Temperature control on wastewater and downstream nitrous oxide emissions in an urbanized river system

Urbanization significantly increases greenhouse gas emissions from a subtropical headwater stream in Southeast China

Streams are disproportionately significant contributors to increases in greenhouse gas (GHG) effluxes in river networks. In the context of global urbanization, a growing number of streams are affected by urbanization, which has been suggested to stimulate the water-air GHG emissions from fluvial systems. This study investigated the seasonal and longitudinal profiles of GHG (N2O, CH4, and CO2) concentrations of Jiuxianghe Stream, a headwater stream undergoing urbanization, and estimated its GHG diffusive fluxes and global warming potentials (GWPs) using the boundary layer method. The results showed that N2O, CH4, and CO2 concentrations in Jiuxianghe Stream were 0.45-7.19 μg L-1, 0.31-586.85 μg L-1, and 0.16-11.60 mg L-1, respectively. N2O, CH4, and CO2 concentrations in the stream showed 4.55-, 23.70-, and 7.68-fold increases from headwaters to downstream, respectively, corresponding to the forest-urban transition within the watershed. Multiple linear regression indicated that NO3--N, NH4+-N, and DOC:NO3--N accurately predicted N2O and CO2 concentrations, indicating that N nutrients were the driving factors. The Jiuxianghe Stream was a source of atmospheric GHGs with a daily GWP of 7.31 g CO2-eq m-2 d-1 on average and was significantly positively correlated with the ratio of construction land and forest in the sub-watershed. This study highlights the critical role of urbanization in amplifying GHG emissions from streams, thereby augmenting our understanding of GHG emissions from river networks. With global urbanization on the rise, streams experiencing urbanization are expected to make an unprecedentedly significant contribution to riverine GHG budgets in the future.

Labile dissolved organic matter (DOM) and nitrogen inputs modified greenhouse gas dynamics: A source-to-estuary study of the Yangtze River

Although rivers are increasingly recognized as essential sources of greenhouse gases (GHG) to the atmosphere, few systematic efforts have been made to reveal the drivers of spatiotemporal variations of dissolved GHG (dGHG) in large rivers under increasing anthropogenic stress and intensified hydrological cycling. Here, through a source-to-estuary survey of the Yangtze River in March (spring) and October (autumn) of 2018, we revealed that labile dissolved organic matter (DOM) and nitrogen inputs remarkably modified the spatiotemporal distribution of dGHG. The average partial pressure of CO2 (pCO2), CH4 and N2O concentrations of all sampling sites in the Yangtze River were 1015 ± 225 μatm, and 87.5± 36.5 nmol L-1, and 20.3 ± 6.6 nmol L-1, respectively, significantly lower than the global average. In terms of longitudinal and seasonal variations, higher GHG concentrations were observed in the middle-lower reach in spring. The dominant drivers of spatiotemporal variations in dGHG were labile, protein-like DOM components and nitrogen level. Compared with the historical data of dGHG from published literature, we found a significant increase in N2O concentrations in the Yangtze River during 2004-2018, and the increasing trend was consistent with the rising riverine nitrogen concentrations. Our study emphasized the critical roles of labile DOM and nitrogen inputs in driving the spatial hotspots, seasonal variations and annual trends of dGHG. These findings can contribute to constraining the global GHG budget estimations and controls of GHG emission in large rivers in response to global change.

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.

Denitrification regulates spatiotemporal pattern of N2O emission in an interconnected urban river-lake network

