scholarly journals Effect of contamination sources on the rate of zinc, copper and nickel release from various soil ecosystems

2020 ◽  
Vol 44 (1) ◽  
Author(s):  
Hesham Mansour ◽  
Fikry Awad ◽  
Mohamed Saber ◽  
Alaa Zaghloul
Keyword(s):  
Industrial Effluents ◽  
Environmental Risks ◽  
Coefficient Of Determination ◽  
Polluted Soils ◽  
Potential Toxic Elements ◽  
Soil Ecosystems ◽  
Nickel Release ◽  
Type Of Land Use ◽  
Quality Water ◽  
Agriculture Irrigation

Abstract Background and objective Soil is a substantive component in biosphere habitually endangered to superfluity contaminants particularly potential toxic elements (PTEs). The source of soil contaminants is very critical in controlling both their release and expected hazards in the different soil ecosystems. This study aims to investigate the effect of low-quality irrigation water (LQW) on the extent of soil pollution through desorption of zinc (Zn), nickel (Ni) and copper (Cu) from different polluted soils, collected from LQW irrigated farms for more than 40–80 years at Giza and Kafr-Elsheikh Governorates, Egypt. Results Models incorporated modified Freundlich (MFE), Elovich, first order and parabolic diffusion (PDE) showed significant results in describing the kinetic data under Egyptian conditions. Results entailed that according to the coefficient of determination (R2) and standard error, all used models well described the desorption of Cu, Ni and Zn, the most prevalent contaminants in the trailed soil ecosystems; for example, the R2 values were higher than 0.96** for zinc desorption using MFE model. As far as the PTEs levels are considered, the highest contaminant desorption rates were recorded at Kafr-Elsheikh site, followed by Kombora, and the lowest ones were in Abo Rawash soil ecosystem. The succession of more than one model to describe the kinetic perspective confirmed that the different mechanisms take place in PTEs sorption, distribution and subsequently release from different soil ecosystems. Conclusions The numerical values indicated that the soil ecosystems contaminated with industrial effluents were higher than those irrigated with sewage effluents regardless of the type of land use. More attention should be paid to low-quality water application in agriculture irrigation and its environmental risks.

scholarly journals Evaluation of biochemical treatments applied in polluted soils irrigated with low quality water for long periods of time through the CO2 efflux

2021 ◽  
Vol 117 (4) ◽  
pp. 1
Author(s):  
Mohamed SABER ◽  
Alaa M ZAGHLOUL
Keyword(s):  
Microbial Population ◽  
Research Centre ◽  
Co2 Efflux ◽  
Soil Ecosystem ◽  
Inorganic Pollutants ◽  
Polluted Soils ◽  
Untreated Soil ◽  
Good Tool ◽  
Soil Ecosystems ◽  
Quality Water

<p class="042abstractstekst"><span lang="EN-US">To sightsee the bearings of the certain remediation amendments, usually applied in the bioremediation of soils irrigated with low quality water for extended periods on the indigenous microbial population, a greenhouse experiment was conducted at National Research Centre (NRC) where the soil ecosystem was supplied with varied mineral remediation amendments and the carbon dioxide (CO<sub>2</sub>) refluxes were followed up. In this study, microbial activity through CO<sub>2</sub> efflux was taken as an indicator to evaluate the effectiveness of eight soil amendments in minimizing the hazards of inorganic pollutants in soil ecosystem irrigated with low quality water s for more than 40 years. Results showed that Ni and Zn were the most dominant contaminants that adversely influenced indigenous microbial activities in untreated soil, while Cu was the most persuasive. All trailed remediation amendments significantly minimized the hazards of inorganic pollutants in treated soil ecosystems. In addition, modified bentonite (Probentonite) was the best persuasive one. Mechanisms take place between trailed remediation amendments and inorganic pollutants in the studied soil ecosystems were discussed. In conclusion application of certain raw or modified clay minerals especially Probentonite could be a good tool in decreasing the rate of the studied inorganic pollutants in a contaminated soil ecosystem irrigated with low quality water for extended periods. </span></p>

scholarly journals Modeling and simulation of the enzymatic degradation of 2,4,6-trichlorophenol using soybean peroxidase

2021 ◽  
Author(s):  
Alexandre Santuchi da Cunha ◽  
Ardson dos Santos Vianna Junior ◽  
Enzo Laurenti
Keyword(s):  
Experimental Data ◽  
Enzymatic Degradation ◽  
Weighted Least Squares ◽  
Industrial Effluents ◽  
Complex Model ◽  
Enzyme Inactivation ◽  
Coefficient Of Determination ◽  
Soybean Peroxidase ◽  
Data Set ◽  
Function Coefficient

