Societal decisions about climate mitigation will have dramatic impacts on eutrophication in the 21st century

Spatio-temporal evolution mechanism and dynamic simulation of nitrogen and phosphorus pollution of the Yangtze River economic Belt in China

Excess nitrogen and phosphorus inputs are the main causes of aquatic environmental deterioration. Accurately quantifying and dynamically assessing the regional nitrogen and phosphorus pollution emission (NPPE) loads and influencing factors is crucial for local authorities to implement and formulate refined pollution reduction management strategies. In this study, we constructed a methodological framework for evaluating the spatio-temporal evolution mechanism and dynamic simulation of NPPE. We investigated the spatio-temporal evolution mechanism and influencing factors of NPPE in the Yangtze River Economic Belt (YREB) of China through the pollution load accounting model, spatial correlation analysis model, geographical detector model, back propagation neural network model, and trend analysis model. The results show that the NPPE inputs in the YREB exhibit a general trend of first rising and then falling, with uneven development among various cities in each province. Nonpoint sources are the largest source of land-based NPPE. Overall, positive spatial clustering of NPPE is observed in the cities of the YREB, and there is a certain enhancement in clustering. The GDP of the primary industry and cultivated area are important human activity factors affecting the spatial distribution of NPPE, with economic factors exerting the greatest influence on the NPPE. In the future, the change in NPPE in the YREB at the provincial level is slight, while the nitrogen pollution emissions at the municipal level will develop towards a polarization trend. Most cities in the middle and lower reaches of the YREB in 2035 will exhibit medium to high emissions. This study provides a scientific basis for the control of regional NPPE, and it is necessary to strengthen cooperation and coordination among cities in the future, jointly improve the nitrogen and phosphorus pollution tracing and control management system, and achieve regional sustainable development.

Uncovering the spatial characteristics of global net anthropogenic nitrogen input at high resolution and across 1.42 million lake basins

Global Net Anthropogenic Nitrogen Input (NANI) at high resolution is crucial for assessing the impact of human activities on aquatic environments. Insufficient global high-resolution data sources and methods have hindered the effective examination of the global characteristics and driving forces of NANI. This study presents a general framework for calculating global NANI, providing estimates at a 5-arc-minute resolution and over 1.42 million lake basins in 2015. The results highlight the region near the Tropic of Cancer as a concentration area for high NANI and an inflection point for latitude-based accumulation variation. It also emphasizes the uneven distribution of NANI among continents, with Asia and Africa having the highest proportions, yet their high and low values are notably lower than those of Europe and South America. A similar pattern is observed in global lakes, where Asia has the smallest quantity and volume, but the highest NANI intensity. In contrast, North America and Europe have larger quantities and volumes but the lowest NANI intensity. The global distribution characteristics reveal a clustering pattern in high and low values, with 1.25 % of the area having a sum of NANI exceeding 20 %. The uncertainty analysis regarding model parameters indicates that continents with the highest NANI do not always exhibit the highest uncertainty. These results bridge the gap between global nitrogen sustainable management and anthropogenic nitrogen input. They support research on spatiotemporal changes and controlling factors of global river nutrient loads, as well as the impact of climatic factors on basin nitrogen loss and its variability.

Uneven consequences of global climate mitigation pathways on regional water quality in the 21st century

Future socioeconomic climate pathways have regional water-quality consequences whose severity and equity have not yet been fully understood across geographic and economic spectra. We use a process-based, terrestrial-freshwater ecosystem model to project 21st-century river nitrogen loads under these pathways. We find that fertilizer usage is the primary determinant of future river nitrogen loads, changing precipitation and warming have limited impacts, and CO2 fertilization-induced vegetation growth enhancement leads to modest load reductions. Fertilizer applications to produce bioenergy in climate mitigation scenarios cause larger load increases than in the highest emission scenario. Loads generally increase in low-income regions, yet remain stable or decrease in high-income regions where agricultural advances, low food and feed production and waste, and/or well-enforced air pollution policies balance biofuel-associated fertilizer burdens. Consideration of biofuel production options with low fertilizer demand and rapid transfer of agricultural advances from high- to low-income regions may help avoid inequitable water-quality outcomes from climate mitigation.

Mitigating nitrogen losses with almost no crop yield penalty during extremely wet years

Climate change-induced precipitation anomalies during extremely wet years (EWYs) result in substantial nitrogen losses to aquatic ecosystems (Nw). Still, the extent and drivers of these losses, and effective mitigation strategies have remained unclear. By integrating global datasets with well-established crop modeling and machine learning techniques, we reveal notable increases in Nw, ranging from 22 to 56%, during historical EWYs. These pulses are projected to amplify under the SSP126 (SSP370) scenario to 29 to 80% (61 to 120%) due to the projected increases in EWYs and higher nitrogen input. We identify the relative precipitation difference between two consecutive years (diffPr) as the primary driver of extreme Nw. This finding forms the basis of the CLimate Extreme Adaptive Nitrogen Strategy (CLEANS), which scales down nitrogen input adaptively to diffPr, leading to a substantial reduction in extreme Nw with nearly zero yield penalty. Our results have important implications for global environmental sustainability and while safeguarding food security.

