• Food Science and Preservation
• /
• v.22 no.6
• /
• pp.915-919
• /
• 2015

This study was performed in order to provide basic data for predicting the usefulness of Jicama (Pachyrhizus erosus) as a food raw material. The changes in the physicochemical properties of freeze-dried and hot air-dried Jicama were investigated and analyzed. The moisture content of raw Jicama was 81.84%. The crude protein, crude fat, crude ash and carbohydrate content of hot air-dried Jicama powder were 2.85, 0.79, 7.93 and 88.44%, while those of freeze-dried Jicama powder were 3.93, 0.83, 7.92 and 87.32%, respectively on dry basis. Regarding the color values, the lightness of freeze-dried Jicama (92.86) was higher than that of the hot air-dried Jicama (88.01), whereas the redness (-0.67) and yellowness (3.21) of freeze-dried Jicama were lower than those of the hot air-dried Jicama (0.43) and (11.96), respectively. The brown index was lower in the freeze-dried Jicama (0.029) than in hot air-dried Jicama (0.107). The total sugar content showed no significant differences between freeze (46.49 mg/g) and hot air-dried Jicama (45.11 mg/g). Finally, the amylose content was higher in freeze-dried Jicama (5.66%) than in hot air-dried Jicama (6.63%).

• Journal of Korea Water Resources Association
• /
• v.54 no.9
• /
• pp.693-704
• /
• 2021

The purpose of this study is to evaluate the relationship between heat wave and river water quality. The daily maximum air temperature (Tmax) of 91 meteorological stations of the Korea Meteorological Administration and 13 river water quality factors (DO, BOD, COD, TOC, TN, DTN, NH4-N, NO2-N, NO3-N, TP, DTP, PO4-P, Chl-a) of Ministry of Environment were analyzed. The correlation analysis was performed on Tmax and water quality factors, and the determination coefficients (R²) of DO, Chl-a, and TN with Tmax showed high values of 0.782, 0.609, and 0.691 respectively. To analyze the spatial impact between heat waves and water quality factors, the heat wave intensity (HWI) and heat wave duration (HWD) were calculated using the Tmax. The hotspot and spatial statistical analyses were applied for spatial impact evaluation. As a result of hotspot analysis, the heat wave index (HWD, HWI) showed high spatial pattern in the downstream of Nakdong River basin, and Chl-a and TN showed the same pattern. In case of spatial statistical analysis for water quality due to heat wave, the most obvious spatial variability was DO.

• Asian Journal of Atmospheric Environment
• /
• v.9 no.1
• /
• pp.91-99
• /
• 2015

The Multi-wavelength Raman LIDAR (MRL) system was developed to enable a better understanding of the complex properties of aerosols in the atmosphere. In this study, the microphysical, optical, and radiative properties of mixed aerosols were retrieved using the discrete aerosol observation products from the MRL. The dust mixing ratio, which is the proportion of dust particles to the total mixed, was derived using the particle depolarization ratio. It was employed in the retrieval of backscattering and extinction coefficient profiles for dust and non-dust particles. The vertical profiles of aerosol optical properties were then used as input parameters in the inversion algorithm for the retrieval of microphysical parameters including the effective radius, refractive index, and the single scattering albedo (SSA). Those products were successfully applied to an analysis of radiative flux using a radiative transfer model. The relationship between the MRL derived extinction and aerosol radiative forcing (ARF) in short-wavelength was assessed over Gwangju, Korea. The results clearly demonstrate that the MRL-derived extinction profiles are a good surrogate for use in the estimation of optical, microphysical, and radiative properties of aerosols. It is considered that the analytical results shown in this study can be used to provide a better understanding of air quality and the variation of local radiative effects due to aerosols.

