Co-application of biochar and biosolids to soil has potential to mitigate N leaching due to physical and chemical properties of biochar. Changes in N cycling pathways in soil induced by co-application of biological amendments could further mitigate N loss, but this is largely unexplored. The aim of this study was to determine whether co-application of a biochar and a modified biosolids product to three pasture soils differing in texture could alter the relative abundance of N cycling genes in soil sown with subterranean clover. The biosolids product contained lime and clay and increased subterranean clover shoot biomass in parallel with increases in soil pH and soil nitrate. Its co-application with biochar similarly increased plant growth and soil pH with a marked reduction in nitrate in two coarse textured soils but not in a clayey soil. While application of the biosolids product altered in silico predicted N cycling functional genes, there was no additional change when applied to soil in combination with biochar. This supports the conclusion that co-application of the biochar and biosolids product used here has potential to mitigate loss of N in coarse textured soils due to N adsoption by the biochar and independently of microbial N pathways.
In the past few decades, there has been a rapid growth in the concentration of nitrogenous compounds such as nitrate-nitrogen and ammonia-nitrogen in rivers, primarily due to increasing agricultural and industrial activities. These nitrogenous compounds are mainly responsible for eutrophication when present in river water, and for 'blue baby syndrome' when present in drinking water. High concentrations of these compounds in rivers may eventually lead to the closure of treatment plants. This study presents a training and a selection approach to develop an optimum artificial neural network model for predicting monthly average nitrate-N and monthly average ammonia-N. Several studies have predicted these compounds, but most of the proposed procedures do not involve testing various model architectures in order to achieve the optimum predicting model. Additionally, none of the models have been trained for hydrological conditions such as the case of Malaysia. This study presents models trained on the hydrological data from 1981 to 2017 for the Langat River in Selangor, Malaysia. The model architectures used for training are General Regression Neural Network (GRNN), Multilayer Neural Network and Radial Basis Function Neural Network (RBFNN). These models were trained for various combinations of internal parameters, input variables and model architectures. Post-training, the optimum performing model was selected based on the regression and error values and plot of predicted versus observed values. Optimum models provide promising results with a minimum overall regression value of 0.92.
Changes in nitrate and nitrite contents (leaves and stem) of Amaranthus gangeticus (AG) and Amaranthus paniculatus (AP), resulting from blanching, storage time (0-4 days), storage temperature (0 and 4ºC), and reheating were analysed. Results showed that fresh AG (1859 ± 7.07 mg/kg) had higher nitrite content than AP (1262 ± 2.12 mg/kg). Nitrites content was 506 ± 2 and 825 ± 3.5 mg/kg for AG and AP, respectively. Reheating and storage times significantly increased the conversion of nitrate to nitrite in AG and AP. Storage at 0 and 4oC exhibited a significant change (P < 0.05) in nitrate and nitrite contents for both samples. Higher nitrite content was found in AP when stored at 4oC and 0oC. The present study indicated that storage time and temperature affected the nitrite contents in blanched AG and AP when stored in low temperatures. Apart from that reheating was also found to increase the formation of nitrite.
Nanocrystalline lead sulfide (PbS) thin films have been successfully grown on glass substrate using the chemical bath deposition technique. Microwave oven was used as a heating source to facilitate the growth process of the thin films. Aqueous solutions of lead nitrate Pb(NO3) and thiourea [SC(NH2)2] were used as lead and sulfur ion sources, respectively. Structural, morphological and optical analyses revealed good quality growth of nanocrystalline PbS thin films. This study introduced a facile and low cost method to prepare high quality nanocrystalline PbS thin films in a relatively short growth time for optoelectronic applications.
Current study report the growth of Zinc Oxide (ZnO) nanorods (NRs) by a facile and low temperature method on Zinc (Zn) foil in deionized (DI) water. These ZnO NRs have a typical length of 500-700 nm and average diameter of 50-70 nm. By using different volume of DI water, the morphology of ZnO nanostructures are tunable from rod-like to flower-like structures. Under the presence of Zn nitrate precursor, mixture of rod/wall-like structures are formed. Both of ZnO NRs and combined nanorods/nanowalls render higher diffraction for the (002) peak reveals, which implies preferred orientation growth along c-axis take place. However, photoluminescence (PL) study indicates that ZnO NRs have strong emission located at ~380 nm if compared to that of combined ZnO nanorods/nanowalls. This shows that ZnO NRs have higher-densities of defects.
