Measured Nitrate Concentrations Research Articles

The Development of a Novel Nitrate Portable Measurement System Based on a UV Paired Diode-Photodiode.

Nitrates can cause severe ecological imbalances in aquatic ecosystems, with considerable consequences for human health. Therefore, monitoring this inorganic form of nitrogen is essential for any water quality management structure. This research was conducted to develop a novel Nitrate Portable Measurement System (NPMS) to monitor nitrate concentrations in water samples. NPMS is a reagent-free ultraviolet system developed using low-cost electronic components. Its operation principle is based on the Beer-Lambert law for measuring nitrate concentrations in water samples through light absorption in the spectral range of 295-315 nm. The system is equipped with a ready-to-use ultraviolet sensor, light emission diode (LED), op-amp, microcontroller, liquid crystal display, quartz cuvette, temperature sensor, and battery. All the components are assembled in a 3D-printed enclosure box, which allows a very compact self-contained equipment with high portability, enabling field and near-real-time measurements. The proposed methodology and the developed instrument were used to analyze multiple nitrate standard solutions. The performance was evaluated in comparison to the Nicolet Evolution 300, a classical UV-Vis spectrophotometer. The results demonstrate a strong correlation between the retrieved measurements by both instruments within the investigated spectral band and for concentrations above 5 mg NO3-/L.

Enhancing groundwater vulnerability assessment for improved environmental management: addressing a critical environmental concern

Groundwater serves as a primary water source for various purposes. Therefore, aquifer pollution poses a critical threat to human health and the environment. Identifying the aquifer’s highly vulnerable areas to pollution is necessary to implement appropriate remedial measures, thus ensuring groundwater sustainability. This paper aims to enhance groundwater vulnerability assessment (GWVA) to manage aquifer quality effectively. The study focuses on the El Orjane Aquifer in the Moulouya basin, Morocco, which is facing significant degradation due to olive mill wastewater. Groundwater vulnerability maps (GVMs) were generated using the DRASTIC, Pesticide DRASTIC, SINTACS, and SI methods. To assess the effectiveness of the proposed improvements, 24 piezometers were installed to measure nitrate concentrations, a common indicator of groundwater contamination. This study aimed to enhance GWVA by incorporating new layers, such as land use, and adjusting parameter rates based on a comprehensive sensitivity analysis. The results demonstrate a significant increase in Pearson correlation values (PCV) between the produced GVMs and measured nitrate concentrations. For instance, the PCV for the DRASTIC method improved from 0.42 to 0.75 after adding the land use layer and adjusting parameter rates using the Wilcoxon method. These findings offer valuable insights for accurately assessing groundwater vulnerability in areas with similar hazards and hydrological conditions, particularly in semi-arid and arid regions. They contribute to improving groundwater and environmental management practices, ensuring the long-term sustainability of aquifers.

Evaluation of Nitrogen Oxide Reduction Performance in Permeable Concrete Surfaces Treated with a TiO2 Photocatalyst.

Fine dust, recently classified as a carcinogen, has raised concerns about the health effects of air pollution. Vehicle emissions, particularly nitrogen oxide (NOx), contribute to ultrafine dust formation as a fine dust precursor. A photocatalyst, such as titanium dioxide (TiO2), is a material that causes a catalytic reaction when exposed to light, has exceptional characteristics such as decomposition of pollutants, and can be used permanently. This study aimed to investigate NOx reduction performance by developing ecofriendly permeable concrete with photocatalytic treatment to reduce fine dust generated from road mobile pollution sources. Permeable concrete specimens containing an activated loess and zeolite admixture were prepared and subjected to mechanical and durability tests. All specimens, including the control (CTRL) and admixture, met quality standard SPS-F-KSPIC-001-2006 for road pavement. Slip resistance and permeability coefficient also satisfied the standards, while freeze-thaw evaluation criteria were met only by CTRL and A1Z1 specimens. NOx reduction performance of the permeable concrete treated with TiO2 photocatalyst was assessed using ISO standard and tank chambers. NOx reduction efficiency of up to 77.5% was confirmed in the permeable concrete specimen with TiO2 content of 7.5%. Nitrate concentration measurements indirectly confirmed photolysis of nitrogen oxide. Incorporating TiO2 in construction materials such as roads and sidewalks can improve the atmospheric environment for pedestrians near roads by reducing NOx levels through photocatalysis.

