Petroleum-contaminated Aquifer Research Articles

Unraveling the mechanisms behind sodium persulphate-induced changes in petroleum-contaminated aquifers’ biogeochemical parameters and microbial communities

Sodium persulphate (PS) is a highly effective oxidising agent widely used in groundwater remediation and wastewater treatment. Although numerous studies have examined the impact of PS with respect to the removal efficiency of organic pollutants, the residual effects of PS exposure on the biogeochemical parameters and microbial ecosystems of contaminated aquifers are not well understood. This study investigates the effects of exposure to different concentrations of PS on the biogeochemical parameters of petroleum-contaminated aquifers using microcosm batch experiments. The results demonstrate that PS exposure increases the oxidation-reduction potential (ORP) and electrical conductivity (EC), while decreasing total organic carbon (TOC), dehydrogenase (DE), and polyphenol oxidase (PO) in the aquifer. Three-dimensional excitation-emission matrix (3D-EEM) analysis indicates PS is effective at reducing fulvic acid-like and humic acid-like substances and promoting microbial metabolic activity. In addition, PS exposure reduces the abundance of bacterial community species and the diversity index of evolutionary distance, with a more pronounced effect at high PS concentrations (31.25 mmol/L). Long-term (90 d) PS exposure results in an increase in the abundance of microorganisms with environmental resistance, organic matter degradation, and the ability to promote functional genes related to biological processes such as basal metabolism, transmission of genetic information, and cell motility of microorganisms. Structural equation modeling (SEM) further confirms that ORP and TOC are important drivers of change in the abundance of dominant phyla and functional genes. These results suggest exposure to different concentrations of PS has both direct and indirect effects on the dominant phyla and functional genes by influencing the geochemical parameters and enzymatic activity of the aquifer. This study provides a valuable reference for the application of PS in ecological engineering.

Evaluation of potential human health risks from exposure to volatile organic compounds in contaminated urban groundwater in the Sava river aquifer, Belgrade, Serbia.

The oil pollutant in the Sava River aquifer in the residential area of Belgrade, Serbia was investigated in order to analyze the extent, origin and spatial distribution of the pollution, with the aim to estimate potential human health risks from exposure to the compounds detected. Analytical methods indicated that the dominant compounds in this oil pollutant were gasoline range organic compounds. Benzene, toluene, ethylbenzene and xylenes (BTEX) were identified as compounds of concern and quantified by headspace gas chromatography. The concentrations of benzene measured at all sampling points were higher than the remediation value while the maximum concentrations of BTEX quantified were among the highest concentrations of these compounds reported in the petroleum-contaminated aquifers in the world. The assessment of the human health risks from exposure to BTEX-covered industrial scenario for adult receptors and residential scenario for adult receptors and children. The exposure routes analyzed were dermal contact with and ingestion of contaminated water, considering both cancer and non-cancer effects. The analysis of the lifetime incremental cancer risk indicated the potential for adverse health effects for human exposure at the investigated location, and because of that it was interpreted as an unacceptable risk level or risks of high priority which required immediate consideration for remedial measures at this location. A complete set of mitigation measures was proposed including: groundwater decontamination treatment, installation of filters for tap water, development of the system for monitoring of BTEX in the groundwater and development of the emergency response capacities at this location.

K-strategy species plays a pivotal role in the natural attenuation of petroleum hydrocarbon pollution in aquifers

The natural attenuation of petroleum hydrocarbons is inseparable from the action of microorganisms, while the degradation methods and ecological strategies of microorganisms in petroleum-contaminated aquifers are still under debate. In the present study, 16 S rRNA sequencing and quantitative real-time polymerase chain reaction were used to assess the potential microbial degradation of petroleum hydrocarbons, and the ecological strategy of microorganisms under petroleum stress was analyzed through a co-occurrence network. The results showed that the microbial community in sediments exhibit higher efficiency and stability and stronger ecological function than that in groundwater. Keystone species coordinated with the community to execute ecosystem processes and tended to choose a K-strategy to survive, with the aquifer sediment being the main site of petroleum hydrocarbon degradation. Under natural conditions, the presence of petroleum hydrocarbons at concentrations higher than 126 μg kg-1 and 5557 μg kg-1 was not conducive to the microbial degradation of polycyclic aromatic hydrocarbons and alkanes, respectively. These results can be used as a reference for an enhanced bioremediation of contaminated groundwater. Overall, these findings provide support to managers for developing environmental management strategies.

