Search Results (22)

Ultraviolet solar radiation at the Earth’s surface significantly impacts both human health and ecosystems. A biologically effective daily radiant exposure (BEDRE) model is proposed for various biological processes with an analytical formula for its action spectrum. The following processes are considered: erythema formation, previtamin D3 synthesis, psoriasis clearance, and inactivation of SARS-CoV-2 virions. The BEDRE model is constructed by multiplying the synthetic BEDRE value under cloudless conditions by a cloud modification factor (CMF) parameterizing the attenuation of radiation via clouds. The CMF is an empirical function of the solar zenith angle (SZA) at midday and the daily clearness index from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) measurements on board the second-generation Meteosat satellites. Total column ozone, from MERRA-2 reanalysis, is used in calculations of clear-sky BEDRE values. The proposed model was trained and validated using data from several European ground-based spectrophotometers and biometers for the periods 2014–2023 and 2004–2013, respectively. The model provides reliable estimates of BEDRE for all biological processes considered. Under snow-free conditions and SZA < 45° at midday, bias and standard deviation of observation-model differences are approximately ±5% and 15%, respectively. The BEDRE model can be used as an initial validation tool for ground-based UV data. Full article

Accurate marine wind detection under all-weather conditions is crucial for maritime activities. The joint detection of lidar and radar is supposed to be a potential way to carry out the all-weather sensing of wind. However, their performance analysis has not been well studied, particularly in the far sea area, where the wind-tracing particles are quite different from those inland. Based on the particle distributions above the sea surface under different weather conditions, this study investigated the scattering and attenuation effects of lidar and radar waves in open sea areas with the Mie theory and T-matrix method. Then, the maximum detection range and velocity accuracies of lidar/radar were comprehensively analyzed based on detection principles to optimize the combination of lidar and radar. According to the simulation results, it was difficult to maintain the detection capability of a single lidar/radar under all-weather conditions, and 1.55 $\mathsf{\mu }$m lidar and W-band radar presented a promising joint detection scheme, as they exhibited optimal weather adaptability in clear sky and precipitation conditions, respectively. Full article

The traditional approach of considering the probability distribution of rain attenuation leads to provide very large power margin (overdesign) in data channels. We have extended a method which, with a small power margin, bandwidth expansion and variable symbol rate, avoids overdesign and can transfer the same data volume as if the link were in clear–sky conditions. It is characterized only by the link mean efficiency, suitably defined. It is useful only if: (a) data must be up– and downloaded when it is raining; (b) real–time communication is not required. We have applied it to the links of GeoSurf satellite constellations (in which, at any latitude of ground stations, propagation paths are at the local zenith) by simulating rain attenuation time series at 80 GHz (mm–wave)–the new frontier of satellite frequencies–with the Synthetic Storm Technique, from rain–rate time series recorded on–site, at sites located in different climatic regions. The power margin to be implemented at 80 GHz ranges from 2.0 dB to 7.4 dB–well within the current technology–regardless the instantaneous rain attenuation. The clear–sky bandwidth is expanded 1.75 to 2.80 times, a factor not large per se, but it may challenge current technology if the clear–sky bandwidth is already large. Full article

While solar power applications are growing rapidly worldwide, information about solar energy availability, its characteristics and the factors that affect it are essential. Among other parameters, a reference spectrum (ASTMG-173-03) is adopted, relying on Standard Test Conditions (STC), under which Photovoltaic (PV) devices are evaluated. However, these rigorously defined conditions can vary considerably from realistic environmental conditions. The objective of the present work is to assess the impact of the variability of atmospheric composition on the spectral distribution of the incident solar spectral irradiance (SSI) and, therefore, its implication on various PV materials performance. Ground-based measurements of global horizontal SSI have been conducted using a Precision Spectroradiometer (PSR) in the framework of the ASPIRE (Atmospheric parameters affecting SPectral solar IRradiance and solar Energy) project in Athens, Greece. The gathered data in combination with spectrally resolved radiative transfer under clear-sky conditions contributed to the investigation of the atmospheric variables that attenuate irradiance (e.g., aerosols). In addition, since PV modules’ spectral absorptivity differs according to the semiconductor material used, the impact of the above-mentioned spectral features on PV performance has been investigated in order to estimate the spectral impact between the theoretical and outdoor conditions on the yield of different PV technologies. Overall, the results denote that smoke has a more significant effect than dust, while the effect on various technologies varies. The highest deviation compared to the STC was observed in the case of a-Si, reaching an absolute difference of 45% in the case of smoke particles in the atmosphere, while the maximum deviation between the different technologies reached approximately 7%. Full article

