Analysis of Basic Physical-Chemical Parameters, Nutrients and Heavy Metals Content in Surface Water of Small Catchment Area of Karašica and Vučica Rivers in Croatia

Amić, Ana; Tadić, Lidija

doi:10.3390/environments5020020

Cited by 18 publications

(14 citation statements)

References 36 publications

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“…However, like Mg in the dry season, Cd poisoning beyond 100 m from the source of pollution is inevitable all season. A similar observation has also been reported in previous studies including Onojake et al (2017) and Amic and Tadic (2018).…”

Section: Transport Of Studied Heavy Metals In the Urban Waterfrontsupporting

confidence: 92%

Estimation of Mg, Cd, and Ni levels in urban waterfront using one-dimensional transport model

Igoni¹,

Tegu²,

Okparanma³

2020

Int. J. Water Res. Environ. Eng.

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Accurate quantification of heavy metals is essential for optimizing remedial efforts at polluted waterfronts. Although surface water quality models can be helpful tools for rapid quantification of heavy metals in streams, they cannot be extrapolated to other water bodies. This study estimated Mg, Cd, and Ni levels in one of the polluted urban waterfronts in the Niger Delta Province, Nigeria (5.317°N, 6.467°E) using one-dimensional transport model. To do this, water samples were collected along the waterfront in both dry and rainy seasons and analyzed for the selected heavy metals using a SHIMADZU ® AA6800 Atomic Absorption Spectrophotometer according to international standards. Model parameters were determined by simple linear regression using the experimental dataset. Results showed that the average concentrations of Mg (5.964 mg/L), Cd (0.088 mg/L), and Ni (0.071 mg/L) in the waterfront in both dry and rainy seasons exceeded both local and international regulatory values. The seasonal variation of the heavy metals in the waterfront showed that the concentrations of Mg and Cd were higher during the dry season. Model validation of experimental data showed reasonable prediction precision with root mean square error (RMSE) of 0.0016-0.2254 mg/L in the dry season, RMSE of 0.0026-0.3259 mg/L in the rainy season, and corresponding average validation r 2 of 0.985 in both seasons. These results suggest that the waterfront is laden with heavy metals and the one-dimensional transport model is a useful tool to rapidly estimate the levels of Mg, Cd, and Ni in the waterfront for pollution control.

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Section: Transport Of Studied Heavy Metals In the Urban Waterfrontsupporting

confidence: 92%

Estimation of Mg, Cd, and Ni levels in urban waterfront using one-dimensional transport model

Igoni¹,

Tegu²,

Okparanma³

2020

Int. J. Water Res. Environ. Eng.

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“…Thereafter, the relative weights (RW) were calculated by dividing the weight for each variable by the sum of the weights for all variables (Eqs. [1][2][3][4]. The weighted arithmetic index method [9] was used for the computation of WQI.…”

Section: Water Quality Index Estimationmentioning

confidence: 99%

“…In comparison with other previous studies, Tibihika et al [42], Maryam et al [23] and Tibebe et al [41] obtained the average NO 3 -N values of 33.8 ± 2.1 μg/L, 0.46 mg/L and 0.21 mg/L slightly higher the values obtained in the current study. In aquatic environments, NO 3 -N are important nutrients necessary for the growth of aquatic plants; nevertheless, the concentration > 90 mg/L is toxic to aquatic organisms [4]. The major pathways that naturally increase NO 3 -N content in lake ecosystems are rain, fog, snow, decomposition of organic matter and fertilizer application in agricultural fields.…”

