Introduction
Water is essential for life and is an integral part of the physical environment [1]. The rapid growth in global population, industrialization, and climate change are severely stressing water quality and quantity in several countries. These pressures on water resources are heightening concerns about ensuring access to safe drinking water, as outlined in Goal 6 of the 17 Sustainable Development Goals (SDGs) of the United Nations. The infiltration of pesticides [2], pharmaceuticals and personal care products (PPCPs) [3–6], and industrial chemicals such as surfactants, disinfectants, engineered nanomaterials, microplastics, and polycyclic aromatic hydrocarbons into water resources in (ng/L to μg/L) concentration range [7–11], is a significant contributor to global water pollution as organic micropollutants (OMPs). Most of these OMPs are compounds that disturb the endocrine system (EDCs). While some OMPs from pesticides and PPCPs are EDCs, OMPs from industrial chemicals appear as per- and poly-fluoroalkyl substances (PFAS) and are generally EDCs [12]. These OMPs are persistent, bioaccumulative, and toxic and are principally distinguished by their potential to interact with the endocrine system, subsequently disturbing hormonal balance and producing multiple health issues, such as reproductive, developmental, and behavioural disorders [13–15]. Consequently, they pose considerable ecological and health dangers due to their ecotoxicological risks and probable human toxicity. Supplementary material Table S1 presents the features of some of the most common OMP–EDCs and PFAS often found in water resources. As presented in Fig. 1, most OMPs gained entrance into water resources through various channels, such as effluent from wastewater treatment plants, domestic wastewater, industrial discharges, agricultural runoff, seep-ages from landfills, and faulty septic tanks, improper disposal of medications, manufacturing processes, and plastic waste degradation, making their presence in the environment widespread. Many OMPs are bioactive, therefore, ingesting any water polluted by them poses severe risks to human health even at low concentrations [16–17]. In addition to being endocrine disruptors, several OMPs are carcinogenic and facilitate the rapid development of antibiotic-resistant bacteria, particularly under prolonged exposures [18–19]. The potential ability of disease-causing bacteria to resist antibiotics is particularly problematic due to the negative impacts of such resistance on public health via ineffective medical treatments [20]. The carcinogenic effects of OMPs on human health are exacerbated by their potential fetotoxicity, neurological toxicity, and genotoxicity [21]. However, the stability of several OMPs against natural degradation is even more disturbing, as this raises regulatory challenges that now require proactive and flexible approaches to water quality standards and water treatments. Several countries and regional organizations have recently formulated and implemented directives and policies aimed at mitigating the potential health and environmental consequences of OMPs. These measures are mostly targeted at regulating the release of OMPs into natural water bodies and their presence in drinking water. The recently updated key regulations made on the Water Framework Directive 2000/60/EC by the European Union (EU) [22], China’s GB5749-2022 standard for drinking water quality and OMP control [23], as well as the German Government’s health-oriented guidance value for drinking water that sets a maximum allowable limit of 0.3 to 0.5 μg/L for OMPs [24], are all notable instances to this fact.
Removal of OMPs such as EDCs and PFAS via conventional water treatment techniques has been proven to be inadequate. For instance, the presence of strong carbon-fluorine bonds in PFAS makes them highly stable and resistant to biochemical degradation [25]. This has heightened recent research efforts involving the utilization of advanced water treatment techniques in removing EDCs and PFAS from water. The potential of advanced oxidation processes (AOPs) in destroying EDCs and PFAS in water has been extensively investigated. These processes generate strong oxidizing species, particularly hydroxyl radicals, using various methods such as photolysis, ozonation, Fenton or Fenton-Photo reactions, ultrasonication, electrochemical oxidation, persulfate oxidation, and their mechanisms, often in the presence of catalysts and/or radiation sources to achieve specific treatment objectives [7, 26]. However, AOPs are disadvantaged by high operational costs, originating from the purchase of reagents and energy utilization. Also, residues of the chemicals are sometimes detected in the treated effluent, and in certain instances, oxidation of the entire EDCs and PFAS is hardly accomplished, and disinfection byproducts such as aldehydes, ketones, and haloacetic acids are also created. Membrane technologies involving the use of microfiltration, ultrafiltration, nanofiltration, and reverse osmosis are another effective treatment system for removing various EDCs and PFAS. These systems operate continuously to eliminate these contaminants from water without producing any byproducts or metabolites due to their broad selectivity. Membrane processes can use different filter media, such as ceramics, polymers, and zeolites, to filter out high molecular weight solutes through hydrostatic pressure [27]. Research indicates that the efficiency of EDC removal by membranes largely depends on the physicochemical properties of the compounds, such as their molecular weight, hydrophobicity (log Kow), water solubility, and electrostatic characteristics [28]. However, membrane technologies tend to be more expensive than other water treatment technologies such as advanced oxidation, biodegradation, and adsorption. Biodegradation treatment options for removing EDCs can be broadly divided into three primary groups: aerobic, anaerobic, and mixed procedures, which correspond to biological activated carbon, sludge filtration, and biological filtration technologies [27], respectively. Aerobic processes mostly involve a combination of granular activated carbon (GAC) covered with biofilm to remove these chemicals via adsorption and microbial degradation mechanisms, adsorption in residual sludge, chemical or biological transformation/degradation, and volatilization [29]. Anaerobic reactions involve bacteria utilizing refractory compounds into smaller components in the absence of oxygen. The choice between aerobic and anaerobic activities lies on the electron-accepting circumstances of the receptor. The efficiency of these biological treatments is determined by the properties of the water which might vary based on geographic location and human activities. Various microorganisms have shown the ability to degrade the organic structures of EDCs, including non-ligninolytic fungi (Umbelopsis isabelina), yeasts (Candida rugopelliculosa), and bacteria (Sphingomonas spp., Stenotrophomonas spp., Virgibacillus halotolerans, Bacillus flexus, Bacillus licheniformis, Camelimonas spp., and Enterococcus faecalis) [27]. The bioremediation process under a biodegradation treatment system involving microalgae, as an agent, has been successfully utilized to remove parabens from water [30]. Other treatment systems such as electrochemical or electrocoagulation separation [31–32], and ion exchange [33] have been extensively investigated in removing different types of OMPs in water.
The use of adsorption technologies for removing diverse OMPs, including EDCs and PFAS from water has been thoroughly investigated [26–28]. Their versatility, cost-effectiveness, and ease of operation coupled with high efficiency, have placed adsorption as the most preferred treatment technique for removing these contaminants from water [34–35]. However, the performance of the adsorption process in removing these compounds from water depends on several factors, such as the adsorbent characteristics, the pollutant properties, and the adsorption conditions [36–38]. Effective removal of EDCs and PFAS from water via the adsorption process requires the optimization of these variables due to the complex interactions that mostly exist between the three factors. Modelling adsorption processes may enhance the conception, design, and operation of adsorption systems for effective removal of EDCs and PFAS from water, while ensuring improved performance and cost-effectiveness. It may also assist in designing and testing novel adsorbents. By predicting the performance of new materials under diverse conditions, such adsorbents may be customized to target particular pollutants more effectively. However, predicting the behaviour and interactions of EDCs and PFAS with any adsorbent is problematic due to their structural and chemical stabilities [39]. Besides, diverse adsorbents, such as activated carbons, metal-organic framework (MOFs), and other novel materials may demonstrate variable affinities for EDCs and PFAS, with the prospect of such variability contradicting the generality of adsorption models [40]. Environmental variables such as pH, temperature, and the existence of competing natural organic matter (NOM) typically add another substantial layer of complexity that could affect the adsorption capacity and efficiency, which might in turn impact the modelling efforts. Obtaining precise kinetic and equilibrium data is crucial for modelling but may be hard due to the slow adsorption rates and low concentrations of EDCs and PFAS in water. Existing conventional modelling approach may not fully capture the slow and usually nonlinear adsorption rates found with these contaminants. Comprehensive information is scarce on the adsorption of EDCs and PFAS, which makes it difficult to design and assess trustworthy models. Much research works have been done with focus on certain compounds or situations and hence is limited in the applicability of the resulting models to bigger scenarios. A robust understanding of the desorption processes and the regeneration of adsorbents is crucial for developing sustainable adsorption systems, and modelling these processes involves knowledge of the interaction mechanisms between EDCs or PFAS and adsorbents, which often have limitations [39]. Despite several research efforts over the years to maximize the impacts of these components on EDCs or PFAS removal from the water via adsorption processes, there exists a notable lack of comprehensive information regarding the extent of progress in each area. This paper aims to investigate the various advances in adsorption modelling, mechanisms, types of adsorbents, and their characteristics that influence EDCs or PFAS removal from water and wastewater. The critical roles adsorbent characteristics play in influencing EDCs or PFAS adsorption are examined, based on valuable insights provided by researchers and practitioners in the water engineering sector.