Thirty years of experience in water pollution control in Taihu Lake: A review

Taihu Lake has suffered from eutrophication and algal blooms for decades, primarily due to increasing anthropogenic pollutants from human activities. Extensive research and widespread implementation of water pollution control measures have significantly contributed to the improvement of water quality of Taihu Lake. However, the relevant experience of Taihu Lake pollution control has not been well summarized to provide insight for future lake restoration. This review article seeks to address this gap by first providing a comprehensive overview of Taihu Lake's water quality dynamics over the past thirty years, characterized by two distinct stages: (I) water quality deterioration (1990s-2007); and (II) water total nitrogen (TN) improvement but total phosphorus (TP) fluctuation (2007-current). Subsequently, we conducted a thorough review of the experiences and challenges associated with water pollution control during these two stages. Generally, pollution control practices emphasized point source control but overlooked non-point sources before 2007, possibly due to point sources being easier to identify and manage. Accordingly, the focus shifted from industrial point sources to a combination of industrial point and agricultural non-point sources after 2007 to control water pollution in the Taihu Lake Basin. Numerous studies have delved into non-point source pollution control, including source control, transport intercept, in-lake measures, and the integration of these technologies. Taken together, this paper provides suggestions based on the needs and opportunities of this region. Further research is needed to better understand and model the underlying pollution processes, as well as to increase public participation and improve policy and law implementation, which will assist decision-makers in formulating better water management in Taihu Lake.

A bioenergy-focused versus a reforestation-focused mitigation pathway yields disparate carbon storage and climate responses

Limiting global warming to 2 °C requires urgent action on land-based mitigation. This study evaluates the biogeochemical and biogeophysical implications of two alternative land-based mitigation scenarios that aim to achieve the same radiative forcing. One scenario is primarily driven by bioenergy expansion (SSP226Lu-BIOCROP), while the other involves re/afforestation (SSP126Lu-REFOREST). We find that overall, SSP126Lu-REFOREST is a more efficient strategy for removing CO2 from the atmosphere by 2100, resulting in a net carbon sink of 242 ~ 483 PgC with smaller uncertainties compared to SSP226Lu-BIOCROP, which exhibits a wider range of -78 ~ 621 PgC. However, SSP126Lu-REFOREST leads to a relatively warmer planetary climate than SSP226Lu-BIOCROP, and this relative warming can be intensified in certain re/afforested regions where local climates are not favorable for tree growth. Despite the cooling effect on a global scale, SSP226Lu-BIOCROP reshuffles regional warming hotspots, amplifying summer temperatures in vulnerable tropical regions such as Central Africa and Southeast Asia. Our findings highlight the need for strategic land use planning to identify suitable regions for re/afforestation and bioenergy expansion, thereby improving the likelihood of achieving the intended climate mitigation outcomes.

Crop production and water quality under 1.5 °C and 2 °C warming: Plant responses and management options in the mid-Atlantic region

The 2015 "Paris Agreement" aims to limit the global average temperature rise to significantly less than 2 °C, preferably within 1.5 °C above pre-industrial levels. A multitude of studies have focused on evaluating how different sectors respond to such levels of warming. Nonetheless, most of these studies fail to provide a clear roadmap to mitigate these impacts. A case in point is the anticipated decline in corn and soybean yields and increased phosphorus (P) and nitrogen (N) discharge into water bodies, a trend linked to past agricultural practices and climate change. In this research, we employ a novel assessment of how existing management practices under 1.5 °C and 2 °C global warming (GW) scenarios can affect nutrient availability in time and space as well as crop yield in a typical agricultural watershed in the Mid-Atlantic Region, specifically the Upper Maurice River Watershed (UMRW) in New Jersey. Using the Soil and Water Assessment Tool (SWAT) with multiple Global Climate Model (GCM) projections, we found that compared to 1.5 °C, a 2 °C GW scenario would exacerbate runoff, leading to amplified nutrient leaching. These losses decrease nutrient availability during the crop growing season. Moreover, a mismatch between the timing of fertilizer application and crop nutrient absorption caused nutrient-related stress. This nutrient and anticipated temperature stress resulted in a more significant decrease in crop yields under the 2 °C GW scenario than the 1.5 °C scenario. We have designed a management scenario to reduce future nutrient losses while increasing crop yields. The strategy involves altering the timing of planting/harvesting and the fertilizer application rate in response to a warming climate. This approach is projected to increase corn and soybean yields by +39 % (+21 %) and +2 % (+17 %), respectively, under the 1.5 °C (2.0 °C) GW scenario for the RCP-4.5 pathway. Simultaneously, it is expected to decrease the N and P loads at 1.5 °C (2.0 °C) GW. Comparable projections are also observed under the RCP-8.5 pathway.

Effect of climate change on the water quality of Mediterranean rivers and alternatives to improve its status

Surface water (SW) quality is particularly vulnerable to increased concentrations of nutrients, and this issue may be exacerbated by climate change. Knowledge of the effects of temperature and rainfall on SW quality is required to take the necessary measures to achieve good SW status in the future. To address this, the aims of this study were threefold: (1) to assess how a changing climate may alter the nitrate, ammonium, phosphorus and biological oxygen demand status (BOD5) of SW; (2) assess the relationship between water quality and flow; and (3) simulate diffuse and point source pollution reduction scenarios in the Júcar River Basin District in the Mediterranean region. A regionalised long-term climate scenario was used following one Representative Concentration Pathway (RCP8.5) with the data incorporated into the coupling of hydrological and water quality models. According to these climate change scenarios, SW with poor nitrate, ammonium, phosphorus and BOD5 status are expected to increase in the future by factors of 1.3, 1.9, 4 and 4, respectively. Furthermore, median ammonium and phosphorus concentration may be doubled in months with low flows. Additional measures are required to maintain current status in the water bodies, and it is necessary to reduce at least 25% of diffuse nitrate pollution, and 50% of point loads of ammonium, phosphorus, and BOD5.