Urban rivers are hotspots of N2O production and emission. Interconnected river-lake networks are constructed to improve the water quality and hydrodynamic conditions of urban rivers in many cities of China. However, the impact of the river-lake connectivity project on N2O production and emission remains unclear. This study investigated dissolved N2O and emission of the river-lake network in Wuhan City, China from March 2021 to December 2021. The results showed that river-lake connection greatly decreased riverine Nitrogen (N) concentration and increased dissolved oxygen (DO) concentration compare to traditional urban rivers. N2O emissions from the urban river interconnected with lakes (LUR: 67.3 ± 92.6 μmol/m2/d) were much lower than those from the traditional urban rivers (UR: 467.3 ± 1075.7 μmol/m2/d) and agricultural rivers (AR: 20.4 ± 15.3μmol/m2/d). Regression tree analysis suggested that the N2O concentrations were extremely high when hypoxia exists (DO < 1.6 mg/L), and TDN was the primary factor regulating N2O concentrations when hypoxia does not occur. Thus, we ascribe the low N2O emission in the LUR and AR to the lower N contents and higher DO concentrations. The microbial process of N2O production and consumption were quantitatively estimated by isotopic models. The mean proportion of denitrification derived N2O (fbD) was 63.5 %, 55.6 %, 42.3 % and 42.7 % in the UR, LUR, lakes and AR, suggested denitrification dominated N2O production in the urban rivers, but nitrification dominated N2O production in the lakes and AR. The positive correlation between logN2O and fbD suggested that denitrification is the key process to regulate the N2O production and emission. The abundance of denitrification genes (nirS and nirK) was much higher than that of nitrification genes (amoA and amoB), also evidenced that denitrification was the main N2O source. Therefore, river-lake interconnected projects changed the nutrients level and hypoxic condition, leading to the inhibition of denitrification and nitrification, and ultimately resulting in a decrease of N2O production and emission. These results advance the knowledge on the microbial processes that regulate N2O emissions in inland waters and illustrate the integrated management of water quality and N2O emission.

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

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.

Dissolved N2O concentrations in oil palm plantation drainage in a peat swamp of Malaysia

Oil palm plantations in Southeast Asia are the largest supplier of palm oil products and have been rapidly expanding in the last three decades even in peat-swamp areas. Oil palm plantations on peat ecosystems have a unique water management system that lowers the water table and, thus, may yield indirect N₂O emissions from the peat drainage system. We conducted two seasons of spatial monitoring for the dissolved N₂O concentrations in the drainage and adjacent rivers of palm oil plantations on peat swamps in Sarawak, Malaysia, to evaluate the magnitude of indirect N₂O emissions from this ecosystem. In both the dry and wet seasons, the mean and median dissolved N₂O concentrations exhibited over-saturation in the drainage water, i.e., the oil palm plantation drainage may be a source of N₂O to the atmosphere. In the wet season, the spatial distribution of dissolved N₂O showed bimodal peaks in both the unsaturated and over-saturated concentrations. The bulk δ¹⁵N of dissolved N₂O was higher than the source of inorganic N in the oil palm plantation (i.e., N fertilizer and soil organic nitrogen) during both seasons. An isotopocule analysis of the dissolved N₂O suggested that denitrification was a major source of N₂O, followed by N₂O reduction processes that occurred in the drainage water. The δ¹⁵N and site preference mapping analysis in dissolved N₂O revealed that a significant proportion of the N₂O produced in peat and drainage is reduced to N₂ before being released into the atmosphere.

Methane and nitrous oxide concentrations and fluxes from heavily polluted urban streams: Comprehensive influence of pollution and restoration

Streams draining urban areas are usually regarded as hotspots of methane (CH₄) and nitrous oxide (N₂O) emissions. However, little is known about the coupling effects of watershed pollution and restoration on CH₄ and N₂O emission dynamics in heavily polluted urban streams. This study investigated the CH₄ and N₂O concentrations and fluxes in six streams that used to be heavily polluted but have undergone different watershed restorations in Southwest China, to explore the comprehensive influences of pollution and restoration. CH₄ and N₂O concentrations in the six urban streams ranged from 0.12 to 21.32 μmol L^-1 and from 0.03 to 2.27 μmol L^-1, respectively. The calculated diffusive fluxes of CH₄ and N₂O were averaged of 7.65 ± 9.20 mmol m^-2 d^-1 and 0.73 ± 0.83 mmol m^-2 d^-1, much higher than those in most previous reports. The heavily polluted streams with non-restoration had 7.2 and 7.8 times CH₄ and N₂O concentrations higher than those in the fully restored streams, respectively. Particularly, CH₄ and N₂O fluxes in the fully restored streams were 90% less likely than those found in the unrestored ones. This result highlighted that heavily polluted urban streams with high pollution loadings were indeed hotspots of CH₄ and N₂O emissions throughout the year, while comprehensive restoration can effectively weaken their emission intensity. Sewage interception and nutrient removal, especially N loadings reduction, were effective measures for regulating the dynamics of CH₄ and N₂O emissions from the heavily polluted streams. Based on global and regional integration, it further elucidated that increasing environment investments could significantly improve water quality and mitigate CH₄ and N₂O emissions in polluted urban streams. Overall, our study emphasized that although urbanization could inevitably strengthen riverine CH₄ and N₂O emissions, effective eco-restoration can mitigate the crisis of riverine greenhouse gas emissions.

