Application of machine learning approaches to predict ammonium nitrogen transport in different soil types and evaluate the contribution of control factors.

The loss of nitrogen in soil damages the environment. Clarifying the mechanism of ammonium nitrogen (NH4+-N) transport in soil and increasing the fixation of NH4+-N after N application are effective methods for improving N use efficiency. However, the main factors are not easily identified because of the complicated transport and retardation factors in different soils. This study employed machine learning (ML) to identify the main influencing factors that contribute to the retardation factor (Rf) of NH4+-N in soil. First, NH4+-N transport in the soil was investigated using column experiments and a transport model. The Rf (1.29 - 17.42) was calculated and used as a proxy for the efficacy of NH4+-N transport. Second, the physicochemical parameters of the soil were determined and screened using lasso and ridge regressions as inputs for the ML model. Third, six machine learning models were evaluated: Adaptive Boosting, Extreme Gradient Boosting (XGB), Random Forest, Gradient Boosting Regression, Multilayer Perceptron, and Support Vector Regression. The optimal ML model of the XGB model with a low mean absolute error (0.81), mean squared error (0.50), and high test r2 (0.97) was obtained by random sampling and five-fold cross-validation. Finally, SHapely Additive exPlanations, entropy-based feature importance, and permutation characteristic importance were used for global interpretation. The cation exchange capacity (CEC), total organic carbon (TOC), and Kaolin had the greatest effects on NH4+-N transport in the soil. The accumulated local effect offered a fundamental insight: When CEC > 6 cmol+ kg-1, and TOC > 40 g kg-1, the maximum resistance to NH4+-N transport within the soil was observed. This study provides a novel approach for predicting the impact of the soil environment on NH4+-N transport and guiding the establishment of an early-warning system of nutrient loss.

Arbuscular mycorrhizal fungi offset NH3 emissions in temperate meadow soil under simulated warming and nitrogen deposition.

Most soil ammonia (NH3) emissions originate from soil nitrogen (N) that has been in the form of exchangeable ammonium. Emitted NH3 not only induces nutrient loss but also has adverse effects on the cycling of N and accelerates global warming. There is evidence that arbuscular mycorrhizal (AM) fungi can alleviate N loss by reducing N2O emissions in N-limited ecosystems, however, some studies have also found that global changes, such as warming and N deposition, can affect the growth and development of AM fungi and alter their functionality. Up to now, the impact of AM fungi on NH3 emissions, and whether global changes reduce the AM fungi's contribution to NH3 emissions reduction, has remained unclear. In this study, we examined how warming, N addition, and AM fungi alter NH3 emissions from high pH saline soils typical of a temperate meadow through a controlled microscopic experiment. The results showed that warming significantly increased soil NH3 emissions, but N addition and combined warming plus N addition had no impact. Inoculations with AM fungi strongly reduced NH3 emissions both under warming and N addition, but AM fungi effects were more pronounced under warming than following N addition. Inoculation with AM fungi reduced soil NH4+-N content and soil pH, and increased plant N content and soil net N mineralization rate while increasing the abundance of ammonia-oxidizing bacterial (AOB) gene. Structural equation modeling (SEM) shows that the regulation of NH3 emissions by AM fungi may be related to soil NH4+-N content and soil pH. These findings highlight that AM fungi can reduce N loss in the form of NH3 by increasing N turnover and uptake under global changes; thus, AM fungi play a vital role in alleviating the aggravation of N loss caused by global changes and in mitigating environmental pollution in the future.

Effects of the nitrogen form ratios on photosynthetic productivity of poplar under condition of phenolic acids.

