Evaluating the long-term performance of low-cost adsorbents using small-scale adsorption column experiments
This study investigated a novel method of predicting the long-term phosphorus removal performance of large-scale adsorption filters, using data derived from short-term, small-scale column experiments. The filter media investigated were low-cost adsorbents such as aluminum sulfate drinking water trea...
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Veröffentlicht in: | Water research (Oxford) 2016-09, Vol.101, p.429-440 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This study investigated a novel method of predicting the long-term phosphorus removal performance of large-scale adsorption filters, using data derived from short-term, small-scale column experiments. The filter media investigated were low-cost adsorbents such as aluminum sulfate drinking water treatment residual, ferric sulfate drinking water treatment residual, and fine and coarse crushed concretes. Small-bore adsorption columns were loaded with synthetic wastewater, and treated column effluent volume was plotted against the mass of phosphorus adsorbed per unit mass of filter media. It was observed that the curve described by the data strongly resembled that of a standard adsorption isotherm created from batch adsorption data. Consequently, it was hypothesized that an equation following the form of the Freundlich isotherm would describe the relationship between filter loading and media saturation. Moreover, the relationship between filter loading and effluent concentration could also be derived from this equation. The proposed model was demonstrated to accurately predict the performance of large-scale adsorption filters over a period of up to three months with a very high degree of accuracy. Furthermore, the coefficients necessary to produce said model could be determined from just 24 h of small-scale experimental data.
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•This study develops a mathematical model to predict adsorbent performance.•The model successfully described the performances of four adsorbent media.•Small-scale experiments were used to predict the performance of large-scale filters.•Only 24 h of experimental data were required to determine model coefficients. |
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ISSN: | 0043-1354 1879-2448 |
DOI: | 10.1016/j.watres.2016.05.093 |