Effects of anthropogenic nitrogen discharge on dissolved inorganic nitrogen transport in global rivers

Identifying groundwater ammonium hotspots in riverside aquifer of Central Yangtze River Basin

Elevated ammonium (NH4-N) contents in groundwater are a global concern, yet the mobilization and enrichment mechanisms controlling NH4-N within riverside aquifers (RAS) remain poorly understood. RAS are important zones for nitrogen cycling and play a vital role in regulating groundwater NH4-N contents. This study conducted an integrated assessment of a hydrochemistry dataset using a combination of hydrochemical analyses and multivariate geostatistical methods to identify hydrochemical compositions and NH4-N distribution in the riverside aquifer within Central Yangtze River Basin, ultimately elucidating potential NH4-N sources and factors controlling NH4-N enrichment in groundwater ammonium hotspots. Compared to rivers, these hotspots exhibited extremely high levels of NH4-N (5.26 mg/L on average), which were mainly geogenic in origin. The results indicated that N-containing organic matter (OM) mineralization, strong reducing condition in groundwater and release of exchangeable NH4-N in sediment are main factors controlling these high concentrations of NH4-N. The Eh representing redox state was the dominant variable affecting NH4-N contents (50.17 % feature importance), with Fe2+ and dissolved organic carbon (DOC) representing OM mineralization as secondary but important variables (26 % and 5.11 % feature importance, respectively). This study proposes a possible causative mechanism for the formation of these groundwater ammonium hotspots in RAS. Larger NH4-N sources through OM mineralization and greater NH4-N storage under strong reducing condition collectively drive NH4-N enrichment in the riverside aquifer. The evolution of depositional environment driven by palaeoclimate and the unique local environment within the RAS likely play vital roles in this process.

Rising CO2 and land use change amplify the increase in terrestrial and riverine export of dissolved organic carbon over the past four decades

The lateral transport of dissolved organic carbon (DOC) from land to rivers and oceans is a significant but overlooked component of the global carbon cycle. However, there are still large uncertainties in the magnitude and trend of global DOC export fluxes, as well as their response to environmental change. In this study, several simulations were conducted using a developed land surface model that considered riverine DOC transport and anthropogenic disturbance to investigate the terrestrial DOC loading and riverine DOC export, and to quantify the relative contributions of natural and anthropogenic factors over the past four decades (1981-2016). These factors include climate change, nitrogen deposition, land use change, atmospheric CO2 concentration, anthropogenic water regulation, and fertilizer and manure application. Results showed that the average global annual terrestrial DOC loading was about 432.30 ± 53.59 Tg C yr-1, and rivers exported about 209.73 ± 36.58 Tg C yr-1 to oceans over the past four decades. Simultaneously, a significant increase in terrestrial DOC loading and riverine DOC export fluxes (3.36 Tg C yr-2 and 2.99 Tg Cyr-2, p < 0.01) was found, which increased by 26.88 % and 47.02 %, respectively. According to our factorial analysis, the interannual variability in DOC fluxes in most regions was mainly attributed to climate change and contributed more than 60 % of the long-term increase. In addition, rising atmospheric CO2 and land use change amplified the increase in terrestrial DOC loading, with the area dominated by the two factors expanding from 7.94 % in the 1980s to 23.84 % in the 2010s, and riverine DOC export showed a similar pattern, which may be related to the increased soil DOC sources. Anthropogenic water regulation and nitrogen addition have led to a slight increase in DOC fluxes, which should not be ignored, otherwise carbon fluxes may be underestimated.

