Global Radiation Research Articles

Short-term global horizontal irradiance forecasting using weather classified categorical boosting

Accurate short-term solar irradiance (SI) forecasting is crucial for renewable energy integration to ensure unit commitment and economic load dispatch. However, hourly SI prediction is very challenging due to atmospheric conditions and weather fluctuations. This study proposes a hybrid approach using weather classification and boosting algorithms for short-term global horizontal irradiance (GHI) forecasting. In data pre-processing steps, we employ random forest for feature selection and K-means clustering for weather classification. The weather-based clustered data is used for the model training using categorical boosting (CatBoost). The proposed weather-classified categorical boosting (WC-CB) scheme is compared with benchmarks in literature like adaptive boosting (AdaBoost), bi-directional long short-term memory (BiLSTM) and gated recurrent unit (GRU) using datasets from two distinct geographical locations obtained from the National Solar Radiation Database (NSRDB). The results show that the proposed WC-CB hybrid approach has lower forecast errors compared to conventional CatBoost modelling. The error reduction of 16% and 39% in root mean square error and 6% and 9% in mean absolute error is recorded for the two datasets, respectively. These findings demonstrate the importance of weather classification in improving forecasting accuracy with potential implications for broader renewable energy applications.

Green hydrogen production from photovoltaic power station as a road map to climate change mitigation

Abstract The increasing recognition of hydrogen as a critical element in the global net-zero transition and its clear role in decarbonizing challenging sectors coincide with the growing urgency to address climate change. Africa's favourable renewable-energy capacity, ranging from 28% to 36% for solar, has been reported by the global solar irradiance index. However, the majority of hydrogen production today relies on fossil fuels (96%), with only a small fraction (4%) being produced through water electrolysis. Even though there have been many studies on climate change mitigation with a focus on Africa, a green hydrogen production from a photovoltaic power station approach has not been reported. Also, literature with a focus on Nigeria is lacking. This study focuses on the African green hydrogen production industry, utilizing Nigeria as a case study to explore the feasibility of generating clean hydrogen vectors from a percentage of photovoltaic power output in various regions of the country through stand-alone solar grid electrification projects. Analyses of the usage and effectiveness of the produced hydrogen fuel in each region are carried out, with the highest region having an annual output of 12 247 278 kg of green hydrogen and 8 573 094 kg of ammonia and the lowest region having an output of 511 245 kg of green hydrogen and 357 871 kg of ammonia, and the expected production from the proposed usage of 50% of the power generation output of the installed 1.6-MWp and 80-kWp solar power minigrids in the regions is calculated. The analyses were repeated for the other considered regions in the country. The results showcased the enormous advantages of the electrolytic production of hydrogen and how the greener economy project can play a major role in mitigating climate change effects and overreliance on fossil fuels as the driver of the economy in many African countries.

Light absorption properties and source contributions of black and brown carbon in Guangxi, southern China

Black carbon (BC) and brown carbon aerosols (BrC) are primary light-absorbing carbonaceous aerosols that significantly influence the global and regional radiation balance, as well as air quality. Guangxi Zhuang Autonomous Region, as a primarily agricultural province of China and neighbouring Southeast Asia, is subjected to both local emissions and pollution transport from Southeast Asian biomass burning. To investigate the light absorption properties and source contributions of BC and BrC in this region, observations from a 7-wavelength Aethalometer are employed to estimate the light absorption properties of BC and BrC over the period from March to December 2020 in Nanning, China. This study focuses on analysing the absorption contributions of BC and BrC to the total absorption of carbonaceous aerosols, identifying their emission sources, and exploring the impact of long-range transport of biomass burning (BB) from Southeast Asia on BC and BrC based on backward trajectory and weighted concentration-weighted trajectories (WCWT) model. Our results show that the absorption Ångström exponent (AAE) of light-absorbing carbonaceous aerosols varies from 0.54 to 2.08, reflecting the presence of different absorbing aerosol sources with specific optical properties. The average absorption coefficients of BC and BrC at 370 nm, denoted as babs,BC(370) and babs,BrC(370), are 42.25 Mm−1 and 9.63 Mm−1, respectively, with the highest value observed in winter. The average absorption of BrC contributes 19% to the total absorption from light-absorbing carbonaceous aerosols, and this contribution decreases for high babs,BrC(370) values, with the highest value in summer at 20%. For the BC source apportionment using a site-specific AAE, fossil fuel combustion (FF) contributes 57%, with its highest proportion in summer (62%). Meanwhile, biomass burning (BB) accounts for 43%, with the greatest contribution in winter (58%). These results highlight the considerable role of BB in Guangxi. In terms of the BrC sources, secondary BrC (BrCsec) is responsible for 32% of the total light absorption of BrC at 370 nm, and is particularly characterized by a much higher level of 35% at night, meaning the dominant role of BrCsec in Nanning. The relative contribution of babs,BrC,sec(370) increases with a higher contribution of babs,BrC(370) to aerosol absorption. Compared with the BrCsec, primary BrC values are higher in spring and winter, due to the increased emissions from biomass burning. Based on the analysis of backward trajectory and WCWT, the increase in BC and BrC during March and April is mainly influenced by the long-range transport of BB from Southeast Asian countries, e.g., Laos and Thailand. Overall, the contributions of BB and FF emissions to BC are comparable in Guangxi, while BrC mainly formed from primary sources is significantly impacted by both local emissions and the long-range transport of BB. Studying the optical characteristics and emission sources in this region can promote the understanding of the radiative effect of light-absorbing carbonaceous aerosols under the joint contributions from biomass burning and industrial emissions.

