Estimating Yangtze River basin's riverine N2O emissions through hybrid modeling of land-river-atmosphere nitrogen flows.

Sun, H; Tian, Y; Zhan, W; Zhang, H; Meng, Y; Li, L; Zhou, X; Zuo, W; Ngo, HH

Estimating Yangtze River basin's riverine N2O emissions through hybrid modeling of land-river-atmosphere nitrogen flows.

Sun, H Tian, Y Zhan, W Zhang, H Meng, Y Li, L Zhou, X Zuo, W Ngo, HH

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Water Res, 2023, 247, pp. 120779
Issue Date:: 2023-12-01

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Field	Value	Language
dc.contributor.author	Sun, H
dc.contributor.author	Tian, Y
dc.contributor.author	Zhan, W
dc.contributor.author	Zhang, H
dc.contributor.author	Meng, Y
dc.contributor.author	Li, L
dc.contributor.author	Zhou, X
dc.contributor.author	Zuo, W
dc.contributor.author	Ngo, HH
dc.date.accessioned	2024-03-11T01:43:55Z
dc.date.available	2023-10-22
dc.date.available	2024-03-11T01:43:55Z
dc.date.issued	2023-12-01
dc.identifier.citation	Water Res, 2023, 247, pp. 120779
dc.identifier.issn	0043-1354
dc.identifier.issn	1879-2448
dc.identifier.uri	http://hdl.handle.net/10453/176435
dc.description.abstract	Riverine ecosystems are a significant source of nitrous oxide (N2O) worldwide, but how they respond to human and natural changes remains unknown. In this study, we developed a compound model chain that integrates mechanism-based modeling and machine learning to understand N2O transfer patterns within land, rivers, and the atmosphere. The findings reveal a decrease in N2O emissions in the Yangtze River basin from 4.7 Gg yr-1 in 2000 to 2.8 Gg yr-1 in 2019, with riverine emissions accounting for 0.28% of anthropogenic nitrogen discharges from land. This unexpected reduction is primarily attributed to improved water quality from human-driven nitrogen control, while natural factors contributed to a 0.23 Gg yr-1 increase. Notably, urban rivers exhibited a more rapid N2O efflux ( [Formula: see text] ), with upstream levels nearly 3.1 times higher than rural areas. We also observed nonlinear increases in [Formula: see text] with nitrogen discharge intensity, with urban areas showing a gradual and broader range of increase compared to rural areas, which exhibited a sharper but narrower increase. These nonlinearities imply that nitrogen control measures in urban areas lead to stable reductions in N2O emissions, while rural areas require innovative nitrogen source management solutions for greater benefits. Our assessment offers fresh insights into interpreting riverine N2O emissions and the potential for driving regionally differentiated emission reductions.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Elsevier
dc.relation.ispartof	Water Res
dc.relation.isbasedon	10.1016/j.watres.2023.120779
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Environmental Engineering
dc.subject.mesh	Humans
dc.subject.mesh	Nitrogen
dc.subject.mesh	Rivers
dc.subject.mesh	Ecosystem
dc.subject.mesh	Environmental Monitoring
dc.subject.mesh	Nitrous Oxide
dc.subject.mesh	Atmosphere
dc.subject.mesh	China
dc.subject.mesh	Humans
dc.subject.mesh	Nitrogen
dc.subject.mesh	Nitrous Oxide
dc.subject.mesh	Ecosystem
dc.subject.mesh	Atmosphere
dc.subject.mesh	Rivers
dc.subject.mesh	Environmental Monitoring
dc.subject.mesh	China
dc.subject.mesh	Humans
dc.subject.mesh	Nitrogen
dc.subject.mesh	Rivers
dc.subject.mesh	Ecosystem
dc.subject.mesh	Environmental Monitoring
dc.subject.mesh	Nitrous Oxide
dc.subject.mesh	Atmosphere
dc.subject.mesh	China
dc.title	Estimating Yangtze River basin's riverine N2O emissions through hybrid modeling of land-river-atmosphere nitrogen flows.
dc.type	Journal Article
utslib.citation.volume	247
utslib.location.activity	England
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	University of Technology Sydney/Strength - CTWW - Centre for Technology in Water and Wastewater Treatment
utslib.copyright.status	closed_access	*
dc.date.updated	2024-03-11T01:43:54Z
pubs.publication-status	Published
pubs.volume	247

Abstract:

Riverine ecosystems are a significant source of nitrous oxide (N2O) worldwide, but how they respond to human and natural changes remains unknown. In this study, we developed a compound model chain that integrates mechanism-based modeling and machine learning to understand N2O transfer patterns within land, rivers, and the atmosphere. The findings reveal a decrease in N2O emissions in the Yangtze River basin from 4.7 Gg yr-1 in 2000 to 2.8 Gg yr-1 in 2019, with riverine emissions accounting for 0.28% of anthropogenic nitrogen discharges from land. This unexpected reduction is primarily attributed to improved water quality from human-driven nitrogen control, while natural factors contributed to a 0.23 Gg yr-1 increase. Notably, urban rivers exhibited a more rapid N2O efflux ( [Formula: see text] ), with upstream levels nearly 3.1 times higher than rural areas. We also observed nonlinear increases in [Formula: see text] with nitrogen discharge intensity, with urban areas showing a gradual and broader range of increase compared to rural areas, which exhibited a sharper but narrower increase. These nonlinearities imply that nitrogen control measures in urban areas lead to stable reductions in N2O emissions, while rural areas require innovative nitrogen source management solutions for greater benefits. Our assessment offers fresh insights into interpreting riverine N2O emissions and the potential for driving regionally differentiated emission reductions.

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http://hdl.handle.net/10453/176435