• Journal of Korean Society for Atmospheric Environment
• /
• v.20 no.4
• /
• pp.437-450
• /
• 2004

Extensive forest fire activities occurred across the border in Russia, particularly east of Lake Baikal between the Amur and Lena rivers in May 2003. These forest fires released large amounts of particulates and gases into the atmosphere, resulting in adverse effects on regional air quality and the global radiation budget. Smoke pollution from the Russian fires near Lake Baikal was transported to Korea through Mongolia and eastern China. On 20 May 2003, a number of large fires were burning in eastern Russian, producing a thick, widespread pall of smoke over much of Northeast Asia. In this study, separation technique was used for aerosol retrieval application with imagery from MODIS aboard TERRA satellites. MODIS true-color image shows the location of fires and the grayish color of the smoke plumes over Northeast Asia. Aerosol optical thckness (AOT) retrieved from the MODIS data were compared with fire hot spots, ground-based radiation data and TOMS -based aerosol index data. Large AOT, 2.0-5.0 was observed on 20 May 2003 over Korea due to the influence of the long range transport of smoke aerosol plume from the Russian fires, while surface observed fine mode of aerosol size distribution increased.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.324-324
• /
• 2022

정확한 오염물질 예측은 기상학, 자연재해, 기후변화 연구 등 현장에서 필수적인 과제 중 하나이다. 주변 관측소에서 얻은 데이터를 사용하는 경우 모델 학습을 위한 불필요한 데이터로 인해 예측 결과에 왜곡 문제가 있을 수 있습니다. 따라서, 우리는 종합적인 대기질 지수 행동에 영향을 미치는 요인을 제공하는 최적의 데이터 소스를 찾기 위해 네트워크 방식을 사용했습니다. 본 연구에서는 2015년부터 2020년까지 우리나라의 6개 오염물질과 종합적인 대기질 지수 예측에 대한 네트워크 기법을 적용한 LSTM 및 DNN 모델을 적용하였다. 본 연구는 미세먼지(PM10), 초미세먼지(PM2.5), 오존(O3), 이산화황(SO2), 이산화질소(NO2), 일산화탄소(CO) 등 6가지 오염물질을 기반으로 종합적인 대기질 지수를 예측하는 2단계로 구성되어 있다. LSTM을 이용하여, 개별적으로 예측된 6가지 오염물질을 이용하여 DNN 모형을 이용하여 종합적인 대기질 지수를 예측한다. 6가지 오염물질에 대한 각 모델의 예측능력과 종합적인 대기질 지수 예측은 관측된 대기질 데이터와 비교하여 평가하였다. 본 연구는 심층신경망 모델과 네트워크 방식을 결합한 것이 높은 예측력을 제공함을 보여주었으며, 종합적인 대기질 지수 예측을 위한 최적의 모델로 선정되었다. 재난관리의 필요성이 증가함에 따라 네트워크 방식의 딥러닝 모델은 자연재해 피해를 줄이고 재난관리를 개선할 수 있는 충분한 잠재력을 가질 것으로 기대된다.

• Journal of Korean Society for Atmospheric Environment
• /
• v.29 no.2
• /
• pp.186-198
• /
• 2013

The present work is an attempt to improve the performance of a regional air quality model by means of liking it with a global chemistry transport model. The global chemical transport model of GEOS-Chem is used to provide BC (Boundary Condition)s which reflect temporal and spatial variations at boundaries of regional chemical transport model of CMAQ over East Asia. First, GEOS-Chem outputs are evaluated by comparing predicted concentrations with observed monthly data of gas phase species and secondary inorganic aerosols from EANET (Acid Deposition Monitoring Network in East Asia) sites. The results show that predicted PM10 concentrations are in good agreement with the observations. This implies that GEOS-Chem outputs could be used to provide BCs to CMAQ. Simulated daily and monthly mean PM10 concentrations of CMAQ with the linkage of GEOS-Chem's BCs and constant BCs are then evaluated by comparing predicted concentrations with observations at API (Air Pollution Index) sites in China as well as EANET sites in Korea. CMAQ with the GEOS-Chem outputs improves model simulation in depicting observed PM10 concentrations comparing with those with constant BCs. It is also found that influence of aerosol species are largely dependent on the BCs over East Asia and Korea. Mean biases between simulated versus observed daily and monthly mean concentrations of PM10 with the GEOS-chem were improved by 1~8 ${\mu}g/m^3$ in China region, 3.26 ${\mu}g/m^3$ in Korea.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.3
• /
• pp.1879-1887
• /
• 2013

