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Devpura, India

Bhargava D.S.,Bhargava Lane
Indian Journal of Environmental Protection | Year: 2013

Advances in industrial activities have resulted in numerous kinds of wastewater generation. The problems of industrial wastewater management, therefore, manifest more complexities. They may interfere with each other. Thus, a common treatment is neither economical nor desirable. Apart from modifications in raw materials use and in process technology, segregation and reuse (or recycle) of the various wastewaters is an effective strategy for an efficient management. The paper discusses recycle application through an integrated quality index of the various wastewaters, in regard to the various water uses in the industrial complex. The wastewaters quality ca, if necessary, be improved, through minor treatments for reuse in the various industrial processes. A matching of the wastewater quality indices and the index requirement of the various water uses would ultimately leave verv little of industrial wastewater to be finally treated and disposed off.© 2013 Kalpana Corporation. Source


Bhargava D.S.,Bhargava Lane | Rajagopal K.,Salem College
Indian Journal of Environmental Protection | Year: 2011

For a class-II sedimentation, the design parameters, such as the overflow rate, detention time, etc., are at present evaluated from the results obtained from the column tests. To evaluate the effect of the initial suspended solids concentration and the nature of the suspended materials to be removed, column settling tests were conducted for the different initial concentrations of the several suspended materials, such as in the sugar mill waste and domestic wastewater (both containing the settleable organic solids), and the floes of the aluminium hydroxide and the ferric hydroxide (both representing the chemical floes). Using the column test data, a general predictive model has been developed to determine the overall percentage removals in relation to the depth of the basin, initial suspended solids concentration and overflow rate for the above said suspended materials. The settling material characteristics of the organic wastes and chemical floes expressed through the sludge volume index (SVI) has been correlated with some of the model coefficients. Such predictive models can be used to evaluate the interrelationships between clarifier design parameters. The paper is presented in three parts, respectively dealing with : (I) Preliminaries, experimentation and modelling, (II) alternate modelling based on the data of other authors and (III) modelling utilizing the polynominal approach. This paper is only dealing with preliminaries, experimentation and modelling for a class-II sedimentation. Part II and III will be discussed in the coming issues. © 2011 - Kalpana Corporation. Source


Bhargava D.S.,Bhargava Lane | Rajagopal K.,Salem College
Indian Journal of Environmental Protection | Year: 2011

For a class-II sedimentation, the design parameters, such as the overflow rate, detention time, etc., are at present evaluated from the results obtained from the column tests. To evaluate the effect of the initial suspended solids concentration and the nature of-the suspended materials to be removed, column settling tests were conducted for the different initial concentrations of the several suspended materials, such as in the sugar mill waste and domestic wastewater (both containing the settleable organic solids), and the floes of the aluminium hydroxide and the ferric hydroxide (both representing the chemical floes). Using the column test data, a general predictive model has been developed to determine the overall percentage removals in relation to the depth of the basin, initial suspended solids concentration and overflow rate for the above said suspended materials. The settling material characteristics of the organic wastes and chemical floes expressed through the sludge volume index (SVI) has been correlated with some of the model coefficients. Such predictive models can be used to evaluate the interrelationships between clarifier design parameters. The paper is presented in 3 parts, respectively dealing with : (I) Preliminaries, experimentation and modelling, (II) alternate modelling based on the data of other authors and (III) modelling utilizing the polynominal approach. This paper is dealing with alternative modelling based on the data of other authors and modelling utilizing the polynominal approach. Part 1-Preliminaries, experimentation and modelling has already been published in April 2011 issue of this journal © 2011 - Kalpana Corporation. Source


Bhargava D.S.,Bhargava Lane | Shrihari S.,Bhargava Lane | Shrihari S.,National Institute of Technology Karnataka
Indian Journal of Environmental Protection | Year: 2011

Field observations were conducted at Kanpur to analyze the ration of biochemical oxygen demand (BOD) contributions by benthalsludge to the overlying waters of the river Ganga. This data was later correlated to the data obtained under different conditions of operating and process variables in the laboratory. Observations were made at 3 sections along the river downstream of an outfall discharging partially treated wastewater. The rate of BOD contribution by benthalsludge to the overlying waters was estimated by utilizing the observed values of dissolved oxygen (DO) and BOD and is presented in Part 2 of this paper. The rate of BOD contribution was higher at section A during summer and at section B during winter, throughout the depth of overlying waters. This is because of the higher stabilization of the settled organic matter during summer. In winter, the BOD released gets carried away to the downstream sections. The rate of BOD contributions (expressed as a percentage of the BOD remaining in the top benthalsludge layers) was insignificant during winter. The rate of BOD contribution (expressed as a percentage of the BOD added continuously) was higher at sections closer to the outfall during summer, but higher at section B in winter. Predictive models were developed for the rate of BOD contribution by benthalsludge. The observations in the laboratory were done on a significantly smaller model and the field data differed by an order of magnitude. Models were developed to predict the overall scale factor (OSF) for different field conditions by benthalsludge by using the laboratory models. © 2011 - Kalpana Corporation. Source


Bhargava D.S.,Bhargava Lane | Shrihari S.,Bhargava Lane | Shrihari S.,National Institute of Technology Karnataka
Indian Journal of Environmental Protection | Year: 2011

Field observations conducted at Kanpur, to analyze the ration of biochemical oxygen demand (BOD) contributions by benthalsludge to the overlying waters of the river Ganga were presented in Part 1 of this paper. This data was later correlated to the data obtained under different conditions of operating and process variables in the laboratory. Observations were made at 3 sections along the river downstream of an outfall discharging partially treated wastewater. The rate of BOD contribution by benthalsludge to the overlying waters was estimated by utilizing the observed values of dissolved oxygen (DO) and BOD. The rate of BOD contribution was higher at section A during summer and at section B during winter, throughout the depth of overlying waters. This is because of the higher stabilization of the settled organic matter during summer. In winter, the BOD released gets carried away to the downstream sections. The rate of BOD contributions (expressed as a percentage of the BOD remaining in the top benthalsludge layers) was insignificant during winter. The rate of BOD contribution (expressed as a percentage of the BOD added continuously) was higher at sections closer to the out fall during summer, but higher at section B in winter. Predictive models were developed for the rate of BOD contribution by benthalsludge. The observations in the laboratory were done on a significantly smaller model and the field data differed by an order of magnitude. Models were developed to predict the overall scale factor (OSF) for different field conditions by benthalsludge by using the laboratory models. © 2011 - Kalpana Corporation. Source

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