Experimental study for visualizing CO2-dissolved water plume migration under hydraulic gradient conditions and implication for field monitoring data.

Investigating the possible direction of a CO2-dissolved water plume migration near the potential CO2 leakage area is a significant task because it helps estimate the spatial and temporal monitoring scale to detect the signal of released CO2 from the storage. Accordingly, the Korea CO2 Storage Environmental Management (K-COSEM) research center tried to develop an intensive monitoring system and applied it to the artificial CO2 release test in the actual field. Monitoring data from the field tests depicted the horizontal movement of the CO2-dissolved water plume along the direction of the groundwater flow. However, it remains unclear how the CO2-dissolved water plume migrates vertically and how gas accumulation occurs near the capillary zone. The present study simulated the CO2 release test with a visual expression method utilizing a Hele-Shaw cell with hydraulic gradient conditions (i = 0, 0.1, and 0.01) and tried to estimate the significant influences on a diffusive-advective transport of the dissolved gas plume with the shallow aquifer condition. The visualization experiment results were intuitively verified to determine whether the theoretical principles of action related to plume flow applied in this context. The results suggest that a CO2-dissolved water plume is distributed by hydraulic gradients and density-driven CO2 convective flow. The plume shape, center, and area were analyzed using an image analyzer program; the results demonstrated that the plume characteristic evolved depending on the significant effects on the plume. When the plume was mainly affected by the hydraulic gradient, it rapidly moved from the injection point to the last boundary; in contrast, when it was influenced primarily by density-driven CO2 convective flow, it flowed diagonally downward in the shape of varied branches. The numerical model calculated the migration of the CO2-dissolved water plume affected by both factors. The laboratory experiment and numerical simulation results suggest that the migration of a CO2-dissolved water plume may be affected by the hydraulic gradient and density-driven CO2 convective transport. As such, these factors should be considered when designing and analyzing CO2 monitoring signals to detect CO2 leaks from shallow aquifer systems.

Evaluation of intensive remediation using simulation-optimization modeling based on long-term monitoring at a DNAPL contaminated site.

Simulation-optimization modeling is extensively used to identify optimal remediation designs. However, verifying these optimal solutions often remains unclear. In this study, we determine optimal groundwater remediation strategies using simulation-optimization modeling and assess the effectiveness of previous remediation efforts by validating optimized results through 14 years of long-term monitoring of trichloroethylene (TCE) contamination. The study site is the Road Administrative Office (RAO) in Wonju, Korea, where significant TCE contamination has occurred, and long-term in-situ remediation and monitoring have been conducted. We employ MODFLOW for simulating groundwater flow and MT3D for modeling dissolved TCE concentration distribution. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied to derive optimal groundwater remediation designs. Initial simulation results effectively predicted long-term TCE contamination trends and the impact of short-term in-situ remediation. Our evaluation involved comparing these optimal designs with field test outcomes, leading to the integration of continuous intensive pump-and-treat with in-situ remediation strategies. By comparing various modeling scenarios against long-term TCE contamination trends, we confirmed the effectiveness of previous remediation efforts and demonstrated that the optimal remediation design substantially minimized TCE concentrations at the main source zone. This study highlights successful strategies in historical contamination and remediation trend assessments, proposing an optimal design for pump-and-treat with reduced pumping stress to manage remaining TCE contamination at the site effectively.

Reproducing natural variations in CO2 concentration in vadose zone wells with observed atmospheric pressure and groundwater data.

Continuous CO2 gas monitoring was performed to understand the natural variations of the gas concentration in the vadose zone wells. The monitoring results demonstrated sudden rise and fall signals, which posed a possibility of error in interpreting the CO2 leaking signal from the sequestrating reservoir or evaluating the quantity of removed VOCs at a contaminated site. Based on the monitoring data, conceptual models were established and three cases were numerically simulated to determine whether or not reproducing the natural variations of gas concentration is possible. The simulated numerical model indicated that the atmospheric pressure and groundwater level data should be considered together, rather just only one boundary condition each (top or bottom). Reproducing the natural pattern of the target gas and understanding the gas flow and transport under real closed natural conditions would also be useful. The results demonstrated the need for numerical simulation to predict the natural pattern of the CO2 gas concentration before designing or performing actual CO2 release test or CO2 leakage monitoring in the wells of the vadose zone, as well as at the geologic carbon sequestration site.

