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Energy poverty is a multidimensional and complex phenomenon, and several indicators have been developed to evaluate and quantify it. However, often greater complexity does not mean greater precision. In the case of Chile, the Energy Poverty Network established the Three-dimensional and Territorial Indicator of Energy Poverty (EPTTI in Spanish) to assess the energy poverty situation of Chilean families. The EPTTI is based on a multidimensional approach with 10 indicators. Although, their evaluation involves resources that may hinder a practical application. This study analyzed the consistency between the individual responses of an indicator and the adapted EPTTI evaluation, using a database of 641 families. The results show that the excessive energy expenditure and the type and energy source of heating systems indicators are the variables with the greatest influence on energy poverty assessments. These results served to both propose simplified approaches for energy poverty assessment with the indicator, and establish policies of action that regional governments should address to reduce the situation of energy poverty Confort ambiental y pobreza energ´etica (+CO-PE)” of the University of the Bío-Bío, the Thematic Network 722RT0135 “Red Iberoamericana de Pobreza Energ´etica y Bienestar Ambiental” (RIPEBA) National Agency for Research and Development (ANID, in Spanish) Thematic Networks of the CYTED Program for 2021 Universidad de Granada / CBUA

This study show the experimental feasibility of the Solar thermal energy-based disinfection and inactivation of viruses, including the SARS CoV-2 from the different surfaces and utensils. A small prototype device is proposed and fabricated to serve the purpose. This device was tested in the field conditions using cotton clothes as a material/surface/utensil to observe the heating performance of the proposed device to attain the desired temperature range and corresponding timeline of heat-based 4 and 5 log viral load reduction/inactivation protocol. A new parameter ‘Disinfection Power’ is proposed to comment on the thermal performance of the SDC. The SDC satisfactorily reached temperatures ∼75–80 °C required for the 4 and 5 log heat-based viral load reduction protocol for disinfection cycles and maintained it for the heat for desired time line of minimum 60 min for the rated load of utensils. The value of the disinfection power at mean temperature difference (25 °C in the present case) is 29.9 W. The exergy efficiency of the SDC shows variation between 12.62 % and 22.69 %. Thus, SDC offers an affordable solution to reduce the risk of spreading the virus through contact with clothes and utensils.

In recent years, photovoltaic energy has become one of the most implemented electricity generation options to help reduce environmental pollution suffered by the planet. Accuracy in this photovoltaic energy forecasting is essential to increase the amount of renewable energy that can be introduced to existing electrical grid systems. The objective of this work is based on developing various computational models capable of making short-term forecasting about the generation of photovoltaic energy that is generated in a solar plant. For the implementation of these models, a hybrid architecture based on recurrent neural networks (RNN) with long short-term memory (LSTM) or gated recurrent units (GRU) structure, combined with shallow artificial neural networks (ANN) with multilayer perceptron (MLP) structure, is established. RNN models have a particular configuration that makes them efficient for processing ordered data in time series. The results of this work have been obtained through controlled experiments with different configurations of its hyperparameters for hybrid RNN-ANN models. From these, the three models with the best performance are selected, and after a comparative analysis between them, the forecasting of photovoltaic energy production for the next few hours can be determined with a determination coefficient of 0.97 and root mean square error (RMSE) of 0.17. It is concluded that the proposed and implemented models are functional and capable of predicting with a high level of accuracy the photovoltaic energy production of the solar plant, based on historical data on photovoltaic energy production.

Abstract Desalination powered by renewable energy sources is an attractive solution to address the worldwide water-shortage problem without contributing significant to greenhouse gas emissions. A promising system for renewable energy desalination is the utilization of low-temperature direct contact membrane distillation (DCMD) driven by a thermal solar energy system, such as a salt-gradient solar pond (SGSP). This investigation presents the first experimental study of fresh water production in a coupled DCMD/SGSP system. The objectives of this work are to determine the experimental fresh water production rates and the energetic requirements of the different components of the system. From the laboratory results, it was found that the coupled DCMD/SGSP system treats approximately six times the water flow treated by a similar system that consisted of an air–gap membrane distillation unit driven by an SGSP. In terms of the energetic requirements, approximately 70% of the heat extracted from the SGSP was utilized to drive thermal desalination and the rest was lost in different locations of the system. In the membrane module, only half of the useful heat was actually used to transport water across the membrane and the remainder was lost by conduction in the membrane. It was also found that by reducing heat losses throughout the system would yield higher water fluxes, pointing out the need to improve the efficiency throughout the DCMD/SGSP coupled system. Therefore, further investigation of membrane properties, insulation of the system, or optimal design of the solar pond must be addressed in the future.