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.

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.

Nitrate attenuation potential in karst conduits and aquifer matrix

A critical determinant of the effective denitrification potential in karst aquifers is the relative contribution of matrix and non-matrix (e.g., conduits) to the total groundwater flow. This work tests the hypothesis that observed karst aquifer-scale denitrification rates represent the superposition of the effects from matrix zones, which have low denitrification rates and long residence times, and non-matrix zones, which have higher denitrification rates and short residence times. To better evaluate karst whole-aquifer denitrification capacity, this study examined groundwater chemical data from 69 individual wells across the springshed of Silver Springs, FL, and conducted five push–pull tracer tests (PPTTs) in matrix and non-matrix aquifer sections. Mean residence times and mean zero-order denitrification rates (K0) were determined using reduced-complexity analytical models for matrix and non-matrix zones. Significant nitrate degradation at the local scale was observed in wells that sampled matrix portions of the aquifer (K0 ≈ 5 to 7 × 103 μmol N/L/d), indicating denitrification hotspots comparable to previous results employing the same PPTT method. However, PPTTs in matrix portions of the aquifer found no evidence of aquifer denitrification, likely due to the short residence times experienced during PPTTs. The analytical models coupled with the measured nitrate concentrations and excess N2 data in groundwater discharged at the spring vents showed whole-aquifer estimates of residence times tavg = 4.2 years and aquifer denitrification rate K0,avg = 0.01 ± 0.01 μmol N/L/d that were consistent with previous studies. However, the average denitrification rate for non-matrix zones K0,nm = 1.29 ± 0.92 μmol N/L/d was two orders of magnitude higher than that for matrix zones K0,m = 0.002 ± 0.001 μmol N/L/d. Whole-aquifer denitrification measures thus reflect the weighted contributions of low denitrification in non-matrix zones, which constitute the majority of the groundwater flow, and high-denitrification but low-flow matrix zones. The modeling approach with non-matrix networks from this study can provide insight into the catchment-scale N budget and transport in karst aquifers.

Effect of cultivar on measurements of nitrate concentration in petiole sap and leaf N content in greenhouse soil-grown cucumber, melon, and sweet pepper crops

Excessive N fertilizer applications in intensive vegetable production in soil is commonly associated with appreciable N losses causing negative environmental impact. Measuring petiole sap [NO3−‒N] and leaf N content (%) are simple and practical monitoring methods to assess crop N status for improving N fertilizer management. The effect of cultivar on petiole sap [NO3−‒N] and leaf N content was evaluated. One cucumber, two melon, and two sweet pepper crops were grown in different cropping periods, with three cultivars in each crop. Three N treatments, deficient (N1), sufficient (N2) and excessive (N3) N supply, were applied by combined fertigation with drip irrigation. For a given N supply, there were often significant differences between cultivars in petiole sap [NO3−‒N] and leaf N content in cucumber, the two melon crops and one pepper crop. This was, particularly so with the sufficient (N2) and excessive (N3) N supply. In the cucumber and two melon crops, there were consistent differences in petiole sap [NO3−‒N] between cultivars in two or three of the different N treatments. In some crops, very little petiole sap [NO3−‒N] was measured with deficient (N1) N supply. In the two pepper crops, the differences between cultivars were less clear than with cucumber and melon. In general, for the three species examined, petiole sap [NO3−‒N] was subject to more consistent and larger effects between cultivars, than was leaf N. Average differences between cultivars in petiole sap [NO3−‒N] of 200‒450 mg NO3−‒N L−1 were observed during periods of 4‒6 weeks in cucumber and melon. The differences between different cultivars of the same species in petiole sap [NO3−‒N] and leaf N content, when receiving the same N supply, has implications for the practical applications of these methods for monitoring crop N status.