Tilted global solar irradiance in Bahrain: an experimental study

Abstract In the present work, tilted global solar irradiance data are presented and analysed, measured for a period of 1 year on the campus of Bahrain Polytechnic, Kingdom of Bahrain, from both a fixed photovoltaic panel and a moving one via a two-axis solar tracker. The fixed panel faces south with an angle of 26° with respect to the horizontal, coinciding with the local geographical latitude. The second panel is moved by two motors, controlled by a global positioning system and suitable software so that the Sun’s rays are perpendicular to the panel surface. A pyranometer is installed on each panel, recording the tilted global solar irradiance, stored by using a data logger. The analysis of the data obtained shows a 33% solar energy gain on an annual basis for the moving panel (2780 versus 2088 kWh/m2 on the fixed panel). More importantly, in June, when the energy demand in Bahrain is elevated due to the increased residential cooling loads, the solar energy received by the moving panel is 54.7% higher compared with that of the fixed panel. On a percentage basis, the increase in solar energy from the moving panel is profound in the early morning and late evening hours. Moreover, the reduction in the solar energy received by the fixed panel from May to June does not appear in the moving panel because of the adjustable orientation of the latter. Throughout the year, the mean daily solar power varies between 0.37 and 0.56 kW/m2 for the fixed panel, and 0.45 and 0.70 kW/m2 for the moving panel. In winter, solar energy fluctuations are elevated due to erratic weather conditions that present a peak standard deviation of 28% of the corresponding mean. The data presented are useful for potential solar investments in Gulf countries.

Global horizontal irradiance prediction for renewable energy system in Najran and Riyadh

Producing and supplying energy efficiently are important for many countries. Using models to predict energy production can help reduce costs, improve efficiency, and make energy systems work better. This research predicts solar electricity production in the Najran and Riyadh regions of Saudi Arabia by analyzing 14 weather factors. The weather factors that were considered in the study include date, time, Global Horizontal Irradiance (GHI), clear sky, top of atmosphere, code, temperature, relative humidity, pressure, wind speed, wind direction, rainfall, snowfall, and snow depth. GHI is the most important factor because it determines how much solar energy a system can produce. Therefore, it is important to be able to predict GHI accurately. This study used a variety of data-driven models to predict GHI, including the elastic net regression, linear regression, random forest, k-nearest neighbor, gradient boosting regressor, light gradient boosting regressor, extreme gradient boosting regressor, and decision tree regressor. The models were evaluated using a set of metrics, including the mean absolute error, mean squared error, root mean square error, coefficient of determination (R2), and adjusted coefficient of determination. This study found that the decision tree regression, Random Forest (RF), and Extreme Gradient Boosting (XGB) models performed better in the Riyadh region than in the Najran region. The R2 values for the Riyadh region were 99%, 99%, and 98%, while the R2 values for the Najran region were 89%, 94%, and 94%. This suggests that the Riyadh region is a more suitable location for solar energy conversion systems. These findings are important for policymakers and investors who are considering the development of solar energy projects in Saudi Arabia.