Application of geographically weighted regression models to predict spatial characteristics of nitrate contamination: Implications for an effective groundwater management strategy.

Groundwater nitrate contamination has been the main water quality problem threatening the sustainable utilization of water resources in Jeju Island, South Korea. The spatially varying distribution of nitrate levels associated with complex environmental and anthropogenic factors has been a major challenge restricting improved groundwater management. In this study, we applied ordinary least squares (OLS) regression and geographically weighted regression (GWR) models to determine the relationships between the NO3-N concentration and various parameters (topography, hydrology and land use) across the island. A comparison between the OLS regression and GWR prediction models showed that the GWR models outperformed the OLS regression models, with a higher R2 and a lower corrected Akaike Information Criterion (AICc) value than the OLS regression models. Interestingly, the GWR model was able to provide undiscovered information that was not revealed in the OLS regression models. For example, the GWR model found that orchards (OR) and urban (UR) variables significantly contributed to nitrate enrichment in the certain parts of the island, whereas these variables were ignored as a statistically insignificant factor in the OLS regression model. Our study highlighted that GWR models are a useful tool for investigating spatially varying relationships between groundwater quality and environmental factors; therefore, it can be applied to establish advanced groundwater management plans by reflecting the spatial heterogeneity associated with environmental and anthropogenic conditions.

Real-time multi-level CO2 concentration monitoring in vadose zone wells and the implication for detecting leakage events.

Multi-level wells screened at different depths in the vadose zone were installed and used for CO2 and carbon isotope monitoring. Well CO2 time series data were collected along with subsurface and atmospheric parameters such as air pressure, temperature, wind speed, and moisture content. Our aim was to determine the natural factors affecting the variation of CO2 concentration and how the influence of these factors varies with time of day and seasons of the year. We were motivated to understand the cause and extent of CO2 natural fluctuations in vadose zone wells in order to separate natural variation from signals due to anthropogenic CO2 leaks anticipating future monitoring using these wells. Variations of seasonal mean and variance of CO2 concentrations at different depths seem to follow the diurnal trend of subsurface temperature changes that reflect the atmospheric temperature but with time delay and amplitude damping due to heat transport considerations. The temperature in the ground lags behind the change in the atmospheric temperature, thus, the deeper the depth, the longer the time delay and the smaller the amplitude of the change. Monitored seasonal variation as shown in Appendix A shows the temperature-dependent depth-dependent CO2 production in the soil zone indicating higher CO2 concentrations in the summer and fall seasons with high concentrations ranging between 10,990 and 51,600 ppm from spring to summer, and 40,100 and 17,760 ppm from fall to winter. As the temperature in the organic-rich topsoil layer changes from daytime to nighttime, the concentration of CO2 in the soils also changes dynamically in response to chemical and biological reactions. When a screened well is installed in the vadose zone the dynamic temporal and depth difference in CO2 production is further complicated by upward (out of the subsurface) or downward (into the subsurface) gas flow, which will amplify or attenuate the temporal and vertical biochemically produced differences. Nested wells screened at different depths in the vadose zone and wells fully screened through the vadose zone were used for comparison. In addition, experiments changing the well from open to surface air to sealed at the top were conducted. The flow rates of inhaled (downward) and exhaled (upward) gas were estimated based on multi-level monitoring data. Based on time-series monitoring data, we proposed a time-dependent conceptual model to explain the changes of CO2 concentration in wells. The conceptual model was tested through analytical model computations. This conceptual model of natural variation of CO2 will be helpful in utilizing the vadose zone well as a method for monitoring CO2 leakage from subsurface storage or anthropogenic CO2 -producing activities.

Thermal characteristics and bacterial diversity of forest soil in the Haean basin of Korea.

