Nitrate Removal Process Research Articles

Novel sulfide-driven denitrification methane oxidation (SDMO) system based on SBR-MBfR and EGSB-MBfR

Traditional denitrification process consumes external organic carbon leading to an increase in treatment costs and carbon emission. A novel sulfide-driven denitrification methane oxidation (SDMO) system, which could simultaneously utilize CH4 and H2S in biogas as electron donors for denitrification to reduce the cost and carbon emission, has been successfully operated in two kinds of reactors SBR-MBfR and EGSB-MBfR for ∼ 200 days in this study. The performance and microbial community were explored meanwhile machine learning approach have been used for predicting the complex effects on SDMO’s denitrification efficiency. Result shows SBR-MBfR’s superior performance with the maximum nitrate removal efficiency > 90 % while the denitrification rates and biological activity were also better than EGSB-MBfR. The autotrophic denitrification (Auto-D) contributed 5 % much more for nitrate removal in SBR-MBfR than EGSB-MBfR while denitrification anaerobic methane oxidation (DAMO) was more prominent in EGSB-MBfR. Nineteen machine learning models were used for operation data training and random forest regressor was demonstrated to be the optimal model for predicting nitrate removal efficiency in SDMO. According to random forest regressor’s analysis, HRT presented the highest importance in affecting SDMO nitrate removal efficiency. After the introduction of biogas for domestication, Auto-D bacteria Thiobacillus was the dominant bacteria in both systems occupying > 20 % and the abundance would increase gradually from ∼ 20 % to ∼ 60 % as H2S content rising. A hidden positive correlation between DAMO bacteria Candidatus Methylomirabilis and Thiobacillus was uncovered by mantel test analysis here, implying the integrating of Auto-D and DAMO process for nitrate removal. This study not only provides insights into the novel SDMO technology but also offers a potential advancement in simultaneously low-carbon wastewater treatment and biogas utilization.

Bioremediation of nitrate in agricultural drainage ditches: Impacts of low-grade weirs on microbiomes and nitrogen cycle gene abundance

Artificial drainage is essential for the success of modern agriculture, but it can also accelerate the movement of nutrients, especially nitrate, from soil to surrounding and downstream water bodies. Removal of nitrate from agricultural drainage by using controlled drainage systems, such as ditches installed with low-grade weirs, has been shown to help reduce nutrient loading into watersheds. However, the effect of low-grade weirs varies greatly, likely due to the differences in climate, system designs (e.g., hydraulic characteristics), and the resulting variation in microbial structures and functions in the ditch. In this study, we analyzed the temporal and spatial dynamics of microbiomes in a paired ditch system with weir-installed and uninstalled (control) channels over two years by using the 16S rRNA gene amplicon sequencing and the high-throughput quantitative PCR targeting various N cycle-associated genes [the Nitrogen Cycle Evaluation (NiCE) chip]. The installation of the low-grade weir had a significant impact on the microbiome structure and the distribution of denitrifiers. Microbiome structures also differed significantly between the ditch inlets and the outlets. Denitrification functional genes were more abundant in the inlets than in the other locations and in the channel installed with a low-grade weir. Additionally, oxygenic denitrifiers that utilize nitric oxide dismutase (nod) to produce N2 and O2 gases from nitric oxide were detected in the ditch channels, suggesting the occurrence of nitrate removal process that bypasses the production of nitrous oxide (N2O). The ditch microbiomes sampled during high-flow seasons (i.e., spring and fall) exhibited greater similarity to each other than microbiomes sampled during low-flow seasons (i.e., summer). Taken together, this study indicates that the low-grade weirs have the potential to foster a more favorable environment for denitrifiers, resulting in an increase in the abundance of denitrification functional genes. These findings could offer valuable insights into system management and optimization strategies.

