Evaluating the spatial distribution of quantitative risk and hazard level of arsenic exposure in groundwater, case study of Qorveh County, Kurdistan Iran

Human health risk assessment due to consumption of dried fish in Chennai, Tamil Nadu, India: a baseline report

The current study sought to determine the levels of radioactivity and heavy metal contamination in 22 dried fish samples collected in Chennai, Tamil Nadu. The study found that there were substantial heavy metals concentrations for Pb, Mn, Cr, Co, and Cd. The concentration of heavy metal Pb being alarmingly high (32.85 to 42.09 mg/kg), followed by Cd (2.18 mg/kg to 3.51 mg/kg) than the permissible limit of WHO (2.17 mg/kg) for Pb and (0.05 mg/kg) for Cd. In terms of radioactivity, the gross alpha activity in the dried fish samples ranged 6.25 ± 0.12 to 48.21 ± 0.11 Bg/kg with an average of 20.35 Bg/kg and with a gross beta activity from 6.48 ± 0.02 to 479.47 ± 0.65 Bg/kg, for an average of 136.83 Bg/kg. The study found that the internal radiation dose that people receive upon consuming the fish species Sphyraena obtusata, Rachycentron canadum, Lepidocephalichthys thermalis, Synodontidae, Carangoides malabaricus, Sardina pilchardus, Scomberomorus commerson, Sillago sihama, Gerres subfasciatus, and Amblypharyngodon mola is above the ICRP-recommended limit of less than 1 mSv/year. Annual gonadal dose equivalent (AGDE) and total excessive lifetime cancer risk (ELCR) ranged 0.488 µSv year-1 and 0.004 µSv year-1 respectively, the values of AGDE being higher than the global average value. The findings of the study indicate that the analyzed dried fish samples are contaminated with Pb and Cd, which shall pose cancer risk to the consumers as a result.

Systematic review and meta-analysis of arsenic concentration in drinking water sources of Iran

Recent studies have found arsenic contamination of drinking water in some parts of Iran, as in many other countries. Thus, a comprehensive systematic review is necessary to assess the distribution and concentration of arsenic in drinking water sources. For this purpose, articles published from the first identification until December 2023, were retrieved from various national and international databases. Of all the studies examined (11,726), 137 articles were selected for review based on their conceptual relationship to this survey. A review of the extracted studies presented that ICP methods (ICP-MS, ICP-OES, 56%) and atomic absorption spectrophotometry (AAS, 34.1%) were the two most commonly used techniques for the analysis of arsenic in water samples. The order of arsenic content in the defined study areas is descending, as follows: northwest ˃ southeast ˃ southwest ˃ northeast. A review of studies performed in Iran depicted that provinces such as Kurdistan, Azerbaijan, and Kerman have the highest arsenic concentrations in water resources. Accordingly, the maximum concentration of arsenic was reported in Rayen, Kerman, and ranged from < 0.5-25,000 µg/L. The primary cause of elevated arsenic levels in water resources appears to be geologic structure, including volcanic activity, biogeochemical processes, sulfur-bearing volcanic rocks, Jurassic shale, the spatial coincidence of arsenic anomalies in tube wells and springs, and, to some extent, mining activities. The findings of the presented survey indicate that it is essential to take serious measures at the national level to minimize the health risks of arsenic contamination from drinking water consumption.

Groundwater Health Risk Assessment Based on Monte Carlo Model Sensitivity Analysis of Cr and As–A Case Study of Yinchuan City

