Hardware and software systems for remote sensing of atmospheric carbon dioxide
大気中の二酸化炭素を遠隔計測するためのハードウェア・ソフトウェアシステム (AI 翻訳)
A. Kryuchkov, M.P. Garesimova, A. Markova, S. Sadovnikov, V. Filatov, S. Yakovlev, O. Romanovskii, Yury V. Kistenev
🤖 gxceed AI 要約
日本語
本論文は、TDLASとDASを組み合わせた高精度のCO2遠隔リアルタイム監視システムの開発を報告。Red PitayaプラットフォームとFPGAを用いた信号処理により、大気乱流下でも高いSN比を実現。逆スペクトル問題をリアルタイムで解き、サブ秒の時間分解能で人為排出や全球温室効果ガス動態を検出可能。
English
This paper reports the development of a high-precision remote real-time CO2 monitoring system combining TDLAS and DAS. Using Red Pitaya platform and FPGA signal processing, it achieves high SNR under atmospheric turbulence. It solves the inverse spectroscopic problem in real time, detecting anthropogenic emissions and global greenhouse gas dynamics with sub-second temporal resolution.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では、環境省や自治体によるCO2濃度監視ネットワークの高度化が進んでおり、本論文のような小型・高精度センサーはモバイルLIDARやドローン搭載型の監視システムへの応用が期待される。SSBJや有報での排出量算定には直接関係しないが、実測による検証手法として参考になる。
In the global GX context
Globally, the paper contributes to the technical foundation for distributed greenhouse gas monitoring, which can support verification of emissions reported under frameworks like the Global Stocktake and national inventories. It offers a compact, scalable approach that could enhance transparency in climate action tracking.
👥 読者別の含意
🔬研究者:Provides a detailed technical implementation of a CO2 remote sensing system using TDLAS/DAS and FPGA, relevant for those working on environmental monitoring instrumentation.
🏢実務担当者:Environmental monitoring firms or utilities could explore this system for cost-effective, mobile CO2 detection in urban or industrial areas.
📄 Abstract（原文）
This paper describes the development and technical implementation of a high-precision hardware and software system designed for remote real-time monitoring of atmospheric carbon dioxide. The proposed solution is based on an integrated hardware complex for greenhouse gas sensing using a combination of Tunable Diode Laser Absorption Spectroscopy (TDLAS) and Direct Absorption Spectroscopy (DAS) techniques. The underlying physical principle relies on the Beer-Lambert law, while the data processing unit utilizes the Voigt profile analysis to account for both Doppler and collision broadening of spectral lines, ensuring measurement accuracy under fluctuating atmospheric pressures and temperatures. The system architecture is built upon the Red Pitaya platform, leveraging the computational power of the Xilinx Zynq FPGA. To achieve high sensitivity, the FPGA logic incorporates Direct Digital Synthesis (DDS) modules for precise laser frequency scanning along with high-speed digital averaging and coherent integration algorithms. These hardware-level features significantly improve the signal-to-noise ratio (SNR) in the presence of atmospheric turbulence and optical path distortions. The developed complex enables the solution of the inverse spectroscopic problem in real time, providing a robust tool for environmental remote sensing and climate monitoring. By integrating on-chip digital signal processing with advanced spectroscopic modeling, this research offers a compact and scalable approach for mobile LIDAR systems capable of detecting anthropogenic emissions and global greenhouse gas dynamics with sub-second temporal resolution, meeting the stringent requirements of modern environmental instrumentation and radio-electronic engineering.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.30898/1684-1719.2026.2.15first seen 2026-06-29 08:47:19
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