A Remote Sensing Technique for CO<sub>2</sub> Column Density

Ground-based remote sensing, as a critical technique for monitoring atmospheric greenhouse gas column density and calibrating satellite data, provides robust scientific support for establishing carbon accounting systems, studying regional carbon cycles, assessing the effectiveness of carbon reduction policies, and analyzing the dynamics of carbon sources and sinks. We have developed a novel greenhouse gas remote sensing device, hyperspectral atmospheric greenhouse gas remote sensor (HAGRES), which uses a grating spectrometer and a home-built solar tracker to determine atmospheric CO₂ column density by analyzing solar spectra in the 1597.4–1618 nm band. The CO₂ column density results were validated against temporally coinciding on-site measurements taken with the Total Carbon Column Observing Network (TCCON) IFS125HR spectrometer. Over a year of comparative observations, the mean difference between the device and TCCON data was (0.12±0.23) %, with a correlation coefficient of R=0.98. Additionally, CO₂ data from the GOSAT satellite around Hefei was compared with ground-based results, demonstrating correlation coefficients of 0.95 with TCCON and 0.92 with HAGRES. HAGRES has operated automatically and stably outdoors for 12 months, showing strong optical stability and environmental adaptability after applying waterproof protection treatment. These results suggest that HAGRES is a cost-effective tool for satellite validation and carbon budget studies, supporting effective emission reduction strategies and contributing to China’s carbon neutrality goals.

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Publication Details

Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/tgrs.2025.3579265
Citations
1
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
1.11

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article

A Remote Sensing Technique for CO2 Column Density

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IEEE Transactions on Geoscience and Remote Sensing
Atmospheric and Environmental Gas Dynamics
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article

A Remote Sensing Technique for CO2 Column Density

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article en
1 citations

Abstract

Ground-based remote sensing, as a critical technique for monitoring atmospheric greenhouse gas column density and calibrating satellite data, provides robust scientific support for establishing carbon accounting systems, studying regional carbon cycles, assessing the effectiveness of carbon reduction policies, and analyzing the dynamics of carbon sources and sinks. We have developed a novel greenhouse gas remote sensing device, hyperspectral atmospheric greenhouse gas remote sensor (HAGRES), which uses a grating spectrometer and a home-built solar tracker to determine atmospheric CO₂ column density by analyzing solar spectra in the 1597.4–1618 nm band. The CO₂ column density results were validated against temporally coinciding on-site measurements taken with the Total Carbon Column Observing Network (TCCON) IFS125HR spectrometer. Over a year of comparative observations, the mean difference between the device and TCCON data was (0.12±0.23) %, with a correlation coefficient of R=0.98. Additionally, CO₂ data from the GOSAT satellite around Hefei was compared with ground-based results, demonstrating correlation coefficients of 0.95 with TCCON and 0.92 with HAGRES. HAGRES has operated automatically and stably outdoors for 12 months, showing strong optical stability and environmental adaptability after applying waterproof protection treatment. These results suggest that HAGRES is a cost-effective tool for satellite validation and carbon budget studies, supporting effective emission reduction strategies and contributing to China’s carbon neutrality goals.

IEEE Transactions on Geoscience and Remote SensingVol. 63
University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Hefei Institutes of Physical Science (CN), Anhui Institute of Optics and Fine Mechanics (CN), National Science Centre (PL)
National Natural Science Foundation of China
Openalex Percentile: Top 23%
Atmospheric and Environmental Gas Dynamics
1.11
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