H. Dulkadiroglu

Effect of Ozonation on the Biological Treatability of a Textile Mill Effluent

Ozonation, applied prior to biological processes, has proved to be a very effective chemical treatment step mostly for colour removal when soluble dyes are used in textile finishing operations. Its impact on biological treatability however has not been fully evaluated yet. This study evaluates the effect of ozonation on the quality of wastewater from a textile mill involving bleaching and reactive dyeing of cotton and synthetic knit fabric. The effect of ozonation on COD fractionation and kinetic coefficients defining major biological processes is emphasised. The results indicate that the extent of ozone applied greatly affects the remaining organic carbon composition in the wastewater. The relative magnitude of different COD fractions varies as a function of the ozone dose. Ozonation does not however exert a measurable impact on the rate of major biological processes.

Wastewater Reuse for the Minimization of Fresh Water Demand in Coastal Areas—Selected Cases from the Textile Finishing Industry

Abstract Availability of water to the industry often becomes prohibitive, both in terms of quality and cost, in coastal areas. This study takes the textile industry and evaluates the prerequisites of water recovery and reuse. In this context, a large spectrum are studied for their water, the general quality of wastewater generated, quality and treatability of reuse wastewater streams, and expected changes in the overall effluent quality after segregation of the recovery wastewater portion.

Recovery and Reuse in the Textile Industry - A Case Study at a Wool and Blends Finishing Mill

The paper provides experimental justification for a scientific approach to optimizing wastewater recovery and reuse potential in the textile industry. A wool and blends finishing mill, with a high wastewater generation rate, was selected as a case study. A detailed survey was carried out on a selected process to generate a comprehensive pollution profile, which identified a reusable fraction of more than 50%. Chemical settling and oxidation tests were performed to improve the quality of this fraction. COD fractionation and respirometric assessment of biological treatability were evaluated for the wastewater remaining after segregation of the recovered portion, with specific emphasis on the technological implications for appropriate biological treatment.

Feasibility Analysis of In-Plant Control for Water Minimization and Wastewater Reuse in a Wool Finishing Textile Mill

Abstract This study evaluates the feasibility of water minimization and wastewater reuse for a wool finishing textile mill. The evaluation process is based upon a detailed analysis on water use, process profile and wastewater characterization, indicating a potential for 34% reduction in water consumption and for 23% of wastewater recovery for reuse. Wastewater reuse requires treatment and results in a remaining wastewater stream with stronger character and consequently more costly to treat. The feasibility includes technical considerations for appropriate treatment alternatives and related cost factors for water consumption, treatment for reuse and for discharge either to sewer or to receiving media.

Modeling nitrate concentrations in a moving bed sequencing batch biofilm reactor using an artificial neural network technique

AbstractIn this study, the performance data of a moving-bed sequencing batch biofilm reactor (MBSBBR) treating synthetic wastewater were simulated using multi-layer perceptron neural-network technique. Multi-linear regression (MLR) technique is also used for a comparison. The performance of MBSBBR was evaluated using these models for a set of experimental results obtained from a model reactor operated with different cycle times and temperatures. The experimental data were retrieved from a previous reported work. Operational time, temperature, ammonium nitrogen, and pH were used as inputs for modeling, whereas nitrate concentration was the output variable. The results of the models were compared using statistical criteria, such as mean square error, mean absolute error, mean absolute relative error, and determination coefficient (R2). The results showed that the multi-layer perceptron neural-network produced more accurate results than those of MLR, although the latter gave reasonable results.

Scientific basis of dissolved organic carbon limitation for landfilling of municipal treatment sludge – Is it attainable and justifiable?

This study evaluated the scientific and technical basis of the dissolved organic carbon (DOC) limitation imposed on municipal sludge for landfilling, mainly for assessing the attainability of the implemented numerical level. For this purpose, related conceptual framework was analyzed, covering related sewage characteristics, soluble microbial products generation, and substrate solubilization and leakage due to hydrolysis. Soluble COD footprint was experimentally established for a selected treatment plant, including all the key steps in the sequence of wastewater treatment and sludge handling. Observed results were compared with reported DOCs in other treatment configurations. None of the leakage tests performed or considered in the study could even come close to the prescribed limitation. All observed results reflected 10-20 fold higher DOC levels than the numerical limit of 800 mg/kg (80 mg/L), providing conclusive evidence that the DOC limitation imposed on municipal treatment sludge for landfilling is not attainable, and therefore not justifiable on the basis of currently available technology.