Search Results (52)

Fungal mycelial pellets (MPs) exhibit high biomass-loading capacity; however, their application in wastewater treatment is constrained by structural fragility and the risk of environmental dispersion. To overcome these limitations, a dual-crosslinked polyvinyl alcohol–alginate gel (10% PVA, 2% sodium alginate) embedding strategy was developed and stabilized using 2% CaCl₂ and saturated boric acid. This encapsulation enhanced the tensile strength of MPs by 499% (310.4 vs. 62.1 kPa) and improved their settling velocity by 2.3-fold (1.12 vs. 0.49 cm/s), which was critical for stability under turbulent bioreactor conditions. Following encapsulation, the specific oxygen uptake rates (SOURs) of three fungal strains (F557, Y3, and F507) decreased by 30.3%, 54.8%, and 48.3%, respectively, while maintaining metabolic functionality. SEM revealed tight adhesion between the gel layer and both surface and internal hyphae, with the preservation of porous channels conducive to microbial colonization. In sequential-batch reactors treating sulfamethoxazole (SMX)-contaminated wastewater, gel-encapsulated MPs combined with acclimated sludge consistently achieved 72–75% SMX removal efficiency over six cycles, outperforming uncoated MPs (efficiency decreased from 81.2% to 58.7%) and pure gel–sludge composites (34–39%). The gel coating inhibited hyphal dispersion by over 90% and resisted mechanical disintegration under 24 h agitation. This approach offers a scalable and environmentally sustainable means of enhancing MPs’ operational stability in continuous-flow systems while mitigating fungal dissemination risks. Full article

Chemical recycling via catalytic pyrolysis is constrained by coke deposition and costly catalyst make-up. We investigate polypropylene (PP) and low-density polyethylene (LDPE) conversion over a spent FCC equilibrium catalyst (AXL) and, critically, quantify the re-activation energy landscape of the resulting coke. Using a semi-batch reactor (350 °C) and thermogravimetric analysis to 1100 °C combined with the Ozawa–Flynn–Wall method, we distinguish soft and hard coke under inert, oxidative, and sequential N₂ to air regimes. LDPE yields mainly gas (70.7 wt%) with 5.5 wt% coke, whereas PP favors liquids (47.1 wt%) with 3.4 wt% coke. LDPE-derived coke is softer (71% of total; E_A = 170 kJ mol⁻¹ soft) than PP coke (60% soft; E_A = 166 kJ mol⁻¹), evidencing a more refractory PP residue. Oxygen lowers E_A to ~155 kJ mol⁻¹ for both polymers. We introduce a simple TGA-based “softness ratio” to guide regeneration severity and show that a refinery-waste FCC catalyst delivers selective plastic-to-fuel conversion while enabling energy-aware regeneration protocols. The framework directly supports scale-up by linking polymer structure, coke quality, and atmosphere-dependent re-activation energetics. Full article

The dairy industry generates significant amounts of wastewater, including microfiltration (MF) retentate, a byproduct thickened with organic and inorganic pollutants. This study focuses on the treatment of two times concentrated MF retentate using a hybrid system based on biological treatment in a sequential batch reactor (SBR) and adsorption on activated carbon. The first stage involved cross-flow microfiltration using a 0.2 µm PVDF membrane at 0.5 bar, resulting in reductions of 99% in turbidity and 79% in chemical oxygen demand (COD), as well as a partial reduction in conductivity. The second stage involved 24-h biological treatment in a sequential batch reactor (SBR) with activated sludge (activated sludge index: 80 cm³/g, MLSS 2500 mg/dm³), resulting in further reductions in COD (62%) and TOC (30%), as well as the removal of 46% of total phosphorus (TP) and 35% of total nitrogen (TN). In the third stage, the decantate underwent adsorption in a column containing powdered activated carbon (PAC; 1 g; S_(BET) = 969 m² g⁻¹), reducing the concentrations of key indicators to the following levels: COD 84%, TOC 70%, TN 77%, TP 87% and suspended solids 97%. Total pollutant retention ranged from 24.6% to 97.0%. These results confirm that the MF–SBR–PAC system is an effective, compact solution that significantly reduces the load of organic and biogenic pollutants in MF retentates, paving the way for their reuse or safe discharge into the environment. Full article