Sunlight exposure might account for the relatively low COVID-19 morbidity and mortality in tropical countries.

The present study aimed at exploring whether sunlight exposure might account for the relative difference in COVID-19-related morbidity and mortality between tropical and non-tropical countries. A retrospective observational study was designed and data from the World Health Organization weekly COVID-19 epidemiological update was compiled. We examined the total number of confirmed COVID-19 cases per 100 000 population, as well as the total number of COVID-19-related mortalities per 100 000 population. Solar variables data were obtained from the Global Solar Atlas website (https://globalsolaratlas.info/). These data were analyzed to determine the association of sunlight exposure to COVID-19-related morbidity and mortality in tropical and non-tropical countries. Results revealed a statistically significant decrease in the number of confirmed COVID-19 cases per 100 000 population (P<0.001), as well as the number of COVID-19-related mortalities per 100 000 population (P<0.001) between tropical and non-tropical countries. Analyses of sunlight exposure data found that specific photovoltaic power output, global horizontal irradiation, diffuse horizontal irradiation and global tilted irradiation at optimum angle were significantly inversely correlated to COVID-19-related morbidity and mortality. This suggests that stronger sunlight exposure potentially leads to lower COVID-19-related morbidity and mortality. Findings from this study suggest that the relatively low COVID-19-related morbidity and mortality in tropical countries were possibly due to better sunlight exposure that translates into adequate vitamin D status.

Impact of Climate Change on the Performance of Household-Scale Photovoltaic Systems

The objective of this article was to investigate the impacts of climate change on photovoltaic systems among renewable energies by the end of the 21st century. One hypothesis posited that due to decreased cloud cover as a result of changing climate, the geographical region under examination would receive more solar irradiation—usable by photovoltaic panels—which would in turn increase the annual electrical energy production of these systems. Another hypothesis suggested that the average temperature increase, associated with changing climate conditions, would detrimentally affect the efficiency of electricity production in photovoltaic systems. The study was based on the simulation of a household-scale photovoltaic model. This simulation calculated the system's performance on an hourly basis depending on inputs and summed these to produce an annual value. Input values were derived from climate scenario databases. These variables included global horizontal irradiance, direct horizontal irradiance, temperature, and wind speed. The output was the aforementioned quantity of annual electrical energy production. An analysis occurred between the annual average global horizontal irradiance and the annual average air temperature in relation to the quantities of annual electrical energy production. Pearson and partial correlation examinations among the variables demonstrated that unfavorable scenarios resulted in reduced efficiency of photovoltaic electrical energy production, primarily due to rising temperatures. Among other contributions, this article can support research into the active cooling of photovoltaic systems and the examination of their viability to mitigate efficiency losses caused by current and future temperature increases. Doi: 10.28991/HIJ-2024-05-01-01 Full Text: PDF

Evaluation of the WRF-solar model for 72-hour ahead forecasts of global horizontal irradiance in West Africa: A case study for Ghana

Accurate global horizontal irradiance (GHI) forecasting is critical for integrating solar energy into the power grid and operating solar power plants. The Weather Research and Forecasting model with its solar radiation extension (WRF-Solar) has been used to forecast solar irradiance in different regions around the world. However, the application of the WRF-Solar model to the prediction of GHI in West Africa, particularly Ghana, has not yet been investigated. The aim of this study is to evaluate the performance of the WRF-Solar model for predicting GHI in Ghana, focusing on three automatic weather stations (Akwatia, Kumasi and Kologo) for the year 2021. We used two one-way nested domains (D1 = 15 km and D2 = 3 km) to investigate the ability of the fully coupled WRF-Solar model to forecast GHI up to 72-hour ahead under different atmospheric conditions. The initial and lateral boundary conditions were taken from the ECMWF high-resolution operational forecasts. Our findings reveal that the WRF-Solar model performs better under clear skies than cloudy skies. Under clear skies, Kologo performed best in predicting 72-hour GHI, with a first day nRMSE of 9.62 %. However, forecasting GHI under cloudy skies at all three sites had significant uncertainties. Additionally, WRF-Solar model is able to reproduce the observed GHI diurnal cycle under high AOD conditions in most of the selected days. This study enhances the understanding of the WRF-Solar model’s capabilities and limitations for GHI forecasting in West Africa, particularly in Ghana. The findings provide valuable information for stakeholders involved in solar energy generation and grid integration towards optimized management in the region.

