Trimethylbenzoic acids as metabolite signatures in the biogeochemical evolution of an aquifer contaminated with jet fuel hydrocarbons

Evolution of trimethylbenzoic acids in the KC-135 aquifer at the former Wurtsmith Air Force Base (WAFB), Oscoda, MI was examined to determine the functionality of trimethylbenzoic acids as key metabolite signatures in the biogeochemical evolution of an aquifer contaminated with JP-4 fuel hydrocarbons. Changes in the composition of trimethylbenzoic acids and the distribution and concentration profiles exhibited by 2,4,6- and 2,3,5-trimethylbenzoic acids temporally and between multilevel wells reflect processes indicative of an actively evolving contaminant plume. The concentration levels of trimethylbenzoic acids were 3-10 orders higher than their tetramethylbenzene precursors, a condition attributed to slow metabolite turnover under sulfidogenic conditions. The observed degradation of tetramethylbenzenes into trimethylbenzoic acids obviates the use of these alkylbenzenes as non-labile tracers for other degradable aromatic hydrocarbons, but provides rare field evidence on the range of high molecular weight alkylbenzenes and isomeric assemblages amenable to anaerobic degradation in situ. The coupling of actual tetramethylbenzene loss with trimethylbenzoic acid production and the general decline in the concentrations of these compounds demonstrate the role of microbially mediated processes in the natural attenuation of hydrocarbons and may be a key indicator in the overall rate of hydrocarbon degradation and the biogeochemical evolution of the KC-135 aquifer.     

An assessment of natural biotransformation of petroleum hydrocarbons and chlorinated solvents at an aquifer plume transect

Field biogeochemical characterization and laboratory microcosm studies were performed to assess the potential for future biotransformation of trichloroethylene (TCE) and toluene in a plume containing petroleum hydrocarbons and chlorinated solvents at the former Wurtsmith Air Force Base in Oscoda, MI. In situ terminal electron accepting processes (TEAPs), contaminant composition and microbial phylogeny were studied at a plume transect 100 m downgradient of the source. The presence of reduced electron acceptors, relevant microbial communities, and elevated dissolved methane and carbon dioxide concentrations at the transect, as well as downgradient accumulation of BTEX metabolites and dechlorination products, indicated that past or current reductive dechlorination at the transect was likely driven by BTEX biodegradation in the methanogenic zone. However, TCE and toluene mineralization in sediment-groundwater microcosms without added electron acceptors did not exceed 5% during 300 days of incubation and was nearly invariant with original sediment TEAP, even following amendments of nitrogen and phosphorus. Mineralization rates were on the order of 0.0015-0.03 mumol/g day. After 8 months, microcosms showed evidence of methanogenesis, but CH4 and CO2 production arose from the degradation of contaminants other than toluene. Cis-dichloroethylene was observed in only one methanogenic microcosm after more than 500 days. It appears likely that spatially and temporally dynamic redox zonation at the plume transect will prevent future sustained reductive dehalogenation of highly chlorinated solvents, for during the course of a year, the predominant TEAP at the highly contaminated water table shifted from methanogenesis to iron- and sulfate-reduction. It is recommended that biotransformation studies combine considerations of long-term, spatially relevant changes in redox zonation with laboratory-scale studies of electron donor utilization and cometabolic substrate transformation to yield a more accurate assessment of natural bioattenuation of specific pollutants in aquifers contaminated by undefined organic waste mixtures.     

Coupled oxidation of aromatic hydrocarbons by horseradish peroxidase and hydrogen peroxide

The oxidation capability of horseradish peroxidase (HRP) and hydrogen peroxide (H2O2) coupled oxidation of aromatic hydrocarbons (o-xylene-d10 and naphthalene-d8) was investigated. Batch experiments were conducted using horseradish peroxidase prepared in potassium phosphate buffer in the presence of H2O2. The oxidation of aromatic hydrocarbon was tested as a function of HRP at a fixed concentration of H2O2, and as a function of the concentration of H2O2 at a constant HRP activity (4000 units/ml). The mass removal of o-xylene-d10 and naphthalene-ds increased with increasing HRP enzymatic activity, and up to 54% and 51% of mass removal were observed for o-xylene-d10 and naphthalene-d8, respectively. Increasing the concentration of H2O2 resulted in increased mass removal of aromatic hydrocarbons.     

Cokriging optimization of monitoring network configuration based on fuzzy and non-fuzzy variogram evaluation

A number of optimization approaches regarding monitoring networkdesign and sampling optimization procedures have been reported inthe literature. Cokriging Estimation Variance (CEV) is a usefuloptimization tool to determine the influence of the spatial configuration of monitoring networks on parameter estimations. Itwas used in order to derive a reduced configuration of a nitrateconcentration monitoring well network. The reliability of the reduced monitoring configuration suffers from the uncertainties caused by the variographer's choices and several inherent assumptions. These uncertainties can be described considering thevariogram parameters as fuzzy numbers and the uncertainties by means of membership functions.Fuzzy and non-fuzzy approaches were used to evaluate differencesamong well network configurations. Both approaches permitted estimates of acceptable levels of information loss for nitrate concentrations in the monitoring network of the aquifer of the Plain of Modena, Northern Italy. The fuzzy approach was found torequire considerably more computational time and numbers of wellsat comparable level of information loss.     

A Jackknife Approach to Examine Uncertainty and Temporal Change in the Spatial Correlation of a VOC Plume

The application of geostatistics to spatial interpolation of time-invariant properties in ground-water studies (such as transmissivity or aquifer thickness) is well documented. The use of geostatistics on time-variant conditions such as ground-water quality is also becoming more commonplace. Unfortunately, the detection of temporal changes in spatial correlation through direct comparison of experimental semivariograms is difficult due to the uncertainty in sample semivariograms constructed from field data. This paper discusses the use of the jackknife approach to estimate confidence limits of semivariograms of trichloroethane (TC) and other volatile organic compounds (VOC) in contaminated ground-water in northern Illinois. Examination of the spread of the confidence limits about the semivariograms created from two types of sampling networks are discussed.     

