A dataset of ground-based vertical profile observations of aerosol, NO2, and HCHO from the hyperspectral vertical remote sensing network in China (2019-2023)

3Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.

Abstract

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, NO2, 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 (10.5281/zenodo.15211604, Jiao et al., 2024).

Cite

CITATION STYLE

APA

Jiao, P., Xing, C., Li, Y., Ji, X., Tan, W., Li, Q., … Liu, C. (2025). A dataset of ground-based vertical profile observations of aerosol, NO2, and HCHO from the hyperspectral vertical remote sensing network in China (2019-2023). Earth System Science Data, 17(7), 3167–3187. https://doi.org/10.5194/essd-17-3167-2025

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free