We investigate the possibility of estimating global horizontal irradiance (GHI) in parallel to photovoltaic (PV) power production in India using a radiative transfer model (RTM) called libRadtran fed with satellite information on the cloud and aerosol conditions. For the assessment of PV energy production, we exploited one year’s (January–December 2018) ground-based real-time measurements of solar irradiation GHI via silicon irradiance sensors (Si sensor), along with cloud optical thickness (COT). The data used in this method was taken from two different sources, which are EUMETSAT’s Meteosat Second Generation (MSG) and aerosol optical depth (AOD) from Copernicus Atmospheric Monitoring Services (CAMS). The COT and AOD are used as the main input parameters to the RTM along with other ones (such as solar zenith angle, Ångström exponent, single scattering albedo, etc.) in order to simulate the GHI under all sky, clear (no clouds), and clear-clean (no clouds and no aerosols) conditions. This enabled us to quantify the cloud modification factor (CMF) and aerosol modification factor (AMF), respectively. Subsequently, the whole simulation is compared with the actual recorded data at four solar power plants, i.e., Kazaria Thanagazi, Kazaria Ceramics, Chopanki, and Bhiwadi in the Alwar district of Rajasthan state, India. The maximum monthly average attenuation due to the clouds and aerosols are 24.4% and 11.3%, respectively. The energy and economic impact of clouds and aerosols are presented in terms of energy loss (EL) and financial loss (FL). We found that the maximum EL in the year 2018 due to clouds and aerosols were 458 kWh m⁻² and 230 kWh m⁻², respectively, observed at Thanagazi location. The results of this study highlight the capabilities of Earth observations (EO), in terms not only of accuracy but also resolution, in precise quantification of atmospheric effect parameters. Simulations of PV energy production using EO data and techniques are therefore useful for real-time estimates of PV energy outputs and can improve energy management and production inspection. Success in such important venture, energy management, and production inspections will become much easier and more effective. Full article

China is expected to have a total installed photovoltaic capacity of 1300 GW in 2050, accounting for 39% of the national electricity consumption. However, air pollutants consisting of gases and particulates have attenuation effects on the solar radiation reaching the photovoltaic panels. This work purports to assess the influence of air pollutants on the photovoltaic power potential. We calculated the hourly point-of-array irradiance (POAI) in China for 2010–2020 with a spatial resolution of 0.1° × 0.1° using the PV_LIB model and assessed the effect of air pollutants on POAI. The results indicated that the annual average POAI in China for 2010–2020 ranged from 118 to 286 Wm⁻². The Air Pollution Control Action Plan (APPCAP) has played a certain role in photovoltaic power potential, and POAI has increased in areas where surface concentrations of air pollutants have declined. Especially in North China, the surface concentrations of CO, NO₂, PM₁₀, PM_2.5, and SO₂ decreased throughout the APPCAP period with −0.446, −4.985, −35.610, −30.700, and −26.251 μgm⁻³, respectively, corresponding to an increase in POAI of up to 4.917 Wm⁻². The surface concentrations of CO, NO₂, PM₁₀, PM_2.5, and SO₂ were negatively correlated with POAI, with correlation coefficients of −0.764, −0.854, −0.204, −0.110, and −0.664, respectively. Surface concentrations of air pollutants (CO, NO₂, PM₁₀, PM_2.5, and SO₂) and clear-sky POAI in 2018 showed a High-Low clustering in Northeast China and North China. This study demonstrates the role of China’s air pollution control policy in enhancing photovoltaic power potential. Full article

