Determination of contamination sources and geochemical reactions in groundwater of a mine area using Cu, Zn, and S-O isotopes.

To determine contamination sources and pathways, the use of multiple isotopes, including metal isotopes, can increase the reliability of environmental forensic techniques. This study differentiated contamination sources in groundwater of a mine area and elucidated geochemical processes using Cu, Zn, S-O, and O-H isotopes. Sulfate reduction and sulfide precipitation were elucidated using concentrations of dissolved sulfides, δ34SSO4, δ18OSO4, and δ66Zn. The overlying contaminated soil was possibly responsible for the contamination of groundwater at <5 mbgl, which was suggested by low δ65Cu values (0.419-1.120‰) reflecting those of soil (0.279-1.115‰). The existence of dissolved Cu as Cu(I) may prevent the increase in δ65Cu during leaching of contaminated soil in the sulfate-reducing environment. In contrast, the groundwater at >5 mbgl seemed to be highly affected by the contamination plume from the adit water, which was suggested by high SO42- concentrations (407-447 mg L-1) and δ65Cu (0.252-2.275‰) and δ66Zn (-0.105‰-0.362‰) values at a multilevel sampler approaching those of the adit seepages. Additionally, the O-H isotopic ratios were distinguished between <5 mbgl and >5 mbgl. Using δ65Cu and δ66Zn to support the determination of groundwater contamination sources may be encouraged, particularly where the isotopic signatures are distinct for each source.

Predicting leachate impact on groundwater using electrical conductivity and oxidation-reduction potential measurements: An empirical and theoretical approach.

This study developed innovative predictive models of groundwater pollution using in situ electrical conductivity (EC) and oxidation-reduction potential (ORP) measurements at livestock carcass burial sites. Combined electrode analysis (EC and ORP) and machine learning techniques efficiently and accurately distinguished between leachate and background groundwater. Two models-empirical and theoretical-were constructed based on a supervised classification framework. The empirical model constructs a classifier with high accuracy, sensitivity, and specificity, utilizing the comprehensive in situ EC and ORP measurements. The theoretical model with only two end members achieves comparable performance by simulating the leachate-groundwater interactions using a geochemical mixing model. Besides enhancing the early detection capabilities, our approach considerably reduces the reliance on extensive hydrochemical analyses, thus streamlining the monitoring process. Moreover, the use of field parameters was found to proactively identify potential pollution incidents, enhancing the efficiency of groundwater monitoring strategies. Our approach is applicable to various waste disposal sites, indicating its extensive potential for environmental monitoring and management.

Using isometric log-ratio in compositional data analysis for developing a groundwater pollution index.

This study introduces a novel groundwater pollution index (GPI) formulated through compositional data analysis (CoDa) and robust principal component analysis (RPCA) to enhance groundwater quality assessment. Using groundwater quality monitoring data from sites impacted by the 2010-2011 foot-and-mouth disease outbreak in South Korea, CoDa uncovers critical hydrochemical differences between leachate-influenced and background groundwater. The GPI was developed by selecting key subcompositional parts (NH4+-N, Cl-, and NO3--N) using RPCA, performing the isometric log-ratio (ILR) transformation, and normalizing the results to environmental standards, thereby providing a more precise and accurate assessment of pollution. Validated against government criteria, the GPI has shown its potential as an alternative assessment tool, with its reliability confirmed by receiver operating characteristic curve analysis. This study highlights the essential role of CoDa, especially the ILR -transformation, in overcoming the limitations of traditional statistical methods that often neglect the relative nature of hydrochemical data. Our results emphasize the utility of the GPI in significantly advancing groundwater quality monitoring and management by addressing a methodological gap in the quantitative assessment of groundwater pollution.

Assessment of environmental forensic indicator for anthropogenic groundwater contamination via target/suspect/nontarget analysis using HRMS techniques.

