Development and sensitivity analysis of a fully kinetic model of sequential reductive dechlorination in groundwater

Groundwater chlorinated solvent plumes remediation from the past to the future: a scientometric and visualization analysis

Contamination of groundwater with chlorinated hydrocarbons has serious adverse effects on human health. As research efforts in this area have expanded, a large body of literature has accumulated. However, traditional review writing suffers from limitations regarding efficiency, quantity, and timeliness, making it difficult to achieve a comprehensive and up-to-date understanding of developments in the field. There is a critical need for new tools to address emerging research challenges. This study evaluated 1619 publications related to this field using VOSviewer and CiteSpace visual tools. An extensive quantitative analysis and global overview of current research hotspots, as well as potential future research directions, were performed by reviewing publications from 2000 to 2022. Over the last 22 years, the USA has produced the most articles, making it the central country in the international collaboration network, with active cooperation with the other 7 most productive countries. Additionally, institutions have played a positive role in promoting the publication of science and technology research. In analyzing the distribution of institutions, it was found that the University of Waterloo conducted the majority of research in this field. This paper also identified the most productive journals, Environmental Science & Technology and Applied and Environmental Microbiology, which published 11,988 and 3253 scientific articles over the past 22 years, respectively. The main technologies are bioremediation and chemical reduction, which have garnered growing attention in academic publishing. Our findings offer a useful resource and a worldwide perspective for scientists engaged in this field, highlighting both the challenges and the possibilities associated with addressing groundwater chlorinated solvent plumes remediation.

On the reliable estimation of sequential Monod kinetic parameters

While dozens of studies have attempted to estimate the Monod kinetic parameters of microbial reductive dechlorination, published values in the literature vary by 2-6 orders of magnitude. This lack of consensus can be attributed in part to limitations of both experimental design and parameter estimation techniques. To address these issues, Hamiltonian Monte Carlo was used to produce more than one million sets of realistic simulated microcosm data under a variety of experimental conditions. These data were then employed in model fitting experiments using a number of parameter estimation algorithms for determining Monod kinetic parameters. Analysis of data from conventional triplicate microcosms yielded parameter estimates characterized by high collinearity, resulting in poor estimation accuracy and precision. Additionally, confidence intervals computed by commonly used classical regression analysis techniques contained true parameter values much less frequently than their nominal confidence levels. Use of an alternative experimental design, requiring the same number of analyses as conventional experiments but comprised of microcosms with varying initial chlorinated ethene concentrations, is shown to result in order-of-magnitude decreases in parameter uncertainty. A Metropolis algorithm which can be run on a typical personal computer is demonstrated to return more reliable parameter interval estimates.

Unraveling biogeochemical complexity through better integration of experiments and modeling

The evolution of groundwater quality in natural and contaminated aquifers is affected by complex interactions between physical transport and biogeochemical reactions. Identifying and quantifying the processes that control the overall system behavior is the key driver for experimentation and monitoring. However, we argue that, in contrast to other disciplines in earth sciences, process-based computer models are currently vastly underutilized in the quest for understanding subsurface biogeochemistry. Such models provide an essential avenue for quantitatively testing hypothetical combinations of interacting, complex physical and chemical processes. If a particular conceptual model, and its numerical counterpart, cannot adequately reproduce observed experimental data, its underlying hypothesis must be rejected. This quantitative process of hypothesis testing and falsification is central to scientific discovery. We provide a perspective on how closer interactions between experimentalists and numerical modelers would enhance this scientific process, and discuss the potential limitations that are currently holding us back. We also propose a data-model nexus involving a greater use of numerical process-based models for a more rigorous analysis of experimental observations while also generating the basis for a systematic improvement in the design of future experiments.

Quantifying Impacts of Microcosm Mass Loss on Kinetic Constant Estimation

Microcosm experiments to assess microbial reductive dechlorination of chlorinated aliphatic hydrocarbons typically experience 5-50% mass loss due to frequent sampling events and diffusion through septa. A literature review, however, reveals that models fit to such experiments for kinetic constant estimation have generally failed to account for experimental mass loss. To investigate possible resultant bias in best-fit parameters, a series of numerical experiments was conducted in which Monod kinetic models with and without mass loss were fit to more than 1300 synthetic data sets, generated using published microcosm data. Models that failed to account for mass loss resulted in significant fitted parameter bias. Bias ranged from 5 to 45% of the parameter magnitude for Monte Carlo simulations with low (approximately 10%) mass loss to 20-120% for simulations with high (approximately 40%) mass loss. In addition, for high mass loss simulations, best-fit values consistently fell along the bounds of the optimization range. These results suggest that failure to properly account for mass loss in microcosms may lead to inaccurate estimation of kinetic constants and may explain some of the literature-reported variability in these parameters. A model is presented that provides a method for including sampling and diffusional mass losses to improve kinetic constant estimation accuracy.