Application of flow airlift fluidized bed (CAFB) - Aerobic denitrification bioreactor using polycaprolactone (PADR) as organic carbon source and biofilm carrier for synthetic marine aquaculture wastewater treatment

Aerobic denitrification, a novel method for complete nitrate removal process, relies on a constant carbon supply, and carbon availability can be a limiting factor for the process. Three biodegradable polymers - polybutylene succinate (PBS), polycaprolactone (PCL), and polylactic acid (PLA) were used as carbon source of aerobic denitrifying bacteria, Halomonas venusta for treating recirculating aquaculture wastewater in batch tests, respectively. The group utilizing PCL displayed the greatest efficiency in nitrate removal. Afterwards, a continuous flow airlift fluidized bed (CAFB) - aerobic denitrification bioreactor using PCL(PADR) as bio-carriers and carbon source was started up. The effect of shifting temperature on the nitrate removal and microbial community of CAFB-PADR was investigated under different hydraulic retention times (HRT). The results showed that no significant difference was detected in denitrification activity at 25 and 30 °C condition, where the denitrification rate was 1.1–1.8 times higher than that at 15 °C. However, the nitrogen removal efficiency was above 50 % and there was barely accumulation of nitrite at 15 °C, indicating the good nitrate removal performance in CAFB-PADR at all three temperature conditions. Microbial composition analyses revealed that as the temperature decreased, the relative abundance of Gammaproteobacteria increased, while those of Alphaproteobacteria and Bacteroidia diminished decreased. The existence of denitrifying function genera (Marinobacter, Pseudomonas, Halomonas and Hydrogenophaga) ensured the rapid removal of nitrogen in the biofilter. When the temperature dropped to 15 °C, Pseudomonas progressively took the position of Marinobacter, both of which had denitrification and degradation activities. The relative abundance of the denitrifying bacteria Halomonas that we inoculated has been less than 1 % since phase II. Overall, the PCL-supported CAFB-PADR demonstrated in this study shows potential for removing high concentrations of nitrate from recirculating marine aquaculture wastewater.

Ultrahigh carbon utilization in symbiotic biofilm-sludge denitrification systems using polymers as sole electron donors

The polymer-based denitrification system is an effective nitrate removal process for treating low carbon/nitrogen wastewater. However, in polymer denitrification systems, carbon used for the denitrification reaction is weakly targeted. Improving the efficiency of carbon utilization in denitrification is important to reduce carbon wastage. In this study, a symbiotic biofilm-sludge denitrification system was constructed using polycaprolactone as electron donors. Results show that the carbon release amount in 120 days was 85.32±0.46 g, and the unit mass of polycaprolactone could remove 1.55±0.01 g NO3−-N. Meaningfully, the targeted carbon utilization efficiency for denitrification could achieve 79%-85%. The quantitative results showed that the release of electron donors can be well matched to the demand for electron acceptors in the biofilm-sludge denitrification system. Overall, the symbiotic system can improve the nitrate removal efficiency and reduce the waste of carbon source.

Application of artificial intelligence in modeling of nitrate removal process using zero-valent iron nanoparticles-loaded carboxymethyl cellulose.

This study explores nitrate reduction in aqueous solutions using carboxymethyl cellulose loaded with zero-valent iron nanoparticles (Fe0-CMC). The structures of this nano-composite were characterized using various techniques. Based on the characterization results, the specific surface area of Fe0-CMC measured by the Brunauer-Emmett-Teller analysis were 39.6m2/g. In addition, Scanning Electron Microscopy images displayed that spherical nano zero-valent iron particles (nZVI) with an average particle diameter of 80nm are surrounded by carboxymethyl cellulose and no noticeable aggregates were detected. Batch experiments assessed Fe0-CMC's effectiveness in nitrate removal under diverse conditions including different adsorbent dosages (Cs, 2-10mg/L), contact time (t, 10-1440min), initial pH (pHi, 2-10), temperature (T, 10-55°C), and initial concentration of nitrate (C0, 10-500mg/L). Results indicated decreased removal with higher initial pHi and C0, while increased Cs and T enhanced removal. The study of nitrate removal mechanism by Fe0-CMC revealed that the redox reaction between immobilized nZVI on the CMC surface and nitrate ions was responsible for nitrate removal, and the main product of this reaction was ammonium, which was subsequently completely removed by the synthesized nanocomposite. In addition, a stable deviation quantum particle swarm optimization algorithm (SD-QPSO) and a least square error method were employed to train the ANFIS parameters. To demonstrate model performance, a quadratic polynomial function was proposed to display the performance of the SD-QPSO algorithm in which the constant parameters were optimized through the SD-QPSO algorithm. Sensitivity analysis was conducted on the proposed quadratic polynomial function by adding a constant deviation and removing each input using two different strategies. According to the sensitivity analysis, the predicted removal efficiency was most sensitive to changes in pHi, followed by Cs, T, C0, and t. The obtained results underscore the potential of the ANFIS model (R2 = 0.99803, RMSE = 0.9888), and polynomial function (R2 = 0.998256, RMSE = 1.7532) as accurate and efficient alternatives to time-consuming laboratory measurements for assessing nitrate removal efficiency. These models can offer rapid insights and predictions regarding the impact of various factors on the process, saving both time and resources.