Basic Adsorption Principles
2.1. Adsorption Equilibrium and Natural Organic Matter Effects
Adsorption generally involves the mass transfer between different phases, including from gas to liquid, liquid to liquid, gas to solid, and liquid to solid interface [41]. The application of the adsorption process for water treatment is, however, a surface-based phenomenon wherein ions or molecules (known as the adsorbates) are attracted and adhered to the surface of a solid material, typically referred to as the adsorbent [42–44]. The reverse process of detachment of the adsorbate from the adsorbent is known as desorption [45]. The critical state in which the rates of adsorption and desorption of the adsorbate onto and from the adsorbent surface reach a balance is known as the adsorption equilibrium [46]. At the equilibrium state, the adsorbate concentration in the liquid phase and the amount adsorbed onto the adsorbent surface remain constant over time at given environmental conditions, such as temperature, pH, ionic strength, and pressure. Adsorption is an efficient treatment system that can eliminate a wide range of pollutants from water onto any suitable adsorbent materials. It is a versatile, simple, cost-effective, and efficient technique for removing diverse pollutants [34–35]. It can be operated as either a standalone or pretreatment technology, capable of controlling flux in hybrid adsorption-membrane systems [47]. Adsorption, being widely selective, can be tailored to remove diverse pollutants based on their physicochemical features and adsorbent characteristics [35]. However, adsorbents used for the adsorption process may be expensive; optimization strategies may therefore be necessary for removing certain pollutants from the water or wastewater.
The two adsorption modes by which OMPs are removed from water or wastewater include batch and column adsorption systems. While batch adsorption mode employs a closed small-scale system that combines an adsorbent with OMP-laden water to explore equilibrium conditions [48–49], column adsorption mode mimics continuous flow scenarios of passing OMP-laden water through a column containing adsorbent material to yield breakthrough curves and dynamic data of adsorption performance [50–51]. Both adsorption modes exhibit varying degrees of complex dynamic interactions between their operating parameters. Batch equilibrium tests, for instance, are mostly used as a scaled-down version of dynamic column batch reactor [52], while rapid small-scale column test (RSSCT) comes into play when a full column adsorption process is impractical [53–54]. Scaling up adsorption performance from RSSCTs to full fixed-bed columns involves assessing adsorption capacity and kinetics for OMPs. Mass transfer models are built based on RSSCT data to predict full-scale performance, accounting for difficulties like adsorbent clogging [55]. Robust models and pilot testing are used to lessen the dangers of variations in water quality on the adsorption performance [56]. RSSCT investigates adsorption kinetics, equilibrium, and breakthrough curves, optimizing process parameters like contact time, flow rates, and bed heights [55]. A suitable modelling approach is applied to generalize results and solve hydraulic difficulties. Operating parameters are tweaked, and a reliable monitoring system is built with adequate considerations taken to ensure economic feasibility, and environmental compliance, and to overcome the potential challenges relating to attrition, leaching, or structural changes that could affect the compatibility and stability of adsorbent in larger fixed-bed column system [55]. For each adsorption mode, different adsorbent utilization strategies have been explored by several researchers to investigate OMP removal from water or wastewater. In a differential column batch reactor, for instance, discrete batches of adsorbents are sequentially introduced into the reactor [49, 57], creating a non-continuous process. The adsorption progresses over time within this closed system. In continuous column adsorption mode, however, various adsorbent utilization arrangements, such as fixed bed (or packed bed), pulsed bed, fluidized bed, and moving bed [50], along with several wastewater flow-through types, namely downflow [55], up-flow [58], continuous-flow [59], and crossflow [60] across the adsorbent in the column, have been extensively used for OMP removal.
Mass transfer processes, including external mass transfer (involving film diffusion and surface diffusion), internal mass transfer (or pore diffusion), interparticle mass transfer, interphase mass transfer, and chemical reaction (or surface diffusion), are actively involved in both adsorption modes [61–63]. An illustration of these processes is shown in Fig. 2. RSSCT uses Proportional Diffusivity (PD) and Constant Diffusivity (CD) design approximation to relate the effects of adsorbent particle size on intraparticle diffusion kinetics on OMP removal via adsorption processes [64].
The performance of any adsorption system in removing OMPs from water may depend on the inherent pollutant load including the presence of natural organic matter (NOM). While the types and concentrations of OMPs in wastewaters from any industrial processes are often few [65], different OMPs including competitive natural NOM measured as dissolved organic carbon (DOC) are contained in most water samples from water resources [66]. The impact of NOM on OMP adsorption from water is complex, and diverse, and depends on several factors that lead to varying results. The competition for adsorption sites between NOM and OMPs depends on their composition and concentration in the water or wastewater. This competition may result in blockage of adsorbent pores, as established by recent studies [51, 67–68]. Consequently, this situation restricts the mass transfer of OMPs onto the adsorbent surface and may hamper OMP diffusion into adsorbent pores [69]. This might impair the efficiency of OMP removal. Moreover, electrostatic interactions between positively or negatively charged OMPs and the adsorbents undergo extensive alterations in the presence of NOM, resulting in different influences on adsorption performance. In a specific wastewater environment, for instance, the adsorption of negatively charged OMPs is reduced. This decrease was due to the repulsive electrostatic interaction between NOM and the negatively charged powdered activated carbon (PAC) [68]. Conversely, the adsorption of positively charged OMPs onto the adsorbent was reported to have improved [68]. Under some conditions, such as combining adsorption and flocculation procedures [69], NOM removal and OMP adsorption from water are boosted. Specific interactions or synergies between NOM and OMPs might increase overall adsorption efficiency. The NOM tends to form complexes or induce precipitation with OMPs [70], presumably helping their removal via complexation or precipitation processes. In the presence of NOM, adsorbent regeneration was favourably increased [71]. Given the intricate interplays generated by NOM presence in water or wastewater, the development of adsorption processes for efficient OMP removal by the adsorbent becomes crucial.
2.2. Adsorption Isotherm Models
Adsorption isotherms describe the relationship between the concentration of adsorbate in the solution and its amount adsorbed onto the adsorbent surface at the state of equilibrium [72–74]. The determination of adsorbent’s adsorption capacity for OMP and the removal efficiencies during an adsorption process is based on the concept of adsorption equilibrium and information obtained from the adsorption isotherms [75]. The effectiveness of adsorption isotherms in describing adsorption processes for water treatment depends on the number of targeted OMPs present and the adsorption modes used. Such a description is robustly understood via modelling approaches. Various empirical, thermodynamic, multilinear regression (MLR), and mass transfer rate-controlling diffusion models can be applied for robust analysis of OMP adsorption performance for different adsorbents for water and wastewater treatment, depending on the adsorption mode and properties of the OMP present.
2.2.1. Batch adsorption isotherm models
Batch adsorption isotherm models for single-solute, such as the Langmuir, Freundlich, Temkin, Sips, Dubinin-Radushkevich, Brunauer-Emmett-Teller (BET), Redlich-Peterson, Toth, Modified Langmuir-Freundlich models [45, 76–77], etc., have shown importance in evaluating the adsorption capacities and affinities of specific OMPs towards different adsorbents. These models provide essential information on the mechanisms governing the adsorption process, as well as aid the selection and design of adsorbents for optimal removal efficiency. However, for multisolute batch adsorption process, isotherm models such as the extended Toth [78], extended Redlich–Peterson, extended Langmuir, extended Freundlich, extended Langmuir-Freundlich models [79–80], containing additional mixture of adsorption parameters are determined by competitive adsorption experiments. The batch multisolute adsorption models are predominantly considered ideal and are more reliably superior to single-solute batch models. This is attributed to the complex nature of real-world water and wastewater, which often contain a variety of OMPs and other pollutants [81]. However, analyzing the data obtained from the competitive adsorption experiments for multisolute settings can mostly only provide a mathematical description of the adsorption profiles, whereas a predictive description of the adsorption process is mostly preferred under such circumstances. Moreover, most of these models are only effective when restricted to bisolute adsorption process [82]. A few thermodynamic models, however, exist that accommodate the varying presence of different pollutants and other species to predict the behaviour of multisolute adsorption. The ideal adsorbed solution theory (IAST) [83–84], the vacancy solution theory (VST), and the potential theory for multi-solute adsorption are three such models that characterize the competitive adsorption behaviour of various OMPs onto the adsorbents [85–86]. While IAST postulates an ideal adsorbed phase that offers useful insights into the non-ideality of the adsorption isotherm, VST considers adsorption as filling vacancies in the adsorbent structure to enhance adsorption accuracy. Among these classical predictive thermodynamic models, the IAST has been the most successful and widely used for the predictive modelling of the adsorption of bisolute or multisolute. The most attractive feature of the IAST is that it can predict the adsorption of bisolute mixtures relying solely on single-solute adsorption isotherm, which allows it to be used for several studies [87]. Generally, IAST achieves good predictions for bisolute aqueous adsorption when the adsorbates behave ideally [88]. An ideal behaviour here generally implies that each of the adsorbates in the adsorbed phase behaves independently of the presence of the other adsorbates. This implies that there are considerable interactions between the molecules of the adsorbates in the adsorbed phase that are ignored in the model [89]. However, the IAST has shown very high deviations when bisolute mixture behaves non-ideally. For example, IAST achieves accurate predictions of adsorption capacities of three binary mixtures of nitrobenzene, aniline, and phenol adsorption onto granular activated carbon (GAC), but when the initial concentrations of the adsorbates increased, these bisolute mixtures behaviour become non-ideal in nature [87]. These prediction deviations or the non-ideal behaviour of the adsorbates are largely due to lateral interactions between the solutes that are induced by the heterogeneous properties of the adsorbent causing its different affinity towards various adsorbates [87]. To reduce the high deviation scenarios associated with IAST, an activity coefficient can be introduced into it, as a correcting factor to account for the non-ideality, and the resulting model is referred to as real adsorbed solution theory (RAST) [87]. The activity coefficient can be calculated from bisolute experimental data and then correlated with the fractions of the adsorbates in the adsorbed phase by models such as the Wilson equation Eq. (1) [87]. The correlations obtained can then be used by RAST to predict bisolute adsorption. However, RAST requires bisolute adsorption data to calculate the activity coefficient, which means that RAST cannot predict bisolute adsorption only based on single-solute adsorption data like IAST does [87]. The fitting models for activity coefficient also need experimental data of bisolute adsorption such as the adsorbed amounts [87]. These limitations have greatly restricted the applicability of RAST. So, RAST is often employed in retrospective modelling rather than predictive modelling. Table 1 shows details of the features of these models and other most used aqueous-based single-solute and multisolute isotherm models for batch adsorption systems.
where Δ12 and Δ21 are the adjustable parameters of the model and xi are the predictor variables.
