Polyfunctional Ionogenic Compound Sorption: Challenges and New

Critical Review pubs.acs.org/est

Polyfunctional Ionogenic Compound Sorption: Challenges and New Approaches To Advance Predictive Models Allison A. MacKay†,* and Dharni Vasudevan‡,* †

Civil and Environmental Engineering Department, University of Connecticut, 261 Glenbrook Road, Storrs, Connecticut 06269-2037, United States ‡ Department of Chemistry, Bowdoin College, 6600 College Station, Brunswick, Maine 04011, United States ABSTRACT: Polyfunctional ionogenic compounds are unique in that they sorb to environmental solids at multiple receptor sites via multiple interaction mechanisms. However, existing sorption models fail to accommodate: (i) sorption via a single mechanism (e.g., cation exchange) at one sorbent receptor site type (e.g., exchange site) distributed across multiple soil components (e.g., organic matter and aluminosilicates); and (ii) sorption at a specific sorbent receptor site (e.g., exchange site) involving distinct sorbate structural moieties (e.g., −NH3+ and −COOH) and distinct interaction mechanisms (e.g., cation exchange and cation bridging). In response, this study offers a mechanism-based framework for conceptualizing the equilibrium solid-water sorption coefficient, Kd, with particular emphasis on the mechanisms of cation exchange and surface complexation/cation bridging. The unique mapping of sorbate structural moieties, sorbent receptor sites, and sorption mechanisms is used to advance mechanism-specific probe compounds for cation exchange and surface complexation/cation bridging for quantifying the relevant site abundance and baseline sorption free energy. Existing literature studies point to the feasibility of developing mechanism-specific structural corrections to “adjust” mechanism-specific probe sorption measures to estimate the magnitude of sorption for any polyfunctional ionogenic compound of interest. Advancement of our conceptual framework to a quantitative Kd model requires more extensive evaluation of ionogenic compound sorption under consistent experimental conditions.

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INTRODUCTION Knowledge of the extent of organic compound sorption onto environmental solids is crucial to anticipating environmental fate and for identifying exposure scenarios. A powerful philosophy has emerged over the past 50 years of studying the environmental chemistry of organic compounds: Develop quantitative models of compound fate with parameters that capture both relevant properties of the organic compound and key characteristics of the environmental system. Pertinent tools that have formalized this process are summarized in the classic text, Environmental Organic Chemistry,1 by Schwarzenbach, Gschwend and Imboden. In the case of sorption at the solidwater interface, a long history of experimental work has provided insights into the solid-water sorption coefficient, Kd (L/kg), which describes the equilibrium distribution of an organic compound (sorbate) between the solid (sorbent) and aqueous phases: Kd =

Cs Cw

minerals have indicated important interaction mechanisms to include van der Waals interactions coupled with solvent effects (so-called “hydrophobic partitioning”),2−4 electron donor− acceptor interactions,5 electrostatic interactions of cations and anions with charged sites on environmental solids,6,7 and ligand exchange with surface-bound −OH groups on metal oxide surfaces8−18 (Chart 1, Chart 2). Together, these studies enabled a more complete description of Kd to be proposed that links the extent of sorption to characteristics of the environmental solid:1 Kd =

Cw,neut + Cw,ion

(2)

where Ci refers to the concentration of sorbate in organic carbon (oc, molsorbate/kgoc); on mineral surfaces (min, molsorbate/m2); sorbed by cation or anion exchange (ex, molsorbate/molex_sites) or through bonding via a reversible reaction, including surface complexation, (rxn, molsorbate/ molrxn_sites), or in the aqueous phase (w, molsorbate/Lwater) in

(1)

where Cs (molsorbate/kgsolid) is the sorbed compound concentration and Cw (molsorbate/Lwater) is the dissolved phase concentration. Sorption studies of nonpolar/apolar pesticides and industrial compounds, charged pesticides and organic matter analogue compounds (Figure 1) onto soils and soil © 2012 American Chemical Society

∑ Cocfoc + ∑ CminA surf + ∑ CexσexA surf + ∑ CrxnσsurfrxnA surf

Received: Revised: Accepted: Published: 9209

May 2, 2011 July 20, 2012 August 1, 2012 August 1, 2012 dx.doi.org/10.1021/es301036t | Environ. Sci. Technol. 2012, 46, 9209−9223

Environmental Science & Technology

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water and the favorable van der Waals interactions between a sorbate and the sorbent. Such interactions are particularly important for nonpolar/apolar compound interactions with nonpolar organic matter and poorly solvated mineral surfaces (Chart 2). Electron donor−acceptor interactions involve a weak attraction between electron-rich or -poor domains on a polar moiety of the sorbate with a complementary electronpoor or -rich region on the environmental solid. Each of these Type I sorption interactions occur to some extent for all organic sorbates. Term-specific sorption coefficients for Type I interactions of neutral molecules, for example, Coc foc/Cw = Koc foc and CminAsurf/Cw = KminAsurf, can be estimated by using empirical relationships that capture sorbate properties (Koc,19−23 Kmin24,25) and measures of environmental solids bulk characteristics (foc, Amin 26). The effects of ionogenic compound charge on Type I interactions has also been addressed.27 Polyfunctional ionogenic compounds interact with environmental solids via Type I interactions and via ion exchange and/ or reversible reactions. Ion exchange and reversible reactions (surface complexation and cation bridging) occur at specific receptor sites (charged sites or surficial Al or Fe) on the environmental solid (Chart 2) and are henceforth referred to as Type II interactions. For ionogenic compounds, the driving force for Type II interactions can be greater than the driving force for Type I interactions.28 Descriptive sorption models for Type II sorption interactions that capture sorbate properties are not available presently, nor can the relevant environmental solids characteristics, σi, be quantified reliably. Thus, present estimation of Kd for ionogenic compounds that sorb via ion exchange or surface reactions is entirely reliant upon experimental investigation of individual compound-environmental solid pairs. Such a labor-intensive approach for quantifying Kd is untenable given the anticipated increase in environmental releases of organic compounds, including polyfunctional ionogenic compounds, through expanding urban development, agricultural productivity, biofuel and renewable energy advances, and innovations in consumer products. To overcome this challenge, there is a need for a deeper understanding of sorption mechanisms and for robust predictive models for quantifying Kd for any polyfunctional ionogenic compounds that might be released in a particular environmental setting. The goal of our paper is to develop a conceptual approach for estimating Kd that enables us not only to incorporate the complexity of polyfunctional compound structures and their related multiple interaction mechanisms, but also to advance a new direction for pursuing quantitative modeling that still captures both the structural features of the organic compound and key characteristics of the environmental solid. This review article follows an unconventional roadmap toward achieving this goal of a quantitative predictive capability for polyfunctional ionogenic compound sorption akin to models available for the sorption of polar and neutral compounds19−25 that primarily sorb via Type I interactions. On analysis of the literature on simple and polyfunctional ionogenic compound sorption, we were able to clearly delineate the relevant interaction mechanisms and to obtain an advanced qualitative understanding of how compound structure influences sorption. However, we found that the lack of consistency in experimental conditions between studies, and the absence of studies involving extensive homologous compound sets, precluded us from arriving at quantitative predictive models for compounds