Solar radiation is by nature intermittent and influenced by many factors such as latitude, season and atmospheric conditions. As a consequence, the growing penetration of Photovoltaic (PV) systems into the electricity network implies significant problems of stability, reliability and scheduling of power grid operation. Concerning the very short-term PV power production, the power fluctuations are primarily related to the interaction between solar irradiance and cloud cover. In small-scale systems such as microgrids, the adoption of a forecasting tool is a brilliant solution to minimize PV power curtailment and limit the installed energy storage capacity. In the present work, two different nowcasting methods are applied to classify the solar attenuation due to clouds presence on five different forecast horizons, from 1 to 5 min: a Pattern Recognition Neural Network and a Random Forest model. The proposed methods are tested and compared on a real case study: available data consists of historical irradiance measurements and infrared sky images collected in a real PV facility, the SolarTech^LAB in Politecnico di Milano. The classification output is a range of values corresponding to the future value assumed by the Clear Sky Index (CSI), an indicator allowing to account for irradiance variations only related to clouds passage, neglecting diurnal and seasonal influences. The developed models present similar performance in all the considered time horizons, reliably detecting the CSI drops caused by incoming overcast and partially cloudy sky conditions. Full article

Indoor daylighting quality has impacts on occupants’ physical and psychological aspects. Although daylighting design metrics have strictly restricted the amount of sunlight penetration, studies have shown occupants’ preference towards an appropriate amount of sunlight and distributions. Currently, insufficient studies have focused on the composition of interior daylighting distributions. Therefore, this paper presents a laboratory experiment exploring the psychological influences of sunlight patterns under immersive virtual reality scenes. The sunlight patterns are created by a combination of nine aperture designs, two window sizes and two sky types. The experiment collects 41 valid architecture students’ assessments and their physiological responses. Degrees of eight adjectives, including pleasantness, calmness, interest, excitement, complexity, spaciousness, satisfaction with exterior view amount and brightness, are rated by the participants. Physiological data of heart rates and electroencephalogram are collected. According to the analysis, both the aperture designs and sky types have influences upon subjective responses. The large window enhances beta oscillations and beta power on the right prefrontal lobe area, and the clear sky attenuates the theta rhythm on the pre frontal lobe areas. These findings indicate the important influence of natural lightscape compositions created by aperture designs and sky types upon occupants’ psychological processes. Full article

The direct radiative effects of atmospheric aerosols are essential for climate, as well as for other societal areas, such as the energy sector. The goal of the present study is to exploit the newly developed ModIs Dust AeroSol (MIDAS) dataset for quantifying the direct effects on the downwelling surface solar irradiance (DSSI), induced by the total and dust aerosol amounts, under clear-sky conditions and the associated impacts on solar energy for the broader Mediterranean Basin, over the period 2003–2017. Aerosol optical depth (AOD) and dust optical depth (DOD) derived by the MIDAS dataset, along with additional aerosol and dust optical properties and atmospheric variables, were used as inputs to radiative transfer modeling to simulate DSSI components. A 15-year climatology of AOD, DOD and clear-sky global horizontal irradiation (GHI) and direct normal irradiation (DNI) was derived. The spatial and temporal variability of the aerosol and dust effects on the different DSSI components was assessed. Aerosol attenuation of annual GHI and DNI were 1–13% and 5–47%, respectively. Over North Africa and the Middle East, attenuation by dust was found to contribute 45–90% to the overall attenuation by aerosols. The GHI and DNI attenuation during extreme dust episodes reached 12% and 44%, respectively, over particular areas. After 2008, attenuation of DSSI by aerosols became weaker mainly because of changes in the amount of dust. Sensitivity analysis using different AOD/DOD inputs from Copernicus Atmosphere Monitoring Service (CAMS) reanalysis dataset revealed that using CAMS products leads to underestimation of the aerosol and dust radiative effects compared to MIDAS, mainly because the former underestimates DOD. Full article

In GeoSurf satellite constellations, any transmitter/receiver, wherever it is located, is linked to a satellite with zenith paths. We have studied the tropospheric attenuation predicted for some reference sites (Canberra, Holmdel, Pasadena, Robledo, and Spino d’Adda), which also set the meridian along which we have considered sites with latitudes ranging between 60° N and 60° S. At the annual probability of 1% of an average year, in the latitude between 30° N and 30° S, there are no significant differences between GEO slant paths and GeoSurf zenith paths. On the contrary, at 0.1% and 0.01% annual probabilities, large differences are found for latitudes greater than 30° N or 30° S. For comparing the tropospheric attenuation in GeoSurf paths with that expected in LEO highly variable slant paths, we have considered, as reference, a LEO satellite constellation orbiting in circular at 817 km. GeoSurf zenith paths “gain” several dBs compared to LEO slant paths. The more static total clear-sky attenuation (water vapor, oxygen, and clouds) in both GEO and LEO slant paths shows larger values than GeoSurf zenith paths. Both for rain and clear-sky attenuations, Northern and Southern Hemispheres show significant differences. Full article