Multi-scenario simulation of runoff and nutrient loads in a rapidly urbanizing watershed during China's Dual Carbon periods

Apprehending the hydrological and nutrient variations in rapidly urbanizing watersheds under changing environments is crucial for pollution control and water resource management. However, existing studies have primarily focused on hydrological processes, neglecting water quality aspects, and comprehensive assessment of future runoff and nutrient loads in these watersheds during China's Dual Carbon periods is limited. This study firstly bridges these gaps by constructing multi-scenario with different levels of "Urban Development - Ecological Conservation" and utilizing latest bias-corrected General Circulation Models or Global Climate Models (GCMs) projections to evaluate future runoff and nutrient loads in the Shenzhen River. The calibrated and validated models display satisfactory performance in simulating runoff, nutrient loads, and land use types. The bias-corrected GCMs projections exhibit enhanced accuracy for temperature variables, particularly during the wet season. Implementing effective ecological protection measures is paramount in mitigating water quantity fluctuations and controlling total nitrogen pollution, which is closely associated with urban development and human activities. Conversely, total phosphorus loads demonstrate greater simulation uncertainty, particularly during the dry season of the Carbon Neutrality period, requiring further exploration. Compared to the baseline period, runoff changes minimally, with notable seasonal variations. The findings highlight the escalating uncertainty in load predictions as time progresses. Additionally, addressing uncertainties in precipitation projections driven by GCMs is imperative, given their substantial influence on runoff and nutrient load simulations, particularly during challenging dry seasons. While further research is needed to reduce simulation uncertainty, our study provides valuable insights into nitrogen-phosphorus pollution control and sustainable water resource management in rapidly urbanizing watersheds, especially during the near-term period.

Warming may offset impact of precipitation changes on riverine nitrogen loading

Climate change, especially in the form of precipitation and temperature changes, can alter the transformation and delivery of nitrogen on the land surface and to aquatic systems, impacting the trophic states of downstream water bodies. While the expected impacts of changes in precipitation have been explored, a quantitative understanding of the impact of temperature on nitrogen loading is lacking at landscape scales. Here, using several decades of nitrogen loading observations, we quantify how individual and combined future changes in precipitation and temperature will affect riverine nitrogen loading. We find that, contrary to recent decades, rising temperatures are likely to offset or even reverse previously reported impacts of future increases in total and extreme precipitation on nitrogen runoff across the majority of the contiguous United States. These findings highlight the multifaceted impacts of climate change on the global nitrogen cycle.

Dynamic spatiotemporal change of net anthropogenic phosphorus inputs and its response of water quality in the Liao river basin

The Liao river is one of the seven major rivers in China, and the process of phosphorus (P) cycling and change of water quality in this basin are influenced to a considerable extent human activities. In this work, the traditional net anthropogenic phosphorus inputs (NAPI) model was improved by considering the dynamic change of wastewater treatment capacity and P deposition (PDEP) and reclassifying the sources of phosphorus into human P consumption (PHUM), agriculture P consumption (PAGR), livestock P consumption (PANIM) and PDEP to analyze its dynamic spatio-temporal change in the Liao river basin. The results showed that the annual mean NAPI was 785.53 kg P km^-2 yr^-1 (2001-2020), the maximum value was 940.49 kg P km^-2 yr^-1 in 2009, and the minimum value was 586.04 kg P km^-2 yr^-1 in 2001. The temporal variation of NAPI presented an increasing-fluctuation-increasing trend and was basically in line with that of the water quality throughout the three stages, and the spatial distribution of NAPI gradually increased from upstream to downstream. During the two decades, PANIM was the predominant component of NAPI with a share of 64.32%. PHUM, PAGR, and PDEP accounted for 15.97%, 11.54%, and 8.17%, respectively, and the point source NAPI (NAPIP) contributed to 4.95% of NAPI. Further, the INAPI (Improved NAPI) -MR (Multiple Regression) -SWAT (Soil and Water Assessment Tool) model was developed to predict the spatial distribution of P flux under two scenarios. The results showed that the Liao river basin experienced a reduction in P flux to different degrees due to the improvement of the wastewater treatment system, which was more significant in its downstream area. Long-term water quality monitoring is encouraged to develop refined water quality models in the future.