Most recently, researchers have been using the MLR approach to identify adsorbent materials with high adsorption capacities for the rapid removal of OMPs using computational modelling and molecular or structural simulation approaches [90]. Analytical calculation via density functional theory (DFT) is dominating computational modelling of adsorption performances of adsorbent materials for OMP removal from aqueous systems, but molecular dynamics and Monte Carlo simulations are also gaining prominence. This modelling approach is based on the principle of MLR analysis to facilitate the design of adsorption experiments by quickly estimating the adsorbed amount of different OMPs onto a given adsorbent.
The adsorbed amount (Qe) under an equilibrium concentration (Ce) is essentially a function of three key sets of properties: the properties of the OMP, the properties of the adsorbent, and the equilibrium concentration (Ce) of the OMP, which is also dependent on other factors [99]. The two most used models for predicting the aqueous adsorption of OMPs based on this principle include the Quantitative Structure-Activity Relationships (QSARs) and the polyparameter linear free energy relationships (pp-LFERs). While QSARs correlate molecular features of both adsorbate and adsorbent to provide useful insights about their predictive adsorption performance, pp-LFERs consider multiple parameters that enable a comprehensive understanding of adsorption mechanisms. In using the QSARs, OMPs distribution coefficients (Kd, L/g), which represent the dependent variable, are computed using Eq. (2), and data is determined either experimentally or computationally. A comprehensive suite of QSAR descriptors such as those delineating hydrogen bonding as independent predictor variables can be generated computationally using packages like Dragon 7 [100–101].
where Qe, (mg/g) is the adsorbed amount of OMPs on the adsorbent surface and Ce, (mg/L) is the average concentration of the pollutant in the liquid phase at equilibrium. The Log10Kd values could be predicted based on the addictive principle and a linear combination of transformed and untransformed predictor variables using Eq. (3).
where βi are the parameters of the model and xi are the predictor variables.
QSAR offers a systematic molecular modelling technique that is useful for predicting and analyzing OMPs adsorption isotherms [100, 102]. One of the core usefulness of the QSAR modelling technique is that it can offer preliminary assessment results before real experiments are performed. However, capturing the complex nature of adsorption isotherms demands advanced mathematical methodologies and careful selection of chemical descriptors [103]. Correct estimation of model parameters is critical for calibration and validation, and ambiguity in these parameters might affect the prediction performance. QSAR models created for certain classes of OMPs may lack relevance when applied to various other substances. To enhance applicability, retaining diversity in the training dataset is key. Combining QSAR models with kinetic and thermodynamic models may give a more detailed understanding of adsorption processes [104]. In general, QSAR modelling is a good technique for analyzing batch system of OMP adsorption uptake on any adsorbent, but the uptake adsorption must first be numerically expressed as adsorption affinity by computing a linear slope adsorption amount and the final concentration of the OMP [103]. It often predicts the adsorption capacities based on the molecular characteristics of the adsorbate rather than the adsorbent. Experimental data from batch adsorption research is used to calibrate and validate QSAR models, combining chemical properties with adsorption performance. However, utilizing QSAR directly for fixed bed column system is still challenging. QSAR models may be developed using batch adsorption data, changed, or widened using column adsorption data, and verified against independent batch adsorption data to assess the adsorption performance under continuous column adsorption system [100]. The models created for batch systems may need revisions to account for continuous column adsorption systems. To adapt, the models may incorporate kinetics and mass transfer factors, including time-dependent descriptors and parameters. This approach is yet to be thoroughly investigated in the literature.
In the pp-LFERs approach, MLR is established between logKd and the Abraham descriptors (E, S, A, B, and V) of different OMP under a selected equilibrium concentration level Ce as in Eq. (4) [105].
where the equilibrium concentration level Ce is equal to a fraction of an OMP’s water solubility (Sw), e, s, a, b, v, and c are the fitting parameters, and log Kd (Ce) is the adsorption coefficient of a pollutant under a given Ce. The Abraham descriptors E, S, A, B, and V can capture nonspecific interactions arising from induced dipoles, stable polarity, (i.e., dipole-dipole interactions), the overall H-bonding acidity and basicity (electron-accepting and donating capacities), and cavitation energy and part of London dispersive forces beyond what is captured by the E term, respectively.
2.2.2. Column adsorption breakthrough models
Adsorption isotherms and breakthrough curves are crucial tools for understanding the dynamic behaviour of adsorption processes in fixed bed column systems. Isotherms give a depiction of equilibrium adsorption at varying concentrations, while breakthrough curves indicate equilibrium achieved under continuous flow [106]. Both are influenced by the adsorbent’s properties, such as surface area, pore structure, and chemistry. Isotherms are created under batch settings, while breakthrough curves are formed under continuous flow column adsorption, demonstrating the temporal evolution of effluent concentration [58]. Besides, breakthrough curves illustrate the temporal aspect of adsorption, indicating how effluent concentration fluctuates over time, unlike isotherms, which are equilibrium-focused. In the context of continuous column adsorption systems for single-solute scenarios, a distinct set of models, including the Bohart–Adams, Clark model, Thomas model, Wolborska model, Yan model, and Yoon-Nelson model, are usually employed to assess the adsorption behaviour, which is represented as breakthrough curves [107–108] (refer to Table 2). For adsorption of multiple OMPs in a fixed-bed column system, however, description of the adsorption performance requires the application of complex numerical mathematical equations. This complexity arises due to the intricate interactions among various adsorbates in such settings. The models often involve competitive adsorption theories and complex equilibrium expressions. Researchers have lately focused on extending existing models to account for co-adsorption, competitive interactions, and the influence of one OMP on the adsorption behaviour of others [109]. This insight is crucial in predicting OMP removal under actual settings and optimizing treatment techniques for wastewater [98]. Such multisolute adsorption models lead to a more accurate understanding of the competitive behaviour of OMPs in real-world water and wastewater and they are best analyzed via advanced computational modelling packages.
Adsorption Design Software for Windows (AdDesignSTM) and FAST2.1beta are advanced modelling packages used for simulating breakthrough curves for fixed-bed column adsorption of single-solute and multisolute in water. AdDesignSTM is openly available through the US Environmental Protection Agency, and it incorporates three models: Equilibrium Column Model (ECM), Constant Pattern Homogeneous Surface Diffusion Model (CPHSDM), and the Pore and Surface Diffusion Model (PSDM) [110]. These models help researchers tailor system parameters for optimal adsorption performance [111]. However, AdDesignSTM solely presents adsorption equilibrium based on the Freundlich equation for single adsorbate adsorption and represents competitive adsorption between OMPs based on IAST isotherm, potentially undermining its prediction accuracy compared to other superior isotherm models. This could lead to significant deviations between predictive results and experimental data for different OMPs and adsorbent materials. In addition, only about 300 types of OMPs and 15 types of porous carbon currently exist in the database of the software from which OMP adsorption simulation studies can be conducted. But advances in analytical technologies is rapidly helping the detection of new OMPs in water resources [112–113], and novel adsorbents such as green adsorbents, mineral adsorbents, and nanomaterials, mostly suited for OMP removal from water, are yet to be integrated into this database.
Furthermore, the model is insensitive to coexisting contaminants and varying water constituents and this could impact prediction accuracy under real-world adsorption scenarios. For instance, in a study to predict both pilot and full-scale removal of PFAS using PSDM by Burkhardt et al. [116], notable distinctions were observed in the expected performance of the adsorption process during two seasons in the pilot phase, utilizing the same GAC. Surprisingly, these variations were not accounted for in the uncertainty analysis of the model results. The observed dissimilarities are likely linked to the seasonal fluctuations in water constituents. While simulation packages exist for OMP adsorption in fixed bed columns, the means to achieving accurate and robust simulations for both pilot and full-scale adsorbers remain elusive to researchers. The fouling of adsorbent pores by NOM during the adsorption process introduces a layer of complexity, nonlinearity, and time-sensitivity to the simulation scenario that current PSDM cannot adequately address [51].
