Multisource Remote Sensing Based Estimation of Soil NO _x Emissions From Fertilized Cropland at High‐Resolution: Spatio‐Temporal Patterns and Impacts

Abstract Soil nitrogen oxides (NO x ) emissions from agricultural areas currently dominate in some regions around the world. Since China is largely an agricultural country, an accurate estimation of soil NO x emissions from agricultural areas is essential for monitoring air pollution. In this study, we use high‐resolution multi‐source remote sensing data to enhance data inputs to existing empirical NO x emission models, with a particular emphasis on crop phenological features and the impact of nitrogen fertilizer application on NO x at the grid level. As a result, a high‐resolution emission inventory of soil NO x from agricultural areas in China is built. According to the emission inventory, total national NO x emissions from fertilized croplands were 3,741 ± 0.39, 3,231 ± 0.39, and 3,059 ± 0.39 Gg N/yr during 2017–2019, respectively. Moreover, in 2017, soil NO x emissions contributed to 17.3% of the total emissions. It was found the “Hu Huanyong Line” (Hu line) is a dividing line for China's agricultural soil NO x emissions, with soil NO x emissions dominating in the west of the Hu line while being high in the east. The results also show that emissions are highest in summer and lowest in winter, with a significant difference between the two seasons. Furthermore, crop cultivation structure can affect overall soil NO x emissions, which suggests a potential NO x reduction strategy. We demonstrate that the established emission inventory can precisely reflect the distribution of soil NO x emissions in China's agricultural areas, which will be beneficial to overall NO x emission control and air quality improvement.