A raster-based estimation of watershed phosphorus load and its impacts on surrounding rivers based on process-based modelling

Quantifying phosphorus (P) load from watersheds at a fine scale is crucial for studying P sources in lake or river ecosystems; however, it is particularly challenging for mountain-lowland mixed watersheds. To address this challenge, we proposed a framework to estimate the P load at the grid scale and assessed its risk to surrounding rivers in a typical mountain-lowland mixed watershed (Huxi Region in Lake Taihu Basin, China). The framework coupled three models: the Phosphorus Dynamic model for lowland Polder systems (PDP), the Soil and Water Assessment Tool (SWAT), and the Export Coefficient Model (ECM). The coupled model performed satisfactory for both hydrological and water quality variables (Nash-Sutcliffe efficiency >0.5). Our modelling practice revealed that polder, non-polder, and mountainous areas had P load of 211.4, 437.2, and 149.9 t yr^-1, respectively. P load intensity in lowlands and mountains was 1.75 and 0.60 kg ha^-1 yr^-1, respectively. A higher P load intensity (>3 kg ha^-1 yr^-1) was mainly observed in the non-polder area. In lowland areas, irrigated cropland, aquaculture ponds and impervious surfaces contributed 36.7%, 24.8%, and 25.8% of the P load, respectively. In mountainous areas, irrigated croplands, aquaculture ponds, and impervious surfaces contributed 28.6%, 27.0%, and 16.4% of the P load, respectively. Rivers with relatively high P load risks were mainly observed around big cities during rice season, owing to a large contribution of P load from the non-point source pollution of urban and agricultural activities. This study demonstrated a raster-based estimation of watershed P load and their impacts on surrounding rivers using coupled process-based models. It would be useful to identify the hotspots and hot moments of P load at the grid scale.

A novel framework to improve the consistency of water quality attribution from natural and anthropogenic factors

One critical question for water security and sustainable development is how water quality responses to the changes in natural factors and human activities, especially in light of the expected exacerbation in water scarcity. Although machine learning models have shown noticeable advances in water quality attribution analysis, they have limited interpretability in explaining the feature importance with theoretical guarantees of consistency. To fill this gap, this study built a modelling framework that employed the inverse distance weighting method and the extreme gradient boosting model to simulate the water quality at grid scale, and adapted the Shapley additive explanation to interpret the contributions of the drivers to water quality over the Yangtze River basin. Different from previous studies, we calculated the contribution of features to water quality at each grid within river basin and aggregated the contribution from all the grids as the feature importance. Our analysis revealed dramatic changes in response magnitudes of water quality to drivers within river basin. Air temperature had high importance in the variability of key water quality indicators (i.e. ammonia-nitrogen, total phosphorus, and chemical oxygen demand), and dominated the changes of water quality in Yangtze River basin, especially in the upstream region. In the mid- and downstream regions, water quality was mainly affected by human activities. This study provided a modelling framework applicable to robustly identify the feature importance by explaining the contribution of features to water quality at each grid.

Attribution and driving force of nitrogen losses from the Taihu Lake Basin by the InVEST and GeoDetector models

Quantifying temporal and spatial changes in reactive nitrogen (Nr) losses from a watershed and exploring its main drivers are the key to watershed water quality improvements. Huge Nr losses continue to threaten the safety of the water environment in the Taihu Lake Basin (TLB). Here, the InVEST and GeoDetector models were combined to estimate Nr losses in the TLB from 1990 to 2020 and explore driving forces. Different scenarios for Nr losses were compared, showing that Nr loss peaked at 181.66 × 10³ t in 2000. The key factors affecting Nr loss are land use, followed by elevation, soil, and slope factors, and their mean q-values were 0.82, 0.52, 0.51, and 0.48, respectively. The scenario analysis revealed that Nr losses increased under the business-as-usual and economic development scenarios, while ecological conservation, increased nutrient use efficiency, and reduced nutrient application all contribute to a reduction in Nr losses. The findings provide a scientific reference for Nr loss control and future planning in the TLB.

Identification of nitrate sources of groundwater and rivers in complex urban environments based on isotopic and hydro-chemical evidence

Groundwater and rivers in Chinese cities suffer from severe nitrate pollution. The accurate identification of nitrate sources throughout aquatic systems is key to the water nitrate pollution management. This study investigated nitrogen components of groundwater for twelve years and analyzed the sources of nitrate in the aquatic system based on dual isotopes (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-) in the city of Nanjing, a core city of the Yangtze River Delta region, China. Our results showed that the ratio of nitrate to the sum of ammonia and nitrate in groundwater show an increasing trend during 2010-2021. The nitrate concentration was positively correlated with the proportion of cultivated land and negatively correlated with the proportion of forest land in the buffer zone. The relationship between Cl^- and NO₃^-/ Cl^- showed that agriculture and sewage sources increased during 2010-2015, sewage sources increased during 2016-2018, agriculture sources increased during 2019-2021. Manure and sewage were the primary sources of groundwater nitrate (72 %). There was no significant difference between the developed land (78 %), cultivated land (69 %), and aquaculture area (72 %). This indicates that dense population and intensive aquaculture in the suburbs have a significant impact on nitrate pollution. The contributions of manure and sewage to the fluvial nitrate sources in the lower reaches of the Qinhuai River Basin were 61 %. The non-point sources, including groundwater N (39 %) and soil N (35 %), were 74 % over the upper reaches. This study highlights the necessity of developing different N pollution management strategies for different parts of highly urbanized watersheds and considers groundwater restoration and soil nitrogen management as momentous, long-term tasks.

