A Stochastic Regression Approach to Analyzing Thermodynamic Uncertainty in Chemical Speciation Modeling

Weber, Christopher L.; VanBriesen, Jeanne M.; Small, Mitch

doi:10.1021/es0523035

Cited by 22 publications

(15 citation statements)

References 21 publications

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“…The approach thereby overcomes some of the bias introduced by a single detection window approach (Gledhill and Buck, 2012;Pizeta et al, 2015). Our approach in this study was empirical, and further rigor could be achieved with a statistically sound optimization of the results, once basic parameters such as the number and acidity of marine DOM binding sites were known with greater certainty (e.g., Weber et al, 2006). We found that incorporation of an inert phase was required in order to calculate Fe(NN) 3 concentrations to within an order of magnitude of measured Fe(NN) 3 concentrations in samples with high dissolved iron (Figure 5).…”

Section: The Nica-donnan Approachmentioning

confidence: 99%

Influence of Ocean Acidification on the Organic Complexation of Iron and Copper in Northwest European Shelf Seas; a Combined Observational and Model Study

et al. 2016

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The pH of aqueous solutions is known to impact the chemical speciation of trace metals. In this study we conducted titrations of coastal seawaters with iron and copper at pH 7.91, 7.37, and 6.99 (expressed on the total pH scale). Changes in the concentration of iron and copper that complexed with the added ligands 1-nitroso-2-napthol and salicylaldoxime respectively were determined by adsorptive cathodic stripping voltammetry-competitive ligand equilibrium (AdCSV-CLE). Interpretation of the results, assuming complexation by a low concentration of discrete ligands, showed that conditional stability constants for iron complexes increased relative to inorganic iron complexation as pH decreased by approximately 1 log unit per pH unit, whilst those for copper did not change. No trend was observed for concentrations of iron and copper complexing ligands over the pH range examined. We also interpreted our titration data by describing chemical binding and polyelectrolytic effects using non-ideal competitive adsorption in Donnan-like gels (NICA-Donnan model) in a proof of concept study. The NICA-Donnan approach allows for the development of a set of model parameters that are independent of ionic strength and pH, and thus calculation of metal speciation can be undertaken at ambient sample pH or the pH of a future, more acidic ocean. There is currently a lack of basic NICA-Donnan parameters applicable to marine dissolved organic matter (DOM) so we assumed that the measured marine dissolved organic carbon could be characterized as terrestrial fulvic acids. Generic NICA-Donnan parameters were applied within the framework of the software program visual MINTEQ and the metal-added ligand concentrations [MeAL] calculated for the AdCSV-CLE conditions. For copper, calculated [MeAL] using the NICA-Donnan model for DOM were consistent with measured [MeAL], but for iron an inert fraction with kinetically inhibited dissolution was required in addition to the NICA-Donnan model in order to approximate the trends observed in measured [MeAL]. We calculated iron and copper speciation in Northwest European shelf water samples at ambient alkalinity and projected increased pCO 2 concentrations as a demonstration of the potential of the approach.

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Section: The Nica-donnan Approachmentioning

confidence: 99%

Influence of Ocean Acidification on the Organic Complexation of Iron and Copper in Northwest European Shelf Seas; a Combined Observational and Model Study

et al. 2016

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“…The use of MCMC methods in numerical water quality modeling is still rather limited but is anticipated to increase due to the significant advantages of the method for certain applications (5,6,(24)(25)(26). The Metropolis-Hastings algorithm (23) and the adaptive version of it (26,27) which we use in the MCMC simulation, are based on "guided" random walk in the parameter space.…”

Section: Model Uncertainty Analysis and Calibration: Mcmc Methodmentioning

confidence: 99%

Modeling the Effects and Uncertainties of Contaminated Sediment Remediation Scenarios in a Norwegian Fjord by Markov Chain Monte Carlo Simulation

Saloranta

Armitage

Haario

et al. 2007

Environ. Sci. Technol.

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Multimedia environmental fate models are useful tools to investigate the long-term impacts of remediation measures designed to alleviate potential ecological and human health concerns in contaminated areas. Estimating and communicating the uncertainties associated with the model simulations is a critical task for demonstrating the transparency and reliability of the results. The Extended Fourier Amplitude Sensitivity Test(Extended FAST) method for sensitivity analysis and Bayesian Markov chain Monte Carlo (MCMC) method for uncertainty analysis and model calibration have several advantages over methods typically applied for multimedia environmental fate models. Most importantly, the simulation results and their uncertainties can be anchored to the available observations and their uncertainties. We apply these techniques for simulating the historical fate of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) in the Grenland fjords, Norway, and for predicting the effects of different contaminated sediment remediation (capping) scenarios on the future levels of PCDD/Fs in cod and crab therein. The remediation scenario simulations show that a significant remediation effect can first be seen when significant portions of the contaminated sediment areas are cleaned up, and that increase in capping area leads to both earlier achievement of good fjord status and narrower uncertainty in the predicted timing for this.

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“…Stochastic approaches can be utilized for correction of stability constants when the chemical environment of a system substantially deviates from original laboratory conditions (e.g. Weber et al 2006).…”

Section: Modelling Uncertaintiesmentioning

confidence: 99%

Methodological approaches for fractionation and speciation to estimate trace element bioavailability in engineered anaerobic digestion ecosystems: An overview

Hullebusch¹,

Guibaud

Simon

et al. 2016

Critical Reviews in Environmental Science and Technology

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Optimal supply of trace elements (TE) is a prerequisite for microbial growth and activity in anaerobic digestion (AD) bioprocesses. However, the required concentrations and ratios of essential TE for AD biotechnologies strongly depend on prevailing operating conditions as well as feedstock composition. Furthermore, TE in AD bioreactors undergo complex physicochemical reactions and may be present as free ions, complex bound or as precipitates depending on pH, or on the presence of sulfur compounds or organic macromolecules. To overcome TE deficiency, various commercial mineral products are typically applied to AD processes. The addition of heavy metals poses the risk of overdosing operating systems, which may be toxic to microbial consortia and ultimately the environment. Adequate supplementation, therefore, requires appropriate knowledge not only about the composition, but also on the speciation and bioavailability of TE. However, very little is yet fully understood on this specific issue. Evaluations of TE typically only include the measurement of total TE concentrations but do not consider the chemical forms in which TE exist. Thus detailed information on bioavailability and potential toxicity cannot be provided. This review provides an overview of the state of the art in approaches to determine bioavailable TE in anaerobic bioprocesses, including sequential fractionation and speciation techniques. Critical aspects and considerations, including with respect to sampling and analytical procedures, as well as mathematical modeling, are examined. The approaches discussed in this review are based on our experiences and on previously published studies in the context of the “COST Action 1302: European Network on Ecological Roles of Trace Metals in Anaerobic Biotechnologies.

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A Stochastic Regression Approach to Analyzing Thermodynamic Uncertainty in Chemical Speciation Modeling

Cited by 22 publications

References 21 publications

Influence of Ocean Acidification on the Organic Complexation of Iron and Copper in Northwest European Shelf Seas; a Combined Observational and Model Study

Influence of Ocean Acidification on the Organic Complexation of Iron and Copper in Northwest European Shelf Seas; a Combined Observational and Model Study

Modeling the Effects and Uncertainties of Contaminated Sediment Remediation Scenarios in a Norwegian Fjord by Markov Chain Monte Carlo Simulation

Methodological approaches for fractionation and speciation to estimate trace element bioavailability in engineered anaerobic digestion ecosystems: An overview

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