High Wind Speeds Research Articles

Assessment of power curve performance of wind turbines in Adama-II Wind Farm

The power curve of a manufacturer must be compared with the actual power curve after commissioning because various factors lead to deviations. The main purpose of this study was to assess and compare the performance of the N72, N73, and N74 wind turbines of the Adama-II wind farm against the manufacturer's guaranteed power curve. The methods employed were high-correlation-based nacelle anemometry and Artificial Neural Network (ANN). The high-correlation-based nacelle anemometry method used here differs from the conventional IEC61400–12–2 in that it was based on a strong correlation between the mast and nacelle speed of a turbine from which the nacelle transfer function (NTF) was computed. The NTF was obtained by power interpolation from 10-minute wind mast data and the nacelle speed of N72. The measured power curve was then obtained by applying NTF to the nacelle speeds. The turbines were modeled using ANN, illustrating manufacturer's power curve was higher than the modeled values above 9 m/s. According to the analysis, the measured power curves of N73 and N72 were within the manufacturer's AEP uncertainty range at a mean wind speed of 4–9 m/s but showed a deviation of 10–18 % at higher wind speeds. The power production of the N74 turbine was within the manufacturer’s uncertainty limit only at a mean wind speed of 4–7 m/s, whereas at a wind speed above 7 m/s, it deviated by 22–40 %. Therefore, performances of N72 and N73 in terms of the AEP were better, except at wind speeds of 10 and 11 m/s. However, the performance of the N74 turbine was significantly lower than the manufacturer. ANN also gave similar results except at higher wind speeds where high-correlation-based nacelle anemometry performed better. Overall, the proposed methods demonstrated the performance of the turbines compared with the guaranteed power curve.

Development of Polar Lows in Future Climate Scenarios over the Barents Sea

Abstract Polar lows (PLs) are intense mesoscale cyclones that form over polar oceans during colder months. Characterized by high wind speeds and heavy precipitation, they profoundly impact coastal communities, shipping, and offshore activities. Amid the substantial environmental changes in polar regions due to global warming, PLs are expected to undergo noteworthy transformations. In this study, we investigate the response of PL development in the Barents Sea to climate warming based on two representative PLs. Sensitivity experiments were conducted including the PLs in the present climate and the PLs in a pseudo–global warming scenario projected by the late twenty-first century for Shared Socioeconomic Pathway (SSP) 2-4.5 and SSP 3-7.0 scenarios from phase 6 of the Coupled Model Intercomparison Project (CMIP6). In both warming climate scenarios, there is an anticipated decrease in PL intensity, in terms of the maximum surface wind speed and minimum sea level pressure. Despite the foreseen increase in latent heat release in the future climate, contributing to the enhancement of PL intensity, other primary factors such as decreased baroclinic instability, heightened atmospheric static stability, and reduced overall surface heat fluxes play pivotal roles in the overall decrease in PL intensity in the Barents Sea under warming conditions. The augmentation of surface latent heat flux, however, results in increased precipitation associated with PLs by enhancing the latent heat release. Furthermore, the regional steering flow shifts in the warming climate can influence the trajectory of PLs during their development. Significance Statement Global warming is anticipated to impact cyclone systems worldwide. Polar lows (PLs), intense mesocyclones in polar regions with potential socioeconomic and human life implications, pose uncertainties regarding intensity changes in a warming climate. In this study, we aimed to better understand how PLs over the Barents Sea will respond to the environmental changes in future climate conditions [Shared Socioeconomic Pathway (SSP) 2-4.5 and SSP 3-7.0] by the end of the twenty-first century. Our results find that the intensity of PLs is expected to decrease in the future while there is an expected increase in precipitation associated with PLs in the warming climate. These findings aim to contribute valuable insights for disaster management strategies in the face of evolving climate scenarios.

