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This document presents a qualitative analysis of surface temperatures of the oceanic territory of Panama. These temperatures represent an indication of the potential of the thermal resource in the oceanic territory of Panama and could generate benefits for the success and stability of the national economy facing the current and growing challenges of the society. The OTEC technology is promising for countries located in tropical regions, where sea temperature differentials are ideal for efficient operability. Currently, this technology has low efficiency levels. Therefore, to evaluate its possible implementation in Panama, a theoretical thermodynamic analysis has been carried out. An organic Rankine cycle (ORC) simulation for the net production of 100KW was performed. It considered the temperature differentials of the oceanography of Panama and used refrigerants R717 and R134a as working fluids. Considering the database of Physical Oceanography Distributed Active Archive Center (PODAAC) for the year 2018, the ocean territory of Panama in the Gulf of Chiriqui reflects seawater surface temperatures (SST) of approximately 27.5 °C to almost 29.5 °C. Besides these values they do not reflect representative anomalies in the critical points with respect to the seasons of the year. The importance of the study in this area is its proximity to the deep cold sea waters, considering the Panama bathymetry map, since its SST are not very variable through the year or through the territory?

Abstract Level(s) is a common European Union framework of core sustainability indicators for measuring the performance of buildings along their life cycle, enabling emissions reductions and circular resource flows. A fundamental tool for the development of European policies to boost the market for sustainable, resilient and climate change adapted buildings. The objective of this study is to contribute to the existing body of knowledge in the field of sustainable building research, through the definition of strategies to adopt Level(s) for bringing buildings into the Circular Economy. For this reason, a triple SWOT-Analytical Hierarchy Process (AHP)-TOWS analysis was applied. The strengths, weaknesses, opportunities and threats (SWOT) of the Level(s) have been identified in relation to the availability of resources, product quality, internal and market structure, consumer perception, among others. The results obtained are conclusive in terms of the experts’ positive assessment of the tool; highlighting factors such as its response to the need to adapt buildings to climate change, its a standard reference language, and its use in multiple situations. However, several barriers have also been identified, which may affect its development, including its complexity of use, its lack of self-sufficiency, and its dependence the criteria used in each evaluation. Finally, the key strategies to be carried out for the implementation of the Levels have been established.

Abstract The study presents recent developments in the Turkish power market and introduces an Analytic Hierarchy Process model to evaluate and compare the relative overall attractiveness of power plant options for Turkey. The developed model incorporates technical characteristics, resource availability, socio-economic, environmental, cost, political, legal and organisational aspects, for evaluating and prioritising power plant types (biomass, coal, geothermal, hydro, natural gas, nuclear, petroleum, solar and wind). The study incorporates perspectives of different experts that represent various stakeholders of the Turkish power sector. The study reveals that supply reliability, investment costs and contribution to national economy are perceived as most important factors, whereas waste disposal and decommissioning costs are perceived as least important factors. Considering the overall weights, the most attractive power plant types for the Turkish power market are coal, hydro and natural gas power plants. The study indicates that Turkey should drastically decrease the installed capacity share of traditionally dominant power plants (to 58% from 89% in 2016) and fossil fuel power plants (to 40% from 56% in 2016), and increase the share of renewable power plants (to 52% from 44% in 2016), indigenous resource based power plants (to 67% from 56% in 2016) and nuclear power plants.

Abstract Smart agriculture aims at generating high harvest yields with an efficient resource management, such as the estimation of crop irrigation. One of the factors on which a productive crop irrigation depends on is evapotranspiration, defined as the water loss process from the soil. This is mainly measured by empirical equations, even though they are conditioned by the specific climatological variables they require. In recent years, data mining techniques are proposed as a powerful alternative to predict evapotranspiration. Among them, ensembles are notable in that they provide accurate estimators in different scenarios. Stacking is an ensemble-building technique aimed at strengthening the prediction capabilities of the system by the combined learning from the original features in the data and synthetic features created from the predictions of multiple models. This research proposes the usage of stacking for evapotranspiration prediction, which has been overlooked in the specialized literature, with the aim of a more sustainable management of water resources. The proposal is compared to other state-of-the-art empirical equations and data mining methods over several real-world climatological datasets of different agricultural areas in Spain. This comparison is performed considering separate datasets with features based on temperature, mass transfer, radiation and, finally, using the main meteorological variables together. The results obtained show that stacking is the best approach in all datasets and each group of features evaluated, running as good alternative to predict evapotranspiration when using data of a different nature and under different conditions.