Section: Variability In the Nutrient Concentrationsmentioning

confidence: 99%

Spatio-temporal variations in physicochemical water quality parameters of Lake Bunyonyi, Southwestern Uganda

et al. 2021

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The current study was carried out to examine the spatial and temporal variations of physicochemical water quality parameters of Lake Bunyonyi. The observations were made on the surface water of Lake Bunyonyi for 1 year to determine the water quality. The basic 12 variables used to determine the quality of water were measured monthly at nine stations. Water temperature, dissolved oxygen (DO), turbidity, electric conductivity (EC), pH and Secchi depth (SD) were measured in the field, while parameters like total nitrogen (TN), total phosphorus (TP), nitrite-nitrogen (NO2-N), nitrate-nitrogen (NO3-N), soluble reactive phosphorus (SRP) were determined following APHA 2017 standard guidelines for physicochemical analysis. Taking into account standard guidelines for drinking water by the Uganda National Bureau of Standards (UNBS) and the World Health Organization (WHO), the water quality index (WQI) was used to determine the water quality. Temperature, DO, pH, turbidity and EC did not differ significantly among the study stations (p > 0.05) but showed significant temporal variations among the study months (p < 0.05). Likewise, TN, TP, NO2-N, NO3-N and SRP did not differ significantly among the study stations (p > 0.05) but showed significant temporal variations among the study months (p < 0.05). The WQI values ranged from 28.36 to 49 across and from 28.2 to 56.2 between study months with an overall mean value of 36.9. The measured water quality variables did not exceed the UNBS and WHO standards for drinking water in all months and at all stations. According to these values, the water quality of Lake Bunyonyi generally belongs to the ‘good’ class in terms of drinking water quality based on the WQI classification. The study findings are fundamentally important for policy makers in setting guidelines for effective lake management.

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“…Heavy metal is defined as pollutants and will affect the environment is by participation in biogeochemical cycles, bioaccumulation, high toxicity and biomagnification. The chemical elements naturally occurring in the environment are very small, so a variety of anthropogenic sources such as the oil industry, herbicides, combustion of fossil fuels, pesticides, chemical industry, industry plastic, fertilizer minerals and other bringing significant improvement in their focus [5][6]. Water pollution is a main problem in the global environment.…”

Section: Introductionmentioning

confidence: 99%

Spatial Variation and Possible Sources Assessment at Federal Territory of Kuala Lumpur Water Treatment Plan Using Chemometric Technique

Zolkipli¹,

Juahir²,

Adiana³

et al. 2018

IJET

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This study aims to identify the possible sources in drinking water parameters heavy metal and organic parameters (HMOPs) and spatial variation between untreated water and treated water at Federal Territory of Kuala Lumpur water treatment plant. The indicator HMOPs in drinking water in Kuala Lumpur were selected as parameters to discriminate the possible source of water treatment plants (WTPs) pollutant. Chemometric technique such as principal component analysis (PCA) and discriminant analysis (DA) was identified based on the five years’ availability data starting from 2012 to 2016. PCA were used to identify the most significant parameters which are highlighted eleven strong factors loading of parameter respectively out of sixteen for PCs and classified as possible sources in WTPs. Continue with DA analysis that is successful distinguish two categories region in WTP using the forward stepwise and backward stepwise with significant amount is 98.46%. From this study, we can conclude that this chemometric is the best technique of analysis to get a lot of information such as identify possible sources of pollutant and discriminant of two station sampling categories that will give novelty to Malaysian Ministry of Health (MOH) and collaboration agency in National Drinking Water Quality Surveillances Program (NDWQSP).

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Analysis of Basic Physical-Chemical Parameters, Nutrients and Heavy Metals Content in Surface Water of Small Catchment Area of Karašica and Vučica Rivers in Croatia

Cited by 18 publications

References 36 publications

Estimation of Mg, Cd, and Ni levels in urban waterfront using one-dimensional transport model

Estimation of Mg, Cd, and Ni levels in urban waterfront using one-dimensional transport model

Spatio-temporal variations in physicochemical water quality parameters of Lake Bunyonyi, Southwestern Uganda

Spatial Variation and Possible Sources Assessment at Federal Territory of Kuala Lumpur Water Treatment Plan Using Chemometric Technique

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