Unravelling spatiotemporal N2O dynamics in an urbanized estuary system using natural abundance isotopes

How do varying nitrogen fertilization rates affect crop yields and riverine N2O emissions? A hybrid modeling study

Headwater streams in agricultural areas constitute significant sources of nitrous oxide (N2O) due to nutrient enrichment; however, their emissions are often overlooked in current environmental impact assessments. This scarcity highlights the importance of developing advanced decision tools to evaluate these contributions and create effective mitigation strategies. Our study establishes the first integrated modeling framework that combines a process-based model SWAT+ with a linear mixed model (LMM) to predict N2O emissions from a headwater agricultural river system in Belgium under diverse climate change and fertilization scenarios. In particular, the calibrated and validated SWAT+ model was used to simulate streamflow, nutrient transport, and crop yields under these scenarios, from which, together with biochemical data collected from sampling campaigns, riverine N2O emissions were predicted via LMM. Our results revealed hydrologically driven patterns in riverine N2O emissions, with peak emissions in winter and spring, driven by precipitations enhancing shallow subsurface flows, carrying leached nutrients from fields to the river, and fueling N2O emissions. These phenomena were intensified under climate change scenarios, especially during combined wetter and hotter winters and springs, which elevated headwater N2O emissions by 40 %. Moreover, when coupling these conditions with a 20 % increase in fertilizer rates, riverine N2O emissions would be boosted by 83 %. These findings underscore the importance of integrating land-surface and river processes, to effectively quantify the feedback loop between river nutrient enrichment and climate change under the influence of agricultural practices, and to support comprehensive mitigation strategies under the warming climate.

Satellite-Based Estimation of Nitrous Oxide Concentration and Emission in a Large Estuary

Estuaries are nitrous oxide (N2O) emission hotspots and play an important role in the global N2O budget. However, the large spatiotemporal variability of emission in complex estuary environments is challenging for large-scale monitoring and budget quantification. This study retrieved water environmental variables associated with N2O cycling based on satellite imagery and developed a machine learning model for N2O concentration estimations. The model was adopted in China's Pearl River Estuary to assess spatiotemporal N2O dynamics as well as annual total diffusive emissions between 2003 and 2022. Results showed significant variability in spatiotemporal N2O concentrations and emissions. The annual total diffusive emission ranged from 0.76 to 1.09 Gg (0.95 Gg average) over the past two decades. Additionally, results showed significant seasonal variability with the highest contribution during spring (31 ± 3%) and lowest contribution during autumn (21 ± 1%). Meanwhile, emissions peaked at river outlets and decreased in an outward direction. Spatial hotspots contributed 43% of the total emission while covering 20% of the total area. Finally, SHapley Additive exPlanations (SHAP) was adopted, which showed that temperature and salinity, followed by dissolved inorganic nitrogen, were key input features influencing estuarine N2O estimations. This study demonstrates the potential of remote sensing for the estimation of estuarine emission estimations.

Regulating greenhouse gas dynamics in tidal wetlands: Impacts of salinity gradients and water pollution

Tidal wetlands play a critical role in emitting greenhouse gases (GHGs) into the atmosphere; our understanding of the intricate interplay between natural processes and human activities shaping their biogeochemistry and GHG emissions remains lacking. In this study, we delve into the spatiotemporal dynamics and key drivers of the GHG emissions from five tidal wetlands in the Scheldt Estuary by focusing on the interactive impacts of salinity and water pollution, two factors exhibiting contrasting gradients in this estuarine system: pollution escalates as salinity declines. Our findings reveal a marked escalation in GHG emissions when moving upstream, primarily attributed to increased concentrations of organic matter and nutrients, coupled with reduced levels of dissolved oxygen and pH. These low water quality conditions not only promote methanogenesis and denitrification to produce CH4 and N2O, respectively, but also shift the carbonate equilibria towards releasing more CO2. As a result, the most upstream freshwater wetland was the largest GHG emitter with a global warming potential around 35 to 70 times higher than the other wetlands. When moving seaward along a gradient of decreasing urbanization and increasing salinity, wetlands become less polluted and are characterized by lower concentrations of NO3-, TN and TOC, which induces stronger negative impact of elevated salinity on the GHG emissions from the saline wetlands. Consequently, these meso-to polyhaline wetlands released considerably smaller amounts of GHGs. These findings emphasize the importance of integrating management strategies, such as wetland restoration and pollution prevention, that address both natural salinity gradients and human-induced water pollution to effectively mitigate GHG emissions from tidal wetlands.

