<p>High loadings of nitrate (NO<sub>3</sub><sup>−</sup>) in the aerosol over China significantly exacerbates the air quality and poses a great threaten on ecosystem safety through dry/wet deposition. Unfortunately, limited ground-level observation data makes it challenging to fully reflect the spatial pattern of NO<sub>3</sub><sup>−</sup> level across China. Up to date, the long-term monthly NO<sub>3</sub><sup>−</sup> datasets at a high resolution were still missing, which restricted the assessment of human health and ecosystem safety. Therefore, a unique monthly NO<sub>3</sub><sup>−</sup> dataset at 0.25° resolution over China during 2005–2015 was developed by assimilating surface observation, satellite product, meteorological data, land use types and other covariates using an ensemble model combining random forest (RF), gradient boosting decision tree (GBDT), and extreme gradient boosting (XGBoost). The new developed product featured excellent cross-validation R<sup>2</sup> value (0.78) and relatively lower root-mean-square error (RMSE: 1.19 μg/m<sup>3</sup>) and mean absolute error (MAE: 0.81 μg/m<sup>3</sup>). Besides, the dataset also exhibited relatively robust performance at the spatial and temporal scale. Moreover, the dataset displayed good agreement with (R<sup>2</sup> = 0.85, RMSE = 0.74 μg/m<sup>3</sup>, and MAE = 0.55 μg/m<sup>3</sup>) some unlearning data collected from previous studies. The spatiotemporal variations of the developed product were also shown. The estimated NO<sub>3</sub><sup>−</sup> concentration showed the highest value in North China Plain (NCP) (3.55 ± 1.25 μg/m<sup>3</sup>), followed by Yangtze River Delta (YRD (2.56 ± 1.12  g/m<sup>3</sup>)), Pearl River Delta (PRD (1.68 ± 0.81 μg/m<sup>3</sup>)), Sichuan Basin (1.53 ± 0.63 μg/m<sup>3</sup>), and the lowest one in Tibetan Plateau (0.42 ± 0.25 μg/m<sup>3</sup>). The higher ambient NO<sub>3</sub><sup>−</sup> concentrations in NCP, YRD, and PRD were closely linked to the dense anthropogenic emissions. Apart from the intensive human activities, poor terrain condition might be a key factor for the serious NO<sub>3</sub><sup>−</sup> pollution in Sichuan Basin. The lowest ambient NO<sub>3</sub><sup>−</sup> concentration in Tibetan Plateau was contributed by the scarce anthropogenic emission and favorable meteorological factors (e.g., high wind speed). In addition, the ambient NO<sub>3</sub><sup>−</sup> concentration showed marked increasing tendency of 0.10 μg/m<sup>3</sup>/year during 2005–2014 (<i>p</i> < 0.05), while it decreased sharply from 2014 to 2015 at a speed of −0.40 μg/m<sup>3</sup>/year (<i>p</i> < 0.05). The ambient NO<sub>3</sub><sup>−</sup> levels in Beijing-Tianjin-Hebei (BTH), YRD, and PRD displayed gradual increases at the speed of 0.13, 0.08, and 0.03 μg/m<sup>3</sup>/year (<i>p</i> < 0.05) during 2005–2014, respectively. The gradual increases of NO<sub>3</sub><sup>−</sup> concentrations in these regions from 2005 to 2014 were due to that the emission reduction measures during this period focused on the reduction of SO<sub>2</sub> emission rather than NO<sub><i>x</i></sub> emission and the rapid increase of energy consumption. Afterwards, the government further strengthened these emission reduction measures, and thus caused the dramatic decreases of NO<sub>3</sub><sup>−</sup> concentrations in these regions from 2014 to 2015 (<i>p</i> < 0.05). The long-term NO<sub>3</sub><sup>−</sup> dataset over China could greatly deepen the knowledge about the impacts of emission reduction measures on air quality improvement. The monthly particulate NO<sub>3</sub><sup>−</sup> levels over China during 2005–2015 are open access in <a href="https://doi.org/10.5281/zenodo.3988307" target="_blank">https://doi.org/10.5281/zenodo.3988307</a> (Li et al., 2020c).</p>