A novel permeable reactive biobarrier for ortho-nitrochlorobenzene pollution control in groundwater: Experimental evaluation and kinetic modelling

Three novel permeable reactive barrier (PRB) materials composed of Cu/Fe with 0.24% and 0.43% (w/w) Cu loadings or Fe⁰ supported on wheat straw were prepared (termed materials E, F and G). These materials exhibited excellent pollutant removal efficiency and physical stability as well as the ongoing release of organic carbon and iron. Column experiments showed that materials E, F and G removed almost 100% of ortho-nitrochlorobenzene (o-NCB) from water. The rates of iron release from the E and F columns exceeded those from column G but this had no significant effect on o-NCB removal. The bacteria that degraded o-NCB in E and F were also different from those in G. The levels of these bacteria in the columns were higher than those in the initial materials, with the highest level in column E. The simultaneous reduction and microbial degradation of o-NCB was observed, with the latter being dominant. A kinetic model was established to simulate the dynamic interactions and accurately predicted the experimental results. Organic carbon from the wheat straw supported the majority of the biomass in each column, which was essential for the bioremediation process. The findings of this study suggest an economically viable approach to mitigating o-NCB pollution.

Multiscale Modeling of Uranium Bioreduction in Porous Media by One-Dimensional Biofilms

We formulate a multiscale mathematical model that describes the bioreduction of uranium in porous media. On the mesoscale we describe the bioreduction of uranium [VI] to uranium [IV] using a multispecies one-dimensional biofilm model with suspended bacteria and thermodynamic growth inhibition. We upscale the mesoscopic (colony scale) model to the macroscale (reactor scale) and investigate the behavior of substrate utilization and production, attachment and detachment processes, and thermodynamic effects not usually considered in biofilm growth models. Simulation results of the reactor model indicate that thermodynamic inhibition quantitatively alters the dynamics of the model and neglecting thermodynamic effects may over- or underestimate chemical concentrations in the system. Furthermore, we numerically investigate uncertainties related to the specific choice of attachment and detachment rate coefficients and find that while increasing the attachment rate coefficient or decreasing the detachment rate coefficient leads to thicker biofilms, performance of the reactor remains largely unaffected.

Model-based evidence for the relevance of microbial community variability to the efficiency of the anaerobic reductive dechlorination of TCE

The composition of mixed dechlorinating communities varies considerably in field and laboratory conditions. Dechlorinators thrive alongside with distinctive populations that help or hinder dechlorination. The variability of the composition of dechlorinating communities inevitably precludes a firm consensus regarding the optimal strategies for biostimulation. This lack of consensus motivated a model-based approach for the investigation of how the variability of the composition of a microbial community impacts the electron donor supply strategies for accelerating chloroethene removal. To this end, a kinetic model accounting for dechlorination in conjunction with cooperative and competing processes was developed. Model parameters were estimated using a multi-experiment, multi-start algorithm and data from research previously performed with two generations of a methane-producing, Dehalococcoides mccartyi-dominated consortium. The two generations of the consortium functioned comparably under maintenance conditions but performed divergently under high electron donor surpluses. The multi-experiment, multi-start algorithm overcame the hurdles of poor parameter identifiability and offered a probable cause for the different behaviors exhibited by each of the two generations of the chloroethene-degrading consortium: modest differences in the make-up of non-dechlorinators, which were minority populations, significantly influenced the fate of the offered electron donor.

Thermodynamic Inhibition in a Biofilm Reactor with Suspended Bacteria

We formulate a biofilm reactor model with suspended bacteria that accounts for thermodynamic growth inhibition. The reactor model is a chemostat style model consisting of a single replenished growth promoting substrate, a single reaction product, suspended bacteria, and wall attached bacteria in the form of a bacterial biofilm. We present stability conditions for the washout equilibrium using standard techniques, demonstrating that analytical results are attainable even with the added complexity from thermodynamic inhibition. Furthermore, we numerically investigate the longterm behaviour. In the computational study, we investigate model behaviour for select parameters and two commonly used detachment functions. We investigate the effects of thermodynamic inhibition on the model and find that thermodynamic inhibition limits substrate utilization/production both inside the biofilm and inside the aqueous phase, resulting in less suspended bacteria and a thinner biofilm.