Figure 1. Select chemical structures that have been the subject of sorption studies and potential probe compounds advanced by this study.

truly neutral (neut) form or ionic (ion) form, including zwitterions. The relative contribution of each term in numerator of eq 2 is dependent on both the strength of the sorption interaction and availability of sites on the sorbent. Relevant sorbent characteristics captured in eq 2 include foc, the fraction of organic carbon, Asurf (m2), the solid phase surface area and σi (molsites/m2), the area-normalized concentration of sites for exchange (ex) or reversible surface reaction (surf rxn). As such, availability of sorption sites is quantified in eq 2 in terms of both soil component abundance (e.g., foc) and specific receptor site densities (e.g., exchange capacity) (see Chart 1 for explanation of distinction between components and receptor sites). The summation notation included in eq 2 indicates that multiple solid phase component surfaces (e.g., kaolinite, montmorillonite), each with its own characteristic Asurf and σi, contribute site densities for organic compound sorption.1 We note that this more complete description of sorption afforded by eq 2 contains some implicitly conditional aspects of Kd, including pH since both surface and sorbate speciation are pH dependent, and the linear or nonlinear relationship between C oc , C min , C ex , and/or C rxn and the dissolved phase concentration, Cw. To address the topic of predictive sorption models for polyfunctional ionogenic compounds, we distinguish between two categories of interaction mechanisms. We group the first two terms in eq 2, Coc and Cmin together as arising from Type I interactions: hydrophobic partitioning and electron donor− acceptor interactions. Hydrophobic partitioning of a compound results from the coupled high energy cost of cavity formation in 9210

dx.doi.org/10.1021/es301036t | Environ. Sci. Technol. 2012, 46, 9209−9223


Critical Review

Chart 1. Relationship between Solid Components and Receptor Sites53

in a manner that takes our conceptual framework toward its practical application in the long term. The strategies and the conceptual model presented in this review advance mechanistic understanding of the sorption phenomena and the predictive capabilities for polyfunctional ionogenic compound sorption. We expect that these findings will improve our ability to anticipate and predict the fate of new and existing contaminants and to evaluate human and ecosystem exposure risks.

that sorbed primarily via Type II interactions. In addition, we found that current methods of environmental solid characterization, based largely on their relevance to sorption of neutral organic compounds and inorganic ions or to soil evaluation for agricultural purposes, were not appropriate for polyfunctional ionogenic compounds. In response to these gaps in data, we have developed a conceptual schema for predicting Kd that incorporates current mechanistic information and compound structural criteria relevant to sorption and that advances a new approach for sorbent characterization. Specifically, we present an approach for anchoring sorbent characterization to sorption mechanism and sorbate structure. The resulting conceptual model is novel for polyfunctional ionogenic compounds sorption and is based on established concepts in physical organic chemistry. Transition from this “conceptual” model to a “functioning” model will require additional research. In advancing our conceptual approach for estimating Kd we (i) present the use of mechanism-specific probe sorbates as a means of quantifying the key characteristics of an environmental solid (sorbent) relevant to sorption via cation exchange and surface complexation, (ii) assess prior studies of the influence of sorbate structure on the extent of cation exchange and surface complexation and identify feasible approaches for incorporating structural corrections that extrapolate probe sorbate sorption to other compounds of interest, and (iii) highlight data gaps and advance strategies for filling these gaps

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NECESSARY ATTRIBUTES OF Kd MODELS FOR POLYFUNCTIONAL IONOGENIC COMPOUNDS Recent focus on the fate of pharmaceutical compounds in the environment has highlighted the need to describe quantitatively the sorption of polyfunctional ionogenic compounds. In contrast to our understanding of ionogenic pesticide and organic matter analogue (Figure 1) sorption, compounds such as the veterinary antibiotic, oxytetracycline, sorb to environmental solids via multiple mechanisms (Figure 2).28−34 These sorption interactions occur at specific receptor sites distributed across multiple solid phase components and often involve multiple sorbate functional groups. For example, oxytetracycline can sorb via surface complexation to surficial Fe and Al ions on both metal oxide and aluminosilicate edge sites. In addition, oxytetracycline can sorb via cation exchange and cation bridging to negatively charged sites both on aluminosilicates and organic matter (Figure 2). Importantly, 9211



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Chart 2. Relationship between Interaction Mechanisms, Sorbent Receptor Sites, And Sorbate Structure

Figure 2. Sorption of oxytetracycline to distinct receptor sites on environmental solids via multiple interaction mechanisms: both cation exchange at negatively charge sites and cation bridging to cations sorbed at negatively charge sites, and surface complexation to surficial iron and aluminum cations. Here the environmental solid is not represented in terms of the constituent components (organic matter, aluminosilicates, metal oxides), but rather in terms of the key receptor sites occurring on one or more of the solid components. See Chart 1 for explanation of receptor sites and Chart 2 for description of sorption mechanism.

sorption via these two different mechanisms involve separate sorbate functional groups − cation exchange occurs via the cationic amine functionality, and cation bridging via the hydroxyl group (Figure 2). In the case of oxytetracycline,

these sorption mechanisms dominate over the weak interaction of oxytetracycline with environmental solids via Type I interactions, hydrophobic partitioning (log Dow = −0.1 35) and electron donor−acceptor interactions.28,29,36,37 9212



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Table 1. Key Structural Moieties Relevant to Sorption Mechanisms Structural Moiety Cationic group

Potentially anionic groups (H donors)

Nonpolar neutral moiety Polar/neutral groups (H donors and acceptors)

a

Identification Based on Compound Structure and Charge Moieties Relevant to Type II Sorption Mechanismsa •quaternary amine (R4N+) •primary (RNH3+), secondary (R2NH2+), or tertiary (R3NH+) amines with pKa > 4

•bipolar COOH, OH and neutral R(4‑x)NHx groups with pKa values less than 9 Moieties Relevant to Type I Sorption Mechanismsb •apolar and monopolar regions within a compound •keto group •OH groups with pKa > 9 •cationic amines with pKa < 4

Type II sorption interactions can occur for ionogenic compounds. bType I sorption interactions can occur for all compounds.