Drought reduces nitrogen supply and N2O emission in coastal bays

Severe droughts are increasingly prevalent under global climate change, disrupting watershed hydrology and coastal nitrogen cycling. However, the specific effects of drought on nitrogen transport from land to sea and subsequent nitrogen dynamics remain inadequately understood. In this study, we evaluated the consequences of the 2020-2022 drought on nitrogen supply and N2O emissions in Xiamen Bay, Southeast China. The results showed that drought significantly reduced annual NH4N, NO2N, and NO3N concentrations in Xiamen Bay by 49.4 %, 32.1 %, and 40.3 %, respectively, compared with the pre-drought year of 2019. The decline in NH4N concentration was mainly attributed to reduced surface runoff across all seasons. NO3N and NO2N concentrations declined only during spring and summer, primarily due to increased potential evapotranspiration (PET) hindering nitrogen supply via groundwater and concurrently enhancing land denitrification. Annual N2O emission from Xiamen Bay decreased by 40.0∼72.7 % during the drought, highly correlated with the decline in the concentrations of NO3N, DIN, and DTN (p < 0.001). Comparative analysis revealed that NO3N concentration exhibited consistent negative linear regressions with PET and declined as evaporative demand drought conditions worsened across Xiamen Bay, Sansha Bay, and Chesapeake Bay throughout 2010-2022. NH4N concentration showed a positive regression with river discharge in Xiamen Bay, but negative regressions in the other two bays. Our results indicates that drought reduces N2O emission primarily driven by nitrate substrate reduction in the bay. This study provides new insights for predicting coastal nitrogen dynamics and greenhouse gas emissions under global environmental change.

Spatial-temporal change of river thermal environment and anthropogenic impact in China

River water temperature is important and closely related to river ecosystem, concerning fishery industry, human health, and the land-sea exchange of nutrients, especially for great powers with a good deal of heat emission from once-through cooling systems of thermal power plants. However, the changes in river water temperature under the joint action of climate change and human activity such as the heat emission have not been well investigated for rising powers, hampering environmental policy making for sustainable development. Therefore, we have taken advantage of a recently-developed land surface model including river water temperature calculation with anthropogenic thermal discharge and zonal statistics to quantitatively make out the river water temperature variation and the man-made influence over the past thirty years (1981-2010) in China for the first time. Results show that the estimated water temperature in major rivers is generally close to the observation with the r2 of 0.83, though the underestimation exists in some rivers. The river water in the Pearl River Basin was the warmest with the mean temperature of 19.2 °C and the others in order were in the Southeast Basin, the Huaihe River Basin, the Yangtze River Basin, the Haihe River Basin, the Yellow River Basin, the Southwest Basin, the Song-Liao River Basin, and the Continental Basin, ranging from 16.7 °C to 6.3 °C. The Huaihe River Basin had the fastest mean increase rate of ca. 0.27 °C decade-1, while the slowest mean increase rate of ca. 0.13 °C decade-1 existed in the Pearl River Basin. At the subbasin scale, a meridionally-distributed hot spot zone (along the 115°E) of the increasing water temperature has been identified, where the trends ranged from 0.2 °C decade-1 to 0.5 °C decade-1. Air temperature exerted a major control on the spatial pattern of climatological water temperature, while both air temperature and downwelling solar flux played a leading role in the distribution of water temperature change trends. Although anthropogenic thermal emission heated the rivers locally, the impacts in the Song-Liao River, the Haihe River, the Huaihe River, and the middle and lower reaches of Yellow River and Yangtze River had been raised up to ca. 4.5 °C, when comparing with those controlled by climate change only. In general, these results show an acceptable level of river water temperature simulation in the land surface model, and could provide a scientific reference for the assessment on riverine thermal environment under the climate change and social impact in China.

Systematic tracking of nitrogen sources in complex river catchments: Machine learning approach based on microbial metagenomics

