The Journal of
the Korean Society on Water Environment

Bimonthly
  • ISSN : 2289-0971 (Print)
  • ISSN : 2289-098X (Online)
  • KCI Accredited Journal

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Study on the Removal of Antibiotic-Resistant Bacteria from Wastewater Effluent and Combined Sewer Overflow Using UV-LED

이재은(Jae Eun Lee) ; 김란희(Lan Hee Kim) ; 김성표(Sungpyo Kim)

https://doi.org/10.15681/KSWE.2025.41.3.123

The global rise in antibiotic resistance poses a major public health threat, with wastewater treatment plants (WWTPs) playing a crucial role in its spread through urban water systems. WWTPs receive wastewater from households, hospitals, agriculture, and industries, which contains antibiotic residues, resistant bacteria, and pathogenic microorganisms. The resistome, the collection of environmental antibiotic resistance, is influenced by WWTP effluent, which can facilitate resistance transfer among microorganisms. The current treatment technologies do not completely eliminate antibiotics or resistant bacteria, necessitating effective disinfection methods. Ultraviolet-light-emitting diode (UV-LED) disinfection, a mercury-free technology emitting UV light used to directly damage microbial DNA, has gained attention due to its environmental benefits, energy efficiency, and ease of maintenance. This study evaluated UV-LED (265 nm, 278 nm, and 265 nm + 278 nm) for its efficacy in removing antibiotic-resistant bacteria from 1-liter wastewater samples in a circulating system, with exposure times of 1?30 minutes. Chlorine oxidants (2.4 ppm and 4.8 ppm) were also tested for comparison. The results showed that UV-LED alone achieved a 0.8?2.3 log reduction while combining UV-LED with 2.4 ppm Cl2 increased removal to 1.0?2.3 log and combining with 4.8 ppm Cl2 to 2.0?4.3 log. Multi-wavelength UV-LED treatment achieved similar results, with removal increasing from 1.0?2.3 log to 1.2?2.4 log (2.4 ppm Cl2) and 2.2?4.8 log (4.8 ppm Cl2). These findings highlight the potential of UV-LED, especially when combined with chlorine, as an effective approach for controlling antibiotic-resistant bacteria in WWTP effluent.

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Statistical Analysis of the Discharge Characteristics of Water Pollutants in Industrial Wastewater in Gwangju Metropolitan City

박지영(Ji-young Park) ; 서희정(Hee-jeong Seo) ; 양윤철(Yoon-cheol Yang) ; 김하람(Ha-ram Kim) ; 박주현(Ju-hyun Park) ; 이우진(Woo-jin Lee) ; 전홍대(Hong-dae Jeon) ; 이윤국(Yoon-guk Lee) ; 김연희(Yeon-hee Kim)

https://doi.org/10.15681/KSWE.2025.41.3.133

This study investigated the characteristics of wastewater pollutant emissions from industrial sites in Gwangju Metropolitan City and analyzed water pollution data to assess the risks of exceeding emission standards. It also aimed to predict these risks by identifying the key influencing factors for each industry. The risk assessment by pollutant revealed that among specific water hazardous substances, 1,4-dioxane posed the highest risk of exceeding standards, followed by chloroform and dichloromethane. Industry-specific assessments showed that the steel/metal processing (MT) industry had the highest risk of exceeding standards, followed by the waste treatment/laundry (WT) industry, automobile parts manufacturing (AM), and plating (PT) industry. Principal component analysis of heavy metals was conducted in the AM, PT and MT industries. In the PT industry, factor 1 consisted of Ni, Cr, and Cu, which are directly used in electroplating processes, while factor 2 included Mn, Zn, and Ba, which are commonly used in other plating processes. Regression analysis using the newly derived factors as independent variables produced statistically significant models with explanatory powers of 68.2% for AM, 60.9% for PT, and 98.6% for MT. These findings provide insight into industry-specific pollutant characteristics and enable the prediction of risks exceeding emission standards. This approach facilitates the development of optimized water quality management strategies tailored to the discharge profiles of various industries in Gwangju Metropolitan City.