Pitch Actuator Fault-Tolerant Control of Wind Turbines via an L1 Adaptive Sliding Mode Control (SMC) Scheme

Effective fault identification and management are critical for efficient wind turbine operation. This research presents a novel L1 adaptive-SMC system designed to enhance fault tolerance in wind turbines, specifically addressing common issues such as pump wear, hydraulic leakage, and excessive air content in the oil. By combining SMC with L1 adaptive control, the proposed technique effectively controls rotor speed and power, ensuring reliable performance under various conditions. The controller employs an adjustable gain and an integrated sliding surface to maintain robustness. We validate the controller’s performance in the FAST (Fatigue, Aerodynamics, Structures, and Turbulence) simulation environment using a 5-megawatt wind turbine under high wind speeds. Simulation results demonstrate that the proposed L1 adaptive-SMC outperforms traditional adaptive-SMC and adaptive control schemes, particularly in the presence of faults, unknown disturbances, and turbulent wind fields. This research highlights the controller’s potential to significantly improve the reliability and efficiency of wind turbine operations.

Impact of sampling depth on CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document} flux estimates

The exchange of trace gases between the atmosphere and the ocean plays a key role in the Earth’s climate. Fluxes at the air-sea interface are affected mainly by wind blowing over the ocean and seawater temperature and salinity changes. This study aimed to quantify the use of CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document} partial pressure (pCO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document}) measurements at different depths (1, 5, and 10 m) in ocean surface layers to determine CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document} fluxes (FCO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document}) and to investigate the impacts of wind-sheltered and wind-exposed regions on the carbon budget. Vertical profiles of temperature, salinity, and pCO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document} were considered during a daily cycle. pCO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document} profiles exhibited relatively high values during sunny hours, associated with relatively high sea temperatures. However, the largest FCO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document} corresponded with higher wind speeds. Estimated fluxes between measurements at 1 and 10 m depths decreased by 71% in the sheltered region and 44% in the exposed region. According to the SOCAT dataset, at a depth of 5 m, the Atlantic basin emits approximately 0.29 Tg month-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{-1}$$\\end{document} of CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document} to the atmosphere; nevertheless, our estimates suggest that FCO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document} at the surface is 12.02 Tg month-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{-1}$$\\end{document}, which is 97.6% greater than that at 5 m depth. Therefore, future studies should consider sampling depth to adequately estimate the FCO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document}.

Hybrid CMOD-Diffusion Algorithm Applied to Sentinel-1 for More Robust and Precise Wind Retrieval

Synthetic Aperture Radar (SAR) imagery presents significant advantages for observing ocean surface winds owing to its high spatial resolution and low sensitivity to extreme weather conditions. Nevertheless, signal noise poses a challenge, hindering precise wind retrieval from SAR imagery. Moreover, traditional geophysical model functions (GMFs) often falter, particularly in accurately estimating high wind speeds, notably during extreme weather phenomena like tropical cyclones (TCs). To address these limitations, this study proposes a novel hybrid model, CMOD-Diffusion, which integrates the strengths of GMFs with data-driven deep learning methods, thereby achieving enhanced accuracy and robustness in wind retrieval. Based on the coarse estimation of wind speed by the traditional GMF CMOD5.N, we introduce the recently developed data-driven method Denoising Diffusion Probabilistic Model (DDPM). It transforms an image from one domain to another domain by gradually adding Gaussian noise, thus achieving denoising and image synthesis. By introducing the DDPM, the noise from the observed normalized radar cross-section (NRCS) and the residual of the GMF methods can be largely compensated. Specifically, for wind speeds within the low-to-medium range, a DDPM is employed before proceeding to another CMOD iteration to recalibrate the observed NRCS. Conversely, a posterior-placed DDPM is applied after CMOD to reconstruct high-wind-speed regions or TC-affected areas, with the prior information from regions characterized by low wind speeds and recalibrated NRCS values. The efficacy of the proposed model is evaluated by using Sentinel-1 SAR imagery in vertical–vertical (VV) polarization, collocated with data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Experimental results based on validation sets demonstrate significant improvements over CMOD5.N, particularly in low-to-medium wind speed regions, with the Structural Similarity Index (SSIM) increasing from 0.76 to 0.98 and the Root Mean Square Error (RMSE) decreasing from 1.98 to 0.63. Across the entire wind field, including regions with high wind speeds, the validation data obtained through the proposed method exhibit an RMSE of 2.39 m/s, with a correlation coefficient of 0.979.