Al receptor sites 42), thereby resulting in overprediction of surface site availability.43 Cation and anion exchange capacity (CEC and AEC) represent solid characterization techniques for σex that are not solid component-based. As such, CEC and AEC obtained from compulsive exchange of inorganic ions may be a closer surrogate for σex than AAO and DCB Fe/Al are for σrxn. However, CEC and AEC measures possibly may misestimate sorption for large organic cations because inorganic cations simulate point charges and organic cation sorption may be influenced by steric constraints. Furthermore, use of receptor site characteristics (e.g., CEC) along with soil component characteristics (e.g., foc), such as in empirical multistepwise linear regression Kd models,37,44−46 may “double-count” environmental solids characteristics. One such example is high organic matter soils for which foc and CEC are cocorrelated37,47 and for which cation exchange interactions may effectively be represented twice in a regression that includes both characteristics. The explicit inclusion of both solid component (e.g., foc) and receptor site abundances (e.g., σex) in eq 2 also hampers the inclusion of sorbate properties into predictive models of Kd for polyfunctional ionogenic organic compounds. Conventionally, sorbate properties have been integrated into term-specific sorption coefficients (e.g., Koc (= Coc/Cw), Kmin (=Cmin/Cw)) and hence, in the case of Type II sorption interactions, would be represented in models for Kex (=Cex/Cw) and Krxn (=Crxn/ Cw). The primary challenge to integrating sorbate properties of polyfunctional ionogenic compounds into Kex and Krxn, as formulated in eq 2, is the need to accommodate multiple interaction mechanisms at a single receptor site type, σi. For example, oxytetracycline can interact with negatively charged exchange sites (σex) through two interaction mechanisms (Figure 2): The cationic amine group can exchange with a sorbed cation at the exchange site, whereas the −OH groups can associate with the same receptor site via a bridge with the sorbed cation.48 The structural moieties essential for cation exchange and cation bridging are distinctly different. This poses a challenge to accommodate uniquely parameters for both of these structural features into a model formulated with a single receptor site type (e.g., σex in eq 2). Necessary attributes of quantitative Kd models for polyfunctional ionogenic compounds are the integration of parameters that afford: (i) unique characterization of environmental solid receptor sites that participate in more than one type of sorption

For polyfunctional organic compounds, such as oxytetracycline, the approach of eq 2 provides a powerful conceptual f ramework for describing organic compound sorption; however, the explicit inclusion of sorption site abundances that require knowledge of both individual soil components (e.g., foc) and select receptor sites (e.g., σex) limits the predictive capabilities of this approach. Equation 2 cannot accommodate the case of cation exchange and cation bridging at an aluminosilicate site (Figure 2), as it requires the inclusion of σex sites in both exchange and reactions terms. Soil characterization techniques do not allow for the distinction between the fraction of σex sites involved in cation exchange vs cation bridging with a sorbate. As such, eq 2 has to be recast to utilize receptor sites densities that are not dependent on the solid component characterizations, but rather that are anchored to the relevant sorption mechanisms. One limitation to representing the characteristics of environmental solids for exchange and complexation interactions, as conceptualized in eq 2, is the lack of available sorbent characterization techniques to quantify sorption sites on individual solid components, for example, amount of surfaceaccessible kaolinite, montmorillonite, iron oxide, and aluminum oxide sites. Such emphasis on solid phase component composition is a logical extension of early sorption coefficient models that described neutral organic compound sorption to solids via partitioning to organic matter,3 an easily quantifiable solid phase characteristic.26,38 Adopting a similar approach for Type II sorption interactions wherein conventional soil characteristics would supplant σi is not feasible because conventional solid phase characterization techniques emphasize bulk parameters that may not be relevant to ionogenic organic compound sorption. For example, amorphous and crystalline iron and aluminum oxide content (e.g., acid ammonium oxalate (AAO) and dithionate-citrate-bicarbonate (DCB)−Fe/Al, respectively) are measures of the total metal content of oxide minerals, rather than the surface-accessible Fe and Al sites that are relevant to surface reactions.26,39,40 Even if modifications of the digestion technique could be made to more closely approximate surficial Fe and Al atoms,41 the selectivity of these techniques would fail to quantify accessible surface-bound Fe and Al atoms on aluminosilicate minerals that also contribute sites for sorption via surface complexation. Importantly, the use of digestion techniques for AAO and/or DCB Fe/Al disrupts solid phase component associations (e.g., organic matter coatings on metal oxides that may block Fe and 9213



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Table 2. Mapping of Type II Sorption Mechanisms to Relevant Receptor Site Types and Organic Sorbate Structural Moieties

a Detailed descriptions of sorption mechanisms are provided in Chart 2. environmental solids are provided in Chart 1.

b

Relationships between receptor site types and components of

conceptualize a new strategy to obtain quantitative K d predictions for polyfunctional organic compounds: Measures of sorption for probe compounds containing only one of the two structural moieties relevant to Type II sorption interactions − cationic amine groups, or potentially anionic groups (Table 1) − can be used to provide implicit receptor site abundance measures for sorption via each Type II interaction. (Probe compounds can be chosen to minimize Type I interactions with solids, interactions which can be estimated independently from existing models.) The conceptual feasibility of such an approach arises from the unique relationship between possible organic compound interaction mechanisms and the requisite solid phase receptor sites and relevant sorbate structural moieties (Table 2). We note that the relationships between sorption mechanism, relevant receptor site types and key structural moieties in Table 2 embody an important shift in the perspective of how we envision environmental solids in the context of sorption mechanisms. Rather than focusing on conventional characterization approaches that emphasize particular types of solid phase organic matter and specific mineral components, environmental solids are envisioned as aggregates composed of f ive dif ferent sorption receptor sites, nonpolar neutral domains, polar neutral domains relevant to Type I interactions and negative charge sites, surface-bound Fe and Al, and positive charge sites relevant to Type II interactions (Figure 2, Chart 1). With such a perspective, each mechanism maps uniquely to only one sorption receptor site type, as indicated by a single arrow connecting each mechanism (column 1) to a receptor site type (column 2) in Table 2. Two factors enable us to address the apparent nonunique condition of potentially anionic groups participating in three sorption mechanisms (Table 2). First, we classify anion exchange as a minor interaction because we anticipate negligible extents of anion exchange to occur on environmental solids due to the low density of positively charged sites (i.e., AEC 1−50 meq/kg cf. CEC 80−1400 meq/kg53) for most soils, with the notable exception of acidic mineral horizons of iron oxide-rich Spodosols, Ultisols, and Oxisols.53 We lack definite evidence to similarly classify cation bridging interactions as minor. Cation bridging has been invoked to explain the sorption of antibiotics to organic matter-rich soils and manure solids.7,28,36,46,54,55 In these cases, cation bridging was the only feasible driving force for sorbate retention given the high solubility of these antibiotic compounds (charged or zwitterionic) and the high organic matter contents and low mineral contents of the solids examined. Second, because cation bridging cannot be excluded as an important sorption mechanism, we group cation bridging with surface complexation: Sorbate interactions with a bridging cation on an

mechanism, and (ii) unique representation of sorbate properties that accommodates different structural moieties participating in more than one interaction mechanism at one type of receptor site. To overcome the limitations of eq 2 and to accommodate multiple sorption mechanisms, multiple receptors sites and multiple structural moieties (criteria (i) and (ii), above), we propose new measures of receptor site densities that are anchored to the relevant Type II sorption mechanisms cation exchange, cation bridging, and surface complexation. We do not revisit receptor site characterization for neutral forms of polyfunctional organic compounds since Type I sorption mechanisms are already well-described by existing models.19−23

