지하 매설 수도관은 연약지반의 지반침하, 도심지의 부등침하, 싱크홀 등에 의한 허용한계를 초과하는 지반영구변형에 의해 손상이 발생할 수 있다. 지반변형으로부터 수도관을 보호하기 위한 관이음의 사용으로 수도시설의 안전성 확보가 요구된다. 따라서 매립 수도관의 과도 지반변형에 대한 안전성 평가를 위하여 다중적층형 벨로우즈를 신축관 이음으로 적용한 수도 배관시스템을 제작하 였다. 제작된 배관시스템의 굽힘 및 처짐에 대한 변형 성능 확인을 위하여 4점 굽힘 시험을 수행하였다. 4점 굽힘 시험 결과를 바탕으 로 국내 연약지반 모델을 고려하여 KS D ISO 16134에 따라 지반변형에 대한 안전성을 평가하였다. 안전성 평가 결과 다중적층형 벨로우즈 신축관 이음의 지반변형에 대한 성능은 매우 우수한 것으로 평가되었다.

Accurate estimation of vehicle exhaust emissions at urban intersections is essential to assess environmental impacts and support sustainable traffic management. Traditional emission models often rely on aggregated traffic volumes or measures of average speed that fail to capture the dynamic behaviors of vehicles such as acceleration, deceleration, and idling. This study presents a methodology that leverages video data from smart intersections to estimate vehicle emissions at microscale and in real time. Using a CenterNet-based object detection and tracking framework, vehicle trajectories, speeds, and classifications were extracted with high precision. A structured preprocessing pipeline was applied to correct noise, missing frames, and classification inconsistencies to ensure reliable time-series inputs. Subsequently, a lightweight emission model integrating vehicle-specific coefficients was employed to estimate major pollutants including CO and NOx at a framelevel resolution. The proposed algorithm was validated using real-world video data from a smart intersection in Hwaseong, Korea, and the results indicated significant improvements in accuracy compared to conventional approaches based on average speed. In particular, the model reflected variations in emissions effectively under congested conditions and thus captured the elevated impact of frequent stopand- go patterns. Beyond technical performance, these results demonstrate that traffic video data, which have traditionally been limited to flow monitoring and safety analysis, can be extended to practical environmental evaluation. The proposed algorithm offers a scalable and cost-effective tool for urban air quality management, which enables policymakers and practitioners to link traffic operations with emission outcomes in a quantifiable manner.

This study developed a QSAR regression model using the XGBoost machine learning algorithm to predict the acute aquatic toxicity of highly hazardous PCBs. EC50 values for Daphnia magna were obtained from QSAR Toolbox 4.7. Input features consisted of approximately 3,000 molecular descriptors and fingerprints generated from official structure data using RDKit and the Morgan algorithm, excluding mixtures. The dataset was split into training and test sets (7 : 3) based on 500,000 randomized seeds, and the most balanced combination was selected using Kolmogorov-Smirnov and Wilcoxon rank-sum tests. Z-score standardization was applied based on the training set, and the XGBoost model was trained using 5-fold cross-validation with grid search optimization. The final model showed excellent predictive performance (R2 =0.97, RMSE= 0.19). A simplified model using only the top 10 predictive molecular features retained approximately 95% of the original accuracy while improving interpretability and efficiency. The model was applied to 38 PCB compounds lacking EC50 values, and the predicted values showed a statistically similar distribution to the measured group, with only minor differences in a few structural fingerprints. These results demonstrate the applicability of XGBoost-based models for reliable toxicity prediction and offer a promising alternative approach for assessing the environmental risk of untested PCBs.

This study aimed to develop a model for accurately predicting the acute aquatic toxicity (48h- EC50) of chlorine disinfection by-products (DBPs). DBPs have caused environmental risks, but experimental toxicity data are difficult to obtain due to time, cost, and ethical constraints. Therefore, a deep learning model was developed using actual concentration-based data. Toxicity data for 139 aliphatic chlorinated compounds were from the OECD QSAR Toolbox and from aquatic toxicity test results provided by the japan ministry of the environment. Various concentration criteria, including nominal and measured concentrations, were encoded as additional inputs, and EC50 values were augmented via log transformation and structural string modifications to overcome small data limitations. The directed message passing neural network (D-MPNN) model, which considers bond directionality, was applied to reflect structural complexity accurately. Also, this model effectively reflected subtle structural differences and showed stable performance even with limited data. Comparisons between models with and without concentration criteria revealed that the model considering all concentration criteria had superior predictive accuracy. This result shows that concentration criteria are a critical factor in toxicity prediction. This study suggests a baseline model that works reliably even with small datasets reflecting realistic concentration criteria, showing its potential use for replacing some experiments and for screening toxic substances.