A long-term Doppler wind LiDAR study of heavy pollution episodes in western Yangtze River Delta region, China

Previous studies are primarily based on surface air pollution for a single event, leaving research on the temporal characteristics of aerosols and wind fields in the atmospheric boundary layer (ABL) and their associations unclear due to a lack of long-term vertical profile data. This study was the first to conduct long-term Doppler wind LiDAR measurements from Sep. 2019 to Aug. 2022 in Hefei in western Yangtze River Delta (YRD) region, China. The spatiotemporal characteristics of retrieved aerosol backscatter coefficient (β) and wind profiles were analyzed from the perspective of long-term statistics and typical heavy pollution episodes (HPEs). The seasonal profile of β showed a peak in the near-surface layer meanwhile the overall β profile (<0.5 km) was the highest in winter but lowest in summer. Combined with ground-based meteorological and air quality observations, 12 HPEs were identified and classified into dust-related events and fog-haze episodes. The results showed a consistency between hourly variations in PM10 (particulate matter smaller than 10 μm) concentration and β retrieved at 300 m during a high PM10 concentration (>150 μg/m3) period. Different roles of horizontal wind at different altitudes and its associated time delay effect on surface PM10 pollution were evaluated based on correlation coefficients (Ф) and air pollution diffusion conditions. Significant positive Ф values were noticed below 0.5 km during the entire dust-related EP4 and EP6, indicating that the higher wind speeds could exacerbate PM10 pollution. In contrast, large negative Ф values meant the removal of PM10 pollutants by strong winds below 0.8 km during 24 h after peak in EP3. Combining with backward trajectory analysis and meteorological condition, notable transboundary pollution with positive contributions from upper winds (>1.5 km) was discovered in dust-related EP1, EP4, EP7, EP9, and EP10. Time delay effect (1-h/2-h lag) of upper winds (>0.8 km) on surface PM10 pollution was explored in EP5, EP6, EP7, EP8, and EP9. In spring dust-related HPEs, surface PM10 pollution was mostly contributed by long-range transport of aerosol particles at higher altitudes (>1.5 km) from the northwest direction, driven by the Mongolian cyclone and the cold front system. Transboundary aerosols originated from the northern part of Anhui province and the YRD region in the middle altitudes (∼0.5 km) was the main contributor to fog-haze HPEs. The findings demonstrated the ability of the real-time Doppler wind LiDAR system to monitor transboundary air pollution and provided a scientific reference for policy makers.

Enhanced Analysis of Ice Accretion on Rotating Blades of Horizontal-Axis Wind Turbines Using Advanced 3D Scanning Technology

This study investigated the meteorological conditions leading to ice formation on wind turbines in a coastal mountainous area. An enhanced ice formation similarity criterion was developed for the experimental design, utilizing a scaled-down model of a 1.5 MW horizontal-axis wind turbine in icing wind tunnel tests. Three-dimensional ice shapes on the rotating blades were obtained and scanned using advanced 3D laser measurement technology. Post-processing of the scanned data facilitated the construction of solid models of the ice-covered blades. This study analyzed the maximum ice thickness, ice-covered area, and dimensionless parameters such as the maximum dimensionless ice thickness and dimensionless ice-covered area along the blade. Under the experimental conditions, the maximum ice thickness reached 0.5102 m, and the ice-covered area extended up to 0.5549 m2. The dimensionless maximum ice thickness and dimensionless ice-covered area consistently increased along the blade direction. Our analysis of 3D ice shape characteristics and the ice volume under different test conditions demonstrated that wind speed and the liquid water content (LWC) are critical factors affecting ice formation on blade surfaces. For a constant tip speed ratio, higher wind speeds and a greater LWC resulted in increased ice volumes on the blade surfaces. Specifically, increasing the wind speed can augment the ice volume by up to 57.2%, while increasing the LWC can enhance the ice volume by up to 149.2% under the experimental conditions selected in this study.

