Effect of N/S ratio on anoxic thiosulfate oxidation in a fluidized bed reactor: Experimental and artificial neural network model analysis

Neural network-based performance assessment of one- and two-liquid phase biotrickling filters for the removal of a waste-gas mixture containing methanol, α-pinene, and hydrogen sulfide

The performance of one- and two-liquid phase biotrickling filters (OLP/TLP-BTFs) treating a mixture of gas-phase methanol (M), α-pinene (P), and hydrogen sulfide (H) was assessed using artificial neural network (ANN) modeling. The best ANN models with the topologies 3-9-3 and 3-10-3 demonstrated an exceptional capacity for predicting the performance of O/TLP-BTFs, with R2 > 99%. The analysis of causal index (CI) values for the model of OLP-BTF revealed a negative impact of M on P removal (CI = -2.367), a positive influence of P and H on M removal (CI = +7.536 and CI = +3.931) and a negative effect of H on P removal (CI = -1.640). The addition of silicone oil in TLP-BTF reduced the negative impact of M and H on P degradation (CI = -1.261 and CI = -1.310, respectively) compared to the OLP-BTF. These findings suggested that silicone oil had the potential to improve P availability to the biofilm by increasing the concentration gradient of P between the air/gas and aqueous phases. Multi-objective particle swarm optimization (MOPSO) suggested an optimum operational condition, i.e. inlet M, P, and H concentrations of 1.0, 1.1, and 0.3 g m-3, respectively, with elimination capacities (ECs) of 172.1, 26.5, and 0.025 g m-3 h-1 for OLP-BTF. Likewise, one of the optimum operational conditions for TLP-BTF is achievable at inlet concentrations of 4.9, 1.7, and 0.8 g m-3, leading to the optimum ECs of 299.7, 52.9, and 0.072 g m-3 h-1 for M, P, and H, respectively. These results provide important insights into the treatment of complex waste gas mixtures, addressing the interactions between the pollutant removal characteristics in OLP/TLP-BTFs and providing novel approaches in the field of biological waste gas treatment.

Deciphering the influence of S/N ratio in a sulfite-driven autotrophic denitrification reactor

Sulfur-based autotrophic denitrification is a cost-effective alternative to heterotrophic denitrification for nitrate removal due to no need of external organic carbon supply. Herein, sulfite-driven autotrophic denitrification (SDAD) was firstly established in a sequencing batch biofilm reactor treating high-strength nitrate-containing wastewater added by the sulfite. The nitrogen removal performance was mainly investigated under a molar ratio of sulfur-to‑nitrogen (S/N) ranging from 0.44 to 3.07 in a total of 180-day operation. Long-term experiment showed the optimal of S/N was found to be 2.63, much close to the stoichiometric value, achieving the highest autotrophic denitrification rate and complete total nitrogen removal efficiency (TNRE) with 92.4 ± 0.3%. Cyclical trial confirmed nitrate reduction and sulfite oxidation simultaneously occurred along with sulfate formation. Meanwhile, nitrite accumulation was observed at a very low S/N conditions. Microbial community analysis identified that Sulfurovum, Thiobacillus, and Thermomonas as key denitrifying sulfur-oxidizing bacteria responsible for SDAD. Moreover, the dynamic shift in functional microorganisms affected by influent S/N was also detected. Finally, the metabolic pathway of SDAD process was unraveled via the cooperative encoding of sulfite oxidases (Sor, Apr, Sat) and nitrate-reducing genes. This study sheds light on a new sulfur-cycle autotrophic denitrification process for the bioremediation of nitrate-contaminated wastewater.