This study compared target/suspect/nontarget analysis via liquid chromatography-high-resolution mass spectrometry (LC-HRMS) with traditional environmental forensic methods, specifically nitrate and its stable N isotope, in assessing groundwater pollution from livestock manure and agriculture. Using an in-house database of 1471 target and suspects, 35 contaminants (pesticides, veterinary drugs, surfactants) were identified, some uniquely linked to specific pollution sources, such as sulfamethazine and 4-formylaminoantipyrine in manure-affected areas. Pesticides were widespread, typically showing higher intensity in agricultural zones. On the other hand, the results of stable N isotope analysis (δ15N-NO3: 4.8 to 16.4‰) indicated the influence of human activities such as fertilizers, sewage, and manure in all sampling sites, including the control site far from the pollution sources and cannot differentiate the specific sources. The study underscores LC-HRMS's efficacy in different pollution sources, surpassing the limitations of stable N isotope analysis, and provides valuable insights for polluted groundwater source tracking strategies.

Identification of organic chemical indicators for tracking pollution sources in groundwater by machine learning from GC-HRMS-based suspect and non-target screening data.

In this study, the strong analytical power of gas chromatography coupled to a high resolution mass spectrometry (GC-HRMS) in suspect and non-target screening (SNTS) of organic micropollutants was combined with machine learning tools for proposing a novel and robust systematic environmental forensics workflow, focusing on groundwater contamination. Groundwater samples were collected from four different regions with diverse contamination histories (namely oil [OC], agricultural [AGR], industrial [IND], and landfill [LF]), and a total of 252 organic micropollutants were identified, including pharmaceuticals, personal care products, pesticides, polycyclic aromatic hydrocarbons, plasticizers, phenols, organophosphate flame retardants, transformation products, and others, with detection frequencies ranging from 3 % to 100 %. Amongst the SNTS identified compounds, a total of 51 chemical indicators (i.e., OC: 13, LF: 12, AGR: 19, IND: 7) which included level 1 and 2 SNTS identified chemicals were pinpointed across all sampling regions by integrating a bootstrapped feature selection method involving the bootfs algorithm and a partial least squares discriminant analysis (PLS-DA) model to determine potential prevalent contamination sources. The proposed workflow showed good predictive ability (Q2) of 0.897, and the suggested contamination sources were gasoline, diesel, and/or other light petroleum products for the OC region, anthropogenic activities for the LF region, agricultural and human activities for the AGR region, and industrial/human activities for the IND region. These results suggest that the proposed workflow can select a subset of the most diagnostic features in the chemical space that can best distinguish a specific contamination source class.

Characteristics of soil contamination by potentially toxic elements in mine areas of Mongolia.

Soil contamination by potentially toxic elements (PTEs), such as metal(loid)s, in mining areas was characterized on a nationwide scale in Mongolia to understand the contamination status throughout the country, according to mine types. Positive matrix factorization (PMF) analysis exhibited better classification and explanation of soil contamination according to ore types compared to conventional statistical analysis methods such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The results of PMF analysis for metal(loid) contents in 1425 topsoil samples collected from 272 mines illuminated four Factors, which primarily contributed to As (Factor 1), Pb, Zn, and Cd (Factor 2), Ni (Factor 3), and Cu and Cd (Factor 4) contaminations, respectively. In hard-rock gold mines, As was enriched and the contribution of Factor 1 was high (31.2%) due to the affinity between As and Au. In placer gold mines, the contribution of Factor 3 (41.8%) was high due to the affinity between Ni and weathering-resistant heavy minerals. For base metal, fluorite, and coal mines, contributions of Factors 2 (32.1-50.9%) and 4 (17.7-33.6%) were high owing to sulfides containing Pb-Zn-d and Cu. These impacts of mine types were altered by local geology (e.g., skarn). Meanwhile, Hg amalgamation contributed to Hg contamination in a few hard-rock gold mines. These results suggest that soil contaminants in mining areas are mainly affected by the type of deposits with geochemical affinities, region-specific ore characteristics, and artificial processing. Understanding these effects will help establish national strategies for countermeasures, such as soil rehabilitation in mining areas.

Fractionation behaviors of Cu, Zn, and S-O isotopes in groundwater contaminated with petroleum and treated by oxidation.

