| Issue |
MATEC Web Conf.
Volume 413, 2025
International Conference on Measurement, AI, Quality and Sustainability (MAIQS 2025)
|
|
|---|---|---|
| Article Number | 01006 | |
| Number of page(s) | 6 | |
| Section | Advanced Measurement | |
| DOI | https://doi.org/10.1051/matecconf/202541301006 | |
| Published online | 01 October 2025 | |
CO2 concentration detection based on TDLAS technology
1 State key Laboratory of Extreme Environment Optoelectronic Dynamic Testing Technology and Instrument, North University of China, Taiyuan Shan’xi Province, 030051, China
2 School of Instrument and Electronics, North University of China, Taiyuan Shan’xi Province, 030051, China
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
With the growth of industrialization and energy consumption, a large number of CO2 gas emissions lead to global warming and cause a series of environmental problems, which have a great negative impact on the global ecosystem. Therefore, accurate monitoring of CO2 concentration is crucial for understanding climate change and formulating emission reduction strategies.The traditional non-optical analysis method is difficult to measure the low concentration of CO2 gas, and the accuracy is generally low. In this paper, based on tunable diode laser absorption spectroscopy ( TDLAS ), a set of CO2 concentration detection system is constructed by selecting 2004 nm as the central wavelength of the laser. Through the static sensitivity calibration experiment, the calibration is carried out at an interval of 100 ppm. The fitting curve of the integral absorbance and concentration of CO2 gas at 0-1500 ppm concentration is obtained. B1y randomly selecting three concentration points, the average error of the system concentration detection is verified to be less than 5%, and the low concentration measurement of CO2 gas is realized.
© The Authors, published by EDP Sciences, 2025
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.
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