Heterogeneous adsorption behavior of landfill leachate on granular activated carbon revealed by fluorescence excitation emission matrix (EEM)-parallel factor analysis (PARAFAC)

• Heterogeneous adsorption of leachates on GAC is explored by EEM-PARAFAC.
• First work to apply EEM-PARAFAC for treatment processes of landfill leachate.
• Two humic-like components are identified from leachate DOM.
• C1 showed a greater isotherm nonlinearity and a slower adsorption speed than C2.
• Heterogeneous behavior is explained by pore blockage and size exclusion effects.

Heterogeneous adsorption behavior of landfill leachate on granular activated carbon (GAC) was investigated by fluorescence excitation-emission matrix (EEM) combined with parallel factor analysis (PARAFAC). The equilibrium adsorption of two leachates on GAC was well described by simple Langmuir and Freundlich isotherm models. More nonlinear isotherm and a slower adsorption rate were found for the leachate with the higher values of specific UV absorbance and humification index, suggesting that the leachate containing more aromatic content and condensed structures might have less accessible sites of GAC surface and a lower degree of diffusive adsorption. Such differences in the adsorption behavior were found even within the bulk leachate as revealed by the dissimilarity in the isotherm and kinetic model parameters between two identified PARAFAC components. For both leachates, terrestrial humic-like fluorescence (C1) component, which is likely associated with relatively large sized and condensed aromatic structures, exhibited a higher isotherm nonlinearity and a slower kinetic rate for GAC adsorption than microbial humic-like (C2) component. Our results were consistent with size exclusion effects, a well-known GAC adsorption mechanism. This study demonstrated the promising benefit of using EEM-PARAFAC for GAC adsorption processes of landfill leachate through fast monitoring of the influent and treated leachate, which can provide valuable information on optimizing treatment processes and predicting further environmental impacts of the treated effluent.