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Performance Evaluation of Domestic and Foreign MBP for UPW Production in Semiconductors

김재현(Jae-Hyun Kim) ; 이형돈(Hyung-Don Lee) ; 방우혁(Woo-Hyuck Bang) ; 여인설(Inseol Yeo) ; 박찬규(Chan-gyu Park)

https://doi.org/10.15681/KSWE.2025.41.3.143

We developed a performance evaluation method to objectively compare and test the performance of mixed bed polishers (MBPs) used in ultrapure industrial production to promote and supply domestically produced equipment for semiconductor-grade ultrapure water (UPW) production, particularly MBPs units. The evaluation criteria included resistance, metal concentration removal efficiency, and metal extraction from resins. We tested both domestic and foreign-produced ion-exchange resins in compacted MBPs using these methods and compared the results. The tests showed that both domestic and foreign MBPs exhibited similar ion removal efficiencies, as indicated by effluent resistance. We found that both domestic and foreign MBPs achieved an average of 17.9 MΩ cm after processing. In contrast, the metal concentration removal performance varied depending on the specific metal elements and the MBP used. Domestic MBPs showed higher performance in removing Li, Cu, Co, Al, Pb, Na, Mn, and V, whereas foreign MBPs had higher performance in removing Cr, Mg, As, Ni, and Fe. In terms of extraction, both MBPs required similar times for the process to conclude, although domestic MBPs showed higher extraction levels of Ni, Mg, and Al. Overall, the comparison indicated that domestically produced MBPs demonstrated performance that was nearly identical to their foreign counterparts.

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Regression-Based Estimation of Pollutant Loads from Direct Runoff and Baseflow

박윤식(Youn Shik Park) ; 허용구(Younggu Her)

https://doi.org/10.15681/KSWE.2025.41.3.151

Because water quality data are more costly to collect and analyze than streamflow data, they are often unavailable for the full duration of streamflow records. As a result, pollutant loads are commonly estimated using statistical models such as the LOAD ESTimator (LOADEST). While LOADEST offers a convenient method for interpolating pollutant loads, recent studies have highlighted the need to evaluate its performance more rigorously. In this study, we assessed the performance of the LOADEST model by grouping water quality data and separating baseflow using a digital filter equation. The measured water quality data were divided into four groups, and each group was used for model calibration and validation. Additionally, baseflow and direct runoff were separated to estimate pollutant loads associated with each flow component. Daily pollutant loads were analyzed for five water quality parameters: BOD, COD, T-N, TOC, and T-P. Overall, the model met acceptable levels of performance across three evaluation criteria for both the calibration and validation phases. This approach enabled the monthly estimation of pollutant loads from baseflow and total streamflow. The baseflow contributions to total pollutant loads were estimated as follows: 17.30% for BOD, 25.82% for COD, 24.69% for T-N, 18.82% for TOC, and 20.51% for T-P. Notably, pollutant loads from baseflow were higher in spring and winter compared to summer and fall.

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Simulating of Harmful Cyanobacteria in the Middle of Nakdong River of a 3-D Hydrodynamic and Water Quality Model With Genetic Algorithm

전유경(Yu Kyeong Jeon) ; 이혜원(Hye Won Lee) ; 최정현(Jung Hyun Choi)

https://doi.org/10.15681/KSWE.2025.41.3.163

Harmful cyanobacteria are the main cause of harmful algal blooms (HABs) and have a negative impact on water quality and public health by inducing bad taste and toxic substances. Thus, it is necessary to develop an algae prediction model, especially for harmful cyanobacteria, with reliable accuracy to establish an effective water quality management strategy for HABs. Since the accuracy of algae prediction models is greatly affected by the parameter settings, it is crucial to estimate appropriate parameters counting on the algal communities of target area. In this study, an environmental fluid dynamics code model was applied to the middle of the Nakdong River. Parameter optimization based on a genetic algorithm was utilized to estimate the optimal parameters reflecting the characteristics of variable algal groups in the target areas. The optimal parameter values for different algal groups differed depending on the algal occurrence pattern and dominant algal species. Model calibration was conducted using the 2022 observed data. It properly reproduced the time-series patterns of water elevation, water temperature, DO, TOC, TN, NH4-N, NO3-N, TP, PO4-P, Chl-a, and harmful cyanobacteria in the study area. The reliability of the model was verified by simulating the number of harmful cyanobacteria at the algae alert system station, Gangjeong-Goryeong. The observed and simulated values ??showed similar levels. The study results are expected to improve the reliability of model prediction by applying parameter optimization, reflecting the characteristics of variable algal groups of the target areas and providing scientific evidence for establishing preemptive algae management.