Process-based modeling of electrokinetic-enhanced bioremediation of chlorinated ethenes

This study presents a process-based modeling analysis of electrokinetic-enhanced bioremediation (EK-Bio) to illuminate the complex interactions between physical, electrostatic and biogeochemical processes occurring during the application of this remediation technique. The features of the proposed model include: (i) multidimensional electrokinetic transport in saturated porous media by electromigration and electroosmosis, (ii) charge interactions, (iii) degradation kinetics, (iv) microbial populations dynamics of indigenous and specialized exogenous degraders, (v) mass transfer limitations, and (vi) geochemical reactions. A scenario modeling investigation is presented, which was inspired by an EK-Bio pilot application conducted in a clayey aquitard at the Skuldelev site (Denmark) contaminated by chlorinated ethenes. Lactate and specialized degraders are delivered under conservative and reactive transport conditions. In the considered setup, transport of lactate using electrokinetics results in more than fourfold increase in the distribution efficiency with respect to a diffusion-only scenario. Moreover, EK transport by electromigration and electroosmosis yields fluxes at least two orders of magnitude larger than diffusive fluxes. Quantitative metrics are also defined and used to assess the amendment distribution and the enhanced contaminant biodegradation in the different conservative and reactive transport scenarios.

Thermodynamic Inhibition in Chemostat Models : With an Application to Bioreduction of Uranium

We formulate a mathematical model of bacterial populations in a chemostat setting that also accounts for thermodynamic growth inhibition as a consequence of chemical reactions. Using only elementary mathematical and chemical arguments, we carry this out for two systems: a simple toy model with a single species, a single substrate, and a single reaction product, and a more involved model that describes bioreduction of uranium[VI] into uranium[IV]. We find that in contrast to most traditional chemostat models, as a consequence of thermodynamic inhibition the equilibria concentrations of nutrient substrates might depend on their inflow concentration and not only on reaction parameters and the reactor's dilution rate. Simulation results of the uranium degradation model indicate that thermodynamic growth inhibition quantitatively alters the solution of the model. This suggests that neglecting thermodynamic inhibition effects in systems where they play a role might lead to wrong model predictions and under- or over-estimate the efficacy of the process under investigation.

Impact of iron- and/or sulfate-reduction on a cis-1,2-dichloroethene and vinyl chloride respiring bacterial consortium: experiments and model-based interpretation

Process understanding of microbial communities containing organohalide-respiring bacteria (OHRB) is important for effective bioremediation of chlorinated ethenes. The impact of iron and sulfate reduction on cis-1,2-dichloroethene (cDCE) and vinyl chloride (VC) dechlorination by a consortium containing the OHRB Dehalococcoides spp. was investigated using multiphase batch experiments. The OHRB consortium was found to contain endogenous iron- and sulfate-reducing bacteria (FeRB and SRB). A biogeochemical model was developed and used to quantify the mass transfer, aquatic geochemical, and microbial processes that occurred in the multiphase batch system. It was determined that the added SRB had the most significant impact on contaminant degradation. Addition of the SRB increased maximum specific substrate utilization rates, k_max, of cDCE and VC by 129% and 294%, respectively. The added FeRB had a slight stimulating effect on VC dechlorination when exogenous SRB were absent, but when cultured with the added SRB, FeRB moderated the SRB's stimulating effect. This study demonstrates that subsurface microbial community interactions are more complex than categorical, guild-based competition for resources such as electron donor.

A modeling approach integrating microbial activity, mass transfer, and geochemical processes to interpret biological assays: An example for PCE degradation in a multi-phase batch setup

