Nitrate Concentrations In Water Research Articles

A hybrid deep learning approach to predict hourly riverine nitrate concentrations using routine monitored data

With high-frequency data of nitrate (NO3–N) concentrations in waters becoming increasingly important for understanding of watershed system behaviors and ecosystem managements, the accurate and economic acquisition of high-frequency NO3–N concentration data has become a key point. This study attempted to use coupled deep learning neural networks and routine monitored data to predict hourly NO3–N concentrations in a river. The hourly NO3–N concentration at the outlet of the Oyster River watershed in New Hampshire, USA, was predicted through neural networks with a hybrid model architecture coupling the Convolutional Neural Networks and the Long Short-Term Memory model (CNN-LSTM). The routine monitored data (the river depth, water temperature, air temperature, precipitation, specific conductivity, pH and dissolved oxygen concentrations) for model training were collected from a nested high-frequency monitoring network, while the high-frequency NO3–N concentration data obtained at the outlet were not included as inputs. The whole dataset was separated into training, validation, and testing processes according to the ratio of 5:3:2, respectively. The hybrid CNN-LSTM model with different input lengths (1d, 3d, 7d, 15d, 30d) displayed comparable even better performance than other studies with lower frequencies, showing mean values of the Nash-Sutcliffe Efficiency 0.60–0.83. Models with shorter input lengths demonstrated both the higher modeling accuracy and stability. The water level, water temperature and pH values at monitoring sites were main controlling factors for forecasting performances. This study provided a new insight of using deep learning networks with a coupled architecture and routine monitored data for high-frequency riverine NO3–N concentration forecasting and suggestions about strategies about variable and input length selection during preprocessing of input data.

High-Resolution Estimates of N2O Emissions from Inland Waters and Wetlands in China.

Inland waters (rivers, lakes, and reservoirs) and wetlands (marshes and coastal wetlands) represent large and continuous sources of nitrous oxide (N2O) emissions, in view of adequate biomass and anaerobic conditions. Considerable uncertainties remain in quantifying spatially explicit N2O emissions from aquatic systems, attributable to the limitations of models and a lack of comprehensive data sets. Herein, we conducted a synthesis of 1659 observations of N2O emission rates to determine the major environmental drivers across five aquatic systems. A framework for spatially explicit estimates of N2O emissions in China was established, employing a data-driven approach that upscaled from site-specific N2O fluxes to robust multiple-regression models. Results revealed the effectiveness of models incorporating soil organic carbon and water content for marshes and coastal wetlands, as well as water nitrate concentration and dissolved organic carbon for lakes, rivers, and reservoirs for predicting emissions. Total national N2O emissions from inland waters and wetlands were 1.02 × 105 t N2O yr-1, with contributions from marshes (36.33%), rivers (27.77%), lakes (25.27%), reservoirs (6.47%), and coastal wetlands (4.16%). Spatially, larger emissions occurred in the Songliao River Basin and Continental River Basin, primarily due to their substantial terrestrial biomass. This study offers a vital national inventory of N2O emissions from inland waters and wetlands in China, providing paradigms for the inventorying work in other countries and insights to formulate effective mitigation strategies for climate change.

The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model

AbstractTransit time‐based water quality models using StorAge Selection (SAS) functions are crucial for nitrate (NO3−) management. However, relying solely on instream NO3− concentration for model calibration can result in poor parameter identifiability. This is due to the interaction, or correlation, between transport parameters, such as SAS function parameters, and denitrification rate, which challenges accurate parameters identification and description of catchment‐scale hydrological processes. To tackle this issue, we conducted three Monte‐Carlo experiments for a German mesoscale catchment by calibrating a SAS‐based model with daily instream NO3− concentrations (Experiment 1), monthly instream stable water isotopes (e.g. δ18O) (Experiment 2) and both datasets (Experiment 3). Our findings revealed comparable ranges of SAS transport parameters and median water transit times (TT50) across the experiments. This suggests that, despite their distinct reactive or conservative nature, and sampling strategies, the NO3− and δ18O time series offer similar information for calibration. However, the absolute values of transport parameters and TT50 time series, as well as the degree of parameter interaction differed. Experiment 1 showed greater interaction between certain transport parameters and denitrification rate, leading to greater equifinality. Conversely, Experiment 3 yielded reduced parameters interaction, which enhanced transport parameters identifiability and decreased uncertainty in TT50 time series. Hence, even a modest effort to incorporate only monthly δ18O values in model calibration for highly frequent NO3−, improved the description of hydrological transport. This study showcased the value of combining NO3− and δ18O model results to improve transport parameter identifiability and model robustness, which ultimately enhances NO3− management strategies.

