Organic contaminants are of major concern for drinking water treatment, and many of them are listed in the drinking water quality standards for different nations and organizations. Activated carbon (AC) adsorption is a common method used to remove organic contaminants from water. During AC applications for drinking water treatment, the adsorption capacities for specific AC/compound combinations need to be known in advance. Since the number of organic compounds is very large, it is not possible or feasible to directly measure the adsorption capacities for all compounds. Therefore, models able to predict adsorption isotherms with reasonable accuracy based on the specific properties of organic contaminants and ACs may greatly reduce the experimental effort for obtaining the adsorption capacities. The aims of this study were to develop models for the prediction of adsorption capacities for organic compounds onto ACs in water, simply based on the properties of ACs and targeted organic compounds. The pore size distribution (PSD) data of ACs and the molecular properties of chemicals were chosen in the models as input parameters. The models were then tested for chemicals with different functional groups onto different ACs in both deionized and natural water.
The model approach was first developed for the adsorption isotherms of low-molecular-weight nonpolar organic compounds (LMWNPOCs) onto ACs. The Polanyi-Dubinin (PD) equation, with the limiting pore volume of adsorbent estimated from the PSD data, and the adsorption affinity (N) of adsorbate described by the molecular connectivity index (MCI) was used to simulate the adsorption data. The model was first trained for the adsorption data of 34 LMWNPOCs onto a typical AC, F400, in deionized water. The results revealed that PSD may be used to represent limiting adsorption volume (Wo), with the best justified exponential constant (n) equal to 1.1, and the N’s best described with 15 molecular connectivity indexes (MCIs) pairs. The developed model was then successfully applied to predict adsorption capacity of 8 other compounds onto F400 and Turumi HC-30 ACs. Because the properties of GACs and adsorbates are considered in the model, the model is able to predict the adsorption capacity of LMWNPOCs onto ACs with known PSD information, thus providing a simple approach for isotherm prediction for LMWNPOCs onto different ACs.
In the second part of this study, a model was then developed to predict the competitive adsorption isotherms of small organic compounds onto ACs in natural water. Similar to that in the model for deionized water, PD equation was used for the adsorption isotherm, and Wo was estimated from the PSD data of AC. To incorporate the competitive adsorption of natural organic matter (NOM), and the Ideal adsorbed solution theory - equivalent background compound (IAST-EBC) model was incorporated with the PD equation. The model was successfully tested for atrazine, MTBE, 2-MIB and 2,4,6-trichlorophenol onto 14 ACs in 22 synthetic and natural waters, and results showed that the models follows the experimental data reasonably well. This study proved that the prediction of adsorption capacity for organic compounds onto different ACs in the same natural water is feasible based on the developed PD-IAST-EBC model, if the ACs were thermally activated with known pore size information. in a few of the cases that the pore volume distribution of ACs is significantly different to that of others, the models did not follow the experimental data well, suggesting that the pore volume (size) distribution may have some small effect on the adsorption capacity.
Finally, the PC-MCI model was extended to the adsorption of other chemical groups, including low-molecular-weight polar organic compounds (LMWPOCs), halogenated LMWPOCs, and dye chemicals onto activated carbons (ACs). Attempts have been made to include all the 112 LMWPOCs and 22 dyes into one correlation for N to simulate the adsorption capacity. However, the degree of fit was not good enough for the simulation, very likely due to distinct molecular properties of the chemicals. Therefore, three correlations, one for dyes, another for halogenated LMWPOCs, the other for non-halogenated LMWPOCs, were developed for the model. The good simulation results suggest that the model may provide a simple approach for the prediction of adsorption capacity for those organic chemicals onto different ACs, suggesting that the model approach may be further extended to other chemical groups if the adsorption data is sufficient for the correlation of N’s.

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