Solar Radiation Hours Research Articles

Numerical and Design Study of Beehive in Building for Thermal Storage During Hours of Absence of Solar Radiation

This study investigates the numerical and design performance of Phase Change Materials (PCMs) embedded in a beehive structure within building envelopes for thermal energy storage during periods without solar radiation. Using Computational Fluid Dynamics (CFD) simulations in ANSYS Fluent, the study examines how the PCM system stabilizes indoor temperatures and improves energy efficiency. The research focuses on three months: January, November, and December, in Baghdad, Iraq, where diurnal solar radiation variations and temperature patterns are prevalent. Results reveal that the PCM-enhanced structure effectively absorbs heat during peak solar radiation hours, with solar radiation peaking at 574 W/m² in January, 596 W/m² in November, and 557 W/m² in December. The heat storage and release ability of the PCM keep up the interior temperature at its maximum of 309.96K and 310.04 K in Jan and Nov and 309.23 K in Dec with slightly less drop in the evening. The heat transfer coefficient was maximum in November 11.37 W/m²·K, while the PCM mass fractions showed significant phase change and the maximum value 0.425 in November. The thermal efficiency of the system was highest in November at 68.23% and also fluctuates slightly in the other remaining months. This study suggests that PCM systems, especially with the beehive structure, additionally improve isothermal stability and energy densities of the buildings in the changing climate, which is cost-effective and a more environmentally friendly strategy for regulating heating and cooling requirements.

Properties of foam concrete containing phase change material impregnated pumice

Energy consumption rises as a result of numerous electrical devices used to maintain thermal comfort of interior building areas. Using building materials with low thermal conductivity and density as well as an effective thermal energy storage plan can help to mitigate this. In order to enhance thermal performance of building, phase change material (PCM) was incorporated to foam concrete mixture in this study. Capric acid (CA)-palmitic acid (PA) eutectic mixture was prepared and impregnated with pumice (50 % by weight), a light and porous material. DSC results indicated that pumice/CA-PA composite exhibited a melting temperature of 22.84˚C and a freezing temperature of 20.85˚C, with corresponding enthalpy values for melting and freezing determined to be 85.4 J/g and 85.1 J/g, respectively. TGA analyses demonstrated that operational temperature of pumice/CA-PA composite was significantly below its thermal degradation temperature (194˚C). The prepared pumice/CA-PA composites were replaced with silica aggregate at different rates and incorporated in foam concrete mixture. Porosity and water absorption values rose as pumice/PCM content increased, yet there was a 7.2–41.1 % drop in dry unit weight when compared to reference. Compressive strength also showed a linear decrease and the lowest compressive strength value was recorded as 4.71 MPa in the presence of 40 % pumice/PCM. Thermal conductivity dropped from 0.487 W/mK to 0.167 W/mK, suggesting that foam concrete samples that were produced are all suitable as insulation materials. In peak solar radiation hours, PCM-impregnated pumice foam concrete (PFC) provided about 11.8 % and 8.72 % surface and room center temperatures compared to that of the reference in maximum case. PFC with PCM provided 6.54 % warmer surface temperature in cold weather. PFC-PCM can provide a cooler indoor temperature during peak temperature hours. Therefore, it may have a great potential to decrease the cooling load of a building.

A novel hybrid passive cooling system for providing thermal comfort conditions and reducing energy consumption in buildings in hot climates

In the present study, the performance of a novel hybrid passive cooling system was studied analytically and numerically in terms of its ability to achieve thermal comfort conditions, produce electricity, and reduce energy consumption. The new hybrid system that has been proposed in this study consists of a photovoltaic solar chimney (SC-PV) system, which in turn consists of a solar chimney (SC) combined with photovoltaic panels (PV). An underground space (UGS) system connects to the photovoltaic solar chimney (SC-PV) system through a residential room. This novel hybrid system is a completely new passive cooling system that is called SC-PV-UGS in the present study. The present system's performance has been studied in hot and moderate climates. The results indicated that the SC-PV-UGS system can provide thermal comfort conditions for the room's residents. The total electricity produced during the hours of solar radiation for the three test days in the hot climate was 310 kWh, while it was 329 kWh in the moderate climate. The total annual electricity produced by the SC-PV-UGS system for the hot climate was 2024 kWh, and for the moderate climate, it was 2318 kWh. The total cooling demand in a hot climate was reduced to 339 kWh, which is 55.9 % of the total cooling demand of the conventional non-passive system.