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Influence of Repetitive Freeze-Thaw Perturbation on Anammox Microbial Communities in Low-Temperature Environment

김수빈(Subin Kim) ; 김상균(Sangkyun Kim) ; 박면호(Myeonho Park) ; 김성아(Seunga Kim) ; 이민주(Minjoo Lee) ; 박준홍(Joonhong Park)

https://doi.org/10.15681/KSWE.2025.41.3.178

In our previous study, freeze-thaw cycle (FTC) pre-treatment in the absence of ammonia and nitrite was found to selectively enrich anammox bacteria adapted to low-temperature environments. However, whether FTC-treated anammox bacteria can be reactivated under low-temperature conditions with substrate addition remains unclear. In this study, survival, activity recovery, and bacterial population dynamics were explored in low-temperature reactivation experiments in anammox microbial communities with repetitive FTC pre-treatment. The results showed that specific anammox activity (SAA) increased with the number of FTC cycles compared to the mesophilic condition (30°C) and no FTC treatment at 15°C. SAA activation was primarily driven by nitrite removal efficiency, whereas ammonia removal efficiency remained low. Additionally, 16S rDNA-based microbiome analysis using next-generation sequencing showed a shift in microbial community structure and population dynamics, with a decreased relative abundance of anammox bacteria and an increased relative abundance of non-anammox microorganisms, especially Pseudomonas, which is known for its ability to maintain high activity under low-temperature conditions. This suggests that the increased Pseudomonas population outcompeted anammox bacteria for nitrite (NO2-), playing a critical role in nitrogen removal efficiency. The study findings suggest that further studies are needed to determine the optimal conditions for reactivating FTC pre-treated anammox consortia under cold conditions.

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Degradation Behavior of Methane-Derived Halocarbons and Mixed Contaminants in Groundwater Using Persulfate-Based Oxidation

한경진(Kyungjin Han) ; 염여훈(Yuhoon Yeum) ; 김재빈(Jaebin Kim) ; 권수열(Sooyoul Kwon)

https://doi.org/10.15681/KSWE.2025.41.3.188

This study evaluated the degradation behavior of methane-derived halocarbons in groundwater using a persulfate-based oxidation process under various conditions. Batch experiments were conducted using dichloromethane (DM), chloroform (CF), or carbon tetrachloride (CT) to determine the behavior of each compound. A binary mixture of trichloroethylene (TCE) and CF was used to simulate realistic scenarios of industrial groundwater contamination. The degradation reactivity was found to be closely linked to the specific molecular structure of each compound. Particularly, the presence of C?H bonds played a critical role in oxidation performance. DM and CF possessing one or more C?H bonds exhibited substantial degradation through direct oxidation by persulfate. The first-order degradation rate constant was ?1.1275 d-1 for DM and ?0.7248 d-1 for CF under non-activated conditions. In contrast, CT lacking C?H bonds showed negligible degradation. In binary systems, the optimal persulfate to activator (Fe²?) ratio was determined to be at least 1:0.01, achieving a notably high degradation rate constant of ?1.8240 d-1 for TCE and ?0.2362 d-1 for CF. These findings clearly highlight that the presence or absence of C-H bonds in the molecular structure of halocarbons can critically influence the oxidation efficiency. These results underscore the importance of developing target-specific treatment strategies based on compounds’ chemical reactivities, which are essential for achieving cost and time-effective groundwater remediation.

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Analysis on the Species-Area Relationship of Benthic Macroinvertebrates Using Probability Distribution Models

공동수(Dongsoo Kong) ; 권용주(Yongju Kwon) ; 김예지(Ye Ji Kim) ; 김명철(Myoung Chul Kim) ; 전영철(Yung-Chul Jun) ; 권순직(Soon Jik Kwon) ; 전용락(Yong Lak Jeon)