This study examines the seismic vulnerability of non-structural components in high-rise buildings by proposing a normalized floor response spectrum (FRS) suitable for practical application. A Bayesian-mode-based method (BMBM) is used to develop the FRS, incorporating both modal amplification effects and the probabilistic variability observed across different building heights and story levels. The resulting spectrum is methodically compared with existing code-based and empirical methods to assess its consistency, conservatism, and relevance to engineering practices. The findings demonstrate that the proposed FRS provides a realistic yet reliable upper-bound estimate of floor accelerations, particularly in the upper stories where modal interactions are significant. This research offers a robust and practical framework for enhancing the seismic design of nonstructural components in vertical structures.

본 연구에서는 고분자 점도 조절제를 첨가하여 졸-겔법 기반 알루미나 나노여과막을 단일 공정으로 제조하고, 코 팅층의 구조 및 성능을 제어하는 방법을 제시하였다. Hydroxypropyl cellulose (HPC, Mw ~80000) 고분자를 알루미나 졸에 첨가하여 점도를 10 mPa·s에서 최대 4200 mPa·s까지 조절하였으며, 이를 통해 알루미나 중공사 지지체 표면에 균일하고 결 함이 없는 선택층을 형성하였다. HPC 함량이 증가할수록 코팅층 두께가 증가하였으나, 기공 크기 증가에 따라 분리 성능이 저하되었다. 2:1 (졸:HPC 고분자 용액) 혼합비에서 제조된 나노여과막은 두께 3.20 μm의 얇은 선택층을 형성하여 높은 수투 과도(12.9 LMH/bar)와 우수한 제거 성능(PPG 1050 Da 제거율 60%, PEG 1500 Da 제거율 90%, MgCl2 제거율 80%)을 나타 냈다. 반면, 1:2 혼합비에서는 선택층 두께가 10.2 μm로 증가하였으나, 기공 크기가 증가하여 3400 Da MWCO와 64% 염 제 거율을 보였다. HPC 고분자를 활용한 점도 제어는 졸-겔 코팅층의 두께, 기공 구조 및 분리 성능을 효과적으로 조절할 수 있 음을 입증하였다.

This study was conducted to analyze odor regulation policies of major countries and explore development directions for Korea’s odor management system through international comparison. Korea has achieved significant progress in odor management over the past 20 years since the enactment of the Odor Prevention Act in 2004, including the establishment of real-time monitoring systems, integrated complaint management systems, and scientific management infrastructure in major odor management areas such as Sihwa-Banwol Industrial Complex and metropolitan landfills in Incheon and Daejeon. To identify potential development directions, a literature review and comparative analysis were conducted on four regions: the United States, the European Union, Japan, and Singapore. The analysis revealed that each region has developed unique approaches: Japan’s Odor Judge system (involving 3,352 active professionals) for measurement standardization; the United States’s citizen science-based monitoring systems, such as the Odor Explore project that utilizes community participation; the EU’s preventive management policies through the application of Best Available Techniques (BAT) and land use planning integration; and Singapore’s systematic management approach through its myENV app and urban planning integration. Based on Korea’s existing achievements and international experiences, this study identified eight development areas, including measurement system standardization, management scope expansion, integrated management system enhancement, real-time monitoring implementation, technology development investment, complaint resolution mechanism improvement, preventive management system enhancement, and information transparency enhancement. This study proposes development directions that build upon Korea’s current infrastructure and policy achievements, considering the country’s unique socio-economic conditions and environmental characteristics. These directions are expected to contribute to the continuous advancement of Korea’s odor management system while leveraging existing strengths and addressing future challenges.

