While Asia is projected to be one of the major nitrous oxide (N2O) sources in the coming decades, a more accurate assessment of N2O budget has been hampered by low data resolution and poorly constrained emission factor (EF). Since urbanized coastal reservoirs receive high nitrogen loads from diverse sources across a heterogeneous landscape, the use of a single fixed EF may lead to large errors in N2O assessment. In this study, we conducted high spatial resolution sampling of dissolved N2O, nitrate-nitrogen (NO3--N) and other physico-chemical properties of surface water in Wenwusha Reservoir and other types of water bodies (river, drainage channels, and aquaculture ponds) in its catchment areas in southeastern China between November 2018 and June 2019. The empirically derived EF (calculated as N2O-N:NO3--N) for the reservoir showed considerable spatial variations, with a 10-fold difference ranging from 0.8 × 10-3 to 8.8 × 10-3. The average EF varied significantly among the four types of water bodies in the following descending order: aquaculture ponds > river > drainage channels > reservoir. Across all the water bodies, the mean EF in summer was 1.8-3.5 and 1.7-2.8 fold higher than that in autumn and spring, respectively, owing to the elevated water temperature. Overall, our derived EF deviated considerably from the IPCC default value, which implied that the use of default EF could result in over- or under-estimation of N2O emissions by up to 42%. We developed a multiple regression model that could explain 82% of the variance in EF based on water temperature and the ratio between dissolved organic carbon and nitrate-nitrogen (p < 0.001), which could be used to improve the estimate of EF for assessing N2O emission from coastal reservoirs and other similar environments.
Keywords: Greenhouse gas; IPCC; Inland waters; N(2)O; Nitrate-nitrogen; Spatio-temporal variation.
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