Phenolic acids can reduce nitrogen utilization rate of poplar, which seriously restrict the productivity of poplar plantation. In this study, three phenolic acid concentrations (T0, T1, and T2) and three ratios of nitrogen forms (NH4+-N to NO3--were 1:3, 1:7, and 1:14) were chosen for orthogonal experiment on poplar (Populus × euramericana "Neva") seedlings to study the effects of the nitrogen form ratios on photosynthetic productivity of poplar under environment of phenolic acids. Results showed that photosynthetic physiology parameters were influenced by both phenolic acid concentration and nitrogen form ratio. The order of net photosynthetic rate (PN) values obtained from 9 treatments were T1-1:3, T0-1:3, T2-1:3, T0-1:7, T1-1:7, T0-1:14, T2-1:7, T1-1:14, and T2-1:14 (from high to low). Under environment of phenolic acids, when poplar were treated with NH4+-N to NO3--N ratio of 1:14, the major limitation factor of photosynthesis was non stomatal factor. When poplar were treated with NH4+-N to NO3-N ratio of 1:3, the major limitation factor of photosynthesis changed to stomatal factor. The leaf nitrogen content and total biomass were obviously positively related with PN (p < 0.05). Phenolic acid inhibited photosynthetic productivity of poplar in a major way and this effect decreased with increase of the content of NH4+-N.

Increasing the ratio of ammonia nitrogen fertilizer in soil can effectively reduce the toxic effect of phenolic acids on poplar and improve the photosynthetic productivity of poplar.

Coupling process-based modeling with machine learning for long-term simulation of wastewater treatment plant operations.

Effective treatment of sewage by wastewater treatment plants (WWTPs) are essential to protecting water environment as well as people's health worldwide. However, operation of WWTPs is usually intricate due to precarious influent characteristics and nonlinear sewage treatment processes. Effective modeling of WWTPs can provide valuable decision-making support to facilitate their daily operations and management. In this study, we have built a novel hybrid model by combining a process-based WWTP model (GPS-X) with a data-driven machine learning model (Random Forest) to improve the simulation of long-term hourly effluent ammonium-nitrogen concentration of a WWTP. Our study results have shown that the hybrid GPS-X-RF model performs the best with a coefficient of determination (R2) of 0.95 and root mean squared error (RMSE) of 0.23 mg/L, followed by the GPS-X model with a R2 of 0.93 and RMSE of 0.33 mg/L and last the Random Forest model with a R2 of 0.84 and RMSE of 0.41 mg/L. Capable of incorporating wastewater treatment mechanisms and utilizing superior data mining capabilities of machine learning, the hybrid model adapts better to the large fluctuations in influent and operating conditions of the WWTP. The proposed hybrid modeling framework may be easily extended to WWTPs of various size and types to simulate their operations under increasingly variable environmental and operating conditions.

Genome Identification and Expression Profiles in Response to Nitrogen Treatment Analysis of the Class I CCoAOMT Gene Family in Populus.

Lignin is essential for the characteristics and quality of timber. Nitrogen has significant effects on lignin contents in plants. Nitrogen has been found to affect wood quality in plantations and lignin content in plants. Caffeoyl-CoA 3-O-methyltransferase (CCoAOMT) is an important methyltransferase in lignin biosynthesis. However, the classification of woody plant CCoAOMT gene family members and the regulation mechanism of nitrogen are not clear. Bioinformatics methods were used to predict the members, classification, and transcriptional distribution of the CCoAOMT gene family in Populus trichocarpa. The results showed that there were five PtCCoAOMTs identified, and they could be divided into three sub-groups according to their structural and phylogenetic features. The results of tissue expression specificity analysis showed that: PtCCoAOMT1 was highly expressed in roots and internodes; PtCCoAOMT2 was highly expressed in roots, nodes, and internodes, PtCCoAOMT3 was highly expressed in stems; PtCCoAOMT4 was highly expressed in young leaves, and, PtCCoAOMT5 was highly expressed in roots. Different forms and concentrations of nitrogen had varying effects on the expression patterns of genes in different plant tissue types. The results of real-time PCR showed that the expression levels of PtCCoAOMT1 and PtCCoAOMT2 in stems increased significantly under different forms of nitrogen. PtCCoAOMT3 and PtCCoAOMT4 were induced by nitrate nitrogen in upper stems and lower leaves, respectively. PtCCoAOMT4 and PtCCoAOMT5 were induced by different concentrations of nitrate nitrogen in lower stems and roots, respectively. These results could provide valuable information for revealing the differences between functions and expression patterns of the various CCoAOMT gene family members under different forms and concentrations of exogenous nitrogen in poplar.

Rapid Detection of Available Nitrogen in Soil by Surface-Enhanced Raman Spectroscopy.