Development of an Inexpensive, Rapid Method to Measure Nitrates in Freshwater to Enhance Student Learning

A laboratory experiment was designed and implemented in a STEM teaching laboratory at Michigan State University to engage students in an activity that not only introduced an innovative nitrate detection technique but also addressed one of the negative impacts of climate change, that is, the eutrophication of water bodies. The adverse effects of eutrophication on public health due to the presence of cyanotoxins make it crucial to monitor the trophic state of water bodies, which can be assessed by measuring the nitrate and phosphate concentrations. We developed a rapid method to measure nitrate concentrations in freshwater samples using a Hanna Instruments Checker, which was designed to measure nitrate levels in seawater. We identified the sample matrix that would maximize the accuracy of the Checker instrument for freshwater samples and validated the analytical method via ion chromatography. Students gained knowledge of other aspects of laboratory procedures, such as sample collection, sample storage, and material compatibility, which are often ignored during conventional teaching practices.

A submersible probe with in-line calibration and a symmetrical reference element for continuous direct nitrate concentration measurements.

Current methods to monitor nitrate levels in freshwater systems are outdated because they require expensive equipment and manpower. Punctual sampling on the field or at a fixed measuring station is still the accepted monitoring procedure and fails to provide real-time estimation of nitrate levels. Continuous information is of crucial importance to evaluate the health of natural aquatic systems, which can strongly suffer from a nitrogen imbalance. We present here a nitrate-selective potentiometric probe to measure the analyte continuously without requiring maintenance or high-power consumption. Owing to a simple design where the sensors are located directly in contact with the sample, the need for constant pump usage is eliminated, requiring just 0.7 mW power per day instead of 184 mW per day and per pump. It is estimated that with this power consumption, the setup can easily run for more than 97 h on four simple Li-ion batteries. A simple in-line one-point calibration step was implemented to allow for drift correction. At the same time, a symmetrical design was used involving a second nitrate probe as a reference electrode placed in the calibrant compartment. This, combined with an in situ calibration step, allows one to quantify nitrate ion concentrations directly, instead of yielding activities. The dependence on ion activity was removed by using the analysed sample spiked with nitrate as the calibrant. This results in essentially the same activity coefficients and additionally reduces junction potentials to a fraction of a millivolt. In addition, a symmetrical reference element served to compensate for fluctuations caused by environmental factors (temperature, convection, etc.) to achieve improved stability and signal reproducibility compared to a traditional Ag/AgCl based reference electrode. The final prototype was deployed in the Arve River in Geneva for 75 h without requiring any intervention. The nitrate levels measured using the symmetrical reference element over this period were estimated at 44.0 ± 3.5 M and agreed well with the values obtained with ion chromatography (38.2 ± 2.1 μM) used as the reference method. Thanks to a modular sensing head the potentiometric sensors can be easily exchanged, making it possible to quantify other types of analytes and leading the way to a new monitoring strategy.

Management of aquifer and dam reservoir quantitative-qualitative interaction

Investigating the quantity and quality interaction of the surface and groundwater resources plays an essential role in the integrated management of the surface and groundwater resources. In this study, to estimate the discharge and nitrate concentration of the interaction between the Chadegan aquifer and the Zayandeh-Roud reservoir, a quantitative-qualitative simulation model is developed using MODFLOW and MT3DMS codes. Here, the model is calibrated using the data from the beginning of winter 2011 to the end of winter 2014, and validated for spring 2014 to summer 2020. For the quantitative calibration, in the steady and unsteady conditions, the RMSE values of the water level are 0.74 m and 1.84 m, respectively, and for the qualitative calibration, the measured nitrate concentration values is 1.89 mg/L. In addition, for the validation state of the proposed model, the values of RMSE for the water levels and nitrate concentrations are 3.76 m and 2.85 mg/L, respectively. The results indicate that the aquifer has always been recharged by the reservoir during this time. In addition, the exchange nitrate concentration value is between 39.56 and 48.85 mg/L. The decreasing trend of the water level and the increase in the nitrate concentration, which exceed the permissible limit in some areas, indicate the necessity of adopting the immediate managerial policies. Five managerial scenarios are proposed and the effect on the aquifer conditions in terms of increase in the water level and the decrease of nitrate concentration is investigated. The results indicate that the 20% gradual reduction of the agricultural water consumption and simultaneously a 20% gradual reduction in nitrate fertilizers consumption and completing the urban wastewater treatment systems is the most effective quantitative-qualitative scenario for this region, with a 0.24% increase in the average water level and a 11.36% decrease in the average concentration of the nitrate in the aquifer by the end of the forecasting period.

