Risk Of Arsenic Contamination Research Articles

Mitigation of heavy metal toxicity in pigeon pea by plant growth promoting Pseudomonas alcaliphila strain PAS1 isolated from contaminated environment.

The risk of arsenic contamination is rising globally, and it has negative impacts on the physiological processes and growth of plants. Metal removal from contaminated soils can be accomplished affordably and effectively with plant growth promoting rhizobacteria (PGPR)-based microbial management. From this angle, this research evaluated the mitigation of arsenic toxicity using the bacteria isolated from contaminated site, Mettur, Salem district, South India. The newly isolated bacterial strain was screened for plant growth promotion potential and arsenic tolerance such as (100ppm, 250ppm, 500ppm, 800ppm and 1200ppm). The metal tolerant rhizobacteria was identified using 16S rRNA gene sequence analysis as Pseudomonas alcaliphila strain PAS1 (GenBank accession number: OQ804624). Pigeon pea (Cajanus cajan) plants were used in pot culture experiments with varying concentrations of arsenic, (5ppm, 10ppm and 25ppm) both with and without bacterial culture, for a period of 45days. At the concentration of 25ppm after the application of PAS1 enhanced the plant growth, protein and carbohydrate by 35.69%, 18.31% respectively. Interestingly, P. alcaliphila strain PAS1 significantly reduced the stress-induced elevated levels of proline, flavonoid, phenol and antioxidant enzyme in pigeon pea plants was 40%, 31.11%, 27.80% and 20.12%, respectively. Consequently, PAS1 may significantly reduce the adverse effects that arsenic causes to plant development in acidic soils, improve plant uptake of nutrients, and increase plant production. The findings of this study reveal that P. alcaliphila PAS1 is intrinsic for phytoremediation by reducing arsenic accumulation in the root and shoot.

Spatial Distribution of Arsenic in the Aksu River Basin, Xinjiang, China: The Cumulative Frequency Curve and Geostatistical Analysis

The quality of drinking water is crucial for human health and the sustainable development of societies. The Aksu River Basin, a typical inland river system, has areas where groundwater arsenic levels exceed safe drinking water standards (i.e., arsenic concentrations greater than 10 μg/L). Identifying the causes of high arsenic levels in the basin’s groundwater requires further study. Analyzing the hydrogeochemical composition of the Aksu River basin helps us to understand the spatial distribution of groundwater environments and locate areas with dangerously high arsenic levels. In this research, we collected 196 groundwater samples from along the river. Out of these, 38 samples had arsenic levels above 10 μg/L, which represents 19.4% of the total samples collected. By examining the slope changes in the cumulative frequency curves of major ion ratios and employing geostatistics (specifically, the Kriging interpolation), and taking into account the environmental characteristics of the entire basin, we divided the study area into five sub-regions (Zone I through Zone V). The geostatistical analysis showed a significant spatial variability in groundwater arsenic levels, with a clear spatial correlation. Our findings demonstrate that arsenic concentrations in the Aksu River basin’s groundwater vary widely, with Zones II and III—mainly located in the northeastern part of the basin and in Awat County—being hotspots for high-arsenic water. Factors such as a weak reducing environment, intense evaporation, strong cation exchange, and the low-permeability recharge of surface water contribute to the accumulation of arsenic in the basin’s groundwater. The results of this study are vital for assessing the risk of arsenic contamination in groundwater in similar basins and for identifying critical areas for further investigation and research.

Predicting geogenic groundwater arsenic contamination risk in floodplains using interpretable machine-learning model

Long-term exposure to geogenic arsenic (As)-contaminated groundwater poses a severe threat to public health problems. Generally, elevated As concentrations have been observed with high amounts of ammonium in groundwater of floodplains. An extreme gradient boosting algorithm was conducted to develop a probability model based on hydrogeochemical data, which predicted the occurrence rates of groundwater As on a regional scale. Results showed that concentrations of NH4+, Eh, K, Cl−, SO42−, and NO3− were powerful predictive variables of As exposure. The model revealed the co-enrichment of As with NH4+, suggesting that the mineralization of nitrogen-containing organic matter promoted the reduction of As-bearing iron-oxides. The predicted distribution of high-As groundwater showed high consistency with known spatial distribution of As contamination, and the model also accurately predicted As concentrations in Jiangbei Plain of China and typical As-affected floodplains of Southeast Asia. The model can serve as a low-cost and rapid virtual sensor for detecting As concentrations in private or newly drilled wells, thereby providing critical information for informed management decisions, environmental protection and public health safety.

