Nitrate Concentrations In Water Research Articles

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.

Prenatal exposure to nitrosatable drugs and timing of puberty in sons and daughters: A nationwide cohort study.

N-nitroso compounds (NOCs) can be formed by endogenous reactions between nitrosatable drugs and nitrite. Animal studies have found that several NOCs are teratogenic, and epidemiological studies report associations between prenatal exposure to nitrosatable drugs and adverse birth outcomes. It is unknown whether prenatal exposure to nitrosatable drugs is harmful to the child's reproductive health, including pubertal development. We investigated whether prenatal exposure to nitrosatable drugs was associated with timing of puberty and whether nitrate, nitrite and antioxidant intake modified any association. The population-based Danish National Birth Cohort (DNBC) Puberty Cohort, which includes 15,819 children, was used to investigate the association between prenatal exposure to nitrosatable drugs and timing of puberty. Around gestational week 11 and gestational week 18, mothers provided information about drug use during pregnancy. The children's self-reported information on onset of pubertal milestones was collected every six months from 11 years of age and throughout puberty. To investigate potential effect modification by nitrite, nitrate and antioxidant intake, information on these factors was obtained from a food frequency questionnaire completed by the mothers in gestational week 25, and information on nitrate concentration in maternal drinking water at her residential address was obtained from monitoring data from public waterworks. Data were analysed using a multivariable regression model for interval-censored data estimating difference in months in timing of puberty between exposure groups. A total of 2,715 children were prenatally exposed to nitrosatable drugs. We did not find an association between prenatal exposure to nitrosatable drugs and timing of puberty. This finding was supported by null-findings in the following sub-analyses investigating: 1. subtypes of nitrosatable drugs (secondary and tertiary amines and amides), 2. dose-dependency (duration of drug intake), 3. effect modification by maternal intake of nitrate, nitrite, and antioxidants. 4. confounding by indication. Prenatal exposure to nitrosatable drugs was not associated with timing of puberty. Nitrosatable drugs are commonly used drugs in pregnancy, and further research is needed to allow firm conclusions on the potential effect of prenatal exposure to nitrosatable drugs on the child's reproductive health.

Douglas-fir plantations impact stream and groundwater chemistry in western Europe: Insights from three case studies in France and Luxembourg

In rural areas, nitrate concentrations in surface waters most often originate from the leaching of excess N fertilizer in agricultural lands, whereas forested catchments often have good water quality. However, Douglas-fir plantations may induce nitrogen cycle unbalances which may lead to an excess of nitrate production in the soil. We hypothesize that the excess of production of nitrate in the soil and nitrate leaching to streamwater is greater in catchments planted with Douglas fir. We used paired catchments in both France and Luxembourg with different land covers (Douglas-fir, Spruce, Deciduous, Grassland and clearcut) which were monitored over a 3–5 year period in order to assess the effect of Douglas-fir plantations on the chemical composition of surface water. Nitrate concentration in the soil and groundwater were also monitored. The results show that nitrate concentrations in streams draining Douglas-fir catchments were two to ten times higher than in streams draining other land covers, but were similar to the clearcut catchment. Nitrate concentrations under Douglas-fir in groundwater (up to 50 mg L−1) and in the soil were also higher than under all other land covers. Soil nitrate concentration was related to stream nitrate concentration. This suggests that soil processes, through excessive nitrate production under Douglas-fir, are driving the nitrate concentration in the stream water and our hypothesis of a transfer of a fairly large proportion of this excessive production from the soil to the stream is supported. This study also shows that nitrate concentrations in surface and ground waters in rural areas could also originate from Douglas fir forested catchments. The impact of Douglas-fir is nevertheless reduced downstream through a dilution effect: mixing tree species at the catchment scale could thus be a solution to mitigate the effect of Douglas-fir on nitrate concentration in surface waters.

