湿地
环境科学
反硝化
氮气
溶解有机碳
环境化学
水文学(农业)
生态系统
水生生态系统
植被(病理学)
一氧化二氮
化学
生态学
地质学
医学
病理
岩土工程
有机化学
生物
作者
Wangshou Zhang,Hengpeng Li,Steven G. Pueppke
标识
DOI:10.1016/j.scitotenv.2022.157538
摘要
Increasing levels of nitrogen (N) in aquatic ecosystems due to intensified human activities is focusing attention on N removal mechanisms as a means to mitigate environmental damage. Important N removal processes such as denitrification can resolve this issue by converting N to gaseous emissions. Here, the spatiotemporal variability of N removal rates in China's Zhongtian River, a headwater stream that contains wetlands, was investigated by quantifying gaseous emissions of the main end products, N2 and N2O, using the water-air exchange model. Excess concentrations of these gases relative to their saturations in the water column generally varied within 1.4-8.7 μmol L-1 and 8.7-20.3 nmol L-1, with mean values of 4.5 μmol L-1 and 13.7 nmol L-1, respectively, demonstrating significant N removal in the river. The reach with wetlands was characterized by higher in-stream N2 production than the non-wetland reach, especially in July, when aquatic vegetation is most abundant. High N2O emissions during the same period in the non-wetland reach indicate that environmental conditions associated with vegetation are conducive to N2 production and likely constrain N2O emission. Changes in dissolved oxygen, pH, temperature, and carbon to nitrogen ratios are correlated with the observed spatiotemporal variabilities in gaseous N production. The mean N removal rate in the wetland reach was roughly twice that in the non-wetland reach, i.e., 22.4 vs. 10.3 mmol N m-2 d-1, while the corresponding efficiency was about five times as high, i.e., 15 % vs. 3 %. This study reveals the spatiotemporal patterns of in-stream N removal in a headwater stream and highlights the efficacy of wetlands in N removal. The data provide a strong rationale for constructing artificial wetlands as a means to mitigate N pollution and thereby optimize riverine environmental conditions.
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