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MECHANISM-SPECIFIC PROBES: ANCHORING SORPTION RECEPTOR SITE ABUNDANCES FOR POLYFUNCTIONAL IONOGENIC Kd MODELS TO SORPTION MECHANISMS AND SORBATE STRUCTURE From the perspective of sorption interaction mechanisms with environmental solids, only a limited number of key structural moieties are of importance to cation exchange, cation bridging and surface complexation (Table 1), despite the overall wide variety of organic sorbate structures. Cation exchange interactions with a sorbent surface necessitate the presence of at least one cationic group on the sorbate molecule (see moieties, Table1). Similarly, cation bridging and surface complexation interactions require the sorbate molecule to have one or more potentially anionic groups (see moieties, Table 1). Comparative sorption studies of analogue compounds with and without key functional groups show these groups to be critical to sorbate interactions with appropriate receptor sites.49 As such, cationic amine, −COOH and −OH groups represent key structural moieties for Type II interactions. Other substituent groups typically present within organic compounds (e.g., sulfonate, amide, alkyl, nitro, and halo groups) do not always interact directly with environmental solids but do influence the interaction strength of the key structural moieties.16,27,30,50−52 Such groups are known to influence van der Waals interactions, solvation effects, and electron donor− acceptor interactions of polar groups important to Type I mechanisms. Similarly, van der Waals interactions, solvation effects and electronic effects arising from alkyl, nitro, halo, and other substituent groups exert additional influence on interactions of key functional groups participating in Type II mechanisms (addressed in detail later in this paper). Thus, we consider substituent/structure influences on sorption to be independent for each Type II interaction and distinct from influences on Type I interactions. Recognizing that only cationic amine, −COOH and −OH groups are key structural moieties for Type II interactions, we 9214



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KType I = 0.7 L/kg),with a minor contribution of Type I interactions that can be estimated from existing models. When allowed to sorb to an environmental solid, a probe molecule implicitly samples the relevant sites on the sorbent and offers a combined measure of both site abundance and a baseline driving force for sorption for that particular sorption mechanism. As such, the magnitudes of probe sorption provide a measure of relative contributions from CE and SC+CB interactions for sorption to a particular environmental solid. To extrapolate probe sorption to other structurally related sorbate compounds possessing key moieties that interact via cation exchange and/or surface complexation/cation bridging, mechanism-specific structural correction would be required for each of the relevant Type II mechanisms. Generally, with this conceptual approach a priori estimates of Kd, subject to a mass balance constraint on the distribution of sorbate mass between sorbed and dissolved phase pools, would be constructed as follows:

environmental solid, or with a surficial Fe or Al atom via inneror outer-sphere complexes are similar types of interactions, but clearly different from cation exchange or Type I interactions Furthermore, from the context of sorbate structure, the same potentially anionic structural moieties are relevant to both cation bridging and surface complexation. As such, the use of probe molecules relevant to cation exchange and surface complexation/cation bridging allows us to measure sorption site densities and anchor sorbent characterization to sorption mechanisms relevant to polyfunctional ionogenic organic molecules. Formulating Kd From a Mechanism-Based Framework. The mapping of sorption mechanisms with receptor sites and structural moieties (Table 2) positions us to adopt a mechanism-based framework for conceptualizing polyfunctional organic compound sorption to environmental solids. Based on the presence or absence of key structural moieties (Table 1), the total amount of compound sorbed to an environmental solid may contain contributions from sorbate molecules interacting via Type I interactions (Type I) and via Type II mechanisms, cation exchange (CE), cation bridging (CB) and/ or surface complexation (SC). Given the simultaneous occurrence of multiple sorption mechanisms for which the sorbed compound concentrations, Cs, for each mechanism is at equilibrium with a common solution phase sorbate concentration, Cw, we have an additive relationship between sorption coefficients that describe the different interactions that a polyfunctional organic compound could participate in Kd =

probe XS probe XS Kd = KType I + f (K CE , K CE ) + f (K CS + CB , K SC + CB)

(4)

Kiprobe

where f() denotes as yet unspecified functions of and KiXS for cation exchange and surface complexation interaction mechanisms. Kiprobe is a measure of sorption of the cation exchange (CE) or surface complexation and cation bridging (SC+CB) probe (e.g., Langmuirian constant1,31) that captures both the site availability and baseline interaction energy of the probe with the appropriate receptor site type. Kiprobe can be determined in the linear range of the sorption isotherm or measured in a manner that directly captures nonlinearity, paralleling efforts previously applied to other sorption interactions.23 Thus, Kiprobe serves as the descriptor of solid phase characteristics, supplanting current soil characteristics such as AAO/DCB Fe/Al. KiXS is a structural scaling factor that accounts for the differing sorption free energy arising from the difference in chemical structure between the sorbate of interest and relevant cation exchange (CE) or surface complexation and cation bridging (SC+CB) probe. We envision KiXS scaling factors (different for CE and SC+CB) to be analogous to free energy corrections that have been used previously (e.g., estimation of log Kow 56 and pKa values57); however, explicit development of mathematical formulations for KCEXS and KSC+CBXS are required before eq 4 can be advanced to the point of being a practical tool. With this approach, solid phase characterization obtained by Kiprobe and scaling with KiXS allows for the prediction of sorption of “any” polyfunctional ionogenic compound to environmental solids of interest. In concept, the approach of using mechanism-specific sorbate probes for cation exchange and surface complexation/cation bridging overcomes the previously described limitations arising from approaches that combine solid component and receptor site measures for sorbent characteristics. The use of probe compounds can also accommodate polyfunctional ionogenic compounds with distinctly different structural moieties that result in multiple sorption interactions at a single site (e.g., oxytetracycline interactions with negatively charged receptor sites via cation exchange and cation bridging, Figure 2) because the structural moieties and receptor sites are implicitly grouped by sorption mechanism in eq 3 and 4. The full utility of this approach is only realizable if the mechanism-specific probe sorption measures can be extrapolated to other structurally related sorbate compounds possessing key moieties that

Cs,Type I + Cs,CE + Cs,SC + CB Cw

= KType I + K CE + KSC + CB

(3)

where the Ki values would embody both characteristics of the environmental solid and properties of the sorbate. Like past predictive Kd models, use of eq 3 in a predictive mode to describe the distribution of a polyfunctional ionogenic organic compound between an environmental solid and the aqueous phase must be accompanied by a mass balance constraint that enables distribution of a fixed mass of sorbate among the sorbed pools of compound participating in parallel sorption interactions (Cs,Type I, Cs,CE, Cs,SC+CB), and the dissolved phase with the proviso that each sorbed pool is independently at equilibrium with the common dissolved phase concentration, Cw. We note at this stage that eq 3 is a theoretical representation for polyfunctional ionogenic organic compound sorption. Advancement of eq 3 toward a practical application, from which a numerical estimation of Kd could be obtained, requires other factors to be addressed (e.g., receptor site heterogeneity (isotherm nonlinearity), pH, and competing sorbates); these are taken up later (from Concept to Practice) following our further development of the conceptual framework of eq 3. The formulation of Kd conceptualized in eq 3 opens the door to a new approach for a priori predictions of Kd for polyfunctional ionic compounds through the use of mechanism-specific organic compound probes to quantify the contributions of Type II sorption interactions (CE, SC + CB). We define as a probe an organic molecule possessing one relevant structural moiety−cationic amine for cation exchange (e.g., benzyl amine, Figure 1 with KType I = 0.05 L/kg for soil with 2% organic carbon), or −COOH/OH group for surface complexation and cation bridging (e.g., salicylic acid, Figure 1; 9215



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Figure 3. Illustration of probe compound concept using flumequine and phenylpiperazine to assess cation exchange (CE) and surface complexationplus-cation bridging (SC+CB) interactions, respectively, for an environmental solid. Probe sorption measures are adjusted with structure-based correction factors, KSC+CBXS and KCEXS, to extrapolate CE and SC+CB interactions to a sorbate of interest, here ciprofloxacin. Structural differences between the probe compounds and the sorbate are highlighted in red.

