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저수지 co<sub>2</sub> 배출량 산정을 위한 기계학습 모델의 적용
유지수 ( Jisu Yoo ),정세웅 ( Se-woong Chung ),박형석 ( Hyung-seok Park ) 한국물환경학회(구 한국수질보전학회) 2017 한국물환경학회지 Vol.33 No.3
Lakes and reservoirs have been reported as significant sources of carbon emissions released into the atmosphere of many countries. Although field experiments and theoretical investigations based on the fundamental gas exchange theory have proposed quantitative amounts of Net Atmospheric Flux (NAF) in various climate regions, there is significant uncertainty about the global scale estimation. Mechanistic models can be manipulated for understanding and estimating temporal and spatial variations of NAFs for considering complex hydrodynamic and biogeochemical processes in a reservoir, but such models require extensive and costly datasets and model parameters. However, data driven machine learning (ML) algorithms are likely to be alternative tools to estimate NAFs in responding to independent environmental variables. The objective of this study was to develop random forest (RF) and multi-layer artificial neural network (ANN) models for the estimation of the daily CO<sub>2</sub> NAFs in Daecheong Reservoir located in Geum River in South Korea, and compare the models` performance against the multiple linear regression (MLR) model that was proposed in the previous study (Chung et al” 2016). As a result, the RF and ANN models revealed much enhanced performance in the estimation of high NAF values, while the MLR model significantly underestimated them. A cross-validation with 10-fold random samplings was applied to evaluate the performance of the three models,and it indicated that the ANN model is best, followed by RF and MLR models.
광분해 반응에 의한 비스페놀 A의 에스트로겐 활성 저감에 미치는 방류수 유기물질의 영향
유지수 ( Jisu Yoo ),나주림 ( Joolim Na ),정진호 ( Jinho Jung ) 한국환경생물학회 2016 환경생물 : 환경생물학회지 Vol.34 No.1
본 연구는 자외선 광분해에 의한 비스페놀 A(BPA)의 에스트로겐 활성 저감에 미치는 하수처리장 방류수 유기물질의 영향을 조사하였다. 방류수 유기물질과 표준으로 사용한 스와니강 자연 유기물질은 극성에 따라 소수성, 반친수성, 친수성 분획으로 분리하였다. 특이 자외선 흡수 (SUVA) 분석 결과, 방류수 유기물질은 높는 소수성을 가지고 있는 자연 유기물질과 다르게 소수성이 낮은 미생물 기원 유기물질과 유사한 특성을 나타내었다. 3시간의 자외선 조사는 방류수 및 자연 유기물질의 극성에 따라 SUVA 값을 유의하게 감소시켰다 (p< 0.0001). 유기물질이 없는 조건에서, BPA(5.0×10<sup>-5</sup> M)의 상대 에스트로겐 활성도는 자외선 광분해에 의해 86%에서 63%로 감소하였다. 그러나 유기물질이 있는 조건에서 상대 에스트로겐 활성도는 평균적으로 68%에서 37%로 감소하였으며, 유기물질의 종류 (방류수 또는 자연유기물질) 및 극성 (소수성, 반친수성, 친수성)과 유의한 차이를 나타내지 않았다 (p >0.05). 결과적으로, 유기물질이 있고 없는 조건에서 자외선 광분해에 의해 감소한 BPA의 상대에스트로겐 활성도는 각각 31%와 23%였으며, 이것은 방류수와 자연 유기물질 모두 광분해에 의한 BPA의 에스트로겐 활성 저감을 촉진시킨다는 것을 제시한다. This study investigates the effect of effluent organic matter (EfOM) from sewage wastewater treatment plants on estrogenic activity reduction of bisphenol A (BPA) by UV photolysis. The EfOM and Suwannee River natural organic matter (SR-NOM) as reference were isolated into hydrophobic (HPO), transphilic (TPI) and hydrophilic (HPI) fractions depending on polarity. The specific ultraviolet absorbance (SUVA) analysis indicated that EfOM showed similar properties to microbially derived organic matters with low hydrophobicity, which is different from SR-NOM having high hydrophobicity. UV irradiation upto 3 hr significantly reduced SUVA values of both EfOM and SR-NOM (p< 0.0001), depending on the polarity of organic matters. In the absence of organic matters, the relative estrogenic activity (REA) of BPA(5.0×10<sup>-5</sup> M) was decreased from 86% to 63% by UV photolysis (2 hr). However, the decrease of mean REA was from 68% to 37% in the presence of organic matters, which was significantly independent on the type (EfOM or SR-NOM) and polarity (HPO, TPI or HPI) of organic matters (p >0.05). As a result, the reduced REA by UV photolysis of BPA with and without organic matters was 31% and 23%, respectively, suggesting that both EfOM and SR-NOM accelerated the photolytic reduction of BPA estrogenic activity.
공사장 소음 피해지역의 예측 소음도를 이용하는 소음 모니터링 시스템 활용 방안 연구
유지수(Jisu Yoo),김민종(Min-jong Kim),장서일(Seo Il Chang) 한국소음진동공학회 2024 한국소음진동공학회 논문집 Vol.34 No.2
Complaints related to construction-site noise account for the largest proportion of noise-related complaints and are consistently raised annually, necessitating effective management and countermeasures. However, managing construction-site noise is challenging because of the diverse variables that arise during different stages of construction. Furthermore, there are various limitations in the prediction technique applied in environmental-impact assessments, leading to actual damage in surrounding areas due to the noise from construction sites. Therefore, in this study, we reviewed the existing literature on noise-monitoring systems installed at construction sites as one noise management strategy. We determined that the optimal installation position for a noise-monitoring system was at the boundary line of a construction site based on this review. However, it was concluded that when installing a noise-monitoring system along a construction-site boundary, it is necessary to consider all the cardinal directions (north, south, east, west). Additionally, a method was proposed to predict and manage constructionsite noise by integrating the installed noise-monitoring system with 3D modeling, which was explained in three stages.