Total Nitrogen Concentration In Water Research Articles

Abundance and composition of invertebrate-feeding leeches in relation to fish status in ponds

Leeches feeding on invertebrates are an important component of freshwater communities, including those dominated by fish, but the effects of fish on their abundance and distribution are not well explored. The relative densities and assemblage structure of two leech families, Erpobdellidae and Glossiphoniidae, were studied from May to August 2014 in ponds stocked with low biomass densities of young common carp Cyprinus carpio, too small to prey on leeches (low-fish ponds), and in ponds containing high biomass densities of large (one- or two-year-old) carp (high-fish ponds), using two types of activity traps (placed either on the bottom or near the water surface). The most common and numerous species were Erpobdella octoculata, Helobdella stagnalis, and Erpobdella nigricollis. The traps near the water surface captured relatively small numbers of leeches, yet the catches showed that in summer some of the leeches moved to the upper layers of the water column, which was free of macrophytes. No differences in leech species richness or diversity were found with respect to fish status of ponds; however, bottom erpobdellids were more abundant in high-fish ponds. Redundancy analysis identified the fish status of the ponds and total nitrogen concentration in water as the only significant variables explaining the distribution of leeches among ponds. Species distribution was nested, but the nestedness pattern was not affected by the fish status of the pond. While fish are generally believed to adversely affect macroinvertebrate diversity and abundance, our study shows that some predatory leech species can persist in the presence of fish and possibly indirectly benefit from it.

Do stable carbon and nitrogen isotope values of Nitella flexilis differ between softwater and hardwater lakes?

The composition of stable carbon and nitrogen isotopes (δ13C and δ15N) is widely used for tracking the origin of organic matter (OM) present in lacustrine sediments. These isotopes also define the evolution of OM in food web loops. Charophyte species Nitella flexilis C. Agardh, 1824 can be found in different aquatic environments where it contributes significantly to sediment formation and influences biota function. Therefore, it is crucial to study more about δ13C and δ15N in different lake types. Here, we present the results of the first comprehensive study of N. flexilis δ13C and δ15N, which add to the knowledge of the C and N isotope records of charophytes. We obtained the δ13C and δ15N records of N. flexilis OM from hardwater and softwater lakes and checked for differences between these records. We also analyzed the differences in physical and chemical parameters. Finally, we compared the δ13C and δ15N records with physical and chemical parameters to identify the variables that have the highest influence on N. flexilis δ13C and δ15N values. Our study showed that both δ13C and δ15N did not differ significantly in the two types of lakes, although the lakes had significant differences in several physical and chemical parameters (pH, Ca2+, dissolved inorganic carbon, total phosphorus, conductivity). However, we observed that δ13C values were influenced by light conditions (photosynthetic active radiation, depth, dissolved OM), while δ15N values were influenced by the total nitrogen concentration in water.

GHG Emissions from Drainage Ditches in Peat Extraction Sites and Peatland Forests in Hemiboreal Latvia

We determined the magnitude of instantaneous greenhouse gas (GHG) emissions from drainage ditches in hemiboreal peatlands in Latvia during the frost-free period of 2021 and evaluated the main affecting factors. In total, 10 research sites were established in drained peatlands in Latvia, including active and abandoned peat extraction sites and peatland forests. Results demonstrated that in terms of global warming potential, the contribution of CO2 emissions to the total budget of GHG emissions from drainage ditches can exceed the CH4 contribution. The average CO2 and N2O emissions from drainage ditches in peatland forests were significantly higher than those from ditches in peat extraction sites, while there was no difference in average CH4 emissions from ditches between peatland forests and peat extraction sites. Emissions from ditches of all GHGs increased with increasing temperature. In addition, CO2 and N2O emissions from drainage ditches increased with decreasing groundwater (GW) level. They were also negatively correlated with water level in ditches, but positively with potassium (K) and total nitrogen (TN) concentrations in water. By contrast, CH4 emissions from drainage ditches increased with increasing GW level and water level in ditches but were negatively correlated with K and TN concentrations in water.