Catalytic upgrading of pyrolysis oils is an important step for producing replacement hydrocarbon-rich liquid biofuels from biomass and can help to advance pyrolysis technology. Catalysts play a pivotal role in influencing the selectivity of chemical reactions leading to the formation of main compounds in the final upgraded liquid products. The present work involved a systematic study of solvent-free catalytic reactions of cyclohexanone in the presence of hydrogen gas at 160 °C for 3 h in a batch reactor. Cyclohexanone can be produced from biomass through the selective hydrogenation of lignin-derived phenolics. Three types of catalysts comprising undoped NbOPO₄, 10 wt% NiO/NbOPO₄, and 30 wt% NiO/NbOPO₄ were studied. Undoped NbOPO₄ promoted both aldol condensation and the dehydration of cyclohexanol, producing fused ring aromatic hydrocarbons and hard char. With 30 wt% NiO/NbOPO₄, extensive competitive hydrogenation of cyclohexanone to cyclohexanol was observed, along with the formation of C₆ cyclic hydrocarbons. When compared to NbOPO₄ and 30 wt% NiO/NbOPO₄, the use of 10 wt% NiO/NbOPO₄ produced superior selectivity towards bi-cycloalkanones (i.e., C₁₂) at cyclohexanone conversion of 66.8 ± 1.82%. Overall, the 10 wt% NiO/NbOPO₄ catalyst exhibited the best performance towards the production of precursor compounds that can be further hydrodeoxygenated into energy-dense aviation fuel hydrocarbons. Hence, the presence and loading of NiO was able to tune the activity and selectivity of NbOPO₄, thereby influencing the final products obtained from the same cyclohexanone feedstock. This study underscores the potential of lignin-derived pyrolysis oils as important renewable feedstocks for producing replacement hydrocarbon solvents or feedstocks and high-density sustainable liquid hydrocarbon fuels via sequential and selective catalytic upgrading. Full article

This study evaluated the viability of using the solid residues (bagasse) of the mezcal industry produced with Agave durangensis as a substrate for biogas production, using two chemical pretreatments, acid (HCl) and alkaline (KOH + Ca(OH)₂), to enhance its biodegradability and improve the anaerobic digestion (AD) process. The chemical composition of bagasse was analyzed before and after the chemical pretreatments and then AD experiments were conducted in anaerobic sequential batch reactors (A-SBR) to analyze the effect of pretreatments on biogas production performance. The results showed that acid pretreatment increased cellulose content to 0.606 g, which represented an increase of 34%, and significantly reduced hemicellulose. In contrast, alkaline pretreatment did not show significant changes in cellulose composition, although it caused a swelling of the Agave durangensis mezcal bagasse (Ad-MB) fibers. In terms of biogas production, Ad-MB pretreated with acid (Ad-MB-acid) increased cumulative production by 76% compared to the Agave durangensis mezcal bagasse that was not pretreated (Ad-MB-not pretreated) and by 135% compared to Agave durangensis mezcal bagasse pretreated with an alkaline solution (Ad-MB-alkaline). These results confirmed that Agave durangensis solid waste from the mezcal industry that receives acidic chemical pretreatment has the potential to generate biogas as a sustainable biofuel that can be used to reduce the ecological footprint of this industry. Full article

This study evaluated the efficacy of acclimated cow manure as a seed microbiome to enhance food waste hydrolysis. Anaerobic hydrolysis was performed on simulated food waste in a hydrolytic–acidogenic leach bed reactor (LBR) operated in batch mode under mesophilic conditions (35 °C) for 16 days. The acclimation process involved three sequential runs: Run-1 utilized 20% (w/w) cow manure as seed, Run-2 employed the digestate from Run-1 (day 5), and Run-3 used the digestate from Run-1 (day 10). Run-3 achieved 70.4% removal of volatile solids (VSs), surpassing Run-1 (47.1%) and Run-2 (57.1%). Compared with the first run, the production of chemical oxygen demand (COD) and total soluble products (TSPs) increased by 48.7% and 75.9%, respectively, in Run-3. The hydrolysis rate of proteins was 48.4% in Run-1, while an increase of 16.9% was achieved in Run-3 with the acclimatized consortium. A molecular analysis of the microbial community existing in the reactors of Run-2 and Run-3 indicated that the improvement in process performance was closely related to the selection and enrichment of specific hydrolytic–acidogenic bacteria in the reactor. A functional analysis showed that the gene copy numbers for pyruvate synthesis and fatty acid synthesis and metabolism pathways were higher in all bacterial species in Run-3 compared to in those of the other two runs, indicating improved capacity through acclimation in Run-3. The experimental results demonstrate that the hydrolysis of food waste can be enhanced through the acclimation of seed microbes from cow manure. Full article

