Evaluating Flow Distribution in a Multiaquifer Recharge Well Using an In Situ Flowmeter.

Quantifying the flow rate distribution in a multiple-screen recharge well is relevant to understanding groundwater flow and solute transport behavior in managed aquifer recharge (MAR) operations. In this study, an impeller flowmeter was deployed to measure flow rate distribution in a multiple-screen MAR well under both recharge and pumping conditions screened in the multiple-strata of the Virginia Coastal Plain aquifer system. Preferential flow distribution in the well was observed through the uppermost screens during recharge while flow distribution was more evenly distributed along all screens under pumping conditions. Analysis of flow along individual screens also indicates preferential flow to the upper part of the screen during both recharge and pumping. Comparison of flowmeter results under both recharge and pumping conditions to previous site-specific measurements suggests that the distribution of flow may vary with time, depending on well screen condition and well rehabilitation efforts, and should be monitored over the duration of an MAR project. These results have implications for groundwater quality given that flow distribution in a multiscreen recharge well has profound impact on travel time and on transport modeling if flow is assumed to be steady and consistent under a range of operational conditions.

Resolving the Water Crisis: There's a Way, But Is There the Will?

In this issue paper, the authors refine the definition of water sustainability to account for temporal dynamics and spatial variability, identify specific challenges that must be resolved in the very near future to avoid catastrophic outcomes on levels ranging from economic disruption to survival of mankind, discuss related policy changes and potential effectiveness, and describe several technologies available to achieve water security and sustainability. While water quality certainly poses formidable challenges, in this piece we emphasize and address challenges associated with dynamic water supply availability. Our future as a society will depend upon how well and how rapidly we navigate these challenges in the coming years. As such, the main objective is to encourage private and public sector practitioners to consider revising existing programs, and to update current industry business models in a manner that promotes expedited solutions, alignment of beneficial goals, and motivates the biggest consumers of water to adopt modern data collection and decision support technologies.

Numerical modeling of an abiotic hyporheic mixing-dependent reaction: Chemical evolution of mixing and reactant production zones.

Mixing-dependent reactions occur where groundwater and surface water mix in shallow sediments (hyporheic zone) and can attenuate contaminants along upwelling flowpaths, thus reducing transport to surface water. Here we used MODFLOW/SEAM3D to numerically simulate prior laboratory observations of a mixing-dependent reaction between sodium sulfite (Na2SO3) and dissolved oxygen (DO) to produce sodium sulfate (Na2SO4). This reaction is not common in nature but is used as a surrogate for mixing-dependent DO consuming reactions of environmental significance. We evaluated how location and thickness of mixing zones and reaction product production zones dynamically respond to variations in hydraulic and chemical boundary conditions and reaction kinetic rate. Sensitivity analysis showed that location and thickness of mixing zones and reactant production zones were most sensitive to changes in the balance of hydrologic inflow from groundwater and surface water (inflow ratio). Mixing zone thickness for reactive DO calibrated to experimental data was thinner than that for the "DO tracer" (identical source location and concentration as DO but conservative tracer), indicating that as DO is consumed its mixing zone narrows. The SO4 production zone was consistently thicker than the DO mixing zone. Small changes in mixing/production zone thicknesses were linked to large changes in mass consumed and produced, indicating the potential for simpler field metrics like thickness to act as surrogates for more challenging measurements such as contaminant flux or consumption in monitoring natural attenuation. This study improves understanding of the evolution of hyporheic mixing-dependent reaction zones that occur even under steady state hydraulics, emphasizing their complex controls.

Demonstration of Managed Aquifer Recharge in a Coastal Plain Aquifer: Lessons Learned.

