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As a relatively mature technology, biomass molded fuel (BMF) is widely used in distributed and centralized heating in China and has received considerable government attention. Although many BFM incentive policies have been developed, decreased domestic traditional fuel prices in China have caused BMF to lose its economic viability and new policy recommendations are needed to stimulate this industry. The present study built a regionalized net present value (NPV) model based on real production process simulation to test the impacts of each policy factor. The calculations showed that BMF production costs vary remarkably between regions, with the cost of agricultural briquette fuel (ABF) ranging from 86 US dollar per metric ton (USD/t) to 110 (USD/t), while that of woody pellet fuel (WPF) varies from 122 USD/t to 154 USD/t. The largest part of BMF’s cost composition is feedstock, which accounts for up 50%–60% of the total; accordingly a feedstock subsidy is the most effective policy factor, but in consideration of policy implementation, it would be better to use a production subsidy. For ABF, the optimal product subsidy varies from 26 USD/t to 57 USD/t among different regions of China, while for WPF, the range is 36 USD/t to 75 USD/t. Based on the data, a regional BMF development strategy is also proposed in this study.

The decarbonisation of heating in the United Kingdom is likely to entail both the mass adoption of heat pumps and widespread development of district heating infrastructure. Estimation of the spatially disaggregated heat demand is needed for both electrical distribution network with electrified heating and for the development of district heating. The temporal variation of heat demand is important when considering the operation of district heating, thermal energy storage and electrical grid storage. The difference between the national and urban heat demands profiles will vary due to the type and occupancy of buildings leading to temporal variations which have not been widely surveyed. This paper develops a high-resolution spatiotemporal heat load model for Great Britain (GB: England, Scotland a Wales) by identifying the appropriate datasets, archetype segmentation and characterisation for the domestic and nondomestic building stock. This is applied to a thermal model and calibrated on the local scale using gas consumption statistics. The annual GB heat demand was in close agreement with other estimates and the peak demand was 219 GWth. The urban heat demand was found to have a lower peak to trough ratio than the average national demand profile. This will have important implications for the uptake of heating technologies and design of district heating.

Shading the greenhouses is necessary in summer to reduce the solar radiation load. This however generates a considerable amount of thermal radiation heat load that needs to be removed via cooling systems. This study aimed to evaluate the effect of different shading configurations on the solar and thermal radiation in a greenhouse. Nets at four different locations were employed to shade the roof and side-walls of a polycarbonate, mechanically ventilated greenhouse. The spectral radiative properties of all these plastic materials were measured in short and long wave spectrum bands. The net solar and thermal radiations and air temperature were measured outside and inside two identical shaded and unshaded greenhouses. The results showed that external roof-shading is desirable, as it reduced the generated thermal radiation in the greenhouse by 21% and 15% during the day and night time, respectively and reduced the greenhouse air temperature during the day. The internal shading (roof and side walls) is undesirable, since it drastically increased the generated thermal radiation in the greenhouse by 147% and strongly increased the greenhouse air temperature during the day. Shading the side-walls is not recommended because it significantly reduces the transmitted solar radiation in the morning and afternoon (when the outside irradiance is low) and is useless at around noon when the outside irradiance is extremely high.

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.

Deployment of photovoltaic (PV) systems has recently been encouraged for large-scale and small-scale businesses in order to meet the global green energy targets. However, one of the most significant hurdles that limits the spread of PV applications is the dust accumulated on the PV panels’ surfaces, especially in desert regions. Numerous studies sought the use of cameras, sensors, power datasets, and other detection elements to detect the dust on PV panels; however, these methods pose more maintenance, accuracy, and economic challenges. Therefore, this paper proposes an intelligent system to detect the dust level on the PV panels to optimally operate the attached dust cleaning units (DCUs). Unlike previous strategies, this study utilizes the expanded knowledge and collected data for solar irradiation and PV-generated power, along with the forecasted ambient temperature. An expert artificial intelligence (AI) computational system, adopted with the MATLAB platform, is utilized for a high level of data prediction and processing. The AI was used in this study in order to estimate the unprovided information, emulate the provided measurements, and accommodate more input/output data. The feasibility of the proposed system is investigated using actual field data during all possible weather conditions.