A case study on single basin solar still augmented with wax filled metallic cylinders

This experimental study introduces a novel approach to enhancing solar still performance through the integration of wax-filled rods, marking a significant advancement in solar desalination technology. These rods, innovatively designed to absorb and store both sensible and latent heat during peak solar radiation hours, release this stored energy gradually, particularly during the evening and night. This unique mechanism results in a notable and consistent increase in water temperature within the modified solar still after 17:00, setting it apart from conventional models. The study's findings reveal that the modified solar still achieves a 12.8 % higher cumulative distillate yield and a 16.3 % increase in efficiency compared to traditional solar stills. Furthermore, this enhancement translates into a 6.3 % reduction in distillate production costs, underscoring the economic viability and superior performance of the modified design.

Enhanced water production and improving solar water distillation efficiency of double-slope solar stills: Modeling and validation

Solar distillation is a promising technology for producing clean water using renewable energy, especially in regions with water scarcity and contamination. This study investigates the impact of design modifications on the efficiency of a double-slope solar still coupled with evacuated tubes and external reflectors. Using Matlab software analysis, key findings indicate that packing factors, temperature control, and solar radiation exposure all contribute to the system’s optimal performance. Solar radiation levels directly correlate with production rates, emphasizing the need for effective sunlight exposure. The system’s ability to rely on stored heat at night enhances its practicality. This study shows how to make solar stills more efficient at producing clean water. It is found that the best way to do this is to use PV cells with a packing factor of 0.25. A packing factor of 0.25 outperforms other factors, significantly increasing water production and system efficiency. With this optimal factor, the system achieved a remarkable thermal efficiency of 83.5 % and a maximum daily production of 19 L per square meter during peak solar radiation hours. The system’s overall efficiency is 94 % increased by 13 % over the highest value recorded in previous studies. Furthermore, the system’s productivity increased by 40 % from the highest value recorded in previous studies. The amount of electrical energy produced is directly proportional to the packing factor, by the power of 41.1 W-hours (Wh) at a PV cell with a packing factor of 0.25.

Optimization of power dispatching schedule of a charging station based on a micro grid with a photovoltaic module

The world is on a course toward total electrification of vehicles. In the near future, most vehicles will run on electric power. One of the main reasons for users' dissatisfaction with electric vehicles is the lack of public direct current charging stations. Since electric vehicles charging can cause an additional increase in peak load on the grid, the optimal solution is direct current charging stations with photovoltaic generation with a micro grid architecture. If the charging station has a connection to the public grid, then, provided that the solar energy and storage system are optimally utilized, the station aggregator's profit can be increased by selling excess energy to the grid. This paper analyzes the charging habits of customers at direct current charging stations. It was found that the peak demand for charging is observed around 9:00 and 14:00-17:00, the same time as the general peak load on the grid. Thus, the peak charging demand coincides with the peak grid load and increases the net peak of the system. However, this excess demand on the system in the form of charging load can be met by the installed solar photovoltaic system, as the output power of the photovoltaic system is sufficient to meet the charging demand during the peak hours of solar radiation. Thus, for the considered direct current charging station, the optimization problem of dynamic economic dispatch was formulated, since the generation and load schedules change over time. The goal of optimization is to minimize the cost of primary energy. This problem, formalized as a mixed integer linear programming problem, was solved using the interior-point solver of the GEKKO library in Python. Four scenarios for the operation of the station were worked out, in summer and winter, with a fixed and dynamic electricity tariff. According to the results of the study, it was found that in the conditions of a fixed tariff in the summer, the cost of primary energy can be reduced 2.5 times, in fact, increase profits, thanks to the sale of electricity to the public grid. In winter, the use of the optimization algorithm of the station will provide an insignificant cost savings due to low photovoltaic generation. Under the conditions of a dynamic tariff that corresponds to the prices on the day-ahead market, using the optimization algorithm, it was found that for this experimental variant of the station's operation, the maximum profit in summer will be 207.60 UAH, while in winter the cost of primary energy will be 177.47 UAH. The results obtained indicate that the operation of a charging station under dynamic tariffs in the day-ahead market in Ukraine is a promising direction for the development of charging infrastructure in the country and proves the possibility of efficient use of renewable energy sources. Thus, this paper analyzes the global experience of developing charging stations based on micro grids, the integration of renewable energy sources into them, and approaches to building electricity dispatch schedules. The financial feasibility of the station's operation in the context of the electricity market in Ukraine was also investigated