Cryosphere and land cover influence on stream water quality in Central Asia's glacierized catchments

This work helps address recent calls for systematic water quality assessment in Central Asia and considers how nutrient and salinity sources, and transport, affect water quality along the continuum from the cryosphere to the lowland plains. Spatial and, for the first time, temporal variations in stream water pH, temperature, electrical conductivity, and nitrate and phosphate concentrations are presented for four catchments (485–13,500 km2), all with glaciers and major urban areas. The catchments studied were: Kaskelen (Kazakhstan), Ala-Archa (Kyrgyzstan), Chirchik (Uzbekistan) and the Kofarnihon (Tajikistan). Measurements were made in cryosphere, stream water, groundwater, reservoir and lake samples over a 22-month period at fortnightly intervals from 35 sites. The results highlight that glacier, permafrost and rock glacier outflows were primary and secondary nitrate sources (>1 mg N L−1) to the headwaters, and there were major increases in salinity and nitrate concentrations where rivers receive inputs from agriculture and settlements. Overall, the water quality complied with national and World Health Organization standards, however there were pollution hot-spots with shallow urban groundwaters contaminated with nitrate (>11 mg N L−1) and stream electrical conductivity above 800 μS cm−1 in some agricultural areas indicative of high salinity. Phosphate concentrations were generally low (<0.06 mg P L−1) throughout the catchments, though elevated (>0.2 mg P L−1) in urban areas due to effluent contamination. A melt water dilution effect along the main river channels was discernible, in the electrical conductivity and nitrate concentration seasonal dynamics, 100 s of km from the headwaters. Thus, the input of relatively clean water from the cryosphere is an important regulator of main channel water quality in the urban and farmed lowland plains adjacent to the Tien Shan and Pamir. Improved sewage treatment is needed in urban areas.

Spatial distribution, sources, and human health risk assessment of elevated nitrate levels in groundwater of an agriculture-dominant coastal area in Hainan Island, China

In order to comprehend the groundwater nitrate contamination in Hainan Island, which is recognized as China's sole “tropical agricultural production base,” the distribution characteristics of nitrate in different aquifers and land-use types were elucidated through hydrochemical and geostatistical analysis methods. Principal component analysis (PCA), hierarchical cluster analysis (HCA), and absolute principal component score-multiple linear regression (APCS-MLR) were employed for qualitative and quantitative analysis of the nitrate source. The results showed that NO3−-high (>88.57 mg/L) groundwater accounted for about 10 % of the total distribution area of the western coastal area in Hainan Island. Moreover, the proportions of NO3−-high groundwater in pore water and fissure water were 10 % and 7 %, respectively. The order of groundwater nitrate concentration in different land-use types was as follows: bare land, cultivated land, construction land, grassland, and woodland. The main sources of elevated nitrate concentrations in pore water were animal feces and nitrogen/potassium fertilizers, accounting for 45.4 % of the overall contribution. These substances infiltrated through the vadose zone, leaching out and mobilizing selenium within this zone, ultimately leading to the characteristic enrichment patterns observed in pore water, including nitrate, arsenic, potassium, and selenium. Furthermore, the occurrence of high nitrate in fissure water was mainly attributed to the leaching of cultured manure, septic tank leakage, and infiltration of domestic sewage, accounting for a contribution rate of 32.9 %. Simultaneously, under oxidizing conditions, selenium became activated and entered groundwater through water flow, thereby exhibiting common enrichment characteristics with nitrate and potassium in fissure water. In addition, the assessment of human health risks revealed that 16 % and 40 % of groundwater samples posed unacceptable non-carcinogenic risks to adults and children respectively, with a higher risk for local children. The study recommends the reasonable application of chemical fertilizers, as well as the strengthening of sewage treatment capacity and standardized disposal of manure and feces, to reduce nitrate contamination of groundwater at source and ensure the safety of drinking water.

