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이병우(Byeongwoo Lee),이병천(Byoungcheun Lee),김필제(Pilje Kim),윤효정(Hyojung Yoon) 한국환경보건학회 2020 한국환경보건학회지 Vol.46 No.1
Objectives: This study intends to evaluate the ecological risk of lead (Pb), arsenic (As), and their compounds according to the 2010 action plan on inventory and management for national priority chemicals and provide calculations of risks to the environment. By doing so, we aim to inform risk management measures for the target chemicals. Methods: We conducted species sensitivity distribution (SSD) analysis using the collected ecotoxicity data and obtained predicted no effect concentrations (PNECs) for the in-water environment using a hazardous concentration of 5% (HC5) protective of most species (95%) in the environment. Based on the calculated PNECs for aquatic organisms, PNEC values for soil and sediment were calculated using the partition coefficient. We also calculated predicted exposure concentration (PEC) from nation-wide environmental monitoring data and then the hazard quotient (HQ) was calculated using PNEC for environmental media. Results: Ecological toxicity data was categorized into five groups and five species for Pb and four groups and four species for As. Based on the HC5 values from SSD analysis, the PNEC value for aquatic organisms was calculated as 0.40 μg/L for Pb and 0.13 μg/L for As. PNEC values for soil and sediment calculated using a partition coefficient were 77.36 and 350.50 mg/kg for Pb and 24.20 and 112.75 mg/kg for As. The analysis of national environmental monitoring data showed that PEC values in water were 0.284 μg/L for Pb and 0.024 μg/L for As, while those in soil and sediment were respectively 45.9 and 44 mg/kg for Pb, and 11.40 and 19.80 mg/kg for As. Conclusions: HQs of Pb and As were 0.70 and 0.18 in water, while those in soil and sediment were 0.59 and 0.13 for Pb and 0.47 and 0.18 for As. With HQs <1 of lead and arsenic in the environment, their ecological risk levels are found to be low.
Comparison of Real Time Nanoparticle Monitoring Instruments in the Workplaces
Ham, Seunghon,Lee, Naroo,Eom, Igchun,Lee, Byoungcheun,Tsai, Perng-Jy,Lee, Kiyoung,Yoon, Chungsik Occupational Safety and Health Research Institute 2016 Safety and health at work Vol.7 No.4
Background: Relationships among portable scanning mobility particle sizer (P-SMPS), condensation particle counter (CPC), and surface area monitor (SAM), which are different metric measurement devices, were investigated, and two widely used research grade (RG)-SMPSs were compared to harmonize the measurement protocols. Methods: Pearson correlation analysis was performed to compare the relation between P-SMPS, CPC, and SAM and two common RG-SMPS. Results: For laboratory and engineered nanoparticle (ENP) workplaces, correlation among devices showed good relationships. Correlation among devices was fair in unintended nanoparticle (UNP)-emitting workplaces. This is partly explained by the fact that shape of particles was not spherical, although calibration of sampling instruments was performed using spherical particles and the concentration was very high at the UNP workplaces to allow them to aggregate more easily. Chain-like particles were found by scanning electron microscope in UNP workplaces. The CPC or SAM could be used as an alternative instrument instead of SMPS at the ENP-handling workplaces. At the UNP workplaces, where concentration is high, real-time instruments should be used with caution. There are significant differences between the two SMPSs tested. TSI SMPS showed about 20% higher concentration than the Grimm SMPS in all workplaces. Conclusions: For nanoparticle measurement, CPC and SAM might be useful to find source of emission at laboratory and ENP workplaces instead of P-SMPS in the first stage. An SMPS is required to measure with high accuracy. Caution is necessary when comparing data from different nanoparticle measurement devices and RG-SMPSs.
