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.

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.

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.

Monitoring the movement of artificially injected CO2 at a shallow experimental site in Korea using carbon isotopes.

The greenhouse effect is closely related to elevated atmospheric CO2 concentrations and therefore, carbon capture and storage (CCS) has attracted attention worldwide as a method for preventing the release of CO2 into the atmosphere, which highlights the importance of monitoring CO2 released from subsurface deposits. In this study, CO2 gas with a δ13C value of -30‰ was injected into soil through pipes installed at a depth of 2.5 m, and samples of CO2 gas released from the soil surface and three soil depths were collected from September 2015 to March 2016 to estimate subsurface CO2 movement. Before and after CO2 injection, the δ13C values of CO2 released from the soil surface ranged from -24.5 to -13.4‰ (average -20.2 ± 2.1‰, n = 25) and from -31.6 to -11.9‰ (average -23.2 ± 4.3‰, n = 49), respectively. The results indicated that the leakage of injected CO2 was successfully detected at the surface. The δ13C values were visualized using an interpolation map to estimate the subsurface CO2 distribution, which confirmed that diffusion of the injected CO2 gas extended to the soil zone where CO2 was not injected. Additionally, variation in δ13C for soil CO2 was detected at the three soil depths (15, 30, and 60 cm), where the values were -16.1, -20.0, and -22.1‰, respectively. Different δ13C values horizontally and vertically indicated that soil heterogeneity led to different CO2 migration pathways and rates. We suggest that the carbon isotope ratio of CO2 is an effective tool for concurrently monitoring CO2 leakage on and under surface in a soil zone if a thorough baseline study is carried out in the field.

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.

Correction to: Potential CO2 intrusion in near-surface environments: a review of current research approaches to geochemical processes.

In the original publication of the article, the third author name has been misspelt. The correct name is given in this correction. The original version of this article was revised.

Potential CO2 intrusion in near-surface environments: a review of current research approaches to geochemical processes.

Carbon dioxide (CO2) capture and storage (CCS) plays a crucial role in reducing carbon emissions to the atmosphere. However, gas leakage from deep storage reservoirs, which may flow back into near-surface and eventually to the atmosphere, is a major concern associated with this technology. Despite an increase in research focusing on potential CO2 leakage into deep surface features and aquifers, a significant knowledge gap remains in the geochemical changes associated with near-surface. This study reviews the geochemical processes related to the intrusion of CO2 into near-surface environments with an emphasis on metal mobilization and discusses about the geochemical research approaches, recent findings, and current knowledge gaps. It is found that the intrusion of CO2(g) into near-surface likely induces changes in pH, dissolution of minerals, and potential degradation of surrounding environments. The development of adequate geochemical research approaches for assessing CO2 leakage in near-surface environments, using field studies, laboratory experiments, and/or geochemical modeling combined with isotopic tracers, has promoted extensive surveys of CO2-induced reactions. However, addressing knowledge gaps in geochemical changes in near-surface environments is fundamental to advance current knowledge on how CO2 leaks from storage sites and the consequences of this process on soil and water chemistry. For reliable detection and risk management of the potential impact of CO2 leakage from storage sites on the environmental chemistry, currently available geochemical research approaches should be either combined or used independently (albeit in a manner complementarily to one another), and the results should be jointly interpreted.

Compositional data analysis and geochemical modeling of CO2-water-rock interactions in three provinces of Korea.

The CO2-rich spring water (CSW) occurring naturally in three provinces, Kangwon (KW), Chungbuk (CB), and Gyeongbuk (GB) of South Korea was classified based on its hydrochemical properties using compositional data analysis. Additionally, the geochemical evolution pathways of various CSW were simulated via equilibrium phase modeling (EPM) incorporated in the PHREEQC code. Most of the CSW in the study areas grouped into the Ca-HCO3 water type, but some samples from the KW area were classified as Na-HCO3 water. Interaction with anorthite is likely to be more important than interaction with carbonate minerals for the hydrochemical properties of the CSW in the three areas, indicating that the CSW originated from interactions among magmatic CO2, deep groundwater, and bedrock-forming minerals. Based on the simulation results of PHREEQC EPM, the formation temperatures of the CSW within each area were estimated as 77.8 and 150 °C for the Ca-HCO3 and Na-HCO3 types of CSW, respectively, in the KW area; 138.9 °C for the CB CSW; and 93.0 °C for the GB CSW. Additionally, the mixing ratios between simulated carbonate water and shallow groundwater were adjusted to 1:9-9:1 for the CSW of the GB area and the Ca-HCO3-type CSW of the KW area, indicating that these CSWs were more affected by carbonate water than by shallow groundwater. On the other hand, mixing ratios of 1:9-5:5 and 1:9-3:7 were found for the Na-HCO3-type CSW of the KW area and for the CSW of the CB area, respectively, suggesting a relatively small contribution of carbonate water to these CSWs. This study proposes a systematic, but relatively simple, methodology to simulate the formation of carbonate water in deep environments and the geochemical evolution of CSW. Moreover, the proposed methodology could be applied to predict the behavior of CO2 after its geological storage and to estimate the stability and security of geologically stored CO2.