To predict biotic responses to disturbances in forest environments, it is important to examine both the thermophysical properties of forest soils and the diversity of microorganisms that these soils contain. To predict the effects of climate change on forests, in particular, it is essential to understand the interactions between the soil surface, the air, and the biological diversity in the soil. In this study, the temperature and thermal properties of forest soil at three depths at a site in the Haean basin of Korea were measured over a period of four months. Metagenomic analyses were also carried out to ascertain the diversity of microorganisms inhabiting the soil. The thermal diffusivity of the soil at the study site was 5.9 × 10(-8) m(2) · s(-1). The heat flow through the soil resulted from the cooling and heating processes acting on the surface layers of the soils. The heat productivity in the soil varied through time. The phylum Proteobacteria predominated at all three soil depths, with members of Proteobacteria forming a substantial fraction (25.64 to 39.29%). The diversity and richness of microorganisms in the soil were both highest at the deepest depth, 90 cm, where the soil temperature fluctuation was the minimum.

Groundwater pumping effects on contaminant loading management in agricultural regions.

Groundwater pumping changes the behavior of subsurface water, including the location of the water table and characteristics of the flow system, and eventually affects the fate of contaminants, such as nitrate from agricultural fertilizers. The objectives of this study were to demonstrate the importance of considering the existing pumping conditions for contaminant loading management and to develop a management model to obtain a contaminant loading design more appropriate and practical for agricultural regions where groundwater pumping is common. Results from this study found that optimal designs for contaminant loading could be determined differently when the existing pumping conditions were considered. This study also showed that prediction of contamination and contaminant loading management without considering pumping activities might be unrealistic. Motivated by these results, a management model optimizing the permissible on-ground contaminant loading mass together with pumping rates was developed and applied to field investigation and monitoring data from Icheon, Korea. The analytical solution for 1-D unsaturated solute transport was integrated with the 3-D saturated solute transport model in order to approximate the fate of contaminants loaded periodically from on-ground sources. This model was further expanded to manage agricultural contaminant loading in regions where groundwater extraction tends to be concentrated in a specific period of time, such as during the rice-growing season, using a method that approximates contaminant leaching to a fluctuating water table. The results illustrated that the simultaneous management of groundwater quantity and quality was effective and appropriate to the agricultural contaminant loading management and the model developed in this study, which can consider time-variant pumping, could be used to accurately estimate and to reasonably manage contaminant loading in agricultural areas.

Coupling of radon and microbial analysis for dense non-aqueous-phase liquid tracing and health risk assessment in groundwater under seasonal variations.

Dense non-aqueous-phase liquids (DNAPLs) represent one of the most hazardous contaminants of groundwater, posing health risks to humans. Radon is generally used to trace DNAPLs; however, external factors, such as rainfall or stream water, can influence its efficacy. To overcome these limitations, this study pioneered the integration of radon and microbial community structures to explore DNAPL tracing and natural attenuation in the context of seasonal variations for human health risk assessments. The results showed that a radon tracer can estimate DNAPL saturation in the source zone, especially during the dry season when radon deficiency predominates. However, samples exhibited mixing effects during the wet season because of local precipitation. Moreover, bioremediation and low health risks were observed in the plume boundary zone, indicating that microbial dechlorination was a predominant factor determining these risks. The abnormal patterns of radon observed during the wet season can be elucidated by examining microbiological communities. Consequently, a combined approach employing radon and microbial analysis is advocated for the boundary zone, albeit with a less intensive management strategy, compared with that for the source zone. This novel coupling method offers a theoretical and practical foundation for managing DNAPL-contaminated groundwater.

Improving monitoring network design to detect leaks at hazardous facilities: Lessons from a CO2 storage site.