The origin of high salinity and hydrogeochemical characteristics of groundwater in semi-arid area of the Linta Basin, Southwestern Madagascar

The Linta Basin, located in the Southwestern Madagascar, is a semi-arid area where groundwater in fractured media bedrock aquifer constitutes the main source of water supply. In the last two decades, highly mineralized groundwater was identified in this area; however, the origin of the salinity was not clear. The purpose of the study was to clarify the origin of salinity and to identify hotspots with groundwater unsuitable for water supply. Groundwater quality in this basin was investigated by hydrogeochemical and isotopic methods accompanied by mineralogical study. In total, 32 groundwater samples were collected and analyzed. The results showed that groundwater temperature varied from 25.2 °C to 31.7 °C. Values of pH and TDS varied from 6.55 to 8.24 and 221 to 5612 mg/L, respectively. The aquifer, which is mainly fractured, showed 7 groundwater types, namely Mg–HCO3,Na–HCO3 and also Na–C1, Mg–Cl, Na–Cl–HCO3, Mg–Cl–HCO3-, and Ca–Mg–HCO3. Two groups of variables have been identified by factor analysis; the factor F1 comprises EC, Ca2+, Mg2+, SO42−, and Cl− whereas the factor F2 comprises HCO3−, K+, and Na+, and they were interpreted in terms of hydrogeochemical processes. Values of saturation indices (SI) for carbonate minerals were generally positive, indicating their possible precipitation. Based on the Gibbs diagram and factor analysis, groundwater mineralization is affected by water-rock interactions and evaporation, respectively. The important role of evaporation is confirmed by enrichment of stable isotopes with δ18O values up to 1.2 ‰. Processes such as base ionic exchange process and reverse ionic exchange process may also be important locally. The main origin of groundwater mineralization is the hydrolysis of silicate minerals such as feldspars and micas coupled with evaporation. In several wells, salinity is too high for water supply and nitrate concentration is above the WHO limit for drinking water. Results of the study highlighted groundwater chemistry formation processes and are applicable in other African countries with bedrock aquifers.

Assessing impacts of cemeteries on water quality in an urban headwater watershed with mixed human‐built infrastructure

AbstractCemeteries are understudied integral components to urban watersheds, which provide ecosystem services but can also export nutrients, trace elements, and other contaminants to nearby water bodies. In this study, we focus on Meadowbrook Creek, an urban headwater stream in Syracuse, New York (USA), which has shown significant nitrate contributions from a local cemetery. We collected biweekly surface water samples over the course of 1 year from 2022 to 2023 for analysis of major and trace elemental concentrations including Na, Ca, Mg, K, F, Cl, sulfate, and nitrate. Here, we aim to assess the impact of various human infrastructures on urban stream water quality with a particular focus on the cemetery and nitrate. A comparison between the new dataset in this study and previously reported water chemistry data in Meadowbrook in 2012 suggests a decade‐long impact of road salting and the cemetery on water quality particularly with respect to Na, Cl, and nitrate. Sulfate, Mg, Ca, and K are likely mainly geogenic. Stable nitrogen isotope data, the usage of concrete or steel vaults in the cemetery in the past 50 years, and the lack of correlation between nitrate and fluoride concentrations in stream water argue against burial decay products being a major source of nitrate to the stream. Instead, other nitrate sources that exist in the cemetery such as, fertilizer, decaying plant material, and wastewater, are more viable dominant nitrate sources. In addition, nitrate loading calculations indicate that the groundwater‐connected reach, including the cemetery, acts as an annual net sink for nitrate despite the seasonally varying sink‐source patterns.

