Predicting Organic Cation Sorption Coefficients: Accounting for

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Predicting organic cation sorption coefficients: Accounting for competition from sorbed inorganic cations using a simple probe molecule William C. Jolin, Reaha Goyetche, Katherine Carter, John Medina, Dharni Vasudevan, and Allison A MacKay Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 01 May 2017 Downloaded from http://pubs.acs.org on May 1, 2017

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Environmental Science & Technology

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Predicting organic cation sorption coefficients:

2

Accounting for competition from sorbed inorganic

3

cations using a simple probe molecule

4

William C. Jolin†, Reaha Goyetcheҗ, Katherine Carter җ, John Medina җ, Dharni Vasudevanҗ*,

5

and Allison A. MacKay‡*

6

†

Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT

7

06269 җ

8 9

‡

Department of Civil, Environmental and Geodetic Engineering, The Ohio State University,

10

11

12

Department of Chemistry, Bowdoin College, Brunswick, ME 04011

Columbus, OH 43210

ABSTRACT

With the increasing number of emerging contaminants that are cationic at environmentally

13

relevant pH values, there is a need for robust predictive models of organic cation sorption

14

coefficients (Kd). Current predictive models fail to account for the differences in the identity,

15

abundance, and affinity of surface-associated inorganic exchange ions naturally present at

16

negatively charged receptor sites on environmental solids. To better understand how organic

17

cation sorption is influenced by surface-associated inorganic exchange ions, sorption coefficients

18

of ten organic cations (including eight pharmaceuticals and two simple probe organic amines)

ACS Paragon Plus Environment

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were determined for six homoionic forms of the aluminosilicate mineral, montmorillonite.

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Organic cation sorption coefficients exhibited consistent trends for all compounds across the

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various homoionic clays with sorption coefficients (Kd) decreasing as follows: KdNa+ > KdNH4+ ≥

22

KdK+ > KdCa2+ ≥ KdMg2+ > KdAl3+. This trend for competition between organic cations and

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exchangeable inorganic cations is consistent with the inorganic cation selectivity sequence,

24

determined for exchange between inorganic ions. Such consistent trends in competition between

25

organic and inorganic cations suggested that a simple probe cation, such as

26

phenyltrimethylammonium or benzylamine, could capture soil-to-soil variations in native

27

inorganic cation identity and abundance for the prediction of organic cation sorption to soils and

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soil minerals. Indeed, sorption of two pharmaceutical compounds to 30 soils was better described

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by phenyltrimethylammonium sorption than by measures of benzylamine sorption, effective

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cation exchange capacity alone, or a model from the literature (Droge & Goss, Environ. Sci.

31

Technol., 2013, 47, 14224). A hybrid approach integrating structural scaling factors derived from

32

this literature model of organic cation sorption, along with phenyltrimethylammonium Kd values,

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allowed for estimation of Kd values for more structurally complex organic cations to homoionic

34

montmorillonites and to heteroionic soils (mean absolute error = 0.27 log units). Accordingly,

35

the use of phenyltrimethylammonium as a probe compound was concluded to be a promising

36

means to account for the identity, affinity and abundance of natural exchange ions in the

37

prediction of organic cation sorption coefficients for environmental solids.

38 39

INTRODUCTION

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A growing number of environmental contaminants of interest, including pharmaceuticals,

41

surfactants, and ionic liquids,1 are positively charged under environmentally-relevant pH values,


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creating the need for accurate sorption models for organic cations.2-5 Traditional sorption

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prediction approaches (e.g. EPISUITE6) accommodate only compounds that are neutral, with no

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ionic moieties. In the case of organic cation sorption, positive charge on the amine moiety

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interacts with negative charge sites on aluminosilicate clay mineral and organic matter

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components of environmental solids.3-5,7-12 Local charge neutrality is maintained because the

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sorbing organic cations displace a naturally-occurring inorganic cation from the charged site;

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however, additional sorption energy contributions from the non-charged portions of the organic

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cation (hydrophobic exclusion from the aqueous phase, polar interactions with the solid phase13-

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15

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counterparts for sorption sites at orders of magnitude lower concentration or abundance.17 As a

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result, accurate predictive models for organic cation sorption must integrate both characteristics

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of the environmental solids (site availability) and structural features of the compound itself.

