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全球河流一氧化二氮排放:小溪和大河的作用。

Global riverine nitrous oxide emissions: The role of small streams and large rivers.

机构信息

Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento 38123, Italy.

School of Forestry and Environmental Studies, Yale University, New Haven, CT 06520, USA; Center for Research Computing, Yale University, New Haven, CT 06520, USA.

出版信息

Sci Total Environ. 2021 Jul 1;776:145148. doi: 10.1016/j.scitotenv.2021.145148. Epub 2021 Feb 11.

DOI:10.1016/j.scitotenv.2021.145148
PMID:33647646
Abstract

Nitrous oxide, NO, is the leading cause of stratospheric ozone depletion and one of the most potent greenhouse gases (GHG). Its concentration in the atmosphere has been rapidly increasing since the green revolution in the 1950s and 1960s. Riverine systems have been suggested to be an important source of NO, although their quantitative contribution has been estimated with poor precision, ranging between 32.2 and 2100 GgNO - N/yr. Here, we quantify reach scale NO emissions by integrating a data-driven machine learning model with a physically-based upscaling model. The application of this hybrid modeling approach reveals that small streams (those with widths less than 10 m) are the primary sources of riverine NO emissions to the atmosphere. They contribute nearly 36 GgNO - N/yr; almost 50% of the entire NO emissions from riverine systems (72.8 GgO - N/yr), although they account for only 13% of the total riverine surface area worldwide. Large rivers (widths wider than 175 m), such as the main stems of the Amazon River (~ 6 GgNO - N/yr), the Mississippi River (~ 2 GgNO - N/yr), the Congo River (~ 1 GgNO - N/yr) and the Yang Tze River (~ 0.7 GgNO - N/yr), only contribute 26% of global NO emissions, which primarily originate from their water column. This study identifies, for the first time, near-global NO emission and NO removal hot spots within watersheds and thus can aid the development of local- to global-scale management and mitigation strategies for riverine systems with respect to NO emissions. The presented framework can be extended to quantified biogeochemical, besides NO emissions, processes at the global scale.

摘要

一氧化二氮(Nitrous oxide,NO)是平流层臭氧消耗的主要原因,也是最主要的温室气体(GHG)之一。自 20 世纪 50 年代和 60 年代的绿色革命以来,其在大气中的浓度迅速增加。尽管已经提出河川系统是一氧化二氮的一个重要来源,但它们的定量贡献估计精度较差,范围在 32.2 至 2100GgNO-N/yr 之间。在这里,我们通过整合数据驱动的机器学习模型和基于物理的扩展模型来量化流域尺度的一氧化二氮排放。这种混合建模方法的应用表明,小河流(宽度小于 10m 的河流)是河川一氧化二氮排放到大气中的主要来源。它们贡献了近 36GgNO-N/yr;占河川系统全部一氧化二氮排放量(72.8GgO-N/yr)的近 50%,尽管它们仅占全球河川总面积的 13%。大型河流(宽度大于 175m 的河流),如亚马逊河干流(6GgNO-N/yr)、密西西比河(2GgNO-N/yr)、刚果河(1GgNO-N/yr)和长江(0.7GgNO-N/yr),仅贡献了全球一氧化二氮排放量的 26%,主要来自它们的水柱。本研究首次在流域内确定了全球范围内的一氧化二氮排放和去除热点,从而有助于制定针对河川系统一氧化二氮排放的从局部到全球规模的管理和缓解策略。所提出的框架可以扩展到全球范围内量化除一氧化二氮排放以外的生物地球化学过程。

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