Articles | Volume 16, issue 9
https://doi.org/10.5194/essd-16-4051-2024
https://doi.org/10.5194/essd-16-4051-2024
Data description paper
 | 
12 Sep 2024
Data description paper |  | 12 Sep 2024

PM2.5 concentrations based on near-surface visibility in the Northern Hemisphere from 1959 to 2022

Hongfei Hao, Kaicun Wang, Guocan Wu, Jianbao Liu, and Jing Li

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Revised manuscript accepted for ESSD
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Cited articles

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Ali, M. A., Bilal, M., Wang, Y., Nichol, J. E., Mhawish, A., Qiu, Z., de Leeuw, G., Zhang, Y., Zhan, Y., Liao, K., Almazroui, M., Dambul, R., Shahid, S., and Islam, M. N.: Accuracy assessment of CAMS and MERRA-2 reanalysis PM2.5 and PM10 concentrations over China, Atmos. Environ., 288, 119297, https://doi.org/10.1016/j.atmosenv.2022.119297, 2022. 
Bai, K. and Li, K.: LGHAP v2: Global daily 1-km gap-free PM2.5 grids (2000), Zenodo [data set], https://doi.org/10.5281/zenodo.8307595, 2023a. 
Bai, K. and Li, K.: LGHAP v2: Global daily 1-km gap-free PM2.5 grids (2001), Zenodo [data set], https://doi.org/10.5281/zenodo.8307597, 2023b. 
Bai, K. and Li, K.: LGHAP v2: Global daily 1-km gap-free PM2.5 grids (2002), Zenodo [data set], https://doi.org/10.5281/zenodo.8307599, 2023c. 
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In this study, daily PM2.5 concentrations are estimated from 1959 to 2022 using a machine learning method at more than 5000 terrestrial sites in the Northern Hemisphere based on hourly atmospheric visibility data, which are extracted from the Meteorological Terminal Aviation Routine Weather Report (METAR).
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