Cropland fertilization is the largest anthropogenic source of nitrous oxide (N2O-N) emissions in China and could be mitigated through manure substitution. However, accurate quantification of N2O-N losses under different combinations of manure and chemical fertilizer applications remains challenging due to limited national data, oversimplified methods of estimation, and neglect of the nitrogen (N) source (chemical-N and manure-N) interaction effects under mixed fertilization on N2O-N production processes. Using a dataset consisting of 2186 observations across China, we developed N2O-N models for fertilized (chemical fertilizer and manures) croplands incorporating climate, soil, fertilization and cropping variables, with particular emphasis on the manure component, through machine-learning approaches. Model simulations estimated a median N2O-N flux of 1.1 kg ha-1 and a total national N2O-N loss of 243.7 Gg in 2019, with a hotspot in Northcentral China. During 2000-2019, N2O-N losses were driven mainly by annual total N input. By 2050, merely pursuing 100% manure recycling without considering improved manure-N use efficiency could lead to an 18% increase in N2O-N losses compared with 2019. Hence, this study provides a high-resolution modeling framework to predict how developments in manure substitution will affect the magnitude and spatial distribution of N2O-N losses. We also demonstrate that future manure substitution policies will need to promote improved manure nutrient management at the same time as greater manure recycling rates.
Ba et al. (Wed,) studied this question.