The sustainable water initiative for tomorrow (SWIFT) is a 378,000 m3 /day (100 MGD) managed aquifer recharge (MAR) program designed by the Hampton Roads Sanitation District (HRSD) to rehabilitate the Potomac Aquifer System (PAS) in the Coastal Plain of Eastern Virginia. Groundwater is a primary water source in Eastern Virginia with over 93% of reported use derived from the PAS. Starting in May 2018, HRSD has operated a 3780 m3 /day (1.0 MGD) MAR demonstration facility at the SWIFT Research Center (SWIFT-RC) in Suffolk, Virginia. The primary aim of the SWIFT-RC is to demonstrate, at a meaningful scale, the feasibility of MAR using deep well recharge into confined PAS hydrostratigraphic unit. The SWIFT-RC employs advanced water treatment technology to bring secondary effluent from an HRSD wastewater treatment plant to drinking water standards. Lessons learned include the evaluation and selection of a multiple barrier carbon-based treatment system to ensure water quality and maintain geochemical compatibility between MAR water and native groundwater, and the evaluation and selection of aluminum chlorohydrate for stabilizing aquifer clays immediately around the well to accept the fresher recharge water. The distribution of flow in the SWIFT-RC multiscreen recharge well and associated well injectivity were variable with time resulting from changing conditions in the well. Dynamic recharge well performance was quantified through the combined analysis of intrinsic and artificial tracer transport, in situ flowmeter testing, and water level analysis. Monitoring well nests and a depth-discrete sampling system supported a robust sampling plan to analyze chemical transport and attenuation in SWIFT-RC groundwater.

Upscaled modeling of complex DNAPL dissolution.

A straightforward, upscaled DNAPL mass dissolution model is developed using relatively simple input consisting of characteristic dimensions and saturations of a DNAPL accumulation. Multiple accumulations are aggregated into a single source zone volume. Physically, the dissolution process is a combination of flow through the mass (advective component) and flow around the mass (dispersive component). The contribution of each component is based on initial characteristic length scales and the average initial saturation. Changes over time with the depletion of mass are captured with a changing relative permeability and a power law relationship for the fraction of initial mass remaining. The utility of the upscaled process model is demonstrated with data from three studies: numerical simulation of multiple pools, two-dimensional test cell experiments with mixed architecture and with heterogeneous soil, and a controlled field study of multicomponent DNAPL release and depletion. Use of the model successfully reproduced the observed multistage mass discharge in each study and illuminated the governing processes. The power law exponent was relatively constant for the various conditions and relative permeability changes were integral to the success. The numerical and experimental studies were run to complete mass depletion which the upscaled model matched. The input parameters are minimal and are found in typical DNAPL source zone characterization data.

Hyporheic transverse mixing zones and dispersivity: Laboratory and numerical experiments of hydraulic controls.

Mixing of surface water and groundwater in shallow sediments is important to biogeochemical cycling and contaminant migration, and is often used to define the hyporheic zone. Yet knowledge of mixing processes in hyporheic zones is supported by surprisingly few rigorous lab or field observations, and differ from those in deeper groundwater by presence of enhanced head gradients, sediment heterogeneity, and temporal fluctuations. In a laboratory sediment (sand) tank we photographed a conservative dye to analyze transverse mixing zones between upwelling groundwater and bidirectional hyporheic exchange flows. We then conducted numerical modeling to investigate processes behind observed phenomena and estimate dispersivities. We found that transverse mixing zones were thin (i.e. mixing thickness measured in direction of steepest concentration gradient, δ, less than 5 cm), consistent with a small calibrated transverse dispersivity (~0.1 mm) and prior lab studies conducted at similar scales. In steady-state experiments and simulations, δ and estimated dispersion coefficients increased with the surface water head drop driving exchange flows. Given relatively constant deeper groundwater heads, increased Δh led to increased mixing zone length for both steady-state and transient conditions, indicating larger bedforms or weaker gaining conditions enhance subsurface mixing. However, Peclet number and flux-related dilution index simultaneously increased and decreased, respectively, indicating that enhancement of subsurface advection outpaced that of dispersion. In transient experiments and simulations, δ was greater than for steady-state, probably from temporary addition of longitudinal dispersion. During transient experiments, δ exhibited temporal noise, perhaps due to the mixing zone moving past varying patterns of sediment packing. Our results provide basic knowledge of mixing zone behavior in hyporheic zones with implications for hyporheic zone definitions, solute transport, mixing-dependent reaction, and water quality.

Detailed chemical characterization of the composition and variability of soil gas at remediated residential heating oil discharges.

