Use of iron-coated sand for removing soluble phosphorus from drainage water.

Mitigation measures are needed for reducing chronic dissolved phosphorus (P) losses from agricultural soils with a legacy of excessive P inputs to surface waters. Since pipe drains are an important pathway for P transport from agricultural soils to surface waters in flat areas, removing P from drainage water can be an effective measure. During a 4.5 year-field experiment, we tested the performance of a pipe drain enveloped with Fe-coated sand for removing soluble P from drainage water. Iron-coated sand is a by-product of the drinking water industry and has a high ability to bind P. The P concentration in the effluent from the enveloped pipe drain remained at a very low level over the entire monitoring period, with a removal percentage amounting to 93% for total P. During the field experiment, the enveloped pipe drain was below the groundwater level for a prolonged time. Nevertheless, no reduction of Fe(III) in the Fe-coated sand occurred during the first two years, most likely due to preferential reduction of Mn oxides present in the coatings of the sand particles, as reflected in elevated effluent Mn concentrations. Thereafter, reductive dissolution of Fe oxides in the coatings caused a gradual increase in the Fe concentration in the enveloped pipe drain effluent over time. Concomitantly, the dissolved Mn concentration decreased, most probably due to the depletion in easily accessible Mn oxides in the Fe-coated sand. The Fe in the Fe-coated sand was identified as silicate-containing ferrihydrite (Fh). The submerged conditions of the enveloped pipe drain neither affected the stability of Fh in the Fe-coated sand nor the ability of this measure to capture P from drainage water. Enveloping pipe drains with Fe-coated sand is an effective method for reducing dissolved P inputs from agricultural soils to surface waters and holds great promise for implementation in practice.

Influence of pH and Dissolved Organic Matter on Iron Speciation and Apparent Iron Solubility in the Peruvian Shelf and Slope Region.

The chemical speciation of iron (Fe) in oceans is influenced by ambient pH, dissolved oxygen, and the concentrations and strengths of the binding sites of dissolved organic matter (DOM). Here, we derived new nonideal competitive adsorption (NICA) constants for Fe(III) binding to marine DOM via pH-Fe titrations. We used the constants to calculate Fe(III) speciation and derive the apparent Fe(III) solubility (SFe(III)app) in the ambient water column across the Peruvian shelf and slope region. We define SFe(III)app as the sum of aqueous inorganic Fe(III) species and Fe(III) bound to DOM at a free Fe (Fe3+) concentration equal to the limiting solubility of Fe hydroxide (Fe(OH)3(s)). A ca. twofold increase in SFe(III)app in the oxygen minimum zone (OMZ) compared to surface waters is predicted. The increase results from a one order of magnitude decrease in H+ concentration which impacts both Fe(III) hydroxide solubility and organic complexation. A correlation matrix suggests that changes in pH have a larger impact on SFe(III)app and Fe(III) speciation than DOM in this region. Using Fe(II) measurements, we calculated ambient DFe(III) and compared the value with the predicted SFe(III)app. The underlying distribution of ambient DFe(III) largely reflected the predicted SFe(III)app, indicating that decreased pH as a result of OMZ intensification and ocean acidification may increase SFe(III)app with potential impacts on surface DFe inventories.

Evaluation of the Single Dilute (0.43 M) Nitric Acid Extraction to Determine Geochemically Reactive Elements in Soil.

Recently a dilute nitric acid extraction (0.43 M) was adopted by ISO (ISO-17586:2016) as standard for extraction of geochemically reactive elements in soil and soil like materials. Here we evaluate the performance of this extraction for a wide range of elements by mechanistic geochemical modeling. Model predictions indicate that the extraction recovers the reactive concentration quantitatively (>90%). However, at low ratios of element to reactive surfaces the extraction underestimates reactive Cu, Cr, As, and Mo, that is, elements with a particularly high affinity for organic matter or oxides. The 0.43 M HNO3 together with more dilute and concentrated acid extractions were evaluated by comparing model-predicted and measured dissolved concentrations in CaCl2 soil extracts, using the different extractions as alternative model-input. Mean errors of the predictions based on 0.43 M HNO3 are generally within a factor three, while Mo is underestimated and Co, Ni and Zn in soils with pH > 6 are overestimated, for which possible causes are discussed. Model predictions using 0.43 M HNO3 are superior to those using 0.1 M HNO3 or Aqua Regia that under- and overestimate the reactive element contents, respectively. Low concentrations of oxyanions in our data set and structural underestimation of their reactive concentrations warrant further investigation.

Modelling metal accumulation using humic acid as a surrogate for plant roots.