Capacitance sensitivity study of interdigital capacitive sensor based on graphene for monitoring Nitrates concentrations

In order to increase agricultural productivity, it is necessary to manage the nutrients that the plants receive. In this sense, nitrogen is one of the most important nutrients for the adequate development and growth of plants and whose control contributes to the conservation of the environment. Traditionally, the quantification of nitrates is performed employing methods such as ion chromatography conducted in a laboratory, which leads to problems such as processing time, complexity in the analysis process itself and the need to have people trained to handle such analysis equipment. To alleviate these difficulties, some sensors use electrochemical principles; however, they present several limitations such as manufacturing complexity, cost, and difficulties in conducting real-time measurements.On the other hand, capacitive sensors have also been developed whose operating principle is based on analyzing the changes in the electrical characteristics of these devices produced by variations in the environment surrounding the sensor. For example, solutions with different concentrations of nitrates will produce an alteration of the electric field generated by the electrodes of the capacitor, producing changes in parameters such as its electrical impedance. However, the materials used to manufacture these sensors are metals, being unattractive for agricultural applications due to the corrosion they may suffer. To counteract this problem, it is possible to use other types of materials, among which graphene emerge as it has been shown to have excellent properties such as being a mechanically strong material and presenting good electrical conductivity. For this reason, in this work, the study of the sensitivity of a graphene-based interdigital capacitive sensor applied to the measurements of nitrate concentrations is performed. Different analytical methods were used. In general, the interdigital capacitive sensor shows repeatability in the measurements, especially for concentrations greater than 10 ppm with variability of ∼16%. Also, parameters such as the detection limit of the sensor were calculated, the result of which was 1.71 ppm. Also, measurements were made on agricultural soil samples showing differences in readings with respect to the ion chromatography method. Differences that are attributable to the different methodologies used in the calculation of the nitrate concentration and the fertilization process that was applied to the crop field a few weeks before. Despite the difference between the sensor measurements and the results obtained by ion chromatography, both procedures showed a high amount of nitrate concentration.

Assessment of groundwater vulnerability in coastal zone using SI method and GIS: case study of Bouficha aquifer (northeast Tunisia).

Nowadays, groundwater is under stress due to contamination, over-exploitation, seawater intrusion, climate change, etc. The groundwater contamination is the major problem which can engender the total deterioration of the aquifer. The groundwater vulnerability assessment may contribute to predicate and to delimitate the areas affected by contamination or any future pollution. This research aims to zoning the potential pollution of the Bouficha shallow aquifer, located in the northeast Tunisia, using the SI model and GIS. Five parameters are presented in the SI model: depth to groundwater (D), recharge (R), aquifer media (A), topography (T), and land use (LU). The different parameters were collected from diverse sources for assess groundwater vulnerability. The net recharge map was generated using GIS-based multi-criteria analysis method based on different parameters (slope, lithology, LU, soil, and drainage density). The generated vulnerability map shows three vulnerability classes: low vulnerability (< 45), moderate vulnerability (45-64), and high vulnerability (64-84) which represent 3.14%, 76.8%, and 20.06% of the total area, respectively. The SI vulnerability represent a moderate positive correlation with the measured nitrate concentrations (R2 = 0.76). The sensitivity analysis shows that the land use parameter is the most influential parameter for groundwater vulnerability in BFC.

