中国农田氨非线性排放及其对肥料优化管理措施的响应

Ammonia (NH3) is a predominant alkaline gas in the atmosphere that contributes significantly to the formation of fine particles, water eutrophication, soil acidification, and the damage of human health. Cropland NH3 emissions is the main source for atmospheric NH3. China has become the largest cropland NH3 emitter due to the overuse of agricultural fertilizers. However, the spatial and temporal heterogeneities of cropland NH3 emissions caused by complex effects of anthropogenic (agricultural management practices) and natural (climate and soil properties) factors lead to large uncertainties in NH3 emission estimates. Meanwhile, our mechanistic understanding on how the variations in anthropogenic and natural factors drive the changes of China’s cropland NH3 emissions is hitherto very poor. In this proposed project, we will compile a national NH3 observation network and build a high resolution force dataset. The aim is three-fold: 1) to improve a nonlinear estimation model of cropland NH3 emissions for China, and to uncover the influence of nitrogen application rate, nitrogen placement and fertilizer type on cropland NH3 nonlinear emissions; 2) to identify hotspots of NH3 emissions during 1978-2017 and to reveal the driving mechanisms of observed inter-annual NH3 emission trends; and 3) to quantitatively evaluate the response of cropland NH3 emissions to knowledge-based agricultural fertilizer management practices. Results of this project will provide new understandings for NH3 emission estimates and inform cropland NH3 emission mitigation measures, and also offer scientific basis for policy-makers on more effective sustainable development strategies and air quality improvement approaches in China.

氨作为大气中重要碱性气体，对大气细颗粒形成、水体富营养化、土壤酸化和人体健康等都有重要影响。农田是氨第一大排放源。我国是农田氨年排放量最大的国家，其主要原因在于农田肥料的过量施用。农田氨排放时空差异大，人为（农田管理措施）和自然（气候、土壤属性）因素的综合影响复杂，导致估算存在较大不确定性。此外，人为和自然因素变化对中国农田氨排放趋势的驱动机制尚不清楚。本项目拟在汇编的中国农田氨观测网络数据集和建立的高分辨率模型驱动数据集基础上，1）改进中国农田氨非线性排放估算模型，揭示施氮量、施肥方式和肥料类型等因素对农田氨非线性排放的影响机理；2）识别1978~2017年中国农田氨排放热点和阐释年际排放趋势的驱动机制；3）定量评估农田氨排放对农田肥料优化管理措施的响应。本项目的研究结果可为农田氨排放的估算和减排提供新的思路，同时也可为我国决策者制定更有效的可持续发展策略和改善大气环境质量提供科学依据。

农田氨排放时空差异大，人为（农田管理措施）和自然（气候、土壤属性）因素的综合影响复杂。本项目在汇编的中国农田氨观测网络数据集和建立的高分辨率模型驱动数据集基础上，1）改进了中国农田氨排放估算模型，获得了2017年中国县域农田氨排放的时空分布；2）阐释了1978-2017年中国农田氨排放变化及驱动；3）揭示了有机和保护性农业对氨排放和作物生产力的协同影响机制；4）定量评估了农业环境因素和管理措施对氨排放和作物生产力的影响。本项目结果可为我国实现多个可持续发展目标、提高粮食安全和空气质量等提供数据驱动的路径和选择。在项目的支持下，发表SCI论文3篇（其中第一标注2篇），包括Nature Food，Environmental Science & Technology，Geophysical Research Letters杂志论文。