A Dual-Stage Solar Power Prediction Model That Reflects Uncertainties in Weather Forecasts

Renewable energy sources are being expanded globally in response to global warming. Solar power generation is closely related to solar radiation and typically experiences significant fluctuations in solar radiation hours during periods of high solar radiation, leading to substantial inaccuracies in power generation predictions. In this paper, we suggest a solar power generation prediction method aimed at minimizing prediction errors during solar time. The proposed method comprises two stages. The first stage is the construction of the Solar Base Model by extracting characteristics from input variables. In the second stage, the prediction error period is detected using the Solar Change Point, which measures the difference between the predicted output from the Solar Base Model and the actual power generation. Subsequently, the probability of a weather forecast state change within the error occurrence period is calculated, and this information is used to update the power generation forecast value. The performance evaluation was restricted to July and August. The average improvement rate in predicted power generation was 24.5%. Using the proposed model, updates to weather forecast status information were implemented, leading to enhanced accuracy in predicting solar power generation.

Efficacy of natural circulation loop based parabolic trough collector- An analytical approach

ABSTRACT Realizing the importance of the natural circulation loop (NCL), which is a passive heat transport device, an analytical study is undertaken to demonstrate the functioning of an NCL-based parabolic trough collector (PTC). Multiple validated analytical models were incorporated to evaluate the system performance. The parametric study involved variations in loop height, loop length, and solar radiation. The loop flow rate enhances by increasing its height or the receiver length. At maximum radiation, 1.3 kg/s flow rate was observed for loop geometry of 5 m height and 7.8 m length against 0.79 kg/s for 1 m height. The flow rate predicted for a 10 m length and 1 m height loop was 0.87 kg/s. Since instability rises with height and heat loss and receiver temperature increase with receiver length, a trade-off between the two is necessary to function NCL-based PTC properly. Otherside, though the higher heat output with an increase in the receiver length is evident, a noticeable drop in thermal efficiency (≈7%) during the peak hours of solar radiation is a matter of concern. Further, the outlet temperature was not affected by the loop height for the defined flow condition of the process fluid. Like in conventional PTC systems, the process fluid’s exit temperature or flow rate can also be maintained constant during a day operation by varying the flow condition. The proposed model can deliver ≈ 1500 liters of hot water in six hours with an average 68% thermal efficiency without external power, in contrast to the necessity of notable pumping power and associated overhead charges in conventional PTC. Further, the system’s stability was predicted using linear stability analysis, and stability maps were generated for different loop heights and found that as the loop height decreases, the unstable zone diminishes. Though the steady-state data points are in the unstable flow region, stable operation is expected by incorporating pertinent instability restraining technique, that is, loop tilt.

