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Updated: Jul 2, 2025

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
Published on: January 7, 2019
Labile dissolved organic matter (DOM) and nitrogen inputs modified greenhouse gas dynamics: A source-to-estuary study
Jiarui Li1, Enhang Liang1, Chunfang Deng1
1College of Environmental Sciences and Engineering, Key Laboratory of Water and Sediment Sciences, Ministry of Education, Peking University, Beijing 100871, PR China; State Environmental Protection Key Laboratory of All Materials Flux in River Ecosystems, Beijing 100871, PR China.
Abstract:
Although rivers are increasingly recognized as essential sources of greenhouse gases (GHG) to the atmosphere, few systematic efforts have been made to reveal the drivers of spatiotemporal variations of dissolved GHG (dGHG) in large rivers under increasing anthropogenic stress and intensified hydrological cycling. Here, through a source-to-estuary survey of the Yangtze River in March (spring) and October (autumn) of 2018, we revealed that labile dissolved organic matter (DOM) and nitrogen inputs remarkably modified the spatiotemporal distribution of dGHG. The average partial pressure of CO2 (pCO2), CH4 and N2O concentrations of all sampling sites in the Yangtze River were 1015 ± 225 μatm, and 87.5± 36.5 nmol L-1, and 20.3 ± 6.6 nmol L-1, respectively, significantly lower than the global average. In terms of longitudinal and seasonal variations, higher GHG concentrations were observed in the middle-lower reach in spring. The dominant drivers of spatiotemporal variations in dGHG were labile, protein-like DOM components and nitrogen level. Compared with the historical data of dGHG from published literature, we found a significant increase in N2O concentrations in the Yangtze River during 2004-2018, and the increasing trend was consistent with the rising riverine nitrogen concentrations. Our study emphasized the critical roles of labile DOM and nitrogen inputs in driving the spatial hotspots, seasonal variations and annual trends of dGHG. These findings can contribute to constraining the global GHG budget estimations and controls of GHG emission in large rivers in response to global change.
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