Global demand for rare earth resources and strategies for green mining.

Rare earth elements (REEs) are essential raw materials for emerging renewable energy resources and 'smart' electronic devices. Global REE demand is slated to grow at an annual rate of 5% by 2020. This high growth rate will require a steady supply base of REEs in the long run. At present, China is responsible for 85% of global rare earth oxide (REO) production. To overcome this monopolistic supply situation, new strategies and investments are necessary to satisfy domestic supply demands. Concurrently, environmental, economic, and social problems arising from REE mining must be addressed. There is an urgent need to develop efficient REE recycling techniques from end-of-life products, technologies to minimize the amount of REEs required per unit device, and methods to recover them from fly ash or fossil fuel-burning wastes.

Detection of Carbonaceous Aerosols Released in CNT Workplaces Using an Aethalometer.

OBJECTIVES: Black carbon (BC) originating from various combustion sources has been extensively surveyed to characterize the effects of BC on global warming and human health, and many online monitors are available. In this study, BC was considered as a surrogate for carbon-based nanomaterials in an occupational health study. METHODS: Specifically, BC concentrations were monitored continuously with an aethalometer for 24h at four carbon nanotube (CNT) workplaces located in rural, urban, and industrial areas, which had different background air pollution levels. Average BC concentrations for both nonworking (background) and working periods were compared with the recommended exposure limit (REL) of 1 µg m(-3) for elemental carbon that was suggested by the National Institute for Occupational Safety and Health (NIOSH). RESULTS: Diurnal variation of BC concentrations indicated that BC measurements corresponded well with carbonaceous aerosols such as vehicle exhaust particles and CNT aerosols. In the rural CNT workplace, the average background BC concentration (0.36 µg m(-3)) was lower than the REL, but the BC concentration without background correction was higher than the REL during manufacturing hours. In this case, BC measurement is useful to estimate CNT exposure for comparison with the REL. Conversely, in the urban and industrial CNT workplaces, average background BC concentrations (2.05, 1.82, and 2.64 µg m(-3)) were well above the REL, and during working hours, BC concentrations were substantially higher than the background level at workplace C; however, BC concentrations showed no difference from the background levels at workplaces B and D. In these cases (B and D), it is hard to determine CNT exposure because of the substantial environmental exposures. CONCLUSION: Most of the urban ambient BC concentrations were above the REL. Therefore, further analysis and test methods for carbonaceous aerosols need to be developed so that the exposure assessment can be easily carried out at CNT workplaces with high background BC levels such as in urban and industrial areas.

Examination of surface phenomena of V2O5 loaded on new nanostructured TiO2 prepared by chemical vapor condensation for enhanced NH3-based selective catalytic reduction (SCR) at low temperatures.

In this article, we describe the investigation and surface characterization of a chemical vapor condensation (CVC)-TiO2 support material used in a V2O5/TiO2 catalyst for enhanced selective catalytic reduction (SCR) activity and confirm the mechanism of surface reactions. On the basis of previous studies and comparison with a commercial TiO2 catalyst, we examine four fundamental questions: first, the reason for increased surface V(4+) ion concentrations; second, the origin of the increase in surface acid sites; third, a basis for synergistic influences on improvements in SCR activity; and fourth, a reason for improved catalytic activity at low reaction temperatures. In this study, we have cited the result of SCR with NH3 activity for removing NOx and analyzed data using the reported result and data from previous studies on V2O5/CVC-TiO2 for the SCR catalyst. In order to determine the properties of suitable CVC-TiO2 surfaces for efficient SCR catalysis at low temperatures, CVC-TiO2 specimens were prepared and characterized using techniques such as XRD, BET, HR-TEM, XPS, FT-IR, NH3-TPD, photoluminescence (PL) spectroscopy, H2-TPR, and cyclic voltammetry. The results obtained for the CVC-TiO2 materials were also compared with those of commercial TiO2.

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.

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.

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.

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.

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.

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.

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.