Evaluating the performance of anaerobic moving bed bioreactor and upflow anaerobic hybrid reactor for treating textile desizing wastewater

Nickel augmented biochar for sustaining produced water treatment to decarbonize oil and gas industrial waste using anaerobic-aerobic granular cylindrical periodic discontinuous batch reactors

This study assessed the efficacy of granular cylindrical periodic discontinuous batch reactors (GC-PDBRs) for produced water (PW) treatment by employing eggshell and waste activated sludge (WAS) derived Nickel (Ni) augmented biochar. The synthesized biochar was magnetized to further enhance its contribution towards achieving carbon neutrality due to carbon negative nature, Carbon dioxide (CO2) sorption, and negative priming effects. The GC-PDBR1 and GC-PDBR2 process variables were optimized by the application of central composite design (CCD). This is to maximize the decarbonization rate. Results showed that the systems could reduce total phosphorus (TP) and chemical oxygen demand (COD) by 76-80% and 92-99%, respectively. Optimal organic matter and nutrient removals were achieved at 80% volumetric exchange ratio (VER), 5 min settling time and 3000 mg/L mixed liquor suspended solids (MLSS) concentration with desirability values of 0.811 and 0.954 for GC-PDBR1 and GC-PDBR2, respectively. Employing four distinct models, the biokinetic coefficients of the GC-PDBRs treating PW were calculated. The findings indicated that First order (0.0758-0.5365) and Monod models (0.8652-0.9925) have relatively low R2 values. However, the Grau Second-order model and Modified Stover-Kincannon model have high R2 values. This shows that, the Grau Second Order and Modified Stover-Kincannon models under various VER, settling time, and MLSS circumstances, are more suited to explain the removal of pollutants in the GC-PDBRs. Microbiological evaluation demonstrated that a high VER caused notable rises in the quantity of several microorganisms. Under high biological selective pressure, GC-PDBR2 demonstrated a greater percentage of nitrogen removal via autotrophic denitrification and a greater number of nitrifying bacteria. The overgrowth of bacteria such as Actinobacteriota spp. Bacteroidota spp, Gammaproteobacteria, Desulfuromonas Mesotoga in the phylum, class, and genus, has positively impacted on granule formation and stability. Taken together, our study through the introduction of intermittent aeration GC-PDBR systems with added magnetized waste derived biochar, is an innovative approach for simultaneous aerobic sludge granulation and PW treatment, thereby providing valuable contributions in the journey toward achieving decarbonization, carbon neutrality and sustainable development goals (SDGs).

Development of a Novel Energy Saving and Environmentally Friendly Starch via a Graft Copolymerization Strategy for Efficient Warp Sizing and Easy Removal

Warp sizing is a key process in textile production. However, before the yarn/fabric finishing, such as dyeing, the paste adhering to the warp must be eliminated to ensure optimal dyeing properties and the flexibility of the fabric. Therefore, the sizing will often consume a lot of energy and produce a lot of industrial wastewater, which will cause serious harm to the environment. In this study, we have developed an energy saving and environmentally friendly starch-based slurry by modifying natural starch with acrylamide. The paste has excellent viscosity stability and fiber adhesion, and exhibits excellent performance during warp sizing. In addition, the slurry has good water solubility at 60-70 °C, so it is easy to desize at low temperatures. Because of this, the sizing of the warp can be deslimed directly from the yarn during subsequent washing processes. This work can not only reduce some costs for the textile industry, but also achieve the purpose of energy conservation and emission reduction.

Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology

Agro-industrial biorefinery effluent (AIBW) is considered a highly polluting source responsible for environmental contamination. It contains high loads of chemical oxygen demand (COD), and phenol, with several other organic and inorganic constituents. Thus, an economic treatment approach is required for the sustainable discharge of the effluent. The long-term process performance, contaminant removal and microbial response of AIBW to rice straw-based biochar (RSB) and biochar-based geopolymer nanocomposite (BGC) as biosorbents in an activated sludge process were investigated. The adsorbents operated in an extended aeration system with a varied hydraulic retention time of between 0.5 and 1.5 d and an AIBW concentration of 40-100% for COD and phenol removal under standard conditions. Response surface methodology was utilised to optimize the process variables of the bioreactor system. Process results indicated a significant reduction of COD (79.51%, 98.01%) and phenol (61.94%, 74.44%) for BEAS and GEAS bioreactors respectively, at 1 d HRT and AIBW of 70%. Kinetic model analysis indicated that the Stover-Kincannon model best describes the system functionality, while the Grau model was better in predicting substrate removal rate and both with a precision of between R2 (0.9008-0.9988). Microbial communities examined indicated the abundance of genera, following the biosorbent addition, while RSB and BGC had no negative effect on the bioreactor's performance and bacterial community structure of biomass. Proteobacteria and Bacteroidetes were abundant in BEAS. While the GEAS achieved higher COD and phenol removal due to high Nitrosomonas, Nitrospira, Comamonas, Methanomethylovorans and Acinetobacter abundance in the activated sludge. Thus, this study demonstrated that the combination of biosorption and activated sludge processes could be promising, highly efficient, and most economical for AIBW treatment, without jeopardising the elimination of pollutants or the development of microbial communities.