Abstract The enzymatic degradation of organic pollutants is a promising and ecological method for the remediation of industrial effluents. 2,4,6-Trichlorophenol is a major pollutant in many residual waters, and its consumption has been linked to lymphomas, leukemia, and liver cancer. The goal of the present work is to comprehend the enzymatic degradation of 2,4,6-trichlorophenol using soybean peroxidase. Different assumptions for the kinetic model were evaluated, and the simulations were compared to experimental data, which was obtained in a microreactor. The literature pointed out that the bi-bi ping-pong model represents well the kinetics of soybean peroxidase degradation. Since it is a complex model, some reactions can be considered or not. Six different possibilities for the model were considered, regarding different combinations of the generated enzyme forms that depend on the hypotheses for simplifying the model. The adjustment of the models was compared based on different metrics, such as the value of the objective function, coefficient of determination and root-mean-square error. The process modeling was obtained by the mass balance of all the reaction components, and all the simulations were performed in MATLAB® R2015a. Reaction parameters were estimated based on the weighted least squares between the experimental data set and the values predicted by the model. The results showed that the data were better adjusted by the model that considers all the enzyme forms, including enzyme inactivation. Therefore, a better comprehension of the reaction mechanism was achieved, which allows a more precise reactor project and process simulation.

scholarly journals Optimization of Chromium Removal by the Indigenous Bacterium Bacillus spp. REP02 Using the Response Surface Methodology

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
C. K. Venil ◽  
V. Mohan ◽  
P. Lakshmanaperumalsamy ◽  
M. B. Yerima
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Yeast Extract ◽  
Industrial Effluents ◽  
Quadratic Model ◽  
Coefficient Of Determination ◽  
Indigenous Bacterium ◽  
Bacillus Spp ◽  
Chromium Electroplating ◽  
Bacterium Bacillus

An indigenous bacterium, Bacillus REP02, was isolated from locally sourced chromium electroplating industrial effluents. Response surface methodology was employed to optimize the five critical medium parameters responsible for higher % Cr2+ removal by the bacterium Bacillus REP02. A three-level Box-Behnken factorial design was used to optimize K2HPO4, yeast extract, MgSO4, NH4NO3, and dextrose for Cr2+ removal. A coefficient of determination (R2) value (0.93), model F-value (3.92) and its low P-value (F<0.0008) along with lower value of coefficient of variation (5.39) indicated the fitness of response surface quadratic model during the present study. At optimum parameters of K2HPO4 (0.6 g L−1), yeast extract (5.5 g L−1), MgSO4 (0.04 g L−1), NH4NO3 (0.20 g L−1), and dextrose (12.50 g L−1), the model predicted 98.86% Cr2+ removal, and experimentally, 99.08% Cr2+ removal was found.

Application of statistical experimental design to the treatment of bleaching kraft mill effluent using a mediated free radical system

2007 ◽  
Vol 55 (6) ◽  
pp. 1-7 ◽  
Author(s):  
V. Arantes ◽  
A.M.F. Milagres
Keyword(s):  
Experimental Design ◽  
Regression Model ◽  
Oxygen Demand ◽  
Industrial Effluents ◽  
Second Order ◽  
Cod Removal ◽  
Coefficient Of Determination ◽  
Statistical Experimental Design ◽  
Kraft Mill Effluent ◽  
Kraft Mill

The aim of this work was to evaluate the effect of chelator mediated-Fenton reaction (CMFR) on the chemical oxygen demand (COD) removal from bleaching kraft mill effluent. Effluent treatments were carried out to study the effect of the chelator 3, 4-dihydroxyphenylacetic acid (DOPAC), Fe3 +  and H2O2 concentrations on COD removal. For optimization of COD removal, the methodology of statistical experimental design was employed. The estimated second-order polynomial multiple regression model predicts a maximum COD removal of 75.5% (COD/COD0 = 0.245) at the confidence level of 95%. Analysis of variance (ANOVA) showed a good coefficient of determination (R2) value of 0.90, thus ensuring a satisfactory adjustment of the second-order regression model with the experimental data. Indeed, CMFR proved to be a potential process to treat industrial effluents characterized by its high COD.

scholarly journals Water quality indices and abiotic characteristics of western Yamuna canal in Yamunanagar, Haryana

