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

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 minutes) dataset of vertical profile observations of atmospheric composition (aerosols, NO2, and HCHO) conducted using passive remote sensing technology across 32 sites in seven major regions of China from 2019 to 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 policy-making. Its sharing would facilitate the scientific community in exploring of source-receptor relationships, investigating the impacts of atmospheric composition on regional and global climate and feedback mechanisms.大气成分垂直廓线观测对于理解区域大气污染的生成、演化与传输过程至关重要。然而，现有技术局限与观测成本掣肘，导致垂直廓线观测数据较为匮乏。本研究构建了一套高时间分辨率（约15分钟）的大气成分垂直廓线观测数据集，该数据集采用被动遥感（passive remote sensing）技术，于2019至2023年间在中国七大主要区域的32个观测站点获取，观测组分涵盖气溶胶（aerosols）、二氧化氮（NO₂）与甲醛（HCHO）。本研究精细刻画了上述污染物的垂直分布、季节变化与日变化规律，揭示了中国不同区域大气成分的长期演变趋势。该数据集可为区域环境管理与政策制定提供关键科学依据。其共享将助力科学界深入探究污染源-受体关系，解析大气成分对区域及全球气候的影响与反馈机制。