scholarly journals Humic Ion-Binding Model VII: a revised parameterisation of cation-binding by humic substances

2011 ◽  
Vol 8 (3) ◽  
pp. 225 ◽  
Author(s):  
E. Tipping ◽  
S. Lofts ◽  
J. E. Sonke
Keyword(s):  
Organic Matter ◽  
Metal Binding ◽  
Environmental Chemistry ◽  
Equilibrium Constants ◽  
Laboratory Data ◽  
Cation Binding ◽  
Model Parameters ◽  
Ion Binding ◽  
Binding Model ◽  
Mean Values

Environmental contextNatural organic matter exerts a powerful control on chemical conditions in waters and soils, affecting pH and influencing the biological availability, transport and retention of metals. To quantify the reactions, we collated a wealth of laboratory data covering 40 metals and acid–base reactions, and used them to parameterise the latest in a series of Humic Ion-Binding Models. Model VII is now available to interpret field data, and contribute to the prediction of environmental chemistry. AbstractHumic Ion-Binding Model VII aims to predict the competitive reactions of protons and metals with natural organic matter in soils and waters, based on laboratory results with isolated humic and fulvic acids (HA and FA). Model VII is simpler in its postulated multidentate metal binding sites than the previous Model VI. Three model parameters were eliminated by using a formal relationship between monodentate binding to strong- and weak-acid oxygen-containing ligands, and removing factors that provide ranges of ligand binding strengths. Thus Model VII uses a single adjustable parameter, the equilibrium constant for monodentate binding to strong-acid (carboxylate) groups (KMA), for each metallic cation. Proton-binding parameters, and mean values of log KMA were derived by fitting 248 published datasets (28 for protons, 220 for cationic metals). Default values of log KMA for FA were obtained by combining the fitted values for FA, results for HA, and the relationship for different metals between log KMA and equilibrium constants for simple oxygen-containing ligands. The equivalent approach was used for HA. The parameterised model improves on Model VI by incorporating more metals (40), providing better descriptions of metal binding at higher pH, and through more internally consistent parameter values.

scholarly journals Estimation of WHAM7 constants for GaIII, InIII, SbIII and BiIII from linear free energy relationships, and speciation calculations for natural waters

2020 ◽  
Vol 17 (2) ◽  
pp. 140 ◽  
Author(s):  
Edward Tipping ◽  
Montserrat Filella
Keyword(s):  
Organic Matter ◽  
Metal Binding ◽  
Metal Ion ◽  
Natural Waters ◽  
Chemical Speciation ◽  
Equilibrium Constants ◽  
Model Parameters ◽  
Binding Model ◽  
Critical Elements ◽  
Linear Free Energy

Environmental contextNatural organic matter exerts a powerful control on chemical conditions in waters and soils, affecting pH and influencing the biological availability, transport and retention of metals. Modelling can help to predict these effects, but for many metals, model parameters are missing. We report parameters for four technology-critical elements in a chemical speciation model, and consider the chemistries of the elements in natural waters. AbstractWe compiled the equilibrium constants for the interactions of the technology-critical elements (TCEs) GaIII, InIII, SbIII and BiIII with ammonia, fluoride, hydroxyl and ligands with oxygen atoms. We then combined them with predictive equations to estimate parameters for Humic Ion-Binding Model VII, which permits the calculation of metal binding by natural organic matter (fulvic acid, FA, and humic acid, HA). Derived values of the Model VII parameter quantifying the interaction of metal ions with carboxyl-type groups (log KMA) were among the highest estimated so far, as were the values for the parameter (ΔLK2) that quantifies the tendency of the metal ion to interact with softer ligand atoms (N and S). The Windermere Humic Aqueous Model, version 7 (WHAM7), which incorporates Model VII, was then used to estimate the chemical speciation of each TCE element.

Cation binding by acid-washed peat, interpreted with Humic Ion-Binding Model VI-FD

2004 ◽  
Vol 55 (3) ◽  
pp. 433-447 ◽  
Author(s):  
E. J. Smith ◽  
C. Rey-Castro ◽  
H. Longworth ◽  
S. Lofts ◽  
A. J. Lawlor ◽  
...  
Keyword(s):  
Cation Binding ◽  
Ion Binding ◽  
Binding Model

scholarly journals Determination of intrinsic equilibrium constants at alumina/electrolyte interface

2004 ◽  
Vol 69 (12) ◽  
pp. 1063-1072 ◽  
Author(s):  
Zaklina Todorovic ◽  
Slobodan Milonjic
Keyword(s):  
Equilibrium Constants ◽  
Point Of Zero Charge ◽  
Ionization Constants ◽  
Hydroxyl Groups ◽  
Alkali Cations ◽  
Binding Model ◽  
Complexation Constant ◽  
Mean Values ◽  
Surface Hydroxyl ◽  
Electrolyte Interface

Intrinsic ionization and complexation constants at an alumina/electrolyte interface were studied by the site binding model, while the sorption of alkali cations from aqueous solutions was interpreted by the triple-layer model. The surface properties of alumina were investigated by the potentiometric acid-base titrationmethod. The point of zero charge (pHpzc) of alumina obtained by thismethod was found to be 7.2. The obtained mean values of the intrinsic protonation and ionization constants of the surface hydroxyl groups and the intrinsic surface complexation constant, in different electrolytes, are pKinta1 = 4.4, pKinta2 = 9.6 and pKintM+ = 9.5 respectively.