Fractionation behaviors of Cu and Zn isotopes have been increasingly studied at the field scale, but those in various redox conditions of groundwater contaminated with petroleum and treated by oxidation have not been assessed. In this study, δ65Cu and δ66Zn as well as δ34SSO4 and Δδ18OSO4-H2O were assessed in wells undergoing contamination by total petroleum hydrocarbons (TPH) and oxidation using H2O2 in 2021 and 2022. High δ34SSO4 and relevant parameters (e.g., dissolved sulfide and HCO3-) indicated the occurrence of sulfate reduction. The plot of δ65Cu versus δ34SSO4 effectively indicated precipitation of Cu sulfides and their reoxidation at oxidation wells. Although the plot of δ66Zn versus δ34SSO4 could also indicate reoxidation of Zn sulfides, the Zn isotopic fingerprint of sulfide precipitation may have been masked by fractionation by sorption. The advantage of using δ65Cu in the redox reactions resulted from the wider range of δ65Cu owing to the redox behavior of Cu. The plot combining isotopic fractionations of Cu and S can assist in assessing sulfide precipitation and oxidative treatment in TPH-contaminated groundwater.

A supervised machine learning approach to discriminate the effect of carcass leachate on shallow groundwater quality around on-farm livestock mortality burial sites.

The evaluation of leachate leakage at livestock mortality burial sites is challenging, particularly when groundwater is previously contaminated by agro-livestock farming. Supervised machine learning was applied to discriminate the impacts of carcass leachate from pervasive groundwater contamination in the following order: data labeling, feature selection, synthetic data generation, and classification. Physicochemical data of 359 water samples were collected from burial pits (LC), monitoring wells near pits (MW), pre-existing shallow household wells (HW), and background wells with pervasive contamination (BG). A linear classification model was built using two representative groups (LC and BG) affected by different pollution sources as labeled data. A classifier was then applied to assess the impact of leachate leakage in MW and HW. As a result, leachate impacts were observed in 40% of MW samples, which indicates improper construction and management of some burial pits. Leachate impacts were also detected in six HW samples, up to 120 m downgradient, within one year. The quantitative decision-making tool to diagnose groundwater contamination with leachate leakage can contribute to ensuring timely responses to leakage. The proposed machine learning approach can also be used to improve the environmental impact assessment of water pollution by improper disposal of organic waste.

Complex behavior of petroleum hydrocarbons in vadose zone: A holistic analysis using unsaturated soil columns.

The migration of petroleum hydrocarbons in vadose zone involves complex coupled processes such as downward displacement and natural attenuation. Despite its significance in determining groundwater vulnerability to petroleum contamination and optimizing the remedial strategy, it has not been comprehensively studied in terms of overall processes under field-relevant conditions. In this study, a series of unsaturated soil column experiments were conducted by simulating subsurface diesel contamination within a vadose zone using different soil textures at different soil bulk densities and initial diesel concentrations, while partly exposing them to simulated precipitation. The results showed that the soil column with less fine fraction was favorable for the downward migration of diesel but unfavorable for its natural degradation. However, precipitation complicated the relative conductivities of multiple fluids (water, air, and diesel) through the pore network, therby decreasing diesel migration and degradation. For example, the downward migration of diesel in the SL column decreased by 8.4% under precipitation, while the overall attenuation rate dropped to almost 0.24% of its original state. Lowering bulk density (from 1.5 to 1.23 g/cm3), however, could enhance the attenuation rate presumably due to the secured void space for the incoming fluids. A high initial concentration of diesel (2%; w/w) inhibited its natural attenuation, while its influence on its vertical propagation after the precipitation was not significant. The present findings provide a mechanistic basis for approximating the behavior of petroleum hydrocarbons in a random vadose zone.

Metal(loid)-specific sources and distribution mechanisms of riverside soil contamination near an abandoned gold mine in Mongolia.

Tailings were discharged to the Boroo River from gold mining by amalgamation, resulting in soil contamination near the river. To identify the sources and distribution mechanisms of each metal(loid) in the soil, a total of 184 soil samples were collected near the river and analyzed for As, Cd, Cu, Pb, Zn, and Hg contents. According to the positive matrix factorization result, three factors affected the contamination levels: the application of Hg for gold mining (Factor 1), light minerals containing Cu and Zn (Factor 2), and heavy minerals containing As and Cd (Factor 3). Soil samples were classified into four groups by hierarchical clustering. Groups A and B seemed to be affected by light and heavy minerals discharged in early and later stages of ore processing, respectively. The spatial distribution of the groups suggested differentiation in travel distances by specific gravity. Groups C and D showed high Hg contents implying the effect of Hg mismanagement and spill accidents. The study results show that the distribution of soil contaminants near rivers in mining areas is controlled by the specific gravity of minerals discharged to the environment (e.g., river), ore processing stages, and insufficient recovery and/or spills of Hg, which will help establish restoration measures.

