• Atmosphere
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• v.22 no.2
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• pp.137-147
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• 2012

The technique of Brightness Temperature Difference (BTD) between 11 and $12{\mu}m$ separates yellow sand dust from clouds according to the difference in absorptive characteristics between the channels. However, this method causes consistent false alarms in many cases, especially over the desert. In order to reduce these false alarms, we should eliminate the background noise originated from surface. We adopted the Background BTD (BBTD), which stands for surface characteristics on clear sky condition without any dust or cloud. We took an average of brightness temperatures of 11 and $12{\mu}m$ channels during the previous 15 days from a target date and then calculated BTD of averaged ones to obtain decontaminated pixels from dust. After defining the BBTD, we subtracted this index from BTD for the Yellow Sand Index (YSI). In the previous study, this method was already verified using the geostationary satellite, MTSAT. In this study, we applied this to the polar orbiting satellite, MODIS, to detect yellow sand dust over Northeast Asia. Products of yellow sand dust from OMI and MTSAT were used to verify MODIS YSI. The coefficient of determination between MODIS YSI and MTSAT YSI was 0.61, and MODIS YSI and OMI AI was also 0.61. As a result of comparing two products, significantly enhanced signals of dust aerosols were detected by removing the false alarms over the desert. Furthermore, the discontinuity between land and ocean on BTD was removed. This was even effective on the case of fall. This study illustrates that the proposed algorithm can provide the reliable distribution of dust aerosols over the desert even at night.

• Advances in Energy Research
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• v.7 no.2
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• pp.123-134
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• 2020

Photovoltaic systems are progressively attached importance and their installed capacity increases day by day because of their reliability, decremented installation and operating cost and simple construction structure. Generated power obtained from a photovoltaic system changes depending upon regional distinctness, and It can be estimated approximately by taking into consideration mean global radiation amount, temperature and humidity. However, there may be different regional negative or positive factors like dust, air pollution, desert powder which affect generated power. The best reliable data for a region can be obtained from the existing photovoltaic system in the region. For this purpose, a monitoring system for 1000W monocrystalline photovoltaic system constructed at Kocaeli University Uzunciftlik Nuh Cimento Vocational High Scholl is prepared. The installed monitoring system shows and records real values generated from the photovoltaic system and environmental data. In the study, Instantaneous data obtained from the monitoring system for October 2018 and 7th October 2018 is given within figures. Additionally, daily and monthly total energy productions of the photovoltaic system are given for October 2018 and date interval between July 2018 and March 2018, respectively.

• Journal of the Korean Chemical Society
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• v.55 no.4
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• pp.680-684
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• 2011

Seed oil of Balanites aegyptica was transesterified to produce biodiesel and its quality and biodegradability assessed. The specific gravity (SG), density and flash point of the methyl esters were found to be 0.897, 0.89 g/$cm^3$ and $163^{\circ}C$ respectively. Biodegradability of the biodiesel assessed by the standard $CO_2$ evolution method using two different inoculums revealed that the Balanites aegyptica biodiesel was readily biodegradable in both inoculums (82.58% and 86.98%), compared with the $D_2$ diesel which was partially biodegradable (27.02% and 27.33%). These suggest that Balanites aegyptiaca seed oil is a potential source of environmentally friendly biodiesel.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.681-691
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• 2016

Using various satellite measurements in UV, visible and IR, diverse algorithms to retrieve aerosol information have been developed and operated to date. Advanced Himawari Imager (AHI) onboard the Himawari 8 weather satellite was launched in 2014 and has 16 channels from visible to Thermal InfRared (TIR) in high temporal and spatial resolution. Using AHI, it is very valuable to retrieve aerosol optical properties over dark surface to demonstrate its capability. To retrieve aerosol optical properties using visible and Near InfRared (NIR) region, surface signal is very important to be removed which can be estimated using minimum reflectivity method. The estimated surface reflectance is then used to retrieve the aerosol optical properties through the inversion process. In this study, we retrieve the aerosol optical properties over dark surface, but not over bright surface such as clouds, desert and so on. Therefore, the bright surface was detected and masked using various infrared channels of AHI and spatial heterogeneity, Brightness Temperature Difference (BTD), etc. The retrieval result shows the correlation coefficient of 0.7 against AERONET, and the within the Expected Error (EE) of 49%. It is accurately retrieved even for low Aerosol Optical Depth (AOD). However, AOD tends to be underestimated over the Beijing Hefei area, where the surface reflectance using the minimum reflectance method is overestimated than the actual surface reflectance.