The Homogeneous Surface Diffusion Model (HSDM) is a vital package that aids robust understanding of surface diffusion dynamics, as it provides insights into adsorption kinetics for optimizing processes and predicting breakthrough curves in water treatment. It is particularly useful in simulating OMP adsorption in fixed bed column systems. The FAST2.1beta software, which incorporates HSDM, allows researchers to predict and analyze performance under diverse conditions, optimizing critical parameters like flow rates and adsorbent characteristics [117]. Such simulation results aid in designing and evaluating adsorption processes by identifying optimal adsorbents and operational parameters for efficient OMP removal [118]. The simulation approach minimizes costs by reducing the need for extensive experimental trials and allowing for the virtual assessment of multiple scenarios [119]. However, the reliance of HSDM on surface diffusion uniformity limits its ability to capture the complexity of OMP adsorption processes and its performance across diverse OMP types.
2.3. Adsorption Kinetic Models
The adsorption kinetics describes the time dependence of the adsorption process, which implies the increasing loading of the adsorbent surfaces over time or the decreasing concentration of the adsorbates in the liquid phase with time [120]. The adsorption rate primarily results from slow mass transfer mechanisms occurring between the liquid and solid interphase. In continuous column adsorption, where the process is intricately linked to both temporal factors and temperature variations, the adsorption rate is denoted as adsorption dynamics [121]. In general, adsorption equilibrium is a precondition for applying both kinetic and dynamic adsorption models [120]. This adsorption kinetics is not only valid for single-solute and multisolute batch adsorption systems but also for continuous column adsorption systems, which is characterized by adsorbates’ competition for the available adsorption sites in fixed-bed adsorbers by displacement process [93]. The pore diffusion phenomenon associated with batch and column adsorption processes is a critical phase in the process and is often depicted as the intraparticle diffusion that transfers the OMP molecules from the bulk solution into the interior of the adsorbent pores [114, 122]. This process is controlled by the concentration gradient between the solution and the adsorbent surface [120]. The rate of intraparticle diffusion is regulated by parameters such as particle size, pore structure, and surface area of the adsorbent [123]. Large surface areas and well-defined pore structures allow faster intraparticle diffusion, resulting in speedier adsorption kinetics [124]. Prior to intraparticle diffusion, OMP molecules must first move across the border layer enclosing the adsorbent particles, known as the film diffusion zone [114]. The thickness of this boundary layer, which is determined by factors like agitation rate and flow conditions, impacts the rate of mass transfer between the solution and the adsorbent surface [125]. High agitation rates and turbulent flow conditions can reduce the thickness of the boundary layer, which can help to improve film diffusion rates and overall adsorption kinetics [126].
For slurry adsorbers or breakthrough behaviour in fixed-bed columns, equilibrium relationships, obtained from data of adsorption breakthrough curve are essential component for modelling description of adsorption kinetics. However, existing models are complex and usually require numerical or mathematical approach to arrive at their solutions, especially for designing and optimizing continuous adsorption in fixed-bed columns. But such a model is particularly necessary because the effluent/inlet concentration (C/Co) profile for a given adsorbate in the liquid phase under all conditions inside the column can be determined by the verified models. Some OMPs may form chemical complexes or undergo interactions with functional groups on the adsorbent surface [127]. The kinetics of these chemical interactions influence the entire adsorption process [128]. Faster response rates contribute to faster OMP uptake, while slower reaction kinetics may lengthen the time required to attain equilibrium [129]. In cases where adsorption is taking place in fixed-bed columns or other flow-through systems, external mass transfer becomes a significant element [35]. The rate at which pollutant can be carried from the bulk solution to the adsorbent surface is determined by factors like flow velocity, column design, and packing density [108, 115]. Efficient design considerations can enhance external mass transfer that can boost overall adsorption performance.
The kinetics of desorption or the process of eliminating adsorbed pollutants from the adsorbent surface is critical for regenerating and reusing the adsorbent material [130]. Rapid desorption kinetics can facilitate the regeneration process, which can allow the adsorbent to be successfully reused in subsequent treatment cycles [131–132]. In complex water matrices, numerous OMPs may compete for adsorption sites on the adsorbent surface. The kinetics of these competing interactions are critical for predicting and enhancing overall OMP removal effectiveness [129]. Overall, addressing the kinetics of adsorption is necessary for rapid and effective removal of OMPs from water and wastewater and enables the design of more efficient and cost-effective water treatment methods. However, the prediction of multisolute adsorption behaviour from single-solute data is an additional challenge in practice-oriented adsorption modelling [93]. Table 3 summarizes details of the linear and non-linear models mostly used for describing the adsorption kinetic for both batch and continuous column adsorption systems.
Adsorption Mechanisms for OMP Removal
The adsorption mechanism refers to the nature of interactive forces between the adsorbent surface and the adsorbed molecules [133]. Depending on the nature of interactive forces binding the adsorbates onto the adsorbent, adsorption processes are broadly categorized into two types–physisorption and chemisorption [45]. When weak physical interactive forces are heavily involved in binding adsorbates onto the adsorbent surfaces, physisorption is said to be dominant; in which case, the adsorption process is reversible [134]. Examples of such weak interactive forces are the van der Waals forces (including London dispersion forces, dipole-dipole interactions, π-π interactions) and electrostatic interactions [134]. Electrostatic interactions occur when there is a charge differential between the adsorbate and adsorbent. The principal electrostatic forces include coulombic attraction or repulsion forces between charged functional groups on the adsorbent surface and the charged or polar groups of the OMP molecules [72]. For instance, several ionic or polar OMPs generally contain polar functional groups like amines, carboxylates, or sulfonates, which can interact with oppositely charged sites on the adsorbent surface through electrostatic attractions [135]. These interactions can lead to the adsorption of polar OMPs onto surfaces containing charged sites [70], such as activated carbon, zeolites, or ion-exchange resins. The electrostatic interaction mechanism is particularly crucial when dealing with OMPs that possess considerable charge or polarity [136], such as pharmaceuticals. Generally, the long-range attractive forces involved in physisorption are often non-specific and arise from momentary dipoles induced by polarization in atoms or molecules. The energy changes involved between these forces are relatively low, usually between 2–20 kJ/mol [137], which indicates a reversible process. The low activation energy also means that physisorption occurs quickly at relatively low temperatures. An increase in temperature generally leads to desorption due to the weakening of the interactive forces.
The adsorbent surface does not need to possess specific chemical functionalities before multilayer adsorption can take place, since the process is not limited by the formation of bonds at the surface of the adsorbent. Physisorption allows the reversible attachment of mostly non-polar or weak polar OMPs. Other physisorption mechanisms (Fig. 3), including pore-filling, surface complexation, ion exchange, partition, and co-precipitation are also of critical significance in the adsorption of OMPs from the aqueous system [141].
On the other hand, chemisorption refers to the strong attractive covalent or ionic bonds between the adsorbate and the adsorbent surface. These bonds allow the adsorption of OMP to occur only on a single layer of the adsorbent, thus making it appropriate for applications where contaminant desorption is not desirable [133, 142]. The interaction forces induced by the bonds between the adsorbate and the adsorbent surfaces are specific and often involve significant energy changes, typically around 40–400 kJ/mol [143]. The activation energies in chemisorption are also higher, which can result in slower adsorption kinetics, and are dependent on higher temperatures that are necessary for generating the energy required for overcoming any activation barriers and for forming strong chemical bonds [144]. Chemisorption is maximized by increasing the surface functionality of adsorbents, and this can be regulated by changing pH conditions to promote chemical interactions and designing adsorbents to target specific OMPs [145]. Chemisorption is highly specific, depending on the chemical compatibility between the adsorbent and the adsorbate. Specific functional groups on the adsorbent surface play a critical role in the adsorption process. It typically results in monolayer adsorption due to the limited availability of specific binding sites on the adsorbent surface. For instance, functionalized polymers, such as those modified with Fe3O4@3-phenylglutaric acid, have been reported to enhance the removal efficiency for specific pharmaceuticals through chemisorption mechanisms [146]. The covalent bond is the dominant binding force involved in the sharing of electron pairs between the adsorbate and adsorbent. For instance, recent studies indicate that hydrophobic interactions induced by covalent bonds favour the adsorption of hydrophobic perfluorooctanoic acid (PFOA) onto covalent organic frameworks with oxygen-containing functional groups on the surface of the PFAS [33, 147].
Ion exchange mechanisms are also involved in the exchange of ions between the adsorbent and the solution. Zeolites, for instance, exhibit ion exchange properties that allow for the selective adsorption of specific OMPs from wastewater [149–150]. Hydrogen bonding is significant in cases where polar adsorbates interact with functional groups on the adsorbent surface. Silica-based adsorbents often utilize hydrogen bonding to capture OMPs like pharmaceuticals from aqueous solutions [26]. The presence of various oxygen-containing groups on graphene oxide (GO) has been adjudged to enable strong chemisorptive interactions with OMPs to enhance their removal capacity [151]. In general, chemisorption is particularly effective for the adsorption of ionic and highly polar or charged OMPs, such as pesticides and certain pharmaceuticals via covalent or ionic bonding [152–153].
Generally, the type of dominating mechanism in any adsorption process can be indicated by the adsorption kinetics and thermodynamic variables such as enthalpy. For instance, a perfectly described adsorption by the pseudo-second-order kinetics reflects the dominance of the chemisorption process [154], while physisorption is reflected by pseudo-first-order kinetics.
