Application of multicriteria decision analysis to jar-test results for chemicals selection in the physical–chemical treatment of textile wastewater

https://doi.org/10.1016/j.jhazmat.2008.08.046Get rights and content

Abstract

Jar-test is a well-known tool for chemicals selection for physical–chemical wastewater treatment. Jar-test results show the treatment efficiency in terms of suspended matter and organic matter removal. However, in spite of having all these results, coagulant selection is not an easy task because one coagulant can remove efficiently the suspended solids but at the same time increase the conductivity or increase considerably the sludge production containing chemicals and toxic dyes. This makes the final selection of coagulants very dependent on the relative importance assigned to each measured parameter.

In this paper, the use of multicriteria decision analysis (MCDA) is proposed to help on the selection of the coagulant and its concentration in the physical–chemical wastewater treatment, since textile wastewater contains hazardous substances. Therefore, starting from the parameters fixed by the jar-test results, these techniques will allow to weight these parameters, according to the judgements of wastewater experts, and to establish priorities among coagulants. Two well-known MCDA techniques have been used: analytic hierarchic process (AHP) and preference ranking organization method for enrichment evaluations (PROMETHEEs) and their results were compared.

The method proposed has been applied to the particular case of textile wastewaters. The results obtained show that MCDA techniques are useful tools to select the chemicals for the physical-technical treatment.

Introduction

Physical–chemical treatment of wastewaters is widely used in the field of the waste industrial effluents. Its application in textile industries can be performed in combination with a biological treatment or as unique treatment if the final effluent is discharged into a sewer. By means of a physical–chemical treatment, removal efficiencies of both suspended solids and COD can reach values up to 95 and 70%, respectively, [1], [2] and colour can also be removed depending on the chemical used [3]. Other authors report about processes combining physical–chemical treatment with hydrolysis/acidification and Fenton oxidation [4] and about biological treatment plus membrane processes [5].

Jar-tests are a valuable tool in wastewater treatment to evaluate the efficiency of a physical–chemical treatment [6]. Chemicals selection and optimum operating conditions (pH and chemicals concentrations) are determined by means of these experiments.

However, selection of the best chemical and the best conditions is not an easy task, since high suspended and organic matter removals are coupled with an increase in conductivity and above all an increase in the sludge production. Besides, the coagulant selection is difficult at first sight since different coagulants show many similar results. Thus, decision has to be made according to different criteria and not only evaluating the pollutants removal efficiency.

In this work, multicriteria decision analysis (MCDA) is proposed as a tool for helping in the design of the physical–chemical wastewater treatment. MCDA “is a term that includes a set of concepts, methods and techniques that seek to help individuals or groups to make decisions, which involve several points of view in conflict and multiple stakeholders” [7]. All these MCDA concepts and methods have been largely studied in the operational research literature [7], [8].

Selection of the mathematical model based on MCDA is not easy. According to Bouyssou et al. [9], there are several models that can be used in a decision-making process. There is no best model. In this paper, the use of two well-known MCDA techniques is proposed: analytic hierarchy process (AHP) [10] and PROMETHEE II [11], the results of which will be analysed and compared.

In the field of water management the MCDA techniques have already been used by different authors. AHP has been applied in Refs. [12], [13], [14]. On the other hand, PROMETHEE has been used in Refs. [15], [16]. Other different MCDA techniques have been used in Refs. [17], [18], [19]. However, no references related to jar-test coagulant selection have been found.

Section snippets

Wastewater characterization

The parameters analysed were conductivity, pH, COD, colour and turbidity. COD was determined with Spectroquant Nova 60 from Merck and turbidity with D-112 apparatus from DINKO. Both conductivity and pH were measured with CRISON apparatus. Colour was calculated by means of the spectral absorption coefficients at three different wavelengths (436, 525 and 620 nm) according to the following equation [20]:colour=A4362+A5252+A6202A436+A525+A620Absorption coefficients values were measured by means of a

Wastewater characterization

In Table 1, characterization results of the raw wastewater of a printing, dyeing and finishing textile industry are shown. As expected, for textile wastewaters COD is approximately 2.5 times higher than for domestic wastewaters. Other characteristics to be highlighted are the alkaline pH (10.5), the salt content, given by the conductivity and the brown colour.

Criteria weights

The criteria weights statement is essential in any MCDA process. The assessment and interpretation of criteria weights have been matters

Conclusions

The authors of this work conclude that MCDA is a useful tool to choose after the jar-tests the chemicals to be used for a physical–chemical wastewater treatment. The use of MCDA techniques has allowed to aggregate the whole volume of information generated with jar-tests and to select the most suitable coagulant for the specific problem to be solved. The proposed tool has the advantage that it brings much information to the decision process and justifies the selection of the chemicals and their

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