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Volume 25
Issue 19
10.3390/s25196114
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Effects of Environmental Factors on the Performance of Ground-Based Low-Cost CO2 Sensors

by
Xiaoyu Ren
1,2,
Kai Wu
1,2,*,
Dongxu Yang
1,2,*,
Yi Liu
1,2,
Yong Wang
3,
Ting Wang
1,2,
Zhaonan Cai
1,2,
Lu Yao
1,2,
Tonghui Zhao
1,2,
Jing Wang
1,2 and
Zhe Jiang
1,2
1
1. Carbon Neutrality Research Center (CNRC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
2
2. Key Laboratory of Middle Atmospheric Physics and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
3
3. Nanjing ZTWEATHER Technology Company Limited, Nanjing 210044, China
*
Authors to whom correspondence should be addressed.
Sensors 2025, 25(19), 6114; https://doi.org/10.3390/s25196114
Submission received: 2 September 2025 / Revised: 21 September 2025 / Accepted: 24 September 2025 / Published: 3 October 2025
(This article belongs to the Section Environmental Sensing)
Versions Notes

Abstract

This paper presents a multivariable linear regression calibration method for non-dispersive infrared (NDIR) CO2 sensors in a low-cost carbon monitoring network. We test this calibration method with data collected in a temperature- and pressure-controlled laboratory and evaluate the calibration method with long-term observational data collected at the Xinglong Atmospheric Background Observatory. Compared to data collected by a high-accuracy cavity ring-down spectrometer (Picarro), the results show that a multivariable linear regression approach incorporating temperature, pressure, and relative humidity can reduce the mean absolute bias from 5.218 ppm to 0.003 ppm, with root mean square errors (RMSE) within 2.1 ppm after calibration. For field observations, the RMSE is reduced from 8.315 ppm to 2.154 ppm, and the bias decreases from 39.170 ppm to 0.018 ppm. The calibrated data can effectively capture the diurnal variation of CO2 mole fraction. The test of the number of reference data shows that about 10 days of co-located reference data are sufficient to obtain reliable measurements. Calibration windows taken from winter or summer provide better results, suggesting a strategy to optimize short-term calibration campaigns.
Keywords: CO2 mole fraction measurements; calibration; low-cost sensors; long-term field observation CO2 mole fraction measurements; calibration; low-cost sensors; long-term field observation

Share and Cite

MDPI and ACS Style

Ren, X.; Wu, K.; Yang, D.; Liu, Y.; Wang, Y.; Wang, T.; Cai, Z.; Yao, L.; Zhao, T.; Wang, J.; et al. Effects of Environmental Factors on the Performance of Ground-Based Low-Cost CO2 Sensors. Sensors 2025, 25, 6114. https://doi.org/10.3390/s25196114

AMA Style

Ren X, Wu K, Yang D, Liu Y, Wang Y, Wang T, Cai Z, Yao L, Zhao T, Wang J, et al. Effects of Environmental Factors on the Performance of Ground-Based Low-Cost CO2 Sensors. Sensors. 2025; 25(19):6114. https://doi.org/10.3390/s25196114

Chicago/Turabian Style

Ren, Xiaoyu, Kai Wu, Dongxu Yang, Yi Liu, Yong Wang, Ting Wang, Zhaonan Cai, Lu Yao, Tonghui Zhao, Jing Wang, and et al. 2025. "Effects of Environmental Factors on the Performance of Ground-Based Low-Cost CO2 Sensors" Sensors 25, no. 19: 6114. https://doi.org/10.3390/s25196114

APA Style

Ren, X., Wu, K., Yang, D., Liu, Y., Wang, Y., Wang, T., Cai, Z., Yao, L., Zhao, T., Wang, J., & Jiang, Z. (2025). Effects of Environmental Factors on the Performance of Ground-Based Low-Cost CO2 Sensors. Sensors, 25(19), 6114. https://doi.org/10.3390/s25196114

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