Arsenic in Petroleum-Contaminated Groundwater near Bemidji, Minnesota Is Predicted to Persist for Centuries

We used a reactive transport model to investigate the cycling of geogenic arsenic (As) in a petroleum-contaminated aquifer. We simulated As mobilization and sequestration using surface complexation reactions with Fe(OH)3 during petroleum biodegradation coupled with Fe-reduction. Model results predict that dissolved As in the plume will exceed the U.S. and EU 10 µg/L drinking water standard for ~400 years. Non-volatile dissolved organic carbon (NVDOC) in the model promotes As mobilization by exerting oxygen demand, which maintains anoxic conditions in the aquifer. After NVDOC degrades, As re-associates with Fe(OH)3 as oxygenated conditions are re-established. Over the 400-year simulation, As transport resembles a “roll front” in which: (1) arsenic sorbed to Fe(OH)3 is released during Fe-reduction coupled to petroleum biodegradation; (2) dissolved As resorbs to Fe(OH)3 at the plume’s leading edge; and (3) over time, the plume expands, and resorbed As is re-released into groundwater. This “roll front” behavior underscores the transience of sorption as an As attenuation mechanism. Over the plume’s lifespan, simulations suggest that As will contaminate more groundwater than benzene from the oil spill. At its maximum, the model simulates that ~5.7× more groundwater will be contaminated by As than benzene, suggesting that As could pose a greater long-term water quality threat than benzene in this petroleum-contaminated aquifer.

Insights into Biodegradation Related Metabolism in an Abnormally Low Dissolved Inorganic Carbon (DIC) Petroleum-Contaminated Aquifer by Metagenomics Analysis.

In petroleum-contaminated aquifers, biodegradation is always associated with various types of microbial metabolism. It can be classified as autotrophic (such as methanogenic and other carbon fixation) and heterotrophic (such as nitrate/sulfate reduction and hydrocarbon consumption) metabolism. For each metabolic type, there are several key genes encoding the reaction enzymes, which can be identified by metagenomics analysis. Based on this principle, in an abnormally low dissolved inorganic carbon (DIC) petroleum-contaminated aquifer in North China, nine groundwater samples were collected along the groundwater flow, and metagenomics analysis was used to discover biodegradation related metabolism by key genes. The major new finding is that autotrophic metabolism was revealed, and, more usefully, we attempt to explain the reasons for abnormally low DIC. The results show that the methanogenesis gene, Mcr, was undetected but more carbon fixation genes than nitrate reduction and sulfate genes were found. This suggests that there may be a considerable number of autotrophic microorganisms that cause the phenomenon of low concentration of dissolved inorganic carbon in contaminated areas. The metagenomics data also revealed that most heterotrophic, sulfate, and nitrate reduction genes in the aquifer were assimilatory sulfate and dissimilatory nitrate reduction genes. Although there was limited dissolved oxygen, aerobic degrading genes AlkB and Cdo were more abundant than anaerobic degrading genes AssA and BssA. The metagenomics information can enrich our microorganic knowledge about petroleum-contaminated aquifers and provide basic data for further bioremediation.

