Articles | Volume 13, issue 5
Earth Syst. Sci. Data, 13, 2147–2163, 2021
https://doi.org/10.5194/essd-13-2147-2021
Earth Syst. Sci. Data, 13, 2147–2163, 2021
https://doi.org/10.5194/essd-13-2147-2021
Data description paper
19 May 2021
Data description paper | 19 May 2021

Long-term trends of ambient nitrate (NO3) concentrations across China based on ensemble machine-learning models

Rui Li et al.

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Latest update: 25 May 2022
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Short summary
A unique monthly NO3− dataset at 0.25° resolution over China during 2005–2015 was developed by assimilating multi-source variables. The newly developed product featured an excellent cross-validation R2 value (0.78) and relatively lower RMSE (1.19 μg N m−3) and mean absolute error (MAE: 0.81 μg N m−3). The dataset also exhibited relatively robust performance at the spatial and temporal scales. The dataset over China could deepen knowledge of the status of N pollution in China.