Survey of Heavy Metal Contamination in Water Sources in the Municipality of Torola, El Salvador, through In Situ Sorbent Extraction

Anticó, Enriqueta; Cot, Sergi; Ribó, Alexandre; Rodríguez-Roda, Ignasi; Fontàs, Cláudia

doi:10.3390/w9110877

Cited by 5 publications

(2 citation statements)

References 23 publications

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“…In this basin, 68% of the surface waters of El Salvador are found [35]. On the other hand, El Salvador has the largest population density in America (304 inhabitants per km 2 ) [36]. The Lempa River basin encompasses 13 of 14 departments of El Salvador, comprising 3,967,159 inhabitants (77.5% of the country's population).…”

Section: Case Studymentioning

confidence: 99%

Spatiotemporal Drought Risk Assessment Considering Resilience and Heterogeneous Vulnerability Factors: Lempa Transboundary River Basin in The Central American Dry Corridor

Khoshnazar

Corzo

Diaz

2021

JMSE

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Drought characterization and risk assessment are of great significance due to drought’s negative impact on human health, economy, and ecosystem. This paper investigates drought characterization and risk assessment in the Lempa River basin in Central America. We applied the Standardized Evapotranspiration Deficit Index (SEDI) for drought characterization and drought hazard index (DHI) calculation. Although SEDI’s applicability is theoretically proven, it has been rarely applied. Drought risk is generally derived from the interactions between drought hazard (DHI) and vulnerability (DVI) indices but neglects resilience’s inherent impact. Accordingly, we propose incorporating DHI, DVI, and drought resilience index (DREI) to calculate drought risk index (DRI). Since system factors are not equally vulnerable, i.e., they are heterogeneous, our methodology applies the Analytic Hierarchy Process (AHP) to find the weights of the selected factors for the DVI computation. Finally, we propose a geometric mean method for DRI calculation. Results show a rise in DHI during 2006–2010 that affected DRI. We depict the applicability of SEDI via its relationship with El Nino-La Nina and El Salvador’s cereal production. This research provides a systematic drought risk assessment approach that is useful for decision-makers to allocate resources more smartly or intervene in Drought Risk Reduction (DRR). This research is also useful for those interested in socioeconomic drought.

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Section: Case Studymentioning

confidence: 99%

Spatiotemporal Drought Risk Assessment Considering Resilience and Heterogeneous Vulnerability Factors: Lempa Transboundary River Basin in The Central American Dry Corridor

Khoshnazar

Corzo

Diaz

2021

JMSE

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“…Heavy metals in surface waters are an important issue because of their environmental toxicity, bioaccumulation and persistency in the natural environment (Hasan et al, 2019). Heavy metal contamination in waterways is mainly caused by anthropogenic activities such as discharge of industrial and domestic wastewater, accidental leaking of chemicals and direct dumping of various types of wastes (Anticó et al, 2017). Potential effects of heavy metals in an aquatic environment rely on the concentration of heavy metals, geochemical speciation and predominant microbiological activities in the receiving environment.…”

Section: Introductionmentioning

confidence: 99%

Prediction of heavy metals removal by polymer inclusion membranes using machine learning techniques

Yaqub

Eren

Eyüpoğlu

2021

Water & Environment J

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This study predicts heavy metals removal from aqueous solution by polymer inclusion membranes (PIMs) process using machine learning (ML) techniques such as multiple layer perceptron neural networks (MLPNN) and multiple linear regression (MLR) after data analysis. The removal efficiency (RE) of the PIMs process is predicted for cobalt (Co), cadmium (Cd) and chromium (Cr) by changing operating conditions including time, carrier type, carrier rate, film thickness, plasticizer type and plasticizer rate. The MLPNN model presents reliable results with lower mean square error (MSE) for an unseen testing dataset, whereas the MLR model shows higher MSE values. The coefficient of determination (R2) of the MLPNN model for the testing dataset is 0.93, 0.90 and 0.86 for Co, Cd and Cr, respectively, whereas MLR shows poor results. Therefore, the MLPNN model can be a competitive, robust and fast alternate to optimize the PIMs process with minimum experimental work.

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Exposure risk to heavy metals through surface and groundwater used for drinking and household activities in Ifite Ogwari, Southeastern Nigeria

et al. 2023

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Surface and groundwater are the most common sources of water in Nigeria's rural communities, which are used for a variety of purposes ranging from farming to industrial processes and other domestic household activities including drinking. Water that contains heavy metals in excess of the maximum permitted levels poses a risk to human health. This study aims to evaluate the levels of heavy metals in surface and groundwater in Ifite Ogwari, a rural community in Anambra State, Southeast Nigeria, as well as their ecological indices and human health risks assessment. The concentration levels of Ni, Cr, Cd, Pb, Zn, Fe, Mn, and Cu were determined in fifteen water samples from the major water sources in the study area, viz., streams, river, and hand-dug wells. The water samples were collected using precleaned 500 cm3 glass bottles and were analyzed using Atomic Absorption Spectroscopy (AAS) technique. The results showed that four metals (Cr, Cu, Mn, and Pb) out of the eight heavy metals were not detected in all the samples. The concentration levels of total Ni had a range of 0.029–0.11 mg/L with highest concentration occurring at Isiachala stream, Onowulugbe well, and Omambala river (0.11 mg/L). The Cd levels in the water samples had a range of 0.001–0.036 mg/L, with Isiachala and Iyiutu having the highest values (0.036 mg/L). The concentration of Fe ranged from 0.01 to 0.047 mg/L. Mn was detected at a concentration level of 0.003 mg/L in Iyiutu stream only. The Pearson correlation deduced a strong correlation (> 0.75) and a medium correlation (0.50–0.75) for sample locations and analytes, while three factors (principal component analysis) were produced, which indicates the influence of anthropogenic release rather than natural release. Ecological indices showed the impact of multi-elemental matrices on the ecology, while health risk assessments showed that there was no adverse cancer risk or non-cancer risk across respondents (adults and children). The obtained results showed that anthropogenic release has an extensive mobility influence on the natural level of metals in surface and ground water in Ifite Ogwari, and so proper treatment is advocated. This study has shown that the water sources from Ifite Ogwari pose no adverse health risk to the residents. Consequently, additional research on Ifite Ogwari water is needed to characterize “forever chemicals,” per- and polyfluoroalkyl substances (PFAS) which are ubiquitous, cancerous and have been linked to reproductive and immune system harm, and suggest routes for remediation.

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Survey of Heavy Metal Contamination in Water Sources in the Municipality of Torola, El Salvador, through In Situ Sorbent Extraction

Cited by 5 publications

References 23 publications

Spatiotemporal Drought Risk Assessment Considering Resilience and Heterogeneous Vulnerability Factors: Lempa Transboundary River Basin in The Central American Dry Corridor

Spatiotemporal Drought Risk Assessment Considering Resilience and Heterogeneous Vulnerability Factors: Lempa Transboundary River Basin in The Central American Dry Corridor

Prediction of heavy metals removal by polymer inclusion membranes using machine learning techniques

Exposure risk to heavy metals through surface and groundwater used for drinking and household activities in Ifite Ogwari, Southeastern Nigeria

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