Microwave land surface emissivity (MLSE) is an important geophysical parameter to determine the microwave radiative transfer over land and has broad applications in satellite remote sensing of atmospheric parameters (e.g., precipitation, cloud properties), land surface parameters (e.g., soil moisture, vegetation properties), and the parameters of interactions between atmosphere and terrestrial ecosystem (e.g., evapotranspiration rate, gross primary production rate). In this study, MLSE in China under both clear and cloudy sky conditions was retrieved using satellite passive microwave measurements from Aqua Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), combined with visible/infrared observations from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), and the European Centre for Medium-Range Weather Forecasts (ECMWF) atmosphere reanalysis dataset of ERA-20C. Attenuations from atmospheric oxygen and water vapor, as well as the emissions and scatterings from cloud particles are taken into account using a microwave radiation transfer model to do atmosphere corrections. All cloud parameters needed are derived from MODIS visible and infrared instantaneous measurements. Ancillary surface skin temperature as well as atmospheric temperature-humidity profiles are collected from ECMWF reanalysis data. Quality control and sensitivity analyses were conducted for the input variables of surface skin temperature, air temperature, and atmospheric humidity. The ground-based validations show acceptable biases of primary input parameters (skin temperature, 2 m air temperature, near surface relative humidity, rain flag) for retrieving using. The subsequent sensitivity tests suggest that 10 K bias of skin temperature or observed brightness temperature may result in a 4% (~0.04) or 7% (0.07) retrieving error in MLSE at 23.5 GHz. A nonlinear sensitivity in the same magnitude is found for air temperature perturbation, while the sensitivity is less than 1% for 300 g/m² error in cloud water path. Results show that our algorithm can successfully retrieve MLSE over 90% of the satellite detected land surface area in a typical cloudy day (cloud fraction of 64%), which is considerably higher than that of the 29% area by the clear-sky only algorithms. The spatial distribution of MLSE in China is highly dependent on the land surface types and topography. The retrieved MLSE is assessed by compared with other existing clear-sky AMSR-E emissivity products and the vegetation optical depth (VOD) product. Overall, high consistencies are shown for the MLSE retrieved in this study with other AMSR-E emissivity products across China though noticeable discrepancies are observed in Tibetan Plateau and Qinling-Taihang Mountains due to different sources of input skin temperature. In addition, the retrieved MLSE exhibits strong positive correlations in spatial patterns with microwave vegetation optical depth reported in the literature. Full article

Solar energy production is affected by the attenuation of incoming irradiance from underlying clouds. Often, improvements in the short-term predictability of irradiance using satellite irradiance models can assist grid operators in managing intermittent solar-generated electricity. In this paper, we develop and test a satellite irradiance model with short-term prediction capabilities using cloud motion vectors. Near-real time visible images from Himawari-8 satellite are used to derive cloud motion vectors using optical flow estimation techniques. The cloud motion vectors are used for the advection of pixels at future time horizons for predictions of irradiance at the surface. Firstly, the pixels are converted to cloud index using the historical satellite data accounting for clear, cloudy and cloud shadow pixels. Secondly, the cloud index is mapped to the clear sky index using a historical fitting function from the respective sites. Thirdly, the predicated all-sky irradiance is derived by scaling the clear sky irradiance with a clear sky index. Finally, a power conversion model trained at each site converts irradiance to power. The prediction of solar power tested at four sites in Australia using a one-month benchmark period with 5 min ahead prediction showed that errors were less than 10% at almost 34–60% of predicted times, decreasing to 18–26% of times under live predictions, but it outperformed persistence by >50% of the days with errors <10% for all sites. Results show that increased latency in satellite images and errors resulting from the conversion of cloud index to irradiance and power can significantly affect the forecasts. Full article