Feasibility of Structure-Based Correction Factors (KiXS). Advancement of our structure-based approach for conceptualizing Kd (eq 4) into a predictive tool depends on the development of robust models of KiXS that account for sorbate structure influences on cation exchange and surface complexation/cation bridging interactions. Relationships between sorbate structure and free energy of sorption via cation exchange or surface complexation have not been studied with the intensive focus that structure-based free energy relationships have been pursued for Type I sorption interactions (e.g., hydrophobic partitioning1). The few cation exchange and surface complexation sorption studies that have been conducted with homologue compound sets under the same conditions (i.e., sorbent type, pH, ionic strength, etc.) highlight structural features relevant to KiXS for either cation exchange or surface complexation and point to the feasibility of developing quantitative measures of KiXS in each case. Cation Exchange. Close examination of homologue sets of cationic organic compounds indicates that structural changes impart multiple influences on the magnitude of sorption via cation exchange. Early studies identified the importance of compound hydrophobicity (due to compound size, solvation effects, and greater potential for van der Waals interactions) for enhancing cationic amine sorption to aluminosilicate surfaces.6,58,59 We revisited these, and other studies with pure phase minerals, to examine how free energy of sorption via cation exchange, ΔGsorb (J/mol), changed with addition of various moieties across homologue compound sets.6,30,50,51 Using log Kow fragment constants 60 as a readily available measure of substituent hydrophobicity (Δ log Kow) for a wide variety of substituents, we found that increases in ΔGsorb do occur with changes in substituent hydrophobicity (ΔGsorb/Δ log Kow, Table3). However, across different homologue sets, the incremental increase in sorption energy per unit hydrophobicity is not constant. For example, the incremental change in sorption energy arising from methyl group addition to the carbon chain in primary n-alkyl amines (Table 3, line 1−2) differs from methyl group addition to the aromatic ring (Tab. 3, lines 4−5), methyl group addition to the amine nitrogen (secondary, tertiary, quaternary, Tab. 3, line 8, 12, 13) and methyl group addition to other substructures (Table 3, line 6). While compound hydrophobicity clearly has an impact on

interact via cation exchange and/or surface complexation/ cation bridging.

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FEASIBILITY OF MECHANISM-BASED Kd PREDICTIONS USING PROBE COMPOUNDS Proof of Mechanism-Specific Probe Concept. The concept underlying eq 4 has been demonstrated previously in an effort to distinguish cation exchange interactions of ciprofloxacin (Figure 3) from surface complexation interactions.31 In the case of ciprofloxacin, probe compounds, or structural analogue compounds that participated in only cation exchange (phenyl piperazine, Figure 3) or surface complexation (flumequine, Figure 3) were readily available. Sorption of the probe compounds and ciprofloxacin were compared for the pure phase minerals, kaolinite and goethite, which possess receptor sites that participate in sorption via only one mechanism, cation exchange and surface complexation, respectively. These probe-ciprofloxacin comparisons yielded empirical scaling factors that were equivalent to KCEXS and KSC+CBXS proposed in eq 4. Assuming that empirical scaling factors obtained from pure phase sorbents were also applicable to environmental solids, these KCEXS and KSC+CBXS values were applied to scale the measured sorption of the probe compounds on soils and yield estimates of the cation exchange and surface complexation/cation bridging contributions for ciprofloxacin sorption to soils. These estimates of ciprofloxacin sorption to eight test soils were generally within a factor of 2 (at pH 7.2) or less (pH 5) of measured values of ciprofloxacin sorption to soils that had varied cation exchange capacities (CEC: 8−440 mmol/kg) and oxide contents (DCB Fe/Al: 8−900 mg/kg). Thus, we concluded that the concept proposed in eq 4 was feasible; however, this prior work clearly showed that a more robust approach than the use of empirical scaling factors from mechanism-specific structural analogs would be necessary. First, for many compounds, mechanism-specific structure analogues are not readily available without synthesis. Second, obtaining and using empirical scaling factors for each sorbate of interest is a labor-intensive approach that defeats the purpose of a priori Kd estimation tools. As such, the identification of universal probes (e.g., benzylamine and salicylic acid, Figure 1) and the construction of explicit structure-based scaling factors are essential for the successful development of our new framework. 9216



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Table 3. Change in Cation Exchange Sorption Free Energy, ΔGsorb, with Hydrophobicity (Δ log Kow) for Homologue Compound Sets

ΔGsorb values were used as reported, or derived from Kd values (ΔGsorb = −RT ln Kd). bChanges in log Kow values were assessed by summing the fragment constants60 corresponding to the substituents added to the base compound to make each homologue compound in the set. cItalics indicate significant relationship, p < 0.05. dKd values obtained at pH 3 and normalized by the mass fraction of cation using pKa values reported by Weber.51 a

among amine pKa values within homologue sets.61 As such, differences in electron distributions within the molecule should also influence the extent of sorption since the primary driving

cationic amine sorption to aluminosilicate minerals, it is important to also recognize that substituents exert electronic effects on amine functionalities, as evidenced by differences 9217



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referred to as ligand groups) also point to multiple and coupled structural influences on the extent of sorption via surface complexation. Compounds that exist as either a neutral or an anionic species in bulk solution can form surfaces complexes as shown below, where >Fe−OH represents a surface iron receptor site, and x-R-COOH and x-R−OH represent potentially anionic compounds with a nonligand substituent x:

force for cation exchange is electrostatic attraction of the cationic amine group to the sorbent surface. This knowledge, coupled with the findings of regular increases in ΔGsorb with alkyl addition to a particular substructure, but variations in the magnitude of ΔGsorb/Δ log Kow across substructures (in Table. 3), suggest that the differences in ΔGsorb with alkyl substitution are a manifestation of the coupled effects of substituents on the size of the sorbate (van der Waals/hydrophobicity), and electronic effects of substituents on the amine group. Two examples highlight the coupled importance of substituent influence on compound hydrophobicity and charge distributions on the amine group. Prior work indicated that the sorption free energies of n-methyl substituted anilines and ptoluidines that were correlated with compound hydrophobicity (Table 3, line 11−12) were also correlated with the calculated charge-per-area of the amine group (defined as the N and attached Hs):30 r2 = 0.97 (p = 0.11) for anilines and r2 = 0.91 (p = 0.19) for p-toluidines. A coupled substituent influence is also observed for s-triazine pesticides (line 14, Table 3): Sorption free energies are more strongly correlated with Hammett constants (σp or σp−) (r2 = 0.99, p < 0.01) than hydrophobicity (r2 = 0.5, p = 0.3) for these molecules which possess multiple polar moieties. Hammett constants capture the electronic effect of a substituent on the ionization of an acidic functionality.62 Hence, Hammett constants can conceivably provide a surrogate measure of the charge distribution on the amine group: electron-withdrawing substituents can confer more positive charge ‘character’ to the cationic amine and hence enhance sorption. In the case of organotin compound sorption to clays, opposing effects of charge per area and hydrophobicity were observed with increasing substituent chain length.63 Thus, the above-mentioned cases also reinforce the coupled nature of electronic effects and hydrophobicity in cation exchange interactions. In addition to hydrophobicity and electronic effects, several other structural features also influence organic compound sorption by cation exchange. For example, charge delocalization into heterocyclic rings influences cationic amine interactions with negatively charged surfaces, either by enhancing sorption via attractive forces between an electron deficient aromatic ring and negative charge sites, or by suppression of sorption via repulsive forces between electron-rich moieties proximate to the amine cation.30 The proximity of charged groups is also important, with greater separation between positively charged and negatively charged groups associated with enhanced sorption of zwitterionic amino acids6 and antibiotics.30 Finally, molecular orientation in the clay interlayer contributes to the extent of organic compound sorption by cation exchange by enhancing attractive electrostatic interactions and minimizing repulsive interactions.64,65 These prior studies allowed us to identify qualitatively the multiple and coupled influences of structure on cation exchange but they were insufficient to extract robust multiparameter KCEXS models because of the wide range of experimental conditions used in these studies, small range in solid phase properties and the small data sets available (see p-values > 0.05, Table 3). Clearly, more systematic studies of organic cation sorption, obtained under standardized experimental conditions, are required to yield sufficiently robust data sets from which to transition our qualitative understanding of cationic amine sorption to a quantitative framework. Surface Complexation. Sorption studies of compounds containing potentially anionic groups (COOH, OH, NH2; also

>Fe−OH + x−R−COO− → >Fe−OOC−R−x + OH− (5)

>Fe−OH + x−R−OH → >Fe−O−R−x + H 2O

(6)

For neutral species (e.g., R−OH, eq 6), deprotonation (or formation of the anion) occurs in the near surface region during surface complex formation and can be configured as a combination of the two reactions, shown below. x−R−OH → x−R−O− + H+ −

>Fe−OH + x−R−O → >Fe−O−R−x + OH

(6a) −

(6b)

Unlike cation exchange that occurs through an electrostatic attraction between the key functional group and a surface receptor site, surface complexation on metal oxide surfaces is also influenced by covalent contributions to bonding.66 Since covalent contributions are enhanced by favorability for electron sharing across the sorbate key functional group and surface metal orbitals,66 nonligand substituents (e.g., x = CH3, OCH3, NO2) are expected to impart significant electronic effects on the nature of key functional group-surface metal interactions. Importantly, the influence of nonligand substituents on electronic contributions to surface complexation is complicated by the required deprotonation of −COOH and −OH groups in the near-surface region, during complexation of the −COO−/− O− functional groups to the surface-bound metal.66,67 In this two-step process, the net electronic effect of a nonligand substituent (x) balances two trends: Electron withdrawing groups, such as a −NO2 group (lower pKas), lead to desired formation of deprotonated species (product in eq 6a), but they contribute to decreased metal−ligand bond strength of the surface complex product (eq 6b). In contrast, electron donating groups, such as −CH3 group (higher pKas), favor the neutral protonated species (reactant in eq 6a) but contribute to increased metal−ligand bond strength of the surface complex (eq 6b). The importance of the former effect, ligand group deprotonation, is evident in studies of substituted phenols67 and amino phenols16 (pKaOHgroup: 7.6−10.6), which existed primarily as neutral species at the pH of the experiments (pHexperiment < pKa). Here, the extent of sorption was greater for compounds with nonligand substituents with greater electron withdrawing potential which facilitated proton dissociation from the −OH groups in the process of sorption.67 Nevertheless, the phenolic C−O bond position (from IR studies) indicated that stronger bonds with surficial Fe groups were formed by phenols with electron donating substituents. The second effect of substituents − on covalent bond formation − is more easily demonstrated for para-substituted benzoic acids (pKa = 3.5−4.8) which existed as anions at the pH of the experiment (pHexperiment > pKa). For these anionic compounds (in the deprotonated state), both the extent of benzoic acid sorption and Fe-benzoate bond strength (from IR studies) was greater for compounds with nonligand substituents with greater electron donating potential.68 These seeming opposing effects of nonligand substituents clearly emphasize that the ligand group must be deprotonated in the 9218


Environmental Science & Technology 16

Computed with Spartan 08, Hatree Fock 6-31G* basis set in aqueous solution. bUnreported data precluded comparison on a common basis of log Kd for all studies. a

Qualitative increase in sorption with decrease in HOMO energies

increase sorption pH: 7 titanium dioxide catechols (n = 2)

16 increase sorption Increase in sorption (log Kd) with decrease in HOMO energies (R2 = 0.85; p = 0.076) pH: ∼7 titanium dioxide 2-aminophenols (n = 4)

67 increase sorption Qualitative increase in sorption (uM/gb) with decrease in HOMO energies, steric effects p-substituted phenols (n = 3)

pH: 5.5 amorphous Fe oxide

52 increase sorption pH: 4.1 manganese oxide Cl-phenols (n = 9)

Increase in sorption (logQadsb) with decrease in HOMO energies (R2 = 0.63; p = 0.01) (logQads (unitless): Cads (M)/Cbulksolution(M)), hydrophobic and steric effects

decrease sorption Increase in sorption (logK) with increase in HOMO energies (R = 0.97, p = 0.016) (logK (L/kg): from sorption isotherms) pH: 5.3 noncrystalline Fe hydroxide p-substituted benzoates (n = 4)

Ref Effect of Electron Withdrawing Groups Quantitative/Qualitative Relationship between the Extent of Sorption and HOMOa Energies; Other Ef fects Noted Experimental Conditions Homologous Series

Table 4. Relationship between the Extent of Sorption and Computed HOMO Energies (kJ/mol) 9219