Groundwater is an important resource for domestic use and irrigation in the Yinchuan region of northwest China. However, the quality of groundwater in this region is declining due to human activities, with adverse effects on human health. In order to study the effects of chemical elements in groundwater on human health, the human health risk of drinking groundwater was calculated based on the actual situation in China and on the U.S. Environmental Protection Agency (USEPA) model. Moreover, the sensitivity of contaminant exposure in drinking water wells was quantified using Monte Carlo simulation to minimize uncertainty in conjunction with USEPA risk assessment techniques, with the aim to identify the major carcinogenic factors. In addition, Visual Minteq was used to analyze the possible ionic forms of the major factors in the hydrogeological environment of the study area. The results showed that the mean CR values for As were 2.94 × 10−0.5 and 5.93 × 10−0.5for the dry and rainy seasons, respectively, while for 2018 they were 5.48 × 10−0.5 and 3.59 × 10−0.5, respectively. In parallel, the CR values for children for 2017 were 6.28 × 10−0.5 and 1.27 × 10−0.4, respectively, and 1.17 × 10−0.4 and 7.67 × 10−0.5, respectively, indicating a considerably higher carcinogenic risk for children than for adults. results of the sensitivity analysis of Cr6+ and As using Crystal Ball software showed association values of 0.9958 and 1 for As and 0.0948 and 0 for Cr in the dry and rainy seasons in 2017, and 0.7424 and 0.5759 for As and 0.6237 and 0.8128 for Cr in the dry and rainy seasons in 2018, respectively. Only in the rainy season of 2018, the association values for As were lower than those for Cr, indicating that As is more sensitive to total carcinogenic risk. The results of the visual coinage model analysis showed that among all the possible ionic forms of As, the activity of HAsO42− had the largest logarithmic value and that of H3AsO4 had the smallest value, regardless of pH changes. This indicates that HAsO42− is the ionic form of As with the main carcinogenic factor in the hydrogeological environment of the study area. Therefore, corresponding environmental control measures need to be taken in time to strengthen the monitoring and control of As, especially HAsO42−, in the groundwater of the study area. This study is of great significance for Yinchuan city to formulate groundwater pollution risk management and recovery.

Arsenic in the rock-soil-plant system and related health risk in a magmatic-metamorphic belt, West of Iran

Following earlier reports of water contamination and arsenic (As) toxicity symptoms in residents of Kurdistan Province, As was determined in rock, soil and plant samples to investigate its fate from rock to crops and its potential effects on human health. Total As content ranged from 4.9 to 10,000 mg/kg, 7.7-430 mg/kg and < 0.05-25,079 µg/kg (dry weight) in rock, soil and plant samples, respectively. The Qorveh-Bijar region data indicated that magmatic differentiation has enriched late magmatic fluids in As. High rare earth elements concentration, dissociation coefficient, and positive Eu anomaly in volcanic rocks, indicated the prevalence of intermediate to felsic composition. The highest As concentration was measured in travertine. In soil, As average level in Qorveh and Bijar was 48.5 and 107 mg/kg, respectively. Higher pollution index and geoaccumulation index (I_geo) were also calculated for Bijar County. The As concentration in crop samples was greater than the recommended maximum permissible concentration for foodstuff. Mann-Whitney U test revealed significant differences between As concentration in different plant species and no difference between plants in Bijar and Qorveh. Also, alfalfa displayed the highest biological accumulation coefficient among the investigated plants. The calculated chronic daily intake of As in Bijar County was higher than the recommended levels for wheat and barley grains. Moreover, the hazard quotient (HQ) and incremental lifetime cancer risk assessments revealed high non-cancer (HQ > 1 for both adults and children) and cancer (particularly for barley in Bijar) risks for inhabitants via consumption of As contaminated crops cultivated in the study area.

Large-scale association analysis of climate drought and decline in groundwater quantity using Gaussian process classification (case study: 609 study area of Iran)

BACKGROUND

The level of groundwater resources is changing rapidly and this requires the discovery of newer groundwater resources. Drought is one of the most significant natural phenomena affecting different aspects of human life and environment. During the last decades, the application of artificial intelligent techniques has been recognized as effective approaches to forecast an annual precipitation rate.

METHOD

In this study, the association analysis of climate drought and a decline in groundwater level is addressed using Gaussian process classification (GPC) and backpropagation (BP) artificial neural network (ANN). This methodology is proposed to create a framework for decision making and reduce uncertainty in water resource management calculations, and in particular to optimize the management of groundwater drinking water sources.