Development of Solid-State Chemiresistive Devices for Simultaneous Detection of Nitrate, Nitrite and Ammonium Ions in Aqueous Solutions

The presence of various ions is an important factor in evaluating water quality. Nitrate, nitrite and ammonium in water can cause health issues and pose environmental concerns1,2. Some sources of the nitrogen species are from natural water and some of them arise from industrial and agricultural activities. Currently commercially available sensors for measuring nitrogen compounds in water are based on colorimetric techniques and potentiometric methods incorporating ion selective electrodes. Progress still needs to be made towards fabricating devices with less instrumentation costs, less complexity, less maintenance and without need for any reagents to facilitate measurement of species1. Chemiresistive sensors are solid-state devices which can be simply fabricated from two contacts and a conductive sensing material affixed on a suitable substrate. They operate by detecting modulations in resistance of the conducting film due to surface charge transfer as a result of interactions with the analyte(s)3.Here, we demonstrate chemiresistive devices capable of quantifying aqueous nitrate, nitrite and ammonium ions selectively. Due to challenges in the aqueous phase such as ionic strength effect, probability of side reactions, non-specific bonding on the surface, low interaction energy between analyte and surface, chemiresistive technology has not been developed extensively in water quality sensors4,5. In this study, we have overcome the issues in water by coating the chemiresistive devices with selective membranes. If the fabricated sensors are used as an array, the total nitrogen concentration in water can be measured online which is a significant advance since nitrate, nitrite and ammonium may interconvert and a single nitrate, nitrite or ammonium sensor by itself cannot give the total amount of nitrogen in a sample. For device fabrication, p-doped carbon nanotubes were selected as a sensitive conductive layer which were modified with selective membranes to improve the sensing performance. Nitrite sensors worked over a dynamic range of 67 ppb to 67 ppm with a 27.6% response at 67 ppm. Nitrate showed 13.2% response from 2.2 ppm to 220 ppm. Ammonium devices operated over a dynamic range of 10 ppb to 100 ppm with a 23.6% response at 100 ppm. The proposed response mechanism involves both an electrostatic gating effect and surface charge transfer. Compared with paper-based colorimetric sensors, the proposed devices perform better with a lower detection limit and the ability to perform continuous online measurements. Moreover, the chemiresistive responses of the devices were compared with their potentiometric responses and found to be equally sensitive but more selective. Unlike ion-selective electrodes, the resulting devices do not require the use of reference electrodes and are therefore potentially more robust for use in continuous water analyzers and in resource-poor settings. The chemiresistive devices showed low interferences and good reversibility. They were also tested in river water samples and showed satisfactory results. The fabricated devices are an advanced proof of concept and have the potential to replace the current technology. Nuñez, L., Cetó, X., Pividori, M. I., Zanoni, M. V. B. & del Valle, M. Development and application of an electronic tongue for detection and monitoring of nitrate, nitrite and ammonium levels in waters. Microchem. J. 110, 273–279 (2013).Li, D., Xu, X., Li, Z., Wang, T. & Wang, C. Detection methods of ammonia nitrogen in water: A review. TrAC - Trends Anal. Chem. 127, 115890 (2020).Choi, S. J. & Kim, I. D. Recent Developments in 2D Nanomaterials for Chemiresistive-Type Gas Sensors. Electronic Materials Letters vol. 14 (The Korean Institute of Metals and Materials, 2018).Kruse, P. Review on water quality sensors. J. Phys. D. Appl. Phys. 51, (2018).Dalmieda, J., Zubiarrain-Laserna, A., Saha, D., Selvaganapathy, P. R. & Kruse, P. Impact of Surface Adsorption on Metal-Ligand Binding of Phenanthrolines. J. Phys. Chem. C 125, 21112–21123 (2021). Figure 1

Impacts of soil use and management on water quality in agricultural watersheds in Southern Brazil

