Rapid Assessment of Trichloroethylene in Ground Water

On-site analysis of trichloroethylene (TCE) in aqueous samples by head- space sample preparation and gas chromatography (HS/GC) provides for quick and precise concentration estimates. This analytical approach is well suited for the on-site determination of volatile organic compounds (VOCs) in a variety of sample matrices, including ground water and saturated and unsatured soils. For these reasons, HS/GC can be used to establish analyte concentrations on a near real time basis to help select appropriate casing material during monitoring well installation. This application and the collection of multiple well samples during sampling events facilitates the hydrogeological site interpretation and the formulation of remediation strategies.     

Comparison of Two Integrated Methods for the Collection and Analysis of Volatile Organic Compounds in Ground Water

The principal difficulties with determinations of volatile organic compounds (VOCs) in ground water are the reliability of sampling procedures and analytical methods. Two integrated methods have been developed for routine sampling, processing, and analysis of VOCs in ground water. These methods involve in situ collection of ground water using a modified syringe sampler from PVC piezometers or using dedicated glass syringes from stainless steel multilevel bores. The samples are processed in the syringe using purge and trap or microsolvent extraction and analyzed by GC/MSD.
The modified purge-and-trap method is time-consuming and limited to volatile organic compounds. However, it is extremely sensitive and flexible: the volume of sample used can be varied by the use of different-size glass syringes (sample volumes from 1 to 100 mL).
In cases where extremely low sensitivity (<10 mg 1⁻¹) is not critical, the microextraction technique is a more cost-effective method, allowing twice as many samples to be analyzed in the same time as the purge-and-trap method. It enables less volatile compounds such as polynuclear aromatic hydrocarbons, phenol, and cresols to be analyzed in the same GC run. Also, the microextraction method can be used in the field to avoid delays associated with transportation of ground water samples to the laboratory.     

Field Investigation of Vapor‐Phase‐Based Groundwater Monitoring

The use of in‐field analysis of vapor‐phase samples to provide real‐time volatile organic compound (VOC) concentrations in groundwater has the potential to streamline monitoring by simplifying the sample collection and analysis process. A field validation program was completed to (1) evaluate methods for collection of vapor samples from monitoring wells and (2) evaluate the accuracy and precision of field‐portable instruments for the analysis of vapor‐phase samples. The field program evaluated three vapor‐phase sample collection methods: (1) headspace samples from two locations within the well, (2) passive vapor diffusion (PVD) samplers placed at the screened interval of the well, and (3) field vapor headspace analysis of groundwater samples. Two types of instruments were tested: a field‐portable gas chromatograph (GC) and a photoionization detector (PID). Field GC analysis of PVD samples showed no bias and good correlation to laboratory analysis of groundwater collected by low‐flow sampling (slope = 0.96, R² = 0.85) and laboratory analysis of passive water diffusion bag samples from the well screen (slope = 1.03; R² = 0.96). Field GC analysis of well headspace samples, either from the upper portion of the well or at the water‐vapor interface, resulted in higher variability and much poorer correlation (consistently biased low) relative to laboratory analysis of groundwater samples collected by low‐flow sample or passive diffusion bags (PDBs) (slope = 0.69 to 0.76; R² = 0.60 to 0.64). These results indicate that field analysis of vapor‐phase samples can be used to obtain accurate measurements of VOC concentrations in groundwater. However, vapor samples collected from the well headspace were not in equilibrium with water collected from the well screen. Instead, PVD samplers placed in the screened interval represent the most promising approach for field‐based measurement of groundwater concentrations using vapor monitoring techniques and will be the focus of further field testing.     

Estimating the Sampling Uncertainty for the Analysis of Solid Refused Fuel

Uncertainty assessment of the parameters used for the reporting in the emissions trading system (ETS) to characterize fuels includes not only the processes in a laboratory but has to be expanded for inclusion of sampling and sample preparation. Analysis of variance was used to allocate the contributing uncertainties to the steps described. Apart from some specific results for sampling methods, it was observed that the uncertainty of sampling was in the same order of magnitude than the analytical and the sample preparation error. Several measures to enhance quality assurance in sampling and sample preparation could be derived from specific results. The results were used in the European Monitoring and Reporting Regulation, which set out the requirements for ETS. Sampling and sample preparation have to be included in uncertainty assessment as well as sampling procedures and sampling plans (including quality assurance) have to be agreed upon by the laboratories, carrying out the analytics of those samples.     