Ham, Seunghon,Kim, Sunju,Lee, Naroo,Kim, Pilje,Eom, Igchun,Lee, Byoungcheun,Tsai, Perng-Jy,Lee, Kiyoung,Yoon, Chungsik Informa UK (TaylorFrancis) 2017 Journal of applied statistics Vol.44 No.4
<P>Real-time monitoring is necessary for nanoparticle exposure assessment to characterize the exposure profile, but the data produced are autocorrelated. This study was conducted to compare three statistical methods used to analyze data, which constitute autocorrelated time series, and to investigate the effect of averaging time on the reduction of the autocorrelation using field data. First-order autoregressive (AR(1)) and autoregressive-integrated moving average (ARIMA) models are alternative methods that remove autocorrelation. The classical regression method was compared with AR(1) and ARIMA. Three data sets were used. Scanning mobility particle sizer data were used. We compared the results of regression, AR(1), and ARIMA with averaging times of 1, 5, and 10min. AR(1) and ARIMA models had similar capacities to adjust autocorrelation of real-time data. Because of the non-stationary of real-time monitoring data, the ARIMA was more appropriate. When using the AR(1), transformation into stationary data was necessary. There was no difference with a longer averaging time. This study suggests that the ARIMA model could be used to process real-time monitoring data especially for non-stationary data, and averaging time setting is flexible depending on the data interval required to capture the effects of processes for occupational and environmental nano measurements.</P>
Han, Yosep,Hwang, Gukhwa,Kim, Donghyun,Bradford, Scott A.,Lee, Byoungcheun,Eom, Igchun,Kim, Pil Je,Choi, Siyoung Q.,Kim, Hyunjung Elsevier 2016 Water research Vol.90 No.-
<P><B>Abstract</B></P> <P>The transport, retention, and long-term release of zinc oxide nanoparticle aggregates (denoted below as ZnO-NPs) were investigated in saturated, bare and biofilm (<I>Pseudomonas putida</I>) coated sand packed columns. Almost complete retention of ZnO-NPs occurred in bare and biofilm coated sand when the influent solution pH was 9 and the ionic strength (IS) was 0.1 or 10 mM NaCl, and the retention profiles were always hyper-exponential. Increasing the solution IS and biofilm coating produced enhanced retention of ZnO-NPs near the column inlet. The enhanced NPs retention at high IS was attributed to more favorable NP-silica and NP-NP interactions; this was consistent with the interaction energy calculations. Meanwhile, the greater NPs retention in the presence of biofilm was attributed to larger roughness heights which alter the mass transfer rate, the interaction energy profile, and lever arms associated with the torque balance; e.g., scanning electron and atomic force microscopy was used to determine roughness heights of 33.4 nm and 97.8 nm for bare sand and biofilm-coated sand, respectively. Interactions between NPs and extracellular polymeric substances may have also contributed to enhanced NP retention in biofilm-coated sand at low IS. The long-term release of retained ZnO-NPs was subsequently investigated by continuously injecting NP-free solution at pH 6, 9, or 10 and keeping the IS constant at 10 mM. The amount and rate of retained ZnO-NP removal was strongly dependent on the solution pH. Specifically, almost complete removal of retained ZnO-NPs was observed after 627 pore volumes when the solution pH was 6, whereas much less Zn was recovered when the eluting solution pH was buffered to pH = 9 and especially 10. This long-term removal was attributed to pH-dependent dissolution of retained ZnO-NPs because: (i) the solubility of ZnO-NPs increases with decreasing pH; and (ii) ZnO-NPs were not detected in the effluent. The presence of biofilm also decreased the initial rate and amount of dissolution and the subsequent transport of Zn<SUP>2+</SUP> due to the strong Zn<SUP>2+</SUP> re-adsorption to the biofilm. Our study indicates that dissolution will eventually lead to the complete removal of retained ZnO-NPs and the transport of toxic Zn<SUP>2+</SUP> ions in groundwater environments with pH ranges of 5–9.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Mobility of ZnO-NPs decreases at high ionic strength and in biofilm-coated sand. </LI> <LI> NPs–NPs interaction leads to the hyper exponential shape of retention profiles. </LI> <LI> Lowering pH highly increases the release rate and amount of retained ZnO-NPs. </LI> <LI> The release of ZnO-NPs at low pH mainly occurs by the dissolution of NPs. </LI> <LI> The presence of biofilm retards the release of retained ZnO-NPs. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>