Spatiotemporal variations, sources, water quality and health risk assessment of trace elements in the Fen River

Chai, Ningpan; Yi, Xiu; Xiao, Jun; Liu, Ting; Liu, Yujie; Deng, Li; Jin, Zhangdong

doi:10.1016/j.scitotenv.2020.143882

Cited by 78 publications

(28 citation statements)

References 55 publications

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“…In the health risk assessment model, the direct hand-mouth ingestion intake and dermal contact intake are usually considered as the two main exposure pathways for HMs in aquatic environment (Xiao et al, 2019). The exposure average daily dose for direct ingestion (ADD ing ) and dermal absorption (ADD der ) can be evaluated using the following equations (Chai et al, 2021):…”

Section: Health Risk Assessmentmentioning

confidence: 99%

Spatial and temporal variation of dissolved heavy metals in the Lijiang River, China: implication of rainstorm on drinking water quality

Deng

Shahab

et al. 2021

Environ Sci Pollut Res

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Lijiang River is an essential drinking water source and natural scenery in the Guilin City. For the rst time, implications of rainstorm were taken into consideration by investigating spatial and temporal variation of dissolved heavy metals (HMs) in the Lijiang River water. A total of 68 water samples were collected during low ow (normal) season and high ow (rainstorm) season from 34 sampling sites. Dissolved HMs including Cr, Mn, Co, Cu, Zn, As, Cd, Sb, and Pb were found to meet the respective drinking water standards, while higher concentration was observed after the rainstorm season, except for Cr. Multivariate statistical analysis showed Co, Cu, Cr, Zn, Sb, and Pb in normal season are mainly controlled by anthropogenic sources. Furthermore, higher concentration of Mn, Cu, Cd, Pb, Co and Zn during the high ow season is attributed to rainstorm. The water quality index (WQI) showed good grades, and comparatively lower in rainstorm season. The results of health risk assessment revealed that HMs in Lijiang River pose limited health risk, however, As poses potential health risk during rainstorm season. It is suggested to adopt preventive measures in mining activities and industrial waste-water discharge at the river's upstream and downstream.

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Section: Health Risk Assessmentmentioning

confidence: 99%

Spatial and temporal variation of dissolved heavy metals in the Lijiang River, China: implication of rainstorm on drinking water quality

Deng

Shahab

et al. 2021

Environ Sci Pollut Res

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“…The result in Table S4 shows that non-reporting of vital steps in data analysis and inappropriate statistics are common in many regions. For example, some articles used boxplot to present their descriptive statistics as a result of obvious skewness of their data, but at the same time tabulated mean and standard deviation ( Chai et al., 2021 ; Koliyabandara et al., 2020 ; Liu et al., 2021 ). The preferred reporting of non-normally distributed data was observed in an article where boxplot, and median and range (in a summary table) were used ( Wątor and Zdechlik, 2021 ).…”

Section: Review Results and Discussionmentioning

confidence: 99%

An appraisal of data collection, analysis, and reporting adopted for water quality assessment: A case of Nigeria water quality research

Ewuzie

Aku

Nwankpa

2021

Heliyon

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The appropriate acquisition and processing of water quality data are crucial for water resource management. As such, published articles on water quality monitoring and assessment are meant to convey essential and reliable information to water quality experts, decision-makers, researchers, students, and the public. The implication is that such information must emanate from data obtained and analysed in an up-to-date, scientifically sound manner. Thus, inappropriate data analysis and reporting techniques could yield misleading results and mar the endeavours of achieving error-free conclusions. This study utilises the findings on water quality assessment in Nigeria over the last 20 years to reveal the likely trends in water quality research regarding data collection, data analysis, and reporting for physicochemical, bacteriological parameters, and trace organics. A total of 123 Web of Science and quartile ranked (Q1-Q4) published articles involving water quality assessment in Nigeria were analysed. Results indicated shortcomings in various aspects of data analysis and reporting. Consequently, we use simulated heatmaps and graphs to illustrate preferred ways of analysing, reporting, and visualising some regularly used descriptive and inferential statistics of water quality variables. Finally, we highlight alternative approaches to the customarily applied water quality assessment methods in Nigeria and emphasise other areas of deficiency that need attention for improved water quality research.

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“…the structure of which is shown in Figure 2. shows that the health risks caused by water ingestion are far more significant than those caused by skin contact (Adimalla, 2020b;Chai et al, 2021;Gao et al, 2020). Therefore, this study only considers the threats to health produced by ingesting water.…”

Section: Uncertainty Analysis and Human Health Risk Assessment Proceduresmentioning

confidence: 99%

Uncertainty Health Risk Assessment and Regional Control of Drinking Water: A Case Study of Hanyuan County, Southwest Mountainous Area, China

Lin

Liu

Cheng

et al. 2022

Preprint

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To evaluate the health risks of drinking water in Hanyuan County, 96 samples of peripheral drinking water were collected from 30 sites in the area. The samples were then analysed for physicochemical properties including Fe, Mn, NH 3 -N, , F-, Pb, Hg, As, Cr 6+ , Cd, and so on. The health risks of ten trace elements in drinking water were probabilistically assessed using the health risk assessment model and Monte Carlo simulation. On this basis, sequential indicator simulations were used to classify the health risk levels of drinking water in the region, to conduct hierarchical management and control. The results showed that except for , all other indicators met World Health Organisation standards and China’s drinking water sanitation standards. Drinking water presents a specific carcinogenic risk to adults, and the cumulative contribution of As and Cr 6+ exceeds 95%, and has a specific non-carcinogenic risk to children if the cumulative contribution of F - , , and As exceeds 90%. Grade I, II, and III non-carcinogenic risk areas accounted for 0.89%, 24.72%, and 74.39% of the total area of Hanyuan County, respectively, while grade I, II, and III carcinogenic risk areas accounted for 27.71%, 45.56%, and 26.73% of the total Hanyuan County area, respectively. Finally, according to the health risk characteristics of each control area, corresponding zoning control suggestions were proposed.

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Spatiotemporal variations, sources, water quality and health risk assessment of trace elements in the Fen River

Cited by 78 publications

References 55 publications

Spatial and temporal variation of dissolved heavy metals in the Lijiang River, China: implication of rainstorm on drinking water quality

Spatial and temporal variation of dissolved heavy metals in the Lijiang River, China: implication of rainstorm on drinking water quality

An appraisal of data collection, analysis, and reporting adopted for water quality assessment: A case of Nigeria water quality research

Uncertainty Health Risk Assessment and Regional Control of Drinking Water: A Case Study of Hanyuan County, Southwest Mountainous Area, China

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