Observation and modeling of irradiance near water surface of a photovoltaic pond

Accurate evaluation of near ground solar radiation in photovoltaic (PV) covered areas is essential for controlling adverse environmental effects and comprehensively utilizing the earth’s surface resources. The irradiance near the water surface of a photovoltaic fishpond was measured with eighteen distributed pyranometers. A simplified penetration model is proposed to reveal the shielding effect of PV panels on direct and diffuse irradiance. The model can well capture the spatial–temporal variation of the global irradiance due to the shielding effect of PV arrays. Numerical results show that proper modeling of the shading effect on diffuse irradiance is essential for the calculation accuracy of the cumulative global irradiance loss for various weather types and sky-view restriction levels. The spatial variation range of global radiation penetration ratio under the PV panels is 10%–90%. The spatially-averaged monthly shielding effects show that the maximum (87%) and minimum (46%) relative irradiance loss ratios in the studied PV area occur in December and June, respectively.

Convenient Site Selection of a Floating PV Power Plant in Türkiye by using GIS-Fuzzy Analytical Hierarchy Process.

Floating photovoltaics (FPVs) are appearing as a promising and an alternative renewable energy opinion in which PV panels are mounted on floating platforms in order to produce electricity from renewable energy on water such as seas, dams, rivers, oceans, canals, fish farms, and reservoirs. So far, such studies related to the body knowledge on financial, technical, and environmental aspects of installation of FPV have not been performed in Turkey while expanding steadily in other countries. In this study, suitable site selection for installation of FPV power plants on three lakes in Turkey was studied by performing geographic information system (GIS) and the fuzzy analytic hierarchy process (FAHP) as multi-criteria decision-making (MCDM) method. This detailed study revealed that the criterion of global horizontal irradiance (GHI) was determined as the most crucial criterion for the installation of FPV on Beysehir Lake, Lake of Tuz, and Van Lake. Additionally, it was clearly seen that the Beysehir Lake had the highest value approximately 52% among other lakes for installation, that is why Beysehir Lake is selected as the best option for installation of an FPV system with this multi-criteria approach.

Chorus wave power at the strong diffusion limit overcomes electron losses due to strong diffusion

Earth’s radiation belts consist of high-energy charged particles trapped by Earth’s magnetic field. Strong pitch angle diffusion of electrons caused by wave-particle interaction in Earth’s radiation belts has primarily been considered as a loss process, as trapped electrons are rapidly diffused into the loss cone and lost to the atmosphere. However, the wave power necessary to produce strong diffusion should also produce rapid energy diffusion, and has not been considered in this context. Here we provide evidence of strong diffusion using satellite data. We use two-dimensional Fokker-Planck simulations of electron diffusion in pitch angle and energy to show that scaling up chorus wave power to the strong diffusion limit produces rapid acceleration of electrons, sufficient to outweigh the losses due to strong diffusion. The rate of losses saturates at the strong diffusion limit, whilst the rate of acceleration does not. This leads to the surprising result of an increase, not a decrease in the trapped electron population during strong diffusion due to chorus waves as expected when treating strong diffusion as a loss process. Our results suggest there is a tipping point in chorus wave power between net loss and net acceleration that global radiation belt models need to capture to better forecast hazardous radiation levels that damage satellites.

Comparison of personal exposure to black carbon levels with fixed-site monitoring data and with dispersion modelling and the influence of activity patterns and environment