Performance and cost-benefit analysis of anaerobic moving bed biofilm reactor for pretreatment of textile wastewater

Performance of an anaerobic moving bed biofilm reactor (AnMBBR) was evaluated for pretreatment of real textile desizing wastewater at organic loading rate (OLR) of 1±0.05 to 6.3±0.37 kgCOD/m3/d. After OLR optimization, the performance of AnMBBR was evaluated for biodegradation of reactive dyes. AnMBBR was operated under a mesophilic temperature range of 30 to 36 °C, while the oxidation-reduction potential (ORP) and pH were in the range of 504 to 594 (-mV) and 6.98 to 7.28, respectively. By increasing the OLR from 1±0.05 to 6.3±0.37 kgCOD/m3/d, COD and BOD5 removal was decreased from 84 to 39% and 89 to 49%, respectively. While the production of biogas was increased from 0.12 to 0.83 L/L·d up to an optimum OLR of 4.9±0.43 kgCOD/m3/d. With increase in the dye concentration in the feed, COD, BOD5, color removal and biogas production reduced from 56, 63, 70% and 0.65 L/L·d to 34, 43, 41% and 0.08 L/L·d, respectively. Based on the data obtained, a cost-benefit analysis of AnMBBR was also investigated for the pretreatment of real textile desizing wastewater. Cost estimation of anaerobic pretreatment of textile desizing wastewater indicated a net profit of 21.09 million PKR/yr (114,000 €/yr) and a potential payback period of 2.54 years.

A comparison of nitrogen removal systems through cost-coupled life cycle assessment and energy efficiency analysis

The global water crisis reflects the necessity of exploring the best approaches for the water supply. Therefore, for the first time, the current study compares nitrogen removal systems (NRSs) from life cycle assessment (LCA), economic, kinetic, thermodynamic, and synergistic perspectives. The assessed systems were sequential batch reactor (SBR), oxic/anoxic (OA), and oxic/anaerobic/oxic (OAO) bioreactors. Among all, the SBR configuration showed the best efficiency (98.74 %) for nitrogen removal. The environmental impacts notably presented by marine + freshwater ecotoxicity (53.76 %), and climate change categories (16.39 %), significantly because of metal emissions. Non-renewable sources supplied 95 % of total energy demand. The operation of NRSs showed the most impact on human health (63.67 %) through CH₄ and CO₂ emissions. The total costs significantly belonged to the construction (<86.37 %) > amortization> operation. The influent COD illustrated the most role in environmental burdens (16.44 %) based on the sensitivity analysis. The removal reaction was endothermic, physical, non-spontaneous, and followed a pseudo-second-order kinetic model (R² > 0.98). The chemical exergy provided the major portion of the total calculated exergy (83 %). The exergetic efficiency of the system was 69 %, which was predominantly supplied by biogas (∼50.75 %). Accordingly, this study can present a stepwise guideline for further related investigations.

Experiments and adaptive-network-based fuzzy inference system modelling in a hybrid up-flow anaerobic sludge blanket reactor to assess industrial azadirachtin effluent quality

Experimental investigations were carried out for the treatment of industrial azadirachtin effluent in a hybrid up-flow anaerobic sludge blanket (HUASB) reactor continuously for 115 days in three stages at mesophilic temperature (30 - 35˚C). An adaptive-network-based fuzzy inference system (ANFIS) modelling and statistical regression analysis were applied with the raw data. In the ANFIS modelling as well as in the statistical regression analysis, the operating parameters such as initial pH, influent COD, effluent COD and biogas generation (X₁, X_2, X₃ and X₄) were taken as variables and effluent BOD values as a response (Y). The average percentage error (APE) values of ANFIS modelling were 2.18, 12.29, and 0.01%, for stage-I, II and III respectively. These values indicated that ANFIS modelling performed well in all the three stages and provided more accurate results.

Review on effect of different type of dyes on advanced oxidation processes (AOPs) for textile color removal

The textile industry is one of the most valuable industries, especially in developing countries, because it employs a large portion of the workforce. However, the development of the textile industry has led to increasing concern about environmental issues. Wastewater from the textile industry has a high COD and an undesirable color. Color is one of the problems with the wastewater due to its toxicity and low biodegradability. Color in textile wastewater mainly originates from the dyestuff used during the dyeing or printing process. Amongst all of available technology for color removal, advanced oxidation processes (AOPs) are considered one of the best and the most potential technology. However, the understanding of AOPs reaction mechanism to degrade dyestuff is still limited. In general, dyes degradation mechanism will vary and mainly depend on the chemical structure of the dyes itself. Some reaction pathway that seems less favorable thermodynamically can still happen during the process. Understanding the mechanism will be beneficial for future dyes improvement, especially on developing the moiety of the aromatic compound in order to produce easily degraded dyes while maintaining the fastness quality.