High Purge Volume Sampling—A New Paradigm for Subslab Soil Gas Monitoring

Subslab soil gas sampling and analysis is a common line of evidence for assessing human health risks associated with subsurface vapor intrusion to indoor air for volatile organic compounds; however, conventional subslab sampling methods have generated data that show substantial spatial and temporal variability, which often makes the interpretation difficult. A new method of monitoring has been developed and tested that is based on a concept of integrating samples over a large volume of soil gas extracted from beneath the floor slab of a building to provide a spatially averaged subslab concentration. Regular field screening is also conducted to assess the trend of concentration as a function of the volume removed to provide insight into the spatial distribution of vapors at progressive distances away from the point of extraction. This approach minimizes the risk of failing to identify the areas of elevated soil vapor concentrations that may exist between discrete sample locations, and can provide information covering large buildings with fewer holes drilled through the floor. The new method also involves monitoring the extraction flow rate and transient vacuum response for mathematical analysis to help interpret the vapor concentration data and to support an optimal design for any subslab venting system that may be needed.     

Groundwater Sampling at ISCO Sites: Binary Mixtures of Volatile Organic Compounds and Persulfate

In situ chemical oxidation involves the introduction of a chemical oxidant into the subsurface for the purpose of transforming groundwater contaminants into harmless by‐products. Owing to oxidant persistence, groundwater samples collected at hazardous waste sites may contain both the contaminant(s) and the oxidant in a “binary mixture.” Binary mixtures composed of sodium persulfate (2.5 g/L; 10.5 mM) and volatile organic compounds (VOCs) (benzene, toluene, m‐xylene, perchloroethylene, trichloroethylene) were analyzed to assess the impact on the quality of the sample. A significant decline (49 to 100%) in VOC concentrations was measured in binary mixtures using gas chromatography (GC) purge and trap, and GC mass spectroscopy headspace methods. Preservation of the binary mixture samples was achieved through the addition of ascorbic acid (99 to 100% VOC average recovery). High concentrations of ascorbic acid (42 to 420 mM) did not interfere in the measurement of the VOCs and did not negatively impact the analytical instruments. High concentrations of ascorbic acid favored the reaction between persulfate and ascorbic acid while limiting the reaction between persulfate and VOCs. If an oxidant is detected and the binary sample is not appropriately preserved, the quality of the sample is likely to be compromised.     

Uncertainty in hydrograph separations based on geochemical mixing models

A detailed uncertainty analysis of three-component mixing models based on the Haute–Mentue watershed (Switzerland) is presented. Two types of uncertainty are distinguished: the ‘model uncertainty’, which is affected by model assumptions, and the ‘statistical uncertainty’, which is due to temporal and spatial variability of chemical tracer concentrations of components. The statistical uncertainty is studied using a Monte Carlo procedure. The model uncertainty is investigated by the comparison of four different mixing models all based on the same tracers but considering for each component alternative hypotheses about their concentration and their spatio-temporal variability. This analysis indicates that despite the uncertainty, the flow sources, which generate the stream flow are clearly identified at the catchments scale by the application of the mixing model. However, the precision and the coherence of hydrograph separations can be improved by taking into account any available information about the temporal and spatial variability of component chemical concentrations.     

Interlaboratory comparison of amino acid enantiomeric ratios in Pleistocene fossils

It has been nearly three decades since the last systematic interlaboratory comparison of amino acid racemization (AAR) measurements among active laboratories. The advent of new methods and improved instrumentation for existing techniques requires that these comparisons be conducted more frequently than has occurred. The present study represents a first step in this process. Five homogeneous liquid samples were distributed to six participating laboratories that use one or more of the following analytical methods: Ion-exchange liquid chromatography (IEx), Reverse-phase liquid chromatography (RP), or Gas chromatography (GC). The five samples have been used in previous formal or informal interlaboratory comparisons: three are Pleistocene mollusk samples, two are Pleistocene eggshell samples. Use of homogeneous liquids eliminated variables involved in the majority of the sample preparative steps (sample cleaning, hydrolysis, desalting), so any observed variability between laboratories can be attributed to instrumental factors or possible small effects associated with the hydration procedures employed prior to instrumental analysis. Although most results indicate good agreement (within 10%) for all amino acid d/l values, there are some notable exceptions for certain amino acids or certain samples. For the five amino acids that are most commonly used in geochronological applications (Asx, Glx, Leu, Val, and A/I), inter-method comparisons reported here provide quantitative regressions that can be used when results from one method are compared with those from another.     