AbstractWorldwide, agriculture is considered one of the main activities that influence water quality. The objective of this work was to evaluate the influence of soil use and management on water quality at the small watershed scale, in Southern Brazil. One watershed is characterized by production of annual crop seeds under no‐tillage (zero tillage), with crop rotation and with terraces (Sarandi watershed—SW), while the other is characterized by production of grains in the summer and pasture with grazing in the winter, under no‐tillage, without crop rotation and without terraces (Coxilha watershed—CW). Flow and climatic data were measured during 2 years. Water samples were manually taken at precipitation events and base flow over 1 year for laboratory analysis. During events of high volume, most of the rainfall was converted to base flow in SW, while in CW, most of the rainfall was transformed into overland flow. Overall, higher concentrations and losses of sediments and nutrients occurred in the CW, mainly during precipitation events in the winter crops season. Of the total nitrogen concentration in water, approximately 3% was ammonium‐N and 58% was nitrate‐N, on average, in both watersheds. For total phosphorus concentration in water, more than 75% was particulate in both watersheds, however, the bioavailable phosphorus accounted for 70% of the total phosphorus in the SW and for 35% in the CW. The higher concentration of bioavailable phosphorus in the SW indicates a short‐term pollution potential, but in both watersheds, the water quality was impaired by the high concentrations of total phosphorus. In general, even with no‐tillage, the results highlight the importance of best management practices as terracing, riparian vegetation, crop rotation, better crop systems and fertilizer management to avoid degradation of water resources.

Ensemble machine-learning-based framework for estimating total nitrogen concentration in water using drone-borne hyperspectral imagery of emergent plants: A case study in an arid oasis, NW China

In arid and semi-arid regions, water-quality problems are crucial to local social demand and human well-being. However, the conventional remote sensing-based direct detection of water quality parameters, especially using spectral reflectance of water, must satisfy certain preconditions (e.g., flat water surface and ideal radiation geometry). In this study, we hypothesized that drone-borne hyperspectral imagery of emergent plants could be better applied to retrieval total nitrogen (TN) concentration in water regardless of preconditions possibly due to the spectral responses of emergent plants on nitrogen removal and water purification. To test this hypothesis, a total of 200 groups of bootstrap samples were used to examine the relationship between the extracted TN concentrations from the drone-borne hyperspectral imagery of emergent plants and the experimentally measured TN concentrations in Ebinur Lake Oasis using four machine learning (ML) models (Partial Least Squares (PLS), Random Forest (RF), Extreme Learning Machine (ELM), and Gaussian Process (GP)). Through the introduction of the fractional order derivative (FOD), we build a decision-level fusion (DLF) model to minimize the regression results’ biases of individual ML models. For individual ML model, GP performed the best. Still, the amount of uncertainty in individual ML models renders their performance to be subpar. The introduction of the DLF model greatly minimizes the regression results’ biases. The DLF model allows to reduce potential uncertainties without sacrificing accuracy. In conclusion, the spectral response caused by nitrogen removal and water purification on emergent plants could be used to retrieve TN concentration in water with a DLF model framework. Our study offers a new perspective and a basic scientific support for water quality monitoring in arid regions.

Purification of Forest Clear-Cut Runoff Water Using Biochar: A Meso-Scale Laboratory Column Experiment

Biochar can be an effective sorbent material for removal of nutrients from water due to its high specific surface area, porous structure, and high cation and anion exchange capacity. The aim of this study was to test a biochar reactor and to evaluate its efficiency in runoff water purification and consecutive nutrient recycling in clear-cut peatland forests. The goodness of the method was tested in a meso-scale (water volume thousands of liters) reactor experiment by circulating runoff water through wood biochar-filled columns and by determining water nutrient concentrations in the column inlet and outlet. The pseudo-first and second order kinetic models were fitted to the experimental data and the adsorption rate (Kad) and maximum adsorption capacity (Qmax) of the biochar reactor were quantified. The concentration of total nitrogen (TN) decreased by 58% during the 8-week experiment; the majority of TN adsorption occurred within the first 3 days. In addition, NO3-N and NH4-N concentrations decreased below the detection limit in 5 days after the beginning of the experiment. The maximum adsorption capacity of the biochar reactor varied between 0.03–0.04 mg g−1 biochar for NH4-N, and was equal to 0.02 mg g−1 biochar for TN. The results demonstrated that the biochar reactor was not able to adsorb TN when the water TN concentration was below 0.4 mg L−1. These results suggest that a biochar reactor can be a useful and effective method for runoff water purification in clear-cut forests and further development and testing is warranted. Unlike traditional water protection methods in peatland forestry, the biochar reactor can effectively remove NO3-N from water. This makes the biochar reactor a promising water protection tool to be tested in sites where there is the risk of a high rate of nutrient export after forest harvesting or drainage.