Underground storage tanks containing petroleum or other hazardous substances are used widely for residential storage of home heating oil. Spills and leaks of fuel from these tanks are common, and resulting subsurface petroleum vapors may pose health risks. However, understanding of this risk is limited by a lack of observational data on the chemical composition of vapors from discharged fuel. We present here the composition of soil gas sampled at 66 remediated residential sites of underground heating oil discharges throughout Virginia using a newly developed data analysis technique that allows characterization of hydrocarbons by carbon number and degree of unsaturation. Measured concentrations of total petroleum hydrocarbons exceeded 100,000 µg/m3 at 12 sites, but its composition varied widely between sites. Concentrations of hydrocarbons from chemical classes differing by more than a few carbon numbers or degrees of unsaturation are found to be poorly correlated. Furthermore, differences in composition are poorly described by metrics expected to indicate subsurface weathering (e.g., discharge year, or ratio of n-heptadecane to pristane). These results suggest that the composition and magnitude of residual contamination at remediated subsurface discharges is driven by rarely documented spill characteristics (e.g., age and composition of source material, discharge rate, etc.).

Characterization of Hydrocarbon Groups in Complex Mixtures Using Gas Chromatography with Unit-Mass Resolution Electron Ionization Mass Spectrometry.

Complex mixtures of hydrocarbons are ubiquitous as petroleum fuels and, consequently, environmental contaminants. Because they contain thousands of individual components with similar molecular structures, detailed chemical characterization of hydrocarbon mixtures relies on advanced analytical techniques that are not accessible to many researchers. Many analyses of hydrocarbon mixtures instead characterize them as "unresolved complex mixtures", with quantification limited to a small number of resolvable components and/or total observed mass within specified volatility ranges. This work develops a new analytical approach to characterize the hydrocarbon component of petroleum and environmental mixtures by "hydrocarbon group" (defined by carbon number, degree of unsaturation and, in certain cases, degree of branching) using gas chromatography coupled to a unit-mass-resolution electron ionization quadrupole mass spectrometer (GC/EI-MS), a standard and widely available instrument. Average mass spectra of hydrocarbons from a widely used spectral library are combined with chromatographic signal representing the molecular ion of each hydrocarbon group to recreate the magnitude and mass spectra of the chromatogram. Characterization of hydrocarbons in diesel fuel by this approach is in good agreement with state-of-the-art techniques relying on high-resolution and fast-response mass spectrometers. Application of this approach to subsurface soil gas samples from remediated sites of underground storage tank spills demonstrates that composition of hydrocarbons in environmental samples varies significantly and that the total signal of samples from contaminated sites may contain a substantial fraction of oxygenated components.

Artificial Intelligence Within Pharmacovigilance: A Means to Identify Cognitive Services and the Framework for Their Validation.

INTRODUCTION: Pharmacovigilance (PV) detects, assesses, and prevents adverse events (AEs) and other drug-related problems by collecting, evaluating, and acting upon AEs. The volume of individual case safety reports (ICSRs) increases yearly, but it is estimated that more than 90% of AEs go unreported. In this landscape, embracing assistive technologies at scale becomes necessary to obtain a higher yield of AEs, to maintain compliance, and transform the PV professional work life. AIM: The aim of this study was to identify areas across the PV value chain that can be augmented by cognitive service solutions using the methodologies of contextual analysis and cognitive load theory. It will also provide a framework of how to validate these PV cognitive services leveraging the acceptable quality limit approach. METHODS: The data used to train the cognitive service were an annotated corpus consisting of 20,000 ICSRS from which we developed a framework to identify and validate 40 cognitive services ranging from information extraction to complex decision making. This framework addresses the following shortcomings: (1) needing subject-matter expertise (SME) to match the artificial intelligence (AI) model predictions to the gold standard, commonly referred to as 'ground truth' in the AI space, (2) ground truth inconsistencies, (3) automated validation of prediction missing context, and (4) auto-labeling causing inaccurate test accuracy. The method consists of (1) conducting contextual analysis, (2) assessing human cognitive workload, (3) determining decision points for applying artificial intelligence (AI), (4) defining the scope of the data, or annotated corpus required for training and validation of the cognitive services, (5) identifying and standardizing PV knowledge elements, (6) developing cognitive services, and (7) reviewing and validating cognitive services. RESULTS: By applying the framework, we (1) identified 51 decision points as candidates for AI use, (2) standardized the process to make PV knowledge explicit, (3) embedded SMEs in the process to preserve PV knowledge and context, (4) standardized acceptability by using established quality inspection principles, and (5) validated a total of 126 cognitive services. CONCLUSION: The value of using AI methodologies in PV is compelling; however, as PV is highly regulated, acceptability will require assurances of quality, consistency, and standardization. We are proposing a foundational framework that the industry can use to identify and validate services to better support the gathering of quality data and to better serve the PV professional.