The Western Great Basin Has an Arsenic Problem—Blame Its Geology

A new study links geological factors such as faulting and geothermal activity to an elevated risk of arsenic contamination in private wells across the Great Basin.

Exposure risk of groundwater arsenic contamination from Huaihe River Plain, China

Arsenic poses a danger to public health and drinking arsenic-rich groundwater is the main route for human exposure to this element. The focus of this study is to assess the risk magnitude and likelihood for arsenic-rich groundwater in Huaihe River Plain, China using Risk Magnitude and Indicator Kriging methods. It has been found that 481 in 5515 investigated samples exceed the drinking water standards of the World Health Organization, which present a high exposure risk for public health. Arsenic concentrations range from 0.001 to 356.00 μg/L, with a median of 2.10 μg/L. The proportion of contaminated shallow groundwater samples is 9.77%, and the counterpart from deep layer is 2.85%, respectively. Arsenic concentrations are obviously higher in plain areas than those in hilly areas. High Risk Magnitude and Very High Risk Magnitude samples are sporadically positioned in inland and coastal plain. According to the prediction of Risk Probability maps over shallow and deep groundwater, high arsenic Risk Probability areas is scattered in the inland and coastal portion, and both Risk Probability peaks are similar. Some high arsenic hazard areas have been found to possess high cancer rates, and high Risk Probability peaks are correlated with cancer cluster. The potential high arsenic hazard areas over shallow groundwater encompass more than 4709 km2, while the counterpart over deep groundwater is 1446 km2. 2.88 million people are estimated to be potentially exposed to High Risk Probability of arsenic. This paper carried out research on exposure risk of arsenic contamination from Huaihe River Plain, China, which may provide guidance for regionalization of drinking groundwater safety.

ПРИРОДНЫЕ И ТЕХНОГЕННЫЕ ОСОБЕННОСТИ ЗАГРЯЗНЕНИЯ ПРИРОДНЫХ ВОД МЫШЬЯКОМ (NATURAL AND TECHNOGENIC FEATURES OF POLLUTION NATURAL WATER ARSENIC)

The problem of arsenic in drinking water, which causes a violation of human health, is revealed. The main ways of arsenic ingress from the lithosphere into drinking water are shown. In the earth's crust, arsenic is contained in rocky rocks, from where it under the influence of weathering processes passes into sedimentary rocks, alluvium and silts. When underground water passes through a section of the earth's crust containing arsenic in the form of its minerals, the water is saturated with arsenic. Chemical reactions of arsenic transition to easily soluble forms and its main compounds in natural waters are presented. The mechanism of arsenic migration in natural surface and underground waters is explained. In Bangladesh, about 60 million people use arsenic-contaminated groundwater as drinking water and are therefore at risk of poisoning. Detailed map of the world on the risk of arsenic contamination of natural fresh water. It is shown that in Kazakhstan there are numerous geogenic deposits and ore occurrences of arsenic, which naturally infect groundwater. The West Kalba ore belt, which is about 800 km long and 80-100 km wide, has been identified only within Eastern Kazakhstan, and its ore objects are represented by gold-arsenopyrite (with an arsenic content of up to 2-5 %) ores. In addition, Kazakhstan has a significant technogenic component of arsenic water pollution due to the influence of the mining industry: only in the dumps of the Ust-Kamenogorsk metallurgical plant, more than 300 thousand tons of arsenic mineral products have already accumulated, with an annual increase of 11 thousand tons. The method of disposal of such waste, as well as localization of arsenic from underground polluted waters on technogenic geochemical barriers, is described.

How do data-mining models consider arsenic contamination in sediments and variables importance?