Assessment of groundwater vulnerability based on the modified DRASTIC model: a case study in Baicheng City, China

Accurate assessment of groundwater vulnerability objectively reflects an area’s potential for groundwater pollution and provides a reference basis for pollution control and prevention. The main objective of this study was to modify the original DRASTIC model to improve the consistency of groundwater vulnerability assessment results with regard to the actual conditions of the study area. To optimize the assessment objectivity, two additional factors that are influenced by human activities (land use and degree of groundwater extraction) were added to form the DRASTICLE model. Then, based on the correlation between all factors and measured nitrate concentrations, the improved three-scale analytic hierarchy process (AHP) and the weights of evidence (WOE) methods were used to reassign the factor weights of the DRASTICLE model. The area under the receiver operating characteristic (ROC) curve, denoted as AUC, was used to quantitatively evaluate the accuracy of all four models (original DRASTIC model AUC: 0.62). By modifying the factors and weights, the three new models showed better performance, AUC values were 0.64, 0.73 and 0.85 for the DRASTICLE, AHP-DRASTICLE, and WOE-DRASTICLE models, respectively. These results indicate that the modified models could more accurately convey groundwater vulnerability in the study area. The WOE-DRASTICLE model, which had the best performance, was then used to assess groundwater vulnerability in 2000 and 2010 and these were compared to 2018. In 2000, 2010, and 2018, the proportion of areas with very high groundwater vulnerability was 5%, 6%, 8%, respectively. Meanwhile, the proportion of areas with very low vulnerability decreased from 73 to 75%, and then rose to 82%, indicating that the spatial distribution of groundwater vulnerability has changed over time. Findings of this study are expected to provide a new theoretical basis for the Baicheng City municipal government in China to better manage and exploit groundwater resources.

Development of a spectroscopic approach for non-destructive and rapid screening of cucumbers based on maximum limit of nitrate accumulation

In this research, a non-destructive and low-cost approach based on Vis/NIR spectroscopy was developed for rapid measurement of nitrate concentrations in cucumbers and screening of the samples based on maximum limit of nitrate accumulation. Vis/NIR spectra of intact cucumbers including both field and greenhouse samples with different concentrations of nitrate were analyzed. PLS models were developed based on the pre-processed spectra and reference measurements. Moreover, PCA-DA classification models with different methods of linear, quadratic and Mahalanobis were developed to discriminate the samples based on maximum limit of nitrate accumulation according to Iranian National Standardization Organization (INSO) and World Health Organization (WHO), as well as based on the type. The best PLS model for prediction of nitrate concentrations in the cucumbers was achieved using D2 pre-processing method (rp =0.87, SEP=60.92 mg kg−1, RPD=2.07). It was concluded that Vis/NIR spectroscopy is adequate for screening the cucumbers based on their nitrate concentrations. The results also confirmed that this technology combined with PCA-DA is appropriate (accuracy=72.22%, sensitivity=76.74%, specificity=54.55%) and fairly suitable (accuracy=64.81%, sensitivity=59.26%, specificity=70.37%) for screening of the cucumbers based on maximum limit of nitrate accumulation according to INSO and WHO, respectively. It was excellent technology for classification of the cucumbers based on their type (accuracy=94.44%, sensitivity=93.55%, specificity=95.65%). Consequently, the proposed spectroscopic approach can be used for safety assessment of cucumbers as a rapid method with easy and out-of-laboratory usability.

Machine learning predictions of nitrate in groundwater used for drinking supply in the conterminous United States

Groundwater is an important source of drinking water supplies in the conterminous United State (CONUS), and presence of high nitrate concentrations may limit usability of groundwater in some areas because of the potential negative health effects. Prediction of locations of high nitrate groundwater is needed to focus mitigation and relief efforts. A three-dimensional extreme gradient boosting (XGB) machine learning model was developed to predict the distribution of nitrate. Nitrate was predicted at a 1 km resolution for two drinking water zones, each of variable depth, one for domestic supply and one for public supply. The model used measured nitrate concentrations from 12,082 wells and included predictor variables representing well characteristics, hydrologic conditions, soil type, geology, land use, climate, and nitrogen inputs. Predictor variables derived from empirical or numerical process-based models were also included to integrate information on controlling processes and conditions. The model provided accurate estimates at national and regional scales: the training (R2 of 0.83) and hold-out (R2 of 0.49) data fits compared favorably to previous studies. Predicted nitrate concentrations were less than 1 mg/L across most of the CONUS. Nationally, well depth, soil and climate characteristics, and the absence of developed land use were among the most influential explanatory factors. Only 1% of the area in either water supply zone had predicted nitrate concentrations greater than 10 mg/L; however, about 1.4 M people depend on groundwater for their drinking supplies in those areas. Predicted high concentrations of nitrate were most prevalent in the central CONUS. In areas of predicted high nitrate concentration, applied manure, farm fertilizer, and agricultural land use were influential predictor variables. This work represents the first application of XGB to a three-dimensional national-scale groundwater quality model and provides a significant milestone in the efforts to document nitrate in groundwater across the CONUS.