The rate at which organic contaminants can be degraded in aquatic environments is not only dependent upon specific degrading bacteria, but also upon the composition of the microbial community, mass transfer of the contaminant, and abiotic processes that occur in the environment. In this study, we present three-phase batch experiments of tetrachloroethene (PCE) degradation by a consortium of organohalide-respiring bacteria, cultivated alone or in communities with iron- and/or sulfate-reducers. We developed a modeling approach to quantitatively evaluate the experimental results, comprised of chemical and biomolecular time series data. The model utilizes the IPhreeqc module to couple multi-phase mass transfer between gaseous, organic and aqueous phases with microbial and aquatic geochemical processes described using the geochemical code PHREEQC. The proposed approach is able to capture the contaminant degradation, the microbial population dynamics, the effects of multi-phase kinetic mass transfer and sample removal, and the geochemical reactions occurring in the aqueous phase. The model demonstrates the importance of aqueous speciation and abiotic reactions on the bioavailability of the substrates. The model-based interpretation allowed us to quantify the reaction kinetics of the different bacterial guilds. The model further revealed that the inclusion of sulfate-reducing bacteria lowers the rate of PCE degradation and that this effect is moderated in the presence of iron-reducing bacteria.

Reductive dechlorination of 1,2-dichloroethane in the presence of chloroethenes and 1,2-dichloropropane as co-contaminants

1,2-Dichloroethane (1,2-DCA) is one of the most abundant manmade chlorinated organic contaminants in the world. Reductive dechlorination of 1,2-DCA by organohalide-respiring bacteria (OHRB) can be impacted by other chlorinated contaminants such as chloroethenes and chloropropanes that can co-exist with 1,2-DCA at contaminated sites. The aim of this study was to evaluate the effect of chloroethenes and 1,2-dichloropropane (1,2-DCP) on 1,2-DCA dechlorination using sediment cultures enriched with 1,2-DCA as the sole chlorinated compound (EA culture) or with 1,2-DCA and tetrachloroethene (PCE) (EB culture), and to model dechlorination kinetics. Both cultures contained Dehalococcoides as most predominated OHRB, and Dehalogenimonas and Geobacter as other known OHRB. In sediment-free enrichments obtained from the EA and EB cultures, dechlorination of 1,2-DCA was inhibited in the presence of the same concentrations of either PCE, vinyl chloride (VC), or 1,2-DCP; however, concurrent dechlorination of dual chlorinated compounds was achieved. In contrast, 1,2-DCA dechlorination completely ceased in the presence of cis-dichloroethene (cDCE) and only occurred after cDCE was fully dechlorinated. In turn, 1,2-DCA did not affect dechlorination of PCE, cDCE, VC, and 1,2-DCP. In sediment-free enrichments obtained from the EA culture, Dehalogenimonas 16S rRNA gene copy numbers decreased 1–3 orders of magnitude likely due to an inhibitory effect of chloroethenes. Dechlorination with and without competitive inhibition fit Michaelis-Menten kinetics and confirmed the inhibitory effect of chloroethenes and 1,2-DCP on 1,2-DCA dechlorination. This study reinforces that the type of chlorinated substrate drives the selection of specific OHRB, and indicates that removal of chloroethenes and in particular cDCE might be necessary before effective removal of 1,2-DCA at sites contaminated with mixed chlorinated solvents.

Evaluating alternate biokinetic models for trace pollutant cometabolism

Mathematical models of cometabolic biodegradation kinetics can improve our understanding of the relevant microbial reactions and allow us to design in situ or in-reactor applications of cometabolic bioremediation. A variety of models are available, but their ability to describe experimental data has not been systematically evaluated for a variety of operational/experimental conditions. Here five different models were considered: first-order; Michaelis-Menten; reductant; competition; and combined models. The models were assessed on their ability to fit data from simulated batch experiments covering a realistic range of experimental conditions. The simulated observations were generated by using the most complex model structure and parameters based on the literature, with added experimental error. Three criteria were used to evaluate model fit: ability to fit the simulated experimental data, identifiability of parameters using a colinearity analysis, and suitability of the model size and complexity using the Bayesian and Akaike Information criteria. Results show that no single model fits data well for a range of experimental conditions. The reductant model achieved best results, but required very different parameter sets to simulate each experiment. Parameter nonuniqueness was likely to be due to the parameter correlation. These results suggest that the cometabolic models must be further developed if they are to reliably simulate experimental and operational data.