- for more exhaustive listing see ref [16]) allows these compounds to outcompete their inorganic

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To date, the greatest progress toward a quantitative model for organic cation sorption to

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environmental solids has come through the detailed work of Droge and Goss.14,15,18 Their model

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for organic cation sorption to soils integrates environmental solids characteristics through use of

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the solid’s total cation exchange capacity and an attributed cation exchange contribution for the

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organic matter content of the solids. Structural features of the sorbing cations are captured

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through the compound molar volume, amine rank (primary, secondary or tertiary) and corrective

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factors for additional structural moieties, such as multiple rings, -Cl groups, etc. In this model,

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the extent of exchange site to soil aluminosilicate mineral and soil organic matter was separated

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because sorption studies with pure phase minerals and organic matter showed distinct effects of

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compound structure (sign reversal in empirical term) for the amine rank contributions to

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sorption, as well as some differences in correction factors, between the two sorbent types.14,15


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Overall, this approach of separating cation exchange to aluminosilicate minerals and organic

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matter and representing structural feature contributions with relationships developed from pure

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phase sorbents (illite clay and Pahokee peat organic matter) was quite successful in predicting

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organic cation sorption to two representative soils. This success advances prior modeling efforts

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for organic cations that did not include fundamental site density measures5 or appropriate

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structural feature representations.14

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One limitation of the Droge and Goss model is the inability to account for inorganic

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cation identity and abundance at negative charge sites. Earlier, we identified exchangeable

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inorganic cation identity and abundance as a potentially important factor in organic cation

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sorption.16 Droge and Goss’ model development with pure phase sorbents and validation efforts

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with soils were undertaken in the presence of 5 mM CaCl2 that likely yielded Ca2+ to be the

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charge balancing cations in their sorbent systems. Although calcium is an important soil cation,

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the weathering and anthropogenic histories of many soils can yield solids with a mixture of

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inorganic cations. Prior studies of inorganic cation sorption to soils19-21 and organic polymers22

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show clear trends in ‘selectivity’, or relative affinity for the surface, between cations –

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Li+ ≈ Na+ < NH4+ ≈ H+ ≈ K+ < Mg2+ < Ca2+ < Al3+

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that suggest ion identity should play a role in organic cation exchange. From Li+ through to Al3+,

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inorganic cations with increased affinity to soils should impart increased competition with

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sorbing organic cations, thereby yielding reduced sorption coefficients for sorbing organic

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cations. Indeed, this has been demonstrated in the case of Na+ versus Ca2+ as the saturating

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cation: sorption coefficients for Na+-clays and soils are about one order of magnitude greater

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than for Ca2+-clays and soils, a trend that is observed consistently for organic cations,

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independent of sorbate structure.15,22-24 Extension of such comparisons to a broader suite of

(Sequence I)


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inorganic cations has been undertaken only for a small number of cationic pyridine, purine,

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nucleotide and biguanide compounds.22,24 Measured sorption coefficients in these cases

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decreased for homoionic clays with inorganic cations of greater relative affinity for the surface

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according to Sequence I.

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montmorillonite than Ca2+-montmorillonite, indicating that other properties, such as hydration of

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the inorganic cation25-27, may also affect to organic cation sorption. It is unclear from such a

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small dataset whether other inorganic cations impart a consistent influence on organic cation

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sorption for all compound structures. The potential identification of such a consistent

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competition sequence for inorganic cation displacement by organic cations opens the door to

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quantitative integration of inorganic cation identity into organic cation sorption models. To this

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end, we offer that complex variations in inorganic cation identity, affinity and abundance can be

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better accounted for through the use of a cationic probe compound16,28 rather than the

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cumbersome quantitative assessment of concentrations of individual exchange ions on

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environmental solids.