A Syringe and Cartridge Method for Down-Hole Sampling for Trace Organics in Ground Water

A newly developed technique which allows the down-hole sampling and subsequent analysis of ground water for trace organic contaminants was tested during an investigation of contaminant migration at an inactive landfill site in Burlington, Ontario, Canada. The sampling device, which is lowered down piezometers with a tube, consists of a small cylindrical cartridge of sorbent material attached to a syringe. Vacuum or pressure applied at the surface controls the movement of the plunger in the syringe. The volume of the syringe determines the volume of sample water that passes through the cartridge. The cartridge is removed from the syringe at the surface. One cartridge is used for each sampling; the syringe is reusable. The residual water in the cartridge is removed in the laboratory, and the cartridge is desorbed to a fused silica capillary column for analysis by gas chromatography (GC). The analyses discussed here were performed on a GC/mass spectrometer/data system (GC/MS/DS). Of the many organic compounds that were identified in the samples, three compounds were clearly landfill-related: 1,1,1-trichloroethane, chlorobenzene, and para-dichlorobenzene. The three compounds were found at levels substantially above blank levels in 9, 5, and 5 piezometers, respectively. The average concentrations were 14., 5.3, and 0.88μg/1 (ppb), respectively. The pooled coefficients of variation for the analyses for the three compounds were 27., 6.9, and 6.4%, respectively. The volatility of 1,1,1-trichloroethane was probably the cause of the greater variability in its analytical data. The main advantages of the technique over most conventional sampling methods include: (1) down-hole sampling in a manner which minimizes the potential for volatilization losses; (2) avoidance of passage of the sample through long sections of tubing that may contaminate the sample or cause adsorptive losses; (3) convenience of sample handling, storage, and shipping; and (4) high sensitivity.     

Probabilistic-fuzzy health risk modeling

Health risk analysis of multi-pathway exposure to contaminated water involves the use of mechanistic models that include many uncertain and highly variable parameters. Currently, the uncertainties in these models are treated using statistical approaches. However, not all uncertainties in data or model parameters are due to randomness. Other sources of imprecision that may lead to uncertainty include scarce or incomplete data, measurement error, data obtained from expert judgment, or subjective interpretation of available information. These kinds of uncertainties and also the non-random uncertainty cannot be treated solely by statistical methods. In this paper we propose the use of fuzzy set theory together with probability theory to incorporate uncertainties into the health risk analysis. We identify this approach as probabilistic-fuzzy risk assessment (PFRA). Based on the form of available information, fuzzy set theory, probability theory, or a combination of both can be used to incorporate parameter uncertainty and variability into mechanistic risk assessment models. In this study, tap water concentration is used as the source of contamination in the human exposure model. Ingestion, inhalation and dermal contact are considered as multiple exposure pathways. The tap water concentration of the contaminant and cancer potency factors for ingestion, inhalation and dermal contact are treated as fuzzy variables while the remaining model parameters are treated using probability density functions. Combined utilization of fuzzy and random variables produces membership functions of risk to individuals at different fractiles of risk as well as probability distributions of risk for various alpha-cut levels of the membership function. The proposed method provides a robust approach in evaluating human health risk to exposure when there is both uncertainty and variability in model parameters. PFRA allows utilization of certain types of information which have not been used directly in existing risk assessment methods.     

Accounting for source location errors in the bayesian analysis of seismicity and seismic hazard

A method is presented for incorporating the uncertainties associated with hypocentral locations in the formulation of probabilistic models of the time and space distributions of the activity of potential seismic sources, as well as of the resulting seismic hazard functions at sites in their vicinity. For this purpose, a bayesian framework of analysis is adopted, where the probabilistic models considered are assumed to have known forms and uncertain parameters, the distribution of the latter being the result of an a priori assessment and its updating through the incorporation of the direct statistical information, including the uncertainty associated with the relations between the actual hypocentral locations and the reported data. This uncertainty is incorporated in the evaluation of the likelihood function of the parameters to be estimated for a given sample of recorded locations. For the purpose of illustration, the method proposed is applied to the modelling of the seismic sources near a site close to the southern coast of Mexico. The results of two alternate algorithms for the incorporation of location uncertainties are compared with those arising from neglecting those uncertainties. One of them makes use of Monte Carlo simulation, while the other is based on a closed-form analytical integration following the introduction of some simplifying assumptions. For the particular case studied, accounting for location uncertainties gives place to significant changes in the probabilistic models of the seismic sources. Deviations of the same order of magnitude can be ascribed to differences in the mathematical and/or numerical tools used in the uncertainty analysis. The resulting variability of the seismic hazard at the site of interest is less pronounced than that affecting the estimates of activity of individual seismic sources.     

