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Surface water and groundwater quality assessment using the WQI method and human health risk assessment (HHR) in the lower seybouse (Annaba Plain), northeast Algeria

Fenazi Bilal, Boucenna Fatih, Zeddouri Aziez

Geomatics, Landmanagement and Landscape

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2023

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no. 4

7--25

EN

This study was carried out to investigate the current status of surface water and groundwater quality in Lower Seybouse and Annaba Plain, NE Algeria. 36 surface water and groundwater samples were collected in this area, and various physicochemical parameters were analysed. The quality of surface water and groundwater for drinking and the associated health risks were assessed using a Water Quality Index (WQI) and a Human Health Risk Assessment (HHRA) model. The results show that all samples are alkaline with the EC values ranging from 1139 to 5555 μS/cm. The ionic dominance pattern was in the order of Na+ > Mg2+ > Ca2+ > K+ for cations and Cl– > HCO3 – > SO4 2 – > NO3 – for anions, respectively. The dominant water types are SO4-Cl-Ca-Mg and SO4-Cl-Na, formed by dissolution of evaporative and carbonate-rich material. All samples are unsuitable for drinking, with 1 sample classified as poor (rank = 4) and 35 samples as extremely poor (rank = 5). These samples are mainly located near the Seybouse Wadi, which is a natural outlet for wastewater from human activities. The assessment of non-carcinogenic risk showed that the Hazard Index (HI) for males ranged from 0.12 to 1.01 with a mean of 0.30 and only one sample exceeded value 1. For females, the HI was between 0.16 and 1.28 for females, with a mean of 0.39. The risk for children was even higher, ranging from 0.41 to 3.28, with a mean of 1.03, suggesting that children are more vulnerable to water contamination. The Carcinogenic Risk (CR) values for Pb ranged from 10–3 to 8.6 · 10–3, with a mean of 2.6 · 10–3 for males, and between 1.4 · 10–3 to 10–2, with a mean of 3.3 · 10–3 for females, while for children the CR values ranged from 3.5 · 10–3 to 2.7 · 10–3, with a mean of 8.4 · 10–3, indicating that no possible CR from water drinking

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Analysis of Physicochemical and Microbial Parameters in Refill Drinking Water Sources and Health Risk Assessment: A Case Study in Bandung District, Indonesia

Hasanawi Adib, Salami Indah Rachmatiah Siti

Ecological Engineering & Environmental Technology

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2022

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Vol. 23, iss. 4

45--56

EN

The decline in the quality of groundwater occurred in Bandung District, especially in three areas, namely Ciparay, Dayeuhkolot and Margaasih sub-districts. Pattern shifting in the use of drinking water occurred from groundwater sources to refill drinking water sources. Refill drinking water as a new emerging source is inseparable from contamination. Therefore, a public health risk assessment is carried out due to the use of refill drinking water. Analysis of physicochemical and microbial of refill drinking water was carried out on 45 refill drinking water sample in three areas. Risk characterization is carried out by quantitative methods of calculating the value of the Hazard Quotient (HQ), Hazard Index (HI), and Excess Cancer Risk (ECR) with Monte Carlo analysis. Quality of refill drinking water exceeds the quality standard of Indonesian Minister of Health Regulation No. 492/2010 on the parameters of E. coli, total coliform, and heavy metals (Fe, Al, Se). Oral exposure from refill drinking water showed an acceptable non-carcinogenic risk (HI ≤ 1) in all categories from three areas but adult category in Ciparay Subdistrict has maximum tolerable value for Excess Cancer Risk (ECR), 1 x 10-4, shown that the use of refill drinking water in this area can affect to human health in long-term situation for adults. Reducing public health risk can conducted by improving the process in refill drinking water station, evaluate the quality regularly, and revised the land use masterplan by the government.

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Prediction of remaining useful life for lithium-ion battery with multiple health indicators

Su Chun, Chen Hongjing, Wen Zejun

Eksploatacja i Niezawodność

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2021

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Vol. 23, no. 1

176--183

EN

Lithium-ion (Li-ion) battery has become a primary energy form for a variety of engineering equipments. To ensure the equipments’ reliability, it is crucial to accurately predict Liion battery’s remaining capacity as well as its remaining useful life (RUL). In this study, we propose a novel method for Li-ion battery’s online RUL prediction, which is based on multiple health indicators (HIs) and can be derived from the battery’s historical operation data. Firstly, four types of indirect HIs are built according to the battery’s operation current, voltage and temperature data respectively. On this basis, a generalized regression neural network (GRNN) is presented to estimate the battery’s remaining capacity, and the nonlinear autoregressive approach (NAR) is applied to predict the battery’s RUL based on the estimated capacity value. Furthermore, to reduce the interference, twice wavelet denoising are performed with different thresholds. A case study is conducted with a NASA battery dataset to demonstrate the effectiveness of the method. The result shows that the proposed method can obtain Li-ion batteries’ RUL effectively.