Estimating Biofuel Contaminant Concentration from 4D ERT with Mixing Models
Citation:
Glaser, D., R. Henderson, D. Werkema, T. Johnson, AND R. Versteeg. Estimating Biofuel Contaminant Concentration from 4D ERT with Mixing Models. JOURNAL OF CONTAMINANT HYDROLOGY. Elsevier Science Ltd, New York, NY, 248:104027, (2022). https://doi.org/10.1016/j.jconhyd.2022.104027
Impact/Purpose:
This research presents results from a laboratory tank experiment to determine the direct current (DC) resistivity detectability of fuel grade ethanol (EtOH)detection. The experiments demonstrate that DC resistivity acquired as electrical resistivity tomography (ERT) can detect and monitoring EtOH in this laboratory setting. Furthermore, the paper shows that the EtOH concentration distribution within the tank can be determined from the ERT data and mixing models. This paper demonstrates the potential for using field based geophysical methods to map and monitor ethanol releases from ethanol blended fuels in the subsurface. Such geophysical surveys can greatly increase the accuracy of these plume maps, guide site investigators, and monitor remediation of these impacted sites.
Description:
We present the results of a lab-scaled feasibility study to assess the performance of electrical resistivity tomography for detection, characterization, and monitoring of fuel grade ethanol releases to the subsurface. Further, we attempt to determine the concentration distribution of the ethanol from the electrical resistivity tomography data using mixing-models. Ethanol is a renewable fuel source as well as an oxygenate fuel additive currently used to replace the known carcinogen methyl tert-butyl ether; however, ethanol is preferentially biodegraded and a cosolvent. When introduced to areas previously impacted by nonethanol-based fuels, it will facilitate the persistence of carcinogenic fuel compounds like benzene and ethylbenzene, as well as remobilize them to the ground water. These compounds would otherwise be retained in the soil column undergoing active or passive remediation processes such as soil vapor extraction or natural attenuation. Here, we introduce ethanol to a saturated Ottawa sand in a tank instrumented for three-dimensional geoelectrical measurements. Forward model results suggest pure phase ethanol released into a water saturated silica sand should present a detectable target for electrical resistivity tomography relative to a saturated silica sand only. We observe the introduction of ethanol to the closed hydraulic system and subsequent migration over the duration of the experiment. One-dimensional and three–dimensional temporal data are assessed for the detection, characterization, and monitoring of the ethanol release. Results suggest one-dimensional geoelectrical measurements may be useful for monitoring a release, while three-dimensional geoelectrical field imaging would be useful to characterize, monitor, and design effective remediation approaches for an ethanol release, assuming field conditions do not preclude the application of geoelectrical methods. We then attempt to use predictive mixing models to calculate the distribution of ethanol concentration within the measurement domain. For this study we examine four different models: a nested parallel mixing model, a nested cubic mixing model, the complex refractive index model (CRIM), and the Lichtenecker-Rother (L-R) model. The L-R model, modified to include an electrical formation factor geometry term, provided the best agreement with expected EtOH concentrations.