Exploring the challenges posed by uncertainties in numerical modeling for hazardous material storage, this study introduces methodologies to improve monitoring networks for detecting subsurface leakages. The proposed approaches were applied to the Korea CO2 Storage Environmental Management (K-COSEM) test site, undergoing calibration, validation and uncertainty analysis through hydraulic and controlled-CO2 release tests. The calibration phase involved inter-well tracer and multi-well pumping tests, leveraging the Parameter ESTimation (PEST) model to determine the aquifer flow and solute transport properties of the K-COSEM site. To tackle uncertainties with limited observation data, we adopted Latin Hypercube simulation. Our uncertainty analysis confirmed model accuracy in simulating observed CO2 breakthrough curves. We also explored a probabilistic method to identify the environmental change point (EnCP) through correlation analysis with the distance from the CO2 injection well, revealing a linear trend and pinpointed potential preferential flow pathways by assessing detection probabilities. Evaluating CO2 detection capabilities was crucial for optimizing monitoring well placement, highlighting strategic well selection based on detection probabilities. This study advances managing uncertainties in hydrogeological modeling, underscoring the importance of sophisticated models in designing monitoring networks for hazardous leak detection in complex subsurface conditions.

The effects of heavy rain on the fate of urban and agricultural pollutants in the riverside area around weirs using multi-isotope, microbial data and numerical simulation.

The increase in extreme heavy rain due to climate change is a critical factor in the fate of urban and agricultural pollutants in aquatic system. Nutrients, including NO3- and PO43-, are transported with surface and seepage waters into rivers, lakes and aquifers and can eventually lead to algal blooms. δ15N-NO3-, δ18O-NO3-, and δ11B combined with hydrogeochemical and microbial data for groundwater and surface water samples were interpreted to evaluate the fate of nutrients in a riverside area around weirs in Daegu, South Korea. Most of the ions showed similar concentrations in the groundwater samples before and after heavy rain while concentrations of major ions in surface water samples were diluted after heavy rain. However, Si, PO43-, Zn, Ce, La, Pb, Cu and a number of waterborne pathogens increased in surface water after heavy rain. The interpretation of δ11B, δ15N-NO3-, and δ18O-NO3- values using a Bayesian mixing model revealed that sewage and synthetic fertilizers were the main sources of contaminants in the groundwater and surface water samples. δ18O and SiO2 interpreted using the Bayesian mixing model indicated that the groundwater component in the surface water increased from 4.4 % to 17.9 % during the wet season. This is consistent with numerical simulation results indicating that the direct surface runoff and the groundwater baseflow contributions to the river system had also increased 6.4 times during the wet season. The increase in proteobacteria and decrease of actinobacteria in the surface water samples after heavy rain were also consistent with an increase of surface runoff and an increased groundwater component in the surface water. This study suggests that source apportionment based on chemical and multi-isotope data combined with numerical modeling approaches can be useful for identifying main hydrological and geochemical processes in riverside areas around weirs and can inform suggestions of effective methods for water quality management.

Seasonal effects on hydrochemistry, microbial diversity, and human health risks in radon-contaminated groundwater areas.

Groundwater is an important human resource. Daejeon in South Korea faces severe water quality issues, including radon, uranium, and fluoride pollution, all of which pose health risks to humans. With climate change, threats to potable water, such as heavy rain and typhoons, have become common. Therefore, examining the seasonal effects on groundwater quality and resultant health risks is important for understanding the mechanisms of different hydroclimatological conditions to enable the implementation of sustainable management plans in radon-contaminated groundwater areas. However, this issue has not yet been studied. To bridge this gap, in this study, major ions and microbial community structures were employed and groundwater quality index (GWQI) were calculated with hazard index based on limits set by the World Health Organization (WHO) to investigate the hydrochemical characterization and to assess pollution levels. The results showed that the rainy season had distinct hydrochemical characteristics with high correlations between radon and fluoride, and most groundwater samples collected after the typhoon had characteristics similar to those collected during the dry season, owing to the flow path. Furthermore, the microbial diversity and hazard quotient (HQ) values of fluoride revealed that pollution worsened during the dry season. All of the calculated effective dose values of radon exceeded the threshold limit set by the WHO, despite the low GWQI. Infants and children were particularly susceptible to radon-contaminated groundwater. The statistical results of self-organizing map (SOM) suggested that radon analysis was sufficient for public health intervention in the rainy season; however, in the dry season, combined analyses of radon, fluoride, and microbial diversity played important roles in health risk assessment. Our study presents a comprehensive understanding of radon-contaminated groundwater characteristics under seasonal effects and can serve as a reference for other similar zones to provide significant insights into the effective management of radon contamination.

