A modified and rapid method for the single-well push-pull (SWPP) test using SF6, Kr, and uranine tracers.

In the present study, a single-well push-pull (SWPP) test was conducted with multi-component tracers, including inert gas (SF6 and Kr) and uranine (conservative), to understand the volatile/semi-volatile component transport characteristics in the groundwater system. In an SWPP test, it is essential to obtain an initial breakthrough curve (BTC) of the inert gas concentration at the beginning of the pulling stage to analyze the hydraulic properties of the groundwater system. As a result of the SWPP test using a proposed method in this study, physicochemical parameters of the groundwater and BTC of gas tracers and uranine were acquired simultaneously and successfully. In addition, on-site measurements of uranine, pCO2, and water quality data, such as electrical conductivity (EC), temperature, pH, and dissolved oxygen, were undertaken. Modification of an existing pCO2 measuring system allowed the gas samples to be collected, transported, and analyzed for inert gas components within a few hours. As a result, reliable and interpretable data with a recovery ratio of 26%, 85%, and 95% for SF6, Kr, and uranine, respectively, were obtained. The differences in the recovery ratio were utilized to identify the environmental system, whether it contains gas inside the isolated system (closed) or not (open), and to understand plume behavior characteristics in the experimental zone. By applying a two-dimensional advection-dispersion model to the acquired tracer test data and comparing the observed and computed tracer concentrations, helpful information was obtained on the hydraulic and transport characteristics of the targeted zone. This method can be extended to the design of dissolved CO2 transport monitoring of an aquifer above a CCS site.

Field-scale investigation of nanoscale zero-valent iron (NZVI) injection parameters for enhanced delivery of NZVI particles to groundwater.

The effects of the injection parameters on delivery of nanoscale zero-valent iron (NZVI) to contaminated groundwater were investigated. The first two NZVI injections (gravity injection at low flow rates) resulted in NZVI being poorly mobile and gave total cumulative mass recoveries at the monitoring wells of 1.07%-2.43%. NZVI reached some wells (KDMW-3, MW-2, MW-4, and MW-7) earlier than the bromide tracer. The dominant travel directions for NZVI and the bromide tracer were very different. The NZVI transport characteristics suggested that targeted NZVI delivery requires preferential groundwater flow paths and local heterogeneity to be considered. In the gravity injection tests, the maximum NZVI concentrations and cumulative NZVI mass recoveries in the wells decreased markedly as the injected NZVI concentration and dose increased. In the third and fourth tests, in which NZVI was injected under pressure at high flow rates, NZVI was effectively delivered to the wells despite the injected NZVI concentration and dose being high. Relatively high cumulative mass recoveries of 26.0% and 74.5% were found for the third and fourth injections, respectively. Controlling the flow rate (pressure) and NZVI concentration and dose simply and effectively controlled NZVI mobility in the groundwater. The colloidal and electrostatic characteristics of the NZVI particles were monitored and modeled, and the results indicated that NZVI particles without Derjaguin-Landau-Verwey-Overbeek energy barriers were successfully delivered to the target zone and that decreased magnetic attractive forces between NZVI particles caused by iron corrosion probably decreased the degree of NZVI particle aggregation and therefore contributed to NZVI being delivered to the target zone.

A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model.

In this study, a data-driven method for predicting CO2 leaks and associated concentrations from geological CO2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems.

Identification of the source of nitrate contamination in ground water below an agricultural site, Jeungpyeong, Korea.

This study applied hydrogeological characterization and isotope investigation to identify source locations and to trace a plume of ground water contaminated by nitrate. Most of the study site is agricultural fields with the remainder being residential. A poultry farm is also within the study area, so that potential point and nonpoint sources were present. Estimates of seasonal ground water recharge from irrigation and precipitation, leakage of sewage, and the regional ground water flow were linked to the seasonal changes in isotopic values. Ground water recharge largely occurred in spring and summer following precipitation or irrigation, depending on the locations. Natural and fertilized soils were identified as nonpoint sources of nitrate contamination in this area, while septic and animal wastes were identified as small point sources. The seasonal changes in the relative impact of these sources on ground water contamination were related to such factors as source distribution, the aquifer confining condition, precipitation rate, infiltration capacity, recharge rate, and the land use pattern.