Measuring and Removing Dissolved Metals from Stormwater in Highly Urbanized Areas (2014) / Chapter Skim
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11 3.1 Introduction 3.1.1 Metal Speciation The fate and transport of metals in natural surface waters is highly dependent on the properties of the particular metal, the solution chemistry of the water (i.e., pH, ionic strength, redox state, and presence of biotic, organic, and inorganic ligands) , and interactions with resident particulate matter in the system.
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12 summarizes the concentration of trace elements in major rivers across the world. Average concentrations of selected elements are presented in Table 3-2.
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13 mg/L of metal ion in solution) , and the TSS concentration.
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14 heterogeneity of natural organic matter has significant impacts on its reactivity. The organic matter found in natural aquatic systems is a complex mixture of partially decomposed vegetation, animal matter, and other decaying parent material.
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15 the natural water (allocthanous sources)
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16 and reactivity of humic substances, there is still a lack of consensus as to the nature of these complex materials (Hayes and Clapp 2001; Perminova et al.
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17 Regardless of which model of humic substances emerges from the on-going inquiry, it is clear that these humic substances provide functional groups and hydrophobic moieties that can interact with surfaces and dissolved metals ions in solution. These interactions can significantly impact the mobility and toxicity of metal ions in water.
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18 partitioning. For the average suspended solid concentration of 350 mg/L, only the most mobile elements (e.g., Na, B, Se, As)
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19 lished in the literature and maintained in NIST databases (Martell and Smith 1974)
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20 For example, the first hydrolysis reaction of Fe+3 [written with its waters of hydration as Fe(H2O)
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22 adsorptive properties of the metal and transport across biotic membranes. 3.2.2 Complexation in the Presence of Chelating Agents In many natural systems multidentate ligands or chelating agents are present.
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23 humic and fulvic acid binding is typically characterized using a range of ligand sites that vary with respect to their binding strength. Many researchers have employed small, monodentate organic acids such as those shown in Figure 3-16 to characterize weak binding of metals to fulvic acid, and multidentate ligands such as phthalate, salicylate, citrate, and oxy-succinate to quantify the strong binding sites (Leenheer et al.
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24 and phenolic functional groups with metal cations increases with pH, decreases with metal ion concentration, and increases with humic acid concentration. Recent studies have suggested that acid polysaccharides participate in metal binding in colloidal organic matter and that binding of metals to humic acids greater than 1000 molecular weight units (Daltons)
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25 Over the past several decades several modeling approaches have evolved that have shown potential for predicting metal ion binding to NOM in these complex systems. The key to developing these models is to incorporate the chemical heterogeneity by providing a distribution of sites, competition among metals and protons, and a sub-model that describes the activity corrections resulting from the charge associated with the metal-ligand complexes (Milne 2000)
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26 which both humic and inorganic complexation were included using Model V and Model VI. The modeling effort incorporated competition with Mg, Al, Ca, Fe(II)
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27 precipitation of a chromium hydroxide solid (Gillham et al. 1994; Wilkin et al.
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28 to deprotonate completely, forming the oxyanions AsO3 3-, SeO3 2-, and CrO4 2-. These basic oxyanions undergo acid/base chemistry, forming either di- or tri-protic acid.
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29 While the importance of redox chemistry is evident for redox active metals, it is important to recognize that while metals such as Zn and Cd are not directly influenced by the redox conditions of a system, their fate is dependent on the redox state of elements such as sulfur. In a reducing environment, rich in electrons, sulfate is reduced to sulfide and metal sulfides are extremely insoluble.
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30 the lack of compatibility between the crystal lattices. Both of these studies emphasize the importance of lattice compatibility for nucleation.
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31 more stable phase (Peltier et al.
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32 where ≡S represents a generalized surface site. The pH at which the concentration of [≡SO-]
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33 use a single set of diprotic acidity constants to describe proton release from these surfaces. This approach has been questioned as of late, and significant progress has been made that demonstrates that differentiating adsorption to different site types yields significant improvements in model fits to metal ion adsorption to geothites (Villalobos and Perez-Gallegos 2008; Villalobos et al.
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34 Model – DLM) show the non-linearity of the isotherms and the importance of incorporating pH into modeling approaches.
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35 Organic acids also adsorb to mineral surfaces. A number of researchers have studied the adsorption of organic acids and shown that they form inner sphere complexes that can affect both adsorption and dissolution rates of minerals (Ali and Dzombak 1996; Hwang et al.
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36 and organic acid adsorption; removal decreases with increasing pH and increased fulvic acid shifts the adsorption edge to lower pH (Filius et al.
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37 a plane located further from the surface (the b plane) , or within the diffuse layer depending on the affinity of the sorbing ion for the surface.
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38 The sorption of cations may also be strongly dependent on the presence of competing ions and ligands that can either compete for adsorption sites, or alter the speciation in solution through the formation of non-sorbing aqueous complexes. Stokes (2009)
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40 successfully applied the DLM to mineral assemblages containing amorphous iron oxide, quartz and kaolinite. Limitations in the modeling to the quartz component were attributed to failure of the DLM to capture the ionic strength effects.
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41 independent pathway that does not involve the pathway shown in Figure 3-36 in which dissociation of the complex to the free metal ion precedes uptake by a coordination site on the cell surface. This can include the transmembrane transport of lipophilic complexes [such as Hg(CH3)
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42 species in the bulk solution and the biotic ligand. Campbell et al.
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43 for predicting chemical speciation in water. The thermodynamic constants for complexation of metal ions with inorganic ligands, organic acids, and well-characterized anthropogenic ligands have been incorporated into databases that are tied to these programs.
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44 development at the surface from first principles. Others have focused on the application of more simplistic versions of SCMs that capture the trends in metal ion sorption behavior and the extent of sorption as a function of system conditions in complex laboratory systems and field systems.
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