Articles | Volume 25, issue 20
https://doi.org/10.5194/acp-25-13687-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-13687-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Oct 2025
Research article |
| 24 Oct 2025
| 24 Oct 2025
Urban Area Observing System (UAOS) simulation experiment using DQ-1 total column concentration observations
Jinchun Yi
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Yiyang Huang
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Zhipeng Pei
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China
Ge Han
CORRESPONDING AUTHOR
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
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Methane plumes can be detected with several instruments from space at a high spatial resolution nowadays. We see a ground projection of these methane plumes from the satellites that, similarly to clouds or buildings, are distorted depending on the observation and illumination angle. Here we highlight this issue and propose a methodology to account for it using simulations that could enhance current and upcoming retrieval and quantification algorithms.
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CH4 works as the second-most important greenhouse gas, its reported emission inventories being far less than CO2. In this study, we developed a self-adjusted model to estimate the CH4 emission rate from strong point sources by the UAV-based AirCore system. This model would reduce the uncertainty in CH4 emission rate quantification accrued by errors in measurements of wind and concentration. Actual measurements on Pniówek coal demonstrate the high accuracy and stability of our developed model.
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-215, https://doi.org/10.5194/essd-2022-215, 2022
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Obtaining highly accurate and high-resolution spatiotemporal maps of carbon dioxide concentration distributions is crucial for promoting the study of the carbon cycle, and carbon emissions assessed by top-down theory. The official discrete satellite data provided by Gosat-2, OCO-2, and OCO-3 have data voids and relatively low efficiency. Here, we present carbon dioxide cover dataset, an innovative methodology to obtain XCO2 maps of high spatiotemporal resolution by using satellite data.
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Short summary
The inventory overestimated emissions in Beijing and Riyadh by 10–20 % and underestimated emissions in Cairo by 10–30 %. The biosphere flux has a 20–40 % impact on emissions in Beijing during certain periods. Moreover, using night-time and day-time biosphere flux data separately can improve the simulation accuracy of the same orbit by 20–70 % compared to using daily average data.
The inventory overestimated emissions in Beijing and Riyadh by 10–20 % and underestimated...
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