Spatiotemporal differences in riverine nitrogen and phosphorus fluxes and associated drivers across China from 1980 to 2018

Increases in nutrient loadings to waterways over the past four decades have led to widespread eutrophication and water quality impairments across China. Understanding the spatial, interannual and long-term variations in nutrient loadings and associated drivers at the national scale is crucial for developing effective nutrient reduction strategies. However, the controls on, and spatiotemporal variations in, nutrient fluxes remain a problem from both an academic and management perspective. This study provides spatially extensive and temporally contiguous estimates of changes in riverine total nitrogen (TN), ammonia nitrogen (NH₃-N) and total phosphorus (TP) fluxes for continental area of China based on machine learning stack models and empirical modeling over the period from 1980 to 2018. Results reveal considerable spatial, interannual and long-term variability in annual TN, NH₃-N and TP fluxes, with spatial variations in average TN and NH₃-N fluxes primarily driven by net anthropogenic nitrogen inputs. Interannual variability is dominated by precipitation across continental areas of China. Spatial variability in the estimated average annual TP flux in the undeveloped western and the developed middle east regions of China are primarily controlled by net anthropogenic phosphorus inputs and precipitation, respectively. We found that TN, NH₃-N and TP fluxes increased from 1980 to 2018 in watersheds in East China; the national mean annual TN, NH₃-N and TP fluxes increased before 2015 and decreased after 2015. This study illustrates the important role of precipitation and temperature variability in controlling the spatial, interannual and long-term variability of nutrient fluxes, and indicates that the influence of the meteorological conditions on annual loadings is needed when designing watershed nutrient reduction or management strategies.

Phosphorus removal by steel slag from tile drainage water: Lab and field evaluations

Basic oxygen furnace (BOF) and blast furnace (BF) steel slags are well suited for phosphorous (P) removal from nonpoint sources such as agricultural runoff. However, the reported mechanism(s) of removal varies from study to study which complicates implementation for unique environmental conditions that may interfere with the removal mechanism(s). This work compared laboratory column experiments and field filter experiments to provide insights on the influence of relevant field conditions (water alkalinity, slag grain size distribution, BF:BOF slag ratio, and water stagnation) on P removal by BF and BOF steel slag mixtures. Alkalinity was the most influential variable in lab-scale slag columns that received 250 mg/L alkalinity water and achieved complete P removal throughout the 3-h experiment, while identical columns receiving 500 mg/L alkalinity water averaged 52% P removal and only 14% removal after 2.5 h. Batch regeneration and adsorption experiments were conducted on the exhumed BOF/BF slag mixture from the field filter to evaluate strategies for increasing field P removal capacity. The adsorption capacity of steel slags was effectively regenerated by 0.01 M Al₂(SO₄)₃, which allowed for an additional 34% P removal in batch adsorption tests. The acid neutralization capacity of slag samples was effectively regenerated by 1 M NaOH, which allowed previously expended slag to reach a pH of 9.7 even in high alkalinity test water. The results presented here show that BF slag and Al₂(SO₄)₃ regeneration of BF slag is best suited for high alkalinity influent conditions and removes P through adsorption while BOF slag and NaOH regeneration perform best under low alkalinity conditions and removes P through mineral precipitation.

Random forest-based modeling of stream nutrients at national level in a data-scarce region

Nutrient runoff from agricultural production is one of the main causes of water quality deterioration in river systems and coastal waters. Water quality modeling can be used for gaining insight into water quality issues in order to implement effective mitigation efforts. Process-based nutrient models are very complex, requiring a lot of input parameters and computationally expensive calibration. Recently, ML approaches have shown to achieve an accuracy comparable to the process-based models and even outperform them when describing nonlinear relationships. We used observations from 242 Estonian catchments, amounting to 469 yearly TN and 470 TP measurements covering the period 2016-2020 to train random forest (RF) models for predicting annual N and P concentrations. We used a total of 82 predictor variables, including land cover, soil, climate and topography parameters and applied a feature selection strategy to reduce the number of dependent features in the models. The SHAP method was used for deriving the most relevant predictors. The performance of our models is comparable to previous process-based models used in the Baltic region with the TN and TP model having an R² score of 0.83 and 0.52, respectively. However, as input data used in our models is easier to obtain, the models offer superior applicability in areas, where data availability is insufficient for process-based approaches. Therefore, the models enable to give a robust estimation for nutrient losses at national level and allows to capture the spatial variability of the nutrient runoff which in turn enables to provide decision-making support for regional water management plans.

India's Riverine Nitrogen Runoff Strongly Impacted by Monsoon Variability

Agricultural intensification in India has increased nitrogen pollution, leading to water quality impairments. The fate of reactive nitrogen applied to the land is largely unknown, however. Long-term records of riverine nitrogen fluxes are nonexistent and drivers of variability remain unexamined, limiting the development of nitrogen management strategies. Here, we leverage dissolved inorganic nitrogen (DIN) and discharge data to characterize the seasonal, annual, and regional variability of DIN fluxes and their drivers for seven major river basins from 1981 to 2014. We find large seasonal and interannual variability in nitrogen runoff, with 68% to 94% of DIN fluxes occurring in June through October and with the coefficient of variation across years ranging from 44% to 93% for individual basins. This variability is primarily explained by variability in precipitation, with year- and basin-specific annual precipitation explaining 52% of the combined regional and interannual variability. We find little correlation with rising fertilizer application rates in five of the seven basins, implying that agricultural intensification has thus far primarily impacted groundwater and atmospheric emissions rather than riverine runoff. These findings suggest that riverine nitrogen runoff in India is highly sensitive to projected future increases in precipitation and intensification of the seasonal monsoon, while the impact of projected continued land use intensification is highly uncertain.