Sequential sulfur-based denitrification/denitritation and nanofiltration processes for drinking water treatment

Efficient and cost-effective solutions for nitrogen removal are necessary to ensure the availability of safe drinking water. This study proposes a combined treatment for nitrogen-contaminated groundwater by sequential autotrophic nitrogen removal in a sulfur-packed bed reactor (SPBR) and excess sulfate rejection via nanofiltration (NF). Autotrophic nitrogen removal in the SPBR was investigated under both denitrification and denitritation conditions under different NO₃^- and NO₂^- loading rates (LRs) and feeding strategies (NO₃^- only, NO₂^- only, or both NO₃^- and NO₂^- in the feed). Batch activity tests were carried out during SPBR operation to evaluate the effect of different feeding conditions on nitrogen removal activity by the SPBR biofilm. Bacteria responsible for nitrogen removal in the bioreactor were identified via Illumina sequencing. Dead-end filtration tests were performed with NF membranes to investigate the elimination of excess sulfate from the SPBR effluent. This study demonstrates that the combined process results in effective groundwater treatment and evidences that an adequately high nitrogen LR should be maintained to avoid the generation of excess sulfide.

Biogas maximization using data-driven modelling with uncertainty analysis and genetic algorithm for municipal wastewater anaerobic digestion

Anaerobic digestion processes create biogases that can be useful sources of energy. The development of data-driven models of anaerobic digestion processes via operating parameters can lead to increased biogas production rates, resulting in greater energy production, through process modification and optimization. This study assessed processed and unprocessed input operating parameter variables for the development of regression models with transparent structures ('white-box' models) to: (1) estimate biogas production rates from municipal wastewater treatment plant (MWTP) anaerobic digestors; (2) compare their performances to artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS) models with opaque structures ('black-box' models) using Monte Carlo Simulation for uncertainty analysis; and (3) integrate the models with a genetic algorithm (GA) to optimize operating parameters for maximization of MWTP biogas production rates. The input variables were anaerobic digestion operating parameters from a MWTP including volatile fatty acids, total/fixed/volatile solids, pH, and inflow rate, which were processed via correlation tests and principal component analysis. Overall, the results indicated that the processed data did not improve regression model performances. Additionally, the developed non-linear regression model with the unprocessed inputs had the best performance based on values including R = 0.81, RMSE = 0.95, and IA = 0.89. However, this model was less accurate, but interestingly had less uncertainty, as compared to ANN and ANFIS models which indicates the compromise between model accuracy and uncertainty. Thus, all three models were coupled with GA optimization with maximum biogas production rate estimates of 22.0, 23.1, and 28.6 m³/min for ANN, ANFIS, and non-linear regression models, respectively.

A comprehensive review on application of bioreactor for industrial wastewater treatment

In the recent past, wastewater treatment processes performed a pivotal role in accordance with maintaining the sustainable environment and health of mankind at a proper hygiene level. It has been proved indispensable by government regulations throughout the world on account of the importance of preserving freshwater bodies. Human activities, predominantly from industrial sectors, generate an immeasurable amount of industrial wastewater loaded with toxic chemicals, which not only cause dreadful environmental problems, but also leave harmful impacts on public health. Hence, industrial wastewater effluent must be treated before being released into the environment to restrain the problems related to industrial wastewater discharged to the environment. Nowadays, biological wastewater treatment methods have been considered an excellent approach for industrial wastewater treatment process because of their cost-effectiveness in the treatment, high efficiency and their potential to counteract the drawbacks of conventional wastewater treatment methods. Recently, the treatment of industrial effluent through bioreactor has been proved as one of the best methods from the presently available methods. Reactors are the principal part of any biotechnology-based method for microbial or enzymatic biodegradation, biotransformation and bioremediation. This review aims to explore and compile the assessment of the most appropriate reactors such as packed bed reactor, membrane bioreactor, rotating biological contactor, up-flow anaerobic sludge blanket reactor, photobioreactor, biological fluidized bed reactor and continuous stirred tank bioreactor that are extensively used for distinct industrial wastewater treatment.