Carbon dioxide and weak magnetic field enhance iron-carbon micro-electrolysis combined autotrophic denitrification

Combining iron-carbon micro-electrolysis and autotrophic denitrification is promising for nitrate removal from wastewater. In this study, four continuous reactors were constructed using CO2 and weak magnetic field (WMF) to address challenges like iron passivation and pH stability. In the reactors with CO2 + WMF (10 and 35 mT), the increase in total nitrogen removal efficiency was significantly higher (96.2 ± 1.6 % and 94.1 ± 2.7 %, respectively) than that of the control (51.6 ± 2.7 %), and Fe3O4 converted to low-density FeO(OH) and FeCO3, preventing passivation film formation. The WMF application decreased the N2O emissions flux by 8.7 % and 20.5 %, respectively. With CO2 + WMF, the relative enzyme activity and abundance of denitrifying bacteria, especially unclassified_Rhodocyclaceae and Denitratisoma, increased. Thus, this study demonstrates that CO2 and WMF optimize the nitrate removal process, significantly enhancing removal efficiency, reducing greenhouse gas emissions, and improving process stability.

Stable continuous flow CANDAN process transitioning from anammox UASB reactor by facilitating indigenous nitrite-producing denitrification community

The emerging nitrogen removal process known as CANDAN (Complete Ammonium and Nitrate removal via Denitratation-Anammox over Nitrite) has been developed in Sequencing Batch Reactors (SBRs). Yet, starting up and maintaining stability in continuous-flow reactors remain challenging. This study explores the feasibility of transitioning the CANDAN process from an anammox-dominated process by introducing appropriate external organics to facilitate indigenous nitrite-producing denitrification community in an Upflow Anaerobic Sludge Blanket (UASB) reactor. 150-day operation results indicate that under feeding rates of domestic wastewater at 0.54 L/h and nitrate-containing wastewater at 1.08 L/h, excellent N removal was achieved, with effluent TN below 10.0 mg N/L. Adding external sodium acetate at a COD/NO3−-N = 2.0 triggered denitratation, ex-situ denitrification activity tests showed increased nitrite production rates, maintaining the nitrate-to-nitrite transformation ratio (NTR) above 90 %. Consequently, anammox activity was consistently maintained, dominating Total Nitrogen (TN) removal with a contribution as high as 78.3 ± 8.0 %. Anammox functional bacteria, Brocadia and Kuenenia were identified and showed no decrease throughout the operation, indicating the robustness of the anammox process. Notably, the troublesome of sludge flotation, did not occur, also contributing to sustained outstanding performance. In conclusion, this study advances our understanding of the synergistic interplay between anammox and denitrifying bacteria in the Anammox-UASB system, offering technical insights for establishing a stable continuous-flow CANDAN process for simultaneous ammonium and nitrate removal.

Deficient Tin oxide nanofibers with regulated valence for efficient nitrate reduction to ammonia

Electrocatalytic nitrate reduction emerges as a promising process for removal of nitrate and simultaneous production of value-added ammonia, but robust electrocatalysts with high selectivity are required due to the large dissociation energy of N≡O in nitrate. Herein, we propose oxygen deficient Tin oxide nanofibers with regulated bivalence (SnO) and tetravalency (SnO2-δ) as efficient catalysts for nitrate reduction reaction (NitRR). Such quadrivalent catalyst achieves a large NH3 yield of 17.27 mg h−1 mgcat.−1 and an extremely high Faradaic Efficiency (FE) of 95.67 % in 0.1 M PBS with 0.1 M NO3−, which also exhibits excellent electrochemical stability. Material calculations reveal that SnO2-δ exhibits a direct band gap of 0.79 eV, smaller than 1.17 eV for SnO with an indirect band gap, and the potential determining step (*NO2 → *NO) hits a free energy change of only 0.1 eV.

