| 李晓寒,严星,夏永秋,颜晓元.气体扩散系数法估算水体反硝化速率[J].农业环境科学学报,2023,42(5):1109-1115. |
| 气体扩散系数法估算水体反硝化速率 |
| Estimating the denitrification rate of water bodies by gas diffusion coefficient method |
| 投稿时间：2022-08-02 |
| DOI：10.11654/jaes.2022-0785 |
| 中文关键词: 反硝化速率 气体扩散系数法 密闭培养法 米氏方程 敏感性分析 |
| 英文关键词: denitrification rate gas diffusion coefficient method MIMS-based method Michaelis-Menten equation sensitivity analysis |
| 基金项目:内蒙古自治区科技重大专项（NMKJXM202009）；国家自然科学基金项目（U19A2050，42177401） |
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| 中文摘要: |
| 近年来基于经验系数或者机理过程的气体扩散系数法逐渐被应用于水体反硝化速率的估算，为了探究该方法的可靠性、适用性和不确定性，本研究在不同硝态氮浓度（0、1、2、4、6 mg·L-1，以N计）静态水体条件下比较了密闭培养法和气体扩散系数法。结果表明： BO04、CL07和Xia21 3种气体扩散系数模型估算的反硝化速率与水体硝态氮浓度的关系均符合米氏方程（R2=0.994 6，P<0.01）。3种扩散系数法与密闭培养法测定的水体反硝化速率之间均有显著的线性关系（R2=0.776 7，P<0.05），但斜率各不相同，其中CL07和Xia21模型的估算结果均与密闭培养法的测定结果较为接近，斜率分别为1.22和0.59。进一步应用蒙特卡洛分析法对CL07模型进行参数敏感性分析发现，风速、流速和水温是模型最为敏感的3个因子，其无偏百分比差异分别为12.13%、9.49%和9.42%。研究表明，气体扩散系数法可以较准确地估算水体反硝化速率，为大尺度原位开展水体反硝化估算和氮素循环提供方法基础，但是需要根据实地环境条件选择和标定模型。 |
| 英文摘要: |
| Although the gas diffusion coefficient method based on the empirical coefficient or mechanism process has been developed for simple and accurate denitrification estimation in recent years, little is known about its reliability, applicability, and uncertainty. In this study, a membrane inlet mass spectrometer(MIMS) -based method and the gas-diffusion coefficient method were compared in static water bodies under different nitrate concentrations(0, 1, 2, 4 mg · L-1, and 6 mg · L-1, calculated by N). Results showed that the relationship between nitrate concentration and denitrification rates estimated by the three gas diffusion coefficient methods(BO04, CL07 and Xia21 models) followed the Michaelis-Menten equation(R2=0.994 6, P<0.01). There was a significant linear relationship between the denitrification rates estimated by the three gas diffusion coefficient methods and the MIMS-based method(R2=0.776 7, P<0.05), although with a different slope. Among the three gas diffusion coefficient methods, the CL07 and Xia21 models were more reliable according to the slopes of the measurements from the MIMS-based method, with slopes of 1.22 and 0.59, respectively. Taking the CL07 model as an example, Monte Carlo analysis revealed that wind speed, water flow velocity, and water temperature were the three most sensitive factors, with unbiased percent difference(UPD) of 12.13%, 9.49%, and 9.42%, respectively. In conclusion, this study shows that the gas diffusion coefficient method can accurately estimate the denitrification rate of water bodies, providing a methodological basis for large-scale in-situ denitrification estimation and nitrogen cycling studies. We also emphasize the necessity of selecting and calibrating the gas diffusion coefficient model based on local environmental conditions. |
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