A dataset of ground-based VCDs (O₃, NO₂, HCHO, HONO, SO₂) and AOD observations from the hyperspectral vertical remote sensing network in China (2020–2025)

Abstract. With the rapid development of satellite observations of atmospheric composition and aerosols, long-term, independent, and standardized ground-based column measurements have become increasingly important for satellite product validation, retrieval error diagnosis, and multi-source data fusion. However, long-term ground-based column datasets covering multiple atmospheric constituents and processed using a unified framework remain limited in China. This study presents a ground-based dataset of multi-component vertical column densities (VCDs) and aerosol optical depth (AOD) from the Chinese Hyperspectral Vertical Remote Sensing Network for 2020–2025. The dataset includes VCDs of O₃, NO₂, HCHO, HONO, and SO₂, together with AOD. It is based on observations from 53 MAX-DOAS sites across China, covering approximately 22.5–44.1° N and 80.1–122.7° E. The sites represent urban agglomerations, suburban transition zones, industrial areas, coastal and island environments, inland basins, arid and semi-arid regions, and the Tibetan Plateau. All observations were processed using a unified retrieval and quality-control framework to ensure consistency among sites and species. AOD has the broadest coverage, with 53 valid sites and 1073 valid site-months. NO₂ and HCHO each cover 52 sites and more than 1000 valid site-months. SO₂ and HONO cover 45 and 44 sites, respectively. O₃ covers 29 sites and 588 valid site-months. For valid months, the median monthly completeness is 83.9 % for O₃, NO₂, HCHO, and SO₂, and 86.7 % for HONO and AOD. Comparisons with independent observations show correlation coefficients of 0.899, 0.734, and 0.551 for MAX-DOAS NO₂, HCHO, and O₃ VCDs against satellite products, respectively. The correlation between AOD and AERONET is 0.879. Correlations of NO₂, SO₂, and O₃ VCDs with CNEMC surface observations are 0.720, 0.624, and 0.678, respectively. This dataset provides a long-term, independent, and standardized ground-based reference for validating satellite VCD and AOD products, diagnosing retrieval biases, supporting satellite–AI integration and bias correction, and evaluating chemical transport models. The dataset is freely available at Zenodo (https://doi.org/10.5281/zenodo.22691855, Xing et al., 2026).