Microbial effects on hydraulic conductivity estimation by single-well injection tests in a petroleum-contaminated aquifer

Single-well injection tests in a petroleum-contaminated region stimulate microbial growth and cause bioclogging because of the intrusion of elevated dissolved oxygen (DO), which may affect the hydraulic conductivity (K) estimation. In this study, we developed a mathematical model considering multispecies and multiphase reactive transport and bioclogging for a single-well injection test in a confined aquifer to investigate the microbial effects on parameter estimation. The finite-difference method was used to solve the model. The temporal heads in the injection well in both cases of clean and petroleum-contaminated aquifers were compared. The results indicated that the bioclogging led to an abnormal bulge of the drawdown-time curve at an intermediately late time of injection. Based on sensitivity analysis and Cooper-Jacob straight-line fitting associated with the least square method, the underestimation degree of K was 17.7% with default parameters, 11.9% with double injection rate Q, 31.1% with double maximum biomass growth rate μmax,j and 39.5% with double initial contaminant concentration C2ini. Moreover, introducing an approximate Damköhler number indicated that increasing Q reduced the underestimation by flushing and diluting the essential materials for microbial growth to the downstream and that larger C2ini and μmax,j resulted in an increase in underestimation due to the increase in favorable conditions and strong growth ability of microbes. Finally, we suggest that when petroleum contamination is inevitable in a single-well injection test, moderate increases in Q and the test duration can reduce the underestimation degree of K to a considerable extent.

A bilevel groundwater management model with minimization of stochastic health risks at the leader level and remediation cost at the follower level

Traditional single-objective programs cannot deal with the tradeoffs between the decision makers who represent different perspectives and have inconsistent decision goals. Multi-objective ones can hardly represent a complex dominant-subordinate relationship between the leader and the follower. This study presents a new bilevel programming model with considering leader–follower-related health-risk and economic goals for optimal groundwater remediation management. The bilevel model is formulated by integrating health-risk assessment and environmental standards (the leader or the environmental concern) and remediation cost (the follower or the economic concern) into a general framework. In addition, stochastic uncertainty in health risk assessment is considered into the decision-making process. The developed bilevel model is then applied to a petroleum-contaminated aquifer in Canada. Results indicate that the performance of bilevel programming can not only meet the low remediation cost as the expectation from the follower but also simultaneously conform to the low contamination level as the expectation from the leader. Furthermore, comparative analyses show that the bilevel model with two-level concerns has the advantage of maximizing the interests and satisfaction degrees of decision makers, which can avoid the extreme results generated from the single-level models.

In‐Situ Sonication for Enhanced Recovery of Aquifer Microbial Communities

Sampling methods for characterization of microbial communities in aquifers should target both suspended and attached microorganisms (biofilms). We investigated the effectiveness and reproducibility of low-frequency (200 Hz) sonication pulses on improving extraction efficiency and quality of microorganisms from a petroleum-contaminated aquifer in Studen (Switzerland). Sonication pulses at different power levels (0.65, 0.9, and 1.1 kW) were applied to three different groundwater monitoring wells. Groundwater samples extracted after each pulse were compared with background groundwater samples for cell and adenosine tri-phosphate concentration. Turbidity values were obtained to assess the release of sediment fines and associated microorganisms. The bacterial community in extracted groundwater samples was analyzed by terminal-restriction-fragment-length polymorphism and compared with communities obtained from background groundwater samples and from sediment cores. Sonication enhanced the extraction efficiency up to 13-fold, with most of the biomass being associated with the sediment fines extracted with groundwater. Consecutive pulses at constant power were decreasingly effective, while pulses with higher power yielded the best results both in terms of extraction efficiency and quality. Our results indicate that low-frequency sonication may be a viable and cost-effective tool to improve the extraction of microorganisms from aquifers, taking advantage of existing groundwater monitoring wells.