We examine the impact of atmospheric aerosols and clouds on the surface solar radiation and solar energy at Nainital, a high-altitude remote location in the central Gangetic Himalayan region (CGHR). For this purpose, we exploited the synergy of remote-sensed data in terms of ground-based AERONET Sun Photometer and satellite observations from the MODerate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat Second Generation (MSG), with radiative transfer model (RTM) simulations and 1 day forecasts from the Copernicus Atmosphere Monitoring Service (CAMS). Clouds and aerosols are one of the most common sources of solar irradiance attenuation and hence causing performance issues in the photovoltaic (PV) and concentrated solar power (CSP) plant installations. The outputs of RTM results presented with high accuracy under clear, cloudy sky and dust conditions for global horizontal (GHI) and beam horizontal irradiance (BHI). On an annual basis the total aerosol attenuation was found to be up to 105 kWh m⁻² for the GHI and 266 kWh m⁻² for BHI, respectively, while the cloud effect is much stronger with an attenuation of 245 and 271 kWh m⁻² on GHI and BHI. The results of this study will support the Indian solar energy producers and electricity handling entities in order to quantify the energy and financial losses due to cloud and aerosol presence. Full article

Atmospheric aerosol and ultraviolet index (UVI) measurements performed in Racibórz (50.08° N, 18.19° E) were analyzed for the period June–September 2019. Results of the following observations were taken into account: columnar characteristics of the aerosols (aerosol thickness, Angstrom exponent, single scattering albedo, asymmetry factor) obtained from standard CIMEL sun-photometer observations and parameters of aerosol layers (ALs) in the free troposphere (the number of layers and altitudes of the base and top) derived from continuous monitoring by a CHM-15k ceilometer. Three categories of ALs were defined: residues from the daily evolution of the planetary boundary layer (PBL) aerosols, from the PBL-adjacent layer, and from the elevated layer above the PBL. Total column ozone measurements taken by the Ozone-Monitoring Instrument on board NASA’s Aura satellite completed the list of variables used to model UVI variability under clear-sky conditions. The aim was to present a hybrid model (radiative transfer model combined with a regression model) for determining ALs’ impact on the observed UVI series. First, a radiative transfer model, the Tropospheric Ultraviolet–Visible (TUV) model, which uses typical columnar characteristics to describe UV attenuation in the atmosphere, was applied to calculate hypothetical surface UVI values under clear-sky conditions. These modeled values were used to normalize the measured UVI data obtained during cloudless conditions. Next, a regression of the normalized UVI values was made using the AL characteristics. Random forest (RF) regression was chosen to search for an AL signal in the measured data. This explained about 55% of the variance in the normalized UVI series under clear-sky conditions. Finally, the UVI values were calculated as the product of the RF regression and the relevant UVIs by the columnar TUV model. The root mean square error and mean absolute error of the hybrid model were 1.86% and 1.25%, respectively, about 1 percentage point lower than corresponding values derived from the columnar TUV model. The 5th–95th percentile ranges of the observation/model differences were [−2.5%, 2.8%] and [−3.0%, 5.3%] for the hybrid model and columnar TUV model, respectively. Therefore, the impact of ALs on measured surface UV radiation could be demonstrated using the proposed AL characteristics. The statistical analysis of the UVI differences between the models allowed us to identify specific AL configuration responsible for these differences. Full article

In this research, we performed energy and exergy assessments of a solar driven power plant. Supercritical carbon dioxide (S-CO₂) Brayton cycle is used for the conversion of heat to work. The plant runs on solar energy from 8 a.m. to 4 p.m. and to account for the fluctuations in the solar energy, the plant is equipped with an auxiliary heater operating on hot combustion gases from the combustion chamber. The capital city of Saudi Arabia (Riyadh) is chosen in this study and the solar insolation levels for this location are calculated using the ASHRAE clear-sky model. The solar collector (central receiver) receives solar energy reflected by the heliostats; therefore, a radially staggered heliostat field is generated for this purpose. A suite of code is developed to calculate various parameters of the heliostat field, such as optical efficiencies, intercept factors, attenuation factors and heliostat characteristic angles. S-CO₂ Brayton cycle is simulated in commercial software, Aspen HYSYS V9 (Aspen Technology, Inc., Bedford, MA, USA). The cycle is mainly powered by solar energy but assisted by an auxiliary heater to maintain a constant net power input of 80 MW to the cycle. The heliostat field generated, composed of 1207 rows, provides 475 watts per unit heliostat’s area to the central receiver. Heat losses from the central receiver due to natural convection and radiation are significant, with an average annual loss of 10 percent in the heat absorbed by the receiver. Heat collection rate at the central receiver reveals that the maximum support of auxiliary heat is needed in December, at nearly 13% of the net input energy. Exergy analysis shows that the highest exergy loss takes place in the heliostat field that is nearly 42.5% of incident solar exergy. Full article