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Development of Raman Lidar for Remote Sensing of CO2 Leakage at an Artificial Carbon Capture and Storage Site

DOI:10.3390/rs10091439 期刊:Remote Sensing 出版年份:2018 更新时间:2025-09-23 15:22:29
摘要: We developed a Raman lidar system that can remotely detect CO2 leakage and its volume mixing ratio (VMR). The system consists of a laser, a telescope, an optical receiver, and detectors. Indoor CO2 cell measurements show that the accuracy of the Raman lidar is 99.89%. Field measurements were carried out over a four-day period in November 2017 at the Eumsong Environmental Impact Evaluation Test Facility (EIT), Korea, where a CO2 leak was located 0.2 km from the Raman lidar. The results show good agreement between CO2 VMR measured by the Raman lidar system (CO2 VMRRaman LIDAR) and that measured by in situ instruments (CO2 VMRIn-situ). The correlation coefficient (R), mean absolute error (MAE), root mean square error (RMSE), and percentage difference between CO2 VMRIn-situ and CO2 VMRRaman LIDAR are 0.81, 0.27%, 0.37%, and 4.92%, respectively. The results indicate that Raman lidar is an effective tool in detecting CO2 leakage and in measuring CO2 VMR remotely.
作者: Daewon Kim,Hyeongwoo Kang,Jea-Yong Ryu,Seong-Chun Jun,Seong-Taek Yun,SungChul Choi,SunHo Park,MoonSang Yoon,Hanlim Lee
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To develop a Raman lidar system capable of remotely detecting CO2 leakage and measuring its volume mixing ratio (VMR) for monitoring carbon capture and storage sites.

The developed Raman lidar system demonstrates high accuracy (99.89%) in indoor tests and good agreement with in situ measurements in field tests (R=0.81, percentage difference=4.92%). It is effective for remote detection of CO2 leakage and VMR measurement, but limitations in spatial resolution and environmental factors suggest the need for enhancements such as higher laser power, improved receivers, and algorithm refinements for broader applicability in carbon capture and storage monitoring.

The spatial resolution of the lidar system (37.5 m) may not detect small CO2 leaks effectively. Measurements are limited to night-time due to sunlight interference. The system's performance can be affected by terrain obstacles and wind conditions, which were not quantified due to lack of data. Lowering measurement altitude may introduce noise from fluorescence effects. The current algorithm does not account for fluorescence, and further improvements are needed for better precision and detection limits at low CO2 levels.

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