This study analyzed policy measures to comprehensively achieve two goals: carbon neutrality in buildings and optimization of indoor air quality. While buildings account for approximately 40% of total energy consumption and greenhouse gas emissions, and present-day individuals spend 90% of their daily lives indoors, both goals are critically important. However, these objectives often conflict with each other, and current policies have limitations in effectively addressing this complex relationship. Analysis of related policies, including the Green Building Creation Support Act and the Indoor Air Quality Management Act, revealed significant drawbacks such as the lack of an integrated approach due to policy fragmentation, insufficient consideration of lifecycle carbon emissions, imbalance in economic incentive structures, and rigidity in technical standards. To overcome these challenges, this study proposes innovative improvement measures, including the following: establishing an integrated policy framework, introducing a multi-layered air quality management system, expanding performance-based design that simultaneously considers energy efficiency and indoor air quality, developing region-specific policies, implementing AI-based self-assessment systems, mandating green space ratios, controlling high-radon concentration areas, and expanding government incentives.

Wood ear mushrooms (Auricularia heimuer) are commercially used in various fields in South Korea. Therefore, it is necessary to take appropriate measures, including monitoring and prevention of microbial growth in cultivation houses, as microorganisms can reduce the wood ear mushroom’s marketability and cause food poisoning among consumers. Therefore, this study was conducted to evaluate the direct impact of airborne fungi isolated and identified from the indoor air of domestic wood ear mushroom cultivation houses on the mycelia growth of wood ear mushroom strains. For the evaluation, 11 airborne fungal species were tested with three strains of A. heimuer on PDA using the cocultivation method. Among them, Alternaria alternata, Cladosporium anthropophilum, Cochliobolus kusanoi, Lecanicillium sp., Periconia byssoides, and Periconia pseudobyssoides suppressed the mycelial growth of all three A. heimuer strains. There was no significant difference in the reaction against the 11 tested airborne fungal species among the three A. heimuer strains. The results of this study show that proper management of airborne fungi is necessary in the indoor environment of wood ear mushroom cultivation houses.

In this study, we investigated the characteristics of meteorological factors influencing odor emissions based on odor complaint records and meteorological observation data collected from 2014 to 2021 in Seoul, a megacity with a high population density and no regulated facilities or management zones apart from public environmental infrastructure and neighborhood living facilities. A total of 134,976 odor complaints were recorded over eight years (2,922 days), with a daily peak of 946 cases. From 2018 onward, daily complaints consistently exceeded 200 cases, reaching their highest level in 2019. Complaints were regularly and intensively concentrated during specific periods of the year. Among meteorological factors, dry tide time and dominant wind direction exhibited bimodal distributions within the observation range, while the other 11 meteorological factors were concentrated at a single value. The average meteorological conditions during the period with the highest number of odor complaints and observation days were: temperature 24.2oC, surface temperature 26.7oC, local pressure 1,000.4 hPa, sea-level pressure 1,010.8 hPa, vapor pressure 4.3 hPa, solar irradiance 10.5 MJ/m2, precipitation 0.6 mm, relative humidity 61.5%, wind speed 2.2 m/ s, and dominant wind direction 57.9o. These factors corresponded with the periods of highest odor complaints and observation days; however, dew point temperatures (15.3oC and 19.1oC), dry tide times (14.7 hours and 9.7 hours), and sunshine times (15.1 hours and 9.0 hours) did not coincide with those periods. The meteorological factors with the highest odor complaint emission rates (SROCE, cases/day) across 13 sections, ranked in descending order, were: dry tide time (73.5), surface temperature (67.7), solar irradiance (65.1), sea-level pressure (64.3), temperature (62.7), local pressure (62.7), dew point temperature (60.3), vapor pressure (58.7), sunshine times (54.1), relative humidity (53.1), wind speed (51.2), dominant wind direction (48.7), and precipitation (46.3). The intensity of odor complaint emission (IOCE, cases/day), calculated across the entire meteorological observation range, was highest in the following order: solar irradiance (63.8), dry tide time (60.5), sunshine times (60.3), local pressure (57.2), surface temperature (57.1), sea-level pressure (57.0), temperature (56.4), vapor pressure (55.8), dew point temperature (55.7), relative humidity (49.4), dominant wind direction (49.2), wind speed (49.0), and precipitation (46.5). The IOCE for solar irradiance was 37.2% higher than that for precipitation, which had the lowest IOCE. Additionally, the average IOCE of sunlightrelated meteorological factors such as dry tide time, sunshine times, and solar irradiance was 61.5 cases/day, which is 29.5% higher than that of moisture-related factors, including precipitation and relative humidity (47.5 cases/day). These results suggest that sunlight-related factors significantly contribute to odor complaints. This study evaluated the characteristics of odor emissions associated with complaints within the meteorological observation range, identified meteorological factors corresponding to the highest observed odor emissions, and assessed the contribution of these factors to odor emissions based on the IOCE metric. Based on these results, we anticipate being able to predict odor emission levels using weather forecast data.