Nitrate sources, timing, and pathways of a permeable volcanic aquifer system with mixed land use in Jeju Island, South Korea.

The occurrence of various N-related human activities increases the difficulty in distinguishing the major sources of NO3- contamination in groundwater, especially in areas with mixed land uses. In addition, the estimation of the timing and pathways of NO3- is necessary to better understand the processes of NO3- contamination in the subsurface aquifer system. This study applied environmental tracers, such as stable isotopes and age tracers (δ15N and δ18O of NO3-, δ11B, chlorofluorocarbons, and 3H), to elucidate the sources, timing, and pathways of NO3- contamination in the groundwaters of the Hanrim area, which has suffered from illegal disposal of livestock wastes since the 1980s, and also characterizes them based on mixed N-contaminant sources such as chemical fertilizers and sewage. The combined use of δ15N and δ11B overcame the limitation of using only NO3- isotopes for the identification of overlapping sources of N and successfully identified the major source of N as livestock wastes. The lumped parameter model (LPM) estimated the binary mixing of the young (age: 23-40 years, NO3-N: 2.55-15.10 mg/L) and old (age: >60 years, NO3-N: <3 mg/L) groundwaters, and explained their age mixing behaviors. The young groundwater was highly affected by livestock-derived N loading during 1987-1998, which coincides with the period of improper dumping of livestock wastes. Furthermore, the young groundwater with elevated NO3-N followed the historical NO3-N curves with younger ages (6 and 16 years) than those derived from the LPM, suggesting the possibility of faster inflows of livestock wastes through the permeable volcanic structures. This study demonstrated that a comprehensive understanding of NO3- contamination processes can be achieved using environmental tracer methods, which enables the efficient management of groundwater resources in areas with multiple N sources.

Identifying the origin and fate of dissolved U in the Boeun aquifer based on microbial signatures and C, O, Fe, S, and U isotopes.

The uranium inventory in the Boeun aquifer is situated near an artificial reservoir (40-70 m apart) intended to supply water to nearby cities. However, toxic radionuclides can enter the reservoir. To determine the U mobility in the system, we analyzed groundwater and fracture-filling materials (FFMs) for environmental tracers, including microbial signatures, redox-sensitive elements and isotopes. In the site, U mass flux ranged from only 9.59 × 10-7 µg/L/y to 1.70 × 10-4 µg/L/y. The δ18O-H2O and 14C signatures showed that groundwater originated mainly from upland recharges and was not influenced by oxic surface water. We observed U accumulations (∼157 mg/kg) in shallow FFMs and Fe enrichments (∼226798 mg/kg) and anomalies in the 230Th/238U activity ratio (AR), 230Th/234U AR, δ56Fe and δ57Fe isotopes, suggesting that low U mobility in shallow depths is associated with a Fe-rich environment. At shallow depths, anaerobic Fe-oxidizers, Gallionella was prevalent in the groundwater, while Acidovorax was abundant near the U ore deposit depth. The Fe-rich environment at shallow depths was formed by sulfide dissolution, as demonstrated by δ34S-SO4 and δ18O-SO4 distribution. Overall, the Fe-rich aquifer including abundant sulfide minerals immobilizes dissolved U through biotic and abiotic processes, without significant leaching into nearby reservoirs.

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.

Estimation of nutrient sources and fate in groundwater near a large weir-regulated river using multiple isotopes and microbial signatures.

The excessive input of nutrients into groundwater can accelerate eutrophication in associated surface water systems. This study combined hydrogeochemistry, multi isotope tracers, and microbiological data to estimate nutrient sources and the effects of groundwater-surface water interactions on the spatiotemporal variation of nutrients in groundwater connected to a large weir-regulated river in South Korea. δ11B and δ15N-NO3- values, in combination with a Bayesian mixing model, revealed that manure and sewage contributed 40 % and 25 % respectively to groundwater nitrate, and 42 % and 27 % to nitrate in surface water during the wet season. In the dry season, the source apportionment was similar for groundwater while the sewage contribution increased to 52 % of nitrate in river water. River water displayed a high correlation between NO3- concentration and cyanobacteria (Microcystis and Prochlorococcus) in the wet season. The mixing model using multiple isotopes indicated that manure-derived nutrients delivered with increased contributions of groundwater to the river during the wet season governed the occurrence of cyanobacterial blooms in the river. We postulate that the integrated approach using multi-isotopic and microbiological data is highly effective for evaluating nutrient sources and for delineating hydrological interactions between groundwater and surface water, as well as for investigating surface water quality including eutrophication in riverine and other surface water systems.