A Multiobjective Optimisation Model for Groundwater Remediation Design at Petroleum Contaminated Sites

This study proposes a fuzzy multi-objective model for groundwater remediation in petroleum-contaminated aquifers. The optimisation system is designed based on the PAT technology, and includes two objectives (i.e. total pumping rate and average post-remedial contaminant concentration). The relationship between pumping rates and contamination concentrations at all monitoring wells after remediation are determined by a proxy model, which integrates simulation, inference, and optimisation technologies and is composed of intercept, linear, interactive, and quadratic options. Fuzzy algorithms are used to solve the formulated multi-objective optimisation problem to find optimal solutions. The model is then applied to a petroleum-contaminated aquifer in western Canada. The trade-off and λ analyses of the results indicate that the fuzzy multi-objective model has great potential in groundwater remediation applications as it can: (1) provide reliable groundwater remediation strategies, (2) reduce computational costs in the optimization processes, and (3) balance the trade-off between remediation costs and remediation outcomes.

Estimating In Situ Biodegradation Rates of Petroleum Hydrocarbons and Microbial Population Dynamics by Performing Single-Well Push–Pull Tests in a Fractured Bedrock Aquifer

The single-well push–pull test (SWPPT) was adapted to quantify in situ aerobic respiration and denitrification rates and to assess microbial population dynamics in a petroleum-contaminated fractured bedrock aquifer. Among three test wells, significant dissolved oxygen (DO) consumption was observed only in one well, with average zero- and first-order rate coefficients of 0.32 ± 0.63 and 7.07 ± 13.85 mmol L−1 day−1, respectively. Of the four test wells, significant NO3 − consumption was noted in three wells. The average zero- and first-order rate coefficients were 2.87 ± 2.21 and 11.83 ± 7.99 mmol L−1 day−1, respectively. These results indicate that NO3 − was more effectively consumed within this fractured bedrock aquifer. Significant DO or NO3 − (electron acceptors (EAs)) consumption, the limited contribution of Fe(II) to overall EAs consumption, the production of dissolved CO2 during aerobic respiration and denitrification tests, and N2O production strongly suggest that the EAs consumption was largely due to microbial activity. Detection of Variovorax paradox, benzene-degrading culture, and 28 novel microbial species after the addition of O2 or NO3 − suggests that EA injection into a fractured rock aquifer may stimulate aerobic or denitrifying petroleum-degrading microbes. Therefore, SWPPT may be useful for quantifying in situ aerobic respiration and denitrification rates and for assessing microbial population dynamics in petroleum-contaminated fractured bedrock aquifers.

Anaerobic Benzene Oxidation by Geobacter Species

The abundance of Geobacter species in contaminated aquifers in which benzene is anaerobically degraded has led to the suggestion that some Geobacter species might be capable of anaerobic benzene degradation, but this has never been documented. A strain of Geobacter, designated strain Ben, was isolated from sediments from the Fe(III)-reducing zone of a petroleum-contaminated aquifer in which there was significant capacity for anaerobic benzene oxidation. Strain Ben grew in a medium with benzene as the sole electron donor and Fe(III) oxide as the sole electron acceptor. Furthermore, additional evaluation of Geobacter metallireducens demonstrated that it could also grow in benzene-Fe(III) medium. In both strain Ben and G. metallireducens the stoichiometry of benzene metabolism and Fe(III) reduction was consistent with the oxidation of benzene to carbon dioxide with Fe(III) serving as the sole electron acceptor. With benzene as the electron donor, and Fe(III) oxide (strain Ben) or Fe(III) citrate (G. metallireducens) as the electron acceptor, the cell yields of strain Ben and G. metallireducens were 3.2 × 10(9) and 8.4 × 10(9) cells/mmol of Fe(III) reduced, respectively. Strain Ben also oxidized benzene with anthraquinone-2,6-disulfonate (AQDS) as the sole electron acceptor with cell yields of 5.9 × 10(9) cells/mmol of AQDS reduced. Strain Ben serves as model organism for the study of anaerobic benzene metabolism in petroleum-contaminated aquifers, and G. metallireducens is the first anaerobic benzene-degrading organism that can be genetically manipulated.

