After biological treatment, coke wastewater contains small amounts of phenolic compounds resistant to such treatment. The removal of phenols and COD from coke wastewater subjected to biological treatment was studied. The adsorbents used were granular activated carbon and the resins XAD-2, AP-246 and OC-1074. Equilibrium, kinetics and column assays were carried out, fitting the equilibrium data to Langmuir and Freundlich models and the kinetic data to the Lagergren equation. The best results were obtained with GAC, which presented higher adsorption capacities. In the equilibrium assays, the adsorption capacities (Q) found were 1.48 mg g −1 for GAC versus 0.07 and 0.04 mg g −1 for resins AP-246 and OC-1074, respectively. In the kinetic assays, the values of the Lagergren adsorption parameter, q e , were 1.69, 0.15 and 0.14 mg g −1 for GAC, AP-246 and OC-1074, respectively. In the column assays, the dynamic capacity of GAC for up to 480 bed volumes was 1.82 mg mL −1 . No saturation was obtained for this volume due to the asymptotic shape of the breakthrough curve, whereas for the same percolated volume, the resins AP-246 and OC-1074 were saturated. These two resins presented similar saturation capacities of around 1.1 mg mL −1 .

This paper analyses six strategies for managing the MSW generated in Asturias (Spain) in terms of their environmental impacts applying the Life Cycle Analysis methodology.To this end, the effect of these strategies on Human Health, Ecosystem Quality, GlobalWarming and Resource Depletion is studied. The analysed management options include direct landfill with recovery of biogas (S-0), direct incineration with energy recovery (S-1), biomethanization of the source-separated organic fraction with direct incineration of the mixed fraction (S-2), biomethanization of the source-separated organic fraction, sorting of the mixed fraction and incineration of the rejected fraction (S-3), biomethanization of the source-separated organic fraction, sorting of the mixed fraction and incineration of the rejected fraction following aerobic stabilization of the organic fraction (S-4 ) and biomethanization of the source-separated organic fraction, sorting of the mixed fraction and landfill of the rejected following aerobic stabilization of the organic fraction (S-5). The Consortium for Waste Management (COGERSA) provide data regarding on transport and collection of waste and consumption of energy, water, oil and reagents at each processes. The results obtained suggest that Scenario S-3 has the least impact on the analysed damage categories while the scenarios including landfilling produces the greatest impact in all the categories analysed. Regarding involved processes in studied scenarios, the transport produces a significant impact in the environment, biomethanization contributes to reducing the impact in all the damage categories and incineration adversely affects the categories of Human Health and Climate Change, but helps to reduce damage in the Resources category. M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT NUMBER OF WORDS INCLUDING REFERENCES,

This paper present a study of the effect of applying ultrasound pre-treatment in the production of methane when co-digesting mixtures of cattle manure with food waste and sludge. A series of experiments were carried out under mesophilic and thermophilic conditions in continuously stirred-tank reactors containing 70% cattle manure, 20% food waste and 10% sewage sludge. Ultrasound pre-treatment allows operating at lower HRT, achieving higher volumetric methane yields: 0.85 L CH 4 /L.day at 36ºC and 0.82 CH 4 /L.day at 55ºC, when cattle manure and sewage sludge were sonicated. With respect to the non sonicated waste, these values represent increases of up to 31% and 67% for mesophilic and thermophilic digestion, respectively.

A laboratory-scale Activated Sludge System (ASS) was employed for the biodegradation of coke wastewater, which contains high concentrations of ammonium, thiocyanate, phenols and other organic compounds. The well-known kinetics models of Monod or Haldane are not very useful due to inhibition phenomena amongst the pollutants and also, they need the determination of a wide range of parameters to be introduced in the models. In this paper, a feed-forward neural network is outlined to obtain a satisfactory approach for estimating the effluent ammonium concentration of the treatment plant. The methodology consists in performing a group of different sizes of the hidden layer and different subsets of input variables.The developed model is useful to obtain simulations under different conditions of the influent stream, thus enabling the effluent ammonium concentration to be estimated. This neural network achieves better results than classical mathematical models for biological wastewater treatment as a result of the complex composition of the coke wastewater.

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