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The ethanolic fermentation of liquid fractions (hydrolysates) issued from dilute acid pre-treatment of olive tree biomass by Pichia stipitis is reported for the first time. On the one side, P. stipitis has been reported as the most promising naturally occurring C5 fermenting microorganism; on the other side, olive tree biomass is a renewable, low cost, and lacking of alternatives agricultural residue especially abundant in Mediterranean countries. The study was performed in two steps. First, the fermentation performance of P. stipitis was evaluated on a fermentation medium also containing the main inhibitors found in these hydrolysates (acetic acid, formic acid, and furfural), as well as glucose and xylose as carbon sources. The effect of inhibitors, individually or in a mixture, on kinetic and yield parameters was calculated. In a second step, hydrolysates obtained from 1% (w/w) sulfuric acid pre-treatment of olive tree biomass at 190ºC for 10 min were used as a real fermentation medium with the same microorganism. Due to inhibition, effective fermentation required dilution of the hydrolysate and either overliming or activated charcoal treatment. Results show that ethanol yields obtained from hydrolysates, ranging from 0.35 to 0.42 g/g, are similar to those from synthetic medium, although the process proceeds at lower rates. Inhibiting compounds affect the fermentation performance in a synergistic way. Furfural is rapidly assimilated by the yeast; acetic acid and formic acid concentrations decrease slowly during the process. Activated charcoal or overliming detoxification improve the fermentability of diluted hydrolysates.

Sustainable electricity generation is one of the major current challenges for our society. In this context, the evolution of nanomaterials and nanotechnologies has enabled the fabrication of microscopic devices to produce clean energy from a great variety of renewable sources. To expand the possibilities of energy generation, we have designed and fabricated bioinorganic generators capable to produce electricity by conversion of chemical energy from renewable fuel sources. Unlike traditional generators, the systems described herein produce mechanical energy through enzyme-driven gas production which generates vibration and pressure that are thus converted into electricity by the action of a piezoelectric component properly integrated into the device. Our generators are able to produce an electric ernergy from different renewable sources like glucose, ethanol, and amino acids, attaining energy outputs around 250 nJ cm–2 and reaching maximum open-circuit voltages of up to 1 V. In addition, the produced energy can be easily regulated by adjusting both enzyme and fuel concentration which can tune the electrical output according to the application. The systems described herein propose a new concept for self-sufficient energy harvesting that bridges biocatalysis and piezoelectricity, where the energy production is based on the piezoelectric effect triggered by enzymatic action rather than on the enzyme-driven electron transfer that governs biofuel cells. Although the electric output is too low yet to be considered an alternative for energy production, this technology opens the door to power small devices. We envision the utilization of this technology in such remote locations where mechanical energy is lacking but there are chemical energy reservoirs. We would like to acknowledge Marie-Curie Actions (NANOBIENER project), IKERBASQUE foundation for funding F.L.-G., and the support of COST Action CM1303 Systems Biocatalysis. We also acknowledge HERGAR foundation for the funding. Peer reviewed

The energy considered as waste heat in industrial furnaces owing to inefficiencies represents a substantial opportunity for recovery by means of thermal energy storage (TES) implementation. Although conventional systems based on sensible heat are used extensively, these systems involve technical limitations. Latent heat storage based on phase change materials (PCMs) results in a promising alternative for storing and recovering waste heat. Within this scope, the proposed PCM-TES allows for demonstrating its implementation feasibility in energy-intensive industries at high temperature range. The stored energy is meant to preheat the air temperature entering the furnace by using a PCM whose melting point is 885 °C. In this sense, a heat transfer model simulation is established to determine an appropriate design based on mass and energy conservation equations. The thermal performance is analysed for the melting and solidification processes, the phase transition and its influence on heat transference. Moreover, the temperature profile is illustrated for the PCM and combustion air stream. The obtained results prove the achievability of very high temperature levels (from 700 to 865 °C) in the combustion air preheating in a ceramic furnace; so corroborating an energy and environmental efficiency enhancement, compared to the initial condition presenting an air outlet at 650 °C.

El proyecto REVen “Rehabilitación energética de viviendas sociales, aplicando productos innovadores de ventana con marcado CE” (BIA2014-56650-JIN), tiene como objetivo realizar un análisis integral del impacto de la ventana en los aspectos relativos a eficiencia energética y calidad ambiental. Para caracterizar los flujos de energía y las condiciones ambientales internas se ha construido el Laboratorio REVen. Este artículo describe la construcción y la monitorización de este laboratorio analizando los datos de su primer año de funcionamiento. Los resultados permiten afirmar que se logra una mejora significativa del confort térmico obteniendo un ahorro de energía anual del 25 %.

Considering recent environmental regulations, the need to adapt domestic biomass combustion systems to models that generate less emissions has gained relative importance. The present research proposes an analysis of the bed cooling effects on emission patterns, specifically focusing on the concentration, typology and morphological aspects of the released particles. The study was carried out by comparing the behaviour of a small-scale pilot plant with air stratification, with and without bed cooling. The results revealed an optimal behaviour of the facility with distributions of 30% primary-70% secondary air, accompanied by a significant decrease in emissions due to the reduction in the operating temperatures. More than 75% of the particles were retained in the bed on the cooled surfaces due to the effect of the prominent temperature gradient that was produced. Among the types of emitted particles (mostly with sizes below 0.1 μm), the presence of partial biomass degradation remnants was observed, representing three-quarters of the total collected matter. To a lesser extent, the presence of carbonaceous agglomerates was detected and usually in very compact clusters; however, in cases of high primary air supply, large amounts of immature soot were observed. Agencia Estatal de Investigación | Ref. RTI2018-100765-B-I00

There are different monitoring procedures in wind farms with two main objectives: (i) to improve energy production by the capability of the national electrical network and (ii) to reduce the stooped hours due to preventive and or corrective maintenance activities. In this sense, different sensors are employed to sample in real-time the working conditions of equipment, the electrical production and the weather conditions. Despite this, just the anemometer measurement can be related to the more important errors of interruption of power regulation and anemometer errors. Both errors are related to gusty winds and contribute to more than 33% of the cost of a wind farm. The present paper reports some mathematical relations between weather and maintenance but there are no extreme values of each variable that let us predict a near failure and its corresponding loss of working hours. To achieve this, statistical analysis identifies the relation between weather variables and errors and different models are obtained. What is more, due to the difficulty and economic implications involving the implementation of complex algorithms and techniques of artificial intelligence, it is still a challenge to optimize this process. Finally, the obtained results show a particular case study that can be extrapolated to other wind farms after different case studies to adjust the model to different weather regions, and serve as a useful tool for weather maintenance.