Dewatering anaerobic digested sludge leaves a liquid fraction known as reject water, a liquid organic fertilizer containing high amounts of ammonium nitrogen (NH₄-N). However, its concentration should be enhanced to produce commercial fertilizer. Thus, reject water nitrification for stabilization as well as for nitrate capture in biochar to be used as a slow-release fertilizer is proposed. This study attempted to accomplish enhanced nitrification by tuning the operating parameters in two lab-scale sequential-batch reactors (SBRs), which were fed reject water (containing 520 ± 55 mg NH₄-N/L). Sufficient alkalinity as per stoichiometric value was needed to maintain the pH and free nitrous acid (FNA) within the optimum range. A nitrogen loading rate (NLR) of 0.14 ± 0.01 kg/m³·d and 3.34 days hydraulic retention time (HRT) helped to achieved complete 100% nitrification in reactor 1 (R₁) on day 61 and in reactor 2 (R₂) on day 82. After a well-developed bacterial biomass, increasing the NH₄-N concentration up to 750 ± 85 mg/L and NLR to 0.23 ± 0.03 kg/m³·d did not affect the nitrification process. Moreover, a feeding sequence once a day provided adequate contact time between nitrifying sludge and reject water, resulting in complete nitrification. It can be concluded that enhanced stable nitrification of reject water can be achieved with quick adjustment of loading, alkalinity, and HRT in SBRs. Full article

This study investigated the mechanism by which N-acyl-homoserine lactone (AHL) signaling molecules influence ammonia-oxidizing microorganisms (AOMs) under inhibitory conditions. In laboratory-scale sequential batch reactors (SBRs), the effects of different AHLs (C6-HSL and C8-HSL) on the metabolic activity, microbial community structure, and quorum sensing (QS) system response of AOMs were examined. Caffeic acid, 1-octyne, and allylthiourea were used as ammoxidation inhibitors. The results indicated that under inhibitory conditions, AHLs effectively reduced the loss of ammonia oxidation activity and enhanced the resistance of AOMs to unfavorable environments. Additionally, AHLs enriched AOMs in the microbial community, wherein C6-HSL significantly increased the abundance of amoA genes in AOMs. Furthermore, AHLs maintained the activity of QS-related genes and preserved the communication ability between microorganisms. Correlation analysis revealed a positive relationship between AOMs and QS functional bacteria, suggesting that AHLs can effectively regulate the ammonia oxidation process. Overall, exogenous AHLs can improve the metabolic activity and competitive survival of AOMs under inhibitory conditions. Full article

The study addresses the critical issue of accurately predicting ammonia nitrogen (NH₃-N) concentration in a sequencing batch reactor (SBR) system, achieving reduced consumption through automatic control technology. NH₃-N concentration serves as a key indicator of treatment efficiency and environmental impact; however, its complex dynamics and the scarcity of measurements pose significant challenges for accurate prediction. To tackle this problem, an innovative Transformer-long short-term memory (Transformer-LSTM) network model was proposed, which effectively integrates the strengths of both Transformer and LSTM architectures. The Transformer component excels at capturing long-range dependencies, while the LSTM component is adept at modeling sequential patterns. The innovation of the proposed methodology resides in the incorporation of dissolved oxygen (DO), electrical conductivity (EC), and oxidation-reduction potential (ORP) as input variables, along with their respective rate of change and cumulative value. This strategic selection of input features enhances the traditional utilization of water quality indicators and offers a more comprehensive dataset for prediction, ultimately improving model accuracy and reliability. Experimental validation on NH₃-N datasets from the SBR system reveals that the proposed model significantly outperforms existing advanced methods in terms of root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R²). Furthermore, by integrating real-time sensor data with the Transformer-LSTM network and automatic control, substantial improvements in water treatment processes were achieved, resulting in a 26.9% reduction in energy or time consumption compared with traditional fixed processing cycles. This methodology provides an accurate and reliable tool for predicting NH₃-N concentrations, contributing significantly to the sustainability of water treatment and ensuring compliance with emission standards. Full article