The one exception was lower sorption observed for Mg2+-

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Previously, we have conceptualized that experimentally measured sorption coefficients

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for a cationic probe compound with a simple structure, such as benzylamine or

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phenyltrimethylammonium (PTMA) (structures, Figure S1), could provide a combined measure

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of cation exchange site density and the baseline driving force for sorption to an environmental

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solid while implicitly accounting for competition from naturally-occurring exchangeable

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inorganic cations .16 If a consistent sequence for inorganic cation displacement is noted for a

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wide range of organic cation structures, we propose that the probe compound sorption coefficient

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for a given sorbent should be correlated with sorption coefficients for other organic cations with

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varied structures.

Thus, sorption coefficients for any organic cation, i, (Kid,pred) could be


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predicted from the experimentally-determined sorption coefficient of the probe compound to that

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particular soil (Kd,exptprobe) and a structural scaling factors (Sisoil) that captures the free energy

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differences in sorption arising from structural differences between the organic cation of interest

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and the probe compound: , = ,

×

(1)

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Structural differences, manifest in both hydrophobic and electrostatic contributions to sorption

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interactions, could be determined experimentally or from empirical models.14,15,18 While this

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proposed probe approach may imply the assumption of one negative site ‘type’ in Eq. 1, it does

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still facilitate a hybrid approach in which the influence and distribution site characteristic

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including, sorbed inorganic cation identities and abundance could be captured through Kd,exptprobe,

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and the distinct influence of organic cation structural characteristics on sorption to

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aluminosilicate clay minerals and organic matter (Sisoil) could be integrated explicitly through a

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modified form of the Droge and Goss soil sorption model, for example. Without knowledge of

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the exact framework for Sisoil, a simple structure for the probe compound was conceptualized

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because we anticipated that it would be easier to add adjustments for other moieties (-Cl, -OH,

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etc) to build up to more complex structures than to use a structurally-complex probe that could

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be more representative of all of the potential sorption interactions yet require a more complicated

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adjustment for the structural correction. With the limited application to date of probe compounds

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for predicting sorption of other ionic organic compounds,28 there is a need to evaluate whether

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probe compounds could be used to quantitatively account for the identity and abundance of a

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heterogeneous group of exchangeable inorganic cations, using an extensive soil set. Note that

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our emphasis herein are conditions of low sorbate surface coverage (< 2% sites) where linear

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isotherms are applicable.29


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This study is aimed at improving the predictive capability of organic cation sorption to

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soils. To this end, we (i) identify the influence of exchangeable inorganic cation identity on the

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extent of organic cation sorption and quantify this competitive effect for homoionic

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montmorillonite systems; (ii) establish measures of probe cation sorption (Kd,exptprobe) for

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heteroionic systems (soils) that accesses overall organic cation exchange affinity of a soil or a

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soil mineral, while capturing competition effects from naturally-occurring exchangeable

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inorganic cations, and (iii) develop improved predictive models for organic cation sorption to

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aluminosilicate minerals and soils (Eq. 1) that integrate measures of probe sorption (Kd,exptprobe)

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with scaling factors (Si) delineated by leveraging the Droge and Goss structure-based models for

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sorption to aluminosilicate minerals and organic matter.

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METHODS

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Sorbents and chemicals

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Texas Ca-montmorillonite (STx-1, CEC = 0.844 meq kg-1) was obtained from the Clay

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Minerals Society. Silicon carbide (SiC) was from Alfa Aesar. Thirty soil samples were collected

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from 28 sites across the eastern United States as part of an earlier study by Jones et al.30 Soils

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were previously characterized for native soil pH, effective cation exchange capacity (ECEC), and

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concentrations of exchangeable Na+, K+, Ca2+, Mg2+, and Al3+ (Table S1). Sorbate compounds

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phenyltrimethylammonium (PTMA), benzylamine, serotonin, atenolol, metoprolol, tramadol,

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trimethoprim, propranolol, desipramine, and diltiazem (Figure S1) were from Sigma Aldrich. All

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other chemicals and reagents were ACS grade. Solutions were made with high purity 18.2 MΩ

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water (DI water) from a MilliQ system (Waters).