Metal accumulation in roots was modelled with WHAM VII using humic acid (HA) as a surrogate for root surface. Metal accumulation was simulated as a function of computed metal binding to HA, with a correction term (E(HA)) to account for the differences in binding site density between HA and root surface. The approach was able to model metal accumulation in roots to within one order of magnitude for 95% of the data points. Total concentrations of Mn in roots of Vigna unguiculata, total concentrations of Ni, Zn, Cu and Cd in roots of Pisum sativum, as well as internalized concentrations of Cd, Ni, Pb and Zn in roots of Lolium perenne, were significantly correlated to the computed metal binding to HA. The method was less successful at modelling metal accumulation at low concentrations and in soil experiments. Measured concentrations of Cu internalized in L. perenne roots were not related to Cu binding to HA modelled and deviated from the predictions by over one order of magnitude. The results indicate that metal uptake by roots may under certain conditions be influenced by conditional physiological processes that cannot simulated by geochemical equilibrium. Processes occurring in chronic exposure of plants grown in soil to metals at low concentrations complicate the relationship between computed metal binding to HA and measured metal accumulation in roots.

The use of assemblage models to describe trace element partitioning, speciation, and fate: a review.

The fate of trace elements in soils, sediments, and surface waters is largely determined by their binding to reactive components, of which organic matter, metal oxides, and clays are considered most important. Assemblage models, combining separate mechanistic complexation models for each of the reactive components, can be used to predict the solid-solution partitioning and speciation of trace elements in natural environments. In the present review, the authors provide a short overview of advanced ion-binding models for organic matter and oxides and of their application to artificial and natural assemblages. Modeling of artificial assemblages of mineral components and organic matter indicates that the interactions between organic and mineral components are important for trace element binding, particularly for oxyanions. The modeling of solid-solution partitioning in natural systems is generally adequate for metal cations but less so for oxyanions, probably because of the neglect of organic matter-oxide interactions in most assemblage models. The characterization of natural assemblages in terms of their components (active organic matter, reactive oxide surface) is key to successful model applications. Improved methods for characterization of reactive components in situ will enhance the applicability of assemblage models. Collection of compositional data for soil and water archetypes, or the development of relationships to estimate compositions from geospatially available data, will further facilitate assemblage model use for predictive purposes.

Reducing phosphorus loading of surface water using iron-coated sand.

Phosphorus losses from agricultural soils is an important source of P in surface waters leading to surface water quality impairment. In addition to reducing P inputs, mitigation measures are needed to reduce P enrichment of surface waters. Because drainage of agricultural land by pipe drainage is an important pathway of P to surface waters, removing P from drainage water has a large potential to reduce P losses. In a field trial, we tested the performance of a pipe drain enveloped with Fe-coated sand, a side product of the drinking water industry with a high ability to bind P, to remove P from the drainage water. The results of this trial, encompassing more than one hydrological season, are very encouraging because the efficiency of this mitigation measure to remove P amounted to 94%. During the trial, the pipe drains were below the groundwater level for a prolonged time. Nevertheless, no reduction of Fe(III) in the Fe-coated sand occurred, which was most likely prevented by reduction of Mn oxides present in this material. The enveloped pipe drain was estimated to be able to lower the P concentration in the effluent to the desired water quality criterion for about 14 yr. Manganese oxides are expected to be depleted after 5 to 10 yr. The performance of the enveloped pipe drain, both in terms of its ability to remove P to a sufficiently low level and the stability of the Fe-coated sand under submerged conditions in the long term, needs prolonged experimental research.

Use of reactive materials to bind phosphorus.

Phosphorus (P) losses from agricultural soils have caused surface water quality impairment in many regions of the world, including The Netherlands. Due to the large amounts of P accumulated in Dutch soils, the generic fertilizer and manure policy will not be sufficient to reach in time the surface water quality standards of the European Water Framework Directive. Additional measures must be considered to further reduce P enrichment of surface waters. One option is to immobilize P in soils or manure or to trap P when it moves through the landscape by using reactive materials with a large capacity to retain P. We characterized and tested two byproducts of the process of purification of deep groundwater for drinking water that could be used as reactive materials: iron sludge and iron-coated sand. Both materials contain low amounts of inorganic contaminants, which also have a low (bio)availability, and bound a large amount of P. We could describe sorption of P to the iron sludge in batch experiments well with the kinetic Freundlich equation (Q = × t (m) × C(n)). Kinetics had a large influence on P sorption in batch and column experiments and should be taken into account when iron-containing materials are tested for their capability to immobilize or trap P. A negative aspect of the iron sludge is its low hydraulic conductivity; even when mixed with pure sand to a mixture containing 20% sludge, the conductivity was very low, and only 10% sludge may be needed before application is possible in filters or barriers for removing P from groundwater. Due to its much higher hydraulic conductivity, iron-coated sand has greater potential for use under field conditions. Immobilizing P could be an option for using iron sludge as a reactive material.