Experimental Thermal Performance of Phase Change Material Embedded Solar Air Heater Employing Impinging Stable Air Jet Array Presenting High Power and Energy Density

Abstract This experimental thermal performance investigation presents that the hot air at a significantly high temperature, and simultaneously at high power density and energy density of phase change material (PCM) can be obtained utilizing a novel design of PCM embedded solar air heater employing impinging stable air jet array. Investigation is carried out following two main objectives, i.e., to obtain (i) instant and (ii) long thermal backups. In the reported design configuration, impinging stable air jets on absorber plate are obtained by reducing the flow path of expelled air from upstream air jets that increased the heat transfer rate to air and consequently instant thermal backup. Although, the use of wavy PCM unit provides instant and long thermal backup by increasing heat transfer area that augments the heat transfer to air and the collection of solar radiations, respectively. Moreover, the present study is extended as follows, (i) the use of shutter on glass cover to increase thermal performance during nocturnal hours, (ii) charging of PCM till the maximum solar radiation hours and use of the stored energy during nocturnal hours, (iii) thermal performance analysis to reveal instant thermal backup, (iv) thermal performance investigation during variable weather conditions, and (v) thermal performance investigation for low ambient air temperature. The obtained results revealed that for the unit collector area, significant thermal backup of about 6 h at a temperature rise of ≥5 °C can be obtained by utilizing the above-mentioned provisions in this research.

Improving the Indoor Environment through an Indoor Green Curtain System

People are spending more and more of their lives indoors, making thermal comfort and air quality essential factors for their health and well-being. The use of natural elements within indoor spaces can improve the indoor environment and air quality, but can also bring multiple health and well-being, psychological, cognitive, and behavioral benefits due to its biophilic effect. Indoor vertical greenery strategy in buildings can give these benefits to the building occupants. In this study, a prototype of a living green curtain is assessed to evaluate the benefits that may derive when used as a shading device. The analysis evaluated the performance of the green curtain prototype compared to the other two scenarios, no curtains (control module) and external blind. Temperature, relative humidity, air quality, and solar radiation were measured in the indoor environment. Results indicate that the green curtain module was cooler by 0–4 °C than the control module during the peak solar radiation hours, and the difference even reached up to 8 °C on hotter days. Due to the evapotranspiration effect, the green curtain recorded the highest daily average relative humidity of 67%. This study demonstrates the potential ability of a green curtain to improve air quality and thermal comfort.

A Reinforcement Learning Approach for Integrating an Intelligent Home Energy Management System with a Vehicle-to-Home Unit

These days, users consume more electricity during peak hours, and electricity prices are typically higher between 3:00 p.m. and 11:00 p.m. If electric vehicle (EV) charging occurs during the same hours, the impact on residential distribution networks increases. Thus, home energy management systems (HEMS) have been introduced to manage the energy demand among households and EVs in residential distribution networks, such as a smart micro-grid (MG). Moreover, HEMS can efficiently manage renewable energy sources, such as solar photovoltaic (PV) panels, wind turbines, and vehicle energy storage. Until now, no HEMS has intelligently coordinated the uncertainty of smart MG elements. This paper investigated the impact of PV solar power, MG storage, and EVs on the maximum solar radiation hours. Several deep learning (DL) algorithms were utilized to account for the uncertainties. A reinforcement learning home centralized photovoltaic (RL-HCPV) scheduling algorithm was developed to manage the energy demand between the smart MG elements. The RL-HCPV system was modelled according to several constraints to meet household electricity demands in sunny and cloudy weather. Additionally, simulations demonstrated how the proposed RL-HCPV system could incorporate uncertainty, and efficiently handle the demand response and how vehicle-to-home (V2H) can help to level the appliance load profile and reduce power consumption costs with sustainable power production. The results demonstrated the advantages of utilizing RL and V2H technology as potential smart building storage technology.

Thermal Assessment of a Ventilated Double Skin Façade Component with a Set of Air Filtering Photocatalytic Slats in the Cavity

Indoor air quality is a crucial factor when evaluating habitability, especially in developed countries, where people spend most of their time indoors. This paper presents a novel double skin façade (DSF) system that combines physical and photocatalytic filtering strategies. The air purification system is made up of fixed slats that are both solar protection and air purification system. The objective of this work is to determine the thermal behaviour of the proposed system, so that its suitability for use in various environments may be assessed. This was carried out using a physical 1:1 scale model and a computational fluid dynamics (CFD) model. The maximum temperature inside the scale model cavity was 17–20 °C higher than outdoor air. Additionally, it was discovered that the airflow through the DSF would require forced ventilation. To determine the emissivity values of the photocatalytic coating, additional experimental measurements were made. The CFD model was tested for summer and winter conditions in Barcelona, Chicago, and Vancouver. The average increase in the intake air temperature was around 14.5 °C in winter and 12 °C in summer, finding that the system has its main use potential in temperate or cold areas with many hours of solar radiation.