PEST-ORCHESTRA, a tool for optimising advanced ion-binding model parameters: derivation of NICA-Donnan model parameters for humic substances reactivity

2017 ◽  
Vol 14 (1) ◽  
pp. 31 ◽  
Author(s):  
Noémie Janot ◽  
José Paulo Pinheiro ◽  
Wander Gustavo Botero ◽  
Johannes C. L. Meeussen ◽  
Jan E. Groenenberg
Keyword(s):  
Experimental Data ◽  
Fulvic Acid ◽  
Humic Substances ◽  
New Combination ◽  
Model Parameters ◽  
Ion Binding ◽  
Flexible Tool ◽  
Binding Model ◽  
Geochemical Model ◽  
Donnan Model

Environmental contextThe environmental behaviour of trace metals in soils and waters largely depends on the chemical form (speciation) of the metals. Speciation software programs combining models for the binding of metals to soil and sediment constituents are powerful tools in environmental risk assessment. This paper describes a new combination of speciation software with a fitting program to optimise geochemical model parameters that describes proton and metal binding to humic substances. AbstractHere we describe the coupling of the chemical speciation software ORCHESTRA with the parameter estimation software PEST. This combination enables the computation of optimised model parameters from experimental data for the ion binding models implemented in ORCHESTRA. For testing this flexible tool, the NICA-Donnan model parameters for proton-, Cd- and Zn-binding to Laurentian fulvic acid were optimised. The extensive description of the method implementation and the examples provided facilitate the use of this tool by students and researchers. Three procedures were compared which derive the proton binding parameters, differing in the way they constrain the model parameters and in the implementation of the electrostatic Donnan model. Although the different procedures resulted in significantly different sets of model parameters, the experimental data fit obtained was of similar quality. The choice of the relation between the Donnan volume and the ionic strength appears to have a strong influence on the derived set of optimal model parameters, especially on the values of the protonation constants, as well as on the Donnan potential and Donnan volume. Optimised results are discussed in terms of their physico-chemical plausibility. Coherent sets of NICA-Donnan parameters were derived for Cd and Zn binding to Laurentian fulvic acid.

Relating Ion Binding by Fulvic and Humic Acids to Chemical Composition and Molecular Size. 2. Metal Binding

2001 ◽  
Vol 35 (12) ◽  
pp. 2512-2517 ◽  
Author(s):  
Iso Christl ◽  
Chris J. Milne ◽  
David G. Kinniburgh ◽  
Ruben Kretzschmar
Keyword(s):  
Chemical Composition ◽  
Humic Acids ◽  
Metal Binding ◽  
Molecular Size ◽  
Ion Binding

scholarly journals Modeling Northern Hemisphere Summer Heat Extreme Changes and Their Uncertainties Using a Physics Ensemble of Climate Sensitivity Experiments

2006 ◽  
Vol 19 (17) ◽  
pp. 4418-4435 ◽  
Author(s):  
Robin T. Clark ◽  
Simon J. Brown ◽  
James M. Murphy
Keyword(s):  
Structural Changes ◽  
Heat Waves ◽  
Full Range ◽  
Daily Maximum ◽  
Model Parameters ◽  
Mean Values ◽  
Summer Heat ◽  
Modeling Uncertainties ◽  
Physics Ensemble ◽  
Projected Changes

Abstract Changes in extreme daily temperature events are examined using a perturbed physics ensemble of global model simulations under present-day and doubled CO2 climates where ensemble members differ in their representation of various physical processes. Modeling uncertainties are quantified by varying poorly constrained model parameters that control atmospheric processes and feedbacks and analyzing the ensemble spread of simulated changes. In general, uncertainty is up to 50% of projected changes in extreme heat events of the type that occur only once per year. Large changes are seen in distributions of daily maximum temperatures for June, July, and August with significant shifts to warmer conditions. Changes in extremely hot days are shown to be significantly larger than changes in mean values in some regions. The intensity, duration, and frequency of summer heat waves are expected to be substantially greater over all continents. The largest changes are found over Europe, North and South America, and East Asia. Reductions in soil moisture, number of wet days, and nocturnal cooling are identified as significant factors responsible for the changes. Although uncertainty associated with the magnitude of expected changes is large in places, it does not bring into question the sign or nature of the projected changes. Even with the most conservative simulations, hot extreme events are still expected to substantially increase in intensity, duration, and frequency. This ensemble, however, does not represent the full range of uncertainty associated with future projections; for example, the effects of multiple parameter perturbations are neglected, as are the effects of structural changes to the basic nature of the parameterization schemes in the model.