Evaluation of the performance and limitations of empirical partition-relations and process based multisurface models to predict trace element solubility in soils.

Here we evaluate the performance and limitations of two frequently used model-types to predict trace element solubility in soils: regression based "partition-relations" and thermodynamically based "multisurface models", for a large set of elements. For this purpose partition-relations were derived for As, Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb, Sb, Se, V, Zn. The multi-surface model included aqueous speciation, mineral equilibria, sorption to organic matter, Fe/Al-(hydr)oxides and clay. Both approaches were evaluated by their application to independent data for a wide variety of conditions. We conclude that Freundlich-based partition-relations are robust predictors for most cations and can be used for independent soils, but within the environmental conditions of the data used for their derivation. The multisurface model is shown to be able to successfully predict solution concentrations over a wide range of conditions. Predicted trends for oxy-anions agree well for both approaches but with larger (random) deviations than for cations.

Using advanced surface complexation models for modelling soil chemistry under forests: Solling forest, Germany.

Various dynamic soil chemistry models have been developed to gain insight into impacts of atmospheric deposition of sulphur, nitrogen and other elements on soil and soil solution chemistry. Sorption parameters for anions and cations are generally calibrated for each site, which hampers extrapolation in space and time. On the other hand, recently developed surface complexation models (SCMs) have been successful in predicting ion sorption for static systems using generic parameter sets. This study reports the inclusion of an assemblage of these SCMs in the dynamic soil chemistry model SMARTml and applies this model to a spruce forest site in Solling Germany. Parameters for SCMs were taken from generic datasets and not calibrated. Nevertheless, modelling results for major elements matched observations well. Further, trace metals were included in the model, also using the existing framework of SCMs. The model predicted sorption for most trace elements well.

Uncertainty analysis of the nonideal competitive adsorption-donnan model: effects of dissolved organic matter variability on predicted metal speciation in soil solution.

Ion binding models such as the nonideal competitive adsorption-Donnan model (NICA-Donnan) and model VI successfully describe laboratory data of proton and metal binding to purified humic substances (HS). In this study model performance was tested in more complex natural systems. The speciation predicted with the NICA-Donnan model and the associated uncertainty were compared with independent measurements in soil solution extracts, including the free metal ion activity and fulvic (FA) and humic acid (HA) fractions of dissolved organic matter (DOM). Potentially important sources of uncertainty are the DOM composition and the variation in binding properties of HS. HS fractions of DOM in soil solution extracts varied between 14 and 63% and consisted mainly of FA. Moreover, binding parameters optimized for individual FA samples show substantial variation. Monte Carlo simulations show that uncertainties in predicted metal speciation, for metals with a high affinity for FA (Cu, Pb), are largely due to the natural variation in binding properties (i.e., the affinity) of FA. Predictions for metals with a lower affinity (Cd) are more prone to uncertainties in the fraction FA in DOM and the maximum site density (i.e., the capacity) of the FA. Based on these findings, suggestions are provided to reduce uncertainties in model predictions.

Impact of soil properties on critical concentrations of cadmium, lead, copper, zinc, and mercury in soil and soil solution in view of ecotoxicological effects.

Risk assessment for metals in terrestrial ecosystems, including assessments of critical loads, requires appropriate critical limits for metal concentrations in soil and soil solution. This chapter presents an overview of methodologies used to derive critical (i) reactive and total metal concentrations in soils and (ii) free metal ion and total metal concentrations in soil solution for Cd, Pb, Cu, Zn, and Hg, taking into account the effect of soil properties related to ecotoxicological effects. Most emphasis is given to the derivation of critical free and total metal concentrations in soil solution, using available NOEC soil data and transfer functions relating solid-phase and dissolved metal concentrations. This approach is based on the assumption that impacts on test organisms (plants, microorganisms, and soil invertebrates) are mainly related to the soil solution concentration (activity) and not to the soil solid-phase content. Critical Cd, Pb, Cu, Zn, and Hg concentrations in soil solution vary with pH and DOC level. The results obtained are generally comparable to those derived for surface waters based on impacts to aquatic organisms. Critical soil metal concentrations, related to the derived soil solution limits, can be described as a function of pH and organic matter and clay content, and varying about one order of magnitude between different soil types.