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[Estimation of Nitrous Oxide Emission from River System Based on Water Discharge and Dissolved Nitrous Oxide Concentration].

Authors :
Li BQ
Hu MP
Wang MF
Zhang YF
Wu H
Zhou J
Wu KB
Dai ZZ
Chen DJ
Source :
Huan jing ke xue= Huanjing kexue [Huan Jing Ke Xue] 2022 Jan 08; Vol. 43 (1), pp. 369-376.
Publication Year :
2022

Abstract

Due to increasing active nitrogen pollution loads, river systems have become an important source of nitrous oxide (N <subscript>2</subscript> O) in many areas. Due to the lack of monitoring data in many studies as well as the difficulty in estimating intermediate parameters and expressing temporal-spatial variability in current methods, a high level of uncertainty remains in the estimates of riverine N <subscript>2</subscript> O emission quantity. Based on the monthly monitoring efforts conducted for 10 sampling sites across the Yonganxi River system in Zhejiang Province from June 2016 to July 2019, the temporal and spatial dynamics of riverine N <subscript>2</subscript> O dissolved concentrations ρ (N <subscript>2</subscript> O), N <subscript>2</subscript> O fluxes, and their influencing factors were addressed. A multiple regression model was then developed for predicating riverine N <subscript>2</subscript> O emission flux to estimate annual N <subscript>2</subscript> O emission quantity for the entire river system. The results indicated that observed riverine ρ (N <subscript>2</subscript> O) (0.03-2.14 μg·L <superscript>-1</superscript> ) and the N <subscript>2</subscript> O fluxes[1.32-82.79 μg·(m <superscript>2</superscript> ·h) <superscript>-1</superscript> ] varied by 1-2 orders of magnitude of temporal-spatial variability. The temporal and spatial variability of ρ (N <subscript>2</subscript> O) were mainly influenced by the concentrations of nitrate, ammonia, and dissolved organic carbon, whereas the N <subscript>2</subscript> O emission fluxes were mainly affected by river water discharges and ρ (N <subscript>2</subscript> O). A multiple regression model that incorporates variables of river water discharge and ρ (N <subscript>2</subscript> O) could explain 90% of the variability in riverine N <subscript>2</subscript> O emission fluxes and has high accuracy. The model estimated N <subscript>2</subscript> O emission quantity from the entire Yonganxi River system of 3.67 t·a <superscript>-1</superscript> , with 29% from the main stream and 71% from the tributaries. The IPCC default emission factor method might greatly overestimate and underestimate N <subscript>2</subscript> O emission quantities for rivers impacted by low and high pressures of human activities, respectively. This study advances our quantitative understanding of N <subscript>2</subscript> O emission for the entire river system and provides a reference method for estimating riverine N <subscript>2</subscript> O emission with more accuracy.

Details

Language :
Chinese
ISSN :
0250-3301
Volume :
43
Issue :
1
Database :
MEDLINE
Journal :
Huan jing ke xue= Huanjing kexue
Publication Type :
Academic Journal
Accession number :
34989521
Full Text :
https://doi.org/10.13227/j.hjkx.202105005