Multisource Remote Sensing Based Estimation of Soil NOx Emissions From Fertilized Cropland at High-Resolution: Spatio-Temporal Patterns and Impacts

Abstract

Soil nitrogen oxides (NOx) emissions from agricultural areas currently dominate in some regions around the world. Since China is largely an agricultural country, an accurate estimation of soil NOx 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 NOx emission models, with a particular emphasis on crop phenological features and the impact of nitrogen fertilizer application on NOx at the grid level. As a result, a high-resolution emission inventory of soil NOx from agricultural areas in China is built. According to the emission inventory, total national NOx 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 NOx 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 NOx emissions, with soil NOx 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 NOx emissions, which suggests a potential NOx reduction strategy. We demonstrate that the established emission inventory can precisely reflect the distribution of soil NOx emissions in China's agricultural areas, which will be beneficial to overall NOx emission control and air quality improvement.