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The effect of NOM preloading on the adsorption of phenanthrene (PNT) and trichloroethylene (TCE) by pristine graphene nanosheets (GNS) and graphene oxide nanosheet (GO) was investigated and compared with those of a single-walled carbon nanotube (SWCNT), a multi-walled carbon nanotube (MWCNT), and two coal based granular activated carbons (GACs). PNT uptake was higher than TCE by all adsorbents on both mass and surface area bases. This was attributed to the hydrophobicity of PNT. The adsorption capacities of PNT and TCE depend on the accessibility of the organic molecules to the inner regions of the adsorbent which was influenced from the molecular size of OCs. The adsorption capacities of all adsorbents decreased as a result of NOM preloading due to site competition and/or pore/interstice blockage. However, among all adsorbents, GO was generally effected least from the NOM preloading for PNT, whereas there was not observed any trend of NOM competition with a specific adsorbent for TCE. In addition, SWCNT was generally affected most from the NOM preloading for TCE and there was not any trend for PNT. The overall results indicated that the fate and transport of organic contaminants by GNSs and CNTs type of nanoadsorbents and GACs in different natural systems will be affected by water quality parameters, characteristics of adsorbent, and properties of adsorbate.

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The objective of this paper was to create a comprehensive database for the adsorption of organic compounds by carbon nanotubes (CNTs) and to use the Linear Solvation Energy Relationship (LSER) technique for developing predictive adsorption models of organic compounds (OCs) by multi-walled carbon nanotubes (MWCNTs) and single-walled carbon nanotubes (SWCNTs). Adsorption data for 123 OCs by MWCNTs and 48 OCs by SWCNTs were compiled from the literature, including some experimental results obtained in our laboratory. The roles of selected OCs properties and CNT types were examined with LSER models. The results showed that the r(2) values of the LSER models displayed small variability for aromatic compounds smaller than 220 g/mol, after which a decreasing trend was observed. The data available for aliphatics was mainly for molecular weights smaller than 250 g/mol, which showed a similar trend to that of aromatics. The r(2) values for the LSER model on the adsorption of aromatic and aliphatic OCs by SWCNTs and MWCNTs were relatively similar indicating the linearity of LSER models did not depend on the CNT types. Among all LSER model descriptors, V term (molecular volume) for aromatic OCs and B term (basicity) for aliphatic OCs were the most predominant descriptors on both type of CNTs. The presence of R term (excess molar refractivity) in LSER model equations resulted in decreases for both V and P (polarizability) parameters without affecting the r(2) values. Overall, the results demonstrate that successful predictive models can be developed for the adsorption of OCs by MWCNTs and SWCNTs with LSER techniques.

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The LSER models for adsorption of SOCs by CNMs profoundly depend on compound properties, adsorbent characteristics and the background solution.