Artificial Intelligence and the Future of the Drug Safety Professional.

The healthcare industry, and specifically the pharmacovigilance industry, recognizes the need to support the increasing amount of data received from individual case safety reports (ICSRs). To cope with this increase, more healthcare and qualified professionals are required to capture and evaluate the data. To address the evolving landscape, it will be necessary to embrace assistive technologies such as artificial intelligence (AI) at scale. AI in the field of pharmacovigilance will possibly result in the transformation of the drug safety (DS) professional's daily work life and their career development. Celgene's Global Drug Safety and Risk Management (GDSRM) function has established a series of work activities to drive innovation across the pharmacovigilance value chain (Celgene Chrysalis Fact Sheet. https://www.celgene.com/newsroom/media-library/chrysalis-fact-sheet/, 2018). The development of AI in pharmacovigilance raises questions about the possible changes in DS professionals' lives, who may find themselves curious about their future roles in a workplace assisted by AI. We discuss the current state of pharmacovigilance and the DS professional, AI in pharmacovigilance and the potential skillsets a DS professional may require when working with AI. We also describe the results of research conducted at Celgene GDSRM. The objective of the research was to understand the thoughts of pharmacovigilance professionals about their jobs. These results are provided in the form of aggregated responses to interview questions based on a 12-part questionnaire [see the Electronic Supplementary Material (ESM)]. A sample of six DS professionals representing various areas of pharmacovigilance operations were asked a range of questions about their backgrounds, current roles and future expectations. The DS professionals interviewed were, overall, enthusiastic about their job roles potentially changing with AI enhancements. Interviewees suggested that AI would allow for pharmacovigilance resources, time, and skills to shift the work from a volume-based to a value-based focus. The results suggest that pharmacovigilance professionals wish to use their qualifications, skillsets and experience in work that provides more value for their efforts. Machine learning algorithms have the potential to enhance DS professionals' decision-making processes and support more efficient and accurate case processing.

Training Augmented Intelligent Capabilities for Pharmacovigilance: Applying Deep-learning Approaches to Individual Case Safety Report Processing.

INTRODUCTION: Regulations are increasing the scope of activities that fall under the remit of drug safety. Currently, individual case safety report (ICSR) collection and collation is done manually, requiring pharmacovigilance professionals to perform many transactional activities before data are available for assessment and aggregated analyses. For a biopharmaceutical company to meet its responsibilities to patients and regulatory bodies regarding the safe use and distribution of its products, improved business processes must be implemented to drive the industry forward in the best interest of patients globally. Augmented intelligent capabilities have already demonstrated success in capturing adverse events from diverse data sources. It has potential to provide a scalable solution for handling the ever-increasing ICSR volumes experienced within the industry by supporting pharmacovigilance professionals' decision-making. OBJECTIVE: The aim of this study was to train and evaluate a consortium of cognitive services to identify key characteristics of spontaneous ICSRs satisfying an acceptable level of accuracy determined by considering business requirements and effective use in a real-world setting. The results of this study will serve as supporting evidence for or against implementing augmented intelligence in case processing to increase operational efficiency and data quality consistency. METHODS: A consortium of ten cognitive services to augment aspects of ICSR processing were identified and trained through deep-learning approaches. The input data for model training were 20,000 ICSRs received by Celgene drug safety over a 2-year period. The data were manually made machine-readable through the process of transcription, which converts images into text. The machine-readable documents were manually annotated for pharmacovigilance data elements to facilitate the training and testing of the cognitive services. Once trained by cognitive developers, the cognitive services' output was reviewed by pharmacovigilance subject-matter experts against the accepted ground-truth for correctness and completeness. To be considered adequately trained and functional, each cognitive service was required to reach a threshold of F1 or accuracy score ≥ 75%. RESULTS: All ten cognitive services under development have reached an evaluative score ≥ 75% for spontaneous ICSRs. CONCLUSION: All cognitive services under development have achieved the minimum evaluative threshold to be considered adequately trained, demonstrating how machine-learning and natural language processing techniques together provide accurate outputs that may augment pharmacovigilance professionals' processing of spontaneous ICSRs quickly and accurately. The intention of augmented intelligence is not to replace the pharmacovigilance professional, but rather support them in their consistent decision-making so that they may better handle the overwhelming amount of data otherwise manually curated and monitored for ongoing drug surveillance requirements. Through this supported decision-making, pharmacovigilance professionals may have more time to apply their knowledge in assessing the case rather than spending it performing transactional tasks to simply capture the pertinent data within a safety database. By capturing data consistently and efficiently, we begin to build a corpus of data upon which analyses may be conducted and insights gleaned. Cognitive services may be key to an organization's transformation to more proactive decision-making needed to meet regulatory requirements and enhance patient safety.