Concerning enthalpy, however, Liang et al., [152] declared that enthalpy measurements within the range of 5 kJ/mol<ΔH<10 kJ/mol and 10kJ/mol<ΔH<30kJ/mol indicates that physisorption and chemisorption mechanisms are the rate-controlling order of sharing or trading of available functional groups or molecules between the adsorbent and the adsorbate, respectively. Moreover, the type or composition of OMP in the aqueous system influences its rate-regulating mechanism too. For instance, while tetracycline is removed from biochar via chemisorption [155], removals of atenolol, carbamazepine, ciprofloxacin, diclofenac, gemfibrozil, and ibuprofen onto different nanomaterials follow physisorption process [156]. Furthermore, if favourable conditions are provided, several types of adsorption mechanisms can occur simultaneously in any OMP-laden water system. For instance, Chen et al., [157] reported that even though adsorption of carbamazepine on Zirconium metal-organic framework–UiO-66 was majorly by physisorption, hydrophobic effect, π–π weak electron donor-acceptor interactions and electrostatic interactions also played a useful role in the adsorption process. They further reported that the adsorption of tetracycline hydrochloride on the UiO-66 was majorly by chemisorption, but strong electrostatic attraction and π–π electron donor-acceptor interaction forces, all contributed to helping the inherent nitrogenous groups in tetracycline hydrochloride to replace the carboxylic groups during the formation of the Zr-O clusters. The efficiency of adsorbents like activated carbon is influenced by the adsorption mechanisms applied and a wide spectrum of OMPs, including pharmaceuticals [158–160], EDCs [161], and other organic pollutants [162], have been effectively removed from aqueous systems via different adsorption mechanisms by activated carbon-based adsorption processes.
Advances in Adsorbent Materials for OMP Adsorption
4.1. Natural Adsorbents
The adsorption of OMPs into several types of adsorbents has been extensively investigated. In general, the type or composition of the adsorbent utilized influences the degree of adsorption performance in removing OMP by the adsorbent. Based on advances in production technologies and a continual quest to overcome the limitations of others, the adsorbents utilized for the adsorption of different types of OMPs in aqueous systems can be categorized into four major groups, namely green adsorbents, mineral adsorbents, porous carbon materials, and nanomaterials. The green adsorbents include biomaterials (e.g., biosorbents, agrowastes, algae and macrophytes, peat and humic substances) and mineral adsorbents include zeolites, chitosans, resins, clays, and modified clays (see supplementary material Fig. S1). Different kinds of OMPs have been successfully adsorbed from aqueous solution onto unmodified biomaterials like seaweeds [163], yeast [103], algae, and fruit waste-based biosorbents [164–165]. The adsorptive abilities of these biomaterials are mostly influenced by their inherent organic fraction and the type of functional groups available on their surfaces. For instance, the hydroxyl, ketones, and ethers functional groups present at the surface of a fruit waste-based biosorbent were reported to enhance its attractive forces that bind OMPs onto their surfaces, thereby enhancing their removal efficiency from an aqueous system [164].
Furthermore, the potential adsorptive abilities of several raw agrowastes materials, such as rice husks, sawdust, Argan nuts, etc., for removing OMPs from aqueous systems have been studied [166–167]. Cellulosic polymers have also been synthesized from agrowastes as adsorbents for OMP removal from water [168]. Generally, green adsorbents are only viable and effective in removing low concentrations of OMPs in any water or wastewater than those present in the water at high concentrations. Despite the high economic benefits of utilizing agrowastes as adsorbents for OMP removal, however, their low adsorption capacities, weak physical stability, and non-regenerative potential have limited their large-scale application for OMP removal via water treatment. In addition, subjecting them to surface modification and functionalization processes may enhance their adsorption capacities but such processes are also highly expensive [167].
Zeolites are crystalline aluminosilicate minerals with well-defined porous structures. Their unique features, such as vast availability, high surface area (exceeding 700 m2/g), organized pore structure, high thermal stability, and large cation-exchange capacity [169–170], make them adaptable and efficient in several adsorption and catalytic processes. Zeolites are formed of a three-dimensional network of tetrahedrally-coupled aluminum and silicon atoms [171–172], resulting in a regular pattern of pores and channels that may selectively accommodate various-sized molecules [173]. One of the primary advantages of the large ion exchange capacity of zeolites is that it allows for the substitution of cations inside the zeolite framework. This characteristic is particularly essential for the adsorption of charged OMPs, as zeolites may selectively remove ions or molecules based on their charge and size [174]. Moreover, the organized pore structure of zeolites provides accurate size exclusion [175], making them suitable for removing OMPs with molecular dimensions [169, 176–177]. The hydrophilic and hydrophobic characteristics of zeolites can be adjusted through modification procedures [178], thereby allowing for increased adsorption of both polar and non-polar OMPs [179]. Surface modification with additional functional groups or the introduction of metal ions can further boost zeolite adsorption capacity and selectivity. Such alterations allow for tailoring of its framework to target specific contaminants in aqueous systems, making zeolites a versatile option for water treatment applications. Furthermore, zeolites have been applied in a range of water treatment scenarios, including point-of-use and point-of-entry systems, as well as in larger-scale municipal wastewater treatment plants for removing different OMPs [35, 180–181]. Their stability, renewability, and compatibility with existing treatment procedures make zeolites a realistic alternative for integrated water treatment techniques. Nevertheless, zeolites can lose their adsorption capacities over time, requiring regeneration. However, achieving regeneration without compromising zeolite integrity is challenging [182]. Their selectivity for specific OMPs may vary, making broad-spectrum selectivity difficult [177]. The hydrophobic nature of Zeolites allows them to adsorb hydrophobic OMPs, but this can also reduce their adsorption efficiency for polar OMPs. Mass transfer limitations in fixed-bed column systems can hinder zeolite adsorption performance, and achieving rapid adsorption kinetics for dynamic water treatment scenarios is also challenging [183].
Chitosan is another mineral adsorbent that has been explored for OMP removal from water and wastewater; it is a biopolymer extracted from chitin present in crustaceans and insects. Notably, chitosans exhibit positive charges, possess extensive surface areas, feature multiple functional groups, and demonstrate biodegradability [184]. These inherent characteristics render chitosans appealing as adsorbents for various adsorption techniques due to their eco-friendly nature. Chitosans exhibit non-toxic properties and have demonstrated effectiveness in eliminating diverse OMPs, including pharmaceuticals and insecticides [185]. Their inherent versatility, cost-effectiveness, and ready availability render them indispensable for the implementation of sustainable water treatment strategies. Nevertheless, chitosans, when employed as adsorbents, face limitations, with their pronounced sensitivity to pH levels and selectivity towards specific classes of OMPs. These constraints pose discouraging aspects, as they contribute to significant variations in the adsorption effectiveness of chitosans under distinct pH conditions [186].
Clays and modified clays have also been studied for the adsorption of OMPs in water and wastewater [187–189]. Natural clays like montmorillonite, kaolinite, and bentonites have layered structures and oxidic, and large surface areas that are particularly important for binding ionic OMPs onto their surfaces. They are also cost-effective and readily available, which suites them for large-scale water treatments. To enhance their adsorption capabilities, clays can undergo various modifications, such as ion exchange, organic or inorganic insertion, and surface functionalization [187]. These modifications increase the surface area, porosity, and charge density of clay that can in turn improve its adsorption performance. Different modifications can target specific OMPs, such as cationic surfactant-modified clays for anionic OMPs and metal oxide-decorated clays for surface complexation [190–191]. Modified clays can be tailored to manage a wide range of OMPs and can be integrated into existing water treatment systems [192]. This is because unmodified natural clays are largely hydrophilic, which makes them inefficient in adsorbing hydrophobic OMP-like pharmaceuticals [188].
4.2. Porous Carbon Adsorbents
Porous carbons include activated carbons, biochars, and hydrochars. Activated carbon (AC) is the most extensively researched adsorbent for removing pollutants from water and wastewater because of its high adsorption capacity and adaptability. It is characterized by a high surface area and a porous structure, both of which are critical for its adsorption effectiveness. The porosity provides abundant active sites for OMP molecules to adhere to, while the wide surface area promotes the interface between the adsorbate and the adsorbent [193]; this leads to efficient removal of pollutants via adsorption processes. Activated carbons are mostly synthesized via pyrolytic processes by physical activation method involving carbonization and activation in two steps, or chemical activation method involving the transformation of biomass cellulose structures into carbonaceous material through simultaneous dehydration and carbonization by high oxidizing acid, base, or salt [194], or by combined physical and chemical activation methods, and/or by microwave-assisted activation method [195–197]. The selection and optimization of activated carbon for OMP removal from water and wastewater depend on several criteria, including the OMP properties, the water quality, and the system conditions [100, 198].