Tracking nitrogen pollution sources is crucial for the effective management of water quality; however, it is a challenging task due to the complex contaminative scenarios in the freshwater systems. The contaminative pattern variations can induce quick responses of aquatic microorganisms, making them sensitive indicators of pollution origins. In this study, the soil and water assessment tool, accompanied by a detailed pollution source database, was used to detect the main nitrogen pollution sources in each sub-basin of the Liuyang River watershed. Thus, each sub-basin was assigned to a known class according to SWAT outputs, including point source pollution-dominated area, crop cultivation pollution-dominated area, and the septic tank pollution-dominated area. Based on these outputs, the random forest (RF) model was developed to predict the main pollution sources from different river ecosystems using a series of input variable groups (e.g., natural macroscopic characteristics, river physicochemical properties, 16S rRNA microbial taxonomic composition, microbial metagenomic data containing taxonomic and functional information, and their combination). The accuracy and the Kappa coefficient were used as the performance metrics for the RF model. Compared with the prediction performance among all the input variable groups, the prediction performance of the RF model was significantly improved using metagenomic indices as inputs. Among the metagenomic data-based models, the combination of the taxonomic information with functional information of all the species achieved the highest accuracy (0.84) and increased median Kappa coefficient (0.70). Feature importance analysis was used to identify key features that could serve as indicators for sudden pollution accidents and contribute to the overall function of the river system. The bacteria Rhabdochromatium marinum, Frankia, Actinomycetia, and Competibacteraceae were the most important species, whose mean decrease Gini indices were 0.0023, 0.0021, 0.0019, and 0.0018, respectively, although their relative abundances ranged only from 0.0004 to 0.1 %. Among the top 30 important variables, functional variables constituted more than half, demonstrating the remarkable variation in the microbial functions among sites with distinct pollution sources and the key role of functionality in predicting pollution sources. Many functional indicators related to the metabolism of Mycobacterium tuberculosis, such as K24693, K25621, K16048, and K14952, emerged as significant important factors in distinguishing nitrogen pollution origins. With the shortage of pollution source data in developing regions, this suggested approach offers an economical, quick, and accurate solution to locate the origins of water nitrogen pollution using the metagenomic data of microbial communities.

Elucidating the links between N2O dynamics and changes in microbial communities following saltwater intrusions

Saltwater intrusion in estuarine ecosystems alters microbial communities as well as biogeochemical cycling processes and has become a worldwide problem. However, the impact of salinity intrusion on the dynamics of nitrous oxide (N2O) and associated microbial community are understudied. Here, we conducted field microcosms in a tidal estuary during different months (December, April and August) using dialysis bags, and microbes inside the bags encountered a change in salinity in natural setting. We then compared N2O dynamics in the microcosms with that in natural water. Regardless of incubation environment, saltwater intrusion altered the dissolved N2O depending on the initial saturation rates of N2O. While the impact of saltwater intrusion on N2O dynamics was consistent across months, the dissolved N2O was higher in summer than in winter. The N-related microbial communities following saltwater intrusion were dominated by denitrifers, with fewer nitrifiers and bacterial taxa involved in dissimilatory nitrate reduction to ammonium. While denitrification was a significant driver of N2O dynamics in the studied estuary, nitrifier-involved denitrification contributed to the additional production of N2O, evidenced by the strong associations with amoA genes and the abundance of Nitrospira. Higher N2O concentrations in the field microcosms than in natural water limited N2O consumption in the former, given the lack of an association with nosZ gene abundance. The differences in the N2O dynamics observed between the microcosms and natural water could be that the latter comprised not only indigenous microbes but also those accompanied with saltwater intrusion, and that immigrants might be functionally rich individuals and able to perform N transformation in multiple pathways. Our work provides the first quantitative assessment of in situ N2O concentrations in an estuary subjected to a saltwater intrusion. The results highlight the importance of ecosystem size and microbial connectivity in the source-sink dynamics of N2O in changing environments.

A triple increase in global river basins with water scarcity due to future pollution

Water security is at stake today. While climate changes influence water availability, urbanization and agricultural activities have led to increasing water demand as well as pollution, limiting safe water use. We conducted a global assessment of future clean-water scarcity for 2050s by adding the water pollution aspect to the classical water quantity-induced scarcity assessments. This was done for >10,000 sub-basins focusing on nitrogen pollution in rivers by integrating land-system, hydrological and water quality models. We found that water pollution aggravates water scarcity in >2000 sub-basins worldwide. The number of sub-basins with water scarcity triples due to future nitrogen pollution worldwide. In 2010, 984 sub-basins are classified as water scarce when considering only quantity-induced scarcity, while 2517 sub-basins are affected by quantity & quality-induced scarcity. This number even increases to 3061 sub-basins in the worst case scenario in 2050. This aggravation means an extra 40 million km2 of basin area and 3 billion more people that may potentially face water scarcity in 2050. Our results stress the urgent need to address water quality in future water management policies for the Sustainable Development Goals.