Seasonal isotopic and isotopomeric signatures of nitrous oxide produced microbially in a eutrophic estuary

Anthropogenic input of excess nutrients stimulates massive nitrous oxide (N2O) production in estuaries with distinct seasonal variations. Here, nitrogen isotopic and isotopomeric signatures were utilized to investigate the seasonal dynamics of N2O production and nitrification at the middle reach of the eutrophic Pearl River Estuary in the south of China. Elevated N2O production primarily via ammonia oxidation (> 1 nM-N d-1) occurred from April to November, along with increased temperature and decreased dissolved oxygen concentration. This consistently oxygenated water column showed active denitrification, contributing 20-40 % to N2O production. The water column microbial N2O production generally constituted a minor fraction (10-15 %) of the estuarine water-air interface efflux, suggesting that upstream transport and tidal dilution regulated the dissolved N2O inventory in the middle reach of the estuary. Nitrification (up to 3000 nM-N d-1) played a critical role in bioavailable nitrogen conversion and N2O production, albeit with N2O yields below 0.05 %.

Non-negligible N2O emission hotspots: Rivers impacted by ion-adsorption rare earth mining

Rare earth mining causes severe riverine nitrogen pollution, but its effect on nitrous oxide (N2O) emissions and the associated nitrogen transformation processes remain unclear. Here, we characterized N2O fluxes from China's largest ion-adsorption rare earth mining watershed and elucidated the mechanisms that drove N2O production and consumption using advanced isotope mapping and molecular biology techniques. Compared to the undisturbed river, the mining-affected river exhibited higher N2O fluxes (7.96 ± 10.18 mmol m-2d-1 vs. 2.88 ± 8.27 mmol m-2d-1, P = 0.002), confirming that mining-affected rivers are N2O emission hotspots. Flux variations scaled with high nitrogen supply (resulting from mining activities), and were mainly attributed to changes in water chemistry (i.e., pH, and metal concentrations), sediment property (i.e., particle size), and hydrogeomorphic factors (e.g., river order and slope). Coupled nitrification-denitrification and N2O reduction were the dominant processes controlling the N2O dynamics. Of these, the contribution of incomplete denitrification to N2O production was greater than that of nitrification, especially in the heavily mining-affected reaches. Co-occurrence network analysis identified Thiomonas and Rhodanobacter as the key genus closely associated with N2O production, suggesting their potential roles for denitrification. This is the first study to elucidate N2O emission and influential mechanisms in mining-affected rivers using combined isotopic and molecular techniques. The discovery of this study enhances our understanding of the distinctive processes driving N2O production and consumption in highly anthropogenically disturbed aquatic systems, and also provides the foundation for accurate assessment of N2O emissions from mining-affected rivers on regional and global scales.

Modeling greenhouse gas emissions from riverine systems: A review

Despite the recognized importance of flowing waters in global greenhouse gas (GHG) budgets, riverine GHG models remain oversimplified, consequently restraining the development of effective prediction for riverine GHG emissions feedbacks. Here we elucidate the state of the art of riverine GHG models by investigating 148 models from 122 papers published from 2010 to 2021. Our findings indicate that riverine GHG models have been mostly data-driven models (83%), while mechanistic and hybrid models were uncommonly applied (12% and 5%, respectively). Overall, riverine GHG models were mainly used to explain relationships between GHG emissions and biochemical factors, while the role of hydrological, geomorphic, land use and cover factors remains missing. The development of complex and advanced models has been limited by data scarcity issues; hence, efforts should focus on developing affordable automatic monitoring methods to improve data quality and quantity. For future research, we request for basin-scale studies explaining river and land-surface interactions for which hybrid models are recommended given their flexibility. Such a holistic understanding of GHG dynamics would facilitate scaling-up efforts, thereby reducing uncertainties in global GHG estimates. Lastly, we propose an application framework for model selection based on three main criteria, including model purpose, model scale and the spatiotemporal characteristics of GHG data, by which optimal models can be applied in various study conditions.