A dataset of ground-based vertical profile observations of aerosol, NO<sub>2</sub>, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023)
<p>Vertical profile observations of atmospheric composition are crucial for understanding the generation, evolution, and transport of regional air pollution. However, existing technological limitations and costs have resulted in a scarcity of vertical profile data. This study introduces a high...
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Copernicus Publications
2025-07-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/17/3167/2025/essd-17-3167-2025.pdf |
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| author | P. Jiao C. Xing Y. Li X. Ji W. Tan Q. Li H. Liu C. Liu C. Liu C. Liu C. Liu |
| author_facet | P. Jiao C. Xing Y. Li X. Ji W. Tan Q. Li H. Liu C. Liu C. Liu C. Liu C. Liu |
| author_sort | P. Jiao |
| collection | DOAJ |
| description | <p>Vertical profile observations of atmospheric composition are crucial for understanding the generation, evolution, and transport of regional air pollution. However, existing technological limitations and costs have resulted in a scarcity of vertical profile data. This study introduces a high-time-resolution (approximately 15 min) dataset of vertical profile observations of atmospheric composition (aerosol, <span class="inline-formula">NO<sub>2</sub></span>, and HCHO) conducted using passive remote sensing technology across 32 sites in 7 major regions of China from 2019–2023. The study meticulously documents the vertical distribution, seasonal variations, and diurnal pattern of these pollutants, revealing long-term trends in atmospheric composition across various regions of China. This dataset provides essential scientific evidence for regional environmental management and policymaking. Its sharing would facilitate the scientific community in exploring source–receptor relationships, investigating the impacts of atmospheric composition on regional and global climate and feedback mechanisms. It also holds potential for enhancing satellite retrieval methods and advancing the development of regional transport models. The dataset is available for free at Zenodo (<a href="https://doi.org/10.5281/zenodo.15211604">https://doi.org/10.5281/zenodo.15211604</a>, Jiao et al., 2024).</p> |
| format | Article |
| id | doaj-art-a781d9d8a36d46d399d955deb9c8864b |
| institution | DOAJ |
| issn | 1866-3508 1866-3516 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Science Data |
| spelling | doaj-art-a781d9d8a36d46d399d955deb9c8864b2025-08-20T03:15:03ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162025-07-01173167318710.5194/essd-17-3167-2025A dataset of ground-based vertical profile observations of aerosol, NO<sub>2</sub>, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023)P. Jiao0C. Xing1Y. Li2X. Ji3W. Tan4Q. Li5H. Liu6C. Liu7C. Liu8C. Liu9C. Liu10Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, ChinaKey Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, ChinaSchool of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, ChinaInformation Materials and Intelligent Sensing Laboratory of Anhui Province, Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, ChinaKey Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, ChinaInstitute of Physical Science and Information Technology, Anhui University, Hefei 230601, ChinaInstitute of Physical Science and Information Technology, Anhui University, Hefei 230601, ChinaDepartment of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, ChinaKey Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, ChinaCenter for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, ChinaKey Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China<p>Vertical profile observations of atmospheric composition are crucial for understanding the generation, evolution, and transport of regional air pollution. However, existing technological limitations and costs have resulted in a scarcity of vertical profile data. This study introduces a high-time-resolution (approximately 15 min) dataset of vertical profile observations of atmospheric composition (aerosol, <span class="inline-formula">NO<sub>2</sub></span>, and HCHO) conducted using passive remote sensing technology across 32 sites in 7 major regions of China from 2019–2023. The study meticulously documents the vertical distribution, seasonal variations, and diurnal pattern of these pollutants, revealing long-term trends in atmospheric composition across various regions of China. This dataset provides essential scientific evidence for regional environmental management and policymaking. Its sharing would facilitate the scientific community in exploring source–receptor relationships, investigating the impacts of atmospheric composition on regional and global climate and feedback mechanisms. It also holds potential for enhancing satellite retrieval methods and advancing the development of regional transport models. The dataset is available for free at Zenodo (<a href="https://doi.org/10.5281/zenodo.15211604">https://doi.org/10.5281/zenodo.15211604</a>, Jiao et al., 2024).</p>https://essd.copernicus.org/articles/17/3167/2025/essd-17-3167-2025.pdf |
| spellingShingle | P. Jiao C. Xing Y. Li X. Ji W. Tan Q. Li H. Liu C. Liu C. Liu C. Liu C. Liu A dataset of ground-based vertical profile observations of aerosol, NO<sub>2</sub>, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023) Earth System Science Data |
| title | A dataset of ground-based vertical profile observations of aerosol, NO<sub>2</sub>, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023) |
| title_full | A dataset of ground-based vertical profile observations of aerosol, NO<sub>2</sub>, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023) |
| title_fullStr | A dataset of ground-based vertical profile observations of aerosol, NO<sub>2</sub>, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023) |
| title_full_unstemmed | A dataset of ground-based vertical profile observations of aerosol, NO<sub>2</sub>, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023) |
| title_short | A dataset of ground-based vertical profile observations of aerosol, NO<sub>2</sub>, and HCHO from the hyperspectral vertical remote sensing network in China (2019–2023) |
| title_sort | dataset of ground based vertical profile observations of aerosol no sub 2 sub and hcho from the hyperspectral vertical remote sensing network in china 2019 2023 |
| url | https://essd.copernicus.org/articles/17/3167/2025/essd-17-3167-2025.pdf |
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