Nitrogen and phosphorous recycling from human urine by household electrochemical fixed bed in sparsely populated regions

Decentralized treatment of human urine in sparsely populated regions could avoid the problem of sewage collection in traditionally centralized treatment schemes and simultaneously utilize the recovered N/P fertilizer in-situ to nurture gardens. Herein, an integrated electrochemical fixed bed packed with divided magnesite and carbon zones was constructed for the pretreatment of human urine, followed by the recovery of 95.0% NH₄⁺ and 85.8% PO₄^3- via struvite precipitation and NH₃ volatilization as well as the on-site employment of the produced struvite as fertilizer. In the process, the acid/base zones created by electrochemical water splitting dissolved the magnesite filler as the Mg²⁺ source of struvite, further creating an ideal pH environment for struvite precipitation and NH₃ volatilization in the effluent. Without the need to control solution pH by chemical addition, the system can resist impacts from changes in water quality by adjustment of the current density and flow rate, indicating its great potential for automatic operation. Life cycle assessment indicated that the on-site employment of produced struvite avoids the long-distance fertilizer transportation required for fertilization, thus reducing carbon emission by a hundred million tons per year if the household facility is driven by clean electricity.

Future bioenergy expansion could alter carbon sequestration potential and exacerbate water stress in the United States

The maximum future projected bioenergy expansion potential, in scenarios limiting warming to 2°C or below, is equivalent to half of present-day croplands. We quantify the impacts of large-scale bioenergy expansion against re/afforestation, which remain elusive, using an integrated human-natural system modeling framework with explicit representation of perennial bioenergy crops. The end-of-century net carbon sequestration due to bioenergy deployment coupled with carbon capture and storage largely depends on fossil fuel displacement types, ranging from 11.4 to 31.2 PgC over the conterminous United States. These net carbon sequestration benefits are inclusive of a 10 PgC carbon release due to land use conversions and a 2.4 PgC loss of additional carbon sink capacity associated with bioenergy-driven deforestation. Moreover, nearly one-fourth of U.S. land areas will suffer severe water stress by 2100 due to either reduced availability or deteriorated quality. These broader impacts of bioenergy expansion should be weighed against the costs and benefits of re/afforestation-based strategies.

Actions to halt biodiversity loss generally benefit the climate

The two most urgent and interlinked environmental challenges humanity faces are climate change and biodiversity loss. We are entering a pivotal decade for both the international biodiversity and climate change agendas with the sharpening of ambitious strategies and targets by the Convention on Biological Diversity and the United Nations Framework Convention on Climate Change. Within their respective Conventions, the biodiversity and climate interlinked challenges have largely been addressed separately. There is evidence that conservation actions that halt, slow or reverse biodiversity loss can simultaneously slow anthropogenic mediated climate change significantly. This review highlights conservation actions which have the largest potential for mitigation of climate change. We note that conservation actions have mainly synergistic benefits and few antagonistic trade-offs with climate change mitigation. Specifically, we identify direct co-benefits in 14 out of the 21 action targets of the draft post-2020 global biodiversity framework of the Convention on Biological Diversity, notwithstanding the many indirect links that can also support both biodiversity conservation and climate change mitigation. These relationships are context and scale-dependent; therefore, we showcase examples of local biodiversity conservation actions that can be incentivized, guided and prioritized by global objectives and targets. The close interlinkages between biodiversity, climate change mitigation, other nature's contributions to people and good quality of life are seldom as integrated as they should be in management and policy. This review aims to re-emphasize the vital relationships between biodiversity conservation actions and climate change mitigation in a timely manner, in support to major Conferences of Parties that are about to negotiate strategic frameworks and international goals for the decades to come.

Porous Cellulose Acetate/Block Copolymer Membranes for the Recovery of Polyphenolic Compounds from Aquatic Environments

Polyphenols are natural compounds with strong antioxidant properties synthesized by plants and widely distributed in plant tissues. They compose a broad class of compounds that are commonly employed for multiple applications such as food, pharmaceutical, adhesives, biomedical, agricultural, and industrial purposes. Runoffs from these sources result in the introduction of polyphenols into aquatic environments where they further transform into highly toxic pollutants that can negatively affect aquatic ecosystems and humans. Therefore, the development of extraction and remediation methods for such compounds must be addressed. This study describes the identification and operation of a method to recover polyphenolic compounds from water environments by utilizing membrane-based separation. Composite membranes derived from electrospun cellulose acetate (CA) fibers and diblock copolymer (DiBCP) PEO-b-P4VP were prepared to evaluate the adsorption of polyphenolic compounds from aqueous environments. The highly porous CA fibers were developed using the electrospinning technique, and the fabricated DiBCP/CA membranes were characterized using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), Fourier-transform infrared (FT-IR) spectroscopy, and tensile testing. Finally, the ability of the composite membranes to adsorb the soluble polyphenolic compounds catechol (CAT) and gallic acid (GA), from a wetland environment, was studied via batch adsorption experiments and by solid-phase extraction (SPE). Results revealed a successful recovery of both polyphenols, at concentrations within the parts per million (ppm) range, from the aqueous media. This suggests a novel approach to recover these compounds to prevent their transformation into toxic pollutants upon entrance to water environments.