Particle densities of wetland soils in northern Alberta, Canada

2006 ◽  
Vol 86 (1) ◽  
pp. 57-60 ◽  
Author(s):  
T. E. Redding ◽  
K. J. Devito
Keyword(s):  
Organic Matter ◽  
Particle Density ◽  
Physical Property ◽  
Organic Soils ◽  
Wetland Soil ◽  
Loss On Ignition ◽  
Simple Method ◽  
Mean Values ◽  
Northern Alberta ◽  
Wetland Types

Particle density is a fundamental soil physical property, yet values of soil and organic matter particle density (ρs and ρo) vary widely in the literature. We measured particle density of organic soils from five wetland types, and from exposed sediments of drying ponds, in northern Alberta, Canada. Our measured values of organic soil and pond sediment ρs varied widely (1.43–2.39 Mg m-3); however, calculated values of ρo (1.34–1.52 Mg m-3) were relatively constant. The measured and calculated ρs and ρo values were similar to those obtained in published studies using similar methods, but were higher than the values provided in many reference texts. Given the relatively small variability in ρo, the use of mean values of ρo, combined with measurements of organic matter loss-on-ignition, shows promise as a simple method for obtaining reliable estimates of ρs across a range of wetland types. Key words: Particle density, peat, organic matter, wetland soil, loss-on-ignition

Development of an Inverse Plume Model for Mass Eruption Rate in Unsteady Conditions

2021 ◽  
Author(s):  
Stephen A Solovitz
Keyword(s):  
Laboratory Data ◽  
Model Performance ◽  
Volcanic Eruptions ◽  
Reynolds Numbers ◽  
Model Parameters ◽  
Plume Height ◽  
Eruption Rate ◽  
Mass Eruption Rate ◽  
Downstream Effects ◽  
Order Of Magnitude

Abstract Following volcanic eruptions, forecasters need accurate estimates of mass eruption rate (MER) to appropriately predict the downstream effects. Most analyses use simple correlations or models based on large eruptions at steady conditions, even though many volcanoes feature significant unsteadiness. To address this, a superposition model is developed based on a technique used for spray injection applications, which predicts plume height as a function of the time-varying exit velocity. This model can be inverted, providing estimates of MER using field observations of a plume. The model parameters are optimized using laboratory data for plumes with physically-relevant exit profiles and Reynolds numbers, resulting in predictions that agree to within 10% of measured exit velocities. The model performance is examined using a historic eruption from Stromboli with well-documented unsteadiness, again providing MER estimates of the correct order of magnitude. This method can provide a rapid alternative for real-time forecasting of small, unsteady eruptions.

Influence of chlorination on metal binding by dissolved organic matter: A study using Log-transformed differential spectra

Chemosphere ◽  
2014 ◽  
Vol 103 ◽  
pp. 290-298 ◽  
Author(s):  
Mingquan Yan ◽  
Dechao Li ◽  
Junfa Gao ◽  
Jixia Cheng
Keyword(s):  
Organic Matter ◽  
Dissolved Organic Matter ◽  
Metal Binding

scholarly journals SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems

2015 ◽  
Vol 8 (10) ◽  
pp. 3441-3470 ◽  
Author(s):  
J. A. Bradley ◽  
A. M. Anesio ◽  
J. S. Singarayer ◽  
M. R. Heath ◽  
S. Arndt
Keyword(s):  
Organic Matter ◽  
Microbial Biomass ◽  
Microbial Growth ◽  
Model Development ◽  
Biogeochemical Cycling ◽  
Biogeochemical Model ◽  
Model Parameters ◽  
Glacier Forefield ◽  
Unconstrained Model

Abstract. SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework designed to simulate microbial dynamics and biogeochemical cycling during initial ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The rationale for model development arises from decades of empirical observations in glacier forefields, and enables a quantitative and process focussed approach. Here, we provide a detailed description of SHIMMER, test its performance in two case study forefields: the Damma Glacier (Switzerland) and the Athabasca Glacier (Canada) and analyse sensitivity to identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Primary production is responsible for the initial build-up of labile substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter, and nitrogen fixation, are important in sustaining this productivity. The development and application of SHIMMER also highlights aspects of these systems that require further empirical research: quantifying nutrient budgets and biogeochemical rates, exploring seasonality and microbial growth and cell death. This will lead to increased understanding of how glacier forefields contribute to global biogeochemical cycling and climate under future ice retreat.

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