Groundwater Contamination with Nitrate and Human Health Risk Assessment of North East Alluvial Plains of Bihar, India

Groundwater is natural resources which supplies almost half of all drinking water in the world and plays a key role in food production. Consuming water containing high nitrate concentration have immediate effect on infant and could cause the risk of diseases Methemoglobinemia in which blood lacks the ability to carry sufficient oxygen to the individual body cells. As difference in nitrate concentration in water, made it important to study the undesirable effect of it. In rural areas, groundwater contamination is a problem related to the excessive use of chemical fertilizers by local farmers. Shallow groundwater plays a vital role in water use and the yield of Maize. Nitrogen application significantly affects crop uptake and utilization of water from irrigation, but little is known about groundwater use. Farmers are applying nitrogen on an average 278 kg/ha in Kharif maize, which is about 131.72% more than the RDN of Kharif maize i.e. 120 KgN/ha. The mean value of N application by farmers ranges from 251-323 kg/ha. The Maximum rate of N application was observed in Khagaria (323 kg N/ha) followed by Madhepura (275.08 kg N/ha) and minimum in case of Saharsa district (251.16 kg N/ha). The application rate of nitrogenous fertilizer, varying from 109.25% to 169.16% over the RDN, resulting in NO3- leaching. The groundwater and surfacewater from 12 villages was collected and various quality parameters were analysed. The nitrate in ground water varied (1.87- 6.19 mg/L) and surface water (1.87 – 3.84 mg/L) being maximum concentration of nitrate in Madhepura district. The present study on nitrate leaching in soil, its level of contamination in ground water and human health risk assessment by chronic daily intake of nitrate and Hazard Quotient (H.Q) values in the study area of Khagaria, Saharsa, Madhepura and Supaul has been carried out in the eastern alluvial region of Bihar.

Linking optical data and nitrates in the Lower Mississippi River to enable satellite‐based monitoring of nutrient reduction goals

AbstractHypoxic zones and associated nitrate pollution from farms, cities and industrial facilities is driving declines in water quality that affect ecosystems, economies and human health in major rivers and coastal areas worldwide. In the Mississippi River, the United States Environmental Protection Agency set a goal of reducing nitrogen loading 20% by 2025, but estimating progress towards this goal is difficult because data from in‐stream gauges and laboratory samples are too sparse. Satellites have the potential to provide sufficient data across the Mississippi River, if a key methodological challenge can be overcome. Satellites provide data from visible light, but nitrates are only observable with ultraviolet light. We address this methodological challenge by using a two‐step surrogate modelling procedure to link optical data and nitrates in the Lower Mississippi River. First, we correlate in situ nitrate measurements to common water quality parameters, particularly turbidity and chlorophyll, using data from water sensors installed at Baton Rouge, Louisiana, USA, and a long‐term dataset from Louisiana State University. Second, we correlate these water quality data to satellite estimates of water quality parameters. We found a correlation between these water quality parameters and nitrate concentrations, as indicated by a coefficient of determination, when the relationship was viewed in nonlinear parameter space. The spatial extent of the correlation was tested with an upstream nitrate sensor 140 km north of the estimation location. These results provide proof of concept that we can develop models that use satellite data to provide large‐scale monitoring of nitrates across the Mississippi River Basin and other impaired rivers, globally.

The Influence of Water Nitrate Concentration Combined with Elevated Temperature on Rainbow Trout Oncorhynchus mykiss in an Experimental Aquaponic Setup

Intensive recirculating systems are a fast-developing sector of aquaculture. While several warm-water fish have been reared in aquaponics, almost no data are available for cold-water species. The determination of nitrate toxicity thresholds in recirculating aquaculture is crucial. Different pollutants are typically more toxic at elevated temperatures. We investigated the performance of Oncorhynchus mykiss under two different nitrate levels and two temperatures. We applied a 2 × 2 factorial design, where fish (9.78 ± 0.51 g) were exposed to nitrate concentrations of 40 or 110 mg/L NO3− and to temperatures of 17 °C or 21 °C for 20 days. This study focused on understanding the physiological responses of rainbow trout to relatively low nitrate levels under heat stress in order to investigate the feasibility of integrating this species into commercial aquaponics. The growth, condition, and expression of genes involved in metabolism, heat shock, antioxidant, and immune response were assessed in the liver, together with the activities of enzymes related to glucose and fatty acid metabolism. High nitrate levels at 17 °C affected the condition but did not alter growth, leading to increased glycolytic potential and, occasionally, a greater reliance on lipid oxidation. Antioxidant defense was mainly induced due to high nitrates and the similar expression patterns of antioxidant genes observed under high nitrate at both 17 °C and 21 °C. Warm exposure decreased condition and growth, leading to greatly reduced glucokinase transcription, irrespective of the nitrate levels. Exposure to 21 °C and high nitrate led to equivalent growth and condition as well as to a milder inflammatory response combined with metabolic readjustments (enhancement of glycolytic and lipid oxidation pathways) compared to the low nitrates at 21 °C. Based on the results, rearing at a temperature close to 21 °C should be avoided for fingerling growth, while NO3− concentration until 110 mg/L may not have severe impacts on fingerling health and growth at 17 °C. In addition, rainbow trout fingerlings can tolerate a 20-day exposure at 21 °C and NO3− up to 110 mg/L. Additional factors should always be considered, such as specific water quality parameters, for a comprehensive approach to assessing the feasibility of rainbow trout aquaculture in aquaponics.