BackgroundShort-term studies of health effects from ambient air pollution usually rely on fixed site monitoring data or spatio-temporal models for exposure characterization, but the relation to personal exposure is often not known.ObjectiveWe aimed to explore this relation for black carbon (BC) in central Stockholm.MethodsFamilies (n = 46) with an infant, one parent working and one parent on parental leave, carried battery-operated BC instruments for 7 days. Routine BC monitoring data were obtained from rural background (RB) and urban background (UB) sites. Outdoor levels of BC at home and work were estimated in 24 h periods by dispersion modelling based on hourly real-time meteorological data, and statistical meteorological data representing annual mean conditions. Global radiation, air pressure, precipitation, temperature, and wind speed data were obtained from the UB station. All families lived in the city centre, within 4 km of the UB station.ResultsThe average level of 24 h personal BC was 425 (s.d. 181) ng/m3 for parents on leave, and 394 (s.d. 143) ng/m3 for working parents. The corresponding fixed-site monitoring observations were 148 (s.d. 139) at RB and 317 (s.d. 149) ng/m3 at UB. Modelled BC levels at home and at work were 493 (s.d. 228) and 331 (s.d. 173) ng/m3, respectively. UB, RB and air pressure explained only 21% of personal 24 h BC variability for parents on leave and 25% for working parents. Modelled home BC and observed air pressure explained 23% of personal BC, and adding modelled BC at work increased the explanation to 34% for the working parents.ImpactShort-term studies of health effects from ambient air pollution usually rely on fixed site monitoring data or spatio-temporal models for exposure characterization, but the relation to actual personal exposure is often not known. In this study we showed that both routine monitoring and modelled data explained less than 35% of variability in personal black carbon exposure. Hence, short-term health effects studies based on fixed site monitoring or spatio-temporal modelling are likely to be underpowered and subject to bias.

Evaluating the Potential of Floating Photovoltaic Plants in Pumped Hydropower Reservoirs in Spain

The Spanish government is a strong advocate of reducing CO2 emissions and has made a clear commitment to the implementation of renewable energies. As reflected in Spain’s National Energy and Climate Plan (NECP), its objective is to double the current capacity of pumped hydropower storage (PHS) plants by 2030. Therefore, the study presented here is both current and forward-looking. This paper presents the results of the analysis of the technical potential of installing floating photovoltaic (FPV) plants at 25 PHS plants in Spain, i.e., the total capacity of Spanish hydropower plants. The study was conducted using various assessment indicators: the global horizontal irradiance ratio, electrical efficiency ratio, area required ratio, pumping area ratio, volume ratio of water pumped per day, and achievable power ratio. In summary, the following conclusions can be drawn: (i) The global horizontal irradiance ratio indicates whether a FPV plant is economically viable. From this point of view, the Aguayo PHS plant and the Tanes PHS plant are not suitable, as this ratio is very low; (ii) the compliance with the electrical efficiency ratio is flexible, and all hydropower plants meet this criterion; (iii) maximising the use of the assigned grid connection capacity is one of the goals sought by electrical companies when implementing FPV plants at existing PHS plants. The following hydropower plants are not suitable for the implementation of an FPV plant in view of the following: La Muela I, La Muela II, Aguayo, Sallente, Aldeadavila II, Moralets, Guillena, Bolarque II, Montamara, and IP; (iv) if the aim is energy storage, the following hydropower plants are not suitable for the implementation of an FPV plant: the La Muela I, La Muela II, Tajo de la Encantada, Aguayo, Sallente, Aldeadavila II, Conso, Moralets, Guillena, Bolarque II, Tanes, Montamara, Soutelo, Bao-Puente Bibey, Santiago de Jares, IP, and Urdiceto; (v) if the aim is to expand an FPV plant already installed at a PHS plant, the following hydropower plants do not meet this criterion: the La Muela I, La Muela II, Aguayo, Sallente, Aldeadavila, Moralets, Guillena, Bolarque II, Montamara, and IP. There are only eight hydropower plants that meet conditions (i), (iii) and (iv): the Villarino, Torrejon, Valparaiso, Gabriel y Galan, Guijo de Granadilla, Pintado, and Gobantes.

Study of Global Horizontal and Vertical Solar Irradiance Components Under Different Sky Conditions for Sustainable Building Design In Bali Of Indonesia

The study of global and vertical solar irradiance components under different sky conditions is very important for building design applications. This research has been carried out by analyzing the components of solar radiation based on global horizontal irradiance (GHI) data, and global vertical irradiance for east, west, north, and south oriented. Observational data was acquired for one year starting from July 2022 to June 2023 in Jembrana-Bali of Indonesia. The solar radiation component has been analyzed based on sub-diurnal (daytime) and annual patterns. The clearness index (Kt) was calculated based on the ratio of extra-terrestrial solar radiation to global solar radiation measured at the surface. Sun-path analysis was carried out by considering the relationship of the zenith angle, azimuth angle, and the intensity of each solar radiation component to changes in time. The results show that in all-sky conditions, the average monthly maximum global horizontal irradiance occurs in January at 432.4 W/m², while the minimum monthly average global horizontal irradiance occurs in July at 327.9 W/m². The clearness index statistic shows that the hourly average ranges from 0.12 to 0.68 with an average of 0.47. Based on sun-path analysis, east, north, and west orientations receive more solar radiation in the Jembrana-Bali area. The findings from the study provide important information for architects, engineers, and policymakers that can be used for sustainable building design and building energy planning.