Revolutionizing Oman's energy network with an optimal mixture renewable energy source

<abstract> <p>The electricity demand has increased to 240% during the last decade in the Sultanate of Oman due to population growth and industrial expansion. Solar energy can act as an alternate source of energy production to meet the surge in demand for electric power. Also, the government has planned to derive 30% of the electricity from renewables by 2030. Moreover, agreements have been made to reduce greenhouse gas (GHG) emissions by decreasing 7% by 2030. The main objective of this paper is to design a grid-connected PV solar system based on the real-time data collected from the location called Nizwa, Oman using Hybrid Optimization of Multiple Electric Renewables (HOMER) software. The real-time data of average high and low temperature, solar radiation, estimated monthly average daily sunshine and peak hours of solar radiation of Nizwa has been collected from Meteorological Office Oman for January to December 2022. Nizwa recorded a temperature max of 43 ℃ during summer and 12 ℃ in January. Daily sun radiation in July averages between 5,500 and 6,000 Wh/m<sup>2</sup>, and the average sunshine is 9 hours per day at the selected project area (Nizwa). The collected data has been analyzed and designed using HOMER software. HOMER is used to model, optimize and analyze an integrated energy system that primarily utilizes renewable and non-conventional resources for both grid connected and autonomous systems. A 9-kW grid-connected PV solar panel has been designed and implemented in the proposed system. The proposed PV solar system worked perfectly and gave the results of an estimated number of hours of operation to be 4,362 hrs/year; the cost of energy per kilowatt is ＄ 0.044 and the annual energy saving cost of the hybrid system is ＄ 173.696. For the environmental feasibility of producing 14,765 kWh/yr, carbon dioxide emissions have decreased from 7,230,440 g to 4,396.001 g, with a difference of 7,226,043.9 g of carbon dioxide.</p> </abstract>

Investigation of Solar Energy Potential and PV-Outputs in Rural and Desert Areas: Case Study Egypt

This study aims to identify the best strategic sites in Egypt available to build the PV systems needed to support required electricity to the country and the desert areas, in addition to deduce the total monthly, annual electricity budget and their generation costs. Egypt has a high solar energy potential which is crucial for sustainable development, as it receives 3450 hours of solar radiation (SR) throughout the year with a high intensity ranged from 8.5KWh/m2/d in southwest part to 2.1 KWh/m2/d at the north coast. The observed SR at four stations (Asyut, Aswan, Kharga, Cairo) were used to assess the accuracy of the ERA5 reanalysis dataset. Moreover, seven strategic sites were chosen across the country including the Western Desert (El-Golf, Habatta, and Sewa), the Eastern Desert (Saffaga, Shiab-Elbanat), and the Sinai Peninsula (El-Agma and El-Arish) to identify the most suitable stations for the construction of PV systems. Three different types of PV cells with different efficiency (η1=19.1%, η2=22.6% and η3=22.4 %) were utilized to compute the energy that could be generated at the lowest cost at the seven selected sites across Egypt. The results showed that the monthly total cost from η1 was 0.011 $/W during June and exceeded 0.015 $/W in December, while the annual total costs are ranged from 0.0119 $/W in El-Golf and 0.01494 $/W in El-Arish. Also, the result for η2 was ranged from 0.01$/W to 0.026 over El-Golf and Shiab-Elbanat, while the last cell η3 was recorded high cost over all sites but gives more energy. Finally, it is concluded that El-Golf, Shiab-Elbanat, and Saffaga are the best three sites with the lowest coast for building a PV system followed by Habatta and El-Agma, while the energy generation costs at both El-Arish and Sewa were the highest.

