Articles | Volume 12, issue 4
Earth Syst. Sci. Data, 12, 3067–3080, 2020
https://doi.org/10.5194/essd-12-3067-2020
Earth Syst. Sci. Data, 12, 3067–3080, 2020
https://doi.org/10.5194/essd-12-3067-2020
Data description paper
25 Nov 2020
Data description paper | 25 Nov 2020

A homogenized daily in situ PM2.5 concentration dataset from the national air quality monitoring network in China

Kaixu Bai et al.

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Cited articles

Bai, K., Chang, N.-B., Yu, H., and Gao, W.: Statistical bias correction for creating coherent total ozone record from OMI and OMPS observations, Remote Sens. Environ., 182, 150–168, https://doi.org/10.1016/j.rse.2016.05.007, 2016. 
Bai, K., Chang, N.-B., Zhou, J., Gao, W., and Guo, J.: Diagnosing atmospheric stability effects on the modeling accuracy of PM2.5/AOD relationship in eastern China using radiosonde data, Environ. Pollut., 251, 380–389, https://doi.org/10.1016/j.envpol.2019.04.104, 2019a. 
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, 2019b. 
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, 2019c. 
Bai, K., Li, K., Wu, C., Chang, N.-B., and Guo, J.: A homogenized daily in situ PM2.5 concentration dataset in China during 2015–2019, PANGAEA, https://doi.org/10.1594/PANGAEA.917557, 2020a. 
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Short summary
PM2.5 data from the national air quality monitoring network in China suffered from significant inconsistency and inhomogeneity issues. To create a coherent PM2.5 concentration dataset to advance our understanding of haze pollution and its impact on weather and climate, we homogenized this PM2.5 dataset between 2015 and 2019 after filling in the data gaps. The homogenized PM2.5 data is found to better characterize the variation of aerosol in space and time compared to the original dataset.