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Sorption to Homoionic Montmorillonite: Kd Values Obtained by Column Chromatography


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Pulse input column chromatography was used to obtain sorption coefficients for 10 organic

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cations (Figure S1) each with six homoionic (Na+, K+, NH4+, Ca2+, Mg2+, and Al3+)

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montmorillonite systems. Montmorillonite was chosen as a representative aluminosilicate

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mineral because of (i) the pH-independent nature of the cation exchange sites,21(ii) its use in

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many prior studies,4,9,12,31,32 and (iii) similarities in sorbent behavior to other common clay

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minerals.15 Columns were carefully packed with mixtures of montmorillonite (MMT) and inert

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SiC. Following methods detailed and validated previously,33 montmorillonite-to-water ratios of

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19, 5, and 0.75 grams of montmorillonite per liter of column pore water were used in individual

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columns to balance compound retention against peak spreading. A comparative control column

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was packed entirely with SiC to verify that test compounds had no sorptive interactions with this

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inert solid. Column porosity was similar for both the ‘SiC-only’ and ‘SiC-montmorillonite’

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columns because of the small amounts of montmorillonite used.33 Packed columns were loaded

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into a standard HPLC system (Jasco PU-980 pump, AS-950 auto sampler, 40 µL injection loop,

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and MD-1510 multiwavelength detector). Montmorillonite was converted to homoionic Na+,

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NH4+, K+, Ca2+, and Mg2+ forms by flushing the respective column with air-equilibrated (pH 6 ±

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0.3), 15 mM (NaCl, NH4Cl, KCl) or 5 mM (CaCl2, MgCl2) solutions for 24 hrs (2,800 pore

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volumes) before compound injection. Al3+-montmorillonite was created by flushing with 2.5 mM

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AlCl3 adjusted to pH 3 (HCl) to avoid precipitation of Al(OH)3. Flushing solutions were

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designed to have ionic strengths that matched conditions of the Droge and Goss dataset15 and

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they also served as the experimental background eluent solutions for experiments with the

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respective clays. An operating flowrate of 100 µL min-1, previously determined to allow sorptive

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equilibrium to montmorillonite,33 was used for all experiments. All experiments were performed

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at room temperature (25°C).


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The concentrations of test compounds injected into the column were varied from 4.3 × 10-6 to

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2.6 × 10-4 M in a solution that matched the background eluent. Sorption isotherms consisted of

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at least three concentration points that were each measured in triplicate on both the ‘SiC-only’

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and the ‘montmorillonite-SiC’ columns. Absorbance vs. time data collected following each

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injection were exported directly to a MATLAB routine to calculate Kd values using compound

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and tracer retention times as detailed in the Supplemental Information (SI, 3.1). All Kd values

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were assumed to be in the linear range of the isotherm if surface coverage by organic cations was

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less than 2%, two or more initial concentrations had similar Kd values (within 1 standard

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deviation of each other) and skewness values of runs on ‘montmorillonite-SiC’ columns matched

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(within 4%) those on the ‘SiC-only’ column.33 Sorption coefficients for benzylamine, PTMA,

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and desipramine on Ca2+-montmorillonite were re-measured at the end of the study to ensure that

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the columns remained unchanged through the duration of this work.

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confirmed to provide identical retention times and sorption coefficients for these compounds

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indicating that no loss of mass, or irreversible sorption, occurred.