The aim of the work was to investigate the treatment efficiency of coking wastewater in a hybrid system combining the Fenton process with an SBR reactor. The Fenton reaction was optimised using variable reagent doses of 0.75, 1.0, 1.25 and 1.5 g/L for iron ions and 750, 1000, 1250, and 1500 mg/L for H₂O₂. The effects of Fe²⁺ and H₂O₂ concentration on BOD, COD, TOC, TN N-NH₄⁺ and BOD/COD ratio were studied in detail to optimise the pretreatment performance. The selection of the most favourable parameters for the Fenton reaction was based on the frequency of occurrence of a different combination of the chemical reagents. The most beneficial doses were found to be 0.75 g/L of iron (II) ion and 1000 mg/L of hydrogen peroxide, at which the COD reduction rate was about 40% and a high increase in the BOD₅/COD ratio from 0.1 to 0.31 was observed. Moreover, the obtained results showed that the efficiency of removing organic pollutants and nitrogen compounds was higher in the SBR reactor fed with pretreated wastewater. However, the relatively low efficiency of removing TKN (25%) and NH₄⁺ (21%) indicates the presence of toxic substances in them that may inhibit the removal of nitrogen compounds. Full article

The optimization of wastewater treatment technologies using biological processes is no longer limited to improving the removal of organic matter and nutrients, as it is possible to reduce area and energy consumption, and recover value-added by-products. In this context, the microalgae–bacteria consortium is an alternative for reducing costs, as microalgae produce the oxygen required by bacteria to oxidize organic matter through photosynthesis. Additionally, it is possible to extract different by-products such as lipids, biofertilizers, biogas, alginate-type exopolymers, and others. Furthermore, bioflocculation occurs naturally through the adhesion of microalgae to the surface of bacterial flocs, without the addition of chemical products. This review discusses the main systems that utilize the microalgae–bacteria consortium, the metabolism of the microalgae–bacteria consortium, and its performance in removing organic matter and nutrients, as well as the effect of operating conditions on the physical properties of the biomass. Among the highlighted systems are sequencing batch and single-batch reactors, high-rate ponds, and continuous flow reactors. Among the systems discussed in this work, the sequential batch reactor configurations found better biomass formation and production of extracellular polymeric substances and the continuous flow reactors showed lower installation and operating costs. From this perspective, the potential for full-scale application of each system can be evaluated once the optimum operating conditions have been defined and the limitations of each system have been understood. Full article

Partial nitrification–anaerobic ammonia oxidation represents an innovative nitrogen removal technique, distinguished by its shortened nitrogen removal pathway and reduced energy demands. Currently, partial nitrification is mostly studied in sequential batch reactors, and some of the methods to realize partial nitrification in continuous flow reactors have problems such as complicated operation and management, and can be easily destabilized. This study introduces a novel system utilizing light to establish an algal-bacterial consortium within a partial nitrification framework, where oxygen is supplied by algae and a novel rotating biological contactor (RBC). This approach aims to simplify the control strategy and decrease the energy required for aeration. The results demonstrated that light at an intensity of 200 μmol/(m²·s) effectively inhibited nitrite-oxidizing bacteria (NOB), swiftly stabilizing partial nitrification. In the absence of light, free ammonia (FA) and free nitric acid (FNA) inhibited NOB, with ammonium removal efficiency (ARE) and nitrite accumulation ratio (NAR) at 68.35% and 34.00%, respectively. By day 88, under light exposure, effluent NO₂⁻-N concentrations surged, with ARE and NAR at 64.21% and 69.45%, respectively. By day 98, NAR peaked at 80.28%. The specific oxygen uptake rate (SOUR) of ammonia-oxidizing bacteria (AOB) and NOB outside the disc was 3.24 mg O₂/(g MLSS·h) and 0.75 mg O₂/(g MLSS·h), respectively. Extracellular polymeric substance (EPS) content initially decreased, then increased, ultimately exceeding pre-light exposure levels. Microbial abundance significantly declined due to light exposure, with Nitrosomonas related-AOB decreasing by 91.88% from 1.6% to 0.13%, and Nitrospira related-NOB decreasing by 99.23% from 5.19% to 0.04%, respectively. The results indicated that both AOB and NOB were inhibited by light, especially NOB. It is a feasible strategy to achieve partial nitrification and algal-bacterial consortia by using light in a rotating biological contactor. Full article