To investigate the level of genotoxicity over Bangkok atmosphere, $PM_{10}$ samples were collected at the Klongchan Housing Authority (KHA), Nonsree High School (NHS), Watsing High School (WHS), Electricity Generating Authority of Thailand (EGAT), Chokchai 4 Police Station (CPS), Dindaeng Housing Authority (DHA) and Badindecha High School (BHS). For all monitoring stations, each sample covered a period of 24 hours taken at a normal weekday every month from January-December 2006 forming a database of 84 individual air samples (i.e. $12{\times}7=84$). Atmospheric concentrations of low molecular weight PAHs (i.e. phenanthrene, anthracene, pyrene and fluoranthene) were measured in $PM_{10}$ at seven observatory sites operated by the pollution control department of Thailand (PCD). The mutagenicity of extracts of the samples was compared in Salmonella according to standard Ames test method. The dependence of the effects on sampling time and on sampling location was investigated with the aid of a calculation of mutagenic index (MI). This MI was used to estimate the increase in mutagenicity above background levels (i.e. negative control) at the seven monitoring sites in urban area of Bangkok due to anthropogenic emissions within that area. Applications of the AMES method showed that the average MI of $PM_{10}$ collected at all sampling sites were $1.37{\pm}0.10$ (TA98; +S9), $1.24{\pm}0.08$ (TA98; -S9), $1.45{\pm}0.10$ (TA100; +S9) and $1.30{\pm}0.09$ (TA100; -S9) with relatively less variations. Analytical results reconfirm that the particulate PAH concentrations measured at PCD air quality monitoring stations are moderately low in comparison with previous results observed in other countries. In addition, the concept of incremental lifetime particulate matter exposure (ILPE) was employed to investigate the potential risks of exposure to particulate PAHs in Bangkok atmosphere.

• Korean Journal of Soil Science and Fertilizer
• /
• v.48 no.5
• /
• pp.499-504
• /
• 2015

Decision making by farmers regarding irrigation is critical for crop production. Therefore, the precision irrigation technique is very important to improve crop quality and yield. Recently, much attention has been given to remote sensing of crop canopy temperature as a crop water-stress indicator, because it is a scientifically based and easily applicable method even at field scales. This study monitored a series of time-variant canopy temperature of cucumber under three different irrigation treatments: under-irrigation (control), optimal-irrigation, and over-irrigation. The difference between canopy temperature ($T_c$) and air temperature ($T_a$), $T_c-T_a$, was calculated as an indicator of cucumber water stress. Vapor pressure deficit (VPD) was evaluated to define water stress on the basis of the temperature difference between leaf and air. The values of $T_c-T_a$ was negatively related to VPD; further, cucumber growth in the under- and over-irrigated fields showed water stress, in contrast to that grown in the optimally irrigated field. Thus, thermal infrared measurements could be useful for evaluating crop water status and play an important role in irrigation scheduling of agricultural crops.

• Journal of Bio-Environment Control
• /
• v.24 no.4
• /
• pp.301-307
• /
• 2015

High quality transplants are critical for success in crop production. Increasing numbers of growers purchase their transplants from specialized transplant producers instead of growing their own transplants. A drawback of purchasing transplants is the risk of deterioration to transplants during transportation from transplant producers to the growers. This study evaluates the influence of temperature on the quality of grafted tomatoes transplants (Solanum lycopersicum cv. Super Doterang), in order to propose optimum temperature condition for the transportation of grafted tomato transplants. Grafted tomato transplants with visible flower trusses were exposed to different air temperature ($10^{\circ}C$, $25^{\circ}C$, or $40^{\circ}C$) for 2, 4, or 6 hours. After treatment, the NDVI (Normalized Difference Vegetation Index) values of tomato transplants treated at 25 and $40^{\circ}C$ were lower than that at $10^{\circ}C$. The root fresh weight was lowest at $40^{\circ}C$. After transplanting, the transplants that were exposed to the air temperature of $40^{\circ}C$ exhibited chlorosis and blight on lower leaves. The degree of damage on leaves was severer as the high temperature exposure time was longer. The temperature conditions during the transportation also influenced the growth, flowering and fruit set of tomatoes after transplanting. The fruit number and weight of first truss was lowest at $40^{\circ}C$ for 6 hours. Accordingly, it is recommended that the temperature during the transportation should be controlled and kept at the range from 10 to $25^{\circ}C$ even though the period is short (within as six hours) in order to maintain the quality of transplants.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.967-977
• /
• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.