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Sorption to Soils: Kd from Batch Sorption Experiments

All columns were

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Sorption of four organic cations (benzylamine, PTMA, tramadol, and desipramine) to 30

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soils was measured using standard batch experiments. Column chromatography was not utilized

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to evaluate sorption to soils because eluting columns with DI water or a background electrolyte

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(NaCl or CaCl2) would modify the distribution of naturally occurring exchangeable inorganic

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cations on the soil. A predetermined mass of soil (see SI, 3.2, for details) was placed in a 15-mL

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centrifuge tube and 10 mL of 5 × 10-5 M solution (pH 6-7) of the test compound prepared in DI

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water was added. Soil-free reactors, prepared in the same manner, provided a measure of initial

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concentration and allowed us to confirm the absence of other loss processes. Soil-free and soil-


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containing reactors were rotated end-over-end for 18-24 hr (based on preliminary kinetic

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experiments) in the dark to attain sorptive equilibrium. Then, solutions from the soil-free reactors

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and supernatant from the soil-containing reactors were filtered with 0.45 µm nylon filers,

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dispensed into clean HPLC vials and centrifuge tubes for analysis of aqueous organic cation

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concentrations (Cw, mol L-1) and pH, respectively. Organic cation aqueous concentrations were

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measured by high performance liquid chromatography with diode array detector (HPLC-DAD)

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using an Agilent 1100 Series system (see SI for HPLC methods). Corresponding sorbed

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compound concentrations (Cs, mol kg-1) were calculated by difference, and Kd values were then

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obtained as Cs/Cw. Based on our earlier studies29, we note that our experimental conditions were

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designed to ensure that Kd values obtained were in the linear range of sorption isotherm. Batch

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experiments with soils were conducted using organic cation dissolved in DI water to preserve the

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native heteroionic composition of the soil; we expected that the use of a buffer or a background

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electrolyte would change native soil pH and the composition of exchangeable inorganic cations

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associated with the soil. All experiments were performed in triplicate at native soil pH.

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Desorption experiments using BaCl2 were used to confirm that loss from solution was due

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primarily to sorption phenomena.

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RESULTS AND DISCUSSION

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Effect of Cation Identity on Organic Cation Sorption to Homoionic Montmorillonite

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We evaluated whether exchangeable inorganic cations showed a consistent sequence of

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competition across several organic cations by measuring the sorption coefficients of ten organic

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compounds (Figure S1), including eight pharmaceuticals, with six homoionic montmorillonite

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clays. Test organic cations were chosen to have a range of factors that could influence cation


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exchange, including hydrophobic exclusion from the bulk aqueous phase, amine rank and the

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presence of polar groups. These structural differences contributed to a wide range in Kd values

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across a given montmorillonite system (e.g., 83 to 29600 L/kg for Na-MMT, Table S3) even

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though all test organic cations had the same charge of +1. Nevertheless, some important trends

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were evident across the test organic cations. For all the organic cations examined, Kd values for

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sorption to homoionic montmorillonite saturated with monovalent cations (Na-MMT, NH4-

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MMT, K-MMT) were greater than Kd values for divalent homoionic montmorillonite (Ca-MMT

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and Mg-MMT) which in turn were greater than values for montmorillonite saturated with

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trivalent cations (Al-MMT) (Figure 1). The resulting Kd sequence for the test organic cations was

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found to be:

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KdNa-MMT > KdNH4-MMT ≥ KdK-MMT > KdCa-MMT ≥ KdMg-MMT > KdAl-MMT (Sequence II)

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Because variations between KdX-MMT values are an implicit measure of the extent to which the

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exchangeable inorganic cation, Xn+, suppressed organic cation sorption, the trend of cation order

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from left to right in Sequence II represents increased competition for cation exchange sites from

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inorganic cations. This inorganic cation ordering showed a similar pattern as Sequence I for

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exchange between inorganic cations. The one exception to ordering between Sequence II and

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Sequence I occurred for the divalent cations: Mg2+ showed stronger, or similar, competition with

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organic cations than Ca2+ (Sequence II) compared to inorganic cation affinities to cation

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exchange sites (Sequence I). This trend of KdCa-MMT ≥ KdMg-MMT for organic cations has been

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observed previously by others.22,24


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Figure 1. Sorption coefficients (Log Kd) of organic cations to Na+ (grey), NH4+ (black), K+ (red),

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Ca2+ (green), Mg2+ (yellow), and Al3+ (blue) exchanged montmorillonite followed a general

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pattern of decreased sorption with increased inorganic cation charge. Compound numbers refer

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to structures found in Figure S1.