2

near surface region for electron donating groups to increase favorability of metal−ligand interactions. Unfortunately, there is no unique pH range in which both homologous sets of benzoic acids and phenols exist in either the neutral or the anionic form. As such, the electronic effects of substituents on ligand group deprotonation, as captured by Hammett constants cannot be separated from effects on metal−ligand bond formation for these compounds. In an effort to identify a parameter that could decouple these seemingly opposing electronic effects, we evaluated HOMO energies as a surrogate for capturing substituent electronic effects relevant to sorption via surface complexation. HOMO energies have an advantage over the traditional Hammett and Taft substituent approach in that HOMO energies are based on the electron distribution within the entire molecule and capture the molecule’s electron donor potential. Furthermore, Hammett and Taft constants, that quantify substituent electronic effects are not available for all substituents and positions, nor are they configured to adequately account for substituent influence on multiple ligand groups present within one structure. We computed HOMO energies (Spartan 08, Hartree−Fock 6-31G* basis set in aqueous solution) for the compounds examined in the above-mentioned studies and then explored the relationship between the HOMO energies and the measured extents of sorption (Table 4). We found a strong correlation (r2 = 0.97) between HOMO energies and the extent of sorption for anionic para-substituted benzoic acids (Table 4). HOMO energies were greater for compounds with greater extents of sorption consistent with the noted electronic effects of the electron-donating substituents favoring metal−ligand bond formation. For the neutral substituted phenols and 2aminophenols (r2 = 0.85), HOMO energies were lower for compounds with higher extents of sorption and mirrored the electronic effects favoring proton dissociation. These trends show that HOMO energies cannot decouple the opposing electronic effects on ligand group deprotonation and metal− ligand complex formation. Hence, the electronic effects on surface complexation have to be configured distinctly for neutral and anionic compounds. In addition to electronic effects, compound size and hydrophobicity also contributes to enhanced extents of sorption via surface complexation. Two-ringed analogues of catechols and 2-aminophenols exhibit greater Kd values than their monoaromatic counterparts.16 Similarly, the extent of sorption for protonated, neutral chlorophenol sorption to manganese oxides increased with an increase in the number of chloro substituents, reflecting increased size/hydrophobicity.52 These studies emphasized that the presence of large nonpolar moieties within a structure favor exclusion of the compound from bulk aqueous solution (solvation effects) and enhance the extent of surface complexation. On the other hand, for phenyl n-alkyl acetic acids, sorption of compounds containing shorter chains (e.g., CH2 and (CH2)2) was negligible while sorption for compounds with longer aliphatic chains (e.g., (CH2)5) was significantly higher.11 HOMO calculations alone were not able to adequately capture coupled influences of electronic, hydrophobicity and steric effects (see Cl-phenols, Table 4; r2 = 0.63) speaking again to the need to account for coupled influences of structure on organic sorbate sorption via surface complexation. Beyond electronic and hydrophobic effects, the number, position, and identity of potentially anionic groups have a marked effect on the extent of sorption via surface complex-

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other competing solutes must be addressed, particularly in the case of cation exchange (e.g., K+ vs Ca2+). Again, some small series of data are available that suggest selectivity coefficients may describe consistent trends.14 Finally, the heterogeneity of surface receptor sitesbeing on the face vs edge of a particular mineral grain, or being on different mineralsgives rise to a distribution of site free energies of sorption that yield nonlinear isotherms. As such, the mathematical formulation of eq 4 for the Type II sorption interactions cannot be formulated simply as a linear function of the product of Kiprobe and KiXS, but rather may be incorporated into a nonlinear model, such as a Langmuirian isotherm relationship as previously suggested.1,31 Prior isotherm sensitivity analyses point to the limitation of being able to extract receptor site characteristics (site density, free energy) for only a single integrated site type from experimental data.77 Thus, it will be critical to identify appropriate concentration ranges (high vs low) for conducting sorption experiments. In response to these practical concerns, we offer that anchoring a KiXS model to measures of Kiprobe values for a targeted environmental solid addresses the abovementioned effects of differences in receptor site identity, competing solutes, and effects of surface heterogeneity. Strategies for Developing Kixs Relationships. Once a larger data set of consistent sorption measures for ionogenic organic compounds is available, there are several approaches to fit descriptive structure-based models for KCEXS or KSC+CBXS. Some strategies that have proven successful for describing other environmental fate model parameters, including Kd for neutral organic compounds, are not appropriate for our case of Type II sorption interactions. For example, fragment constant-based sorption free energy models78 are inappropriate for KCEXS or KSC+CBXS because sorption free energy contributions from electrostatic (CE, SC+CB) and/or covalent (SC+CB) interactions are not strictly additive with other effects (e.g., hydrophobicity), except for very simple sorbate structures. Similarly, Hammett- or Taft constant-derived parameters account for structure effects only on electron distributions of the key structural moiety;62 nor are such parameters available for substituents in complex polyfunctional ionogenic organic compounds. A more promising strategy to integrate structure effects into KiXS models is an approach patterned after linear solvation parameter models. Linear solvation parameter models describe phase partitioning using quantitative measures of each of the interactions (e.g., van der Waals, hydrogen bond donor− acceptor, polarizability) between a molecule and its surrounding medium (79,80 and following works). Such models have assumed additivity of energetic contributions to phase transfer processes where parameter contributions are not accounted by individual structural fragments, but rather via molecular descriptors. In some cases, the free energy contributions are not strictly additive, but casting contributions in a linear framework has provided convenience for ease of use with the recognition that some molecular descriptors are not strictly independent. 81 Although linear solvation models were developed for liquid−liquid phase transfer, they have been successfully extended to describe solid−liquid phase transfer for neutral organic compound sorption to mineral surfaces.24,25 Recently, descriptors for ions (J+, J−) have been added to the Abraham linear solvation parameter set.82,83 The parameters, J+ and J−, have no explicit physical meaning,83 but were derived to enable their use with existing neutral species molecular descriptors, thereby eliminating the need to derive a second

ation. The presence of two or more groups allows for surface complexation via multiple groups and thus greatly increases the extent of sorption.11,69,70 More importantly, the location of COOH and/or OH groups on adjacent carbons facilitates surface chelate formation and thus enhances sorption to a greater extent than two ligand groups located at nonadjacent positions which are not conducive to chelate formation. For example, dicarboxylic acids, such as oxalic, phthalic, fumaric, maleic and succinic acids, with adjacent −COOH groups sorbed to similar extents, despite possessing distinctly different pKa values.12,71,72 Finally, the identity of adjacent ligand groups also affects the extent of sorption: Sorption of compounds with adjacent COOH/OH groups is much greater than analogue compounds with COOH or OH adjacent to an amine group.15,16 We note that apart from adjacent NH2/COOH or NH2/OH groups, amine moieties do not result in significant complexation to metal oxides. As with the case of our cation exchange analyses, existing data sets for organic compound surface complexation to metal oxides are too small to attempt to extract robust KSCXS models that account for coupled electronic effects, hydrophobicity effects, the energetic favorability of chelation and anionic group identity. Again, such a goal could be advanced through the systematic undertaking of surface complexation sorption studies under standardized conditions.