Analysis of accumulation formation of sediment contamination in reservoirs after decades of running: a case study of nitrogen accumulation in Biliuhe Reservoir.

Sediment contamination is an important influencing factor for reservoir water quality. Investigations have shown that reservoirs are facing the risk of sediment contamination after running for several decades in China. This paper proposes that the accumulation of sediment contaminant is resulted from the difference between the input and output of contaminant. Further, an accumulation model of reservoir sediment nitrogen is established based on this theory. The calculation result of Biliuhe Reservoir shows that inflow rate of total nitrogen into the reservoir is 4521.47t/a, the outflow rate is 1033.97t/a, nitrogen removal by denitrification is 1465.81t/a, and the accumulation rate is 1841.68t/a. The accumulation rate of total nitrogen is 77.84t/a in water, 924.42t/a in suspended solids, and 839.42t/a in sediment. The accumulation of nitrogen resulted in the total nitrogen concentration in water increasing from 1.71mg/L in 1995 to 3.78mg/L in 2013, and that in sediment increasing from 779.10mg/kg in 1993 to 2725.00mg/kg in 2013. It is concluded that sediment contamination has the characteristics of significant accumulation trend, complex forms, and high security risks, which has been a hidden security risk for reservoirs after decades of running. Heterogeneity of the reservoir and complicated influencing factors of sediment contaminant accumulation should be concerned next.

Long term (1997-2014) spatial and temporal variations in nitrogen in Dongting Lake, China.

In order to protect the water quality of Dongting Lake, it is significant to find out its nitrogen pollution characteristics. Using long-term monthly to seasonally data (1997–2014), we investigated the spatial and temporal variations in nitrogen in Dongting Lake, the second largest freshwater lake in China. The average concentrations of total nitrogen (TN) in the eastern, southern, and western parts of the lake were 1.77, 1.56, and 1.35 mg/L, respectively, in 2014. TN pollution was generally worse in the southern area than in the western area. Concentrations showed temporal variation, and were significantly higher during the dry season than during the wet season. Based on the concentration and growth rate of TN, three different stages were identified in the long term lake data, from 1997 to 2002, from 2003 to 2008, and from 2009 to 2014, during which the concentrations and the growth rate ranged from 1.09–1.51 mg/L and 22.09%-40.03%, 1.05–1.57 mg/L and -9.05%-7.74%, and 1.68–2.02 mg/L and 57.99%-60.41%, respectively. The main controls on the lake water TN concentrations were the quality and quantity of the lake inflows, spatial and temporal variations in hydrodynamic conditions within the lake (flow velocity, flow direction), and point and nonpoint inputs from human activities. Diffuse nutrient losses from agricultural land are a significant contributor. As a priority, the local government should aim to control the pollutant inputs from upstream and non-point nutrient losses from land.

Integration of Bayesian analysis for eutrophication prediction and assessment in a landscape lake.

Eutrophication models have been widely used to assess water quality in landscape lakes. Because flow rate in landscape lakes is relatively low and similar to that of natural lakes, eutrophication is more dominant in landscape lakes. To assess the risk of eutrophication in landscape lakes, a set of dynamic equations was developed to simulate lake water quality for total nitrogen (TN), total phosphorous (TP), dissolve oxygen (DO) and chlorophyll a (Chl a). Firstly, the Bayesian calibration results were described. Moreover, the ability of the model to reproduce adequately the observed mean patterns and major cause-effect relationships for water quality conditions in landscape lakes were presented. Two loading scenarios were used. A Monte Carlo algorithm was applied to calculate the predicated water quality distributions, which were used in the established hierarchical assessment system for lake water quality risk. The important factors affecting the lake water quality risk were defined using linear regression analysis. The results indicated that the variations in the landscape lake receiving recharge water quality caused considerable landscape lake water quality risk in the surrounding area. Moreover, the Chl a concentration in lake water was significantly affected by TP and TN concentrations; the lake TP concentration was the limiting factor for growth of plankton in lake water. The lake water TN concentration provided the basic nutritional requirements. Lastly, lower TN and TP concentrations in the receiving recharge water caused increased lake water quality risk.