249 250

The experimentally-determined Kd values from our set of test organic compounds were

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used to quantify relative ion affinity constants for each inorganic cation. The ion affinity

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constant, Exion-X, was defined as:

253

= log log

(2)

254

where KdX-MMT (L/kg) is the experimentally determined Kd value for montmorillonite homoionic

255

in cation X. Ca-montmorillonite was chosen as a reference homoionic clay because a detailed

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structural model for organic cation sorption to Ca2+-saturated clay was developed by Droge and

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Goss;15 by definition, Exion-Ca = 0. For the other five cations, Exion-X values were remarkably


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similar across the ten test organic cations. The average values were determined to be Exion-Na =

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0.85 ± 0.06; Exion-NH4 = 0.65 ± 0.12; Exion-K = 0.58 ± 0.13; Exion-Mg = -0.15 ± 0.09 and Exion-Al = -

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0.90 ± 0.13. First, we note that our Exion-Na for Na+ matches well with the +1 log unit offset in

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cation exchange capacity-normalized Kd values recommended by Droge and Goss to translate

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their structure-based organic cation sorption model from Ca2+-saturated to Na+-saturated clays.

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Second, the coefficients of variation for Exion-X ranged from 7% (Na+) to 22% (K+), quantitatively

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supporting our prior hypothesis that sorption of each organic cation was influenced similarly by a

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particular inorganic cation. The only exception was Exion-Mg that varied by 60% across the

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compounds because of the differential effect of Mg2+ on Kd values between compounds 1-7

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(Exion-Mg = -0.17 ± 0.06) and compounds 8-10 (Exion-Mg = -0.017 ± 0.006). Our experimentally-

268

derived Exion-X values allow for simple adjustments to the Droge and Goss model to predict

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organic cation sorption to other homoionic clays by adding the value of Exion-X to log Kd values

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calculated from the Ca2+-clay model. (Note that Droge and Goss define sorption coefficients as

271

normalized to solid cation exchange capacity instead of mass as is our definition here; however,

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application of a constant CEC value as a divisor to the two Kd terms in Eq. 2 yields the same

273

values for the two approaches.) The close similarity in Exion-X values across our test organic

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cations shows that each inorganic cation affects the sorption of organic cations in a consistent

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and predictable manner, regardless of organic cation structure. Importantly, this observation

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supports the promise of using a probe cation to account for inorganic exchange ion identity,

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affinity and abundance in the prediction of organic cation sorption coefficients.

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Delineation of Scaling Factors (Si) and Incorporation of Kd,exptprobe into a Predictive Model for

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Cation Sorption in Homoionic Systems


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Using our data for organic cation sorption to homoionic montmorillonites (Table S3),we

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first validated the concept of using probe compound sorption (Kd,exptprobe), along with a scaling

282

factor (Si), to predict Kd values for other compounds. PTMA was chosen to be the probe

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compound because structural corrections (Si, Eq. 1) would largely be additive to extrapolate to

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other compounds in our test set. Although benzylamine also meets this criteria, the low Kd

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values for this compound resulted in greater relative error (e.g., 30% for Al3+-MMT, Table S3),

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thus favoring PTMA. Here, we implemented a hybrid approach by using Droge and Goss’

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detailed structural model of organic cation sorption15 to calculate structural scaling factors by

288

utilizing differences between molar volume and amine rank for PTMA and organic cation i: log ( ! ) = 1.22(& &'( ) 0.22*+, ± ./ !

