Abstract Background and Objective: Monitoring of organic carbon in water resources is a critical quality index in environmental management, water quality monitoring and drinking water projects. In this study, the performance and applicability of artificial neural networ More
Abstract Background and Objective: Monitoring of organic carbon in water resources is a critical quality index in environmental management, water quality monitoring and drinking water projects. In this study, the performance and applicability of artificial neural network and multiple nonlinear regression modeling were investigated and optimized for the prediction of dissolved organic carbon. Method: Optimization was performed using backward elimination method with the highest probable correlation coefficient and minimum number of input parameters. Findings: Model verification showed a good agreement between the predicted organic carbon and actual observations. Results showed the acceptable performance of neural network model with the mean absolute error percentage of 7.6% and correlation coefficient of 0.91. Discussion and Conclusion: Further investigations unveiled that although the multiple regression model, with mean absolute error percentage of 8.4% and correlation coefficient of 0.89, seems to be less appealing but its fast run-time and better performance in critical conditions makes it a better choice for the prediction of organic carbon in aqueous solotions with high range of qualitative changes.
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Estuaries are considered as important zones for the occurrence of environmental، biological and geochemical processes. Elements are carried to the sea through rivers and estuaries are pathways for this transmission. In estuaries dissolved elements of river water ooze ou More
Estuaries are considered as important zones for the occurrence of environmental، biological and geochemical processes. Elements are carried to the sea through rivers and estuaries are pathways for this transmission. In estuaries dissolved elements of river water ooze out of dissolved phase due to several estuarine processes such as flocculation. In the present investigation، for the first time of flocculation Zn، Cu، Pb، Ni and Mn during mixing of a filtered sample (0.45µm) from Persian Gulf water with a filtered water sample taken from the Minab river in 9 different salinity proportions is studied. For the first time flocculation of elements in relation to redox potential (Eh) is investigated and the results indicated that elemental flocculation during estuarine mixing is not controlled by (Eh). The flocculation trend of studied metals is Cu (83.3%)> Ni (82.9)> Zn (75.2%)> Mn (69.4%) > Pb (38%). Flocculation rate varies considerably from one metal to another. Highest flocculation of metals occurs between salinities of 3.3‰ to 11.4‰. Statistical analysis indicate that flocculation of metals (except for Pb) is governed by dissolved organic carbon whose source is teri-genous in the area of study. The amount of metal flocculation is about 30.5، 6.6، 25.3، 10.4 and 36.5 ton/yr for Zn، Pb، Ni، Cu and Mn، respectively، as a result of mixing of Minab river water with the Persian Gulf water. Therefore estuarine processes can be considered as effective mechanisms in clean up of colloidal metals that are anthrop pogenically entered into the fresh water ecosystem.
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Background and Objective: Humic acids are main components of natural organic matters that have many negative effects, especially reaction with chlorine and production of disinfection by-products in water. Thus, the methods for the removal of these substances from water More
Background and Objective: Humic acids are main components of natural organic matters that have many negative effects, especially reaction with chlorine and production of disinfection by-products in water. Thus, the methods for the removal of these substances from water have been considered. Enhanced coagulation is a simple, suitable and efficient process for the removal of humic substances. Method: This study evaluates the enhanced coagulation effectiveness, as a suitable method for the removal of humic substance by polyaluminium chloride as a coagulant in a concentration between 1 to 20 mg/l in jar test. Results: Dissolved organic carbon, ultraviolet absorbance, specific ultraviolet absorbance and humic acid were determined as humic substances indexes in concentration between 0.1 to 5 mg/l. According to the obtained results, high level of specific ultraviolet absorbance index in the water source showed that enhanced coagulation was necessary for the removal of humic substance. Also, according to the obtained results, the average removal efficiency obtained by enhanced coagulation for humic acid was 52%, for dissolved organic carbon was 43% and for UV254 was 57%. Conclusion: It was concluded that employing polyaluminium as a coagulant in enhanced coagulation process is inexpensive, suitable and efficient and can remove humic substance to optimum value without decreasing turbidity efficiency.
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