Spatiotemporal estimation of nutrient data from the northwest pacific and east asian seas

Nutrient data obtained from field observations have the potential to enhance our understanding of oceanic biogeochemical cycling and productivity changes. In particular, long-term nutrient data can provide valuable information on the links between climate change and biogeochemical changes. However, unlike other observational variables such as sea surface temperature, nutrient data are limited in terms of their broad-scale observations and automated sensor-based measurements. In this study, we analyzed nitrate and phosphate data obtained from coastal regions in Northeast Asia and the northwest Pacific from 1980 to 2019 using the spatiotemporal kriging technique and provide results in a spatiotemporal grid format. The data are available at monthly intervals and may be attractive to researchers in the fields of oceanography, marine ecology, and marine biogeochemistry at the climate change scale. Furthermore, sharing the source code of the data production process can contribute to better long-term data reproduction in the future.

Nitrogen in the Yangtze River Basin: Pollution Reduction through Coupling Crop and Livestock Production

Livestock production poses a threat to water quality worldwide. A better understanding of the contribution of individual livestock species to nitrogen (N) pollution in rivers is essential to improve water quality. This paper aims to quantify inputs of dissolved inorganic nitrogen (DIN) to the Yangtze River from different livestock species at multiple scales and explore ways for reducing these inputs through coupling crop and livestock production. We extended the previously developed model MARINA (Model to Assess River Input of Nutrient to seAs) with the NUFER (Nutrient flows in Food chains, Environment, and Resource use) approach for livestock. Results show that DIN inputs to the Yangtze River vary across basins, sub-basins, and 0.5° grids, as well as across livestock species. In 2012, livestock production resulted in 2000 Gg of DIN inputs to the Yangtze River. Pig production was responsible for 55-85% of manure-related DIN inputs. Rivers in the downstream sub-basin received higher manure-related DIN inputs than rivers in the other sub-basins. Around 20% of the Yangtze basin is considered as a manure-related hotspot of river pollution. Recycling manure on cropland can avoid direct discharges of manure from pig production and thus reduce river pollution. The potential for recycling manure is larger in cereal production than in other crop species. Our results can help to identify effective solutions for coupling crop and livestock production in the Yangtze basin.

Spatial heterogeneity of chemistry of the Small Aral Sea and the Syr Darya River and its impact on plankton communities

The shrinking of the Aral Sea represents one of the greatest ecological disasters of modern time. The data on the surviving northern part (Small Aral) is scarce and requires an update. This study aimed to analyze the chemistry, phyto- and zooplankton composition, and their relation in the waters of the Small Aral and its tributary, Syr Darya River. The chemistry of both ecosystems was significantly different. Small Aral was characterized by higher ionic concentrations, salinity, and electric conductivity and more significant spatial variation of chemical properties. The area near the river mouth was more pristine, while the ions concentration and salinity in the distant bays were much higher (>10‰). The highest concentrations of nitrates and total phosphorus in the Syr Darya were observed near Kyzylorda, indicating urban pollution. Overall, 109 phytoplankton taxa were identified in both ecosystems, with diatoms, green algae, and cyanobacteria being most abundantly represented. Oligohalobes dominated, but no polyhalobes and euhalobes algal species were identified. In total, 27 taxa of zooplankton were identified in both studied ecosystems, with the domination of rotifers over microcrustaceans. An exceptionally high level of dominance (65-91%) of rotifer Keratella cochlearis in the Syr Darya was found. The phyto- and zooplankton species richness was higher in the Syr Darya. Plankton communities of the Small Aral reflected horizontal variability of chemical properties. The total phosphorus promoted the prevalence of diatoms, rotifers, and crustaceans. Increased nitrogen concentration promoted cyanobacteria, chlorophytes, cryptophytes and chrysophytes, and rotifers Keratella cochlearis and K. quadrata. The abundance of dinophytes, diatoms Navicula cryptotenella and Cocconeis placentula, green algae Mychonastes jurisii and rotifer Keratella tecta was driven by the higher alkalinity and conductivity/salinity levels. The results represent a reference point for future monitoring of the area and add to understanding the complexity of biological transformations in the Aral Sea and its tributary.