A Multi-Objective Optimal Model for a Petroleum-Contaminated Aquifer Groundwater Remediation in Western Canada

During the groundwater has been suffered from varies degrees pollution. It needs an approach to help decision maker to determine remediation strategies. In this study, a groundwater multi-objective model that includes two objectives (i.e. total remediation cost and average concentration after remediation) is proposed and successfully applied to a petroleum-contaminated aquifer located in western Canada. It can determine a remediation strategy through optimal software MATLAB after convert multi-objective into a non-linear objective using α liner weighting method.

Quasi-Monte Carlo based global uncertainty and sensitivity analysis in modeling free product migration and recovery from petroleum-contaminated aquifers

This paper presents a global uncertainty and sensitivity analysis (GUSA) framework based on global sensitivity analysis (GSA) and generalized likelihood uncertainty estimation (GLUE) methods. Quasi-Monte Carlo (QMC) is employed by GUSA to obtain realizations of uncertain parameters, which are then input to the simulation model for analysis. Compared to GLUE, GUSA can not only evaluate global sensitivity and uncertainty of modeling parameter sets, but also quantify the uncertainty in modeling prediction sets. Moreover, GUSA's another advantage lies in alleviation of computational effort, since those globally-insensitive parameters can be identified and removed from the uncertain-parameter set. GUSA is applied to a practical petroleum-contaminated site in Canada to investigate free product migration and recovery processes under aquifer remediation operations. Results from global sensitivity analysis show that (1) initial free product thickness has the most significant impact on total recovery volume but least impact on residual free product thickness and recovery rate; (2) total recovery volume and recovery rate are sensitive to residual LNAPL phase saturations and soil porosity. Results from uncertainty predictions reveal that the residual thickness would remain high and almost unchanged after about half-year of skimmer-well scheme; the rather high residual thickness (0.73–1.56m 20 years later) indicates that natural attenuation would not be suitable for the remediation. The largest total recovery volume would be from water pumping, followed by vacuum pumping, and then skimmer. The recovery rates of the three schemes would rapidly decrease after 2 years (less than 0.05m3/day), thus short-term remediation is not suggested.

Monitoring the Metabolic Status of Geobacter Species in Contaminated Groundwater by Quantifying Key Metabolic Proteins with Geobacter-Specific Antibodies

Simple and inexpensive methods for assessing the metabolic status and bioremediation activities of subsurface microorganisms are required before bioremediation practitioners will adopt molecular diagnosis of the bioremediation community as a routine practice for guiding the development of bioremediation strategies. Quantifying gene transcripts can diagnose important aspects of microbial physiology during bioremediation but is technically challenging and does not account for the impact of translational modifications on protein abundance. An alternative strategy is to directly quantify the abundance of key proteins that might be diagnostic of physiological state. To evaluate this strategy, an antibody-based quantification approach was developed to investigate subsurface Geobacter communities. The abundance of citrate synthase corresponded with rates of metabolism of Geobacter bemidjiensis in chemostat cultures. During in situ bioremediation of uranium-contaminated groundwater the quantity of Geobacter citrate synthase increased with the addition of acetate to the groundwater and decreased when acetate amendments stopped. The abundance of the nitrogen-fixation protein, NifD, increased as ammonium became less available in the groundwater and then declined when ammonium concentrations increased. In a petroleum-contaminated aquifer, the abundance of BamB, an enzyme subunit involved in the anaerobic degradation of mono-aromatic compounds by Geobacter species, increased in zones in which Geobacter were expected to play an important role in aromatic hydrocarbon degradation. These results suggest that antibody-based detection of key metabolic proteins, which should be readily adaptable to standardized kits, may be a feasible method for diagnosing the metabolic state of microbial communities responsible for bioremediation, aiding in the rational design of bioremediation strategies.