Characterization of simultaneous ammonium and nitrate removal and microbial communities in airlift reactor using 3-hydroxybutyrate-co-3-hydroxyvalerate (PHBV) as carbon source and biofilm carrier

As a novel trend, solid carbon sources are applied to act as electron donors and biofilm carrier in biological denitrification process. In this study, simultaneous nitrate and ammonium removal process in an airlift sequencing batch reactor using 3-hydroxybutyrate-co-3-hydroxyvalerate (PHBV) as carbon source and biofilm carrier under intermittent aeration conditions was established to treat effluent of synthetic marine recirculating aquaculture system. The results showed that maximum nitrate and ammonia nitrogen removal rates of 0.45 and 0.09 kg m−3 d−1 were achieved. No significant nitrite accumulation was found during 200-day operation, while effluent dissolved organic carbon accumulation and particle size reduction significantly increased. Microbial community analysis and batch tests illuminate that the generated sludge and attached biofilm played important roles in nitrogen removal. This study demonstrates the potential mechanism for the nitrogen removal process mediated by 3-hydroxybutyrate-co-3-hydroxyvalerate and provide a new idea for the alternative solutions of solid carbon sources.

Machine learning-based model construction and identification of dominant factor for simultaneous sulfide and nitrate removal process

Accurate water quality prediction models are essential for the successful implementation of the simultaneous sulfide and nitrate removal process (SSNR). Traditional models, such as regression and analysis of variance, do not provide accurate predictions due to the complexity of microbial metabolic pathways. In contrast, Back Propagation Neural Networks (BPNN) has emerged as superior tool for simulating wastewater treatment processes. In this study, a generalized BPNN model was developed to simulate and predict sulfide removal, nitrate removal, element sulfur production, and nitrogen gas production in SSNR. Remarkable results were obtained, indicating the strong predictive performance of the model and its superiority over traditional mathematical models for accurately predicting the effluent quality. Furthermore, this study also identified the crucial influencing factors for the process optimization and control. By incorporating artificial intelligence into wastewater treatment modeling, the study highlights the potential to significantly enhance the efficiency and effectiveness of meeting water quality standards.

Elemental sulfur-driven autotrophic denitrification process for effective removal of nitrate in mariculture wastewater: Performance, kinetics and microbial community

To date, there is a lack of systematic investigation on the elemental sulfur-driven autotrophic denitrification (SDAD) process for removing nitrate (NO3−-N) from mariculture wastewater deficient in organic carbon sources. Therefore, a packed-bed reactor was established and continuously operated for 230 days to investigate the operation performance, kinetic characteristics and microbial community of SDAD biofilm process. Results indicate that the NO3−-N removal efficiencies and rates varied with the operational conditions including HRT (1–4 h), influent concentrations of NO3−-N (25–100 mg L−1) and DO (0.2–7.0 mg L−1), and temperature (10oC–30 °C), in the ranges of 51.4%–98.6% and 0.054–0.546 g L−1 d−1, respectively. Limestone could partially neutralize the produced acidity. Small portions of NO3−-N were converted to nitrite (<4.5%) and ammonia (<2.8%) in the reactor. Operational conditions also influenced the production of acidity, nitrite and ammonia as well as sulfate. Shortening HRT and increasing influent NO3−-N concentration turned the optimal fitting model depicting the NO3−-N removal along the reactor from half-order to zero-order. Furthermore, the NO3−-N removal was accelerated by a higher temperature and influent NO3−-N concentration and a lower HRT and influent DO concentration. Microbial richness, evenness and diversity gradually decreased during the autotrophic denitrifier enrichment cultivation and the reactor start-up and operation. Sulfurimonas constituted the predominate genus and the primary functional bacteria in the reactor. This study highlights the SDAD as a promising way to control the coastal eutrophication associated with mariculture wastewater discharge.