Biochar is a carbonaceous adsorbent generated through the pyrolysis or gasification of biomaterials, which is suitable for removing OMPs from water and wastewater. Its unique qualities, including negative surface charge, high surface area, porous structure, and diverse functional groups [199–200], make it one of the useful and sustainable adsorbents for various environmental applications, such as soil remediation, carbon sequestration, energy storage, and water treatments (see supplementary material Fig. S2). Several biochar production techniques, including fast pyrolysis, slow pyrolysis, gasification, and carbonization, offer a versatile platform for tailoring specific characteristics of biochar [201–202]. The customization extends to biochar surface area and pore size distribution, allowing the strategic design of biochar to effectively target and adsorb specific OMPs in aqueous systems [203]. Each method contributes to the refined engineering of biochar properties, enabling a fine-tuned approach to addressing waterborne OMPs. These techniques play a pivotal role in developing biochar as a tailored adsorbent that enhances the efficiency of OMP removal through optimization of key structural features. Bone char is a type of biochar that exhibits remarkable adsorption capabilities superior to its counterparts such as charcoal and biosolids-derived biochar in removing OMPs mainly due to its calcium hydroxyapatite powder (HAP) content [204].
In their study, Alkurdi et al. [202] observed that elevated levels of water hardness and salinity significantly enhance the OMP adsorption capacity of bone char. This phenomenon was attributed to the concurrent increase in positive surface charge on the bone char under these conditions. The heightened positive charge facilitates an augmented interaction between the negatively charged OMPs and the surface of the bone char. The findings underscore the complex relationship between water quality parameters, specifically hardness, salinity, and adsorption efficiency of bone char in mitigating environmental pollutants. In the realm of water treatment, bone char application not only guarantees efficient pollutant removal but also exemplifies an environmentally conscious approach, as emphasized by Reynel-Ávila et al. [36]. Nevertheless, the utilization of bone char as an adsorbent for water treatment faces prohibitions due to prevailing religious and moral beliefs. In general, the efficiency of biochar in removing organic OMPs in the aqueous system depends on the adsorption mechanisms and the properties of the OMPs. For instance, the physisorption mechanism allows the reversible binding of non-polar and weakly polar OMPs. Additionally, the presence of functional groups on the biochar surface, such as hydroxyl (-OH) and carboxyl (-COOH) groups enhances chemical interactions, resulting in the chemisorption of polar OMPs [205]. These methods operate synergistically to enhance the total adsorption capacity of biochar for a wide spectrum of organic OMPs. The structure of biochar provides substantial surface area and active sites for OMP adsorption. This structure not only allows for efficient adsorption but also encourages microbial activity, making biochar-amended systems potentially advantageous for biological treatment procedures [206]. The capacity of biochar to boost microbial activity in water and wastewater treatment systems presents an interesting option for integrated and sustainable approaches to micropollutant removal [207].
Hydrochar is also a carbonaceous material that is produced from the hydrothermal carbonization of organic feedstock [208]. The hydrothermal method involves subjecting biomass or organic waste materials to elevated temperatures and pressures in an aqueous environment, resulting in the creation of a carbon-rich material with customized properties [209]. Hydrochars are characterized by their high surface area, porous structure, and functional groups, which make them efficient adsorbents for a wide spectrum of OMPs. The manufacturing of hydrochars can be modified by altering the process parameters such as reaction time, temperature, and feedstock content [210]. This enables the fine-tuning of hydrochar characteristics to target certain OMPs. The vast surface area and porous structure of hydrochars provide abundant active sites for adsorption, enabling effective removal of OMPs. Hydrochars also display a high degree of stability and resilience to microbial degradation [207], making them appropriate for long-term use in water and wastewater treatment. Additionally, their hydrophobic nature can promote the adsorption of non-polar and hydrophobic OMPs. The adsorption mechanisms of hydrochars are essentially physisorption, involving van der Waals forces, π-π interactions, and hydrogen bonding. These pathways promote the reversible binding of a wide spectrum of OMPs, including medicines, insecticides, and industrial chemicals. Moreover, the presence of functional groups on the surface of hydrochars, such as carboxyl (-COOH) and hydroxyl (-OH) groups, may contribute to chemical interactions, further boosting their adsorption capacity.
In general, the major limitations hindering the widespread utilization of porous carbons for water treatment include the high prohibitive cost of procuring specialized equipment required for their large-scale production. The potential issues with desorption and loss of adsorption capacity of regenerated porous carbons due to over multiple cycles reuse. The existence of various complex functional groups on the surface of most porous carbons makes it difficult to predict and control their behaviour for the adsorption of specific OMPs. Besides, it is difficult to achieve stable uniform functional groups on the surface of porous carbon via surface modification and functionalization, as it is challenging to maintain the resulting enhanced surface properties of the porous carbon. Finally, handling potential competition for active sites on the modified porous carbon surfaces, especially in complex aqueous environments containing multiple OMPs, portends a serious challenge in ensuring the effective adsorption of targeted OMPs.
4.3. Nanomaterials
In recent years, the porosity, chemical inertness, and adsorption capacity of carbon-based nanomaterials have been investigated, and remarkable physicochemical properties and adsorption quality have been reported [211]. One of the advantages of nanomaterials utilization as alternative adsorbents for water and wastewater treatment is traceable to their nanoscale dimensions, typically falling in the range of 1 to 100 nanometers [212]. The significance of such nanoscales, as shown in supplementary material Fig. S3A, is that they impart distinctive structural properties as well as size and shape effects that influence unique adsorption features, such as high surface-to-volume ratio, high adsorption capacity, distinctive sensitivity and reactivity, and tunable or modifiable surface chemistry, including ease of functionalization, doping, and composite formation [213]. As shown in Fig. S3B, there are vast arrays of nanomaterials that have been developed and utilized for water purification. A series of progressive advances have been incorporated into nanomaterials from carbon-based nanomaterials, metal-organic frameworks (MOFs), metals and metal oxide nanocomposites, and most recently to other nanocomposites formation, to minimize or overcome the individual limitations identified in the earlier types [214]. Carbon-based nanomaterials with large surface areas and variable surface characteristics are effective adsorbents for a wide spectrum of OMPs. Graphenes (GO), carbon nanotubes (CNTs), activated carbon nanotubes (ACNTs), and carbon sponges are the major types of carbon-based nanomaterials that have been used for adsorption of OMPs from aqueous systems [156, 215–217]. GO is a two-dimensional (2D) honeycomb lattice of a single layer of carbon atoms. CNTs are nanostructures formed of coiled graphene sheets that are cylindrical in shape; depending on the number of layers they contain, CNTs can be single-walled (SWCNTs) or multi-walled (MWCNTs) [218]. ACNTs are CNTs that have been subjected to an activation process that involves high-temperature treatment in the presence of a reactive gas. The abundance of active adsorption sites and the addition of chemical functional groups to each of these carbon-based nanomaterials can increase their affinity and promote robust interactions for certain OMP molecules [219]. However, the high cost of producing carbon-based nanomaterials coupled with their limited usefulness after recycling portends significant drawbacks in their applications for water treatment. To minimize the limitations of carbon-based nanomaterials, researchers have produced carbon nanocomposites instead, by loading carbon nanoparticles on natural mineral surfaces to enhance their surface activity [211].
Carbonaceous nanosponges, which are unique hydrophobic (insoluble in water), supramolecular, polymeric materials of high thermal stability, have recently garnered attention as alternate adsorbents for efficient adsorption of OMPs from water and wastewater [220]. These materials have a wide surface area, porous structure, and carbonaceous origin that offer them remarkable adsorption characteristics [221]. They are created from diverse carbon-rich sources through controlled activation techniques, providing a three-dimensional network of interconnected pores for interactions with OMPs [222]. The surface chemistry can be changed through functionalization, doping with heteroatoms, or composite production to enhance adsorption selectivity [223]. Carbonaceous nanosponges are reusable and regeneratable, making them a sustainable and cost-effective solution for long-term water treatment applications.
Metal-organic frameworks (MOFs) are a family of porous materials made of metal ions or clusters joined by organic linkers that make them have up to 90% free space, an interior-specific surface area of approximately 6000 m2/g, well-defined pore structures, and tailorable functionality [224]. These properties help in tailoring MOFs to target specific OMPs through size and shape selectivity, as well as chemical interactions. The adsorption efficiency of MOFs can be further increased by adding functional groups within the frameworks [225]. Hydrogen bonding constitutes the major mechanism involved in OMPs, especially PPCP adsorption by MOFs, where the MOFs act as H–H-donors and the PPCPs as H–acceptors [41]. However, the inadequate stability of most MOFs, their tendency to self-decompose in the aqueous phase, and their high production cost, have limited their application as adsorbents for adsorptive and catalytic processes [226].
Metal-based nanoparticles, such as aluminum and iron nanoparticles, have shown good adsorption capabilities for a wide array of OMPs, including heavy metals and OMPs [227–228]. These nanoparticles can stimulate redox processes, changing some OMPs into less hazardous or non-toxic byproducts. In addition, their high reactivity and surface area-to-volume ratio enhance their interactions with the target OMPs, thereby enabling efficient adsorption and degradation of OMPs. Also, their reactivity allows for numerous surface modification strategies to boost adsorption selectivity. Metal oxide nanoparticles, such as titanium dioxide (TiO2) and iron oxide (Fe3O4) [229–230], have displayed outstanding adsorption characteristics due to their unique surface locations and innate chemical reactivity. TiO2 nanoparticles, for example, are recognized for their photocatalytic activity in addition to adsorption, enabling the degradation of OMPs under UV irradiation [231].