In-situ determination of field-scale NAPL mass transfer coefficients: Performance, simulation and analysis.

Better estimates of non-aqueous phase liquid (NAPL) mass, its persistence into the future, and the potential impact of source reduction are critical needs for determining the optimal path to clean up sites impacted by NAPLs. One impediment to constraining time estimates of source depletion is the uncertainty in the rate of mass transfer between NAPLs and groundwater. In this study, an innovative field test is demonstrated for the purpose of quantifying field-scale NAPL mass transfer coefficients (kl(N)) within a source zone of a fuel-contaminated site. Initial evaluation of the test concept using a numerical model revealed that the aqueous phase concentration response to the injection of clean groundwater within a source zone was a function of NAPL mass transfer. Under rate limited conditions, NAPL dissolution together with the injection flow rate and the radial distance to monitoring points directly controlled time of travel. Concentration responses observed in the field test were consistent with the hypothetical model results allowing field-scale NAPL mass transfer coefficients to be quantified. Site models for groundwater flow and solute transport were systematically calibrated and utilized for data analysis. Results show kl(N) for benzene varied from 0.022 to 0.60d(-1). Variability in results was attributed to a highly heterogeneous horizon consisting of layered media of varying physical properties.

Modeling the effects of naturally occurring organic carbon on chlorinated ethene transport to a public supply well.

The vulnerability of public supply wells to chlorinated ethene (CE) contamination in part depends on the availability of naturally occurring organic carbon to consume dissolved oxygen (DO) and initiate reductive dechlorination. This was quantified by building a mass balance model of the Kirkwood-Cohansey aquifer, which is widely used for public water supply in New Jersey. This model was built by telescoping a calibrated regional three-dimensional (3D) MODFLOW model to the approximate capture zone of a single public supply well that has a history of CE contamination. This local model was then used to compute a mass balance between dissolved organic carbon (DOC), particulate organic carbon (POC), and adsorbed organic carbon (AOC) that act as electron donors and DO, CEs, ferric iron, and sulfate that act as electron acceptors (EAs) using the Sequential Electron Acceptor Model in three dimensions (SEAM3D) code. SEAM3D was constrained by varying concentrations of DO and DOC entering the aquifer via recharge, varying the bioavailable fraction of POC in aquifer sediments, and comparing observed and simulated vertical concentration profiles of DO and DOC. This procedure suggests that approximately 15% of the POC present in aquifer materials is readily bioavailable. Model simulations indicate that transport of perchloroethene (PCE) and its daughter products trichloroethene (TCE), cis-dichloroethene (cis-DCE), and vinyl chloride (VC) to the public supply well is highly sensitive to the assumed bioavailable fraction of POC, concentrations of DO entering the aquifer with recharge, and the position of simulated PCE source areas in the flow field. The results are less sensitive to assumed concentrations of DOC in aquifer recharge. The mass balance approach used in this study also indicates that hydrodynamic processes such as advective mixing, dispersion, and sorption account for a significant amount of the observed natural attenuation in this system.

Effect of biostimulants on 2,4,6-trinitrotoluene (TNT) degradation and bacterial community composition in contaminated aquifer sediment enrichments.