Arsenic (As) is one of the most important dangerous elements as more than 100 million of people are exposed to risk, globally. The permissible threshold of As for drinking water is 10μg/L according to both the WHO's drinking water guidelines and the Iranian national standard. However, several studies have indicated that As concentrations exceed this threshold value in several regions of Iran. This research evaluates an As-susceptible region, the Tajan River watershed, using the following data-mining models: multivariate adaptive regression splines (MARS), functional data analysis (FDA), support vector machine (SVM), generalized linear model (GLM), multivariate discriminant analysis (MDA), and gradient boosting machine (GBM). This study considers 12 factors for elevated As concentrations: land use, drainage density, profile curvature, plan curvature, slope length, slope degree, topographic wetness index, erosion, village density, distance from villages, precipitation, and lithology. The susceptibility mapping was conducted using training (70%) and validation (30%). The results of As contamination in sediment showed that classifications into 4 levels of concentration are very similar for two models of GLM and FDA. The GBM calculated the areas of highest arsenic contamination risk by MARS and SVM with percentages of 30.0% and 28.7%, respectively. FDA, GLM, MARS, and MDA models calculated the areas of lowest risk to be 3.3%, 23.0%, 72.0%, 25.2%, and 26.1%, respectively. The results of ROC curve reveal that the MARS, SVM, and MDA had the highest accuracies with area under the curve ROC values of 84.6%, 78.9%, and 79.5%, respectively. Land use, lithology, erosion, and elevation were the most important predictors of contamination potential with a value of 0.6, 0.59, 0.57, and 0.56, respectively. These are the most important factors. Finally, these data-mining methods can be used as appropriate, inexpensive, and feasible options to identify As-susceptible areas and can guide managers to reduce contamination in sediment of the environment and the food chain.

Targeting at risk households in Bangladesh exposed to arsenic contamination: a spatial analysis

ABSTRACTThis study seeks to identify the spatial risk pattern of households (HHs) exposed to arsenic contamination in Bangladesh by adjusting potential socio-economic, demographic factors. Data from Bangladesh Multiple Indicator Cluster Survey 2012–13 are used where hierarchical Bayesian spatial ordered logit model is implemented. The analysis shows that 25% of HH water samples were arsenic contaminated, although the majority (95%) of HHs used improved water sources. Arsenic contamination risk in the HH water was significantly associated with water source type and location, place of residence and districts. The model-based spatial prediction reveals that the north-east and south-west parts of Bangladesh have a high risk of contamination. To ensure the quality of HH water, our findings suggest that chemical test should be promoted considering the spatial risk of arsenic contaminations variations among HHs of Bangladesh. Furthermore, the study findings can effectively contribute in the planning of future interventions and programs.

Arsenic Contamination Risk Assessment in Hamedan Plain-Spring Using the Fuzzy Method

Arsenic Contamination Risk Assessment in Hamedan Plain-Spring Using the Fuzzy Method

Metal contamination in traditionally used Medicinal plants: a serious threat in Murshidabad district, West Bengal, India

Murshidabad district is one of the most highly Arsenic (As) prone areas of West Bengal, India. The predominantly rural population of this district greatly depends on traditionally used medicinal plants for treatment of various ailments and subjected to risk of arsenic contamination. The present study revealed that some naturally grown medicinal plants in this district were found to have the alarming level of concentration of arsenic and other metals (Fe, Cu) contamination. So, there should be raised more consciousness on the toxic metal contamination of medicinal plants specifically, collected from contaminated sites.

Performance Assessments of a Novel Well Design for Reducing Exposure to Bedrock-Derived Arsenic.

Arsenic in groundwater is a serious problem in New England, particularly for domestic well owners drawing water from bedrock aquifers. The overlying glacial aquifer generally has waters with low arsenic concentrations but is less used because of frequent loss of well water during dry periods and the vulnerability to surface-sourced bacterial contamination. An alternative, novel design for shallow wells in glacial aquifers is intended to draw water primarily from unconsolidated glacial deposits, while being resistant to drought conditions and surface contamination. Its use could greatly reduce exposure to arsenic through drinking water for domestic use. Hypothetical numerical models were used to investigate the potential hydraulic performance of the new well design in reducing arsenic exposure. The aquifer system was divided into two parts, an upper section representing the glacial sediments and a lower section representing the bedrock. The location of the well, recharge conditions, and hydraulic properties were systematically varied in a series of simulations and the potential for arsenic contamination was quantified by analyzing groundwater flow paths to the well. The greatest risk of arsenic contamination occurred when the hydraulic conductivity of the bedrock aquifer was high, or where there was upward flow from the bedrock aquifer because of the position of the well in the flow system.

Does arsenic play an important role in the soil microbial community around a typical arsenic mining area?