Anoxic granular activated sludge process for simultaneous removal of hazardous perchlorate and nitrate

An airtight, anoxic bubble-column sequencing batch reactor (SBR) was developed for the rapid cultivation of perchlorate (ClO4-) and nitrate (NO3-) reducing granular sludge (GS) in this study. Feast/famine conditions and shear force selection pressures in tandem with a short settling time (2-min) as a hydraulic section pressure resulted in the accelerated formation of anoxic granular activated sludge (AxGS). ClO4- and NO3- were efficiently (>99.9%) reduced over long-term (>500-d) steady-state operation. Specific NO3- reduction, ClO4- reduction, chloride production, and non-purgeable dissolved organic carbon (DOC) oxidation rates of 5.77 ± 0.54 mg NO3--N/g VSS·h, 8.13 ± 0.74 mg ClO4-/g VSS·h, 2.40 ± 0.40 mg Cl-/g VSS·h, and 16.0 ± 0.06 mg DOC/g VSS·h were recorded within the reactor under steady-state conditions, respectively. The AxGS biomass cultivated in this study exhibited faster specific ClO4- reduction, NO3- reduction, and DOC oxidation rates than flocculated biomass cultivated under similar conditions and AxGS biomass operated in an up-flow anaerobic sludge blank (UASB) bioreactor receiving the same influent loading. EPS peptide identification revealed a suite of extracellular catabolic enzymes. Dechloromonas species were present in high abundance throughout the entirety of this study. This is one of the initial studies on anoxic granulation to simultaneously treat hazardous chemicals and adds to the science of the granular activated sludge process.

Coupled mixotrophic denitrification and utilization of refractory organics driven by Mn redox circulation for significantly enhanced nitrogen removal

Coupled mixotrophic denitrification and degradation of organics driven by redox transition of Mn for nitrogen removal has attracted much attention. Herein, this study explored the removal performance and mechanisms for nitrogen and refractory organics from secondary effluent in up-flow MnOx biofilter. Results showed that the removal of organics and nitrate was significantly enhanced by the synergistic process of heterotrophic denitrification and Mn(II)-driven autotrophic denitrification (MnAD), which were originated from the facilitation of Mn circulation. But nitrate removal was closely related to the types of carbon source and Mn(II) concentration. Single small molecular carbon source (glucose) performed better than mixed carbon source (humic acid and glucose) in nitrate removal process (74.8% in stage 1–2 vs. 54.1% in stage 3–5). And raising external Mn(II) concentration increased the contribution of MnAD (60.2% in stage 5 vs. 46.5% in stage 3) to nitrate removal. Furthermore, the relationship between Mn/N transformation and microbial community structure shifts revealed that the redox transition between Mn(II) and Mn(IV) promoted the enrichment of denitrogenation bacteria and functional genes, thus contributing to pollutants removal. Our studies expand the knowledge of MnOx-mediated pollutants removal processes and support the potential application of MnOx for removal of residual refractory organics and nitrogen.

Nitrate pollution and its solutions with special emphasis on electrochemical reduction removal.

Nitrate pollution has become a serious environmental concern all over the world including in China due to the mismanagement of water resources and human activities. Agricultural runoff and industrial and nuclear waste are among the major sources of nitrate pollution. Consuming nitrate-rich water can cause many chronic diseases including digestive problems, which can lead to many types of cancer and other serious health issues. Denitrification is the natural process for nitrate reduction under aerobic conditions, but it cannot handle an excess of nitrate, so several methods have been adopted for nitrate removal, i.e., biological, chemical, physicochemical, and electrochemical reduction removal. Among all, electrochemical reduction removal is a cost-effective and environmental-friendly process. To obtain the maximal elimination efficiency ideal conditions of current intensity, pH, plate distance, initial nitrate concentration, and type of electrolyte solution should be studied for effective nitrate removal. Electrochemical reduction removal of nitrate involves the transfer of electrons and hydrogenation. Besides an efficient nitrate removal process, electrochemical reduction removal has some drawbacks like sludge formation, low selectivity for nitrogen, and production of brine that limit its long-term implementation. This review focused on nitrate pollution, previous nitrate removal strategies, and essential principles for understanding the mechanism of electrochemical reduction removal and controlling the products of the reaction.

