원거리의 물과 오일을 구별할 수 있는 UV형광측정시스템 개발과 분석에 대한 연구
Long Distance Identification of Water and Oil using an Ultraviolet Fluorescence Measurement System
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Owing to the rising volume of seaborne trade, oil spills damage the marine environment for over 250 yearly. Thus, various analysismethods such as the Fourier-transform infrared (FTIR), Raman spectroscope, and gas chromatography are used to monitor oil spills atsea, but these methods are expensive. Recently, to reduce operational costs, an underwater fluorometer was adopted. However, thisapproach is not ideal for the remote sensing of oil spills because the device gets submerged in the sea. In this study, we have designedand developed a monitoring system that uses ultraviolet fluorescence to detect spilled oil or water from a distance, as well as proposedan analyzing method defining based on water Raman signal and QF535. Each fluorescence spectrum of water, oil (crude oil), andBunker A was obtained using the system, and was calculated and analyzed from the spectrum individually. Based on the resultsof the analysis, we could successfully identity water and oil at a long distance.
Abstract
Owing to the rising volume of seaborne trade, oil spills damage the marine environment for over 250 yearly. Thus, various analysismethods such as the Fourier-transform infrared (FTIR), Raman spectroscope, and gas chromatography are used to monitor oil spills atsea, but these methods are expensive. Recently, to reduce operational costs, an underwater fluorometer was adopted. However, thisapproach is not ideal for the remote sensing of oil spills because the device gets submerged in the sea. In this study, we have designedand developed a monitoring system that uses ultraviolet fluorescence to detect spilled oil or water from a distance, as well as proposedan analyzing method defining based on water Raman signal and QF535. Each fluorescence spectrum of water, oil (crude oil), andBunker A was obtained using the system, and was calculated and analyzed from the spectrum individually. Based on the resultsof the analysis, we could successfully identity water and oil at a long distance.
참고문헌 (15)
- Y. S. Lee, "Introduction of Korea Oil Identification System(KOIS)", Proc. of KOSOMES biannual meeting on The Korean Society of Marine Environment and safety, pp.85~92 (2006)
- H. Boleydei, "Comparative study on adsorption of crude oil and spent engine oil from seawater and freshwater using algal biomass", Environ. Sci. Pollut. Res, pp.2018~ (2018)
- F. E. HOGE, "Oil film thickness measurement using airborne laser-induced water Raman backscatter", Appl. Opt, 19, pp.3269~3281 (1980)
- Y. S. Lee, "Study for Oil Spill Source Identification by Comprehensive Two Dimensional Gas Chromatography", Proc. of KOSOMES biannual meeting on The Korean Society of Marine Environment and safety, pp.169~174 (2006)
- “Optical methods for water pollution monitoring,” in Spatial and Organizational Dynamics: Discussion Papers, "A. Utkin", University of Algarve, 129~146 (2011)
- S. Patsayeva, "Problems of Remote Diagnostics of Mineral Oil in Sea Water : Oil Films and Oil Dispersed in the Water Body", Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, pp.568~573 (1996)
- D. Zheng, "Aquatic environment monitoring using a drone-based fluorosensor", Appl. Phys. B, 125(6), pp.1~8 (2019)
- S. Si, "Determination of accumulation periods and relative maturity of tight oil and gas in Gaotaizi oil reservoir of Qijia area by using fluorescence spectrum of oil inclusions", China Pet. Explor, 23(6), pp.78~86 (2018)
- A. G. Ryder, "Reviews in Fluorescence 2005", pp.169~198 (2005), Springer
- P. Jacques, "Ultraviolet-fluorescence alteration of hydrocarbon fluid inclusions", Org. Geochem, 18(4), pp.501~509 (1992)
- A. J. Lawaetz, "Fluorescence Intensity Calibration Using the Raman Scatter Peak of Water", Appl. Spectrosc, 63(8), pp.936~940 (2009)
- J. S. Bartlett, "Raman scattering by pure water and seawater", Appl. Opt, 37(15), pp.3324~3332 (1998)
- J. E. Min, "Advanced Surface Reflected Radiance Correction for Airborne Hyperspectral Imagery in Coastal Red Tide Detection", ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci, 3, pp.73~80 (2021)
- Z. Xu, "Classification, identification, and growth stage estimation of microalgae based on transmission hyperspectral microscopic imaging and machine learning", Opt. Express, 28(21), pp.30686~30700 (2020)