Determination of the Appropriate Number of Photovoltaic Panels for Microgeneration and Self-supply of Final Consumers by Energy Production Estimation via Fuzzy Logic

A method is presented to determine the appropriate number of photovoltaic panels that should be installed in an end-user photovoltaic installation to guarantee the supply of energy to the load during the hours of solar radiation, according to factors such as the installation area and global solar radiation. Solar radiation is predicted by approximating the daily distribution of global irradiance through a Gaussian function, which is subsequently corrected using a heuristic approach. Meteorological parameters are used as input data such as the daily solar insolation and the maximum global irradiance for each day; this last parameter is obtained through an expert system based on fuzzy logic that was programmed and trained with the data of ambient temperature and relative humidity that were obtained in the processing stage. Output from this expert system is the predicted values of maximum radiation obtained for each day for a selectable time interval. With the predicted solar radiation, the generation of electrical energy from the photovoltaic panels is calculated. The load is randomly modeled from a pattern of the energy demand of the building to be powered by the photovoltaic system. The number of photovoltaic panels needed is found with the information acquired in the previous stages and the information of the energy demand of the load and the installation area. The results are the number of solar panels that would be needed at all hours of the day from which the radiation prediction was made.

The effect of using phase change materials in a solar wall on the number of times of air conditioning per hour during day and night in different thicknesses of the solar wall

In this paper, the effect of using PCM in a solar wall is investigated numerically and analytically. For this purpose, a solar wall with a room in both PCM and PCM-free modes is simulated in the solar wall. The effective heat capacity method has been used to simulate the PCM melting process. The effect of using PCM in the solar wall in different heat fluxes, different wall thicknesses, average room temperature, etc. on the number of times of natural air conditioning in the room has been investigated. This analysis is performed as a transition for a full day. For this purpose, a handwritten code with COMSOL software has been used. The results of this study showed that storing solar energy in PCM as latent melting energy can provide 24-h ventilation in the room. This is also possible for small solar fluxes. Also, the use of PCM in the wall can significantly reduce the wall thickness. The results also show that the use of PCM with higher thermal conductivity increases the number of times of air conditioning. The highest number of air conditionings per hour occurred during the peak hours of solar radiation.

A Techno-Economic Analysis of Parabolic Trough Collector (PTC) and Solar Power Tower (SPT) as Solar Energy in Malaysia

Malaysia receives an annual average of 2200 hours of solar radiation, making her abundant renewable resources to generate electricity. Thus, a good planning is required to manage the resources efficiently and to utilize the abundant resources fully. Concentrating solar power (CSP) technology is a possible approach to manage renewable resources in Malaysia. Using a techno-economic analysis, the researchers, engineers, industries, or government agencies will be able to identify contributing and discouraging factors of building the CSP technology. This paper presents a techno-economic analysis of two CSP technology: parabolic trough collector (PTC) and solar power tower (SPT), for potential implementation in Malaysia. This paper provides information on two CSP technologies to researchers and industries prior to the planning and design stages. The techno-economic analysis begins with identifying potential locations based on the direct normal irradiation (DNI). Kuah, Kuantan, Miri and Labuan are identified as the potential locations using the RETScreen Expert software. Labuan could be the most promising PTC and SPT technology project because it has the highest DNI received annually. Next, the techno-economic analysis uses two reference projects, ANDASOL-1 and PS-10 systems in Spain, as references for all locations. The techno-economic analysis consists of annual electricity generation, unit cost of electricity, net Present Value (NPV), benefit-to-cost ratio (B/C), internal rate of return (IRR), and payback period calculated in Microsoft Excel. Finally, a sensitivity analysis is conducted to measure the impact of uncertainties of one or more input variables, leading to uncertainties on the output variables. Two sensitive factors are the annual electricity generation and the initial cost, affecting the construction, installation, and implementation of PTC or SPT technology.