Soil-available nitrogen is the main nitrogen source that plants can directly absorb for assimilation. It is of great significance to detect the concentration of soil-available nitrogen in a simple, rapid and reliable method, which is beneficial to guiding agricultural production activities. This study confirmed that Raman spectroscopy is one such approach, especially after surface enhancement; its spectral response is more sensitive. Here, we collected three types of soils (chernozem, loess and laterite) and purchased two kinds of nitrogen fertilizers (ammonium sulfate and sodium nitrate) to determine ammonium nitrogen (NH4-N) and nitrate nitrogen (NO3-N) in the soil. The spectral data were acquired using a portable Raman spectrometer. Unique Raman characteristic peaks of NH4-N and NO3-N in different soils were found at 978 cm-1 and 1044 cm-1, respectively. Meanwhile, it was found that the enhancement of the Raman spectra by silver nanoparticles (AgNPs) was greater than that of gold nanoparticles (AuNPs). Combined with soil characteristics and nitrogen concentrations, Raman peak data were analyzed by multiple linear regression. The coefficient of determination for the validation (Rp2) of multiple linear regression prediction models for NH4-N and NO3-N were 0.976 and 0.937, respectively, which deeply interpreted the quantitative relationship among related physical quantities. Furthermore, all spectral data in the range of 400-2000 cm-1 were used to establish the partial least squares (PLS), back-propagation neural network (BPNN) and least squares support vector machine (LSSVM) models for quantification. After cross-validation and comparative analysis, the results showed that LSSVM optimized by particle swarm methodology had the highest accuracy and stability from an overall perspective. For all datasets of particle swarm optimization LSSVM (PSO-LSSVM), the Rp2 was above 0.99, the root mean square errors of prediction (RMSEP) were below 0.15, and the relative prediction deviation (RPD) was above 10. The ultra-portable Raman spectrometer, in combination with scatter-enhanced materials and machine learning algorithms, could be a promising solution for high-efficiency and real-time field detection of soil-available nitrogen.

LjAMT2;2 Promotes Ammonium Nitrogen Transport during Arbuscular Mycorrhizal Fungi Symbiosis in Lotus japonicus.

Arbuscular mycorrhizal fungi (AMF) are important symbiotic microorganisms in soil that engage in symbiotic relationships with legumes, resulting in mycorrhizal symbiosis. Establishment of strong symbiotic relationships between AMF and legumes promotes the absorption of nitrogen by plants. Ammonium nitrogen can be directly utilised by plants following ammonium transport, but there are few reports on ammonium transporters (AMTs) promoting ammonium nitrogen transport during AM symbiosis. Lotus japonicus is a typical legume model plant that hosts AMF. In this study, we analysed the characteristics of the Lotus japonicus ammonium transporter LjAMT2;2, and found that it is a typical ammonium transporter with mycorrhizal-induced and ammonium nitrogen transport-related cis-acting elements in its promoter region. LjAMT2;2 facilitated ammonium transfer in yeast mutant supplement experiments. In the presence of different nitrogen concentrations, the LjAMT2;2 gene was significantly upregulated following inoculation with AMF, and induced by low nitrogen. Overexpression of LjAMT2;2 increased the absorption of ammonium nitrogen, resulting in doubling of nitrogen content in leaves and roots, thus alleviating nitrogen stress and promoting plant growth.

A comprehensive techno-economic analysis of income-generating sources on the conversion of real sheep slaughterhouse waste stream into valorized by-products.