Development of a kinetic model to evaluate thiosulfate-driven denitrification and anammox (TDDA) process

Recently, the integration of sulfur-driven denitrification and anammox process has been extensively studied as a promising alternative nitrogen removal technology. Most of these studies investigated the process feasibility and monitored the community dynamics. However, an in-depth understanding of this new sulfur-nitrogen cycle bioprocess based on mathematical modeling and elucidation of complex interactions among different microorganisms has not yet been achieved. To fill this gap, we developed a kinetic model (with 7 bioprocesses, 12 variables, and 19 parameters) to assess the sulfur(thiosulfate)-driven denitrification and anammox (TDDA) process in a single reactor. The parameters used in this process were separately estimated by fitting the data obtained from the experiments. Then, the model was further validated under different conditions, and the results demonstrated that the developed model could describe the dynamic behaviors of nitrogen and sulfur conversions in the TDDA system. The newly developed branched thiosulfate oxidation model was also verified by conducting a metagenomics analysis. Using the developed model, we i) examined the interactions between sulfur-oxidizing bacteria and anammox bacteria at steady-state conditions with varying substrates to demonstrate the reliability of TDDA, and ii) evaluated the feasibility and operation of the TDDA process in terms of practical implementation. Our results will benefit further exploration of the significance of this novel S-N cycle bioprocess and guide its future applications.

Markers for the Comparison of the Performances of Anoxic Biotrickling Filters in Biogas Desulphurisation: A Critical Review

The agriculture and livestock industry generate waste used in anaerobic digestion to produce biogas containing methane (CH4), useful in the generation of electricity and heat. However, although biogas is mainly composed of CH4 (~65%) and CO2 (~34%), among the 1% of other compounds present is hydrogen sulphide (H2S) which deteriorates engines and power generation fuel cells that use biogas, generating a foul smell and contaminating the environment. As a solution to this, anoxic biofiltration, specifically with biotrickling filters (BTFs), stands out in terms of the elimination of H2S as it is cost-effective, efficient, and more environmentally friendly than chemical solutions. Research on the topic is uneven in terms of presenting performance markers, underestimating many microbiological indicators. Research from the last decade was analyzed (2010–2020), demonstrating that only 56% of the reviewed publications did not report microbiological analysis related to sulphur oxidising bacteria (SOB), the most important microbial group in desulphurisation BTFs. This exposes fundamental deficiencies within this type of research and difficulties in comparing performance between research works. In this review, traditional and microbiological performance markers of anoxic biofiltration to remove H2S are described. Additionally, an analysis to assess the efficiency of anoxic BTFs for biogas desulphurisation is proposed in order to have a complete and uniform assessment for research in this field.

Electron buffer formation through coupling thiosulfate-dependent denitratation with anammox in a single-stage sequencing batch reactor

The combination of thiosulfate-dependent denitratation and anammox in a single-stage reactor provides a feasible way to improve total nitrogen removal. The molar ratios of NH₄⁺/NO₃^- and S₂O₃^2-/NO₃^- were confirmed to be two key factors affecting the reactor performance. The optimal total nitrogen removal efficiency of 99.4% was achieved at NH₄⁺/NO₃^- of 0.75 and S₂O₃^2-/NO₃^- of 0.85. The multiple thiosulfate oxidation pathways contribute to electron buffers generated in the system. A novel isotope labeling method using ¹⁵N was applied to reveal N transformation pathways and a 3-step model was proposed. The nitrate was first converted to nitrite or nitric oxide (NO) by sulfur-oxidizing bacteria. In the second step, both nitrite and NO were utilized by anammox bacteria. Finally, the nitrate generated from anammox could be removed using sulfur deposits as electron donors. The findings provide a potential solution for mainstream nitrogen removal.

Simultaneous denitrification, phosphorus recovery and low sulfate production in a recirculated pyrite-packed biofilter (RPPB)

The simultaneous removal of nitrate (15 mg N-NO₃^- L^-1) and phosphate (12 mg P-PO₄^3- L^-1) from nutrient-polluted synthetic water was investigated in a recirculated pyrite-packed biofilter (RPPB) under hydraulic retention time (HRT) ranging from 2 to 11 h. HRT values ≥ 8 h resulted in nitrate and phosphate average removal efficiency (RE) higher than 90% and 70%, respectively. Decrease of HRT to 2 h significantly reduced the RE of both nitrogen and phosphorus. The RPPB showed high resiliency as reactor performance recovered immediately after HRT increase to 5 h. Solid-phase characterization of pyrite granules and backwashing material collected from the RPPB at the end of the study revealed that iron-phosphate, -hydroxide and -sulfate precipitated in the bioreactor. Thermodynamic modeling predicted the formation of S⁰ during the study. Residence time distribution tests showed semi-complete mixing hydrodynamic flow conditions in the RPPB. The RPPB can be considered an elegant and low-cost technology coupling biological nitrogen removal to the recovery of phosphorus, iron and sulfur via chemical precipitation.