2009 ◽  
Vol 1 (2) ◽  
pp. 149-154 ◽  
Author(s):  
Anita Bhatnagar ◽  
Girish Chopra ◽  
Priyanka Malhotra
Keyword(s):  
Water Quality ◽  
Fish Fauna ◽  
Industrial Effluents ◽  
Domestic Sewage ◽  
Quality Indices ◽  
Canal Water ◽  
Efficient Treatment ◽  
Physico Chemical ◽  
Quality Water ◽  
Monthly Variations

The present paper deals with the monthly variations of physico-chemical characteristics of western Yamuna canal water, Yamunanagar which is polluted with industrial effluents and domestic sewage. Three sampling points i.e. station-1: Upstream of the river; station-2: Point of influx of industrial effluents and domestic sewage; Station-3: About 6 kms downstream from station 2 were selected for the investigation. Studies revealed high values of turbidity, conductivity, free CO2, alkalinity, calcium, hardness, magnesium, chloride, orthophosphate, phosphate, sulphate and ammonia and low values of DO at station-2. The differences in various parameters were statistically significant (P<0.05) when compared from upstream and downstream stretches of the river particularly in summer. DO and BOD were found to be two important parameters which showed strong correlation with other parameters and hence can serve as good indices of river water quality. Water Quality index designated station-1 as highly polluted and station-2 and 3 as severely polluted. Thus the hydro biological conditions were not congenial/ optimum for the survival/ production of sensitive fish fauna, therefore, proper and efficient treatment of the effluents and sewage should be carried out before discharging these into the canal.

scholarly journals Prediction of Sediment Yield Using the Algoritma Lavenberg-Marquardt

2021 ◽  
Vol 2123 (1) ◽  
pp. 012037
Author(s):  
Uca ◽  
Muhammad Ansarullah S. Tabbu ◽  
Andi Makkawaru
Keyword(s):  
Sediment Yield ◽  
Water Discharge ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Landcover Change ◽  
Quality Water ◽  
Performance Statistics ◽  
Hidden Layer ◽  
Yield Responses ◽  
Basin Area

Abstract Erosion and sediment that occurs in the basin is very important to be studied scientifically.Forcasting of sediment yield in a basins area is important to used to evaluate the land-use/landcover change, soil erosion hazard, planning, water quality, water resources in river, and to determine the extent of the damage that occurred in the basins. The algoritmh lavenberg-marquardt can be used to forcest the total of sediment yield the basin area. Artificial neural networks using feedforward multilayer percePsron with three learning algorithms namely Levenberg-Marquardt. The number of neurons of the hidden layer is three to sixteen, while in the output layer only one neuron because only one output target. The root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2 ), and coefficient of efficiency (CE). The performance value in the training process, R2, and CE (0.98 and 0.98). As well as for the testing process, R2 and CE (0.98 and 0.97). Based on the performance statistics value, LM is very suitable and accurate for to forcesting by modeling the non-linear complex behavior of sediment yield responses to water discharge, intensity of rainfall, and water depth in the river.

Habitat Association of Klebsiella Species

1985 ◽  
Vol 6 (2) ◽  
pp. 52-58 ◽  
Author(s):  
Susan T. Bagley
Keyword(s):  
Drinking Water ◽  
Gastrointestinal Tract ◽  
Surface Waters ◽  
Industrial Effluents ◽  
Opportunistic Pathogen ◽  
Habitat Associations ◽  
Habitat Association ◽  
Klebsiella Species ◽  
Almost All ◽  
Polluted Waters

AbstractThe genus Klebsiella is seemingly ubiquitous in terms of its habitat associations. Klebsiella is a common opportunistic pathogen for humans and other animals, as well as being resident or transient flora (particularly in the gastrointestinal tract). Other habitats include sewage, drinking water, soils, surface waters, industrial effluents, and vegetation. Until recently, almost all these Klebsiella have been identified as one species, ie, K. pneumoniae. However, phenotypic and genotypic studies have shown that “K. pneumoniae” actually consists of at least four species, all with distinct characteristics and habitats. General habitat associations of Klebsiella species are as follows: K. pneumoniae—humans, animals, sewage, and polluted waters and soils; K. oxytoca—frequent association with most habitats; K. terrigena— unpolluted surface waters and soils, drinking water, and vegetation; K. planticola—sewage, polluted surface waters, soils, and vegetation; and K. ozaenae/K. rhinoscleromatis—infrequently detected (primarily with humans).

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