Hydrogeochemistry and isotopic tracing of nitrate contamination of two aquifer systems on Jeju Island, Korea.

The groundwater of Jeju Island (Republic of Korea) is vulnerable to contamination because its aquifers are mainly composed of highly permeable geological units and its agricultural fields are often exposed to excessive use of predominantly synthetic fertilizers. In the Gosan area of Jeju Island, we investigated nitrate contamination in both a perched aquifer above an impermeable clay bed and the regional groundwater beneath this aquitard. The δO and δD values indicate that the perched groundwater is recharged by local precipitation, whereas the regional groundwater is recharged mainly by regional flow from an adjacent mountainous region. The perched groundwater contained very high NO-N concentrations of up to 87 mg/L. The isotopic composition of nitrate in the perched groundwater showed that synthetic fertilizers applied in high excesses of crop N needs were the main cause of aquifer pollution. Elevated nitrate concentrations were also observed in the regional groundwater especially after precipitation events. Concentration and isotopic data revealed that the inflow of shallow perched groundwater along the poorly cemented or uncemented annulus of regional groundwater wells was one of the main reasons for the nitrate contamination observed in the regional groundwater. In both aquifers, δN and δO values showed that the sources of nitrate were derived from synthetic fertilizers that had been recycled in the soil zone by nitrification and in some portions of the perched aquifer (dissolved oxygen concentrations <2 mg/L) indicated that denitrification occurred locally.

Integrated application of a Bayesian mixing model, numerical model, and environmental tracers to characterize groundwater recharge sources in a mountainous area.

In this study, the combined use of a Bayesian mixing model (BMM), numerical model (random walk particle tracking-RWPT), and environmental tracers (δ18O-δD, 3H, and CFC) was applied to elucidate the probabilistic contribution of the recharge sources, flow path, and residence time of groundwater across the mountainous area of Jeju Island, South Korea. Especially, the BMM ability to estimate the variable recharge contributions to the aquifer by different elevations and seasons was investigated. The δ18O-δD isotopes showed that groundwater in the study area was primarily fed by precipitation during the wet season, and the BMM estimated that wet season recharge contributed to approximately 64% of the total. The BMM-based probabilistic estimation of recharge sources revealed a mixed contribution of source waters from different elevations. A notable difference in recharge flow path was observed between highland (>450 masl) and lowland (<400 masl) wells, where the inflow of source water from the regional flow was dominant in the former and both regional and local recharges served as significant groundwater sources in the latter. Evidence from age tracers (3H and CFC-12) also supported different recharge mechanisms between highland and lowland wells. A reasonable match between the BMM- and RWPT-derived recharge contributions (RMSE 0.02-0.06) was achieved within the uncertainty ranges, with RWPT being particularly useful for capturing different flow paths between highland and lowland wells. The dynamics revealed here provide important information for establishing an improved and informed groundwater management plan for the mountainous area of Jeju Island. Ultimately, this study highlights the advantageous integrated analysis of BMM, RWPT, and environmental tracer analyses to enhance the reliability of recharge area estimation and increase the collective understanding of complex hydrogeological systems in mountainous areas.

Abnormal groundwater levels and microbial communities in the Pohang Enhanced Geothermal System site wells pre- and post-Mw 5.5 earthquake in Korea.