Comparison of biogenic and chemical sulfur as electron donors for autotrophic denitrification in sulfur-fed membrane bioreactor (SMBR)

Two sulfur-oxidizing membrane bioreactors (SMBRs) performing autotrophic denitrification at different HRTs (6-26 h), one supplemented with biogenic elemental sulfur (S⁰_bio) and the other with chemically-synthesized elemental sulfur (S⁰_chem), were compared in terms of nitrate reduction rates, impact on membrane filtration and microbial community composition. Complete denitrification with higher rates (up to 286 mg N-NO₃^-/L d) was observed in the SMBR supplemented with S⁰_bio (SMBR_bio), while nitrate was never completely reduced in the SMBR fed with S⁰_chem (SMBR_chem). Trans membrane pressure was higher for SMBR_bio due to smaller particle size and colloidal properties of S⁰_bio. Microbial communities in the two SMBRs were similar and dominated by Proteobacteria, with Pleomorphomonas and Thermomonas being the most abundant genera in both bioreactors. This study reveals that S⁰_bio can be effectively used for nitrate removal in autotrophic denitrifying MBRs and results in higher nitrate reduction rates compared to S⁰_chem.

Pilot-scale application of sulfur-limestone autotrophic denitrification biofilter for municipal tailwater treatment: Performance and microbial community structure

This work aimed to study a pilot-scale sulfur-limestone autotrophic denitrification biofilter (SLADB) to remove nitrogen from municipal tailwater. The capacity of nitrogen removal and spatial distribution of microbial community at low temperature condition were analyzed. Low temperature inhibits nitrogen removal; while prolonging hydraulic retention time (HRT) increased nitrogen removal efficiency. TN and NO₃^--N removal efficiency reached 81.1% and 85.3%, respectively, with HRT of 18 h at the temperature ranging from 6.4 to 9.8 °C. Proteobacteria and Chloroflexi were two dominant phyla. Along the reactor, class β-proteobacteria and ε-proteobacteria decreased, while γ-proteobacteria and Acidobacteria increased. For genus classification, Thiobacillus, Sulfurimonas, and Ferritrophicum which promote sulfur autotrophic denitrification, decreased significantly. While Anaerolineae promoting heterotrophic denitrification increased obviously. Sphingobacteriia coexisted in SLADB and were beneficial to nitrogen removal. Microbial community spatial distribution patterns were related to nitrogen removal. This study achieved reliable pilot-scale application of SLADB under low temperature for municipal tailwater.

Biogas production estimation using data-driven approaches for cold region municipal wastewater anaerobic digestion

The objective of this study was to estimate biogas (including methane, carbon dioxide and hydrogen sulphide) production rates from the anaerobic digesters at the Saskatoon Wastewater Treatment Plant (SWTP), Saskatchewan, Canada. Average daily ambient temperatures typically fluctuate between -40 °C and 30 °C over the year making the management of the SWTP processes challenging. Operating parameters were taken from 2014 to 2016 including volatile fatty acids (VFAs), total solids, fixed solids, volatile solids, pH, and inflow rate. The input parameters were processed using two methods including a correlation test and principal component analysis (PCA) to determine highly correlated variables prior to use in models. The two models used to estimate biogas production rates are a multi-layered perceptron feed forward artificial neural network (ANN) and an adaptive network-based fuzzy inference system (ANFIS) with grid partition (GP), subtractive clustering (SC) and fuzzy c-means clustering (FCMC). The models using PCA processed variables had reasonable performances with shorter model processing times, while reducing model input data. Among various structures of ANN and ANFIS models for estimation of biogas generation, the ANFIS-FCMC results had better agreement with the observed data. Its average approximation of emission rates of CH₄, CO₂ and H₂S from the wastewater digesters were 3,086, 6,351, and 41.5 g/min, respectively. Our group is assessing similar estimation methodology for the remaining SWTP wastewater treatment processes that are more highly impacted by the seasonal temperature variations including primary and secondary treatment processes.