RESULTS

Underground water levels in 609 study plains in Iran were used to predict drought over the test period, extending from 2017 to 2021. The artificial intelligence methods were implemented in the Python programming environment to achieve an annual precipitation rate. A statistical summary of the Rasterized Cells of the zoning maps was used to validate the prediction results. Considering the relationship between water quality reductions and drought in Iranian aquifers due to the occurrence of groundwater drought periods, the results were validated by analysis of the effect of climate drought using the Standardized Precipitation Index (SPI) on the occurrence of observed droughts with the Groundwater Resources Index (GRI). The results are well-illustrated by the observation of the predicted digits in the third dimension of the Gaussian distribution.

CONCLUSION

According to the SPI indicator, the southern regions of the country, and especially the central parts of the plain, can be considered the most affected areas by the most severe future droughts. The prediction results indicate a decrease in drought severity as part of a two-year sequence involving a recurrence of drought exacerbation and relative decline, as well as a failed state after the critical condition of aquifers.

Origin and assessment of groundwater pollution and associated health risk: a case study in an industrial park, northwest China

Groundwater quality which relates closely to human health has become as important as its quantity due to the demand for safe water. In the present study, an entropy-weighted fuzzy water quality index (WQI) has been proposed for performing groundwater quality assessment in and around an industrial park, northwest China, where domestic water requirements are solely met by groundwater. The human health risk was assessed with the model recommended by the United States Environmental Protection Agency. In addition, the sources of major ions and main contaminants were also analyzed. The study shows that groundwater in the study area has been contaminated conjunctively by natural processes and industrial and agricultural activities. Nitrate, manganese (Mn), fluoride, total dissolved solids, total hardness and sulfate are major contaminants influencing groundwater quality. Nitrate and heavy metals such as Mn are mainly affected by human agricultural activities and industrial production, while other contaminants are mainly originated from mineral weathering and water-rock interactions. The results of water quality assessment suggest that half of the groundwater samples collected are of medium quality thus require pretreatment before human consumption. The mean health risk caused by the consumption of contaminated groundwater in the area is 8.42 × 10(-5) per year which surpasses the maximum acceptable level (5 × 10(-5) per year) recommended by the International Commission on Radiologic Protection. The entropy-weighted fuzzy WQI proposed in this study can not only assign proper weights to parameters but also treat uncertainties associated with water quality classification. This study will be of interest to international environmentalists and hydrogeologists. It will also be useful in regional groundwater management and protection.

Histological and histometrical study of the protective role of α-tocopherol against sodium arsenite toxicity in rat ovaries

This study examines histometrical changes induced by sodium arsenite (SA), as an environmental pollutant, and investigates the protective effect of α-tocopherol on ovaries of SA-treated rats during the prenatal stage until sexual maturity. Rats were classified into groups: control, SA (8 ppm/day), α-tocopherol (100 ppm/day), and SA+α-tocopherol. Treatment was performed from pregnancy until maturation when the rats and ovaries were weighed. The Cavalieri method was used to estimate volume of the ovaries, cortex, medulla, and corpus luteum. The mean diameter of oocytes, granulosa cells, and nuclei were measured and volume was estimated using the Nucleator method. The number of oocytes and thickness of the zona pellucida (ZP) were determined using an optical dissector and orthogonal intercept method, respectively. SA reduced the body and ovary weight, the number of secondary, antral and Graafian oocytes, volume of the ovaries, cortex, medulla and corpus luteum, mean diameter and volume of oocytes in primordial and primary follicles, mean diameter and volume of oocyte nuclei in all types of follicles, and mean thickness of the ZP in secondary and antral follicles. Also, the mean diameter and volume of granulosa cells and their nuclei in antral and Graafian follicles decreased significantly. Vacuolization and vascular congestion in the corpus luteum and an increase in the number of atretic oocytes were seen in the SA group. Most of these parameters were unchanged from the control level in the SA+α-tocopherol group. It was concluded that α-tocopherol supplementation reduced the toxic effects of SA exposure on ovarian tissue in rats.