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1.
J Contam Hydrol ; 258: 104230, 2023 09.
Artículo en Inglés | MEDLINE | ID: mdl-37481897

RESUMEN

Surfactant-enhanced in-situ chemical oxidation (S-ISCO) is an emerging innovative remediation technology for the treatment of dense non-aqueous phase liquids (DNAPLs). S-ISCO combines the solubilization of contaminants by means of surfactants with the chemical oxidation by an oxidizing agent, thus, potentially increasing the efficiency of the state-of-the-art ISCO technique. Scientific investigations are needed to enable the technology transfer for potential field applications based on the development of a remediation design under well-defined boundary conditions. For this purpose, experimental upscaling analyses were performed using the special infrastructure of the research facility for subsurface remediation (VEGAS). Batch tests showed that oxidation of the selected surfactant E-Mulse 3® (EM3) by activated persulfate (Na-PS) reduced the solubilization of the model contaminants 1,4-DCB, naphthalene, and PCE. As a consequence, the processes of contaminant solubilization and degradation were temporally and spatially separated in the developed remediation design. A proof of concept was provided by performing an S-ISCO medium-scale experiment (100 cm length, 70 cm height, 12.5 cm width), with 1,2-DCB as model DNAPL contaminant to be treated. A groundwater circulation well (GCW) was used to inject a 60 g/L Na-PS solution and to effectively mix the reagents. Sampling of the experiment's outflow and the soil material after treatment showed that neither rebound effects nor residual mass loadings on the soil material could be detected after termination of the S-ISCO treatment. To further evaluate the S-ISCO remediation design under field-like conditions, a large-scale S-ISCO experiment was conducted (6 m length, 3 m height, 1 m width), allowing for an extensive sampling campaign to monitor relevant processes. An efficient contaminant removal from the former source zone could be reached by surfactant solubilization, decreasing contaminant levels from initially over 2000 mg/L 1,2-DCB to final concentrations below 5 mg/L 1,2-DCB. The heterogeneously distributed contaminant degradation, implemented by a three-filter GCW, was attributed to density-induced migration processes that impeded an optimal reaction zone. A density-dependent numerical transport could qualitatively match the observations. By comparing different simulation scenarios, an adapted operation of the GCW was established that provides for a more efficient distribution of the density-influenced oxidant injection.


Asunto(s)
Agua Subterránea , Contaminantes Químicos del Agua , Tensoactivos , Contaminantes Químicos del Agua/análisis , Oxidación-Reducción , Oxidantes , Suelo/química , Agua Subterránea/química
2.
Ground Water ; 57(3): 420-429, 2019 05.
Artículo en Inglés | MEDLINE | ID: mdl-29862499

RESUMEN

The spatial distribution of hydraulic properties in the subsurface controls groundwater flow and solute transport. However, many approaches to modeling these distributions do not produce geologically realistic results and/or do not model the anisotropy of hydraulic conductivity caused by bedding structures in sedimentary deposits. We have developed a flexible object-based package for simulating hydraulic properties in the subsurface-the Hydrogeological Virtual Realities (HyVR) simulation package. This implements a hierarchical modeling framework that takes into account geological rules about stratigraphic bounding surfaces and the geometry of specific sedimentary structures to generate realistic aquifer models, including full hydraulic-conductivity tensors. The HyVR simulation package can create outputs suitable for standard groundwater modeling tools (e.g., MODFLOW), is written in Python, an open-source programming language, and is openly available at an online repository. This paper presents an overview of the underlying modeling principles and computational methods, as well as an example simulation based on the Macrodispersion Experiment site in Columbus, Mississippi. Our simulation package can currently simulate porous media that mimic geological conceptual models in fluvial depositional environments, and that include fine-scale heterogeneity in distributed hydraulic parameter fields. The simulation results allow qualitative geological conceptual models to be converted into digital subsurface models that can be used in quantitative numerical flow-and-transport simulations, with the aim of improving our understanding of the influence of geological realism on groundwater flow and solute transport.


Asunto(s)
Agua Subterránea , Anisotropía , Geología , Mississippi , Modelos Teóricos , Movimientos del Agua
3.
Environ Sci Technol ; 51(13): 7502-7510, 2017 Jul 05.
Artículo en Inglés | MEDLINE | ID: mdl-28613841

RESUMEN

This paper demonstrates a maximum likelihood (ML)-based approach to derive representative ("best guess") contaminant concentrations from data with censored values (e.g., less than the detection limit). The method represents an advancement over existing techniques because it is capable of estimating the proportion of measurements that are true zeros and incorporating varying levels of censorship (e.g., sample specific detection limits, changes through time in method detection). The ability of the method to estimate the proportion of true zeros is validated using precipitation data. The stability and flexibility of the method are demonstrated with stochastic simulation, a sensitivity analysis, and unbiasedness analysis including varying numbers of significant digits. A key aspect of this paper is the application of the statistical analysis to real site rock core contaminant concentration data collected within a plume at two locations using high resolution depth-discrete sampling. Comparison of the representative values for concentrations at each location along the plume center-line shows a larger number of true zeros and generally lower concentrations at the downgradient location according to the conceptual site model, leading to improved estimates of attenuation with distance and/or time and associated confidence; this is not achievable using deterministic methods. The practical relevance of the proposed method is that it provides an improved basis for evaluating change (spatial, temporal, or both) in environmental systems.


Asunto(s)
Interpretación Estadística de Datos , Contaminantes Ambientales , Límite de Detección
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