The present analysis was conducted as the first research to assess the techno-economic viability of the value-added by-products (struvite, blood meal, bone meal, and raw sheepskin) from a medium-scale sheep slaughterhouse facility with a slaughtering capacity of 300 sheep per day. For this aim, a comparative technical and economic feasibility analysis was performed to assess the synergistic use of slaughterhouse-oriented rendering wastes and struvite recovery from real sheep abattoir effluent within the framework of detailed cost breakdown, break-even point, and payback period analyses. The experimental findings clearly showed that under the optimal conditions (chemical combination of MgCl2.6H2O + NaH2PO4.2H2O, a molar ratio of Mg2+:NH4+-N:PO43--P = 1.2:1:1, a reaction pH of 9.0, an initial ammonium concentration of 240 mg NH4+-N/L, and a reaction time of 15 min), struvite precipitation could effectively remove about 73%, 64%, 59%, and 82% of NH4+-N, TCOD, SCOD, and color, respectively, from the real sheep slaughterhouse waste stream. Based on various up-to-date techno-economic items considered within the break-even point analysis, the sheep slaughterhouse facility was estimated to achieve the targeted net income (€100/day) for any selling prices of €1041.30/ton, €640.05/ton, €263.72/ton, and €1.012/hide, respectively, for struvite, blood meal, bone meal, and raw sheepskin. Steel construction and chemicals were determined as the most costly components for CAPEX (capital expenditures) and OPEX (operating expenditures), respectively, and selling prices of bone meal and raw sheepskin were found to be the most critical income items on the profitability of the slaughterhouse facility. Co-monetary assessment of the struvite process and valorized compounds corroborated the economic viability of the proposed project with the payback periods of about 6.3 and 5.5 years, respectively, for the current market and the profit-oriented conditions without subsidy. The findings of this feasibility analysis, as the first of its own, could be used as guideline for simplifying the decision-making with regards to the feasibility of similar facilities and commercialization of profitable by-products.

Rapid Detection of Different Types of Soil Nitrogen Using Near-Infrared Hyperspectral Imaging.

Rapid and accurate determination of soil nitrogen supply capacity by detecting nitrogen content plays an important role in guiding agricultural production activities. In this study, near-infrared hyperspectral imaging (NIR-HSI) combined with two spectral preprocessing algorithms, two characteristic wavelength selection algorithms and two machine learning algorithms were applied to determine the content of soil nitrogen. Two types of soils (laterite and loess, collected in 2020) and three types of nitrogen fertilizers, namely, ammonium bicarbonate (ammonium nitrogen, NH4-N), sodium nitrate (nitrate nitrogen, NO3-N) and urea (urea nitrogen, urea-N), were studied. The NIR characteristic peaks of three types of nitrogen were assigned and regression models were established. By comparing the model average performance indexes after 100 runs, the best model suitable for the detection of nitrogen in different types was obtained. For NH4-N, R2p = 0.92, RMSEP = 0.77% and RPD = 3.63; for NO3-N, R2p = 0.92, RMSEP = 0.74% and RPD = 4.17; for urea-N, R2p = 0.96, RMSEP = 0.57% and RPD = 5.24. It can therefore be concluded that HSI spectroscopy combined with multivariate models is suitable for the high-precision detection of various soil N in soils. This study provided a research basis for the development of precision agriculture in the future.

Influence of the catchment area use on the water quality in the Utrata River.

The present paper discusses the impact of land use and seasons on the concentration of nutrients in the waters of the Utrata River (Pruszków Poviat, Mazowieckie Voivodeship) from April 2018 to March 2019. The pollution of rivers by nutrients is a major problem for society. Surface water is a source of drinking water, water used for industrial and agricultural purposes. With the increasing pollution of rivers, the purification process for these purposes becomes more expensive and more challenging. To assist in carrying out activities aimed at reducing the inflow of biogenic substances into large river systems and then down to the Baltic Sea, we analyzed the spatial and temporal dynamics of loads from the entire Utrata River catchment area. We divided the entire catchment area into three impact zones: grasslands and wastelands, urbanized areas, and agricultural land and examined changes in nutrient concentrations (total phosphorus, nitrate nitrogen, ammonium nitrogen) in each of the zones. The results were statistically processed using the 1-factor ANOVA method with the p-value of significance below 0.05. Research indicates an increase in the concentration of total phosphorus and nitrogen forms down the course of the river in urban and agricultural areas with persistently low concentrations of these biogenic substances in grasslands.

Advanced phosphate and nitrogen removal in water by La-Mg composite.