Effect of carbon-to-nitrogen ratio on simultaneous nitrification denitrification and phosphorus removal in a microaerobic moving bed biofilm reactor

In this study, long-term simultaneous nitrification denitrification (SND) and phosphorous removal were investigated in a continuous-flow microaerobic MBBR (mMBBR) operated at a dissolved oxygen (DO) concentration of 1.0 (±0.2) mg L^-1. The mMBBR performance was evaluated at different feed carbon-to-nitrogen (C/N) ratios (2.7, 4.2 and 5.6) and HRTs (2 days and 1 day). Stable long-term mMBBR operation and chemical oxygen demand (COD), total inorganic nitrogen (TIN) and phosphorous (P-PO₄^3-) removal efficiencies up to 100%, 68% and 72%, respectively, were observed at a feed C/N ratio of 4.2. Lower TIN removal efficiency and unstable performance were observed at feed C/N ratios of 2.7 and 5.6, respectively. HRT decrease from 2 days to 1 day resulted in transient NH₄⁺ accumulation and higher NO₂^-/NO₃^- ratio in the effluent. Batch activity tests showed that biofilm cultivation at a feed C/N ratio of 4.2 resulted in the highest denitrifying activity (189 mg N gVSS^-1 d^-1), whereas the highest nitrifying activity (316 mg N gVSS^-1 d^-1) was observed after cultivation at a feed C/N ratio of 2.7. Thermodynamic modeling with Visual MINTEQ and stoichiometric evaluations revealed that P removal was mainly biological and can be attributed to the P-accumulating capacity of denitrifying bacteria.

Performance assessment of gas-phase toluene removal in one- and two-liquid phase biotrickling filters using artificial neural networks

The main aim of this work is to study gas-phase toluene removal in one- and two-liquid phase biotrickling filters (O/TLP-BTF) and model the BTF performance using artificial neural networks (ANNs). The TLP-BTF was operated for 60 d in the presence of silicone oil at empty bed residence times (EBRTs) of 120, 60, and 45 s, respectively, and toluene concentrations in the range of 0.9-3.1 g m^-3. A t-test analysis indicated that increasing the silicone oil volume ratio from 5 to 10% v/v, did not significantly improve the TLP-BTF performance (p-value = 0.65 > 0.05). The results from ANN modeling showed that toluene removal was more negatively affected by the inlet concentration (casual index, CI = -5.63) due to the kinetic limitation. The CI values for inlet concentration (+4.01) and liquid trickling rate (-2.45) indicated that the diffusion-limited regime controlled the removal process in the OLP-BTF.

Transient-state operation of an anoxic biotrickling filter for H2S removal

The application of an anoxic biotrickling filter (BTF) for H₂S removal from contaminated gas streams is a promising technology for simultaneous H₂S and NO₃^- removal. Three transient-state conditions, i.e. different liquid flow rates, wet-dry bed operations and H₂S shock loads, were applied to a laboratory-scale anoxic BTF. In addition, bioaugmentation of the BTF with a H₂S removing-strain, Paracoccus MAL 1HM19, to enhance the biomass stability was investigated. Liquid flow rates (120, 60 and 30 L d^-1) affected the pH and NO₃^- removal efficiency (RE) in the liquid phase. Wet-dry bed operations at 2-2 h and 24-24 h reduced the H₂S elimination capacity (EC) by 60-80%, while the operations at 1-1 h and 12-12 h had a lower effect on the BTF performance. When the BTF was subjected to H₂S shock loads by instantly increasing the gas flow rate (from 60 to 200 L h^-1) and H₂S inlet concentration (from 112 (± 15) to 947 (± 151) ppm_v), the BTF still showed a good H₂S RE (>93%, EC of 37.8 g S m^-3 h^-1). Bioaugmentation with Paracoccus MAL 1HM19 enhanced the oxidation of the accumulated S⁰ to sulfate in the anoxic BTF.