(3)

289

where Vxi (L mol-1) is the molar volume, NAii is amine rank or number of hydrogen atoms

290

bonded to the cationic amine group, and CFclay represents corrective factors for compound

291

structural moieties (Table S5). By definition NAi = 0 for PTMA. Sorption coefficients of the

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other nine test compounds (all except PTMA) for the six homoionic clays were predicted with

293

Eq. 1 using Kd,exptPTMA for each clay type, along with scaling factors, Siclay, obtained using Eq. 3.

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The resultant Kd,predX-MMT values were within 0.3 log units of the experimental values (Figure 2).

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We note that predictions for each individual homoionic clay (Xn+-MMT) are uniformly

296

distributed around the 1:1 line, even for Mg2+-MMT that had the most variation in Exion-Mg values

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across the compound set. These observations suggest that there was no bias in the application of

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the probe concept (Eq. 1 with Eq. 3) for a particular homoionic clay.


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Figure 2. Application of PTMA as a probe compound to predict the sorption of other organic

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cations onto MMT showed a strong correlation between predicted and experimental Kd values

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(R2 = 0.97, p < 0.01), indicating that Kd,exptPTMA and Siclay were able to account for competition

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from different inorganic exchange ions in the cases of homoionic Na+ (grey circles), NH4+ (black

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circles), K+ (red circles), Ca2+ (green circles), Mg2+ (yellow circles) and Al3+ (blue circles)

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montmorillonite. Solid line is 1:1 and dashed lines represent ± 0.3 log units.

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A potential source of bias in application of PTMA as a probe to predict organic

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compound sorption to the homoionic montmorillonite surface is the choice of CFclay factors in

308

the calculation of Si (Eq. 3). Our test compounds possessed six structural moieties for which

309

CFclay as defined by Droge and Goss (Table S5) were required. Poorly ascribed correction

310

factors for a given compound would shift predicted Kd,predX-MMT values systematically above or

311

below the 1:1 line (Figure 2). Of all the CFclay factors used, we observed that only the CFclay for

312

ether moieties (-COC-) were ineffective: Predicted Kd values were 2 to 10 times lower than

313

measured values, possibly resulting from overcorrection by assuming additivity when more than

314

one ether moiety was present. Therefore, values in Figure 2 were obtained by setting CFclay = 0


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for -COC- (Table S5). All other CFclay values assigned by Droge and Goss were effective in

316

arriving at our scaling factors. Together, these results indicated that Kd,exptPTMA could be used to

317

account for exchangeable inorganic cation identity in pure phase aluminosilicates without

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explicit measures of exchangeable cation identities or surface abundances.

319 320

Establishing a Hybrid Approach for Using a Probe Compound to Predict Sorption to

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Heteroionic and Heterogeneous Soil Sites

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Soils are heteroionic systems with a variety of inorganic cations balancing negative

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charge at surface sites. Quantitative analysis of inorganic cations displaced in the measurement

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of CEC does reveal the distinct composition of inorganic cations associated with the soil (e.g.,

325

f(Exi), Table S5); however, it is unclear how empirical Exion-X values might be coupled with such

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analyses to apportion the relative competition effects of inorganic soil cations on sorbing organic

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cations. Therefore, we evaluated the potential for using sorption coefficients from a probe

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compound to establish an aggregate measure of inorganic cation competition on aluminosilicate

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mineral-containing soils.

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Evidence that inorganic cation identity and abundance influences organic cation sorption

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to soils was obtained through several regression analyses. First, we performed linear regressions

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of experimental Kd,expt values with soil cation exchange capacity (Fig. 3A, S2A). Experimental

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log Kd,expt values for PTMA, a compound with a simple structure, and tramadol, a

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pharmaceutical, showed correlations with log ECECsoil that were statistically significant (p

Predicting Organic Cation Sorption Coefficients: Accounting for

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