Limited progress in nutrient pollution in the U.S. caused by spatially persistent nutrient sources

Human agriculture, wastewater, and use of fossil fuels have saturated ecosystems with nitrogen and phosphorus, threatening biodiversity and human water security at a global scale. Despite efforts to reduce nutrient pollution, carbon and nutrient concentrations have increased or remained high in many regions. Here, we applied a new ecohydrological framework to ~12,000 water samples collected by the U.S. Environmental Protection Agency from streams and lakes across the contiguous U.S. to identify spatial and temporal patterns in nutrient concentrations and leverage (an indicator of flux). For the contiguous U.S. and within ecoregions, we quantified trends for sites sampled repeatedly from 2000 to 2019, the persistence of spatial patterns over that period, and the patch size of nutrient sources and sinks. While we observed various temporal trends across ecoregions, the spatial patterns of nutrient and carbon concentrations in streams were persistent across and within ecoregions, potentially because of historical nutrient legacies, consistent nutrient sources, and inherent differences in nutrient removal capacity for various ecosystems. Watersheds showed strong critical source area dynamics in that 2-8% of the land area accounted for 75% of the estimated flux. Variability in nutrient contribution was greatest in catchments smaller than 250 km2 for most parameters. An ensemble of four machine learning models confirmed previously observed relationships between nutrient concentrations and a combination of land use and land cover, demonstrating how human activity and inherent nutrient removal capacity interactively determine nutrient balance. These findings suggest that targeted nutrient interventions in a small portion of the landscape could substantially improve water quality at continental scales. We recommend a dual approach of first prioritizing the reduction of nutrient inputs in catchments that exert disproportionate influence on downstream water chemistry, and second, enhancing nutrient removal capacity by restoring hydrological connectivity both laterally and vertically in stream networks.

Reconciling regional nitrogen boundaries with global food security

While nitrogen inputs are crucial to agricultural production, excess nitrogen contributes to serious ecosystem damage and water pollution. Here, we investigate this trade-off using an integrated modelling framework. We quantify how different nitrogen mitigation options contribute to reconciling food security and compliance with regional nitrogen surplus boundaries. We find that even when respecting regional nitrogen surplus boundaries, hunger could be substantially alleviated with 590 million fewer people at risk of hunger from 2010 to 2050, if all nitrogen mitigation options were mobilized simultaneously. Our scenario experiments indicate that when introducing regional N targets, supply-side measures such as the nitrogen use efficiency improvement are more important than demand-side efforts for food security. International trade plays a key role in sustaining global food security under nitrogen boundary constraints if only a limited set of mitigation options is deployed. Policies that respect regional nitrogen surplus boundaries would yield a substantial reduction in non-CO₂ GHG emissions of 2.3 GtCO₂e yr^-1 in 2050, which indicates a necessity for policy coordination.

Future trends of dissolved inorganic nitrogen concentrations in Northwestern Mediterranean coastal waters under climate change

Coastal ecosystems are amongst the most vulnerable to climate change, due to their location at the land-sea interface. In coastal waters, the nitrogen cycle can be significantly altered by rising temperatures and other factors derived from climate change, affecting phytoplankton and higher trophic levels. This research analyzes the effect of meteorological variables on dissolved inorganic nitrogen (DIN) species in coastal inshore waters of a Northwestern Mediterranean region under climate change. We built simple mathematical schemes based on artificial neural networks (ANN), trained with field data. Then, we used regional climatic projections for the Spanish Mediterranean coast to provide inputs to the trained ANNs, and thus, allowing the estimation of future DIN trends throughout the 21st century. The results obtained indicate that nitrite and nitrate concentrations are expected to decrease mainly due to rising temperatures and decreasing continental inputs. Major changes are projected for the winter season, driven by a rise in minimum temperatures which decrease the nitrite and nitrate peaks observed at low temperatures. Ammonium concentrations are not expected to undergo a significant annual trend but may either increase or decrease during some months. These results entail a preliminary simplified approach to estimate the impact of meteorological changes on DIN concentrations in coastal waters under climate change.

The impact of interventions in the global land and agri-food sectors on Nature's Contributions to People and the UN Sustainable Development Goals

Interlocked challenges of climate change, biodiversity loss, and land degradation require transformative interventions in the land management and food production sectors to reduce carbon emissions, strengthen adaptive capacity, and increase food security. However, deciding which interventions to pursue and understanding their relative co-benefits with and trade-offs against different social and environmental goals have been difficult without comparisons across a range of possible actions. This study examined 40 different options, implemented through land management, value chains, or risk management, for their relative impacts across 18 Nature's Contributions to People (NCPs) and the 17 Sustainable Development Goals (SDGs). We find that a relatively small number of interventions show positive synergies with both SDGs and NCPs with no significant adverse trade-offs; these include improved cropland management, improved grazing land management, improved livestock management, agroforestry, integrated water management, increased soil organic carbon content, reduced soil erosion, salinization, and compaction, fire management, reduced landslides and hazards, reduced pollution, reduced post-harvest losses, improved energy use in food systems, and disaster risk management. Several interventions show potentially significant negative impacts on both SDGs and NCPs; these include bioenergy and bioenergy with carbon capture and storage, afforestation, and some risk sharing measures, like commercial crop insurance. Our results demonstrate that a better understanding of co-benefits and trade-offs of different policy approaches can help decision-makers choose the more effective, or at the very minimum, more benign interventions for implementation.