Benthic dinoflagellates are known to occur in the water column. The reason they can be found in different parts of the ecosystem is not clear. This study aims to determine the species and the cell abundance of benthic dinoflagellates in the water column and macrophytes collected from two different locations i.e. semi-enclosed lagoon and open coastal waters. The physico-chemical parameters (temperature, salinity, pH, dissolved oxygen) and nutrients (nitrate and phosphate) were determined. Results showed that in the lagoon, the most abundant dinoflagellate species on the macrophytes was also the most abundant dinoflagellate species in the water column. The species that dominated the water column and marophytes in the lagoon was Bysmatrum caponii. In the coastal area the trend was not clear. Coolia dominated the macrophytes whereas Peridinium quinquecorne dominated the water column. The physico-chemical parameters determined were similar at both sites except for nutrients. Results show that type of substrates and different geomorphology effects benthic dinoflagellates cell abundance in the macrophytes and water column.
In an effort to determine the reason behind excellent nitrate remediation capacity at Kelantan region, a multivariate approach is employed to evaluate extent to which the influence of sea on soil geochemical composition affect variation pattern of groundwater quality. The results obtained from geochemical analysis of paleo-beach soil in coastal site at Bachok revealed multiple redox activity at different soil strata, involving both heterotrophic and autotrophic denitrification. In soil and water analysis, eight of the fourteen hydro-geochemical parameters (conductivity, temperature, soil texture, oxidation reduction potential, pH, total organic carbon, Fe, Cu, Mn, Cl-, SO42-, NO2-, NO3- and PO43-) measured using standard procedures were subjected to multivariate analysis. Evaluation of general variation pattern across the area reveals that the principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA) are in consonance with one another on apportioning three parameters (SO42-, Cl- and conductivity) to the coastal sites and two parameters (Fe and NH4+ or NO3-) to inland sites. The step forward analysis of LDA reveals four parameters in order of decreasing significance as Cl-, Fe and SO42-, while the two-way HCA identifies three clusters on location basis, respectively. In addition to the significant data reduction obtained, the results indicate that proximity to sea and location/geological-based influence are more significant than temporal-based influence in denitrification. By extension, the research reveals that influence of labile portion of natural resources is explorable for broader application in other remediation strategies.
Although estimating the uncertainty of models used for modelling nitrate contamination of groundwater is essential in groundwater management, it has been generally ignored. This issue motivates this research to explore the predictive uncertainty of machine-learning (ML) models in this field of study using two different residuals uncertainty methods: quantile regression (QR) and uncertainty estimation based on local errors and clustering (UNEEC). Prediction-interval coverage probability (PICP), the most important of the statistical measures of uncertainty, was used to evaluate uncertainty. Additionally, three state-of-the-art ML models including support vector machine (SVM), random forest (RF), and k-nearest neighbor (kNN) were selected to spatially model groundwater nitrate concentrations. The models were calibrated with nitrate concentrations from 80 wells (70% of the data) and then validated with nitrate concentrations from 34 wells (30% of the data). Both uncertainty and predictive performance criteria should be considered when comparing and selecting the best model. Results highlight that the kNN model is the best model because not only did it have the lowest uncertainty based on the PICP statistic in both the QR (0.94) and the UNEEC (in all clusters, 0.85-0.91) methods, but it also had predictive performance statistics (RMSE = 10.63, R2 = 0.71) that were relatively similar to RF (RMSE = 10.41, R2 = 0.72) and higher than SVM (RMSE = 13.28, R2 = 0.58). Determining the uncertainty of ML models used for spatially modelling groundwater-nitrate pollution enables managers to achieve better risk-based decision making and consequently increases the reliability and credibility of groundwater-nitrate predictions.