This research focuses on improving the photoelectrochemical performance of binary heterostructure Ag2S/ZnO NRs/ITO by manipulating synthesis conditions, particularly the concentrations of sliver nitrate AgNO3 and thiourea CS(NH2)2. The photoelectrochemical performance of Ag2S/ZnO nanorods on indium tin oxide (ITO) nanocomposite was compared to pristine ZnO NRs/ITO photoanode. The hydrothermal technique, an eco-friendly, low-cost method, was used to successfully produce Ag2S/ZnO NRs at different concentrations of AgNO3 and CS(NH2)2. The obtained thin films were characterized using field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), ultraviolet-visible spectroscopy (UV-vis), and photoelectrochemical studies (PECs). We observed that there was an enhancement in absorbance in the visible region and effective photoelectron transfer between the Ag2S/ZnO NRs/ITO photoelectrode and the electrolyte Red-Ox when illuminated with 100 mW cm−2. Increasing the concentration of AgNO3 caused a remarkable decrease in the optical bandgap energy (Eg) values. However, we noticed that there was an unstable trend in Eg when the concentration of CS(NH2)2 was adjusted. The photoelectrochemical studies revealed that at a bias of 1.0 V, and 0.005 M of AgNO3 and 0.03 M of CS(NH2)2, the maximum photocurrent of the Ag2S/ZnO NRs/ITO photoanode was 3.97 mA/cm2, which is almost 11 times that of plain ZnO nanorods. Based on the outcomes of this investigating, the Ag2S/ZnO NRs/ITO photoanode is proposed as a viable alternative photoanode in photoelectrochemical applications.

Freshwater scarcity is a significant concern due to climate change in some regions of Brazil; likewise, evaporation rates have increased over the years. Floating photovoltaic systems can reduce water evaporation from reservoirs by suppressing the evaporating area on the water surface. This work evaluated the effects of floating photovoltaic systems on water evaporation rates in the Passaúna Reservoir, southeastern Brazil. Meteorological data such as temperature, humidity, wind speed, and solar radiation were used to estimate the rate of water evaporation using FAO Penman–Monteith, Linacre, Hargreaves–Samani, Rohwer, and Valiantzas methods. The methods were tested with the Kruskal–Wallis test, including measured evaporation from the nearest meteorological station to determine whether there were significant differences between the medians of the methods considering a 95% confidence level for hypothesis testing. All methods differed from the standard method recommended by the FAO Penman–Monteith. Simulations with more extensive coverage areas of the floating photovoltaic system were carried out to verify the relationship between the surface water coverage area and the evaporation reduction efficiency provided by the system and to obtain the avoided water evaporation volume. For the floating photovoltaic system with a coverage area of 1265.14 m2, an efficiency of 60.20% was obtained in reducing water evaporation; future expansions of the FPS were simulated with coverage areas corresponding to energy production capacities of 1 MWp, 2.5 MWp, and 5 MWp. The results indicated that for a floating photovoltaic system coverage area corresponding to 5 MWp of energy production capacity, the saved water volume would be enough to supply over 196 people for a year. More significant areas, such as covering up the entire available surface area of the Passaúna reservoir with a floating photovoltaic system, could save up to 2.69 hm3 of water volume annually, representing a more significant value for the public management of water resources.

The increasing demand for energy and commodities has led to escalating greenhouse gas emissions, the chief of which is represented by carbon dioxide (CO2). Blue hydrogen (H2), a low-carbon hydrogen produced from natural gas with carbon capture technologies applied, has been suggested as a possible alternative to fossil fuels in processes with hard-to-abate emission sources, including refining, chemical, petrochemical and transport sectors. Due to the recent international directives aimed to combat climate change, even existing hydrogen plants should be retrofitted with carbon capture units. To optimize the process economics of such retrofit, it has been proposed to remove CO2 from the pressure swing adsorption (PSA) tail gas to exploit the relatively high CO2 concentration. This study aimed to design and numerically investigate a vacuum pressure swing adsorption (VPSA) process capable of capturing CO2 from the PSA tail gas of an industrial steam methane reforming (SMR)-based hydrogen plant using NaX zeolite adsorbent. The effect of operating conditions, such as purge-to-feed ratio and desorption pressure, were evaluated in relation to CO2 purity, CO2 recovery, bed productivity and specific energy consumption. We found that conventional cycle configurations, namely a 2-bed, 4-step Skarstrom cycle and a 2-bed, 6-step modified Skarstrom cycle with pressure equalization, were able to concentrate CO2 to a purity greater than 95% with a CO2 recovery of around 77% and 90%, respectively. Therefore, the latter configuration could serve as an efficient process to decarbonize existing hydrogen plants and produce blue H2.