基于湿地植物光谱的水体总氮估测

利用再生水补充城市湿地是目前湿地恢复与重建的主要方向,然而再水中高浓度的氮、磷含量极易导致水体富营养化。遥感技术已成为富营养化监测的重要手段,但对于植被覆盖水域的富营养化直接探测存在一定的局限性。以北京市典型再生水补水湿地奥林匹克公园南园湿地为研究区,利用湿地植物光谱进行水体富营养化主控因子总氮的遥感探测。测定芦苇(<em>Phragmites australis</em>)和香蒲(<em>Typha angustifolia</em>)的叶片光谱及水体总氮含量,在对数据进行预处理的基础上建立二者的关系模型,包括单变量模型(比值光谱指数(SR)模型和归一化差值光谱指数(ND)模型),与多变量模型(逐步多元线性回归(SMLR)模型和偏最小二乘回归(PLSR)模型),并利用交叉验证决定系数(<em>R</em>_cv²)和均方根误差(RMSE_cv)进行模型精度检验。结果表明,不同回归模型相比,多变量回归模型精度较高;多变量回归模型中,PLSR模型精度较高,<em>R</em>_cv²可达0.72,RMSE_cv仅为0.24,是建立湿地植物光谱与水体总氮含量关系的最优模型。不同湿地植物类型相比,利用芦苇反射光谱建立的各种预测模型的精度都高于香蒲。其他环境因子(总磷)也是影响TN含量与湿地植物反射光谱关系的重要因素。研究成果可以弥补现有水体富营养化遥感探测的不足,并为再生水利用的城市湿地水质监测与管理提供有力的科学依据。;Supplying urban wetlands with reclaimed water is recognized as a superior way for wetland restoration and reconstruction. However, the high concentration of nitrogen and phosphorus in reclaimed water can easily lead to water eutrophication. Although remote sensing technology has become a useful tool to monitor the eutrophication of water body, it is usually employed to detect eutrophication in open water. Limited applications have been found in measuring eutrophication of wetland covered by vegetation. Utilizing plants spectral response to environment can monitor environmental changes. This study explores the possibility to use wetland vegetation reflectance spectra in estimating total nitrogen content which is one of the key indicators of water eutrophication. The South Wetland in the Olympic Park in Beijing, a typical wetland using reused water, was selected as our study area. The leaf reflectance spectra of main wetland plants, reed (<em>Phragmites australis</em>) and cattail (<em>Typha angustifolia</em>), were acquired by means of an ASD FieldSpec 3 spectrometer (350-2500nm). Water quality samples were collected at the same time and analyzed by Center for Environmental Quality Test, Tsinghua University subsequently. The research established several univariate models including simple ratio spectral index (SR) model and normalized difference spectral index (ND) model, as well as multivariate models including stepwise multiple linear regression (SMLR) model and partial least squares regression (PLSR) model. The accuracy of these models was tested through cross-validated coefficient of determination (<em>R</em>_cv²) and cross-validated root mean square error (RMSE_cv). The results have shown that 1) In comparison with univariate techniques, multivariate regressions can improve the estimation of total nitrogen concentration in water. The accuracy of PLSR model was the highest (<em>R</em>_cv²=0.72, RMSE_cv=0.24) among all models. PLSR provides the most useful explorative tool for unraveling the relationship between spectral reflectance of wetland plants and total nitrogen content in water at leaf scale. 2) The accuracy of prediction models built in this study using <em>Phragmites australis</em> reflectance spectra is higher than those using <em>Typha angustifolia</em> reflectance spectra. 3) Other environmental factors should also be discreetly considered in modeling exercise. Total phosphorus is found to have impact on the relationship between TN and reflectance spectra from wetland vegetation. Strong predictive power for multiple regression equations has been achieved when the range of total phosphorus was restricted. The result from this study can not only fill the gaps in the detection of eutrophication using remote sensing, but also provide a strong scientific basis for the water quality monitoring and management of urban wetlands using recycled water.