Macrophytes have been used to mitigate eutrophication and upgrade effluent quality via their nutrient removal capability. However, the available data are influenced by factors such as microbial activities, weather, and wastewater quality, making comparison between nutrient removal performance of different macrophytes almost impossible. In this study, phytoremediation by Spirodela polyrhiza, Salvinia molesta and Lemna sp. were carried out axenically in synthetic wastewater under controlled condition to precisely evaluate nutrient removal efficiency of NO3--N, PO43-, NH3-N, COD and pH in the water sample. The results showed that ammonia removal was rapid, significant for S. polyrhiza and Lemna sp., with efficiency of 60% and 41% respectively within 2 days. S. polyrhiza was capable of reducing 30% of the nitrate. Lemna sp. achieved the highest phosphate reduction of 86% at day 12 to mere 1.07 mg/L PO43--P. Correlation was found between COD and TC, suggesting the release of organic substances by macrophytes into the medium. All the macrophytes showed biomass increment. S. polyrhiza outperformed other macrophytes in nutrient removal despite lower biomass production. The acquired nutrient removal profiles can serve as a guideline for the selection of suitable macrophytes in wastewater treatment and to evaluate microbial activity in non-aseptic phytoremediation system.
Landfills are one of the main point sources of groundwater pollution. This research mainly aims to assess the risk of nitrate [Formula: see text] transport from the unlined landfill to subsurface layers and groundwater using experimental results and the SESOIL model. Samples from 12 groundwater wells downstream of the landfill were collected and analyzed in 2008, 21 years after the landfill construction. The average [Formula: see text] concentration in the wells was 54 mg/L, slightly higher than the World Health Organization ([Formula: see text] 50 mg/L) standards. SESOIL model was used to predict the [Formula: see text] concentration at the bottom of the unsaturated zone. Results indicated that the current mean [Formula: see text] concentration at the bottom of the unsaturated zone is 75 mg/L. the model predicted that the level of NO3 will increased up to 325 mg/L within 30 years. Accordingly, the [Formula: see text] concentration in groundwater wells near the landfill area is expected to gradually increase with time. Although the current risk associated with the [Formula: see text] level might not be harm to adults, however, it might pose severe risks to both adults and infants in the near future due to [Formula: see text] leaching. Urgent mitigation measures such as final cell cover (cap), lining system and vertical expansion should be considered at the landfill to protect the public health in the area.
The flow of unprocessed sewage through municipal sewers is a great source of water contamination. This study aims to observe the pollutants removal efficiencies of walnut shells as an efficient low-cost adsorbent material compared to gravel materials as an anaerobic filter medium. Two models of the De-Centralized Wastewater Treatment System (DEWATS) were constructed. The wastewater flowing from toilets and handwashing places was connected to anaerobic filters filled with walnut shells and gravel. The efficiency of both filter media in the removal of biological oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), total dissolved solids (TDS), nitrate (NO3), and phosphate (PO43), pH and temperature were observed at the influent of the settler tank and then at the effluent of the collection tank (CT). Temperature and pH were within the acceptable limit of wastewater discharge. The results also indicated that the walnut shells filter media was more efficient at removing organic pollutants (TSS 94%, BOD5 88%, COD 85%, Nitrate 57%, phosphate 46%, and TDS 29%) than the gravel (TSS 81%, BOD5 82%, COD 84%, Nitrate 35%, phosphate 38%, and TDS 26%) at the successive stages. The average removal efficiency of the walnut shell was 88% while in the gravel case, it was 83%. The removal efficiency of walnut shell filters was extensively better over the complete experiment compared to gravel filters for the removal of pollutants, representing the high sorption capability of the walnut shell material. The results of this study show that the walnut shells may be a very useful substitute for other conventional fillers for anaerobic treatment in the anaerobic filter of DEWATS.
Edible bird nests (EBNs) are important ethnomedicinal commodity in the Chinese community. Recently, But and others showed that the white EBNs could turn red by vapors from sodium nitrite (NaNO2) in acidic condition or from bird soil, but this color-changing agent remained elusive. The aim of this study was to determine the prevalence of nitrite and nitrate contents and its affects on EBN's color. EBNs were collected from swiftlet houses or caves in Southeast Asia. White EBNs were exposed to vapor from NaNO2 in 2% HCl, or bird soil. The levels of nitrite (NO2-) and nitrate (NO3-) in EBNs were determined through ion chromatography analysis. Vapors from NaNO2 in 2% HCl or bird soil stained white bird nests to brown/red colors, which correlated with increase nitrite and nitrate levels. Moreover, naturally formed cave-EBNs (darker in color) also contained higher nitrite and nitrate levels compared to white house-EBNs, suggesting a relationship between nitrite and nitrate with EBN's color. Of note, we detected no presence of hemoglobin in red "blood" nest. Using infrared spectra analysis, we demonstrated that red/brown cave-EBNs contained higher intensities of C-N and N-O bonds compared to white house-EBNs. Together, our study suggested that the color of EBNs was associated with the prevalence of the nitrite and nitrate contents.