2,4,6-Trinitrotoluene (TNT) is a toxic and persistent explosive compound occurring as a contaminant at numerous sites worldwide. Knowledge of the microbial dynamics driving TNT biodegradation is limited, particularly in native aquifer sediments where it poses a threat to water resources. The purpose of this study was to quantify the effect of organic amendments on anaerobic TNT biodegradation rate and pathway in an enrichment culture obtained from historically contaminated aquifer sediment and to compare the bacterial community dynamics. TNT readily biodegraded in all microcosms, with the highest biodegradation rate obtained under the lactate amended condition followed by ethanol amended and naturally occurring organic matter (extracted from site sediment) amended conditions. Although a reductive pathway of TNT degradation was observed across all conditions, denaturing gradient gel electrophoresis (DGGE) analysis revealed distinct bacterial community compositions. In all microcosms, Gram-negative γ- or ß-Proteobacteria and Gram-positive Negativicutes or Clostridia were observed. A Pseudomonas sp. in particular was observed to be stimulated under all conditions. According to non-metric multidimensional scaling analysis of DGGE profiles, the microcosm communities were most similar to heavily TNT-contaminated field site sediment, relative to moderately and uncontaminated sediments, suggesting that TNT contamination itself is a major driver of microbial community structure. Overall these results provide a new line of evidence of the key bacteria driving TNT degradation in aquifer sediments and their dynamics in response to organic carbon amendment, supporting this approach as a promising technology for stimulating in situ TNT bioremediation in the subsurface.

Multicomponent NAPL source dissolution: evaluation of mass-transfer coefficients.

Mass transfer rate coefficients were quantified by employing an inverse modeling technique to high-resolution aqueous phase concentration data observed following an experimental release of a multicomponent nonaqueous phase liquid (NAPL) at a field site. A solute transport model (SEAM3D) was employed to simulate advective-dispersive transport over time coupled to NAPL dissolution. Model calibration was demonstrated by accurately reproducing the observed breakthrough times and peak concentrations at multiple observation points, observed mass discharge at pumping wells, and the reported mass depletions for three soluble NAPL constituents. Vertically variable NAPL mass transfer coefficients were derived for each constituent using an optimized numerical solute transport model, ranging from 0.082 to 2.0 day(-1) across all constituents. Constituent-specific coefficients showed a positive correlation with liquid-phase diffusion coefficients. Application of a time-varying mass transfer coefficient as NAPL mass depleted showed limited sensitivity during which over 80% of the most soluble NAPL constituent dissolved from the source. Long-term simulation results, calibrated to the experimental data and rendered in terms of mass discharge versus source mass depletion, exhibited multistage behavior.

Influence of petroleum deposit geometry on local gradient of electron acceptors and microbial catabolic potential.

A field survey was conducted following the Deepwater Horizon blowout and it was noted that resulting coastal petroleum deposits possessed distinct geometries, ranging from small tar balls to expansive horizontal oil sheets. A subsequent laboratory study evaluated the effect of oil deposit geometry on localized gradients of electron acceptors and microbial community composition, factors that are critical to accurately estimating biodegradation rates. One-dimensional top-flow sand columns with 12-h simulated tidal cycles compared two contrasting geometries (isolated tar "balls" versus horizontal "sheets") relative to an oil-free control. Significant differences in the effluent dissolved oxygen and sulfate concentrations were noted among the columns, indicating presence of anaerobic zones in the oiled columns, particularly in the sheet condition. Furthermore, quantification of genetic markers of terminal electron acceptor and catabolic processes via quantitative polymerase chain reaction of dsrA (sulfate-reduction), mcrA (methanogenesis), and cat23 (oxygenation of aromatics) genes in column cores suggested more extensive anaerobic conditions induced by the sheet relative to the ball geometry. Denaturing gradient gel electrophoresis similarly revealed that distinct gradients of bacterial communities established in response to the different geometries. Thus, petroleum deposit geometry impacts local dominant electron acceptor conditions and may be a key factor for advancing attenuation models and prioritizing cleanup.

Volatilization and biodegradation of naphthalene in the vadose zone impacted by phytoremediation.