Solar radiation forecasting using gradient boosting based ensemble learning model for various climatic zones

India is seeing a massive boost in solar power installations in the recent years. It is expected that solar energy utilization will be increasing exponentially in near future. Solar radiation forecasting is an essential tool to obtain the optimal performance out of the solar systems. An ensemble model using gradient boosting has been developed for hourly global horizontal irradiance forecasting is proposed for the various climatic zones of India. The gradient boost-based model is benchmarked with Auto Regressive Integrated Moving Average (ARIMA),2-layer feed forward neural network, and Long Short-Term Memory (LSTM). Gradient boosting obtained with marginally better performance metrics, mean absolute error (20.97 W/m2) and mean square error (1357 W2/m4) as compared to that of the neural network (21.66 W/m2, 1479.53 W2/m4) and performed much better than ARIMA and LSTM in terms of mean absolute error (251.66 W/m2) & mean square error (82,290 W2/m4) and mean absolute error (67.60 W/m2) & mean square error (8123 W2/m4). The diverse climatic zones in India and feature importance analysis have been considered during the model development and testing phase. The proposed model is also intended to have practical implications in obtaining solar irradiance data in locations with minimal availability of solar radiation data and solar power systems due to the model ability to provide good performance metrics in a smaller timeframe making it an ideal candidate for real-time solar power predicting model.

Minutely multi-step irradiance forecasting based on all-sky images using LSTM-InformerStack hybrid model with dual feature enhancement

In recent years, the government has attached great importance to promoting innovation in new energy technologies, particularly in the area of solar power generation. Photovoltaic (PV) power generation has become an essential factor in the promotion of renewable energy due to its inherent safety, environmental sustainability and abundant solar energy resources. The efficiency and stability of PV generation systems are closely related to the accurate prediction of real-time global horizontal irradiance (GHI). However, some existing research methods have made some progress in hourly resolution, but the multi-step prediction accuracy and model generalization ability in high time resolution are still unsatisfactory. Therefore, this paper proposes a novel minutely multi-step irradiance forecasting based on all-sky images using LSTM-InformerStack hybrid model with dual feature enhancement scheme. In this scheme, the advantages of both LSTM and InformerStack models are combined to further enhance the global and local features, which can better capture the short-term time series patterns and long-term dependencies and improve the accuracy of the time series. The experimental validation results show that the performance of this prediction scheme is improved by 11.2%, and 26.0% for nRMSE and R2, respectively, and the 24-step prediction can be improved up to 26.1% vs. the persistent model. Meanwhile, the prediction scheme of this paper is also expected to provide a reference in future multi-step time series accurate prediction with higher resolution.

GEOSPATIAL ANALYSIS OF THE POTENTIAL OF THE TERRITORIES OF UKRAINE FOR THE LOCATION OF SOLAR POWER PLANTS BASED ON SATELLITE DATA