Research on On-Line Detection Method and System for Nitrate in Groundwater

In order to monitor the concentration of nitrate in groundwater and evaluate water quality, a specialized sensor has been developed to solve the problems of the passivation effect, short life and poor repeatability of electrodes in conventional electrochemical detection, a novel preparation method of copper-sensitive film was proposed, and the method was combined with a microelectrochemical sensing electrode to detect nitrate in water. Microfabrication technology was used to prepare the micro sensor electrode. A total of 0.05 mol/L CuSO4 was added into the supporting electrolyte, and the dissolution and deposition of copper on the surface of the working electrode and the catalytic reduction reaction of nitrate ions were performed. On-line cleaning of microelectrode, in situ deposition of copper-sensitive film and detection of nitrate concentration in water were realized, respectively. An on-line modified electrode was used to detect the nitrate standard sample, achieving a high detection sensitivity (0.031 μA/[μmol L−1]) in the concentration range of 0–3500 μmol/L. The relative standard deviation of the same nitrate standard sample repeated for 15 times was only 2.48%, which improved the long-term repeatability of nitrate detection, and, at the same time, an on-line system was adopted that included an on-line detection system (DS) and a wireless transmission system (WS).

In situ temperature-compensated ultraviolet spectrophotometry to estimate nitrate and chloride concentrations in estuarine seawater with different salinity and composition

Various methods have been proposed for in situ measurement of nitrate concentrations from the ultraviolet (UV) absorbance spectrum of seawater with stable salinity and constituents. However, salinity and temperature affect the UV absorption spectrum of seawater. In sea areas with large variability in salinity and water temperature, accurate nitrate ion concentration measurements remain challenging. We performed in situ measurements of nitrate, chloride, and bromide in estuarine seawater with different salinity compositions and applied water temperature compensation. First, the impact of water temperature on the UV absorbance of chloride, bromide, and nitrate was experimentally investigated and represented in a mathematical model. Next, chloride, bromide, and nitrate concentrations were estimated by suppressing the impact of residual components from the UV absorbance spectra of seawater using principal component regression (PCR). Hence, the chloride, bromide, and nitrate concentrations were determined by measuring the UV absorbance spectrum of seawater alone, without measuring water temperature and electrical conductivity. The proposed method was more accurate (±1.39 μM below 100 μM and ±0.90 μM below 20 μM) than the conventional method (±2.35 μM below 100 μM and ±1.88 μM below 20 μM) and PCR without water temperature compensation (±3.67 μM). In a field study, an in situ UV spectrophotometer with water temperature compensation was used to measure depth profiles of nitrate concentrations in estuarine seawater. We successfully measured the depth profiles of low chloride and high nitrate concentrations in the surface layer as well as high chloride and low nitrate concentrations in the lower layer. The proposed method enables in situ measurements of nitrate concentrations in waters with either stable or highly variable salinity and composition. Unlike conventional chemical analysis, our method can describe detailed spatiotemporal variations in nitrate concentrations.

Measuring Nitrate Leaching in the Vadose Zone of Loess Soils—Comparison of Batch Extraction and Centrifugation

The nitrate concentration in the subsoil moisture of the vadose zone is an important indicator for future groundwater quality, which is classically determined via centrifugation. Batch extraction is an inexpensive and easy alternative method, but whether these methods measure the same soil water, nitrogen species, and nitrate concentrations is unclear, in particular for loess soils. Two experiments were carried out to assess the differences in nitrate and other anion concentrations between centrifugated soil moisture (centrifugated at different speeds and times) and batch extractions (using double-distilled water and 0.01 M CaCl2). Batch extraction resulted in lower nitrate (−20%) and chloride (−15%) concentrations than centrifugation, mainly due to anion exclusion, where soil microporosity controls the contribution of diffusion, denitrification, and leaching processes. Vice versa, batch extraction overestimated the concentration of nutrients that occur as precipitates in or sorb the soil matrix, such as sulphate (+50%) and ammonium (+96%). Batch extractions can only be used as a proxy to determine actual nitrate concentrations of soil water. However, they are useful to monitor changes in nitrate leaching over time in response to (policy) measures taken. They can also be used as “early warning indicator” and to improve the reliability of spatial explicit monitoring networks.