https://doi.org/10.15681/KSWE.2025.41.3.199

The species-area relationship in benthic macroinvertebrate assemblages from a clean stream in Korea was examined using 20 mathematical models, including 4 types of power and logarithmic functions and 16 probability distribution models. Probability models included two-parameter models (exponential, inverse exponential, monad, sine), three-parameter left-truncated models (normal, logistic, Gumbel), three-parameter models (generalized exponential, Weibull, inverse Weibull, lognormal, logistic power, gamma, sine power), and four-parameter models (generalized logistic power, beta). Among non-probability model groups, the logarithmic function was more suitable than the power function. It was also more appropriate to apply a shifted model with a threshold value than a basic function. While the power function has often been used in species?area analyses of open ecosystems such as terrestrial or marine environments, the logarithmic function appeared to be more appropriate for analyzing less mobile or sedentary benthic macroinvertebrates in a relatively closed habitat of a stream. The best-fitting models were inverse Weibull and generalized logistic distribution models, both of which showed the highest predictive performances. The power function model significantly overestimated species richness, while exponential, inverse exponential, normal, logistic, Gumbel, and sine distribution models underestimated it. Our results suggest that the maximum number of species estimated by inverse Weibull and generalized logistic distribution models might serve as an index of habitat species capacity. Additionally, the half-saturation area (the median of the probability distribution) and differential entropy might be useful indices for assessing microhabitat heterogeneity.

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Multivariate Analysis of Environmental Factors Differentiating the Ecological Distribution of the Mayfly Genus Ephemera (Ephemeroptera: Ephemeridae)

정찬영(Chanyoung Jeong) ; 공동수(Dongsoo Kong)

https://doi.org/10.15681/KSWE.2025.41.3.214

This study investigated environmental determinants, ecological distribution, and niche separation among three Ephemera species (E. orientalis-sachalinensis, E. strigata, and E. separigata) in South Korea. A total of 23,957 samples were collected from 6,664 sites across the country between 2010 and 2021, with 4,962 sites selected for multivariate analysis. To assess the influence of environmental factors, biota-environment matching (BIOENV), redundancy analysis (RDA), partial least squares regression (PLSR), and ordinary least squares (OLS) regression were employed. Environmental variables included altitude, microhabitat characteristics (water depth, mean current velocity, mean diameter), and water quality indicators (pH, DO, BOD, TSS, TN, TP). BIOENV identified altitude as the most influential variable (Pearson’s ρ = 0.1712). RDA revealed that E. strigata and E. separigata were strongly aligned with high-altitude, fast-flowing, and low-pollution conditions, while E. orientalis?sachalinensis was associated with lowland, slow-flowing, and nutrient-enriched environments characterized by high BOD, TSS, and TP. Both PLSR and OLS models consistently indicated that altitude was a key predictor of species occurrence, reflecting coherent ecological responses across methods. Species-specific elevation patterns confirmed niche separation. E. orientalis-sachalinensis dominated in lowland zones (0 ? 200 m). E. strigata was the most frequent at mid-elevations (500 ? 600 m). E. separigata peaked in highland areas (700 ? 800 m). These findings demonstrate that altitude and environmental gradients can drive clear ecological distribuition among Ephemera species, offering a scientific basis for improved bioassessment and conservation strategies targeting benthic macroinvertebrate communities in lotic ecosystems.

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A Study on T-N Pollutant Load Characteristics in the Kyoungan Stream Watershed: Coupled Application of SWAT and WAPLE4

정연지(Jeong Yeonji) ; 박상준(Bak Sangjoon) ; 이봉국(Bong-Kuk Lee) ; 임경재(Lim Kyoung Jae) ; 한정호(Han Jeongho)

https://doi.org/10.15681/KSWE.2025.41.2.91

This study aimed to quantify total nitrogen (T-N) pollutant loads in the Kyoungan Stream watershed by distinguishing among point sources, direct non-point sources, and base non-point sources. Continuous daily streamflow and water quality datasets were generated using the Soil and Water Assessment Tool (SWAT), which was calibrated against observed streamflow and T-N data. Subsequently, the WAPLE4 program was used to separate total streamflow into direct runoff and baseflow and to estimate pollutant loads. Over the study period (2017?2022), the average annual T-N load in the watershed was approximately 4,032 tons, of which direct non-point sources, base non-point sources, and point sources accounted for 68.4%, 25.4%, and 6.2%, respectively. Subwatershed-scale analyses revealed that subwatersheds with higher proportions of urban areas were associated with larger contributions of direct non-point source loads, whereas subwatersheds with abundant agricultural and forested areas showed a higher proportion of base non-point pollution. These findings highlight the critical influence of urban land use on runoff-driven T-N loads and underscore the need for targeted pollution mitigation strategies based on specific pollutant generation characteristics of each control area. Future research should incorporate evolving land use patterns and other environmental factors affecting pollutant behavior to improve long-term pollutant load predictions and guide sustainable watershed management.

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