Effects of climate and acidic deposition on interannual variations of stream water chemistry in forested watersheds in the Shimanto River Basin, southern Japan

AbstractAlthough the amount of acidic deposition has recently decreased in Japan, it has still deteriorated some forest ecosystems during the past several decades. Moreover, recent climate changes can affect stream water chemistry. We investigated the temporal trend and effects of climate conditions on stream water chemistry for more than 20 years in two areas (Yusuhara and Taisho) in the Shmanto River Basin, southern Japan, where the effects of acidic deposition are considered to be modest. Stream water samples were collected monthly from three forest watersheds selected at each site. The annual means of the stream chemistry were predicted by multiple regression analysis. The ammonium, nitrate, and sulfate concentrations in the bulk precipitation have decreased at Yusuhara, and the sodium, magnesium, calcium, chloride, nitrate, and sulfate concentrations in the stream water have decreased in both areas. The nitrate and sulfate concentrations apparently responded to the decreasing input of acidic deposition. The sunlight hours were positively related with the potassium, magnesium, calcium, nitrate, sulfate, and bicarbonate concentrations in stream water. The results suggest that long sunlight hours boost the photosynthetic activities, thus promoting soil respiration and decomposition of soil organic matter. Moreover, a higher carbonic acid concentration in the soil solution promotes cation weathering and carbonic acid dissociation to bicarbonate. Given the decreasing trends in magnesium and calcium concentration with no change in bicarbonate concentration, we inferred that previousinputs of acidic deposition enhanced the rate of rock weathering.

Multimetric socio‐ecological assessment of water hyacinth (Eichhornia crassipes (Mart) solms) invasion of an urban Ramsar wetland lake

AbstractWater hyacinth (Eichhornia crassipes (Mart) solms), a widely distributed invasive aquatic plant in Sri Lanka, has invaded the Diyawannawa wetland lake located in Colombo city, which is the first Ramsar wetland city in South Asia. The present study was conducted to assess the water quality parameters that influence the distribution of water hyacinth and to identify the environmental, economic, and social consequences of its invasion of the Diyawannawa wetland. Five sampling sites were selected from the Diyawannawa lake, and the water pH, temperature, conductivity, total dissolved solids (TDS), salinity, dissolved oxygen concentration (DO), nitrate concentration, and total phosphorus concentration were measured at monthly intervals in the rainy and dry seasons of 2020. The abundance of water hyacinth was recorded at each site at each sampling event. Interviews and focus group discussions (FGDs) were conducted with the representatives of the community associated with the wetland to assess the ecological, economic and social effects of water hyacinth invasion. Principal component analysis of the water quality parameters revealed that phosphorus and nitrate concentrations in water significantly influenced the abundance of water hyacinth. Further, the water quality index (WQI) indicated poor water quality in the sites invaded by water hyacinth. The interviews and FGDs revealed that water hyacinth invasion has adversely affected the lake's fisheries and navigation pathways and increased the frequency of flooding, resulting in an increased mosquito population. The results of the present study highlighted the importance of implementing water quality management programmes in the Diyawannawa wetland to control the invasion of water hyacinth. Further, we recommend increasing community participation in water hyacinth control programmes and providing opportunities for the community to engage in self‐employment activities associated with the uses of water hyacinth.