Performance of sulfur-based autotrophic denitrification process for nitrate removal from permeate of an MBR treating textile wastewater and concentrate of a real scale reverse osmosis process

Textile is one of the industrial sectors generating the highest amount of wastewater with various polluting substances. Lately, water reuse in textile industries, especially, with the reverse osmosis (RO) process following membrane bioreactor (MBR) treatment has been applied more commonly. In this study, an autotrophic sulfur-based denitrifying column performance was evaluated, for the first time, for nitrate reduction from permeate of a lab-scale MBR receiving real textile wastewater and from the concentrate stream of a real scale-RO plant used for recovering water from textile wastewater. Nitrate concentration in the MBR effluent and RO concentrate averaged 35 ± 3 and 12 ± 2 mg-N/L, respectively. With the sulfur-based column bioreactor, quite high (≥90%) denitrification performances were attained both for MBR effluent and RO concentrate up to nitrate loadings of 0.432 and 0.12 g-N/(L.d), respectively. COD present in wastewater was not utilized in the column bioreactor, which illustrates no or minimal contribution of heterotrophic denitrification. Alkalinity concentration in the wastewater was enough to buffer the acid formation during autotrophic denitrification. Sulfate was generated accompanied by nitrate reduction and sulfide was formed at low nitrate loadings. In the batch tests, the denitrification rates for the MBR effluent and RO concentrate were 0.31 and 0.28 g-N/(g-VSS.d), respectively, which were relatively higher than the ones observed for the synthetic nitrate-contaminated groundwater. Autotrophic sulfur-based denitrification is a promising and robust process alternative even for textile RO concentrate with high concentrations of salinity, non-biodegradable COD, and color.

Deciphering the nitrate sources and processes in the Ganga river using dual isotopes of nitrate and Bayesian mixing model

The dual isotopes of dissolved NO3- (n = 43) has been used to delineate the nitrate sources and N-cycling processes in the Ganga river. The proportional contribution of nitrate from different sources has been estimated using the Bayesian mixing model. The seasonal NO3- concentration in the lower stretch of the river Ganga varied between 4.1 and 64.1 μM with higher concentration during monsoon and post-monsoon season and lower concentration during the pre-monsoon and winter season. The temporal variation in the isotopic values ranged between +0.0 and +9.6‰ for δ15NNO3- and −1.2 to +11.0‰ for δ18ONO3-. The spatial NO3- concentration during the post-monsoon season varied between 23.2 and 57.7 μM, with higher values from the middle and lower values from the lower stretch of the river Ganga. The isotopic ratio during the post-monsoon season varied between −1.0 and +11.3‰ for δ15NNO3- and −4.6 to +5.2‰ for δ18ONO3-. The temporal dataset from the lower stretch of the river Ganga showed the dominance of nitrate derived from the nitrification of soil organic matter (SOM) (average ∼53.4%). The nitrate contribution from synthetic fertilizers was observed to be higher during the post-monsoon season (34.7 ± 23.4%) compared to that in the monsoon (25.5 ± 19.5%) and pre-monsoon (22.2 ± 19.6%) season. No significant seasonal variations were observed in the nitrate input from manure/sewage (∼13.9%). Spatial samples collected during the post-monsoon season showed higher contribution of synthetic fertilizer in the lower stretch (34.6 ± 22.7%) compared to the middle stretch (21.1 ± 18.2%), which indicates greater influence of the agricultural activity in the lower stretch. The dual isotope study of dissolved NO3- established that the nitrate in the Ganga river water is mostly derived from the nitrification of incoming organic compounds and is subsequently removed via assimilatory nitrate uptake. The study also emphasises significant nitrification and assimilatory nitrate removal processes operating in the mixing zone of the Ganga river and Hooghly estuary.

Biosorption of Nitrate by Thermodynamic and Kinetics study using Tamarind Fruit Shells

&lt;p&gt;The majority of nitrate (NO3‾) pollutants come from a different type of industries. Even if present in low amounts, these nitrates are harmful to humans and aquatic systems. This research investigated the utilisation of Tamarind Fruit shell (TFS) as biosorbent in the removal of Nitrate from aqueous solution. TFS shell was modified by soaking it with distilled water. Many remediation strategies are available, but they are both costly and ineffectual. However, it has been discovered via significant research that waste materials such as tamarind bark, eggshells, and agricultural wastes are well suited to removing nitrate from waste water using the biosorption process (Panida, et.al., 2010). Biosorption is a nitrate removal process that is both environment friendly and cost-effective. The equilibrium distribution of NO3‾ onto the surface of the TFS can be best explained by Freundlich isotherm. Based upon the reaction of the thermodynamic study the TFS- NO3‾ interaction is an endothermic (Amardeep, et.al., 2013). A substantial chance in the NO3‾ - TFS interaction is expected because of the significant gain in the translational entropy by the displaced synchronised water molecules. Than the Chemiluminescence Analysing techniques Spectroscopic studies shows the biosorption capacity of TFS shows a little variation between 1.25 mg/g for 1 mm size and 2.14 mg/g for 0.13 mm size.&lt;/p&gt;&#x0D;