A simulation-based fuzzy chance-constrained programming model for optimal groundwater remediation under uncertainty

In this study a simulation-based fuzzy chance-constrained programming (SFCCP) model is developed based on possibility theory. The model is solved through an indirect search approach which integrates fuzzy simulation, artificial neural network and simulated annealing techniques. This approach has the advantages of: (1) handling simulation and optimization problems under uncertainty associated with fuzzy parameters, (2) providing additional information (i.e. possibility of constraint satisfaction) indicating that how likely one can believe the decision results, (3) alleviating computational burdens in the optimization process, and (4) reducing the chances of being trapped in local optima. The model is applied to a petroleum-contaminated aquifer located in western Canada for supporting the optimal design of groundwater remediation systems. The model solutions provide optimal groundwater pumping rates for the 3, 5 and 10 years of pumping schemes. It is observed that the uncertainty significantly affects the remediation strategies. To mitigate such impacts, additional cost is required either for increased pumping rate or for reinforced site characterization.

Diffusional and microbial isotope fractionation of methane during gas push–pull tests

A field method called gas push–pull test (GPPT) was previously developed for in-situ quantification of methane (CH 4) oxidation by soil microorganisms. We examined whether natural-abundance stable carbon-isotope analysis of CH 4, a common approach used to measure in-situ bioconversions, could be used as a quantitative tool to complement the GPPT method. During GPPTs strong isotope fractionation of CH 4 due to molecular diffusion can occur. This effect was observed in laboratory experiments regardless of the GPPTs’ advective component (i.e., for different injection/extraction rates). Numerical simulations showed that if a GPPT is applied in soils with low microbial CH 4 oxidation activities, isotope fractionation may be dominated by molecular diffusion rather than by consumption. Because diffusional and microbial isotope fractionation of CH 4 occur simultaneously during a GPPT, CH 4 isotope data alone from a single GPPT cannot be used to assess the bioconversion process. However, microbial fractionation may be estimated if the extent of diffusional fractionation is known. This can be achieved either by conducting two sequential GPPTs, with microbial activity being inhibited in the second test, or by estimating physical transport processes via co-injected tracers’ gas analysis. We present a case study, in which we re-analyzed GPPTs previously performed in the unsaturated zone above a petroleum-contaminated aquifer. At this field site the combination of sequential GPPTs, stable carbon-isotope analysis of CH 4, and a modeling approach, which considers diffusion and microbial CH 4 oxidation, was a powerful tool to estimate in situ both apparent Michaelis–Menten kinetic constants and the microbial kinetic isotope effect.

An integrated simulation, inference, and optimization method for identifying groundwater remediation strategies at petroleum-contaminated aquifers in western Canada

This study advances an integrated simulation, inference, and optimization method (ISIOM) for optimizing groundwater remediation systems. SIOM has the advantages of (i) automotive screening of potential explanatory variables (e.g., the pumping rates at various remediation wells), (ii) providing a flexible manner for investigating the linear, interactive, and quadratic effects of operating conditions on the benzene levels, and (iii) mitigating the computational efforts in optimization processes. The method is applied to a petroleum-contaminated site in western Canada for identifying the optimal remediation strategies under a given set of remediation durations and environmental standard levels. To examine the effect of pumping duration on contaminants removing efficiency, 4 duration options are considered including 5, 10, 15, and 20 years, respectively. The results indicate that the pumping duration would have effect on the optimized scheme. It is suggested that the 10-year duration would be more desirable than the 15-year one. The simulation results demonstrate that the peak benzene concentrations would be reduced to satisfy the environmental standard when the optimal remediation strategy is carried out.

Subsurface clade of Geobacteraceae that predominates in a diversity of Fe(III)-reducing subsurface environments

