Articles | Volume 16, issue 11
https://doi.org/10.5194/essd-16-5287-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-5287-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The global daily High Spatial–Temporal Coverage Merged tropospheric NO2 dataset (HSTCM-NO2) from 2007 to 2022 based on OMI and GOME-2
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
Hongrui Gao
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
Xuancen Liu
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
Pravash Tiwari
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
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Zexia Duan, Zhiqiu Gao, Qing Xu, Shaohui Zhou, Kai Qin, and Yuanjian Yang
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Shuo Wang, Jason Blake Cohen, Chuyong Lin, and Weizhi Deng
Atmos. Chem. Phys., 20, 15401–15426, https://doi.org/10.5194/acp-20-15401-2020, https://doi.org/10.5194/acp-20-15401-2020, 2020
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We analyze global measurements of aerosol height from fires. A plume rise model reproduces measurements with a low bias in five regions, while a statistical model based on satellite measurements of trace gasses co-emitted from the fires reproduces measurements without bias in eight regions. We propose that the magnitude of the pollutants emitted may impact their height and subsequent downwind transport. Using satellite data allows better modeling of the global aerosol distribution.
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Short summary
Satellites have brought new opportunities for monitoring atmospheric NO2, although the results are limited by clouds and other factors, resulting in missing data. This work proposes a new process to obtain reliable data products with high coverage by reconstructing the raw data from multiple satellites. The results are validated in terms of traditional methods as well as variance maximization and demonstrate a good ability to reproduce known polluted and clean areas around the world.
Satellites have brought new opportunities for monitoring atmospheric NO2, although the results...
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