Coupled effect of porous network and water content on the natural attenuation of diesel in unsaturated soils.

The natural attenuation potential of a vadose zone against diesel is critical for optimizing remedial actions and determining groundwater vulnerability to contamination. Here, diesel attenuation in unsaturated soils was systematically examined to develop a qualitative relationship between physical soil properties and the natural attenuation capacity of a vadose zone against diesel. The uniformity coefficient (Cu) and water saturation (Sw, %) were considered as the proxies reflecting the degree of effects by porous network and water content in different soils, respectively. These, in turn, are related to the primary diesel attenuation mechanisms of volatilization and biodegradation. The volatilization of diesel was inversely proportional to Cu and Sw, which could be attributed to effective pore channels facilitating gas transport. Conversely, biodegradation was highly proportional to Cu under unsaturated conditions (Sw = 35-71%), owing to nutrients typically associated with fine soil particles. The microbial community in unsaturated soils was affected by Sw rather than Cu. The overall diesel attenuation including volatilization and biodegradation was optimized at Sw = 35% for all tested soils.

Constraining the effectiveness of inherent tracers of captured CO2 for tracing CO2 leakage: Demonstration in a controlled release site.

Geological storage of carbon dioxide (CO2) is an integral component of cost-effective greenhouse gas emissions reduction scenarios. However, a robust monitoring regime is necessary for public and regulatory assurance that any leakage from a storage site can be detected. Here, we present the results from a controlled CO2 release experiment undertaken at the K-COSEM test site (South Korea) with the aim of demonstrating the effectiveness of the inherent tracer fingerprints (noble gases, δ13C) in monitoring CO2 leakage. Following injection of 396 kg CO2(g) into a shallow aquifer, gas release was monitored for 2 months in gas/water phases in and above the injection zone. The injection event resulted in negative concentration changes of the dissolved gases, attributed to the stripping action of the depleted CO2. Measured fingerprints from inherent noble gases successfully identified solubility-trapping of the injected CO2 within the shallow aquifer. The δ13C within the shallow aquifer could not resolve the level of gas trapping, due to the interaction with heterogeneous carbonate sources in the shallow aquifer. The time-series monitoring of δ13CDIC and dissolved gases detected the stripping action of injected CO2(g), which can provide an early warning of CO2 arrival. This study highlights that inherent noble gases can effectively trace the upwardly migrating and fate of CO2 within a shallow aquifer.

NaHCO3- and NaCl-Type Hot Springs Enhance the Secretion of Inflammatory Cytokine Induced by Polyinosinic-Polycytidylic Acid in HaCaT Cells.

BACKGROUND: Background: Hot springs have been traditionally used as an alternative treatment for a wide range of diseases, including rheumatoid arthritis, bronchial asthma, diabetes, hypertension, psoriasis and atopic dermatitis. However, the clinical effects and therapeutic mechanisms associated with hot springs remain poorly defined. OBJECTIVE: The purpose of this study was to demonstrate the different effects of hot springs on cellular viability and secretion of inflammatory cytokines on keratinocyte in two geographically representative types of hot springs: NaHCO3-type and NaCl-type, which are the most common types in South Korea. METHODS: We performed WST-1, BrdU measurements, human inflammatory cytokine arrays and enzyme-linked immunosorbent assay in HaCaT cells stimulated with toll-like receptor 3 by polyinosinicpolycytidylic acid. RESULTS: The interaction effects of cell viability and cell proliferation were not significantly different regardless of polyinosinic-polycytidylic acid stimulation and cultured hot springs type. Cytokine array and enzymelinked immunosorbent assay analysis showed increased expression of inflammatory cytokines such as interleukin6 and granulocyte-macrophage colony-stimulating factor by polyinosinic-polycytidylic acid stimulation, with expression levels differing according to hot springs hydrochemical composition. Cytokine reduction was not significant. CONCLUSION: The effects and mechanisms of hot springs treatment in keratinocytes were partially elucidated.

Spatial patterns of Zn, Cd, and Pb isotopic compositions of ground and surface water in mine areas of South Korea reflecting isotopic fractionation during metal attenuation.

