Traditional lignin pyrolysis generates a bio-oil with a complex mixture of alkyl-functionalized guaiacol and syringol monomers that have limited utility to completely replace phenol in resins. In this work, formate assisted fast pyrolysis (FAsP) of lignin yielded a bio-oil consisting of alkylated phenol compounds, due to deoxyhydrogenation, that was used to synthesize phenol/formaldehyde resins. A solvent extraction method was developed to concentrate the phenolics in the extract to yield a phenol rich monomer mixture. Phenolic resins were synthesized using phenol (phenol resin), FAsP bio-oil (oil resin), and an extract mimic (mimic resin) that was prepared to resemble the extract after further purification. All three phenolic sources could synthesize novolac resins with reactive sites remaining for subsequent resin curing. Differential scanning calorimetry and thermogravimetric analysis of the three resins revealed similar thermal and decomposition behavior of phenol and the mimic resins, while the oil resin was less stable. Resins were cured with hexamethylenetetramine and the mimic resin demonstrated improved curing energies compared to the oil resin. The adhesive strength of the mimic resin was found to be superior to that of the oil resins. These results confirmed that extracting a mixture of substituted aromatics from FAsP bio-oil could synthesize resins with properties similar to those from phenol and improved over the parent bio-oil.

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Computational self-adapting methods (Support Vector Machines, SVM) are compared with an analytical method in effluent composition prediction of a two-stage anaerobic digestion (AD) process. Experimental data for the AD of poultry manure were used. The analytical method considers the protein as the only source of ammonia production in AD after degradation. Total ammonia nitrogen (TAN), total solids (TS), chemical oxygen demand (COD), and total volatile solids (TVS) were measured in the influent and effluent of the process. The TAN concentration in the effluent was predicted, this being the most inhibiting and polluting compound in AD. Despite the limited data available, the SVM-based model outperformed the analytical method for the TAN prediction, achieving a relative average error of 15.2% against 43% for the analytical method. Moreover, SVM showed higher prediction accuracy in comparison with Artificial Neural Networks. This result reveals the future promise of SVM for prediction in non-linear and dynamic AD processes. Graphical abstract ᅟ.

Higher standards in the European Water Framework Directive and national directive demand advanced wastewater treatment for removal of nutrients and organic micropollutants before the discharge into water bodies. Systematic investigations regarding relative dosage and filtration processes for removal of flocculated solids are currently lacking. In this study, the performance of technologies for advanced removal of total phosphorus down to <100 μg/L with pile cloth-filtration (CF) and membrane filtration was verified and synergy effects for the removal of other contaminants were identified. The results show that an over-stoichiometric addition of coagulants of >5 mol Me3+/mol sRP was necessary to achieve soluble reactive phosphorus (sRP) concentrations of <50 μg/L in the effluent. After the coupled process of tertiary phosphorus removal and solids removal, the soluble non-reactive phosphorus (sNRP) concentration regulates the lowest total phosphorus effluent concentration. sNRP is also partially, but not completely, removed by the use of coagulants. CF has proven to be an alternative technology for the removal of phosphorus and total suspended solids below the detection limit.