Zur Bildung von Artefakten und deren Vermeidung bei der Bestimmung leichtflüchtiger Halogenkohlenwasserstoffe in Wasser mittels Headspace-Gaschromatographie unter den Bedingungen der DIN 38407 Teil 5 (DEV-F5). Teil II: Überhöhte Trihalogenmethanbefunde in gechlortem Schwimmbeckenwasser

Formation of Artefacts and its Suppression during the Determination of Volatile Halogenated Hydrocarbons in Water by Means of Headspace Gas Chromatography under the Standard Conditions of DIN 38407-F5. Part II: Increased Trihalomethane Formation in Chlorinated Swimming-pool Water A comparison of two analytical standard procedures for the determination of trihalomethanes (THM) in water (headspace gas chromatography and pentane extraction/gas chromatography) yielded strongly differing results. Under the conditions recommended by the German Standard Method DIN 38407-F5 (60…80°C for at least 60 min) degradation of thermo-labile chlorination products occurs resulting in elevated THM concentrations. The reactions involved are partly pH-dependant, and these can be suppressed by sample acidification. The degradation of trihalogen acetic acids, however, can only be influenced by minimizing the equilibration time and temperature. Other intermediate chlorination products (haloacetonitriles) are also degraded to THM after preceding hydrolysis to the corresponding carboxylic acids. Comparative results obtained with a purge and trap method at ambient temperature, i.e. without thermal stress during the enrichtment step, are lower than with static headspace GC but still high in comparison to the pentane extraction method. Presumably volatile THM-precursors are also trapped and subsequently decomposed upon thermal desorption from the trap. As the static headspace GC is the most rational method of LHKW determination available, the recommended experimental sample handling conditions should be modified in a way that deterioration reactions are reduced as far as possible.     

Uncertainty Analysis in Atmospheric Dispersion Modeling

The concentration of a pollutant in the atmosphere is a random variable that cannot be predicted accurately, but can be described using quantities such as ensemble mean, variance, and probability distribution. There is growing recognition that the modeled concentrations of hazardous contaminants in the atmosphere should be described in a probabilistic framework. This paper discusses the various types of uncertainties in atmospheric dispersion models, and reviews sensitivity/uncertainty analysis methods to characterize and/or reduce them. Evaluation and quantification of the range of uncertainties in predictions yield a deeper insight into the capabilities and limitations of atmospheric dispersion models, and increase our confidence in decision-making based on models.     

Using geostatistical simulation to disaggregate air quality model results for individual exposure estimation on GPS tracks

In this work, we address the mismatch in spatio-temporal resolution between individual, point-location based exposure and grid cell based air quality model predictions by disaggregating the grid model results. Variability of PM₁₀ point measurements was modelled within each grid cell by the exponential variogram, using point support concentration measurements. Variogram parameters were estimated over the study area globally using constant estimates, and locally by multiple regression models using traffic, weather and land use data. Model predictions of spatio-temporal variability were used for geostatistical unconditional simulation, estimating the deviation of point values from grid cell averages on GPS tracks. The distribution of deviations can be used as an estimate of uncertainty for individual exposure. Results showed a relevant impact of the disaggregation uncertainties compared to other uncertainty sources, dependent of the model used for spatio-temporal variability. Depending on individual behaviour and variability of the pollutant, these uncertainties average out again over time.     

Uncertainty in water resource model parameters used for climate change impact assessment

Despite their acknowledged limitations, lumped conceptual models continue to be used widely for climate‐change impact assessments. Therefore, it is important to understand the relative magnitude of uncertainties in water resource projections arising from the choice of model calibration period, model structure, and non‐uniqueness of model parameter sets. In addition, external sources of uncertainty linked to choice of emission scenario, climate model ensemble member, downscaling technique(s), and so on, should be acknowledged. To this end, the CATCHMOD conceptual water balance model was used to project changes in daily flows for the River Thames at Kingston using parameter sets derived from different subsets of training data, including the full record. Monte Carlo sampling was also used to explore parameter stability and identifiability in the context of historic climate variability. Parameters reflecting rainfall acceptance at the soil surface in simpler model structures were found to be highly sensitive to the training period, implying that climatic variability does lead to variability in the hydrologic behaviour of the Thames basin. Non‐uniqueness of parameters for more complex model structures results in relatively small variations in projected annual mean flow quantiles for different training periods compared with the choice of emission scenario. However, this was not the case for subannual flow statistics, where uncertainty in flow changes due to equifinality was higher in winter than summer, and comparable in magnitude to the uncertainty of the emission scenario. Therefore, it is recommended that climate‐change impact assessments using conceptual water balance models should routinely undertake sensitivity analyses to quantify uncertainties due to parameter instability, identifiability and non‐uniqueness. Copyright © 2005 John Wiley & Sons, Ltd.     