Using Remote and Proximal Sensing in Organic Agriculture to Assess Yield and Environmental Performance

Satellite and sensor-based systems of site-specific fertilization have been developed almost exclusively in conventional farming. Agronomic and ecological advantages can also be expected from these digital methods in organic farming. However, it has not yet been investigated whether the algorithms and models are also applicable under organic farming conditions. In this study, the digital data and systems tested in the years 2021 and 2022 in southern Germany were (a) reflectance measurements with a tractor-mounted multispectral sensor, calculation of the vegetation index REIP, and application of algorithms; (b) satellite data in combination with the plant growth model PROMET; and (c) determination of the vegetation index NDVI based on satellite data. They were used to determine plant parameters (crop yield, biomass potential) and to calculate nitrogen balances at a high spatial resolution (10 × 10 m). The digital systems were tested at two sites with different organic farming systems (arable farming and dairy farming). Validation of the digital methods was carried out with ground-truth data from manual biomass sampling and combine harvester yield measurement. The nitrate leaching risk from the crop rotations of the farms was analyzed via site-specific N balancing using multi-year satellite data. The N balances were validated by measuring nitrate concentrations in leakage water. Additionally, soil properties, such as soil organic carbon (SOC) and total nitrogen (TN), were measured at the sub-field level. Using geostatistics, plant data, soil properties, and nitrate measurements were transferred into grids of the same resolution to enable correlation analyses. The correlations between yield determined with digital systems and the validation data were up to r = 0.77. Site-specific N balancing showed moderately positive correlations with nitrate concentrations in leakage water (r = 0.50–0.66). The strongly positive influence of the soil properties SOC and TN on crop yields underlines the importance of soil organic matter on soil fertility and site-specific yield potentials. The results show that digital methods allow the spatially high-resolution determination of yields and nitrogen balances in organic farming. This can be the basis for new management strategies in organic farming, e.g., the targeted use of limited nutrients to increase yields. Further validations under differentiated soil, climate, and management conditions are required to develop remote and proximal sensing applications in organic farming.

Predictive modeling and analysis of key drivers of groundwater nitrate pollution based on machine learning

Nitrate comtamination of shallow groundwater in agricultural intensification regions is a prevalent and global environment issue affecting food security, human health, and the water ecology. Developing a prediction model for groundwater nitrate contamination is crucial for protection of groundwater resources. Machine learning modeling offer potentials to predict contamination, but often fails to adequately screen input features in complex non-linear environments before modeling. Additionally, there is a tendency to overlook the interpretable description of the relationship between major water chemistry parameters and nitrate concentration after modeling, which hinders scientific decision-making by water resource managers. In this study, a dataset consisting of hydrochemical test results from 316 groundwater samples collected between 2011 and 2015 in intensive agricultural areas of Northeast China was collected. Prior to modeling, the dataset was grouped based on land use type, vadose zones types, and thickness. Based on the grouping of data sets, self-organizing map (SOM) and Spearman's coefficients were employed to identity the correlations between water chemical parameters and nitrate concentration (NO3–-N), which provided a logical basis for selecting the key input variables. A radial basis function artificial neural network (RBF ANN) prediction model and principal components regression (PCR) models was constructed using the dataset, and particle swarm optimization algorithm was applied to determine optimal parameter combinations of the RBF ANN. After conducting modeling, the advantages and disadvantages of RBF ANN and principal components regression (PCR) models were thoroughly examined and discussed, and the primary factors that impact nitrate concentrations in groundwater were analyzed using a PCR model. The results revealed that the RBF ANN model showed greater accuracy, while the PCR model offered better interpretability. Therefore, the integration of the two models is advantageous for nitrate prediction research. Human activities, rainfall, land-use types, vadose zones types and thickness are external factors that affecting nitrate concentration, and the difference between nitrification. Denitrification, and dissimilatory nitrate reduction to ammonium (DNRA) is internal driving factors for the change of nitrate concentration in the aquifer, and partially determine differences in the spatial distribution of aquifer nitrate concentrations under various land use types. This study provides a comprehensive approach for predicting nitrate pollution in groundwater under non-linear environmental conditions, supporting decision making in sustainable groundwater development, management, and conservation.