A novel La-Mg composite was prepared for the removal of low concentration phosphate and ammonium nitrogen to alleviate the eutrophication problem. The composition and morphology of La-Mg composite was characterized; Its surface was composed of La, Mg, C, and O elements, with a specific surface area of 21.92 m2/g. La-Mg composite presented excellent removal of phosphate (100%) and nitrogen (96.8%), and the adsorption capacity reached 49.72 mg-P/g and 159.30 mg-N/g for separated adsorption. The composite also had a wide pH usability range (3-11 for P and 3-9 for N) and the adsorption process was almost not disturbed by coexisting ions. After adsorption, it could be regenerated by Na2CO3 and reused effectively. For actual water treatment, a very low residual P of 0.01 mg/L and N of 0.05 mg/L were achieved. Furthermore, Mechanism analysis showed that P adsorption involved ligand exchange and electrostatic attraction. The potential mechanisms of N adsorption involved electrostatic attraction and ion exchange. The results showed that the La-Mg composite is a novel and efficient adsorbent for actual water treatment to achieve ultra-low nutrients concentration.

Pineapple peel biochar and lateritic soil as adsorbents for recovery of ammonium nitrogen from human urine.

Human urine is a rich source of nitrogen which can be captured to supplement the existing sources of nitrogen fertilizers thus contributing to enhanced crop production. However, urine is the major contributor of macronutrients in municipal wastewater flows resulting into eutrophication of the receiving water bodies. Herein, pineapple peel biochar (PPB), and lateritic soil (LS) adsorbents were prepared for the safe removal of ammonium nitrogen (NH4+-N) from human urine solutions. Physicochemical properties of PPB, and LS were characterized by scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS), X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA) to investigate the relationship of their properties with NH4+-N adsorption. Langmuir, Freundlich, and Dubinin-Radushkevich (D-R) isotherm models were employed to correlate the experimental equilibrium adsorption data. The effect of contact time and initial concentration of NH4+-N adsorption was also evaluated. The D-R isotherm model best described the behaviour of NH4+-N adsorption on both PPB and LS based on the coefficient of correlation values. This model showed that the adsorption of NH4+-N on both samples was a physical process with PPB and LS having mean surface adsorption energies of 1.826 × 10-2, and 1.622 × 10-2 kJ/mol, respectively. The PPB exhibited a slightly higher adsorption capacity for NH4+-N (13.40 mg/g) than LS (10.73 mg/g) with the difference attributed to its higher surface area and porosity. These values are good indicators for assessing the effectiveness of the materials for adsorption of NH4+-N from human urine.

Long-term performance of three mesophilic anaerobic digesters to convert animal and agro-industrial wastes into organic fertilizer.

Few studies have investigated the performance of anaerobic digestion (AD) to convert animal and agro-industrial wastes to organic fertilizers over a long-term field conditions. This paper studied three large-scale mesophilic digesters (D1eD3) over two years for their effects on feedstocks, which were dairy manure for D1 and D2 and co-digestion mixed manure and agro-industrial wastes for D3. Hydraulic retention times (HRT) were 9 d for D1, 12 d for D2, and 34 d for D3. Digester influent and effluent samples were taken every two months from the digesters and analyzed for pH, and concentrations of total solids (TS), ammonium nitrogen (NH4-N), total Kjeldahl nitrogen (TKN), total phosphorus (TP), and eight metals. The study revealed high variability in converting feedstock in the three digesters. Compared with their respective influent, the mean digester effluent pH decreased from 7.9 by 0.6 in D1 (p < 0.01) and by 0.3 in D2 (p < 0.01), but it increased from 6.1 by 1.8 in D3 (p < 0.01). The mean digester effluent TS increased from 3.4% by 0.1% (p > 0.05) in D1, but it decreased from 4.9% by 1.3% in D2 (p < 0.05) and from 12.3% by 4.8% in D3 (p < 0.01). All three digesters significantly increased NH4-N concentrations by 21.4 e81.8% (p < 0.05), but insignificantly changed TKN and TP concentrations (p > 0.05). Effects of AD on all metal concentrations were mixed and were insignificant (p > 0.05) because of large concentration variations. However, study of a ratio quotient (q Mg ) using magnesium (Mg) as the reference discovered accumulation of NH4-N, copper, potassium, and sodium, but loss of TKN, TP, iron, manganese, zinc, and calcium during AD for D2 and D3. The impact of AD conversion was closely related with types of feedstock (on pH) and HRT (on TS and NH4-N). The results of this study can assist in developing strategies for cleaner production using AD in an environmentally sustainable manner.

