Development of a mechanistic model to assess the distribution of heavy metals in municipal waste water treatment
Development of a mechanistic model to assess the distribution of heavy metals in municipal waste water treatment
This research advances the understanding of the fate of two heavy metals, copper and zinc, in municipal wastewater treatment systems and is thus valuable to integrated wastewater management. The principal aim of this project was to develop a modelling tool to determine the fate of heavy metals in municipal wastewater treatment plants.
This was accomplished using a strategy, which consisted of five stages. The first stage, the literature review, revealed that metal interactions in wastewater treatment processes are complex, with many factors and mechanisms influencing heavy metal removal. However, certain factors appear to be of significant importance with regard to the development of a metals predictive model. Of these factors, the fate of suspended solids in the treatment plant was found to closely influence metal removal. Hence, in the second stage, a model was developed to determine the partitioning of the suspended solids between the sludge and liquid phases in the different wastewater treatment processes. The third stage focused on the development of a model for the heavy metals. Modelling of the mechanisms of heavy metal removal can be undertaken using a variety of methods, such as equilibrium chemical modelling, use of adsorption isotherms, empirical as well as mechanistic modelling methods. The use and general applicability of these techniques to achieve the objectives of the current research were critically assessed. The most suitable approach for the purpose of this research was found to be a combination of the approaches. The adsorption isotherm approach to modelling describes the physico-chemical mechanisms that are recognised as being important in the removal of heavy metals, while the mechanistic approach allows these mechanisms to be modelled for a range of influencing factors. In the fourth stage, batch experiments were carried out to determine both the solubility and adsorption of two heavy metals, copper and zinc, under various conditions. The methodology for obtaining model coefficients and correlations with important parameters, such as pH and the solids concentration, was developed. The results of these experiments provide an in depth understanding of the parameters influencing metal removal and how they interact with each other. The objective of the fifth and final stage was the verification of the model and model coefficients. It was accomplished by carrying out field studies at two wastewater treatment plants in the Southampton area. The Solids Mass Balance and Heavy Metals models are programmed under the Visual Basic Editor of Microsoft Excel 97 to provide a userfriendly interface to aid in the prediction of effluent and sludge concentrations of metals.
University of Southampton
Gaber, Noha
f93ba0b1-6d3d-4095-be30-0f6773301ae4
1 June 2001
Gaber, Noha
f93ba0b1-6d3d-4095-be30-0f6773301ae4
Banks, Charles
5c6c8c4b-5b25-4e37-9058-50fa8d2e926f
Gaber, Noha
(2001)
Development of a mechanistic model to assess the distribution of heavy metals in municipal waste water treatment.
University of Southampton, Doctoral Thesis, 465pp.
Record type:
Thesis
(Doctoral)
Abstract
This research advances the understanding of the fate of two heavy metals, copper and zinc, in municipal wastewater treatment systems and is thus valuable to integrated wastewater management. The principal aim of this project was to develop a modelling tool to determine the fate of heavy metals in municipal wastewater treatment plants.
This was accomplished using a strategy, which consisted of five stages. The first stage, the literature review, revealed that metal interactions in wastewater treatment processes are complex, with many factors and mechanisms influencing heavy metal removal. However, certain factors appear to be of significant importance with regard to the development of a metals predictive model. Of these factors, the fate of suspended solids in the treatment plant was found to closely influence metal removal. Hence, in the second stage, a model was developed to determine the partitioning of the suspended solids between the sludge and liquid phases in the different wastewater treatment processes. The third stage focused on the development of a model for the heavy metals. Modelling of the mechanisms of heavy metal removal can be undertaken using a variety of methods, such as equilibrium chemical modelling, use of adsorption isotherms, empirical as well as mechanistic modelling methods. The use and general applicability of these techniques to achieve the objectives of the current research were critically assessed. The most suitable approach for the purpose of this research was found to be a combination of the approaches. The adsorption isotherm approach to modelling describes the physico-chemical mechanisms that are recognised as being important in the removal of heavy metals, while the mechanistic approach allows these mechanisms to be modelled for a range of influencing factors. In the fourth stage, batch experiments were carried out to determine both the solubility and adsorption of two heavy metals, copper and zinc, under various conditions. The methodology for obtaining model coefficients and correlations with important parameters, such as pH and the solids concentration, was developed. The results of these experiments provide an in depth understanding of the parameters influencing metal removal and how they interact with each other. The objective of the fifth and final stage was the verification of the model and model coefficients. It was accomplished by carrying out field studies at two wastewater treatment plants in the Southampton area. The Solids Mass Balance and Heavy Metals models are programmed under the Visual Basic Editor of Microsoft Excel 97 to provide a userfriendly interface to aid in the prediction of effluent and sludge concentrations of metals.
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Gaber
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Published date: 1 June 2001
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Local EPrints ID: 437246
URI: http://eprints.soton.ac.uk/id/eprint/437246
PURE UUID: ad5feb75-3560-485e-ace5-b8ddd79e025c
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Date deposited: 22 Jan 2020 17:33
Last modified: 17 Mar 2024 02:43
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Author:
Noha Gaber
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