Eawag, Swiss Federal Institute of Aquatic Science and Technology, Ueberlandstrasse 133, CH-8600 Duebendorf, Switzerland.
Eawag, Swiss Federal Institute of Aquatic Science and Technology, Ueberlandstrasse 133, CH-8600 Duebendorf, Switzerland; Department of Environmental Sciences, University of Basel, Petersplatz 1, CH-4003 Basel, Switzerland.
Sci Total Environ. 2016 Dec 1;572:526-537. doi: 10.1016/j.scitotenv.2016.08.093. Epub 2016 Aug 24.
Agricultural application of reactive nitrogen (N) for fertilization is a cause of massive negative environmental problems on a global scale. However, spatially explicit and crop-specific information on global N losses into the environment and knowledge of trade-offs between N losses and crop yields are largely lacking. We use a crop growth model, Python-based Environmental Policy Integrated Climate (PEPIC), to determine global N losses from three major food crops: maize, rice, and wheat. Simulated total N losses into the environment (including water and atmosphere) are 44TgNyr. Two thirds of these, or 29TgNyr, are losses to water alone. Rice accounts for the highest N losses, followed by wheat and maize. The N loss intensity (NLI), defined as N losses per unit of yield, is used to address trade-offs between N losses and crop yields. The NLI presents high variation among different countries, indicating diverse N losses to produce the same amount of yields. Simulations of mitigation scenarios indicate that redistributing global N inputs and improving N management could significantly abate N losses and at the same time even increase yields without any additional total N inputs.
农业应用活性氮（N）施肥是全球范围内产生大量负面环境问题的一个原因。然而，对于全球环境中 N 损失的空间具体和作物特异性信息以及 N 损失和作物产量之间的权衡关系的了解还很缺乏。我们使用作物生长模型，基于 Python 的环境政策综合气候模型（PEPIC），来确定三种主要粮食作物：玉米、水稻和小麦的全球 N 损失。模拟的环境中总 N 损失（包括水和大气）为 44TgNyr。其中三分之二，即 29TgNyr，仅损失到水中。水稻造成的 N 损失最高，其次是小麦和玉米。氮损失强度（NLI）定义为单位产量的 N 损失，用于解决 N 损失和作物产量之间的权衡关系。不同国家之间的 NLI 差异很大，表明生产相同产量的 N 损失也不同。缓解情景的模拟表明，重新分配全球 N 投入和改善 N 管理可以显著减少 N 损失，同时甚至在不增加总 N 投入的情况下增加产量。