Impact of volatile fatty acids to alkalinity ratio and volatile solids on biogas production under thermophilic conditions.

The study assessed the impact of volatile fatty acids (VFA) to total alkalinity (TA) ratio (VFA/TA), and percentage volatile solids (VS) reduction of batch and semi-continuous anaerobic co-digestion of palm nut paste waste (PNPW) and anaerobic-digested rumen waste (ADRW) on digester stability and biogas production under the environmental condition of 50 ± 1°C and hydraulic retention time of 21 days for the batch studies and 14 days for semi-continuous co-digestion. The co-digestion ratios were based on percentage digester volume corresponding to 90%:10%, 75%:25% and 50%:50%. During batch and semi-continuous anaerobic co-digestion, VFA/TA of 0.32-1.0 and VS reduction of 53-67% were observed as the stable range at which biogas production was maximum. In terms of semi-continuous anaerobic digestion (AD), except for the 50%:50% ratio where biogas production progressed steadily from the first to fourteenth days, biogas production initially dropped from 180.1 to 171.3 mL between the first and third days of the 90%:10% reaching a maximum of 184 mL on the fourteenth day. Biogas production declined from 198.8 to 187.5 mL on the second day and then increased to 198.8 ± 0.5 mL in the case of the 75%:25% with a significant difference between the treatment ratios at p < 0.05. Therefore, the study can confirm that the 50%:50% ratio (PNPW:ADRW) is a suitable option for managing crude fat-based waste under thermophilic AD due to its potential for rapid start-up and complete biodegradation of active biomass within a 21-day period. This presupposes that residual methane as greenhouse gas will be void in the effluent if disposed of.

Bacillus velezensis LG37: transcriptome profiling and functional verification of GlnK and MnrA in ammonia assimilation.

BACKGROUND: In recent years, interest in Bacillus velezensis has increased significantly due to its role in many industrial water bioremediation processes. In this study, we isolated and assessed the transcriptome of Bacillus velezensis LG37 (from an aquaculture pond) under different nitrogen sources. Since Bacillus species exhibit heterogeneity, it is worth investigating the molecular mechanism of LG37 through ammonia nitrogen assimilation, where nitrogen in the form of molecular ammonia is considered toxic to aquatic organisms. RESULTS: Here, a total of 812 differentially expressed genes (DEGs) from the transcriptomic sequencing of LG37 grown in minimal medium supplemented with ammonia (treatment) or glutamine (control) were obtained, from which 56 had Fold Change ≥2. BLAST-NCBI and UniProt databases revealed 27 out of the 56 DEGs were potentially involved in NH4+ assimilation. Among them, 8 DEGs together with the two-component regulatory system GlnK/GlnL were randomly selected for validation by quantitative real-time RT-PCR, and the results showed that expression of all the 8 DEGs are consistent with the RNA-seq data. Moreover, the transcriptome and relative expression analysis were consistent with the transporter gene amtB and it is not involved in ammonia transport, even in the highest ammonia concentrations. Besides, CRISPR-Cas9 knockout and overexpression glnK mutants further evidenced the exclusion of amtB regulation, suggesting the involvement of alternative transporter. Additionally, in the transcriptomic data, a novel ammonium transporter mnrA was expressed significantly in increased ammonia concentrations. Subsequently, OEmnrA and ΔmnrA LG37 strains showed unique expression pattern of specific genes compared to that of wild-LG37 strain. CONCLUSION: Based on the transcriptome data, regulation of nitrogen related genes was determined in the newly isolated LG37 strain to analyse the key regulating factors during ammonia assimilation. Using genomics tools, the novel MnrA transporter of LG37 became apparent in ammonia transport instead of AmtB, which transports ammonium nitrogen in other Bacillus strains. Collectively, this study defines heterogeneity of B. velezensis LG37 through comprehensive transcriptome analysis and subsequently, by genome editing techniques, sheds light on the enigmatic mechanisms controlling the functional genes under different nitrogen sources also reveals the need for further research.

