Abstract: As an important component of atmospheric nitrogen deposition, dry deposition has considerable effect on the construction and function of terrestrial ecosystems. Because of the complexity of dry deposition and the demanding technology in its observation, there were few monitoring stations with a short of observation time in China. Therefore, the way to obtain a spatial pattern dataset with high resolution and long-term series of dry deposition observation is essential to evaluate its effect on China’s ecosystems. Based on the ground monitoring data of dry deposition and remote sensing data of NO2 and NH3, we constructed remote sensing statistical models for different forms of dry deposition, and compiled the spatial dataset of dry deposition during 2006–2010 and during 2011–2015 in China. The dataset covers 6 dry deposition indices: atmospheric particulate ammonium (NH4+ ), atmospheric particulate nitrate (NO3), gaseous nitrogen dioxide (NO2), gaseous nitric acid (HNO3), gaseous nitric acid (NH3), and the total nitrogen dry deposition flux, with a spatial resolution of 10 km×10 km in tiff format. This dataset is the first public and sharing dataset of the atmospheric nitrogen dry deposition based on ground monitoring data in China, which can provide basic data reference for the evaluation of its ecological and environmental effect and serve as theoretical support for making the policy about nitrogen management.
Keywords: China; dry deposition; remote sensing model; spatial and temporal pattern