Arsenic (As) can cause serious hazards to human health, especially in mining areas. Soil bacterial communities, which are critical parts of the soil ecosystem, were analyzed directly for soil environmental factors. As a consequence, it is of great significance to understand the ecological risk of arsenic contamination on bacteria, especially at the local scale. In this study, 33 pairs of soil and grain samples were collected from the corn and paddy fields around an arsenic mining area in Shimen County in Hunan Province, China. Significant differences were found between the soil nitrogen, As concentrations, and bacteria activities among these two types of land use. According to the structural equation model (SEM) analysis, compared with other environmental factors, soil As was not the key factor affecting the bacterial community, even when grain As was beyond the threshold of the national food hygiene standards of China. In the corn field, soil pH was the main factor dominating the bacterial richness, composition and grain As. Meanwhile, in the paddy field the soil total nitrogen (TN) and total carbon (TC) were the main factors impacting the bacterial richness, and the bacterial community composition was mainly affected by pH. The interactions between grain As and soil As were weak in the corn field. The bacterial communities played important roles in the food chain risk of As. The local policy of transforming paddy soil to dry land could greatly reduce the health risk of As through the food chain.

Review of arsenic speciation, toxicity and metabolism in microalgae

Arsenic is a toxic metalloid and its pollution has become a global environmental problem. This paper reviewed the current knowledge on the speciation, toxicity and metabolism of arsenic in microalgae. A number of arsenic species are present in various microalgae. Due to the great toxicity of inorganic arsenic, microalgae may undergo different processes to reduce the arsenic toxicity, including cell surface binding, arsenite [As(III)] oxidation, arsenate [As(V)] reduction, methylation, transformation into arsenosugars or arsenolipids, chelation of As(III) with glutathione and phytochelatins, as well as excretion from cells. Several genes and enzymes involved in arsenic transformations have been identified and characterized. Many factors, especially nutrient elements (e.g., nitrogen and phosphorus) in cells and in culture, affect arsenic metabolic pathways of microalgae. Arsenic metabolism in the unicellular algae has gained considerable interest because these processes control not only the effectiveness of arsenic phycoremediation, but also the risk of arsenic contamination in algal products. Future research need to focus on (1) the regulative mechanisms of arsenic absorption, biotransformation and excretion at molecular level; (2) the effects of intracellular nutrient dynamics on arsenic speciation; (3) the impacts of culture regime on the arsenic metabolism in microalgae; (4) the transfer of arsenic species across aquatic food web in order to better evaluate the roles of microalgae in arsenic cycling.

Aromatic plants versus arsenic hazards in soils

The present article briefly describes a strategy to address an opportunity in remediation and management of arsenic-contaminated soils through the cultivation of aromatic plants. Furthermore, our concept-based proposal offers sustainable phytoremediation for the utilization of arsenic-contaminated soils by the cultivation of aromatic plants along with economic return. However, the experimental studies are required to assess the risk of arsenic contamination to the end product—the essential oil.

High arsenic contamination in drinking water hand-pumps in Khap Tola, West Champaran, Bihar, India

This study tests the drinking water supply of a marginalized village community of Khap Tola in the state of Bihar, a state in Northern India. Based on hand pump drinking water sample testing and analysis, we found that there was high levels of arsenic (maximum value being 397 ppb) , in excess of the WHO limits of 10ppb. Analysis showed 57% of the samples from private hand-pumps in the shallow aquifer zone of 15-35m have arsenic greater than 200 ppb. Using GIS overlay analysis technique it was calculated that 25% of the residential area in the village is under high risk of arsenic contamination. Further using USEPA guidelines, it was calculated that children age group 5-10 years are under high risk of getting cancer. The Hazard Quotient calculated for 21 children taken for study, indicated that children may have adverse non-carcinogenic health impacts, in the future, with continued exposure. Since the area adds a new arsenic contaminated place in India, further geochemical analysis and health assessment needs to be done in this district of West Champaran in, Bihar.

Effect of arsanilic acid on anaerobic methanogenic process: Kinetics, inhibition and biotransformation analysis

Arsanilic acid (4-aminophenylarsonic acid) is widely used in the poultry and animal industries as a feed additive in the diets. Nearly all the added arsanilic acid is excreted unchanged in manure resulting in the risk of arsenic contamination. In this study, the effects of arsanilic acid on the kinetics, inhibition of methanogenic process and its biotransformation were investigated. The methane yield was not affected by arsanilic acid loading at concentration <0.46mM, while the methane production was completely inhibited at concentration of 0.92mM. The IC50 of arsanilic acid in this study was 0.47mM. After 115 days of incubation, 37–59% of the added arsanilic acid was degraded. The species analysis indicated that at lower initial arsanilic acid concentration, the soluble inorganic arsenic mainly existed in the species of arsenate (As(V)), while at higher initial arsanilic acid concentration (>0.460mM), the soluble inorganic arsenic mainly existed in the species of arsenite (As(III)), which explains why higher arsanilic acid concentration has severe inhibition to methanogens.