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FROM CONCEPT TO PRACTICE: RESEARCH NEEDS We have put forward a conceptual approach to quantify sorption coefficients for polyfunctional ionogenic compounds through the use of mechanism-specific probe compounds that overcomes the intractable challenge of quantifying sorbent receptor site availability for Type II sorption interactions. Prior literature findings are insufficient to quantitatively confirm our approach because few extensive homologue compound sets were studied and because experimental conditions (e.g., pH, ionic strength) were vastly different between studies. Progress toward models to describe influences of sorbate structure on sorption energies via cation exchange or surface complexation/ cation bridging requires more extensive data sets of ionogenic organic compound sorption that are obtained under consistent experimental conditions (pH, solid loading, etc.) with standard pure phase minerals (e.g., Ca-montmorillonite from the Clay Mineral Society) and inclusion of reference or probe compounds (e.g., benzylamine; salicylic acid, Figure 1). We can be guided in these efforts by prior studies that point qualitatively toward the trends in compound structure effects that must be integrated into the sets of test sorbates: amine charge-per-area, hydrophobicity, charge delocalization and charge proximity for cation exchange, and electronic effects, hydrophobicity, number, position and identity of potentially anionic groups for surface complexation/cation bridging. Strategies for Obtaining the Required Experimental Data. Several practical concerns about the applicability of such pure phase system studies to soil and sediment systems have been previously raised: First, confirmation is necessary of the same relative trends for all surface receptor types (e.g., cation exchange on aluminosilicates vs organic matter; surface complexation on iron vs aluminum oxides). Existing studies suggest that compound structure effects may exert regular changes in sorption interactions regardless of sorbent mineralogy;74−76 however, the small extent of observations available under the same experimental conditions preclude general conclusions from being drawn. Second the influence of 9220



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set of parameters for the compound ionic species . As such, a linear solvation parameter model may have potential to capture empirically structure effects on Type II sorption through the use of molecular descriptors. Finally, quantum molecular descriptors also offer an approach upon which to base models for KiXS. For example, descriptors, such as HOMO energies and minimum and maximum surface potential,84 have enabled simplification of the topological distribution of electron charge density on the surface of complex organic molecules. The inclusion of other such parameters calculated from readily available desktop software packages, such as GAUSSIAN, may be able to describe coupled structure influences on ionogenic compound sorption via Type II sorption interactions. Such an approach may be limited to class-specific descriptor relationships, for example, aromatic amines, −COOH/OH anionic group. However, these limitations may be bridged by the growing integration of quantum mechanics/molecular mechanics models into environmental chemistry problems.85,86 Availability of large data sets for ionogenic compound sorption would allow these and other modeling approaches to be tested for their robustness in capturing appropriate structure influences on Type II sorption mechanisms, as have been suggested qualitatively by existing sorption studies.

Critical Review

AUTHOR INFORMATION

Corresponding Author

*Phone: 860-486-2450 (A.A.M.); 207-725-3548(D.V.). E-mail: [email protected] (A.A.M.); [email protected] (D.V.). Author Contributions

Both authors contributed equally to this work Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank Drs. MaryAnne Holmes and Suzanne O’Connell for the opportunity to attend the GAIN Writing Retreat to sketch out our initial ideas for this manuscript. Retreat funding was provided by NSF ADVANCE-PAID grants 0620101 and 0620087. We thank Dr. Phil Gschwend for valuable conversations. We appreciate the contributions of five anonymous reviewers for their thoughtful and detailed comments that helped to improve the clarity of an earlier version of this manuscript.

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REFERENCES

(1) Schwarzenbach, R. P.; Gschwend, P. M.; Imboden, D. M. Environmental Organic Chemistry; 2nd ed. Wiley: New York, NY, 2003. (2) Reactions and Movement of Organic Chemicals in Soils, SSSA Special Publication; Sawhney, B. L., Brown, K., Eds.; Soil Science Society of America and American Society of Agronomy: Madison, WI, 1989; Vol. 22. (3) Karickhoff, S. W.; Brown, D. S.; Scott, T. A. Sorption of hydrophobic pollutants on natural sediments. Water Res. 1979, 13, 241−248. (4) Chiou, C. T.; Peters, L. J.; Freed, V. H. A physical concept of soilwater equilibria for nonionic compounds. Science 1979, 206, 831−832. (5) Haderlein, S. B.; Weissmahr, K. W.; Schwarzenbach, R. P. Specific adsorption of nitroaromatic: Explosives and pesticides to clay minerals. Environ. Sci. Technol. 1996, 30 (2), 612−622. (6) Theng, B. K. G. The Chemistry of Clay-Organic Reactions; John Wiley and Sons: New York, NY, 1974. (7) Kah, M.; Brown, C. D. Adsorption of ionisable pesticides in soils. Rev. Environ. Contam. Toxicol. 2006, 188, 149−217. (8) Davis, J. A. Adsorption of natural dissolved organic matter at the oxide/water interface. Geochim. Cosmochim. Acta. 1982, 46, 2381− 2393. (9) Hering, J. G. Interaction of Organic-Matter with Mineral Surfaces Effects on Geochemical Processes at the Mineral-Water Interface, In Aquatic ChemistryInterfacial and Interspecies Processes; Huang, C. P., O’Melia, C. R, Morgan, J. J., Eds.; American Chemical Society: Washington, DC, 1995. (10) Biber, M. V.; Stumm, W. An in-situ ATR-FTIR studyThe surface coordination of salicylic-acid on aluminum and iron(III) oxides. Environ. Sci. Technol. 1994, 28 (5), 763−768. (11) Evanko, C. R.; Dzombak, D. A. Influence of structural features on sorption of NOM-analogue organic acids to goethite. Environ. Sci. Technol. 1998, 32, 2846−2855. (12) Filius, J. D.; Hiemstra, T.; Van Riemsdijk, W. H. Adsorption of small weak organic acids on goethite: Modeling of mechanisms. J. Colloid Interface Sci. 1997, 195 (2), 368−380. (13) Parfitt, R. L.; Farmer, V. C.; Russell, J. D. Adsorption on hydrous oxides: 1. Oxalate and benzoate on goethite. J. Soil Sci. 1977, 28, 29−39. (14) Lailach, G. E.; Thompson, T. D.; Brindley, G. W. Absorption of pyrimidines, purines, and nucleosides by Li-, Na-, Mg-, and Camontmorilonite (clay-organic studies XII). Clays Clay Miner. 1968, 16, 285−293.

ENVIRONMENTAL SIGNIFICANCE Given that polyfunctional ionic compounds will continue to be released to environmental systems, it is critical that scientists and regulators consider the full suite of potential sorption interactions that may occur: hydrophobic partitioning, electron donor−acceptor interactions, cation exchange, and surface complexation/cation bridging. By casting sorption processes in a mechanism-based framework, we provide a straightforward approach for identifying sorption mechanisms pertinent to a particular organic compound through the identification of key functional groups that are linked uniquely to sorption mechanisms. Whether these interactions will occur depends upon the receptor sites available on environmental solids. To this end, we have proposed that mechanism specific probe compounds hold promise for coupled quantitative measures of receptor site availability and baseline sorption free energies. In parallel, careful investigations must be undertaken to develop relationships between compounds structure and free energies of sorption via cation exchange and surface complexation/cation bridging interactions, an area where the coupling of molecular modeling and experimental observations may hold promise. Ultimately, the availability of structure-based relationships to “adjust” mechanism-specific probe sorption measures to estimate the magnitude of sorption interactions for other organic compounds opens the door to having a universal set of probes for characterizing solid phase receptor sites abundance and estimating the extent of sorption of any polyfunctional ionic compound on a given environmental solid. Thus, our new framework allows for both descriptive and predictive characterization of sorption coefficients for a broad classification of organic compound structures, in particular, addressing the current limitations to quantitative Kd prediction for polyfunctional ionic compounds. Thereby, our mechanistic understanding of polyfunctional organic compound sorption will be advanced, enabling better evaluations of fate and exposure risks for this growing class of environmental contaminants. 9221



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