The combined remediation mechanisms of volatilization and biodegradation in the vadose zone were investigated for naphthalene remediation at a creosote-contaminated site where a poplar tree-based phytoremediation system has been installed. Concurrent field and laboratory experiments were conducted to study the transport and biodegradation of naphthalene in the vadose zone. Soil gas sampling showed that more than 90% of the naphthalene vapors were biodegraded aerobically within 5-10 cm above the water table during the summer months. Peak naphthalene soil gas concentrations were observed in the late summer, corresponding with peak naphthalene aqueous concentrations and the minimum saturated zone thickness. An analytical solution was developed for vapor transport where the diffusion coefficient and first-order biodegradation rate vary vertically in two discrete zones. First-order aerobic biodegradation rates in laboratory columns using unsaturated site soil ranged from 5 to 28 days(-1) with a mean rate of 11 days(-1). The observed naphthalene mass flux at the source (3.3-22 microg cm(-2) d(-1)) was enhanced by aerobic biodegradation and was greater than the mean observed flux in the abiotic control column and the maximum theoretical mass flux by factors of 7 and 28, respectively.

Direct volatilization of naphthalene to the atmosphere at a phytoremediation site.

Phytoremediation systems are known to reduce groundwater contamination by at least three major mechanisms: plant uptake, phytovolatilization, and enhanced rhizosphere bioremediation. The potential for such systems to enhance a fourth remediation pathway--direct surface volatilization of contaminants through the subsurface and into the atmosphere-has not yet been investigated in the field. A vertical flux chamber was used to measure direct surface volatilization of naphthalene over nine months at a creosote-contaminated site in Oneida, Tennessee, where a phytoremediation system of poplar trees was installed in 1997. A maximum flux of 23 microg m(-2) h(-1) was measured in August 2004, and naphthalene removal by the direct volatilization pathway is estimated to be 50 g yr(-1) at this site. Results suggest that direct volatilization fluxes are most strongly affected by the groundwater level (thickness of the saturated zone), soil moisture, and changes in atmospheric pressure. At this site, transpiration and canopy interception resulting from the phytoremediation system significantly reduce the saturated thickness, increasing the vertical concentration gradient of naphthalene in the groundwater and thus increasing the upward diffusive flux of naphthalene through the subsurface. The presence of the trees, therefore, promotes direct volatilization into the atmosphere. This research represents the first known measurement of naphthalene attenuation by the direct volatilization pathway.

Push-pull tests to quantify in situ degradation rates at a phytoremediation site.

Nine push-pull tests (PPTs) were performed to determine in-situ aerobic respiration rates at a creosote-contaminated site and to assess the contribution of hybrid poplar trees to the remediation of polynuclear aromatic hydrocarbons (PAH) in groundwater. PPTs were conducted by injecting a solution containing dissolved oxygen and naphthalene (reactive tracers) with bromide (nonreactive tracer) into wells constructed in a shallow unconfined aquifer. The objective of this study was to determine seasonal variation and spatial differences (contaminated versus uncontaminated areas and treed versus untreed areas) in the rate of consumption of dissolved oxygen. First-order aerobic respiration rates varied from 0.0 (control well) to 1.25 hr(-1), which occurred at a planted area in early summer (June). Rates measured in winter at treed areas were greater by a factor of 3-5 when compared to winter rates determined at nontreed areas of the site. Rates at treed regions were found to increase by over 4 times in summer relative to winter at the same location.

Remediation of polycyclic aromatic hydrocarbon compounds in groundwater using poplar trees.

A seven-year study was conducted to assess the effectiveness of hybrid poplar trees to remediate polycyclic aromatic hydrocarbon (PAH) compounds in soil and groundwater at a creosote-contaminated site. A reduction in the areal extent of the PAH plume was observed in the upper half of the 2-m-thick saturated zone, and PAH concentration levels in the groundwater declined throughout the plume. PAH concentrations began to decline during the period between the third and fourth growing seasons, which coincided with the propagation of the tree roots to the water table region. Remediation was limited to naphthalene and several three-ring PAHs (acenaphthylene and acenaphthene). PAH concentrations in soil and aquifer sediment samples also declined over time; however, levels of four-ring PAHs persisted at the lower depths during the study period. The naphthalene to total PAH concentration ratio in the most contaminated groundwater decreased from >0.90 at the beginning of the second growing season to approximately 0.70 at the end the study. Remediation in the lower region of the saturated zone was limited bythe presence of a 0.3-m-thick layer of creosote present as a dense nonaqueous phase liquid (DNAPL). The nearly steady-state condition of the PAH concentrations observed during the last three years of the study suggests that the effectiveness of the phytoremediation system is limited by the rate of PAH dissolution from the DNAPL source.