This study analyzed the structural performance of a microalgae-based lightweight ecological integration system for large-span structures to achieve carbon neutrality. To address the load problems of existing soil-based ecological systems, a lightweight system utilizing microalgae bioreactors was proposed, and structural performance was evaluated for four types of large-span structures: truss, arch, dome, and cable structures. Structural analysis results through finite element analysis showed that the proposed system achieved a 70% load reduction effect compared to existing systems, with structural performance improvements including 35-40% reduction in maximum deflection, 30-35% reduction in maximum stress, and 25-30% increase in natural frequency. Environmental performance analysis confirmed CO₂absorption capacity of 12-18 kg per m² annually and PM2.5 reduction effects of 15-25%. Economic analysis results indicated that benefits of 3.95-6.7 million KRW per year are generated for a 1,000 m²reference area, creating cumulative benefits of 179.75-227.5 million KRW over 25 years. Verification through the German BIQ House case confirmed CO₂reduction performance of 6 tons per year for 200 m², demonstrating the practical applicability of the system. This study presented the potential of an innovative ecological integration system that can ensure structural safety of large-span structures while simultaneously contributing to carbon neutrality.

연구는 MZ세대 취업준비생의 디지털 리터러시 능력과 디지털 참여 활동이 잡크래프팅 역량에 영향을 미치는 요인이 무엇인지를 알아보는데 목적이 있다. 특히, 잡크래프팅의 주요 하위 역량인 과업 크래프팅, 인지 크래프팅, 관계 크래프 팅과의 연관성에 초점을 두었다. 주요 연구문제는 첫째, 취업준비생의 디지털 리터러시 능력과 디지털 참여 활동에서 과 업 크래프팅 역량에 영향을 미치는 요인은 무엇인가? 둘째, 취업준비생의 디지털 리터러시 능력과 디지털 참여 활동에서 인지 크래프팅 역량에 영향을 미치는 요인은 무엇인가? 셋째, 취업준비생의 디지털 리터러시 능력과 디지털 참여활동에 서 관계 크래프팅 역량에 영향을 미치는 요인은 무엇인가? 등 세 가지다. 연구의 주요 변수인 디지털 리터러시 능력, 디 지털 참여 활동, 잡크래프팅 역량과 관련된 선행 연구를 탐색하였고, MZ세대 취업준비생 364명의 설문 응답을 통계 분 석하였다. 연구 결과에 따르면, 디지털 리터러시 능력의 하위 요인인 디지털 정보 역량, 디지털 의사소통 역량이 높을수 록 과업 크래프팅 역량과 관계 크래프팅 역량이 높은 것으로 나타났고, 디지털 활용 역량, 디지털 정보 역량, 디지털 의 사소통 역량이 높을수록 인지 크래프팅 역량이 높은 것으로 나타났다. 또한, 디지털 참여 활동의 하위 요인인 정보 취득, 정보 선택, 정보 전달이 높을수록 과업 크래프팅, 인지 크래프팅, 관계 크래프팅이 높은 것으로 나타났다. 이러한 연구 결과를 바탕으로 MZ세대 취업준비생의 특성을 파악하고, 향후 지속적인 디지털 리터러시 능력 향상과 디지털 참여 활동 확대를 통해 취업준비생들의 잡크래프팅 역량을 높이는데 긍정적인 영향을 미칠 수 있는 평생교육 및 사교육 프로그램 을 개발하고 활용할 수 있기를 기대한다.