In this study, two geothermal wells (PX-1 and PX-2) exhibiting abnormal groundwater levels and microbial communities were examined at the Enhanced Geothermal System site before and after the Pohang earthquake (November 2017). Furthermore, the EXP-1 well level, water temperature, microbial communities and their association with earthquakes, as well as the possibility of future earthquakes were explored. The primary objectives of this research were to: (1) perform correlation and cluster analyses of hydrophysical parameters for earthquakes using next-generation sequencing; (2) analyze pre-, co-, and post-seismic changes in groundwater levels, temperatures, and microbial communities; and (3) further assess the analyzed results of the post-earthquake changes in the groundwater levels and temperatures to interpret their implications. Although the pre-earthquake water levels in the three wells were unknown, their depth-to-water levels post-earthquake ranged from 50.33-98.20 m, 570.91-735.00 m, and 47.70-56.04 m for wells PX-1 (depth 4362 m), PX-2 (4348 m), and EXP-1 (180 m), respectively. In particular, the water levels of PX-2 were abnormally low compared with the surrounding area. Moreover, the geothermal wells demonstrated unstable microbial communities prior to the earthquake. However, while the microbial communities of PX-1 recovered relatively quickly post-earthquake, those of PX-2 failed to stabilize even within two years after the earthquake. Thus, it was inferred here that the PX-2 well is more closely related to seismic activity, the effects of which can still be seen. Accordingly, it is important that PX-2 is continuously monitored until June 2024, the minimum period predicted for the water levels to reach stability.

Physicochemical and isotopic properties of ambient aerosols and precipitation particles during winter in Seoul, South Korea.

The aim of this study was to characterize the physicochemical properties and microbial communities of particulate matter (PM) in Seoul, Korea. We collected long-term (2017-2019) precipitation samples and PM10 and PM2.5 monitoring data to determine the impact of soluble and insoluble chemical species on the soil surface. Ambient PM10 concentrations were higher than PM2.5 concentrations during the monitoring period, but both decreased during rainfall due to the washing effect of precipitation. PM2.5 particles had a "fluffy" shape and contained sulfur (0.2%), but suspended particles (SPs) contained many carbon particles (approximately 60%). Spherical particles containing metal oxides, Fe and Al, might be originated from coal combustion, wild fires, and metal-refining processes under high-temperature conditions. Dissolved ions in precipitation included those eluted from salts and coal combustion based on the correlation coefficients of Na and Cl (R = 0.953) and F and NO3 (R = 0.706). The δ15N-NO3 and δ34S-SO4 of precipitation were enriched as the atmospheric temperature decreased from 9.8 to -1.6°C, implying the influence of domestic coal combustion. Backward trajectories showed that, in winter, air parcels passed through industrialized cities from China to South Korea. The microbial communities associated with PM were strongly influenced by atmospheric conditions. Proteobacteria (range from 4.6 to 76.7%) and Firmicutes (range from 6.0 to 91.4%) were the most dominant phyla and were significantly affected by changes in the PM2.5 environment. The results indicate that the acidity of precipitation and the composition of aerosols were affected by fossil fuel combustion and mineral dust, and that atmospheric conditions may change as PM2.5 concentrations increase.

Evaluating backward probability model under various hydrogeologic and hydrologic conditions.

Contaminant source identification improves the understanding of contaminant source characteristics including location and release time, which can lead to more effective remediation and water resources management plans. The backward probability model can provide probabilities of source locations and release times under various contaminant properties and hydrogeologic conditions. The backward probability model has been applied to numerous synthetic and real contamination sites for locating possible contaminant sources, but it is also important to evaluate the reliability of the backward probability model through rigorous verification analyses. Here, we present a model verification framework for the backward probability model using a stepwise approach from simple to complex model settings: comparison with previous studies, transient saturated flow under various hydrogeologic conditions, and transient variably-saturated flow conditions. As a simple condition, one-dimensional homogeneous problems under steady-state and transient flow conditions were verified by comparing with previous studies. Model verifications with complex conditions were conducted by comparing forward and backward probability simulation results. The verification results demonstrate that the backward probability model performs well for homogeneous problems. For heterogeneous problems, the backward probability model results in slightly different backward travel times due to differences in solute decay and boundary conditions assigned for both forward and backward probability simulations, but the backward travel time at the maximum probability can be reproduced well.