Spring phytoplankton blooms in the Northern Satsunan region, Japan, stimulated by the intrusion of Kuroshio Branch water

The Kuroshio current greatly affects biological processes in coastal areas. The Kagoshima Bay has good spawning ground for major migratory fish, serves as an important feeding area for fish larvae, and is affected by the Kuroshio current; however, there is little information concerning the biological response to the Kuroshio intrusion in this location. During the mixing period, the Kuroshio current approaches the Kagoshima Bay and a density flow, consisting of surface inflow and bottom outflow, is generated. We hypothesize that the bottom water in the bay, having a high nutrient concentration, mixes with the surface layer when the water flows out of the bay and that this contributes to the high biological production at the bay mouth. In this study, we conducted a field survey of the water quality in March 2016 and, using a three-end member mixing model, examined whether the bottom water of the bay could be a nutrient source supporting the phytoplankton bloom in the bay mouth. We discuss the fate of the organic matter derived from the primary production promoted by a nutrient supply event. The results indicate that the N-based phytoplankton biomass represented less than 80% of the N uptake by the phytoplankton, as estimated by subtracting the measured nitrate concentration from the supplied nitrate concentration based on the mixing model, indicating that the phytoplankton bloom at the bay mouth was supported by the supply of bottom water from the bay. Based on the C/N molar ratio (6.4) calculated by C/chlorophyll a (Chl-a) and N/Chl-a in this study, the highest value of nitrogen uptake was 12 mg C m−3 d−1 in terms of the carbon assimilation. The feeding rate of the mesozooplankton was estimated to be 13.6 mg C m−3 d−1 using a physiological model. An analysis of the food web structure is required to assess the effects of feeding by mesozooplankton; however, most of the phytoplankton bloom caused by mixing could be efficiently transferred to mesozooplankton in this study area.

DRASTIC model adjusted with lineament density to map groundwater vulnerability: a case study in Rania basin, Kurdistan, Iraq.

Groundwater has never been heavily relied on as a water source in Northern Iraq as it has been in the last two decades due to the rapid and often unplanned urbanization, industrial and agricultural projects. This paper attempts to present a concise groundwater vulnerability assessment of Rania basin to the local and regional planning authorities to ensure a more sustainable development in the area. The focus of the study is the Rania basin, which is a part of Dokan subbasin in northeast Iraq. The initial groundwater vulnerability assessment is mapped with standard DRASTIC model. It is then modified by adding "lineament density index" to the original seven DRASTIC parameters due to the previously established close relationship between flow and yield of groundwater with lineament. The area is categorized into five vulnerability index zones of very low (26%), low (32%), medium (31%), high (11%), and very high (0.012%). The modified model offers a slightly different vulnerability classification of very low (16.61%), low (35.45%), medium (30.32), high (17.57), and very high (0.05%). Measured nitrate concentration is used to validate the assessment results. A progressive increase in nitrate level somehow reflects the different vulnerability zones identified by both DRASTIC models. Average nitrate values of samples taken in wet season show 14.99 mg/l, 17.94 mg/l, and 18.63 for very low vulnerability, low vulnerability, and medium vulnerability zones in the standard DRASTIC model. However, when the area is mapped by the modified DRASTIC model, the vulnerability classes of very low and medium show slightly higher nitrate values of 15.96 mg/l and 20.1 mg/l and a lower value of 17.68 mg/l for the low vulnerability class. This is despite a noticeable increase in nitrate level between wet and dry seasons due to the rise in water table in the wet season.

