parameter S_C), Model 5 (LU-DRASTIC-COP procedure, based on DRASTIC-COP method), and Model 6 (designated NVZ). Catchment scale validations of the six models showed similar, highly significant correlations between the percent coverages of the estimated NVZs and those of the alluvial areas polluted by nitrate for Models 1 to 4. Models 5 and 6 did not show any significant results. In light of these results, Models 1 to 4 were considered the best predictors of nitrate pollution and the best methods for NVZ delineation. Results support the idea that including a parameter S in the LU-IV' procedure is not essential since equivalent results were obtained from the original LU-IV procedure. So, the LU-IV procedure should be considered the best and simplest method of those tested for accurately delineating NVZs.

Judging the sources of inferior groundwater quality and health risk problems through intake of groundwater nitrate and fluoride from a rural part of Telangana, India

Evaluation of groundwater quality and related health hazards is a prerequisite for taking preventive measures. The rural region of Telangana, India, has been selected for the present study to assess the sources and origins of inferior groundwater quality and to understand the human health risk zones for adults and children due to the consumption of nitrate ([Formula: see text])- and fluoride (F^-)-contaminated groundwater for drinking purposes. Groundwater samples collected from the study region were determined for various chemical parameters. Groundwater quality was dominated by Na⁺ and [Formula: see text] ions. Piper's diagram and bivariate plots indicated the carbonate water type and silicate weathering as a main factor and man-made contamination as a secondary factor controlling groundwater chemistry; hence, the groundwater quality in the study region is low. According to the Groundwater Quality Index (GQI) classification, 48.3% and 51.7% of the total study region are excellent (GQI: < 50) and good (GQI: 50 to 100) water quality types, respectively, for drinking purposes. However, [Formula: see text] ranged from 0.04 to 585 mg/L, exceeding the drinking water quality limit of 45 mg/L in 34% of the groundwater samples due to the effects of nitrogen fertilizers. This was supported by the relationship of [Formula: see text] with TDS, Na⁺, and Cl^-. The F^- content was from 0.22 to 5.41 mg/L, which exceeds the standard drinking water quality limit of 1.5 mg/L in 25% of the groundwater samples. The relationship of F^- with pH, Ca²⁺, Na⁺, and [Formula: see text] supports the weathering and dissolution of fluoride-rich minerals for high F^- content in groundwater. They were further supported by a principal component analysis. The Health Risk Index (HRI) values ranged from 0.20 to 20.10 and 0.36 to 30.90 with a mean of 2.82 and 4.34 for adults and children, respectively. The mean intensity of HRI (> 1.0) was 1.37 times higher in children (5.70) than in adults (4.16) due to the differences in weight size and exposure time. With an acceptable limit of more than 1.0, the study divided the region into Northern Safe Health Zone (33.3% for adults and 28.1% for children) and Southern Unsafe Health Zone (66.7% for adults and 71.9% for children) based on the intensity of agricultural activity. Therefore, effective strategic measures such as safe drinking water, denitrification, defluoridation, rainwater harvesting techniques, sanitary facilities, and chemical fertilizer restrictions are recommended to improve human health and protect groundwater resources.

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.

An investigation to human health risks from multiple contaminants and multiple origins by introducing 'Total Information Management'

A capability for aggregating risks to aquifers is explored in this paper for cases with sparse data exposed to anthropogenic and geogenic contaminants driven by poor/non-existent planning/regulation practices. The capability seeks 'Total Information Management' (TIM) under sparse data by studying hydrogeochemical processes, which is in contrast to Human Health Risk Assessment (HHRA) by the USEPA for using sample data and a procedure with prescribed parameters without deriving their values from site data. The methodology for TIM pools together the following five dimensions: (i) a perceptual model to collect existing knowledge-base; (ii) a conceptual model to analyse a sample of ion-concentrations to determine groundwater type, origin, and dominant processes (e.g. statistical, graphical, multivariate analysis and geological survey); (iii) risk cells to contextualise contaminants, where the paper considers nitrate, arsenic, iron and lead occurring more than three times their permissible values; (iv) 'soft modelling' to firm up information by learning from convergences and/or divergences within the conceptual model; and (v) study the processes within each risk cell through the OSPRC framework (Origins, Sources, Pathways, Receptors and Consequence). The study area comprises a series of patchy aquifers but HHRA ignores such contextual data and provides some evidence on both carcinogenic and non-carcinogenic risks to human health. The TIM capability provides a greater insight for the processes to unacceptable risks from minor ions of anthropogenic nitrate pollutions and from trace ions of arsenic, iron and lead contaminants.

Introducing the risk aggregation problem to aquifers exposed to impacts of anthropogenic and geogenic origins on a modular basis using 'risk cells'

Proof-of-concept is presented in this paper to a methodology formulated for indexing risks to groundwater aquifers exposed to impacts of diffuse contaminations from anthropogenic and geogenic origins. The methodology is for mapping/indexing, which refers to relative values but not their absolute values. The innovations include: (i) making use of the Origins-Source-Pathways-Receptors-Consequences (OSPRC) framework; and (ii) dividing a study area into modular Risk (OSPRC) Cells to capture their idiosyncrasies with different origins. Field measurements are often sparse and comprise pollutants and water table, which are often costly; whereas supplementary data are general-purpose data, which are widely available. Risk mapping for each OSPRC cell is processed by dividing a study area into pixels and for each pixel, the risk from both anthropogenic and geogenic origins are indexed by using algorithms related to: (i) Vulnerability Indices (VI), which identify the potential for risk exposures at each pixel; and (ii) velocity gradient, which expresses the potency to risk exposures across the risk cell. The paper uses DRASTIC for anthropogenic VI but introduces a new framework for geogenic VI. The methodology has a generic architecture and is flexible to modularise risks involving any idiosyncrasies in a generic way in any site exposed to environmental pollution risks. Its application to a real study area provides evidence for the proof-of-concept for the methodology by a set of results that are fit-for-purpose and provides an insight into the study area together with the identification of its hotspots.