Lower nitrate leaching from dairy cattle slurry compared to synthetic fertilizer calcium ammonium nitrate applied to grassland

Nitrate leaching from agriculture can be reduced by the choice of fertilizer and a proper timing of its application. For permanent grassland grown under temperate conditions, nitrate leaching was hypothesized to be lower from dairy cattle slurry (CS) compared to synthetic fertilizer calcium ammonium nitrate (CAN), based on differences in chemical composition, consequential effects on nitrogen (N) conversion processes in soil, and resulting differences in synchronization of (nitrate) N availability and plant N uptake. We tested the hypothesis in a two-year field experiment on cut grassland on a leaching-sensitive sandy soil, fertilized each year with 320 kg ha−1 of plant-available N from either 100% top-dressed CAN or a combination of 40% from CAN and 60% from sod-injected CS, and measured effects on grass herbage yield, herbage N uptake, and nitrate concentration in pore water at 1.0 m depth. Our results show a comparable level of herbage N uptake for both treatments, allowing for a proper comparison of nitrate leaching at a similar level of plant-available N. Average nitrate concentration in pore water in the main leaching period (over winter) was after the first (dry) growing season 44% lower for CS + CAN (41 mg l−1) compared to CAN only (73 mg l−1), and after the second (wet) growing season 35% lower for CS + CAN (32 mg l−1) compared to CAN only (49 mg l−1). Nitrogen application increased nitrate concentration at 1.0 m depth not only in winter but also in the growing season. We conclude that for permanent grasslands in temperate regions, nitrate leaching from timely applied CS may be considerably lower than from CAN, which is different from previous assumptions.

Modified surfatron device to improve microwave-plasma-assisted generation of RONS and methylene blue degradation in water

Microwave-induced plasmas generated at atmospheric pressure are very attractive for a great variety of applications since they have a relatively high electron density and can generate large amounts of reactive species. Argon plasmas can be sustained inside dielectric tubes but are radially contracted and exhibit filamentation effects when the diameter of the tube is not narrow enough (over 1.5 mm). In this work, we describe a new approach for creating microwave (2.45 GHz) plasmas under atmospheric pressure conditions by using a surfatron device and power from 10 W. This modified design of the reactor enables the sustenance of non-filamented argon plasmas. These new plasmas have a higher gas temperature and electron density than the plasma generated in the original surfatron configuration. The new design also allows for the maintenance of plasmas with relatively high proportions of water, resulting in the generation of larger quantities of excited hydroxyl radicals (·OH*). Thus, this novel configuration extends the applicability of microwave-induced plasmas by enabling operation under new conditions. Finally, the degradation of methylene blue (MB) in aqueous solutions has been assessed under different initial dye concentrations and argon flow conditions. The new plasma produces a substantial increase in hydrogen peroxide and nitrate concentrations in water and leads to a noteworthy enhancement in MB degradation efficiency. The introduction of water into the plasma produces a minor additional improvement.

Surface-Water Nitrate Exposure to World Populations Has Expanded and Intensified during 1970-2010.

Excessive nitrate in surface waters deteriorates the water quality and threatens human health. Human activities have caused increased nitrate concentrations in global surface waters over the past 50 years. An assessment of the long-term trajectory of surface-water nitrate exposure to world populations and the associated potential health risks is imperative but lacking. Here, we used global spatially explicit data on surface-water nitrate concentrations and population density, in combination with thresholds for health risks from epidemiological studies, to quantify the long-term changes in surface-water nitrate exposure to world populations at multiple spatial scales. During 1970-2010, global populations potentially affected by acute health risks associated with surface-water nitrate exposure increased from 6 to 60 million persons per year, while populations at potential chronic health risks increased from 169 to 1361 million persons per year. Potential acute risks have increasingly affected Asian countries. Populations potentially affected by chronic risks shifted from dominance by high-income countries (in Europe and North America) to middle-income countries (in Asia and Africa). To mitigate adverse health effects associated with surface-water nitrate exposure, anthropogenic nitrogen inputs to natural environments should be drastically reduced. International and national standards of maximum nitrate contamination may need to be lowered.

