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Environmental drivers of nitrous oxide emission factor for a coastal reservoir and its catchment areas in southeastern China

Ping Yang, Liangjuan Luo, Kam Tang Orcid Logo, Derrick Y.F. Lai, Chuan Tong, Yan Hong, Linhai Zhang

Environmental Pollution, Volume: 294, Start page: 118568

Swansea University Author: Kam Tang Orcid Logo

  • Accepted Manuscript under embargo until: 24th November 2022

Abstract

Asia is projected to be a major contributor to nitrous oxide (N2O) emission in the coming decades, but assessment of N2O budget and distribution has been hampered by low data resolution and poorly constrained emission factor (EF). Urbanized coastal reservoirs receive high nitrogen loads from diverse...

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Published in: Environmental Pollution
ISSN: 0269-7491
Published: Elsevier BV 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa58721
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Abstract: Asia is projected to be a major contributor to nitrous oxide (N2O) emission in the coming decades, but assessment of N2O budget and distribution has been hampered by low data resolution and poorly constrained emission factor (EF). Urbanized coastal reservoirs receive high nitrogen loads from diverse sources across a heterogeneous landscape, and using a fixed EF may lead to large errors in N2O assessment. We conducted high spatial resolution sampling of dissolved N2O, nitrate-nitrogen (NO3––N) and related hydrographical parameters in Wenwusha Reservoir and its catchment areas (river, drainage channels, and aquaculture ponds) in southeastern China in November 2018, March 2019 and June 2019. The empirically derived EF (calculated as N2O-N:NO3--N) for the reservoir showed 10-fold spatial variations, ranging from 0.8×10-3 to 8.8×10-3. The average EF varied significantly among the four water types in the following descending order: aquaculture ponds > river > drainage channels > reservoir. Across all water types, EF of the summer month was 1.8–3.5 and 1.7–2.8 fold higher on average than that of autumn and spring, respectively. EF was higher in the summer likely due to elevated water temperature. Overall, the EF deviated considerably from the Intergovernmental Panel on Climate Change (IPCC) default value such that using the latter would result in over- or under-estimation of N2O emissions, sometimes by up to 42%. A new regression algorithm for EF based on water temperature, dissolved organic carbon and nitrate-nitrogen had a high and significant explanatory power (r2 = 0.82; p < 0.001), representing an improvement over the IPCC default EF for assessing N2O emission from coastal reservoirs and similar environments.
Keywords: N2O; Greenhouse gas; IPCC; Spatio-temporal variation; Nitrate-nitrogen; Inland waters
College: College of Science
Start Page: 118568