The effects of Fe2+ on sulfur-oxidizing bacteria (SOB) driven autotrophic denitrification

With the short-term exposure to Fe²⁺, the mechanism of autotrophic denitrification and sulfide oxidation and the correlation between microbial community changes and environmental factors have been explored in the ADSOB process. RSM was used to optimize conditions for the maximum nitrate reduction and sulfide oxidation. About 88% of nitrate could be autotrophically denitrified to nitrogen by utilizing sulfide as the electron donor with the molar ratio C/N of 1.14 and S/N of 0.99 at pH 7.1. Lower Fe²⁺ additions can reduce TDS inhibition with dissolved sulfide to form FeS precipitates, while high amount of Fe²⁺ limited the mass transfer of NO₃^- and intermediate products such as S⁰ may be generated. High-throughput sequencing and RDA analysis revealed the correlation between ferrous iron, environmental factors and microorganisms. Sulfurospirillum, Rhodanobacter, Thauera and Thiobacillus were all slightly promoted at NFL level and inhibited at NFH level. And the narrow angles of the arrows indicated that Thauera, Sulfurospirillum and Thiobacillus were positively correlated with SO₄^2- concentrations, while large angles indicated these bacteria were inversely related with TDS and NO₃- arrows, which further confirmed that these bacteria played a dominant role in the ADSOB process, and can reduce NO₃- by the oxidation of TDS. The correlation further indicated that lower Fe²⁺ additions have a promoting effect, while high concentrations have an inhibiting effect.

H2S removal and microbial community composition in an anoxic biotrickling filter under autotrophic and mixotrophic conditions

Removal of H₂S from gas streams using NO₃^--containing synthetic wastewater was investigated in an anoxic biotrickling filter (BTF) at feed N/S ratios of 1.2-1.7 mol mol^-1 with an empty bed residence time of 3.5 min and a hydraulic retention time of 115 min. During 108 days of operation under autotrophic conditions, the BTF showed a maximum elimination capacity (EC) of 19.2 g S m^-3 h^-1 and H₂S removal efficiency (RE) >99%. When the BTF was operated under mixotrophic conditions by adding organic carbon (10.2 g acetate m^-3 h^-1) to the synthetic wastewater, the H₂S EC decreased from 16.4 to 13.1 g S m^-3 h^-1, while the NO₃^- EC increased from 9.9 to 11.1 g NO₃^--N m^-3 h^-1, respectively. Thiobacillus sp. (98-100% similarity) was the only sulfur-oxidizing nitrate-reducing bacterium detected in the BTF biofilm, while the increased abundance of heterotrophic denitrifiers, i.e. Brevundimonas sp. and Rhodocyclales, increased the N/S ratio during BTF operation. Residence time distribution tests showed that biomass accumulation during BTF operation reduced gas and liquid retention times by 17.1% and 83.5%, respectively.

Fluidized bed bioreactor for multiple environmental engineering solutions

Fluidized bed bioreactors (FBR) are characterized by two-phase mixture of fluid and solid, in which the bed of solid particles is fluidized by means of downward or upward recirculation stream. FBRs are widely used for multiple environmental engineering solutions, such as wastewater treatment, as well as some industrial applications. FBR offers many benefits such as compact bioreactor size due to short hydraulic retention time, long biomass retention on the carrier, high conversion rates due to fully mixed conditions and consequently high mass transfer rates, no channelling of flow, dilution of influent concentrations due to recycle flow, suitability for enrichment of microbes with low K_m values. The disadvantages of FBRs include bioreactor size limitations due to the height-to-diameter ratio, high-energy requirements due to high recycle ratios, and long start-up period for biofilm formation. This paper critically reviews some of the key studies on biomass enrichment via immobilisation of low growth yield microorganisms, high-rates via fully mixed conditions, technical developments in FBRs and ways of overcoming toxic effects via solution recycling. This technology has many potential new uses as well as hydrodynamic characteristics, which enable high-rate environmental engineering and industrial applications.