Mixotrophic metabolism was evaluated as an option to augment the growth and lipid production of marine microalga Tetraselmis sp. FTC 209. In this study, a five-level three-factor central composite design (CCD) was implemented in order to enrich the W-30 algal growth medium. Response surface methodology (RSM) was employed to model the effect of three medium variables, that is, glucose (organic C source), NaNO3 (primary N source), and yeast extract (supplementary N, amino acids, and vitamins) on biomass concentration, X(max), and lipid yield, P(max)/X(max). RSM capability was also weighed against an artificial neural network (ANN) approach for predicting a composition that would result in maximum lipid productivity, Pr(lipid). A quadratic regression from RSM and a Levenberg-Marquardt trained ANN network composed of 10 hidden neurons eventually produced comparable results, albeit ANN formulation was observed to yield higher values of response outputs. Finalized glucose (24.05 g/L), NaNO3 (4.70 g/L), and yeast extract (0.93 g/L) concentration, affected an increase of X(max) to 12.38 g/L and lipid a accumulation of 195.77 mg/g dcw. This contributed to a lipid productivity of 173.11 mg/L per day in the course of two-week cultivation.
A study was performed to determine the effect of Conway and f/2 media on the growth of microalgae genera. Genera of Chlorella sp., Dunaliella sp., Isochrysis sp., Chaetoceros sp., Pavlova sp. and Tetraselmis sp. were isolated from the South China Sea. During the cultivation period, the density of cells were determined using Syringe Liquid Sampler Particle Measuring System (SLS-PMS) that also generated the population distribution curve based on the size of the cells. The population of the microalgae genera is thought to consist of mother and daughter generations since these microalgae genera reproduce by releasing small non-motile reproductive cells (autospores). It was found that the reproduction of Tetraselmis sp., Dunaliella sp. and Pavlova sp. could be sustained longer in f/2 Medium. Higher cell density was achieved by genus Dunaliella, Chlorella and Isochrysis in Conway Medium. Different genera of microalgae had a preference for different types of cultivation media.
A two-stage anoxic transformation process, involving growth of biomass utilizing two types of different electron acceptors, namely nitrate and nitrite, has been observed. The present water quality modules established for sewer processes cannot account for the two-stage process. This paper outlines the development of a model concept that enables the two-stage anoxic transformation process to be simulated. The proposed model is formulated in a matrix form that is similar to the Activated Sludge Models and Sewer Process Model matrices. The model was successfully applied to simulate changes in nitrate and nitrite concentrations during anoxic transformations in the bulkwater phase of municipal wastewater.
Nitrates in different water and wastewater streams raised concerns due to severe impacts on human and animal health. Diverse methods are reported to remove nitrate from water streams which almost fail to entirely treat nitrate, except biological denitrification which is capable of reducing inorganic nitrate compounds to harmless nitrogen gas. Review of numerous studies in biological denitrification of nitrate containing water resources, aquaculture wastewaters and industrial wastewater confirmed the potential of this method and its flexibility towards the remediation of different concentrations of nitrate. The denitrifiers could be fed with organic and inorganic substrates which have different performances and subsequent advantages or disadvantages. Review of heterotrophic and autotrophic denitrifications with different food and energy sources concluded that autotrophic denitrifiers are more effective in denitrification. Autotrophs utilize carbon dioxide and hydrogen as the source of carbon substrate and electron donors, respectively. The application of this method in bio-electro reactors (BERs) has many advantages and is promising. However, this method is not so well established and documented. BERs provide proper environment for simultaneous hydrogen production on cathodes and appropriate consumption by immobilized autotrophs on these cathodes. This survey covers various designs and aspects of BERs and their performances.