Insights into size-fractionated anammox granules presented with refractory organics from municipal wastewater-driven partial denitrification to improve the synergy of anammox and denitrification

The recently developed Partial Denitrification/Anammox (PD/A) is an emerging process for simultaneous ammonium and nitrate removal, while the remaining organics from PD may pose an adverse effect on the subsequent anammox process. In this study, a granule-based anammox UASB reactor was developed with receiving municipal wastewater driven PD effluent that contained a certain amount of refractory organic matter, the characterization of different size-fractionated granules on nitrogen removal and microbiological mechanisms were investigated. Anammox activity increased with granule size, while an oversize exceeding 2.5 mm would lead to activity reduction. Significant denitrification activity was detected, it exhibited a contrary relationship with anammox activity. Delightedly, the denitrification was observed to proceed with high nitrite accumulation, especially in smaller granules with nitrate-to-nitrite transformation ratio (NTR) above 84.4%. These results were confirmed by microbial analysis, anammox genus including Candidatus Kuenenia, Brocadia, and Jettenia were identified in all granules, their abundances increased with granule size, and the dominated Kuenenia preferred to grow in larger granule. Various kinds of denitrification bacteria were detected with the relative abundances increased with the decrease in granules size. Particularly, the Thauera that responsible for PD with high nitrite accumulation was revealed to grow in such system, its relative abundance in small-size granules (12.9%, <0.5 mm) was much higher than the large ones (<2.3%). Overall, this study improved our understanding of the synergy of anammox and denitrification bacteria between size-fractionated granules, it provides a guide for system optimization towards great stability by biomass segregation strategy, and sheds new light to develop an efficient anammox coupling with PD process in continuous-flow UASB reactor.

The feasibility of adoption of catalytic removal of nitrate in Saudi Arabia's groundwater: A gate-to-gate environmental analysis

Arguably, one of the most damaging impacts is the nitrate contamination in groundwater that imposes a high risk towards human health. Thus, to control the nitrate level in drinkable water, purification of groundwater technology plays a crucial role. In this study, we investigated the environmental footprints of catalytic removal of nitrate in groundwater using Cu–Pd catalysts, creating a sustainable water system in Saudi Arabia. The functional unit of 1 L of groundwater was adopted in the system boundaries, which includes four processes, consisting of the upstream: Raw material extraction system (U1), midstream: Catalytic synthesis system (U2) and Nitrate removal water treatment (U3), as well as downstream: Transportation of purified groundwater (U4). Based on the life-cycle assessment, the hot spots in this process were being underpinned as follows: U4 > U2 > U1 > U3. The end-point impacts score for the whole catalytic nitrate removal process is calculated to be 78.75 mPt. Also, from sensitivity analysis, the factors that contributed the least to highest impacts towards climate change and human health is found to be as follow: amount of groundwater > raw material transportation distance > catalyst loading > transportation pipeline.

Intelligent control of the electrochemical nitrate removal basing on artificial neural network (ANN)

Artificial intelligence technologies were confirmed as a useful tool for wastewater treatment, but its application in the electrochemical nitrate removal had less been reported. In this work, the artificial neural network in machine learning was used to construct the model, which combines the methods of electrochemistry and artificial intelligence to achieve the prediction and intelligent control of nitrate removal. The control system consists of a prediction module with an artificial neural network (ANN) algorithm model and a control module. First, initial nitrate concentration, pH, time and current density were considered as input. An ANN algorithm using 7 hidden layers and a negative feedback regulation mechanism was developed to optimize the model and predict the nitrate removal rate. Results indicates that the proposed prediction model (4–7–1) yields a better coefficient of determination and lower root mean square error. The optimal set-points of the current density in the electrochemical process can be obtained according to the water quality change and qualified effluent quality using the ANN model. Also, the proposed intelligent control strategy can eliminate the influence of water quality change on nitrate removal and reduce energy consumption by 15.0 % compared to the post strategy. This work demonstrated the potential of artificial intelligence in the electrochemical process of nitrate removal.