There are distinct differences in the physiology of Geobacter species available in pure culture. Therefore, to understand the ecology of Geobacter species in subsurface environments, it is important to know which species predominate. Clone libraries were assembled with 16S rRNA genes and transcripts amplified from three subsurface environments in which Geobacter species are known to be important members of the microbial community: (1) a uranium-contaminated aquifer located in Rifle, CO, USA undergoing in situ bioremediation; (2) an acetate-impacted aquifer that serves as an analog for the long-term acetate amendments proposed for in situ uranium bioremediation and (3) a petroleum-contaminated aquifer in which Geobacter species play a role in the oxidation of aromatic hydrocarbons coupled with the reduction of Fe(III). The majority of Geobacteraceae 16S rRNA sequences found in these environments clustered in a phylogenetically coherent subsurface clade, which also contains a number of Geobacter species isolated from subsurface environments. Concatamers constructed with 43 Geobacter genes amplified from these sites also clustered within this subsurface clade. 16S rRNA transcript and gene sequences in the sediments and groundwater at the Rifle site were highly similar, suggesting that sampling groundwater via monitoring wells can recover the most active Geobacter species. These results suggest that further study of Geobacter species in the subsurface clade is necessary to accurately model the behavior of Geobacter species during subsurface bioremediation of metal and organic contaminants.

Mineralogic Control on Abundance and Diversity of Surface-Adherent Microbial Communities

In this study, we investigated the role of mineral-bound P and Fe in defining microbial abundance and diversity in a carbon-rich groundwater. Field colonization experiments of initially sterile mineral surfaces were combined with community structure characterization of the attached microbial population. Silicate minerals containing varying concentrations of P (∼1000 ppm P) and Fe (∼4 wt % Fe 2 O3), goethite (FeOOH), and apatite [Ca5(PO4)3(OH)] were incubated for 14 months in three biogeochemically distinct zones within a petroleum-contaminated aquifer. Phospholipid fatty acid analysis of incubated mineral surfaces and groundwater was used as a measure of microbial community structure and biomass. Microbial biomass on minerals exhibited distinct trends as a function of mineralogy depending on the environment of incubation. In the carbon-rich, aerobic groundwater attached biomass did not correlate to the P- or Fe- content of the mineral. In the methanogenic groundwater, however, biomass was most abundant on P-containing minerals. Similarly, in the Fe-reducing groundwater a correlation between Fe-content and biomass was observed. The community structure of the mineral-adherent microbial population was compared to the native groundwater community. These two populations were significantly different regardless of mineralogy, suggesting differentiation of the planktonic community through attachment, growth, and death of colonizing cells. Biomarkers specific for dissimilatory Fe-reducing bacteria native to the aquifer were identified only on Fe-containing minerals in the Fe-reducing groundwater. These results demonstrate that the trace nutrient content of minerals affects both the abundance and diversity of surface-adherent microbial communities. This behavior may be a means to access limiting nutrients from the mineral, creating a niche for a particular microbial population. These results suggest that heterogeneity of microbial populations and their associated activities in subsurface environments extend to the microscale and cautions over-interpretation of highly sample-dependent measurements in the context of interpreting field data.

Models to Determine First‐Order Rate Coefficients from Single‐Well Push‐Pull Tests

Push-pull tests (PPTs) have been successfully employed to quantify various microbially mediated processes in the subsurface. Current models for determining first-order rate coefficients (k) from PPTs assume complete and instantaneous mixing of injected test solution in the portion of the aquifer investigated by the test, i.e., the system is treated like a well-mixed reactor. Here we present two alternative models to estimate k that are based on different mixing assumptions, i.e., plug-flow and variably mixed reactor models. Rate coefficients estimated by the models were compared using a sensitivity analysis and numerical simulations of PPTs. Results indicated that all models yielded reasonably accurate k estimates (errors < 13%), while best accuracy (errors < 1%) was obtained using the variably mixed reactor model. The well-mixed reactor model generally overestimated true (simulation input) k values, whereas true k values were consistently underestimated by the plug-flow reactor model. However, estimates of k obtained with the latter models bracketed true k values in all cases. As the variably mixed reactor model is more difficult to apply, we suggest using the well-mixed and plug-flow reactor models to obtain intervals for k estimates that will encompass true k values with high certainty. In an example application, we used all models to reanalyze a published PPT data set to obtain k estimates for nitrate consumption in a petroleum-contaminated aquifer. Similar results were obtained for all three models (relative differences < 10% between k estimates), indicating that all three models are robust tools for estimating k values from PPT experimental data.