Chitosan Modified Zeolite Molecular Sieve Particles as a Filter for Ammonium Nitrogen Removal from Water.

Drinking water containing a high amount of ammonium-nitrogen (NH4+-N) is not effectively removed by conventional treatment processes and can cause eutrophication. In this research, a composite adsorbent based on chitosan crosslink with zeolite molecular sieve (CTS-ZMS) was prepared for NH4+-N removal through dynamic adsorption filter experiments. Effect of bed depth (30, 50 and 70 cm), flow rate (32, 49 and 65 mL/min), initial pH value (4.5, 6.5 and 8.5) and influent NH4+-N concentration (3, 5 and 7 mg/L) was examined by using a filter column packed with CTS-ZMS particles. The Thomas model was applied to study the breakthrough curves and adsorption capacity. The optimal process parameters of the aforementioned factors were obtained at bed depth of 70 cm, flow rate of 32 mL/min, pH of 6.5 and initial NH4+-N concentration of 7 mg/L. Scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and Fourier Transform Infrared Spectroscopy (FTIR) were investigated to analyze the structure and morphology of the CTS-ZMS adsorbents before and after 3 months running. The EDS and FTIR results showed Na+ and the active functional groups of -OH, -NH2 and -COO- on CTS-ZMS adsorbent particles reacted with ammonium nitrogen. The results of this study supported the use of CTS-ZMS to improve drinking water filtration processes by increasing ammonium nitrogen reductions.

Nexus between the microbial diversity level and the stress tolerance within the biogas process.

To investigate whether there is a nexus between the microbial diversity level (taxonomic, functional and ecological) and the stress tolerance potential of the microbial community, the impact of different ammonium sources was evaluated. Therefore reactors adapted either to the anaerobic digestions of sugar beet silage or maize silage (SBS/MS) were supplemented with animal manure (M) or ammonium carbonate (A). The results showed that increasing concentrations of total ammonium nitrogen (TAN) were not the only reason for community changes: the bacterial community in the reactors given animal manure became more similar over time compared to the reactors given ammonium carbonate. However, this study revealed that a bacterial community with a few dominant members led to a functional more flexible archaeal community (SBS reactors) which was more stress resistant under the experimental conditions. This indicates that a higher functional diversity within a certain part of the community, in the present study the archaeal community, is one important factor for process stability due to a higher tolerance to increasing amounts of process-inhibiting metabolites such as TAN. Compared to this a bacterial community with higher amount of more evenly distributed community members combined with a more rigid archaeal community (MS reactors) showed a lower stress tolerance potential. Moreover it was observed that the disappearance of members of the phylum Cloacimonetes can be used as an indicator for an upcoming process disturbance due to increasing TAN concentrations.

Corn waste valorization to generate activated hydrochar to recover ammonium nitrogen from compost leachate by hydrothermal assisted pretreatment.

Valorization of corn waste involves synthesis of hydrochar for use as a sorbent for ammonium nitrogen recovery from swine manure compost leachate. However, the inability to directly capture organic nitrogen and insoluble nitrogen, and the low sorption ability of hydrochar remain key issues. To overcome these issues, we used hydrothermal assisted pretreatment of compost leachate to promote the solubilization of nitrogen contained in feces, and the conversion of organic nitrogen into ammonium nitrogen in the compost leachate. The synthesis hydrochar was activated with KOH to enhance its sorption ability, and then characterized by SEM, FTIR, elemental analysis, specific surface area, pore volume and size analysis. The content of ammonium nitrogen in hydrolysis leachate at 210 °C increased by 22.3% compared with raw compost leachate. 3D-EEM analysis indicated that aromatic protein substances were rapidly hydrolyzed to gradually increase the content of ammonium nitrogen and produce considerable humic acids. The maximum adsorption capacity of ammonium nitrogen reached 140.3 mg/g at 45 °C for KOH-activated hydrochar of 260 °C. The Langmuir isotherm and pseudo second order kinetic models were good fit for the adsorption process of ammonium nitrogen at higher temperature (35 °C or 45 °C), and this reaction was mainly dominated by chemisorption. The adsorption of ammonium nitrogen was exothermic, spontaneous, and showed an increase in disorder at the solid-liquid interface. For resource recovery, the total release amount of ammonium nitrogen of five interval extractions could reach 12.2% of maximum adsorption capacity (140.3 mg/g) under alkaline (pH 8.0) condition. The nitrogen mass balance calculation revealed that 8.9% of total nitrogen in the compost leachate could be recovered.