Benchmarking urban local weather with long-term monitoring compared with weather datasets from climate station and EnergyPlus weather (EPW) data

Weather is essential for building energy simulation and energy efficient retrofitting since building energy use is highly weather-dependent. Weather data provided by EnergyPlus weather (EPW) data or generated by urban climate stations are used in most simulation tools. However, weather varies temporally and spatially, and the gaps may exist in the typical-year weather, weather from peri-urban areas, and local actual weather. This paper compares three types of weather datasets, from EPW data, from an urban climate station (STATION), and from long-term measurement with a local micro-climate station at Southeast University (SEU) campus. Results show there are significant gaps between the three weather datasets and compared with the STATION and EPW data, the average temperature in the micro-climate (SEU) is higher by 1.2 °C and 2.2 °C, respectively. The cooling degree day in SEU weather data is 20.4% and 40.8% higher, with heating degree day 15.7% and 26.3% lower. Comparing average relative humidity shows a big difference of 18.3% and 22.1% between SEU, STATION and EPW, and the former is comparatively lower than the latter two and no clear correlated trend. The SEU weather data has 23.1% more solar radiation hours than STATION weather data. As for wind speed, the average wind speed in the SEU weather data is lower by 1.14m/s and 1.29m/s, respectively, when compared with the STATION and EPW data. This study could be the reference for different trials for energy performance dynamic simulation for building energy analysis.

Effects of air pollution and climatology on COVID-19 mortality in Spain.

The health, economic, and social impact of COVID-19 has been significant across the world. Our objective was to evaluate the association between air pollution (through NO2 and PM2.5 levels) and COVID-19 mortality in Spanish provinces from February 3, 2020, to July 14, 2020, adjusting for climatic parameters. An observational and ecological study was conducted with information extracted from Datadista repository (Datadista, 2020). Air pollutants (NO2 and PM2.5 levels) were analyzed as potential determinants of COVID-19 mortality. Multilevel Poisson regression models were used to analyze the risk of mortality after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Models were adjusted by four climatic variables (hours of solar radiation, precipitation, daily temperature and wind speed) and population size. The mean levels of PM2.5 and NO2 across all provinces and time in Spain were 8.7 μg/m3 (SD 9.7) and 8.7 μg/m3 (SD 6.2), respectively. High levels of PM2.5 (IRR = 1.016, 95% CI: 1.007–1.026), NO2 (IRR = 1.066, 95% CI: 1.058–1.075) and precipitation (IRRNO2 = 0.989, 95% CI: 0.981–0.997) were positively associated with COVID-19 mortality, whereas temperature (IRRPM2.5 = 0.988, 95% CI: 0.976–1.000; and IRRNO2 = 0.771, 95% CI: 0.761–0.782, respectively) and wind speed (IRRNO2 = 1.095, 95% CI: 1.061–1.131) were negatively associated with COVID-19 mortality. Air pollution can be a key factor to understand the mortality rate for COVID-19 in Spain. Furthermore, climatic variables could be influencing COVID-19 progression. Thus, air pollution and climatology ought to be taken into consideration in order to control the pandemic.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11869-021-01062-2.

Evaluation of the cost-effectiveness of grid-connected photovoltaic solar energy in wineries

The objective of this study was to analyze the cost-effectiveness of photovoltaic (PV) solar energy in wineries. The factors analysed were solar radiation, cost of PV installation, prices in the public electricity grid, size of the winery, power of installed panels, influence of the decreased consumption during weekends, and seasonality in the consumption. The study has been based on the European TESLA project, in which 39 energy audits were carried out in wineries in four European countries. A winery of 30,000 hL/year was characterized as a representative winery. The results showed that seasonality was key in the profitability of the system for self-consumption, related to the optimum power to be installed of PV. It was recommended to install, as an optimal PV power, the stable electrical power that is demanded in the daytime period. Optimizing the installed power of PV panels in the representative winery, the percentage of electrical energy consumption covered by photovoltaic energy varied between 16% and 22%. The percentage of the cost of electric energy covered varied between 18% and 24%, with payback values between 18 years (3.1 peak sun hours of solar radiation -PSH) and 10 years (5.6 peak sun hours of solar radiation - PSH). All the factors involved were analyzed.