Parvez, Shahid ; Venkataraman, Chandra ; Mukherji, Suparna (2008) Toxicity assessment of organic contaminants: Evaluation of mixture effects in model industrial mixtures using 2n full factorial design Chemosphere, 73 (7). pp. 1049-1055. ISSN 0045-6535
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Official URL: https://www.sciencedirect.com/science/article/pii/...
Related URL: http://dx.doi.org/10.1016/j.chemosphere.2008.07.078
Abstract
Toxic organic chemicals present in industrial effluents were screened to design mixtures for examining the significant main and interaction effects among mixture components. A set of five four-component mixtures was selected by examining effluents from organic chemical, textile-dye, pulp-paper and petroleum refinery industries. The screening was based on their discharge, solubility, toxicity and volatility. A 2n full factorial approach was used in designing the mixtures, containing components at two dose levels, EC10(−) and EC40(+). Each mixture resulted in 16 combinations. Mixture toxicity was measured using the Vibrio fischeri bioluminescence inhibition assay. The main effects and binary, ternary and quaternary interaction effects were determined and the significance of effects was evaluated using normal order score and multifactor ANOVA. The organic chemicals retained after screening included, acetaldehyde, aniline, n-butanol, p-cresol, catechol, ethylbenzene, naphthalene, phenol, 1,2,4 trimethylbenzene and o-xylene. In all mixtures, the magnitude of main effects was more significant than the interaction effects. The trend in the main effect of components in any mixture was affected by the trends in the physico-chemical properties of the components, i.e., partition coefficient, molecular size and polarity. In some mixtures, a component with significantly higher concentration and significantly lower toxicity was found to depict a relatively high main effect, as observed for acetaldehyde in mixture I and n-butanol in mixture III. Normal order score approach failed to identify the significant interaction effects that could be identified using multifactor ANOVA. In general, the binary interactions were more significant than the ternary and quaternary interactions.
Item Type: | Article |
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Source: | Copyright of this article belongs to Elsevier Science. |
Keywords: | Partition Coefficient; ANOVA; Interaction Effects; Industrial Effluent |
ID Code: | 114474 |
Deposited On: | 28 May 2018 09:59 |
Last Modified: | 28 May 2018 09:59 |
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