This article contains water quality data collected in a shallow and narrow Setiu Lagoon during the southwest monsoon, wet period of northeast monsoon and dry period of northeast monsoon. The surface water quality parameters, which include the temperature, salinity, chlorophyll-a and nutrients (ammonia, nitrate, phosphate, and silicate) were sampled twice per day (high and low tides) at a total of eight stations. Hourly current speed and direction was obtained from mooring of two units of current meters. Compared to the Malaysia Marine Water Quality Criteria and Standard (MWQCS), nutrients in Setiu Lagoon were in Class 2. Although limited, this dataset can provide insights on the changes of water quality condition in Setiu Lagoon under the presence of anthropogenic pressures.
In this study, two native duckweeds (Lemna minor and Azolla pinnata) were cultivated in Palm Oil Mill Effluent (POME) to extract nutrients from the effluent. Five grams of A. pinnata and 2 g of L. minor were transferred to 2 L POME (Initial concentrations: 198 mg/L COD, 4.3 mg/L nitrates, pH 9.53, 4 mg/L phosphate, 2.98 mg/L ammonia) with four different dilutions (2.5%, 5%, 10%, 15%) under greenhouse conditions. Samples of POME were taken every two days up to 10 days. Growth parameter, phosphate, ammonia, nitrates, pH, and COD were monitored within 10 days to select the most suitable growth medium for both plants. Results showed that 2.5% POME dilution had positive effect on L. minor growth and A. pinnata (wet weight increased by 8.7 g and 9.8 g, respectively), with all plants able to survive until the final day of exposure. The highest removal of ammonia was accomplished in 5% POME dilution by A. pinnata (98%) and L. minor (95.5%). The maximum phosphate removal was obtained in 10% POME dilution with 93.3% removal by A. pinnata and 86.7% by L. minor. Significant COD removal in 15% POME was obtained by L. minor (78%) and A. pinnata (66%). Both plants responded positively to the phytoremediation process, especially for A. pinnata which showed significant decreases in all parameters. The nutrient extraction by both plants from POME showed a positive effect on growth parameter, which has further promising potential to be used as animal feedstock.
Hydroxylammonium nitrate (HAN) is a promising green propellant because of its low toxicity, high volumetric specific impulse, and reduced development cost. Electrolytic decomposition of HAN is an efficient approach to prepare it for further ignition and combustion. This paper describes the investigation of a co-electrolysis effect on electrolytic decomposition of HAN-fuel mixtures using stainless steel-platinum (SS-Pt) electrodes. For the first time, different materials were utilized as electrodes to alter the cathodic reaction, which eliminated the inhibition effect and achieved a repeatable and consistent electrolytic decomposition of HAN solution. Urea and methanol were added as fuel components in the HAN-fuel mixtures. When the mass ratio of added urea ≥20%, the electrolytic decomposition of a HAN-urea ternary mixture achieved 67% increment in maximum gas temperature (Tgmax) and 185% increment in overall temperature increasing rate over the benchmark case of HAN solution. The co-electrolysis of urea released additional electrons into the mixtures and enhanced the overall electrolytic decomposition of HAN. In contrast, the addition of methanol did not improve the Tgmax but only increased the overall temperature increasing rate. This work has important implications in the development of an efficient and reliable electrolytic decomposition system of HAN and its mixtures for propulsion applications.
The assessment of water-extractable organic matter using an autoclave can provide useful information on physical, chemical, and biological changes within the soil. The present study used virgin forest soils from Chini Forest Reserve, Langkawi Island, and Kenyir Forest Reserve (Malaysia), extracted using different extraction methods. The dissolved organic carbon (DOC), total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), and ammonium-nitrate content were higher in the autoclave treatments, up to 3.0, 1.3, 1.2, and 1.4 times more than by natural extraction (extracted for 24 h at room temperature). Overall, the highest extractable DOC, TDN, TDP, ammonium and nitrate could be seen under autoclaved conditions 121 °C 2×, up to 146.74 mg C/L, 8.97 mg N/L, 0.23 mg P/L, 5.43 mg N mg/L and 3.47 N mg/L, respectively. The soil extracts became slightly acidic with a higher temperature and longer duration. Similar trends were observed in the humic and nonhumic substances, where different types of soil extract treatments influenced the concentrations of the fractions. Different soil extraction methods can provide further details, thus widening the application of soil extracts, especially in microbes.