Nanocomposites are materials that have emerged as particularly effective adsorbents for the adsorption of different types of OMPs from water and wastewater. These materials are generated by incorporating nanoparticles and/or nanofibers into a matrix material [232–234], resulting in a synergistic combination of properties that improve adsorption performance. The nanoparticles, frequently consist of materials like graphenes, carbon nanotubes, metal oxides, or zeolites [235], offer a wide surface area and tailored surface chemistry, thereby allowing for enhanced adsorption interactions with OMPs. The matrix material, on the other hand, lends mechanical stability and reinforcement to the nanocomposites [232]. This combination results into a material with an ideal balance of surface area, porosity, and mechanical integrity [225], making it particularly effective for adsorption applications. Furthermore, nanocomposites may be produced and modified to target various classes of OMPs [236], which can allow for their selective removal depending on the pollutant’s chemical properties. Additionally, its versatility permits customization for many water treatment situations from industrial wastewater to drinking water purification [237–238]. The employment of nanocomposites as adsorbents consequently marks a substantial leap in water treatment technology [239], presenting a feasible alternative for the reduction of organic OMPs in aquatic settings. Their extensive application can address significant challenges in water quality and safeguard human and environmental health.
4.4. Adsorbent Properties and Their Impacts on OMP Adsorption
4.4.1. Surface area and pore structure
Several adsorbent properties influence OMP removal efficiency by determining the availability of active sites, the diffusion pathways within the adsorbent, the nature of surface interactions, and the selectivity of the OMPs. Generally, the active sites and diffusion pathways are presented by the adsorbent surface area and porous structure, which constitute two critical properties of any adsorbent that affect its capacity to adsorb any OMPs (Fig. 4). In particular, while the porous structure, including the pore size distribution of an adsorbent, represents the active sites on which the adsorbate molecules adhere, the surface area promotes the interface for adsorbent-adsorbate interactions [93], thus leading to enhanced adsorption capacity. A larger surface area often corresponds to better adsorption capacity. The pore structure ensures mass transport and impacts the adsorption of OMPs with variable molecular sizes. In systems where OMPs of different sizes are present, an appropriate pore structure might boost the overall removal efficiency [240]. In addition, the presence of micropores within the adsorbents tends to facilitate the selective adsorption of small-sized adsorbates [241], while mesopores and macropores accommodate larger molecules [242]. This selective adsorption based on pore size highlights another critical role of pore structure in determining the adsorption capacity and efficiency of adsorbents. However, the influence of both surface area and porous structure of an adsorbent on its adsorption capacity is greatly impacted by the functional groups on its surface [92]. Most lignocellulosic biomass precursors of adsorbent, like activated carbon, contain several atoms and heteroatoms, such as oxygen, nitrogen, chlorine, and sulphur, which get greatly altered to form functional groups after the activation process [243]. For instance, Toles et al. [244], reported that the oxidation of nutshells from agro nut-crops by acid-activation was mainly responsible for the formation of carboxyl, carbonyl, and lactone groups on the surface of the activated carbons prepared from the raw materials.
4.4.2. Surface chemistry
In addition to its porous structure, the surface chemistry of an adsorbent determines its potential application in the adsorption process [245]. Generally, the extent of micropollutant adsorption by several types of adsorbents is influenced by the nature of specific functional groups and molecules present on the adsorbent’s surface. Functional groups like hydroxyl (-OH), carboxyl (-COOH), or amine (-NH2) on the adsorbent surface, may promote or hinder the interactions between the adsorbent and the micropollutant molecules, especially due to the formation of hydrogen bonds or electrostatic attraction with the target OMPs, thereby influencing the uptake kinetics and overall efficiency of the adsorption process [74, 240, 246]. Recently, surface modification of adsorbents to introduce more functional groups (e.g., carboxylic acid, phenolic, ketone, carbonyl, etc.,) and molecules such as cyclodextrin have enhanced their adsorption capacities for OMPs [245]. Successful modifications of different adsorbents’ surfaces have been done through chemical oxidation [247], electrochemical oxidation [248], air oxidation [249–250], microwave-induced treatment [251], and plasma or ozone treatment [250]. One important advantage of surface modification of adsorbent particularly that of activated carbons via acid treatment is that the oxidation process helps to remove hydroxyl groups that compete with the OMPs for active sites while replacing them with a large number of oxygen-laden groups on the carbon surface [74]. It has been reported that the number of available functional groups on the surface of adsorbent, such as activated carbon determines its capacity to adsorb metal-containing organic OMPs [252].
4.4.3. Particle size and morphology
The size and shape of any adsorbent particles constitute two of its important properties. This is because while the adsorbent porosity is regulated by its particle size, the particle shape impacts its packing density; both of which influence the availability of adsorption sites that determine the capacity of the adsorbent to remove any micropollutant that is attracted to it within the liquid-solid interface region. The arrangement pattern of sizes and shapes of any adsorbent particles within its mass refers to its morphology and such pattern influences the packing density and porosity of the adsorbent. The morphology of an adsorbent affects its pore structure by impacting the accessibility of OMPs into the internal surface area. It also affects the distribution of the surface area, leading to varied adsorption capacities for different OMPs based on their size and chemical properties. The packing density of smaller particles results in a higher adsorbent mass within a given volume, thereby enhancing the capacity for micropollutant removal. Zhang et al. [253] reported that the larger particle size of biochar decreases its tar removal efficiency because the specific surface area and active sites on the biochar were decreased by the larger particle sizes. Smaller particle size, however, facilitates faster diffusion of OMPs into the pores of the adsorbent material, leading to improved uptake kinetics and more efficient removal of OMPs. Generally, smaller particle sizes cause larger surface areas per unit mass that provide more active sites for adsorption. This increases the capacity of the adsorbent to remove OMPs due to the greater available surface area for interactions. Particle size is important to several adsorbents. For instance, the first characterization process and even classification of nanomaterials into several groups like nanoparticles, nanotubes, nanoplates, and batches of multi-nanolayers are based on particle sizes [254]. Well-defined and interconnected pore structures can improve the adsorption capacity by allowing for effective access to active adsorption sites.
Selected Case Studies of Adsorption Modelling of OMP Removal
Several studies have recently been conducted on the adsorption of OMP by various adsorbents. Many researchers have explored different empirical, thermodynamic, multilinear regression, external mass transfer modelling approaches to gain superior insight of the adsorption processes. It is, therefore, necessary to examine the performances of the adsorbents based on structured adsorption modelling techniques, as insights gained from such information could further the advancement of modelling and optimization of adsorption processes in OMP removal. Table 4 shows a detailed summary of some selected studies on the application of adsorption processes for removing several OMPs by different types of adsorbents.
Li et al. [255] studied the adsorption capacity of bisphenol A (BPA) in biochar that was prepared using corn stalk core, as the precursor. The biochar was characterized and its adsorption performance was investigated under different conditions to determine its potential for wastewater treatment. BC-900 was declared to have the greatest adsorption efficiency, as it completely adsorbed 150 mg/L of BPA within 5 minutes [255]. The adsorption kinetics fitted a pseudo-second-order model, with chemisorption as the rate-limiting phase, while the Langmuir model predicted monolayer adsorption of BPA on a homogenous surface of BC-900 [255]. The influence of humic acid and metal ions on BPA adsorption was modest, suggesting feasible application in real wastewater conditions. The researchers presented mechanistic insights into the adsorption process, but a deeper study into the precise interactions between BPA molecules and the biochar surface is still required. Advanced spectroscopic approaches may be employed to better comprehend these interactions.
Also, Melliti et al. [256] studied the synthesis, characterization, and modelling of activated carbons (ACs) produced from artichoke leaves (AAC) and pomegranate peels (PAC) for the removal of caffeine (CFN) and acetaminophen (ACT) from aqueous solutions. The adsorption capacities of the ACs were examined and optimized using Response Surface Methodology (RSM) with a central composite design (CCD) to maximize the simultaneous removal of CFN and ACT using the AAC. This statistical approach helps establish optimum settings for maximum adsorption efficiency, considering several operational aspects such as pH, adsorbent dose, initial concentration of pollutants, and contact time [256]. The adsorption capabilities of AAC and PAC for CFN and ACT were examined using batch adsorption experiments, with notable results found. The study comprises a full characterization of AAC and PAC, including their surface area analysis, elemental analysis, SEM, FTIR, Raman spectroscopy, and zeta potential tests. The equilibrium adsorption results were best fitted to the Langmuir model, revealing monolayer adsorption on a uniform surface. However, the study may benefit from a more detailed discussion of the utility and limitations of these models in predicting real-world occurrences. The regeneration and reusability of AAC were also studied, which demonstrates that AAC may be regenerated and reused multiple times with no loss in adsorption capacity. Nevertheless, the regeneration process should be discussed in more depth to give insights into the operational feasibility and cost-effectiveness of the recommended adsorbent.
In another study, Pala et al. [257] evaluated the adsorption capacities of Metal-Organic Frameworks (MOFs), Activated Carbon (AC), MOF@AC composites, and functionalized MOFs (MIL-101 (Cr)-NH2) for PFOS removal from water. They applied Langmuir, Freundlich, and Temkin isotherm models to analyze the adsorption processes. The Freundlich model yielded the best fit, which indicates heterogeneous surface adsorption [257]. The adsorption process was driven by electrostatic interactions, hydrophobic effects, and π-π interactions. The authors reported that MIL-101 (Cr) and MIL-101 (Cr)@AC maintained good adsorption efficiency throughout four cycles of utilization with no reduction in adsorption capacity [257]. However, MIL-101 (Cr)-NH2 was discarded owing to inadequate initial adsorption efficiency. Future work should concentrate on enhancing MOF functionalization and assessing its scalability for real-world applications.