As application of multiple metal isotopes can effectively constrain geochemical behavior of contaminants and assess contamination sources and pathways, field-scale studies on the geochemically interlinked fractionation of Zn and Cd isotopes in groundwater are needed. In this study, we collected groundwater samples from multi-level samplers downstream of tailings dumps as well as surface water, ore mineral, precipitate, and tailings samples at the Sambo and Buddeun metallic ore mines in South Korea, and analyzed their Zn, Cd, Pb, and sulfur isotopic compositions. Furthermore, isotopic ratios of ore mineral samples from additional four mines in South Korea (Dangdu, Dongbo, Gomyeong, Samgwang) were compared. A dual isotopic approach using Zn and Cd isotopes was used to assess fractionation processes, and Pb isotopic signatures reflecting their sources were assessed. Increasing trends of δ66Zn and δ114Cd with decreasing Zn and Cd concentrations were observed in groundwater, which was saturated with respect to ZnS (amorphous and sphalerite) and CdS (greenockite). Moreover, for some groundwater samples, δ66Zn showed a positive relationship with δ34SSO4. These results suggest that Zn and Cd are precipitated as sulfide following sulfate reduction. In the plot of δ66Zn against δ114Cd, relatively high and/or increasing δ66Zn in groundwater suggested the effect of fractionation due to sulfide precipitation, while variable and high δ114Cd values suggested the fractionation by adsorption and/or sulfide precipitation, which were based on positive fractionation factors for δ66Zn and δ114Cd during sulfide precipitation and mostly negative and positive fractionation factors for δ66Zn and δ114Cd, respectively, during adsorption. This study shows that the combined use of Zn and Cd isotopes in groundwater can effectively differentiate between adsorption and sulfide precipitation following sulfate reduction in groundwater. Additionally, the 208Pb/206Pb ratios of most water samples reflected those of ore and tailings samples, which verified usefulness of Pb isotopes in water in investigating Pb contamination sources.

Identification of iron and sulfate release processes during riverbank filtration using chemical mass balance modeling.

Various hydrogeochemical processes can modify the quality of river water during riverbank filtration (RBF). Identifying the subsurface processes responsible for the bank-filtered water quality is challenging, but essential for predicting water quality changes and determining the necessity of post-treatment. However, no systematic approach for this has been proposed yet. In this study, the subsurface hydrogeochemical processes that caused the high concentrations of total iron (Fe) and sulfate (SO42-) in the bank-filtered water were investigated at a pilot-scale RBF site in South Korea. For this purpose, water quality variations were monitored in both the extraction well and the adjacent river over five months. The volumetric mixing ratio between the river water and the native groundwater in the RBF well was calculated to understand the effect of mixing on the quality of water from the well and to assess the potential contribution of subsurface reactions to water quality changes. To identify the subsurface processes responsible for the evolution of Fe and SO42- during RBF, an inverse modeling based on the chemical mass balance was conducted using the water quality data and the calculated volumetric mixing ratio. The modeling results suggest that pyrite oxidation by abundant O2 present in an unsaturated zone could be a primary process explaining the evolution of total Fe and SO42- during RBF at the study site. The presence of pyrite in the aquifer was indirectly supported by iron sulfate hydroxide (Fe(SO4)(OH)) detected in oxidized aquifer sediments.

Shift of nitrate sources in groundwater due to intensive livestock farming on Jeju Island, South Korea: With emphasis on legacy effects on water management.