Electrochemical stimulation of microbial roxarsone degradation under anaerobic conditions.

Roxarsone (4-hydroxy-3-nitrophenylarsonic acid) has been commonly used in animal feed as an organoarsenic additive, most of which is excreted in manure. Roxarsone is easily biodegraded to 4-hydroxy-3-aminophenylarsonic acid (HAPA) under anaerobic conditions, but HAPA persists for long periods in the environment, increasing the risk of arsenic contamination through diffusion. We investigated the electrochemical stimulation of the microbial degradation of roxarsone under anaerobic conditions. After the carbon sources in the substrate were depleted, HAPA was slowly degraded to form arsenite under anaerobic conditions. The degradation rate of HAPA was significantly increased when 0.5 V was applied without adding a carbon source. The two-cell membrane reactor assays reveal that the HAPA was degraded in the anode chambers, confirming that the anode enhanced the electron transfer process by acting as an electron acceptor. The degradation product formed with electrochemical stimulation was arsenate, which facilitates the removal of arsenic from wastewater. Based on the high performance liquid chromatography-ultraviolet-hydride generation-atomic fluorescence spectrometry (HPLC-UV-HG-AFS) and gas chromatography-mass spectrometry (GC-MS) data, the pathway for the biodegradation of roxarsone and the mechanisms for the electrochemically stimulated degradation are proposed. This method provides a potential solution for the removal of arsenic from organoarsenic-contaminated wastewater.

Enhancing arsenic mitigation in Bangladesh: Findings from institutional, psychological, and technical investigations

As part of a trans-disciplinary research project, a series of surveys and interventions were conducted in different arsenic-affected regions of rural Bangladesh. Surveys of institutional stakeholders identified deep tubewells and piped water systems as the most preferred options, and the same preferences were found in household surveys of populations at risk. Psychological surveys revealed that these two technologies were well-supported by potential users, with self-efficacy and social norms being the principal factors driving behavior change. The principal drawbacks of deep tubewells are that installation costs are too high for most families to own private wells, and that for various socio-cultural-religious reasons, people are not willing to walk long distances to access communal tubewells. In addition, water sector planners have reservations about greater exploitation of the deep aquifer, out of concern for current or future geogenic contamination. Groundwater models and field studies have shown that in the great majority of the affected areas, the risk of arsenic contamination of deep groundwater is small; salinity, iron, and manganese are more likely to pose problems. These constituents can in some cases be avoided by exploiting an intermediate depth aquifer of good chemical quality, which is hydraulically and geochemically separate from the arsenic-contaminated shallow aquifer. Deep tubewells represent a technically sound option throughout much of the arsenic-affected regions, and future mitigation programs should build on and accelerate construction of deep tubewells. Utilization of deep tubewells, however, could be improved by increasing the tubewell density (which requires stronger financial support) to reduce travel times, by considering water quality in a holistic way, and by accompanying tubewell installation with motivational interventions based on psychological factors. By combining findings from technical and social sciences, the efficiency and success of arsenic mitigation in general – and installation of deep tubewells in particular – can be significantly enhanced.

Groundwater arsenic contamination risk prediction using GIS and classification tree method

Groundwater arsenic contamination is a serious health and environmental problem in Bangladesh. Sources or origin of this heavy metal is known to be natural but the process through which it is being released is poorly understood. In quest of mitigation of the problem it is important to predict area of probable contamination before it causes any damage to human health. In this research an attempt has been made to develop arsenic contamination risk map using a combination of classification tree and GIS technology. Six factors, which might have relation with arsenic contamination, namely geology, soil reaction (pH), elevation, soil organic matter, soil iron and proximity to river were selected as predictor variables. Prediction model was developed using classification algorithm of data mining technology in MATLAB using 80% training data. The developed classification trees were then validated using 20% test dataset. The best tree is found at pruning level 6 with cross validation accuracy result of 78.25%. The classification tree prediction model shows a complex relation of arsenic and the predictors. However, the root classifiers of the classification tree were found to be the surface elevation factor followed by geology. The best tree obtained from cross validation process was used to create the arsenic risk map in GIS environment. The developed risk map is found to be very close to reality where 87.9% of the data were found to be correctly predicted. The research shows that supported by geochemical process the surface elevation of an area determines the degree of accumulation of arsenic in the groundwater.

The Risk of Arsenic Contamination in Czech Urban Soils

The Risk of Arsenic Contamination in Czech Urban Soils