Moreover, Ortiz-Ramos et al. [258] investigated the adsorption rates of three drugs, Trimethoprim (TMP), tetracycline (TC), and chlorphenamine (CPA), onto natural bentonite clay. They utilized three diffusion models to analyze the adsorption kinetics and mass transfer mechanisms. The External Mass Transport Model (EMTM) was found to be unsuitable as it predicted faster adsorption rates than observed experimentally. The Pore Volume Diffusion Model (PVDM) revealed diffusion within the pore volume of bentonite as the main mechanism affecting the adsorption of CPA. The PVSDM improves this model by adding both pore volume and surface diffusion as essential parameters [258]. For TMP and TC, the PVSDM indicated that both surface diffusion and pore volume diffusion play major roles in their adsorption. The PVSDM offers a thorough understanding of the adsorption kinetics, exactly illustrating the experimental concentration decay curves for TMP and TC [258]. In general, the experimental design used for the study was thorough, with variations in initial concentration and stirring speed enhancing the dependability of the data. The employment of various models provides for a thorough understanding of diverse diffusion mechanisms, which is crucial for enhancing adsorption processes in practical applications. However, the study may benefit from a more detailed discussion on the boundaries of each model in real conditions, particularly the EMTM, which was found unsatisfactory. The study concentrates on initial adsorption rates and equilibrium capabilities but lacks a thorough investigation of the long-term stability and regeneration capacity of bentonite clay for recurrent utilization.
Furthermore, Zhao et al. [259] conducted a study on the adsorption behaviour of ionic and neutral pharmaceuticals, as well as EDCs on activated carbon fibre (ACF). They applied linear free energy relationships (LFERs) to create models for predicting the adsorption capacities and affinities of the ACF using batch isotherm adsorption studies. The researchers observed that ACF had high adsorption capacities for both ionic and neutral chemicals, with the ability to effectively adsorb a variety of pharmaceuticals and EDCs across varied initial concentrations, pH levels, and temperatures [259]. The modified model for cations revealed moderate predictability, but the final model for anions showed strong predictability after eliminating the E descriptor. The overall model for cations, anions, and neutral substances excluded three drugs (procaine, furosemide, and 3-hydroxybenzoic acid), before demonstrating adequate prediction and robustness [259]. Validation using a Williams plot verified the model’s applicability domain, with no large outliers or high leverage values [259]. However, the research identifies several areas that may benefit from higher investigation or improvement. While LFER models offer insights into adsorption predictions, a more complete mechanistic investigation could enhance the understanding of specific interactions between adsorbates and the ACF surface. Comparing ACF’s performance with multi-walled carbon nanotubes (MWCNTs) could offer a larger perspective on the relative usefulness of ACF in real-world applications. Future studies should examine regeneration efficiency and adsorption capacity after several cycles of use, as well as the long-term stability of ACF under varied environmental circumstances.
Yuan et al. [260] investigated the role of the air-water interface in the removal of PFAS onto activated carbon (AC) from drinking water by adsorption process using machine learning techniques. They employed molecular dynamics (MD) simulations and QSAR modelling approaches to explore the adsorption behaviour, stability, and interactions of PFAS at the air-water interface. The MD simulations indicated that nanobubbles might stably dwell on the surface of AC due to the oleophobic properties of nonpolar carbon-based materials [260]. The QSAR model was built using 23 representative descriptors, including constitutional and quantum chemical descriptors. The neural network analysis (NNA) model provided the best prediction accuracy using statistical metrics such as correlation coefficient and coefficient of determination [260]. The QSAR model indicated that free energy changes correspond closely with the removal efficiencies of PFAS and it is improved by aeration [260]. However, the umbrella sampling simulations required for extracting ΔGwater-interface data were difficult and time-consuming. The adsorption capacity of AC for PFAS rose with the length of the perfluoroalkyl chains. The dynamic behaviour analysis indicated that PFAS molecules initially at the air-water interface were enriched on the AC surface due to their interactions with nanobubbles. Long-chain PFAS demonstrate greater adsorption due to their larger free energy barriers, making them less likely to escape from the interface region into the bulk water. Despite the extensive understanding of PFAS activity at the air-water interface, the study lacks direct experimental validation, which would strengthen the reliability of the conclusions.
Challenges and Future Perspectives
6.1. Challenges of OMP Removal by Adsorption Processes
Despite the numerous advantages that adsorption system offers for water treatment, only few water treatment plants have incorporated them on large-scale, as part of their advanced water treatment unit processes for OMP removal. The performance of an adsorption process is highly impacted by the choice of adsorbent; however, the process of making the choice is complicated by the diverse nature of OMPs accessible in the environment. Inconsistent adsorption capacities and selectivities across varied OMPs hamper the creation of generalized adsorbents that require a more detailed understanding of specific adsorbate-adsorbent interactions. The cost of adsorbents coupled with the challenging difficulty associated with their regeneration has been a formidable drawback. The difficulty in handling spent adsorbent is also prohibitive due to environmental concerns associated with desorbed OMPs. Adsorption kinetics, especially in continuous column adsorption systems offer the challenges of mass transfer restrictions. Incomplete removal of OMPs over shorter contact periods may impair treatment efficiency and lead to breakthrough occurrences in fixed-bed column systems.
Competitive adsorption among various OMPs may negatively influence the adsorption behaviour of OMPs, resulting in poor performance and difficulties in predicting adsorption behaviour in real-world settings. Regeneration of adsorbents for reuse is crucial for sustainability, although getting efficient regeneration without diminishing adsorption capacity is a challenging problem. Transitioning from laboratory-scale research to large-scale applications causes challenges in maintaining consistent adsorption performance, with erroneous predictions during scale-up capable of causing degrading system design and reduced OMP removal efficiency. The absence of defined procedures for evaluating adsorption performance and defining adsorbents hampers the comparability of results across varied investigations in the field of aquatic research.
The paucity of substantial experiments in continuous column adsorption systems limits researchers’ understanding of adsorption processes in actual, continuous-flow circumstances. Moreover, incorporating any novel OMPs into an existing adsorption system may weaken the usability and efficiency of adsorption systems in future water treatment challenges.
6.2. Potential Solutions and Innovations
More study must, therefore, be dedicated to developing and synthesizing novel adsorbents for all classes of OMPs. This may lead to the manufacture of multi-functional adsorbents with better selectivity and affinity towards a wide variety of OMPs. By using computer modelling approaches, more effective adsorbents might be developed. Also, further study is necessary to investigate innovative reactor designs and flow configurations to improve contact duration and eliminate diffusion constraints in continuous column adsorption systems. Advanced materials like ultrafiltration membranes or immobilized adsorbents could be applied to tackle kinetic difficulties. Further investigations are also necessary for competitive adsorption dynamics in challenging water matrices, pre-treatment procedures, and environmentally relevant regeneration chemicals. Automated regeneration techniques for adsorbents with real-time monitoring meant to boost their efficiency need to be developed. Pilot-scale studies should be encouraged to bridge the gap between laboratory-scale research and full-scale applications. Collaboration and corporations are required among industrial partners, international organizations, and industry authorities to create a standardized strategy for adsorption tests. The emphasis must be extended to inspections of continuous column systems, long-term monitoring, and multidisciplinary research partnerships to understand the adsorption behaviour of novel classes of organic OMPs.
Conclusions
This review explored the complex issues surrounding the occurrence, potential pathways, ecological and health impacts, and advances in adsorption technologies for removing organic micropollutants in water or wastewater. Adsorption technologies are considered among the most effective techniques for OMP removal, with modelling playing a vital role in understanding adsorption isotherms, breakthrough curves, and adsorption kinetics in both batch and continuous column adsorption systems. Several empirical, thermodynamic, multilinear regression, and mass transfer models have been used to analyze adsorption performances in batch and column adsorption modes. Existing models predominantly focus on evaluating the adsorption performance of porous carbons in batch mode. However, it is imperative to underscore the urgent need for comprehensive modelling that extends beyond porous carbons, encompassing various types of adsorbents, particularly in the context of their performance in fixed bed column systems for removing OMPs. The evolution of adsorbent materials, from natural adsorbents such as green and mineral adsorbents to advanced nanocomposites, is discussed, with the various characteristics affecting their adsorption capacities. However, widespread scaling up of adsorption processes for OMP removal from water or wastewater has been hindered by challenges, including different adsorption capacities and selectivities across diverse OMPs, costly production, and regeneration concerns for different types of adsorbents. There is, therefore, the need for further research, especially in developing and synthesizing novel adsorbents tailored to specific classes of OMPs. Computational modelling approaches and advanced materials like ultrafiltration membranes are crucial for creating generalized adsorbents. Investigations into competitive adsorption dynamics in complicated water matrices, pre-treatment procedures, and environmentally suitable regeneration chemicals are also important. Automated regeneration techniques with real-time monitoring are a major frontier. Collaborations and corporations among industrial players, international organizations, and industry authorities are crucial for creating standardized methodologies for adsorption testing.
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