Exotic annual grasses invasion across northern Great Basin rangelands has promoted a grass-fire cycle that threatens the sagebrush (Artemisia spp.) steppe ecosystem. In this sense, high accumulation rates and persistence of litter from annual species largely increase the amount and continuity of fine fuels. Here, we highlight the potential use and transferability of remote sensing-derived products to estimate litter biomass on sagebrush rangelands in southeastern Oregon, and link fire regime attributes (fire-free period) with litter biomass spatial patterns at the landscape scale. Every June, from 2018 to 2021, we measured litter biomass in 24 field plots (60 m × 60 m). Two remote sensing-derived datasets were used to predict litter biomass measured in the field plots. The first dataset used was the 30-m annual net primary production (NPP) product partitioned into plant functional traits (annual grass, perennial grass, shrub, and tree) from the Rangeland Analysis Platform (RAP). The second dataset included topographic variables (heat load index -HLI- and site exposure index -SEI-) computed from the USGS 30-m National Elevation Dataset. Through a frequentist model averaging approach (FMA), we determined that the NPP of annual and perennial grasses, as well as HLI and SEI, were important predictors of field-measured litter biomass in 2018, with the model featuring a high overall fit (R2 = 0.61). Model transferability based on extrapolating the FMA predictive relationships from 2018 to the following years provided similar overall fits (R2 ≈ 0.5). The fire-free period had a significant effect on the litter biomass accumulation on rangelands within the study site, with greater litter biomass in areas where the fire-free period was <10 years. Our findings suggest that the proposed remote sensing-derived products could be a key instrument to equip rangeland managers with additional information towards fuel management, fire management, and restoration efforts.

Road transportation is a significant source of CO2 emissions and energy demand. Conse-quently, initiatives are being promoted to decrease the sector's emissions and comply with the Paris agreement. This article synthesizes the available information about heavy-duty fuel cell trucks as their deployment needs to be considered a complementary solution to decreasing CO2 emissions alongside battery electric vehicles. A thorough evaluation of 95 relevant documents determines that the main research topics in the past ten years converge on public policies, hydrogen supply chain, environmental impact, drivetrain technology, fuel cell, and storage tank applications. The identified research gaps relate to expanding collaboration between institutions and governments in developing joint green macro policies focused on hydrogen heavy-duty trucks, scarce research about hydrogen production energy sources, low interest in documenting hydrogen pilot projects, and minimal involvement of logistic companies, which need to plan their diesel freight's conversion as soon as possible.

Abstract Lithium-ion batteries play an important role in the life quality of modern society as the dominant technology for use in portable electronic devices such as mobile phones, tablets and laptops. Beyond this application lithium-ion batteries are the preferred option for the emerging electric vehicle sector, while still underexploited in power supply systems, especially in combination with photovoltaics and wind power. As a technological component, lithium-ion batteries present huge global potential towards energy sustainability and substantial reductions in carbon emissions. A detailed review is presented herein on the state of the art and future perspectives of Li-ion batteries with emphasis on this potential.

Abstract In central European countries, district heating is a common and standard way to cover the residential heat demand. While the consumers are connected to the heat network and electricity grid, they are being increasingly encouraged to become prosumers by having own distributed renewable energy generation. At the same time, the energy performance requirements for new and renovated buildings are setting progressively higher energy efficiency standards. This tendency is effectively reducing the carbon footprint of the residential sector in Central Europe and will eventually lead to low and zero carbon buildings becoming the standard. One of the emerging technologies within this approach are Photovoltaic thermal hybrid solar collectors, which combine heat and power generation and are easy to integrate in buildings. In this study, the possibility to use such a system, supported by a heat pump, in a Central European multi-family house is addressed. Three configurations are considered; the building, the hybrid and district heating configuration. In the building configuration the heat from the solar collectors is used directly for domestic hot water and space heating and no use is made of excess heat. In the hybrid configuration, the direct heat consumption in the building is prioritized, while excess heat is exported to the district heating network. Finally, in the district heating configuration, the solar system operates as a micro-plant that supplies all produced heat to the district heating network. The study shows that the use of Photovoltaic thermal hybrid solar collectors in combination with district heating provides important benefits in terms of sustainability, energy security, carbon abatement and costs. Thereby, configurations that can export heat to the network have better energy efficiency and result more profitable.