Sino-France Institute of Earth Systems Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, People's Republic of China.
Agricultural Clean Watershed Research Group, Chinese Academy of Agricultural Sciences, Institute of Environment and Sustainable Development in Agriculture, Beijing, 100081, People's Republic of China.
Environ Sci Pollut Res Int. 2019 Mar;26(8):8136-8147. doi: 10.1007/s11356-019-04275-2. Epub 2019 Jan 28.
Current estimates of China's ammonia (NH) volatilization from paddy rice differ by more than twofold, mainly due to inappropriate application of chamber-based measurements and improper assumptions within process-based models. Here, we improved the Jayaweera-Mikkelsen (JM) model through multiplying the concentration of aqueous NH in ponded water by an activity coefficient that was determined based on high-frequency flux observations at Jingzhou station in Central China. We found that the improved JM model could reproduce the dynamics of observed NH flux (R = 0.83, n = 228, P < 0.001), while the original JM model without the consideration of activity of aqueous NH overstated NH flux by 54% during the periods of fertilization and pesticide application. The validity of the improved JM model was supported by a mass-balance-based indirect estimate at Jingzhou station and the independent flux observations from the other five stations across China. The NH volatilization losses that were further simulated by the improved JM model forced by actual wind speed were in general a half less than previous chamber-based estimates at six stations. Difference in wind speed between the inside and outside of the chamber and insufficient sampling frequency were identified as the primary and secondary causes for the overestimation in chamber-based estimations, respectively. Together, our findings suggest that an in-depth understanding of NH transfer process and its robust representation in models are critical for developing regional emission inventories and practical mitigation strategies of NH.
目前，中国稻田氨挥发的估计值差异超过两倍，主要是由于基于气室的测量方法应用不当和基于过程的模型中的假设不当。在这里，我们通过将池塘水中的水合氨浓度乘以根据中国中部荆州站高频通量观测确定的活度系数，对 Jayaweera-Mikkelsen (JM) 模型进行了改进。我们发现，改进后的 JM 模型可以再现观测到的 NH 通量的动态（R=0.83，n=228，P<0.001），而没有考虑水合 NH 活度的原始 JM 模型在施肥和施药期间高估了 NH 通量 54%。改进后的 JM 模型的有效性得到了基于质量平衡的荆州站间接估计和中国其他五个站点的独立通量观测的支持。由实际风速驱动的改进的 JM 模型进一步模拟的 NH 挥发损失通常比六个站点的六个基于气室的估计值少一半。气室内外风速的差异以及采样频率不足被确定为基于气室的估计值过高的主要和次要原因。总的来说，我们的研究结果表明，深入了解 NH 迁移过程及其在模型中的稳健表示对于开发区域排放清单和 NH 的实际缓解策略至关重要。