Network design factors for assessing temporal variability in ground-water quality

Benchmark major ions and nutrients data were collected biweekly for about two years at 12 wells at two sites in a shallow sand and gravel aquifer in west-central Illinois. The purpose of the study was to explore the time series properties of ground-water quality data collected at a relatively high sampling frequency. A secondary purpose was to determine the relative magnitudes of natural and sampling-related sources of variance in ground-water quality time series. The absence of this kind of information has severely hindered the design of ground-water sampling programs in the past.An autocorrelation analysis showed that the median sampling frequency for which the predicted ratio of effective independent sample size to total sample size was 0.5 (50% sampling redundancy) ranged from 6 to 14 samples per year. For a predicted ratio of effective independent sample size to total sample size of 0.9 (10% sampling redundancy) the sampling frequency ranged from 3 to 6 samples per year. This suggests that, for the wells sampled, sampling frequencies much higher than monthly can result in considerable loss of information, and may not be cost effective. Care was taken in the design of the field and laboratory sampling protocol to minimize the effects of measurement error. The data analysis confirmed that this goal was accomplished. In most cases considerably less than five percent of the total variability could be attributed to sampling and analytical error. Because of the relatively short duration of the study (42 biweekly sampling occasions at most wells) it was not possible to identify the magnitude of seasonal variations reliably.     

Statistical trends in ground-water monitoring data at a landfill Superfund site: A case study

This paper describes the use of statistical regression models to characterize temporal trends in groundwater monitoring data collected between 1980 and 1990 on 15 wells and 13 parameters (195 cases in all) at the KL Avenue landfill site in Kalamazoo County, Michigan. This site was used as a municipal landfill prior to 1980, then was placed on the Superfund site list in 1982 after ground-water contamination was found.Six temporal regression trend models were defined using linear and quadratic regression models. These trends were used to classify each of the 195 cases as: improving, deteriorating, or stable over the 1980–1990 time period. Using these classifications it was determined that there were more than twice as many improving cases as deteriorating conditions at the KL site during this time period. These models provide a method for visualizing and interpreting trends in ground-water quality at individual well locations within the contaminant plume and for assessing the chemical trend behavior of the overall plume. The improving, deteriorating, and stable trend categories were developed for two purposes. The first purpose is to facilitate comprehension of information contained in large amounts of water quality data. The second is to assist communication among the many different groups of people who recommend actions, including remediation responsibilities at Superfund sites, like the KL site.A normal probability model was used in the trend classifications. This model contained provisions to accommodate nondetect data and other abnormal laboratory determinations which can influence the trend selection process. The robustness of this classification procedure was examined using a lognormal probability model. The overall conclusions about the KL site using the lognormal model were similar to those obtained using the normal model. However, some individual trend indications were different using the lognormal model. The Shapiro-Wilk test was used to check the adequacy of both the normal and lognormal models. The lognormal model was found to be a somewhat more adequate model for fitting the KL site data, but was not found to be superior to the normal model for each case.The normal and lognormal models were both found to be suitable for determining overall trend conditions at this site. Both models are recommended for these purposes assuming an understanding of the statistical constraints and hydrochemical context. However, it is recommended that the search for more adequate trend models continues.     

The determination of acid-reactive sulfide

Acid-reactive sulfide minerals make up a large fraction of total sulfur in freshwater sediments, waste sludges, and waterlogged soils. Quantitative determinations of acid-reactive sulfide (ARS) by hydrogen sulfide evolution methods have been hampered by sample handling losses, standardization problems, and poor overall recoveries. A systematic study has been made of the optimal conditions for the determination of ARS. The modified method employs a zinc sulfide suspension as a standard in contrast with the current standard of sodium sulfide solution. This change resulted in a great improvement in precision; the addition of sodium hydroxide to the hydrogen sulfide absorption solution improved recoveries to better than 95% in the range of interest, 0.4-4 mg sulfide. ARS in freshly collected lake sediment samples was determined with an average of less than ±14% relative standard deviation. Storage of sediment samples for periods exceeding 6 months was found to increase variability only slightly. The method should prove applicable to various sulfide-containing samples and, with prescribed handling precautions, samples may be stored for extended periods.     

A probabilistic methodology to assess the risk of groundwater quality degradation

An approach to assess the risk of groundwater quality degradation with regard to fixed standards, based on DisjunctiveKriging (DK) is presented. The DK allows one to evaluate the Conditional Probability (CP) of overriding a given threshold of concentration of a pollutant at a given time, and at a generic point in a consideredgroundwater system. The result of such investigation over the considered area can be plotted in form of maps of spatial risk. By repeating this analysis at different times, severalspatial riskmaps will be produced, one for each consideredtime. By means of non-parametric statistics, the temporal trendof the CPs can be evaluated at every point of the considered area. The trend index, assessed by means of a sort of classification of the trend values obtained as described above,can be superimposed on the most recent values of the spatialrisk (i.e.: the most recent values of probability). Consequentlya classification of the risk of groundwater quality degradationresults with which to weigh both the spatial distribution and thetemporal behaviour of the probability to exceed a given standardthreshold. The methodology has been applied to values of nitrateconcentration sampled in the monitoring well network of theModena plain, northern Italy. This area is characterised by intensive agricultural exploitation and hog breeding along withindustrial and civil developments. The influence of agriculture on groundwater results in a high nitrate pollution that limitsits use for potable purposes.