Time lags between anthropogenic nitrogen inputs and their impacts to nitrate levels cause a misunderstanding for sources and subsequently misguide the groundwater management.We investigated the hydrochemical data of groundwater samples (n = 172 from 49 wells) with chlorofluorocarbons (CFCs)-based groundwater age dating and stable N (δ15N) and O isotopes (δ18O) of nitrate to assess the legacy effect of livestock farming to groundwater in an agricultural area where intensive livestock farming started in the 1970s and illegal dumping of manure wastewater in a lava cave was revealed in 2015. Approximately 90% of the groundwater samples had nitrate concentrations exceeding the natural threshold (5.5 mg/L NO3-) for nitrate contamination and 34% exceeded the World Health Organization's guideline for drinking water quality (44.3 mg/L), indicating severe nitrate contamination. The δ15NNO3 values (5.5 to 24.3‰) in groundwater exceeding the threshold of nitrate showed that livestock manure was a major nitrate source, while ammonium fertilizer also seemed influential given the δ15NNO3 values in the overlapping fields of N sources. Factor analysis of hydrochemical data also supported nitrate contamination by manure as well as by plant farming in the study area. Based on the spatial distribution of nitrate levels and δ15NNO3, livestock farming affected nitrate contamination by illegal manure dumping in the leakage cave. According to a Bayesian mixing model, the contribution of manure wastewater was 33.5 to 81.8% as of 2015-2018, with the rest from fertilizers. Meanwhile, the groundwater ages showed negative correlations with both nitrate levels (r = -0.90) and δ15NNO3 values (r = -0.74) on a log scale, consistent with the increasing N release from livestock farming since the 1960s. In particular, the median value of δ15NNO3 rapidly increased to 9.2‰ in groundwater recharged between the late 1970s and early 1990s when N production exponentially increased, implying a significant effect of livestock farming after the 1980s. Groundwater quality is expected to deteriorate over the next several decades based on the groundwater ages (> 23.5 years), the increased N production from livestock farming, and the legacy effect of N. Long-term groundwater management plans (> 25 years) are required to decrease N loads in the study area, because it takes time for management practices to take effect. The study results are a good reference for groundwater management in regions with a source shift to livestock farming under intensive livestock production systems. Moreover, the chronological study using historical N production, groundwater age data, and dual nitrate isotopes can be applied to other regions with multiple N sources and their shifting for identifying sources and estimating time lags.

Delineating the impacts of poultry burial leachate on shallow groundwater in a reclaimed agro-livestock farming area, using multivariate statistical analysis of hydrochemical data.

Burial is applied to dispose of livestock carcasses due to its convenience and cost efficiency despite concerns about groundwater contamination by leachate from burial pits. In particular, the burial method has caused debates about groundwater contamination sources around on-farm livestock burial sites because of pre- and coexisting contamination from livestock production and agriculture. To assess the causes of groundwater contamination around poultry burial pits that were constructed after an outbreak of avian influenza in 2010-11 in Korea, hydrochemical data of groundwater samples from monitoring wells (MWs, n = 14) and household wells (HWs, n = 30) were monitored to differentiate contamination sources. Hydrochemical data indicated that groundwater from MWs is characterized by higher enrichments of inorganic constituents including electrical conductivity (EC), NH4, Ca, Mg, K, SO4, HCO3, Fe(Total), and Mn(Total), but lower concentrations of DO than groundwater from HWs. The combined use of the principal component analysis (PCA) and K-means cluster analysis (KCA) indicated that groundwater in seven MWs was affected by leachate. The parameters such as NH4, Ca, Mg, K, SO4, HCO3, Fe(Total), and Mn(Total) are expected to be useful to identify the impact of leachate on groundwater in agricultural areas. This study suggests that (1) regional hydrochemical characteristics should be assessed to distinguish the effect of livestock burial leachate from other contamination sources and (2) the combined use of PCA and KCA is effective to identify the weakened impact of leachate leakage among overlapping multiple sources and processes of groundwater contamination.

Groundwater contamination assessment in Ulaanbaatar City, Mongolia with combined use of hydrochemical, environmental isotopic, and statistical approaches.

Ulaanbaatar City, Mongolia is rapidly becoming urbanized and attracts great attention because of environmental issues. This study was performed to assess the status of groundwater quality in Ulaanbaatar at an early but growing stage of urbanization, focusing on nitrate contamination in relation to land use. Along with high total dissolved solids and NO3- concentrations, significant contamination of groundwater is indicated by positive loadings of NO3-, Cl- and δ15N-NO3- along the first principal component of the principal component analysis (PCA). Based on the concentrations and δ15N values of nitrate, groundwater is classified into two groups: Group I (baseline quality) and II (contaminated). Nitrate in Group II water in urbanized (esp. peri-urban) areas is higher in concentration (> 10 mg/l NO3-) and N-isotopic values (> 10‰ δ15N-NO3-), while pristine hydrochemistry is observed restrictedly in grassland and forest areas. Other ions (e.g., Cl- and SO42-) are also higher in Group II water. The δ15N-NO3- values in Group II water in combination with the spatial distribution on the land use map indicate that nitrate originates from untreated sewage effluents including pit-latrine leakage in peri-urban areas, while nitrate in Group I water originates from soil organic matter. The relationship between nitrate concentrations and δ2H (and δ18O) values of water suggests that nitrate enrichment is also influenced by evaporation during groundwater recharge. With the help of PCA for compositional data, we suggest a hydrochemical index for groundwater contamination assessment; i.e., the Groundwater Quality Index (GQI) that consists of three variables (concentrations of dissolved silica, nitrate and chloride) and can be used to delineate zones vulnerable to nitrate contamination as a crucial step for the efficient monitoring and management of groundwater quality. The study results suggest an urgent need for the management of unsealed pit latrines that are common in peri-urban areas with high population density.