Agricultural impacts drive longitudinal variations of riverine water quality of the Aral Sea basin (Amu Darya and Syr Darya Rivers), Central Asia

River ecosystems are under increasing stress in the background of global change and ever-growing anthropogenic impacts in Central Asia. However, available water quality data in this region are insufficient for a reliable assessment of the current status, which come as no surprise that the limited knowledge of regulating processes for further prediction of solute variations hinders the development of sustainable management strategies. Here, we analyzed a dataset of various water quality variables from two sampling campaigns in 2019 in the catchments of two major rivers in Central Asia-the Amu Darya and Syr Darya Rivers. Our results suggested high spatial heterogeneity of salinity and major ion components along the longitudinal directions in both river catchments, pointing to an increasing influence of human activities toward downstream areas. We linked the modeling outputs from the global nutrient model (IMAGE-GNM) to riverine nutrients to elucidate the effect of different natural and anthropogenic sources in dictating the longitudinal variations of the riverine nutrient concentrations (N and P). Diffuse nutrient loadings dominated the export flux into the rivers, whereas leaching and surface runoff constituted the major fractions for N and P, respectively. Discharge of agricultural irrigation water into the rivers was the major cause of the increases in nutrients and salinity. Given that the conditions in Central Asia are highly susceptible to climate change, our findings call for more efforts to establish holistic management of water quality.

Place attachment, environmental cognition and organic fertilizer adoption of farmers: evidence from rural China

For preventing the excessive consumption of agricultural resources, it is of vital importance to promote agricultural pro-environmental behavior of farmers. Despite the proven importance of psychological factors in encouraging farmers' adoption of organic fertilizer, the evidence is scarce. To fill this gap, this study aims to explore how place attachment and environmental cognition affect farmers' organic fertilizer adoption with a community sample of 944 rural farmers collected in Hubei province. Specifically, we firstly distinguish two dimensions of place attachment, namely, natural attachment and civic attachment, and then we explore the influence of those dimensions and environmental cognition on farmers' adoption of organic fertilizer. The results reveal that both place attachment and environmental cognition positively affect farmers' organic fertilizer adoption. Furthermore, the roles of place attachment vary across different groups divided by farmers' environmental cognition degree and age. Therefore, to promote green agricultural practices, policy-makers should enhance various farmers' place attachment and environmental cognition by strengthening infrastructure construction, organizing collective activities, and conducting animation propaganda.

Land use and episodic rainfall as drivers of nitrogen exports in subtropical rivers: Insights from δ15N-NO3-, δ18O-NO3- and 222Rn

Ongoing land-use intensification in subtropical catchments is expected to release more inorganic nitrogen to downstream coastal waters similar to historical changes in temperate ecosystems. Here, we examined spatial and temporal drivers of stream nitrogen loads across a subtropical land-use gradient using the isotopic compositions of nitrate (NO₃^--N) and radon (²²²Rn), a natural groundwater tracer. We investigated eleven subtropical creeks/rivers over contrasting hydrological conditions in Australia. NO_x-N (nitrite (NO₂^--N) + nitrate (NO₃^--N)) accounted for 13.1%, 34.0%, and 42.6% of total dissolved nitrogen (TDN-N) in forest, peri-urban and agricultural creeks, respectively. Following an 80 mm rain event, loads of dissolved inorganic nitrogen (DIN-N) from agriculture catchments reached 368 mg N m^-2 catchment area day^-1. Forest and peri-urban catchments had aquatic TDN-N loads 17.8% and 31.1% of loads from agricultural catchments. Radon observations suggest that nitrogen and phosphorus loads were driven primarily by surface runoff rather than groundwater discharge. The δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- values in the agriculture, forest and peri-urban catchments indicate fertilisers and soil nitrogen as the main sources of NO₃^--N. However, one of the catchments (Double Crossing Creek) received a mixture of recirculated greywater and chemical nitrogen fertilisers. Isotopic signatures imply significant NO₃^--N losses via denitrification during dry conditions. Groundwater discharge played a minor role because regional aquifers were not contaminated by nitrogen. Overall, intensive agricultural land use and episodic rainfall events were the major spatial and temporal drivers of nitrogen loads.