Variation of some Water Quality Parameters with Fluctuation of Groundwater Table in Wana Sub-District Northern Iraq

This study aims to investigate the effect of groundwater fluctuation on some water quality characteristics in the Wana region of Northern Iraq. The fluctuations in water table levels in 18 tube wells were monitored to find out if there is a relationship between water table levels with some water quality factors. Groundwater samples were collected monthly from September 2020 to April 2021. Electric conductivity (EC), temperature, pH, water table level, total hardness (TH), sulfate and nitrate concentrations were all measured monthly for eight months. The results showed a wide range of water salinity variation ranging from 715 to 4420 µmohs/cm, with more than half of the examined samples exceeding 3000 µmohs/cm. Even in the same wells, water salinity varied during the monthly monitoring. The depth to the water table ranged from 3.39 to 37.56 m, depending on the topography, recharge rate, and aquifer conditions in the area. All of the wells produced very hard water as a result of the dissolution of gypsum and anhydrite bedrock, with about 84% having high sulphate concentrations of over 250 mg/l. More than a quarter of the samples tested showed pollution with nitrate at concentrations extremely close to or over 50 mg/l. It was found that there is no obvious correlation between groundwater quality properties and the fluctuation of the water table.

Changes of inorganic nitrogen compounds concentration in a mining enterprise wastewater by the microalgae Chlorella vulgaris

Wastewater contamination by nitrogen compounds is a serious problem for the mining, industrial and utility companies. Nitrogen can enter quarry effluent when explosives containing ammonium nitrate are used in blasting operations. This nitrogen pollution of water leads to environmental damage and human disease, companies that exceed the legal limits for nitrogen pollution are subject to fines. Nitrogen is removed from wastewater by biological methods, but their efficiency is low in the Northern regions of Russia due to climatic factors that hinder the vital activity of organisms. Therefore, it is essential to develop wastewater treatment technologies for the removal of nitrogen compounds. This study focuses on the ability of the microalgae Chlorella vulgaris to absorb and utilize various inorganic nitrogen compounds in mining effluents using the example of effluents from the "Karelsky Okatysh" mine and tailings dam (Kostomuksha, Republic of Karelia). Concentrations of ammonium, nitrate and nitrite in water and microalgal biomass in water samples have been investigated. A novelty of the study is the evaluation of pollutant concentrations in parallel experiments with different cultivation conditions. It has been found that when Chlorella vulgaris is cultivated at 26 °C, aeration and artificial light, the concentration of ammonium decreases. These results show the promising application of bioreactor technologies for the treatment of ammonium polluted wastewater.

Organic Carbon, Nitrogen Accumulation and Nitrogen Leaching as Affected by Legume Crop Residues on Sandy Loam in the Eastern Baltic Region.

Legumes have a wide range of positive effects on soil properties, including nitrogen and carbon storage, soil structure and the phytosanitary condition of crops. From an agronomic point of view, legumes are most valued for their ability to take up atmospheric nitrogen in symbiosis with nitrogen-fixing bacteria. The aim of this research was to determine the effect of legume residues (peas, fodder beans, narrow-leaved lupins) on the N (Ntotal) and organic carbon (Corg) accumulation in soil and N leaching under temperate climate conditions. The experiment was carried out in lysimetric equipment in 2016-2023. The effect of legumes on Corg and Ntotal accumulation in soil and N leaching were studied in a Fabaceae-Cereals sequence. Three species of legumes-peas, fodder beans and narrow-leaved lupines-were tested; spring barley (Hordeum vulgare L.) was grown as a control treatment. The lysimeter surface area was 1.75 m2 and the experimental soil layer was 0.60 m (sand loam Haplic Luvisol). It was found that after harvesting, more residues were incorporated into the soil with lupines (p < 0.05), which, compared to pea and bean residues, increased Ntotal and Corg concentrations in the soil. There was a strong correlation (r = 0.95) between the Ntotal concentration in the soil and the N amount incorporated with residues. Mineral N released during residue decomposition was leached from the humic horizon under conditions of excess moisture in the autumn-winter period and increased the nitrate concentration in the lysimeter water. The increase in concentration was recorded within 5 to 6 months after the application of the residues. As a result, the N leaching losses increased on average by 24.7-33.2% (p < 0.05) during the year of legume cultivation. In the following year, after legume residue incorporation, the effect of residues on nitrate concentration and N leaching decreased and did not differ significantly from that of barley residues.