RETRACTED: Research on the Effect of Sewage Concentration on Treatment Efficiency of Constructed Wetlands

Retracted article: By changing the surface flow(SF) and subsurface flow (SSF)constructed wetlands inflow water total nitrogen (TN) concentrations, with 6 plant species (purple leaf canna, water onion, water hyacinth, water celery, calamus, reed) in comparative experiments, comparative analysis of the 6 different SF and SSF constructed wetlands treatment rate with the variation of the concentration obtained in the 6 different plant SF and SSF constructed wetlands, the optimal concentration theory, theory of optimal removal rate, the actual optimal concentration, the actual optimal removal rate and TN maximum daily processing load. The results showed that: in the 6 different plant of SF and SSF constructed wetlands for TN removal efficiency decreased as the concentration increased, different plant, different levels of treatment rate reduction, and removal value of SSF was lower than SF. Purple leaf canna removal reduced the minimum, SF processing rate decreased 17.07%, SSF dropped 15.94%; Reed removal rate decreased obviously, the SF processing rate decreased 20.86%, SSF dropped 18.2%. Meanwhile, according to the result of the experiment, the maximum TN daily remove quantity in the six species of plants of SF constructed wetland was 547.20 g•m-2•d-1;in SSF constructed wetland was 577.60 g•m-2•d-1. Wetland as an efficient, low consumption of new sewage treatment technology has been widely accepted, especially in total nitrogen (TN) in the application phase for the people attention. Study found that of nitrogen removal efficiency of constructed wetlands and external factors, a wetland substrate, plant species, microbes, sewage load, residence time, nitrogen in sewage and water distribution methods[1]. For the wastewater load on the removal of wetlands, Zhou Yaohua so that low concentration of domestic sewage (20% water) on the ground flora as a whole more effective than a higher concentration of the decontamination wastewater (100% effluent) better overall removal [2]. Cui Fang water residence time in the study of the impact of decontamination capability of wetlands that the reed wetland water CODcr, TP, NH3-N concentration had little effect on the removal, and TN concentrations had a significant effect on the removal, removal of only 27% [3], Yuan Donghai and others that wetlands on the initial concentration of pollutants in wastewater have certain requirements, low pollution case, the constructed wetland was better; higher concentration of pollutants cases, the purification efficiency dropped [4]. Effluent decontamination effect on the wetland will have some impact, at present, domestic and international research to a single species of plants, mainly a single type of wetland, considering the different plants, different types of comparative study of wetlands was less. By changing SF and SSF constructed wetlands, inflow water TN concentrations, with 6 plant speciesin comparative experiments, comparative analysis of the 6 different plants of SF and SSF constructed wetlands treatment rate with the variation of the concentration obtained in 6 different plant SF and SSF constructed wetlands, the optimal concentration theory, theory of optimal removal rate, the actual optimal concentration, optimal removal rate and the actual TN maximum daily processing load, optimizing the hydraulic conditions of wetlands. Research on the promotion of artificial wetland technology, further development of eco-environmental rehabilitation has a certain significance

Magnitude of Blue-Green Algal Blooms in a Saline Desert Lake Evaluated by Remote Sensing: Evidence for Nitrogen Control

Seventy-six percent of the 1972–86 variability in remotely sensed maximum surface water biomass of Nodularia spumigena blooms in Pyramid Lake, Nevada, was explained by concentrations of surface water total nitrogen (TN) during the preceding winter circulation. Very large summer–autumn Nodularia blooms were recorded by Landsat subsequent to low early winter surface water TN concentrations, very low fluvial discharge, and fluvial TN loads as predicted, but contrary to predictions, also when fluvial discharge and TN loads were very high. The observed cause of large Nodularia blooms following high fluvial nitrogen influx was temporary meromixis produced by the large volume of freshwater transporting this nitrogen. Incomplete winter lake circulation reduced internal transport of hypolimnetic nitrogen to surface waters. Meromixis resulted in early stable summer thermal stratification and early depletion of epilimnetic inorganic nitrogen, followed by early and large Nodularia blooms. Variations in magnitude of historic Nodularia blooms in a saline desert lake support the generality of blue-green algal dominance in lakes with low nitrogen and high phosphorus concentrations (i.e. low N:P ratios). However, climatic forcing of fluvial discharge and lake mixing patterns were also shown to be important determinants of seasonal succession of phytoplankton to blue-greens.