Photocatalytic activity of new nanostructures of an Ag(i) metal–organic framework (Ag-MOF) for the efficient degradation of MCPA and 2,4-D herbicides under sunlight irradiation

A new Ag(i) metal–organic framework (Ag-MOF) [Ag(p-OH-C₆H₄COOH)₂(NO₃)]_n [Ag(PHBA)₂(NO₃)]_n, (1) (PHBA: C₈H₆O₄ {p-hydroxybenzoic acid}) was synthesized using two different methods; the laying method (single crystal) and sonochemical irradiation (nanostructures).

Modeling the Contribution of Crops to Nitrogen Pollution in the Yangtze River

Agriculture contributes considerably to nitrogen (N) inputs to the world's rivers. In this study, we aim to improve our understanding of the contribution of different crops to N inputs to rivers. To this end, we developed a new model system by linking the MARINA 2.0 (Model to Assess River Input of Nutrient to seAs) and WOFOST (WOrld FOod STudy) models. We applied this linked model system to the Yangtze as an illustrative example. The N inputs to crops in the Yangtze River basin showed large spatial variability. Our results indicate that approximately 6,000 Gg of N entered all rivers of the Yangtze basin from crop production as dissolved inorganic N (DIN) in 2012. Half of this amount is from the production of single rice, wheat, and vegetables, where synthetic fertilizers were largely applied. In general, animal manure contributes 12% to total DIN inputs to rivers. Three-quarters of manure-related DIN in rivers are from vegetable, fruit, and potato production. The contributions of crops to river pollution differ among sub-basins. For example, potato is an important source of DIN in rivers of some upstream sub-basins. Our results may help to prioritize the dominant crop sources for management to mitigate N pollution in the future.

Identification of quantitative trait loci associated with nitrogen use efficiency in winter wheat

Maintaining winter wheat (Triticum aestivum L.) productivity with more efficient nitrogen (N) management will enable growers to increase profitability and reduce the negative environmental impacts associated with nitrogen loss. Wheat breeders would therefore benefit greatly from the identification and application of genetic markers associated with nitrogen use efficiency (NUE). To investigate the genetics underlying N response, two bi-parental mapping populations were developed and grown in four site-seasons under low and high N rates. The populations were derived from a cross between previously identified high NUE parents (VA05W-151 and VA09W-52) and a shared common low NUE parent, ‘Yorktown.’ The Yorktown × VA05W-151 population was comprised of 136 recombinant inbred lines while the Yorktown × VA09W-52 population was comprised of 138 doubled haploids. Phenotypic data was collected on parental lines and their progeny for 11 N-related traits and genotypes were sequenced using a genotyping-by-sequencing platform to detect more than 3,100 high quality single nucleotide polymorphisms in each population. A total of 130 quantitative trait loci (QTL) were detected on 20 chromosomes, six of which were associated with NUE and N-related traits in multiple testing environments. Two of the six QTL for NUE were associated with known photoperiod (Ppd-D1 on chromosome 2D) and disease resistance (FHB-4A) genes, two were reported in previous investigations, and one QTL, QNue.151-1D, was novel. The NUE QTL on 1D, 6A, 7A, and 7D had LOD scores ranging from 2.63 to 8.33 and explained up to 18.1% of the phenotypic variation. The QTL identified in this study have potential for marker-assisted breeding for NUE traits in soft red winter wheat.

Long-Term Changes in Precipitation and Temperature Have Already Impacted Nitrogen Loading

Increases in nitrogen loading over the past several decades have led to widespread water quality impairments across the U.S. Elevated awareness of the influence of climate variability on nitrogen loading has led to several studies investigating future climate change impacts on water quality. However,  it remains unclear whether long-term climate impacts can already be observed in the historical record. Here, we quantify long-term trends in total nitrogen loading over the period 1987-2012 across the contiguous U.S. and attribute these trends to long-term changes in nitrogen inputs and climatic variables. We find that annual precipitation, extreme springtime precipitation, and springtime temperature are key drivers of trends in historical loading in most regions. These decadal climate trends have either  amplified or offset loading trends expected from nitrogen inputs alone. We also find that rising temperatures have been insufficient to offset precipitation-induced loading increases, suggesting that future increases in temperature under climate change may have limited potential to counteract loading increases expected as a result of anticipated changes in precipitation. This work demonstrates the important role of decadal climate variability in long-term nitrogen loading, emphasizing the need to consider climate change risks when designing and monitoring nutrient reduction programs.