Ángeles Blanco Suárez

Application of Multi-Barrier Membrane Filtration Technologies to Reclaim Municipal Wastewater for Industrial Use

The significant percentage of the world water consumption devoted to industrial use, along with an increasingly higher environmental concern of society, has awaken the interest of industry on using municipal reclaimed water for replacing fresh water use coming from utilities or natural resources. Depending on the type of industry and the specific application, water must meet certain quality requirements. Therefore, those water quality standards that are required for those most relevant industrial applications wherein the use of reclaimed water has noticeably been reported are herewith reviewed. Although the use of internal water treatments for recycling and reusing their own effluents has recently and widely been reported within many industrial sectors worldwide, the substitution of fresh water by reclaimed municipal wastewater has yet to be extended much. The increasing proportion of municipal wastewater reclamation plants that rely on membrane filtration technologies versus the total number of reclamation facilities that are distributed worldwide is also assessed within this review, including the discussion of their main related drawbacks.

Assessing the effect of inorganic anions on TiO2-photocatalysis and ozone oxidation treatment efficiencies

Abstract Considering the application of AOPs might be limited for the treatment of industrial wastewater with high inorganic load, and that partial results reported to date regarding this particular are inconclusive, even opposite in some cases, the effect of inorganic anions on the oxidation efficiency of photocatalysis and ozonation has been further assessed with statistical significance. While the presence of sulphate and chloride did not appreciably affect the photocatalytic oxidation of phenol, nitrate significantly enhanced the removal of COD (≈ 8-15%). The addition of carbonate simply increased the pH, which strongly inhibited the photocatalytic process; whereas if pH=5 was kept constant, the reduction of the COD was not affected by the presence of carbonate. On the other hand, sulphate, chloride and nitrate did not significantly affect the degradation of phenol by ozonation; whereas the presence of carbonate apparently enhanced the reduction of COD. It is actually proved that this improvement in the efficiency of the treatment was produced by the pH buffering effect of these ions, rather than to its presence itself, which actually significantly reduced the removal of COD (5-10%) by radical scavenging action in comparison to when the treatment was performed in the absence of anions in the solution adjusting the pH to similar basic values (≈9.5-13.5). When ozonation was performed at a pH close to neutral (6.5 ± 0.2) or basic (12 ± 0.2), at which the indirect oxidation of hydroxyl radical is surely widely active, the results were significantly enhanced in any case (COD removal ≈ 70-75%), whether in the absence or the presence of these anions; despite the significant slight radical scavenging effect (COD removal ≈ 65-70%) that was attributed to the addition of carbonate.

Estimation of Chlamydomonas reinhardtii biomass concentration from chord length distribution data

A novel method to estimate the concentration of Chlamydomonas reinhardtii biomass was developed. The method employs the chord length distribution information gathered by means of a focused beam reflectance probe immersed in the culture sample and processes the data through a feedforward multilayer perceptron. The multilayer perceptron architecture was systematically optimised through the application of a simulated annealing algorithm. The method developed can predict the concentration of microalgae with acceptable accuracy and, with further development, it could be implemented online to monitor the aggregation status and biomass concentration of microalgal cultures.

Laser reflectance measurement for the online monitoring of Chlorella sorokiniana biomass concentration

Fast and reliable methods to determine biomass concentration are necessary to facilitate the large scale production of microalgae. A method for the rapid estimation of Chlorella sorokiniana biomass concentration was developed. The method translates the suspension particle size spectrum gathered though laser reflectance into biomass concentration by means of two machine learning modelling techniques. In each case, the model hyper-parameters were selected applying a simulated annealing algorithm. The results show that dry biomass concentration can be estimated with a very good accuracy (R2=0.87). The presented method seems to be suited to perform fast estimations of biomass concentration in suspensions of microalgae cultivated in moderately turbid media with tendency to aggregate.