A novel analytical approach for the simultaneous measurement of nitrate and dissolved organic carbon in soil water

Abstract. In this paper, we present a novel approach, enabling the measurement of nitrate concentrations in natural soil porewater containing natural soil dissolved organic carbon (DOC). The method is based on UV absorbance spectroscopy, combined with fluorescence spectroscopy, for simultaneous analysis of DOC and nitrate concentrations. The analytical procedure involves deduction of the absorption caused by the DOC from the total absorbance in the UV range that is attributed to both DOC and nitrate in the water solution. The analytical concept has been successfully tested in soil water samples obtained from five agricultural sites, as well as in water samples obtained from a commercial humus soil mixture. We believe that the new analytical concept can provide a scientific foundation for developing a sensor for real-time nitrate concentration measurements in agricultural soils. As such, it can play a significant role in reducing nitrate pollution in water resources, optimizing input application in agriculture, and decreasing food production costs.

Vulnerability assessment, transport modeling and simulation of nitrate in groundwater using SI method and modflow-MT3DMS software: case of Sminja aquifer, Tunisia

Like most North African countries, Tunisia is characterized by a harsh arid and semi-arid climate with scarce water resources and poor water quality on most of its territory. The quality of groundwater is not immune to pollution. Sminja aquifer, located in Zaghouan district in Northeastern Tunisia, has been used to meet Zaghouan agglomeration needs for drinking purposes and irrigation uses. On the other hand, the region has suffered from inefficient usage and mismanagement of water resource due to appropriate legal, political, and economic frameworks to take into consideration the regional vulnerability to climate change and population growth. The application of the Susceptibility Index (SI) makes it possible to evaluate the impact of agricultural activities on the water quality in Sminja aquifer, using five parameters [depth of water (D), net recharge (R), aquifer media (A), topography (T) and Land use (LU)]. Modular three-dimensional multispecies transport model was used to assess, simulate and predict pollution transport of nitrate. The vulnerability index's spatial distribution shows that the most vulnerable area was found in the extreme north of the Sminja aquifer. It shows that a high vulnerability characterizes 21% of the study area (70 < SI < 60). The moderate to high vulnerability areas to pollution occupied 12% of the aquifer and the moderate to low vulnerability zones occupied 67% of the total area. The outputs of the SI reflect a good correlation with the measured nitrate concentrations. After calibration completion, the MT3DMS transport model results showed a good correlation between measured and simulated nitrate concentrations. The predict scenarios show that the nitrate propagates in all the aquifer, from the irrigated area to the non-irrigated area.

An Improved Algorithm for Measuring Nitrate Concentrations in Seawater Based on Deep-Ultraviolet Spectrophotometry: A Case Study of the Aoshan Bay Seawater and Western Pacific Seawater.

Nowadays, it is still a challenge for commercial nitrate sensors to meet the requirement of high accuracy in a complex water. Based on deep-ultraviolet spectral analysis and a regression algorithm, a different measuring method for obtaining the concentration of nitrate in seawater is proposed in this paper. The system consists of a deuterium lamp, an optical fiber splitter module, a reflection probe, temperature and salinity sensors, and a deep-ultraviolet spectrometer. The regression model based on weighted average kernel partial least squares (WA-KPLS) algorithm together with corrections for temperature and salinity (TSC) is established. After that, the seawater samples from Western Pacific and Aoshan Bay in Qingdao, China with the addition of various nitrate concentrations are studied to verify the reliability and accuracy of the method. The results show that the TSC-WA-KPLS algorithm shows the best results when compared against the multiple linear regression (MLR) and ISUS (in situ ultraviolet spectrophotometer) algorithms in the temperatures range of 4–25 °C, with RMSEP of 0.67 µmol/L for Aoshan Bay seawater and 1.08 µmol/L for Western Pacific seawater. The method proposed in this paper is suitable for measuring the nitrate concentration in seawater with higher accuracy, which could find application in the development of in-situ and real-time nitrate sensors.