Quantitative assessment of deep-seated CO2 leakage around CO2-rich springs with low soil CO2 efflux using end-member mixing analysis and carbon isotopes.

This study examined a mountainous area with two hydrochemically distinct CO2-rich springs to understand the origin, flow, and leakage of CO2, which may provide implications for precise monitoring of CO2 leakage in geological carbon storage (GCS) sites. The carbon isotopic compositions of dissolved inorganic carbon (DIC) in CO2-rich water (δ13CDIC) and those of soil CO2 (δ13CCO2) indicated a deep-seated CO2 supply to the near-surface environment in the study area. The hydrochemical difference (e.g. pH, total dissolved solids) for the two CO2-rich springs separated by 7 m, despite similar δ13CDIC and partial pressure of CO2, was considered as the result of different evolution of shallow groundwater affected by deep-seated CO2 preferentially rising along fracture zones. Electrical resistivity tomography also suggested flow through fracture zones beneath the CO2-rich springs, showing low resistivity compared to other surveyed zones. However, soil CO2 efflux was low compared to that in other natural CO2 emission sites, and in particular it was noticeably low near the CO2-rich springs, whereas δ13CCO2 was high close the CO2-rich springs. The dissolution of CO2 in the near-surface water body seemed to decrease the deep-seated CO2 leakage through the soil layer, while δ13CCO2 imprinted the source. End-member mixing analysis was performed to assess the contribution of deep-seated CO2 to the low soil CO2 efflux by assuming that atmospheric CO2 and soil CO2 (by respiration) as well as deep-seated CO2 contribute to the soil CO2 efflux. For each end-member, characteristic δ13CCO2 and CO2 concentrations were defined, and then their apportionment to soil CO2 efflux was estimated. The resultant proportion of deep-seated CO2 was up to 8.8%. Unlike the spatial distribution of high soil CO2 efflux, high proportions exceeding 3% were found around the CO2-rich springs along the east-west valley. The study results indicate that soil CO2 efflux measurement should be combined with carbon isotopic analysis in GCS sites for CO2 leakage detection because CO2 dissolution in the underground water body may blur leakage detection on the surface. The implication of this study is the need to quantitatively assess the contribution of deep-seated CO2 using the soil CO2 concentration, soil CO2 efflux, and δ13CCO2 at each measurement site.

Efficacy of in situ well-based denitrification bio-barrier (WDB) remediating high nitrate flux in groundwater near a stock-raising complex.

This study assessed the feasibility of an in situ well-based denitrification bio-barrier (WDB) for managing groundwater contaminated with high-strength nitrate. To evaluate the efficacy of WDB using fumarate as a carbon source and/or electron donor, three sequential single-well push-pull tests (SWPPTs) were conducted at six test sites. The values of the isotope enrichment factor (ɛ) ranging from -6.5‰ to -22.6‰ and the detection and degradation of nitrite and nitrous oxide confirmed complete in situ denitrification of nitrate to nitrogen gas. The ratio of the first-order rate coefficient of fumarate to nitrate (k1,fum/k1,NO3) was obtained to estimate the amount and frequency of fumarate injection for the effective design of WDB. At three sites, the ratios ranged from 0.67 to 0.80, while the other two sites showed higher ratios of 2.97 and 2.20 than the theoretical values and significant amounts of sulfate reduction, theoretically equivalent to 6.5% of total fumarate consumption. Considering the theoretical mole ratio of fumarate to nitrate of 0.98, the amount and frequency of fumarate injection is site specific. During the operating WDB, the average annual nitrate mass degraded (95% CI) was 2.2 ± 1.0 kg N/yr/well. The amount of N reduced by one well of WDB is equivalent to treating 110 m3 of groundwater at 30 mg N/L to the level of 10 mg N/L for one year. WDB would be an effective remediation option for managing high nitrate flux in groundwater.