Numerical modelling of the suspended sediment transport in Torres Strait

One-dimensional vertical and three-dimensional fine-resolution numerical models of sediment transport have been developed and applied to the Torres Strait region of northern Australia. The one-dimensional model, driven by measured waves and currents, was calibrated against measured suspended sediment concentrations using a sequential data assimilation algorithm. The algorithm produced a good match between model and data, but this was achieved only by allowing some temporal variability in parameter values, suggesting that there were underlying uncertainties in the model structure and forcing data. Implications of the assimilation results to the accuracy of the numerical modelling are discussed and the need for observational programmes having an extensive spatial and temporal coverage is highlighted. The three-dimensional sediment model, driven by modelled waves and currents, simulates sediment transport over the shelf during the monsoon and trade-wind seasons covering 1997–2000. The model predicts strong seasonal variability of the sediment transport on the shelf attributed to seasonally varying hydrodynamics, and illustrates significant inter-annual variability of the sediment fluxes driven by extreme events. The developed model provides a platform for testing scientific hypothesis. With additional calibration, including uncertainty analysis, it can also be used in a management context.     

Parameter Estimation for Groundwater Models under Uncertain Irrigation Data

The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression‐based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least‐squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least‐squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least‐squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p < 0.05) bias in estimated parameters and model predictions that persist despite calibrating the models to different calibration data and sample sizes. However, by directly accounting for the irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.     

Sampling for Purgeable Organic Compounds Using Positive-Displacement Piston and Centrifugal Submersible Pumps: A Comparative Study

Positive-displacement piston pumps that minimize sample agitation have no apparent advantage over centrifugal submersible pumps when used to collect ground water samples for analysis of low concentrations of purge-able organic compounds. Analytical uncertainties inherent in laboratory environments appear to influence analytical results of low-concentration purgeable organic compound samples more than either pump type or sampling team. Centrifugal submersible pumps are at least equally efficient as positive-displacement piston pumps in the recovery of carbon tetrachloride, 1,1,1-trichloroethane, trichloroethylene, and chloroform after sampling and analytical influences are made constant.     

Used Motor Oil as a Source of MTBE, TAME, and BTEX to Ground Water

Methyl tert-butyl ether (MTBE), the widely used gasoline oxygenate, has been identified as a common ground water contaminant, and BTEX compounds (benzene, toluene, ethylbenzene, and xylenes) have long been associated with gasoline spills. Because not all instances of ground water contamination by MTBE and BTEX can be attributed to spills or leaking storage tanks, other potential sources need to be considered. In this study, used motor oil was investigated as a potential source of these contaminants. MTBE in oil was measured directly by methanol extraction and gas chromatography using a flame ionization detector (GC/FID). Water was equilibrated with oil samples and analyzed for MTBE, BTEX, and the oxygenate tert-amyl methyl ether (TAME) by purge- and-trap concentration followed by GC/FID analysis. Raoult's law was used to calculate oil-phase concentrations of MTBE, BTEX, and TAME from aqueous-phase concentrations. MTBE, TAME, and BTEX were not detected in any of five new motor oil samples, whereas these compounds were found at significant concentrations in all six samples of the used motor oil tested for MTBE and all four samples tested for TAME and BTEX. MTBE concentrations in used motor oil were on the order of 100 mg/L. TAME concentrations ranged from 2.2 to 87 mg/L. Concentrations of benzene were 29 to 66 mg/L, but those of other BTEX compounds were higher, typically 500 to 2000 mg/L.     

DYNAMIC RESPONSE VARIABILITY OF STRUCTURES WITH UNCERTAIN PROPERTIES

A modal-based analysis of the dynamic response variability of multiple degree-of-freedom linear structures with uncertain parameters subjected to either deterministic or stochastic excitations is considered. A probabilistic methodology is presented in which random variables with specified probability distributions are used to quantify the parameter uncertainties. The uncertainty in the response due to uncertainties in the structural modelling and loading is quantified by various probabilistic measures such as mean, variance and coefficient of excess. The computation of these probabilistic measures is addressed. A series expansion involving orthogonal polynomials in terms of the system parameters is first used to model the response variability of each contributing mode. Linear equations for the coefficients of each series expansion are derived using the weighted residual method. Mode superposition is then used to derive analytical expressions for the variability and statistics of the uncertain response in terms of the coefficients of the series expansions for all contributing modes. A primary–secondary system and a ten-story building subjected to deterministic and stochastic loads are used to demonstrate the methodology, as well as evaluate its performance by comparing it to existing methods, including the computationally cost-efficient perturbation method.