Characteristics identification and mitigating potentials of provincial gaseous reactive nitrogen emissions from livestock and poultry breeding systems in China

The growth of population and changes in dietary structure have led to a continuous increase in demand for livestock and poultry products, resulting in the increase of the gaseous reactive nitrogen (GNr) emissions from livestock and poultry breeding systems and posing a threat to the human and ecosystem health. The characteristics from GNr emissions of six livestock and poultry breeding systems at the provincial level of China in 2020 were evaluated with the framework of life cycle analysis. Additionally, this study explored the impact of silage maize replacing traditional maize as feed on reducing GNr emissions. The GNr emissions from producing 1 ton of beef were the highest, approximately 9 times higher than those from producing 1 ton of milk. The GNr emissions for production of 1 ton of pork and egg were the biggest in Zhejiang. And the biggest emissions for 1 ton of beef, mutton, chicken and milk production were in Xizang, Shaanxi, Guangdong, and Guangxi, respectively. The total GNr emissions from pork production were highest. Compared with other stages, the stages of manure management and feed production contributed the majority of GNr emissions. Assuming that all the feed crops required for the production of livestock and poultry products in 2020 were locally grown, the total GNr emissions from the production of livestock and poultry products of China in 2020 were 6143.94 kt N, indicated that local emissions in China only accounted for 57.90%. Moreover, when the substitution rate of silage maize reached 100%, the GNr emissions from livestock and poultry breeding systems would be reduced by 10.05% (324.98 kt N). This study provided a detailed and spatial overview of the GNr emissions in livestock and poultry production in China, which could support reducing GNr emissions in livestock and poultry breeding systems for decision-makers and air pollution control.