• Journal of Korean Society of Environmental Engineers
• /
• v.35 no.11
• /
• pp.835-860
• /
• 2013

Recently, the consumption of nanomaterials has been significantly increased in both industrial and commercial sectors, as a result of steady advancement in the nano-technologies. This ubiquitous use of nanomaterials has brought up the concern that their exposure to environments may cause detrimental effects on human health as well as natural ecosystems, and it is required to characterize their behavior in various environmental media and to evaluate their ecotoxicity. For the sake of accomplishing those assessments, the development of methods to effectively separate them from diverse media and to quantify their properties should be requisitely accompanied. Among a number of separation techniques developed so far, this study focuses on Field-Flow Fractionation (FFF) because of its strengths, such as relatively less disturbance of samples and simple pretreatment, and we review overseas and domestic literatures on the separation of nanomaterials using the FFF technique. In particular, researches with Flow Field-Flow Fractionation (FlFFF) are highlighted due to its most frequent application among FFF techniques. The basic principle of the FlFFF is briefly introduced and the studies conducted so far are classified and scrutinized based on the sort of target nanomaterials for the purpose of furnishing practical data and information for the researchers struggling in this field. The literature review suggests that the operational conditions, such as pretreatment, selection of membrane and carrier solution, and rate (velocity) of each flow, should be optimized in order to effectively separate them from various matrices using the FFF technique. Moreover, it seems to be a prerequisite to couple or hyphenate with several detectors and analyzers for quantification of their properties after their separation using the FFF. However, its application has been restricted regarding the types of target nanomaterials and environmental media. Furthermore, domestic literature data on both separation and characterization of nanomaterials are extremely limited. Taking into account the overwhelmingly increasing consumption of nanomaterials, the efforts for the area seem to be greatly urgent.

• Journal of the Korean earth science society
• /
• v.37 no.7
• /
• pp.420-433
• /
• 2016

The purpose of this study is to improve the calibration matrixes of 2-D and 3-D convective rainfall rates (CRR) using the brightness temperature of the infrared $10.8{\mu}m$ channel (IR), the difference of brightness temperatures between infrared $10.8{\mu}m$ and vapor $6.7{\mu}m$ channels (IR-WV), and the normalized reflectance of the visible channel (VIS) from the COMS satellite and rainfall rate from the weather radar for the period of 75 rainy days from April 22, 2011 to October 22, 2011 in Korea. Especially, the rainfall rate data of the weather radar are used to validate the new 2-D and 3-DCRR calibration matrixes suitable for the Korean peninsula for the period of 24 rainy days in 2011. The 2D and 3D calibration matrixes provide the basic and maximum CRR values ($mm\;h^{-1}$) by multiplying the rain probability matrix, which is calculated by using the number of rainy and no-rainy pixels with associated 2-D (IR, IR-WV) and 3-D (IR, IR-WV, VIS) matrixes, by the mean and maximum rainfall rate matrixes, respectively, which is calculated by dividing the accumulated rainfall rate by the number of rainy pixels and by the product of the maximum rain rate for the calibration period by the number of rain occurrences. Finally, new 2-D and 3-D CRR calibration matrixes are obtained experimentally from the regression analysis of both basic and maximum rainfall rate matrixes. As a result, an area of rainfall rate more than 10 mm/h is magnified in the new ones as well as CRR is shown in lower class ranges in matrixes between IR brightness temperature and IR-WV brightness temperature difference than the existing ones. Accuracy and categorical statistics are computed for the data of CRR events occurred during the given period. The mean error (ME), mean absolute error (MAE), and root mean squire error (RMSE) in new 2-D and 3-D CRR calibrations led to smaller than in the existing ones, where false alarm ratio had decreased, probability of detection had increased a bit, and critical success index scores had improved. To take into account the strong rainfall rate in the weather events such as thunderstorms and typhoon, a moisture correction factor is corrected. This factor is defined as the product of the total precipitable waterby the relative humidity (PW RH), a mean value between surface and 500 hPa level, obtained from a numerical model or the COMS retrieval data. In this study, when the IR cloud top brightness temperature is lower than 210 K and the relative humidity is greater than 40%, the moisture correction factor is empirically scaled from 1.0 to 2.0 basing on PW RH values. Consequently, in applying to this factor in new 2D and 2D CRR calibrations, the ME, MAE, and RMSE are smaller than the new ones.