Pd/Cu bimetallic nano-catalyst supported on anion exchange resin (A520E) for nitrate removal from water: High property and stability

High nitrate concentration in water can lead to eutrophication and the disruption of healthy aquatic ecosystems. Additionally, in the human digestive system, it has the potential to be reduced to nitrite, which can be damaging to people's physical health. Catalytic hydrogenation of nitrate is one of the strategies for removing nitrate from water. Using A520E resin as support, we prepared Pd/Cu nano-catalyst (Pd/Cu@A520E) according to a liquid phase reduction method. A520E could improve the transfer process of nitrate in the solution to the activity sites of Pd/Cu nanoparticles, thus increase the reaction rate of nitrate reduction. Pd/Cu bimetallic nano-particles were evenly distributed on/in the resin with a size range from 2 nm to 10 nm. The External Circulating System equipped with Venturi tube (ECSV) was designed to improve the utilization efficiency of H2 in both batch tests and long-term continuous-flow tests. Nearly 100% of nitrate removal efficiency and above 90% of N2 selectivity were achieved in both batch tests and continuous-flow tests. Coexisting Cl− and SO42− at 300 mg/L showed little impact on the property of Pd/Cu@A520E. Pd/Cu@A520E also showed high nitrate removal property and stability in continuous-flow tests of more than 800 h. NO3− was adsorbed onto the active sites (functional groups and Pd/Cu particle sites), meanwhile H2 was adsorbed onto the active sites of Pd/Cu@A520E to form Pd [H]. Then the adsorbed NO3− was reduced into N2 (main product) or NH4+ by Pd [H]. In addition, Pd/Cu@A520E showed high nitrate removal property from municipal waste water.

Yielding of aquaponics using probiotics to grow tomatoes with tilapia

Aquaponics is a cutting-edge technology where plants and fish are grown together in a close-loop re-circulating system. It is not feasible to use growth-promoting agents, such as pharmaceutical antibiotics, with this biological and ecologically friendly technology to prevent or treat fish diseases. Examination of different growth booster substances became necessary because of this, and probiotics are one potential solution. The purpose of this experiment was to figure out the effect of gut probiotics, water probiotics and biofloc inputs in aquaponics to grow tilapia and tomato. Tilapia was fed with 29.40% protein containing feed with the supplement of gut probiotics (AQ-GT), water additive probiotic (AQ-WT), combination of probiotics-molasses-yeast (AQ-BF) and without any probiotic supplement (AQ) as control in media-based aquaponics. The investigation was incorporated for 75 days with triplicates of each treatment. Water quality, tilapia and tomato plant were sampled at 15-days interval. Moreover, matured tomatoes were harvested regularly. The findings showed that the treatments differed significantly in terms of electric conductivity, dissolved solids, calcium, sodium, potassium, magnesium, phosphorus, boron, copper, ammonia, nitrite, and nitrate concentration in tank water. The highest tomato flower was recorded in control (P < 0.01). On the other hand, the highest tomato and tilapia production were in AQ-BF (P < 0.01). The research findings revealed that biofloc technology (AQ-BF) significantly lower the feed conversion ratio and enhance the specific growth rate of tilapia than the other treatments. Moisture, crude protein, crude lipid, crude fiber, ash, and nitrogen free extract percentage in tilapia varied significantly among the treatments. Contrarily, statistical similarity among the treatments exists in terms of moisture, lipid, and ash content of tomato. The results indicate that, combination of biofloc technology with aquaponics is more viable for higher fish and vegetable production with favorable water quality than the other ways of probiotic inclusion in aquaponics.

Quantifying the spatiotemporal variability of nitrate in irrigation water across the Wisconsin Central Sands.

The Wisconsin Central Sands is home to large scale vegetable production on sandy soils and managed with frequent irrigation, fertigation, and widespread nitrogen fertilizer application, all of which make the region highly susceptible to nitrate loss to groundwater. While the groundwater is used as the primary source of drinking water for many communities and rural residences across the region, it is also used for irrigation. Considering the high levels of nitrate found in the groundwater, it has been proposed that growers more accurately account for the nitrate in their irrigation water as part of nitrogen management plans. Our objectives were to 1) determine the magnitude of nitrate in irrigation water, 2) quantify the spatiotemporal variability of nitrate, and 3) determine key predictors of nitrate concentration in the region. We sampled irrigation water from 38 fields across six farms from 2018 to 2020. Across the 3 years of our study, nitrate concentration varied more across space than time. On average, our samples were tested at 19.0mg L-1 nitrate-nitrogen, or nearly two times the U.S. Environmental Protection Agency (EPA) threshold for safe drinking water, equivalent to 48.1kg ha-1 of applied nitrate-nitrogen with 25.4cm (or 10 in.) of irrigation. To better understand the spatiotemporal variability in nitrate levels, week of sampling, year, well depth, well casing, and nitrogen application rate were analyzed for their role as predictor variables. Based on our linear mixed effects model, nitrogen application rate was the greatest predictor of the nitrate concentration of irrigation water (p<0.05).