Chemical composition and bioactive properties of Cichorium spinosum L. in relation to nitrate/ammonium nitrogen ratio.

BACKGROUND: Nitrogenous fertilizers may affect the yield and quality of leafy vegetables via the application rate and nitrogen form. In the present study, the effect of the nitrate:ammonium nitrogen ratio in the nutrient solution on the chemical composition and bioactive properties of Cichorium spinosum leaves was evaluated. For this purpose, C. spinosum plants were fertigated with nutrient solution containing different ratios of nitrate: ammonium nitrogen: (i) 100:0 NO3 -N:NH4 -N; (ii) 75:25 NO3 -N:NH4 -N; (iii) 50:50 NO3 -N:NH4 -N; (iv) 25:75 NO3 -N:NH4 -N; and (v) 0:100 NO3 -N:NH4 -N of total nitrogen; as well as (vi) 100% ureic nitrogen. RESULTS: The only detected tocopherol isoforms were α- and δ-tocopherol, which were positively affected by nitrate nitrogen (100:0 NO3 -N:NH4 -N). Similar results were observed for individual and total organic acids. The main detected sugars were fructose, glucose and sucrose, with a varied effect of nutrient solution composition on their content, whereas total sugar concentration was positively affected by a balanced or a slightly increased proportion of NH4 -N (50:50 and 25:75 NO3 -N:NH4 -N). The fatty acids profile was beneficially affected by the highest NH4 -N ratio (0:100 NO3 -N:NH4 -N), whereas higher amounts of NO3 - than NH4 + nitrogen (75:25 NO3 -N:NH4 -N) resulted in a higher content of total phenolic compounds. Finally, no cytotoxic effects were observed against non-tumor (PLP2, HeLa) and tumor (HepG2, MCF-7, NCI-H460) cell lines for any of the studied nutrient solutions. CONCLUSION: The modulation of NO3 -N:NH4 -N ratio in the nutrient solution supplied to C. spinosum may enhance the content of desirable health-promoting compounds and reduce the content of antinutrients, thus increasing the overall quality of the final product without compromising yield. © 2019 Society of Chemical Industry.

Revealing the effect of preparation parameters on zeolite adsorption performance for low and medium concentrations of ammonium.

The effect of preparation parameters on the performance of zeolite for ammonium (20-300 mg N/L) adsorption from simulated wastewater is reported. It was found that the ratios of Na2O/SiO2 and Si/Al had a more important influence than crystallization time on zeolite adsorption properties. Relatively low Na2O/SiO2 ratios were beneficial for fabrication of zeolites with high proportions of micropore area and volume, which led to the surface adsorption mechanism being dominated by surface free energy and pore effects. However, with decreasing Si/Al ratios, the effect of ion-exchange was more prominent due to the high negative surface potential of zeolite. In addition, the concentration of weak acid sites on the zeolites was increased with lower ratios of Na2O/SiO2 and Si/Al, which may promote ammonium removal. Therefore, the most effective zeolite for ammonium removal, which was fabricated at Na2O/SiO2 = 1.375, Si/Al = 4 and crystallization time of 48 hr, exhibited the cooperative effects of adsorption, ion-exchange and a large amount of weak acid sites. The maximum ammonium adsorption capacity (35.06 ±â€¯0.98 mg/g) and the removal efficiency (94.44% ±â€¯4.00%) were obtained at the dosage of 4.0 g/L zeolite NaX at ammonium concentrations of 300 mg N/L and 20 mg N/L, respectively. The Freundlich isotherm and pseudo-first-order kinetics models provided excellent fitting for the ammonium adsorption process. In addition, zeolite NaX showed about 1.23-3.2 times the ammonium adsorption capacity of clinoptilolite. The stable and efficient reusability of zeolite NaX after five regeneration cycles demonstrated that this adsorbent has considerable potential for practical industrial applications.