| Issue |
EPJ Web Conf.
Volume 362, 2026
31st International Laser Radar Conference (ILRC 31) Held Together with the 22nd Coherent Laser Radar Conference (CLRC 22)
|
|
|---|---|---|
| Article Number | 01015 | |
| Number of page(s) | 4 | |
| Section | Joint CLRC/ILRC Session: New Lidar Technologies and Methods | |
| DOI | https://doi.org/10.1051/epjconf/202636201015 | |
| Published online | 09 April 2026 | |
https://doi.org/10.1051/epjconf/202636201015
Safe Detection of Hazardous Substances Using Resonance Raman LIDAR
(a) Shikoku Research Institute Inc. 2109-8 Yashima-nishimachi, Takamatsu-shi, Kagawa-ken 761-0192, Japan
(b) Central Research Institute of Electric Power Industry 2-6-1 Nagasaka, Yokosuka-shi, Kanagawa-ken 240-0196, Japan
(c) Institute for Laser Technology 3-11-20 Nakouji, Amagasaki-shi, Hyogo-ken 661-0794, Japan This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 9 April 2026
Abstract
New technologies to measure hazardous substances quickly and safely are always required in a wide range of fields. However, the physical properties and the physical states of hazardous substances generated by such as: air pollution, volcanic activity, CBRNE disasters are assumed to vary. For this reason, there is still no device can measure hazardous substances comprehensively. To solve this problem, we have been focusing on the research and development of remote sensing device that is highly sensitive and applicable to various hazardous substances by using resonance Raman effect. We selected air pollutants sulfur dioxide and ammonia as target gases for remote sensing. Three sigma limits for sulfur dioxide and ammonia in this measurement were 3 ppb and 15 ppb at 100 m.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