Temporal and Spatial Distribution Characteristics and Source Analysis of Nitrate in Surface Water of Wuding River Basin

The Wuding River Basin is a first-class tributary of the Yellow River, and the quality of its water ecological environment has a profound impact on the ecological protection and high-quality development of the Yellow River Basin. In order to identify the source of nitrate pollution in the Wuding River Basin, surface water samples of the Wuding River were collected from 2019 to 2021, and the temporal and spatial distribution characteristics and influencing factors of nitrate concentration in surface water in the basin were explored. Nitrogen and oxygen isotope tracer technology and the MixSIAR model were used to qualitatively and quantitatively determine the sources of surface water nitrate and their contribution rates. The results showed that there were significant spatial and temporal differences in nitrate concentrations in the Wuding River Basin. In terms of time, the mean concentration of NO-3-N in surface water in the wet season was higher than that in the flat-water period; spatially, the mean concentration of NO-3-N in the downstream surface water was higher than that in the upstream. The spatial and temporal differences in surface water nitrate concentrations were mainly affected by rainfall runoff, soil types, and land use types. The main sources of nitrates in the surface water of the Wuding River Basin during the wet season were domestic sewage, manure, chemical fertilizers, and soil organic nitrogen, whose contribution rates were 43.3%, 27.6%, and 22.1%, respectively, and the contribution rate of precipitation was only 7.0%. There were differences in the contribution rate of nitrate pollution sources in surface water of different river sections. The contribution rate of soil nitrogen in the upstream was significantly higher than that in the downstream, which was 26.5%. The contribution rate of domestic sewage and manure in the downstream was significantly higher than that in the upstream, which was 48.9%. To provide a basis for the analysis of nitrate sources and pollution control in Wuding River and even rivers in arid and semi-arid regions.

KARAKTERISTIK DISTRIBUSI ZAT HARA NITRAT DAN FOSFAT PADA AIR DAN SEDIMEN DI ESTUARIA TANJUNG LIMAU KOTA BONTANG KALIMANTAN TIMUR

This research was conducted in May 2021 - January 2022. The purpose of this study was to determine the distribution of nitrate and phosphate content in water and sediment in the Tanjung Limau estuary, Bontang City, East Kalimantan. Sampling of water and sediment was carried out at 4 research stations using a random method which was then analyzed at the Water Quality Laboratory and Soil Science Laboratory of PPLH Mulawarman University. The results showed that the nitrate content in the water was 0.012-0.018mg/L, 4.20-9.09% in the sediment, while the phosphate in the water was 0.014-0.077 mg/L and the phosphate in the sediment was 0.021-0.030%. The results of the analysis show that the nitrate and phosphate content is higher at Station 1 and lower towards Station 4. There is a significant difference between the nitrate and phosphate content in the water and in the sediment. The content of nitrate and phosphate is mostly sourced from upstream of the river, namely in residential areas and mangrove forests.

Identifying nitrate sources and transformations in an agricultural watershed in Northeast China: Insights from multiple isotopes

Accurate identification of riverine nitrate sources is required for preventing and controlling nitrogen contamination in agricultural watersheds. The water chemistry and multiple stable isotopes (δ15N–NO3, δ18O–NO3, δ2H–H2O, and δ18O–H2O) of the river water and groundwater in an agricultural watershed in China's northeast black soil region were analyzed to better understand the sources and transformations of riverine nitrogen. Results showed that nitrate is an important pollutant that affects water quality in this watershed. Affected by factors such as seasonal rainfall changes and spatial differences in land use, the nitrate concentrations in the river water showed obvious temporal and spatial variations. The riverine nitrate concentration was higher in the wet season than in the dry season, and higher downstream than upstream. The water chemistry and dual nitrate isotopes revealed that riverine nitrate came primarily from manure and sewage (M&S). Results from the SIAR model showed that it accounted for more than 40% of riverine nitrate in the dry season. The proportional contribution of M&S decreased during the wet season due to the increased contribution of chemical fertilizers and soil nitrogen induced by large amounts of rainfall. The δ2H–H2O and δ18O–H2O signatures implied that interactions occurred between the river water and groundwater. Considering the large accumulation of nitrates in the groundwater, restoring groundwater nitrate levels is essential for controlling riverine nitrate pollution. As a systematic study on the sources, migration, and transformations of nitrate/nitrogen in agricultural watersheds in black soil regions, this research can provide a scientific support for nitrate pollution management in the Xinlicheng Reservoir watershed and provide a reference for other watersheds in black soil regions in the world with similar conditions.