Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-907-2022
https://doi.org/10.5194/essd-14-907-2022
Data description paper
 | 
24 Feb 2022
Data description paper |  | 24 Feb 2022

LGHAP: the Long-term Gap-free High-resolution Air Pollutant concentration dataset, derived via tensor-flow-based multimodal data fusion

Kaixu Bai, Ke Li, Mingliang Ma, Kaitao Li, Zhengqiang Li, Jianping Guo, Ni-Bin Chang, Zhuo Tan, and Di Han

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Revised manuscript accepted for ESSD
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Cited articles

Bai, K., Chang, N.-B., and Chen, C.-F.: Spectral Information Adaptation and Synthesis Scheme for Merging Cross-Mission Ocean Color Reflectance Observations From MODIS and VIIRS, IEEE T. Geosci. Remote, 54, 311–329, https://doi.org/10.1109/TGRS.2015.2456906, 2016. 
Bai, K., Li, K., Chang, N.-B., and Gao, W.: Advancing the prediction accuracy of satellite-based PM2.5 concentration mapping: A perspective of data mining through in situ PM2.5 measurements, Environ. Pollut., 254, 113047, https://doi.org/10.1016/j.envpol.2019.113047, 2019a. 
Bai, K., Ma, M., Chang, N.-B., and Gao, W.: Spatiotemporal trend analysis for fine particulate matter concentrations in China using high-resolution satellite-derived and ground-measured PM2.5 data, J. Environ. Manage., 233, 530–542, https://doi.org/10.1016/j.jenvman.2018.12.071, 2019b. 
Bai, K., Li, K., Wu, C., Chang, N.-B., and Guo, J.: A homogenized daily in situ PM2.5 concentration dataset from the national air quality monitoring network in China, Earth Syst. Sci. Data, 12, 3067–3080, https://doi.org/10.5194/essd-12-3067-2020, 2020a. 
Bai, K., Li, K., Guo, J., Yang, Y., and Chang, N.-B.: Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles, Atmos. Meas. Tech., 13, 1213–1226, https://doi.org/10.5194/amt-13-1213-2020, 2020b. 
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The Long-term Gap-free High-resolution Air Pollutant concentration dataset, providing gap-free aerosol optical depth (AOD) and PM2.5 and PM10 concentration with a daily 1 km resolution for 2000–2020 in China, is generated and made publicly available. This is the first long-term gap-free high-resolution aerosol dataset in China and has great potential to trigger multidisciplinary applications in Earth observations, climate change, public health, ecosystem assessment, and environment management.
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