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Remote Sens. 2018, 10(9), 1439; https://doi.org/10.3390/rs10091439

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

1
Division of Earth Environmental System Science Major of Spatial Information Engineering, Pukyong National University, Busan 48513, Korea
2
Department of Urban Environmental Engineering, Kyungnam University, Gyeongsangnam-do 631-701, Korea
3
GeoGreen21 Co., Ltd., Seoul 08376, Korea
4
Department of Earth and Environmental Sciences, Korea University, Seoul 02841, Korea
5
SOLETOP Co., Ltd., 409 Expo-ro, Yuseong-gu, Daejeon 34051, Korea
*
Author to whom correspondence should be addressed.
Received: 17 July 2018 / Revised: 3 September 2018 / Accepted: 6 September 2018 / Published: 9 September 2018
(This article belongs to the Section Atmosphere Remote Sensing)
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Abstract

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. View Full-Text
Keywords: CO2; Raman lidar; Carbon capture and storage; CO2 leakage remote sensing CO2; Raman lidar; Carbon capture and storage; CO2 leakage remote sensing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Kim, D.; Kang, H.; Ryu, J.-Y.; Jun, S.-C.; Yun, S.-T.; Choi, S.; Park, S.; Yoon, M.; Lee, H. Development of Raman Lidar for Remote Sensing of CO2 Leakage at an Artificial Carbon Capture and Storage Site. Remote Sens. 2018, 10, 1439.

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