The magnitude and drivers of harmful algal blooms in China's lakes and reservoirs: A national-scale characterization

Harmful algal blooms (HABs) can have dire repercussions on aquatic wildlife and human health, and may negatively affect recreational uses, aesthetics, taste, and odor in drinking water. The factors that influence the occurrence and magnitude of harmful algal blooms and toxin production remain poorly understood and can vary in space and time. It is within this context that we use machine learning (ML) and two 14-year (2005-2018) data sets on water quality and meteorological conditions of China's lakes and reservoirs to shed light on the magnitude and associated drivers of HAB events. General regression neural network (GRNN) models are developed to predict chlorophyll a concentrations for each lake and reservoir during two study periods (2005-2010 and 2011-2018). The developed models with an acceptable model fit are then analyzed by two indices to determine the areal HAB magnitudes and associated drivers. Our national assessment suggests that HAB magnitudes for China's lakes and reservoirs displayed a decreasing trend from 2006 (1363.3 km²) to 2013 (665.2 km²), and a slightly increasing trend from 2013 to 2018 (775.4 km²). Among the 142 studied lakes and reservoirs, most severe HABs were found in Lakes Taihu, Dianchi and Chaohu with their contribution to the total HAB magnitude varying from 89.2% (2013) to 62.6% (2018). HABs in Lakes Taihu and Chaohu were strongly associated with both total phosphorus and nitrogen concentrations, while our results were inconclusive with respect to the predominant environmental factors shaping the eutrophication phenomena in Lake Dianchi. The present study provides evidence that effective HAB mitigation may require both nitrogen and phosphorus reductions and longer recovery times; especially in view of the current climate-change projections. ML represents a robust strategy to elucidate water quality patterns in lakes, where the available information is sufficient to train the constructed algorithms. Our mapping of HAB magnitudes and associated environmental/meteorological drivers can help managers to delineate hot-spots at a national scale, and comprehensively design the best management practices for mitigating the eutrophication severity in China's lakes and reservoirs.

Nitrogen and phosphorus retention budgets of a semiarid plain basin under different human activity intensity

Excessive nitrogen (N) and phosphorus (P) runoff from human activities results in degraded water quality. It is, therefore, crucial to quantitatively assess nutrient inputs over time and their impact on riverine nutrient exports. In this study, we estimated the long-term (1995-2015) nutrient inputs at the county scale by integrating Net Anthropogenic Nitrogen Input (NANI) and Net Anthropogenic Phosphorus Input (NAPI) methods, and nutrient exports into rivers by the Export Coefficient Model (ECM) for a semiarid plain basin, the Baiyangdian (BYD) Basin, China. The results showed that N and P input intensities in the year 2015 reached 18852 kg N km² yr^-1 and 2073 kg P km^-2 yr^-1, showing a 35% and 11% increase in comparison with 1995, respectively. About 60% of these nutrients were derived from fertilizer application. The multi-year averaged N and P exported to rivers was 548 kg N km^-2 yr^-1 and 79 kg P km^-2 yr^-1, respectively. Hotspots for nutrient budgets were found in the southeastern counties. Hotspots covered about 12% of the total land, but contributed by 38-52% of total nutrient budgets. The nutrient export ratios showed no significantly temporal variations, and only about 2.15-2.89% of NANI and NAPI were exported into rivers. The low nutrient export ratio was due to the low water discharge that limited the nutrient transportation in the semi-arid plain basin. As most of anthropogenic nutrient inputs were retained in the basin, their impacts on the pollution of soils and aquifers need to be considered and adequately addressed in the future. This study constructs the spatial quantitative nutrient budgets, which can provide effective information for region policy formulation.

Application of Stable Isotopes of Water to Study Coupled Submarine Groundwater Discharge and Nutrient Delivery

Submarine groundwater discharge (SGD)—including terrestrial freshwater, density-driven flow at the saltwater–freshwater interface, and benthic exchange—can deliver nutrients to coastal areas, generating a negative effect in the quality of marine water bodies. It is recognized that water stable isotopes (18O and 2H) can be helpful tracers to identify different flow paths and origins of water. Here, we show that they can be also applied when assessing sources of nutrients to coastal areas. A field site near a lagoon (Ringkøbing Fjord, Denmark) has been monitored at a metric scale to test if stable isotopes of water can be used to achieve a better understanding of the hydrochemical processes taking place in coastal aquifers, where there is a transition from freshwater to saltwater. Results show that 18O and 2H differentiate the coastal aquifer into three zones: Freshwater, shallow, and deep saline zones, which corresponded well with zones having distinct concentrations of inorganic phosphorous. The explanation is associated with three mechanisms: (1) Differences in sediment composition, (2) chemical reactions triggered by mixing of different type of fluxes, and (3) biochemical and diffusive processes in the lagoon bed. The different behaviors of nutrients in Ringkøbing Fjord need to be considered in water quality management. PO4 underneath the lagoon exceeds the groundwater concentration inland, thus demonstrating an intra-lagoon origin, while NO3, higher inland due to anthropogenic activity, is denitrified in the study area before reaching the lagoon.