Low nitrous oxide concentration and spatial microbial community transition across an urban river affected by treated sewage

Urban rivers receive used water derived from anthropogenic activities and are a crucial source of the potent greenhouse gas nitrous oxide (N₂O). However, considerable uncertainties still exist regarding the variation and mechanisms of N₂O production in response to the discharge of treated sewage from municipal wastewater treatment plants (WWTPs). This study investigated N₂O concentrations and microbial processes responsible for nitrogen conversion upstream and downstream of WWTPs along the Tama River flowing through Tokyo, Japan. We evaluated the effect of treated sewage on dissolved N₂O concentrations and inherent N₂O consumption activities in the river sediments. In summer and winter, the mean dissolved N₂O concentrations were 0.67 µg-N L^-1 and 0.82 µg-N L^-1, respectively. Although the dissolved N₂O was supersaturated (mean 288.7% in summer, mean 240.7% in winter) in the river, the N₂O emission factors (EF_5r, 0.013%-0.025%) were significantly lower than those in other urban rivers and the Intergovernmental Panel on Climate Change default value (0.25%). The nitrate (NO₃^-) concentration in the Tama River increased downstream of the WWTPs discharge sites, and it was the main nitrogen constituent. An increasing trend of NO₃^- concentration was observed from upstream to downstream, along with an increase in the N₂O consumption potential of the river sediment. A multiple regression model showed that NO₃^- is the crucial factor influencing N₂O saturation. The diversity in the upstream microbial communities was greater than that in the downstream ones, indicating the involvement of treated sewage discharge in shaping the microbial communities. Functional gene quantification for N₂O production and consumption suggested that nirK-type denitrifiers likely contributed to N₂O production. Structural equation models (SEMs) revealed that treated sewage discharged from WWTPs increased the NO₃^- loading from upstream to downstream in the river, inducing changes in the microbial communities and enhancing the N₂O consumption activities. Collectively, aerobic conditions limited denitrification and in turn facilitated nitrification, leading to low N₂O emissions even despite high NO₃^- loadings in the Tama River. Our findings unravel an overestimation of the N₂O emission potential in an urban oxygen-rich river affected by treated sewage discharge.

Source tracking of dissolved organic nitrogen at the molecular level during storm events in an agricultural watershed

Accelerated export of nitrogen-containing dissolved organic matter (DOM) or dissolved organic nitrogen (DON) to streams and rivers from agricultural watersheds has been reported worldwide. However, few studies have examined the dynamics of DOM molecular composition with the attention paid to the relative contributions of DON from various sources altered with flow conditions. In this study, end-member mixing analysis (EMMA) was conducted with the optical properties of DOM to quantify the relative contributions of several major organic matter sources (litter, reed, field soil, and manure) in two rivers of a small agricultural watershed. DOC and DON concentration increased during the storm events with an input of allochthonous DOM as indicated by an increase in specific ultraviolet absorbance at 254 nm (SUVA₂₅₄) and a decrease in biological index (BIX), fluorescence index (FI), and protein-like component (%C3) at high discharge. EMMA results based on a Bayesian mixing model using stable isotope analysis in R (SIAR) were more accurate in source tracking than those using the traditional IsoSource program. Manure (>30%) and field soil (also termed as "manure-impacted field soil") (>23%) end-members revealed their predominant contributions to the riverine DOM in SIAR model, which was enhanced during the storm event (up to 56% and 38%, respectively). The molecular composition of the riverine DOM exhibited a distinct footprint from the manure and manure-impacted field soil, with a larger number of CHON formulas and abundant polyphenols and condensed aromatics in peak flow samples in the studied rivers. The riverine DOM during peak flow contained many unique molecular formulas in both rivers (4980 and 2082) of which >60% originated from manure and manure-impacted field soil. Combining the EMMA with DOM molecular composition clearly demonstrated the effect of manure fertilizer on the riverine DOM of the watershed with intensive agriculture. This study provides insights into the source tracking and regulation of DON leaching from anthropogenically altered river systems worldwide.

