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Nowadays, heating using wood, briquettes, or pellets is a curious replacement to fossil fuels such as coal, oil, or gas. Unfortunately, the combustion of biofuels, especially in low-power boilers with unstable operating conditions, releases a lot of gas pollutants (e.g., carbon monoxide (CO), nitric oxide (NO), and various organic compounds) that are usually generated due to the incomplete product combustion. The combustion of biofuel in grate boilers with top-down ignition is a new approach, popular in society (mainly used for coal fuels), which improves the combustion process and reduces the amount of pollutants emitted. This study evaluated the impact of ignition techniques on the emission level of gas pollutants during the combustion of wood logs, briquettes, and pellets of pine in grate-based charging boilers. The combination of top ignition mode with pinewood logs allowed us to achieve a reduction of 6% in CO and sulfur dioxide (SO2) emission into the atmosphere. However, the combination of top-down ignition mode with pellets and briquettes produced, in fully operational conditions, 1- to 18-fold higher levels of CO and SO2 respectively, than bottom-up ignition, after an initial period of low level CO and SO2 emissions. During the tests (mainly with ignition from top), substantial emissions of NO were observed of up to 400 mg·m−3 at 10% O2. Therefore, further research is required to decrease emission related to the content of nitrogen in biomass. In this respect, research of impact on the combustion temperature of such emissions is needed.

Microbial electrochemical technologies (METs) constitute the core of a number of emerging technologies with a high potential for treating urban wastewater due to a fascinating reaction mechanism—the electron transfer between bacteria and electrodes to transform metabolism into electrical current. In the current work, we focus on the model electroactive microorganism Geobacter sulfurreducens to explore both the design of new start-up procedures and electrochemical operations. Our chemostat-grown plug and play cells, were able to reduce the start-up period by 20-fold while enhancing chemical oxygen demand (COD) removal by more than 6-fold during this period. Moreover, a filter-press based bioreactor was successfully tested for both acetate-supplemented synthetic wastewater and real urban wastewater. This proof-of-concept pre-pilot treatment included a microbial electrolysis cell (MEC) followed in time by a microbial fuel cell (MFC) to finally generate electrical current of ca. 20 A·m−2 with a power of 10 W·m−2 while removing 42 g COD day−1·m−2. The effective removal of acetate suggests a potential use of this modular technology for treating acetogenic wastewater where Geobacter sulfurreducens outcompetes other organisms.

The prevailing need for a more sustainable management of natural resources depends not only on the decisions made by governments and the will of the population, but also on the knowledge of the role of energy in our society and the relevance of preserving natural resources. In this sense, critical work is being done to instill key concepts—such as the circular economy and sustainable energy—in higher education institutions. In this way, it is expected that future professionals and managers will be aware of the importance of energy optimization, and will learn a series of computational methods that can support the decision-making process. In the context of higher education, this paper reviews the main trends and challenges related to the concepts of circular economy and sustainable energy. Besides, we analyze the role of simulation and serious games as a learning tool for the aforementioned concepts. Finally, the paper provides insights and discusses open research opportunities regarding the use of these computational tools to incorporate circular economy concepts in higher education degrees. Our findings show that, while efforts are being made to include these concepts in current programs, there is still much work to be done, especially from the point of view of university management. In addition, the analysis of the teaching methodologies analyzed shows that, although their implementation has been successful in favoring the active learning of students, their use (especially that of serious games) is not yet widespread.

In this study, our aim was to explore the potential energy savings obtainable from the recycling of 1 tonne of Construction and Demolition Waste (C&DW) generated in the Metropolitan City of Naples. The main fraction composing the functional unit are mixed C&DW, soil and stones, concrete, iron, steel and aluminium. The results evidence that the recycling option for the C&DW is better than landfilling as well as that the production of recycled aggregates is environmentally sustainable since the induced energy and environmental impacts are lower than the avoided energy and environmental impacts in the life cycle of recycled aggregates. This LCA study shows that the transition to the Circular Economy offers many opportunities for improving the energy and environmental performances of the construction sector in the life cycle of construction materials by means of internal recycling strategies (recycling C&DW into recycled aggregates, recycled steel, iron and aluminum) as well as external recycling by using input of other sectors (agri-food by-products) for the manufacturing of construction materials. In this way, the C&D sector also contributes to realizing the energy and bioeconomy transition by disentangling itself from fossil fuel dependence.

The yeast Yarrowia lipolytica is an industrially relevant microorganism, which is able to convert low-value wastes into different high-value, bio-based products, such as enzymes, lipids, and other important metabolites. Waste cooking oil (WCO) represents one of the main streams generated in the food supply chain, especially from the domestic sector. The need to avoid its incorrect disposal makes this waste a resource for developing bioprocesses in the perspective of a circular bioeconomy. To this end, the strain Y. lipolytica W29 was used as a platform for the simultaneous production of intracellular lipids and extracellular lipases. Three different minimal media conditions with different pH controls were utilized in a small-scale (50 mL final volume) screening strategy, and the best condition was tested for an up-scaling procedure in higher volumes (800 mL) by selecting the best-performing possibility. The tested media were constituted by YNB media with high nitrogen restriction (1 g L−1 (NH4)2SO4) and different carbon sources (3% w v−1 glucose and 10% v v−1 WCO) with different levels of pH controls. Lipase production and SCO content were analyzed. A direct correlation was found between decreasing FFA availability in the media and increasing SCO levels and lipase activity. The simultaneous production of extracellular lipase (1.164 ± 0.025 U mL−1) and intracellular single-cell oil accumulation by Y. lipolytica W29 growing on WCO demonstrates the potential and the industrial relevance of this biorefinery model.

Steam methane reforming (SMR) for hydrogen production was studied by simulating the reformer and pre-reformer sections. This simulation was validated by using available data taken from a real industrial plant, which enabled precise correlations with the real industrial process to be found. Moreover, the influence of the molar ratio between the raw materials (steam-to-carbon molar ratio, S/C) and the reformer outlet temperature (Tcc) was studied. The energy requirements for the reforming reaction increased with the S/C ratio. The energy needed for developing the reforming reaction also increased with Tcc, but the hydrogen yield when operating with a high S/C ratio and Tcc increased. In addition, an exergetic analysis was carried out to identify exergy losses in the SMR process, and most were destroyed in the chemical reactors. Increasing the combustion air flow was proposed for finding an optimum value for exergetic efficiency in the process, thereby reducing fuel consumption. Finally, there was a study into the economic viability of this investment, with a reduction of 22% in utility costs with the optimum exergetic value.

The behaviours of individual flow structures have become a relevant matter of study in turbulent flows as the computational power to allow their study feasible has become available. Especially, high instantaneous Reynolds Stress events have been found to dominate the behaviour of the logarithmic layer. In this work, we present a viability study where two machine learning solutions are proposed to reduce the computational cost of tracking such structures in large domains. The first one is a Multi-Layer Perceptron. The second one uses Long Short-Term Memory (LSTM). Both of the methods are developed with the objective of taking the the structures’ geometrical features as inputs from which to predict the structures’ geometrical features in future time steps. Some of the tested Multi-Layer Perceptron architectures proved to perform better and achieve higher accuracy than the LSTM architectures tested, providing lower errors on the predictions and achieving higher accuracy in relating the structures in the consecutive time steps.