This research arises from the need to know the elements that have an impact on the audiovisual competencies of adolescents during the confinements provoked to prevent the spread of COVID-19. The purpose is to diagnose the development of audiovisual communication skills among Ecuadorian adolescents as a contribution to sustainability, based on the intervention of educational actors. The methodology is qualitative, with a descriptive approach. The instruments used were: focus groups with parents, students, and teachers from public and private institutions in Ecuador; semi-structured interviews with experts: and non-participant observation. It can be concluded that adolescents acquire audiovisual skills, processes, and languages autonomously before entering college, but they do so without the social context, ethical values and responsibilities that should be part of complete media learning. The demands of online learning during the pandemic have resulted in the development of skills and attitudes, but they have not led to full media literacy. It is pertinent to provoke innovations and updates in the curricula of higher education, specifically in the careers of social communication, in order to be aware of the technological changes on the basis of deontological principles and in favour of democratic values, tolerance, and responsibility with the sustainability of nature and people.

In this study, the sizing problem of hybrid diesel–photovoltaic–battery systems was determined using a particle swarm optimization approach. The goal was to optimize the number of solar panels and batteries that could be installed to reduce the overall cost of an isolated grid system, originally powered by diesel generators, located on Isabela Island in the Galapagos, Ecuador. In this study, real solar radiation and temperature profiles were used, as well as the load demand and electrical distribution system relative to this island. The results reveal that the total cost for the proposed approach is lower as it reaches the global optimal solution. It also highlights the advantage of a hybrid diesel–photovoltaic–battery (DG-PV-BAT) system compared to conventional systems operated exclusively by diesel generators (DGs) and systems made up of DGs and PV panels; compared to them, a reduction in diesel consumption and total cost (71% and 56%, respectively) is achieved. The DG-PV-BAT system also considerably improves environmental factors and the quality of the power line. This study demonstrates the advantages of hybridizing systems isolated from the network through the proposed approach.

Analyzing plant phenology and plant–animal interaction networks can provide sensitive mechanistic indicators to understand the response of alpine plant communities to climate change. However, monitoring data to analyze these processes is scarce in alpine ecosystems, particularly in the highland tropics. The Andean páramos constitute the coldest biodiversity hotspot on Earth, and their species and ecosystems are among the most exposed and vulnerable to the effects of climate change. Here, we analyze for the first time baseline data for monitoring plant phenological dynamics and plant–pollinator networks along an elevation gradient between 4,200 and 4,600 m asl in three mountain summits of the Venezuelan Andes, which are part of the GLORIA monitoring network. We estimated the presence and density of plants with flowers in all the summits and in permanent plots, every month for 1 year. Additionally, we identified pollinators. We calculated a phenological overlap index between species. We summarized the plant–pollinator interactions as a bipartite matrix and represented a quantitative plant–pollinator network, calculating structural properties (grade, connectance, nestedness, and specialization). We also evaluated whether the overall network structure was influenced by differences in sampling effort, changes in species composition between summits, and phenology of the plant species. Finally, we characterized the pollination syndrome of all species. Flowering showed a marked seasonality, with a peak toward the end of the wet season. The overall phenological overlap index was low (0.32), suggesting little synchrony in flowering among species. Species richness of both plants and pollinators decreased along the elevation gradient. Flies, bumblebees, and hummingbirds were the most frequent pollinators in the network, while entomophily and anemophily were the prevailing pollination syndromes. The interaction network in all summits showed high connectance values, significant specialization (H2), and low nestedness. We did not find a significant effect of sampling effort, summit plant species composition, or plant phenology on network structure. Our results indicate that these high tropical alpine plant communities and their plant-pollination networks could be particularly vulnerable to the loss of species in climate change scenarios, given their low species richness and functional redundancy coupled with a high degree of specialization and endemism.

What kind of facade is the most energy efficient for a Mediterranean climate like Santiago? This article presents an energy efficiency analysis in offices built in Santiago between 2005 and 2011. The conclusions are far from what we see today: buildings with mixed facades (walls and windows) are more efficient than glazed facades. Keywords. Author Keywords:ENERGY CONSUMPTION; OFFICE BUILDINGS; TYPOLOGICAL ANALYSIS; SUSTAINABILITY; SANTIAGO