Quantification of soil N2O and CH4 fluxes using the flux gradient method on a drainage water managed farm on the eastern shore of Maryland

Drainage water management (DWM) is an effective best management practice (BMP) to reduce hydrological nitrate export from croplands to surface and ground water by controlling the timing and the amount of ditch discharge and retaining water within ditches and adjacent fields using drainage control structures (DCS). While the intended consequences of maintaining higher water table levels are to increase denitrification and thereby decrease nitrate leaching, an unintended consequence is possible increased production of nitrous oxide (N2O) from denitrification and methane (CH4) from methanogenesis, both potent greenhouse gasses (GHGs). Hence, application of DWM may lead to a "pollution swapping" concern – i.e., does DWM trade reduction of nitrate concentrations in ditch water for increases in soil emissions of N2O and CH4 to the atmosphere?Here we employed the micrometeorological flux gradient (FG) technique to a corn-soybean rotation on an operational farm with DCS in eastern Maryland on the Delmarva Peninsula to answer this question. Soil N2O and CH4 fluxes were quantified under DWM and non-DWM management of a soybean crop without N fertilization (2018) and a corn crop with synthetic N fertilization (2019). To our knowledge, this is the first study employing a micrometeorological method to evaluate the effects of agricultural DWM on GHG emissions. No consistent or statistically significant differences in N2O and CH4 fluxes were observed between DWM and non-DWM fields, suggesting that DWM did not trade reduced nitrate leaching for increased soil GHG emissions. The FG measurements were also compared with chamber measurements, which revealed similar patterns, but chamber measurements had large spatial variability and overall higher daily mean flux estimates, while the tower measurements revealed more frequent, short-lived N2O pulses following fertilization and precipitation events. This research adds to the existing understanding of benefits and risks of DWM as a BMP.

Application of classification machine learning algorithms for characterizing nutrient transport in a clay plain agricultural watershed

Excess nutrients in surface water and groundwater can lead to water quality deterioration in available water resources. Thus, the classification of nutrient concentrations in water resources has gained significant attention during recent decades. Machine learning (ML) algorithms are considered an efficient tool to describe nutrient loss from agricultural land to surface water and groundwater. Previous studies have applied regression and classification ML algorithms to predict nutrient concentrations in surface water and/or groundwater, or to categorize an output variable using a limited number of input variables. However, there have been no studies that examined the application of different ML classification algorithms in agricultural settings to classify various output variables using a wide range of input variables. In this study, twenty-four ML classification algorithms were implemented on a dataset from three locations within the Upper Parkhill watershed, an agricultural watershed in southern Ontario, Canada. Nutrient concentrations in surface water were classified using geochemical and physical water parameters of surface water and groundwater (e.g., pH), climate and field conditions as the input variables. The performance of these algorithms was evaluated using four evaluation metrics (e.g., classification accuracy) to identify the optimal algorithm for classifying the output variables. Ensemble bagged trees was found to be the optimal ML algorithm for classifying nitrate concentration in surface water (accuracy of 90.9%), while the weighted KNN was the most appropriate algorithm for categorizing the total phosphorus concentration (accuracy of 87%). The ensemble subspace discriminant algorithm gave the highest overall classification accuracy for the concentration of soluble reactive phosphorus and total dissolved phosphorus in surface water with an accuracy of 79.2% and 77.9%, respectively. This study exemplifies that ML algorithms can be used to signify exceedance of recommended concentrations of nutrients in surface waters in agricultural watersheds. Results are useful for decision makers to develop nutrient management strategies.