Temporal triggers of N2O emissions during cyclical and seasonal variations of a full-scale sequencing batch reactor treating municipal wastewater

To investigate the major triggers of nitrous oxide (N₂O) production in a full-scale wastewater treatment plant, N₂O emissions and wastewater characteristics (ammonia, nitrite, nitrate, total nitrogen, dissolved inorganic carbon, dissolved organic carbon, pH, temperature, dissolved oxygen and specific oxygen uptake rate), the results of variations in the cycling of a sequential batch reactor (SBR, where only full nitrification was performed), were monitored seasonally for 16 months. Major triggers of N₂O production were investigated based on a seasonal measured database using a random forest (RF) model and sensitivity analysis, which was applied to identify important input variables. As the result of seasonal monitoring in the full-scale SBR, the N₂O emission factor relative to daily total nitrogen removal ranged from 0.05 to 2.68%, corresponding to a range of N₂O production rate from 0.02 to 0.70 kg-N/day. Results from the RF model and sensitivity analysis revealed that emissions during nitrification were directly or indirectly related to nitrite accumulation, temperature, ammonia loading rate and the specific oxygen uptake rate ratio between ammonia oxidizing bacteria and nitrite oxidizing bacteria (sOUR-ratio). However, changes in the microbial community did not significantly impact N₂O emissions. Based on these results, the sOUR-ratio could represent the major trigger for N₂O emission in a full-scale BNR system: a higher sOUR-ratio value with an average of 3.13 ± 0.23 was linked to a higher N₂O production rate with an average value of 1.27 ± 0.12 kg-N/day (corresponding to 3.96 ± 1.20% of N₂O emission factor relative to daily TN removal), while a lower sOUR-ratio with an average value of 2.39 ± 0.27 was correlated with a lower N₂O production average rate of 0.17 ± 0.11 kg-N/day (corresponding to 0.74 ± 0.69% of N₂O emission factor) (p-value = 0.00001, Mann-Whitney test).

Integrated mechanistic and data-driven modeling for risk assessment of greenhouse gas production in an urbanized river system

Surrounded by intense anthropogenic activities, urban polluted rivers have increasingly been reported as a significant source of greenhouse gases (GHGs). However, unlike pollution and climate change, no integrated urban water models have investigated the GHG production in urban rivers due to system complexity. In this study, we proposed a novel integrated framework of mechanistic and data-driven models to qualitatively assess the risks of GHG accumulation in an urban river system in different water management interventions. Particularly, the mechanistic model delivered elaborated insights into river states in four intervention scenarios in which the installation of a new wastewater treatment plant using two different technologies, together with new sewage systems and additional retention tanks, were assessed during dry and rainy seasons. From the insights, we applied fuzzy rule-based models as a decision support tool to predict the GHG accumulation risks and identify their driving factors in the scenarios. The obtained results indicated the important role of new discharge connection and additional storage capacity in decreasing pollutant concentrations, consequently, reducing the risks. Moreover, among the major variables explaining the GHG accumulation in the rivers, DO level was considerably affected by the reaeration capacity of the rivers that was strongly dependent on river slope and flow. Furthermore, river water quality emerged as the most critical variable explaining the pCO₂ and N₂O accumulation that implied that the more polluted and anaerobic the sites were, the higher were their GHG accumulation. Given its simplicity and transparency, the proposed modeling framework can be applied to other river basins as a decision support tool in setting up integrated urban water management plans.