Removal processes of disinfection byproducts in subsurface-flow constructed wetlands treating secondary effluent

The removal efficiencies and the kinetics of disinfection byproducts (DBPs) were studied in six greenhouse laboratory-scale SSF CWs. Cattail (Typha latifolia) and its litter (collected from the aboveground samples of cattail in autumn) were used as a potential phytoremediation technology and as a primary substrate, respectively, for DBP removal. Results showed that most of the 11 DBPs (except chloroform and 1, 1-dichloropropanone) were efficiently removed (>90%) in six SSF CWs with hydraulic retention time of 5 d and there were no significant differences among the systems. Under the batch mode, the removal of DBPs in SSF CWs followed first-order kinetics with half-lives of 1.0-770.2 h. As a primary DBP in wastewater effluent, removal efficiencies for chloroform were higher in planted systems than in unplanted ones and plant uptake accounted for more than 23.8% of the removal. Plant litter greatly enhanced the removal of trihalomethanes (THMs) by supplying primary substrates and reducing conditions, and the formation of dichloromethane supported the anaerobic biodegradation of THMs via reductive dechlorination in SSF CWs. Trichloroacetonitrile was completely removed within 10 h in each system and hydrolysis was considered to be the dominant process as there was a rapid formation of the hydrolysis byproduct, trichloroacetamide.

The impact of bioaugmentation on dechlorination kinetics and on microbial dechlorinating communities in subsurface clay till

A molecular study on how the abundance of the dechlorinating culture KB-1 affects dechlorination rates in clay till is presented. DNA extracts showed changes in abundance of specific dechlorinators as well as their functional genes. Independently of the KB-1 added, the microbial dechlorinator abundance increased to the same level in all treatments. In the non-bioaugmented microcosms the reductive dehalogenase gene bvcA increased in abundance, but when KB-1 was added the related vcrA gene increased while bvcA genes did not increase. Modeling showed higher vinyl-chloride dechlorination rates and shorter time for complete dechlorination to ethene with higher initial concentration of KB-1 culture, while cis-dichloroethene dechlorination rates were not affected by KB-1 concentrations. This study provides high resolution abundance profiles of Dehalococcoides spp. (DHC) and functional genes, highlights the ecological behavior of KB-1 in clay till, and reinforces the importance of using multiple functional genes as biomarkers for reductive dechlorination.

An improved cellular automaton method to model multispecies biofilms

Biomass-spreading rules used in previous cellular automaton methods to simulate multispecies biofilm introduced extensive mixing between different biomass species or resulted in spatially discontinuous biomass concentration and distribution; this caused results based on the cellular automaton methods to deviate from experimental results and those from the more computationally intensive continuous method. To overcome the problems, we propose new biomass-spreading rules in this work: Excess biomass spreads by pushing a line of grid cells that are on the shortest path from the source grid cell to the destination grid cell, and the fractions of different biomass species in the grid cells on the path change due to the spreading. To evaluate the new rules, three two-dimensional simulation examples are used to compare the biomass distribution computed using the continuous method and three cellular automaton methods, one based on the new rules and the other two based on rules presented in two previous studies. The relationship between the biomass species is syntrophic in one example and competitive in the other two examples. Simulation results generated using the cellular automaton method based on the new rules agree much better with the continuous method than do results using the other two cellular automaton methods. The new biomass-spreading rules are no more complex to implement than the existing rules.

Self-inhibition can limit biologically enhanced TCE dissolution from a TCE DNAPL

Biodegradation of trichloroethene (TCE) near a Dense Non Aqueous Phase Liquid (DNAPL) can enhance the dissolution rate of the DNAPL by increasing the concentration gradient at the DNAPL-water interface. Two-dimensional flow-through sand boxes containing a TCE DNAPL and inoculated with a TCE dechlorinating consortium were set up to measure this bio-enhanced dissolution under anaerobic conditions. The total mass of TCE and daughter products in the effluent of the biotic boxes was 3-6 fold larger than in the effluent of the abiotic box. However, the mass of daughter products only accounted for 19-55% of the total mass of chlorinated compounds in the effluent, suggesting that bio-enhanced dissolution factors were maximally 1.3-2.2. The enhanced dissolution most likely primarily resulted from variable DNAPL distribution rather than biodegradation. Specific dechlorination rates previously determined in a stirred liquid medium were used in a reactive transport model to identify the rate limiting factors. The model adequately simulated the overall TCE degradation when predicted resident microbial numbers approached observed values and indicated an enhancement factor for TCE dissolution of 1.01. The model shows that dechlorination of TCE in the 2D box was limited due to the short residence time and the self-inhibition of the TCE degradation. A parameter sensitivity analysis predicts that the bio-enhanced dissolution factor for this TCE source zone can only exceed a value of 2 if the TCE self-inhibition is drastically reduced (when a TCE tolerant dehalogenating community is present) or if the DNAPL is located in a low-permeable layer with a small Darcy velocity.