Paper
20 December 2024 Water/water vapor monitoring using compact Raman Lidar for radiation detection
Author Affiliations +
Abstract
This study explores the potential of Raman Lidar for measuring water vapor and water clusters generated by radiation ionization, addressing challenges in detecting radioactive isotopes in high radiation environments. The most common method for measuring alpha nuclide contaminants is to place a detector close to the contaminant and measure the alpha rays emitted. In this study, on the fundamental experiment, pure water particles were injected into a cubic glass chamber, and Raman signals for water (403.7 nm) and water vapor (407.8 nm) were detected for 355 nm incident light. A narrow bandpass filter (1.5 nm bandwidth) effectively distinguished between the Raman signals of water and water vapor. This led to the development of a three-channel Raman lidar capable of detecting nitrogen (387 nm), water (404 nm), and water vapor (408 nm). Measurements were conducted in a humidity-controlled environment using sealed Americium radiation sources at the Japan Atomic Energy Agency. Results showed that as radioactivity increased, water vapor signals decreased while water signals increased. It is expected that water values will rise at a rate of 7.5 times relative to the decrease in water vapor, with observed results indicating a change rate of approximately six times. Future work will focus on evaluating these change rates, improving measurement reproducibility, and estimating the diameter of water clusters.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Fumitaka Muto, Takashi Okada, Jun Saegusa, and Tatsuo Shiina "Water/water vapor monitoring using compact Raman Lidar for radiation detection", Proc. SPIE 13265, Lidar and Optical Remote Sensing for Environmental Monitoring XVII, 1326508 (20 December 2024); https://doi.org/10.1117/12.3046059
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KEYWORDS
LIDAR

Raman spectroscopy

Ionizing radiation

Laser irradiation

Laser radiation

Particles

Remote sensing

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