Simultaneous nitrification and autotrophic denitrification (SNAD) has received attention as an efficient biological nitrogen removal alternative. However, SNAD using elemental sulfur (S⁰) has scarcely been studied. Thus, the main objective of this research was to study the behavior of a simultaneous nitrification–autotrophic denitrification operation in a sequential batch reactor (SNAD-SBR) at a lab scale using S⁰ as an electron donor, including its kinetics. Two-scale reactors were operated at lab scales in cycles for 155 days with an increasing nitrogen loading rate (NLR: 0.0296 to 0.0511 kg N-NH₄⁺/m³/d) at 31 °C. As a result, simultaneous nitrification–autotrophic denitrification using S⁰ as an electron donor was performed successfully, with nitrification efficiency of 98.63% and denitrification efficiency of 44.9%, with autotrophic denitrification as the limiting phase. The kinetic model adjusted for ammonium-oxidizing bacteria (AOB) was the Monod-type kinetic model (µmax = 0.791 d⁻¹), while, for nitrite-oxidizing bacteria (NOB), the Haldane-type model was employed (µmax = 0.822 d⁻¹). For denitrifying microorganisms, the kinetic model was adjusted by a half order (k_1/2v = 0.2054 mg^1/2/L^1/2/h). Thus, we concluded that SNAD could be feasible using S⁰ as an electron donor, with kinetic behavior similar to that of other processes. Full article

To improve the nitrogen removal and reduce the chemical oxygen demand (COD) of a full-scale wastewater treatment plant, two sequential batch reactor devices were used to treat chemical wastewater with biocarriers in low carbon-to-nitrogen (C/N) ratio conditions. The results showed that the addition of biocarriers to the anoxic tank reduced the average concentration of COD in the effluent from 98.1 mg/L to 80.7 mg/L and increased total nitrogen (TN) removal by 9.4%. Metagenomic sequencing was performed to study the composition and function of microbial community samples taken from anoxic sludge and anoxic-carrier biofilms in this wastewater treatment plant. The results showed that Proteobacteria and Actinobacteria were the dominant phyla in the two samples, ensuring their capability for organic matter removal. The anoxic-carrier biofilms were mainly enriched with denitrifying bacteria such as Thauera (10.7%) and Comammonas (2.2%) and the anammox bacteria Candidatus Kuenenia (0.03%). Meanwhile, the nitrogen metabolism pathway was elaborated and the abundance of the functional genes involved in the nitrogen metabolism pathway was quantified. In addition, results from qPCR showed increased copy numbers of denitrification and anammox genes in the anoxic-carrier biofilms compared to those in the anoxic sludge, further confirming the enrichment of functional bacteria. Full article

A major operation in petroleum refinery plants, blend scheduling management of stocks and their mixtures, known as blend-shops, is aimed at feeding process units (such as distillation columns and catalytic cracking reactors) and production of finished fuels (such as gasoline and diesel). Crude-oil, atmospheric residuum, gasoline, diesel, or any other stream blending and scheduling (or blend scheduling) optimization yields a non-convex mixed-integer nonlinear programming (MINLP) problem to be solved in ad hoc propositions based on decomposition strategies. Alternatively, to avoid such a complex solution, trial-and-error procedures in simulation-based approaches are commonplace. This article discusses solutions for blend scheduling (BS) in petroleum refineries, highlighting optimization against simulation, continuous (simultaneous) and batch (sequential) mixtures, continuous- and discrete-time formulations, and large-scale and complex-scope BS cases. In the latter, ordinary least squares regression (OLSR) using supervised machine learning can be utilized to pre-model blending of streams as linear and nonlinear constraints used in hierarchically decomposed blend scheduling solutions. Approaches that facilitate automated decision-making in handling blend scheduling in petroleum refineries must consider the domains of quantity, logic, and quality variables and constraints, in which the details and challenges for industrial-like blend-shops, from the bulk feed preparation for the petroleum processing until the production of finished fuels, are revealed. Full article