Climate change necessitates the relevance of renewable energy utilization worldwide. The Green Deal defines the energy development policy in Europe until 2030. This challenge holds particular significance for Ukraine in the context of post-war energy infrastructure recovery. Therefore, an important issue is the analysis of the suitability of Ukrainian territories for the installation of large-scale solar power plants (solar farms) and the optimization of their placement. This research aims to determine the suitability of Ukrainian territories for solar power plant placement using satellite data on climate and terrain characteristics. Among the factors determining the suitability of the territory for solar farms, the greatest impact lies in climatic indicators, including data on the total global horizontal solar irradiation (GHI), accumulated temperature above 25 °C at a height of 2 meters, average annual wind speed, and map of accumulated annual precipitation from the ERA5-Land dataset. In this study, terrain maps containing information on elevations, slopes, and terrain shading from the Shuttle Radar Topography Mission (SRTM) project were also used to determine the suitability of the territories. The suitability of the territories is determined through geospatial analysis using weighted sums. Based on the research results, a suitability map was constructed, depicting the distribution of zones with different suitability coefficients (ranging from 0 to 1). It was found that a significant portion of Ukraine’s territory is favorable for the placement of solar power plants. Over 48 % of the country has moderate suitability values (0.3…0.4). The obtained suitability map was used to analyze the optimal placement of already constructed major solar power plants in Ukraine. Data from Wikimapia was utilized to determine the locations of these energy facilities. Overall, all the analyzed large-scale solar power plants in Ukraine were situated in optimal territories. The research also revealed that certain regions, such as Odesa, Poltava, Kharkiv, Zaporizhzhia, Dnipro, Donetsk, and Luhansk, have good suitability values (0.3…0.4) but are not fully utilized. These areas have significant potential for the future construction of powerful and productive solar power plants

Facilitating greenhouse gas emissions reduction via photovoltaic site characterization and deployment in Jeddah, Saudi Arabia

Abstract The study shows that oil production and consumption in the various sectors accounted for over 80% of the rising GHG emissions, especially CO2. Additionally, the study examines the solar photovoltaic (PV) potential of Jeddah, Saudi Arabia, using computational modelling. The results show that the yearly average global horizontal irradiation, direct normal radiation and diffuse horizontal irradiations are 2244, 1967 and 863.3 kWh/m2, respectively. Other results are the yearly sum of monthly global tilted irradiation (GTI) and an average yearly daily sum of GTI are 2348.4 and 6.44 kWh/m2, respectively. These results show that Jeddah has huge solar PV potential.

Novel use of an adapted ultraviolet double monochromator for measurements of global and direct irradiance, ozone, and aerosol

Abstract. A novel ultraviolet spectrometer has been developed and tested over 10 years at Lauder, New Zealand. The system, UV2, makes alternating measurements of the global and direct UV irradiance and can therefore be used to measure ozone and aerosol optical depth. After an analysis of the stability of UV2, these measurements, along with UV irradiance, are compared to relevant observations made by an additional UV spectrometer (UV4), a Dobson spectrophotometer (no. 072), and two radiometers measuring aerosol optical depth – a Prede sky radiometer and a Middleton Solar radiometer (SP02). UV2 irradiance is shown to be lower than UV4 by between 2.5 % and 3.5 %, with a standard deviation of a similar magnitude. Total column ozone values are shown to agree with Dobson spectrophotometer values with a mean bias of 2.57 Dobson units (DU) and standard deviation of 1.15 DU when using the direct sun measurements. Aerosol optical depth at 400–412 and 500 nm agrees to within 0.015 and is comparable to the difference between the reference radiometers. Further work is needed, particularly in the radiometric calibration at longer wavelengths, in order to determine if this instrument can supersede or enhance measurements made by the Dobson spectrophotometer or the aerosol radiometers.

A Vision for Global CT Radiation Dose Optimization

The topic of CT radiation dose management is receiving renewed attention since the recent approval by CMS for new CT dose measures. Widespread variation in CT dose persists in practices across the world, suggesting that current dose optimization techniques are lacking. The author outlines a proposed strategy for facilitating global CT radiation dose optimization. CT radiation dose optimization can be defined as the routine use of CT scan parameters that consistently produce images just above the minimum threshold of acceptable image quality for a given clinical indication, accounting for relevant patient characteristics, using the most dose-efficient techniques available on the scanner. To accomplish this, an image quality–based target dose must be established for every protocol; for nonhead CT applications, these target dose values must be expressed as a function of patient size. As variation in outcomes is reduced, the dose targets can be decreased to more closely approximate the minimum image quality threshold. Maintaining CT radiation dose optimization requires a process control program, including measurement, evaluation, feedback, and control. This is best accomplished by local teams made up of radiologists, medical physicists, and technologists, supported with protected time and needed tools, including analytics and protocol management applications. Other stakeholders critical to facilitating CT radiation dose management include researchers, funding agencies, industry, regulators, accreditors, payers, and the ACR. Analogous coordinated approaches have transformed quality in other industries and can be the mechanism for achieving the universal goal of CT radiation dose optimization.