Ocean Wave Directional Distribution from GPS Buoy Observations off the West Coast of Ireland: Assessment of a Wavelet-Based Method

Abstract Knowledge of the directional distribution of a wave field is crucial for a better understanding of complex air–sea interactions. However, the dynamic and unpredictable nature of ocean waves, combined with the limitations of existing measurement technologies and analysis techniques, makes it difficult to obtain precise directional information, leading to a poor understanding of this important quantity. This study investigates the potential use of a wavelet-based method applied to GPS buoy observations as an alternative approach to the conventional methods for estimating the directional distribution of ocean waves. The results indicate that the wavelet-based estimations are consistently good when compared to the framework of widely used parameterizations for the directional distribution. The wavelet-based method presents advantages in comparison with the conventional methods, including being purely data-driven and not requiring any assumptions about the shape of the distribution. In addition, it was found that the wave directional distribution is narrower at the spectral peak and broadens asymmetrically at higher and lower scales, particularly sharply for frequencies below the peak. The directional spreading appears to be independent of the wave age across the entire range of frequencies, implying that the angular width of the directional spectrum is primarily controlled by nonlinear wave–wave interactions rather than by wind forcing. These results support the use of the wavelet-based method as a practical alternative for the estimation of the wave directional distribution. In addition, this study highlights the need for continued innovation in the field of ocean wave measuring technologies and analysis techniques to improve our understanding of air–sea interactions. Significance Statement This study presents a wavelet-based technique for obtaining the directional distribution of ocean waves applied to GPS buoy. This method serves as an alternative to conventional methods and is relatively easy to implement, making it a practical option for researchers and engineers. The study was conducted in a highly energetic environment characterized by high wind speeds and large waves, providing a valuable dataset for understanding the dynamics of marine environment in extreme conditions. This research has implications for improving our understanding of directional characteristics of ocean waves, which is crucial for navigation, offshore engineering, weather forecasting, and coastal hazard mitigation. This study also highlights the challenges associated with understanding wave directionality and emphasizes a need for further observations.

Global assessment of production benefits and risk reduction in agroforestry during extreme weather events under climate change scenarios

Climate change and extreme weather events are threatening agricultural production worldwide. The anticipated increase in atmospheric temperature may reduce the potential yield of cultivated crops. Agroforestry is regarded as a climate-resilient system that is profitable, sustainable, and adaptable, and has strong potential to sequester atmospheric carbon. Agroforestry practices enhance agroecosystems’ resilience against adverse weather conditions via moderating extreme temperature fluctuations, provisioning buffers during heavy rainfall events, mitigating drought periods, and safeguarding land resources from cyclones and tsunamis-type events. Therefore, it was essential to comprehensively analyze and discuss the role of agroforestry in providing resilience during extreme weather situations. We hypothesized that integrating trees in to the agro-ecosystems could increase the resilience of crops against extreme weather events. The available literature showed that the over-story tree shade moderates the severe temperature (2–4°C) effects on understory crops, particularly in the wheat and coffee-based agroforestry as well as in the forage and livestock-based silvipasture systems. Studies have shown that intense rainstorms can harm agricultural production (40–70%) and cause waterlogging. The farmlands with agroforestry have been reported to be more resilient to heavy rainfall because of the decrease in runoff (20–50%) and increase in soil water infiltration. Studies have also suggested that drought-induced low rainfall damages many crops, but integrating trees can improve microclimate and maintain crop yield by providing shade, windshield, and prolonged soil moisture retention. The meta-analysis revealed that tree shelterbelts could mitigate the effects of high water and wind speeds associated with cyclones and tsunamis by creating a vegetation bio-shield along the coastlines. In general, existing literature indicates that implementing and designing agroforestry practices increases resilience of agronomic crops to extreme weather conditions increasing crop yield by 5–15%. Moreover, despite its widely recognized advantages in terms of resilience to extreme weather, the systematic documentation of agroforestry advantages is currently insufficient on a global scale. Consequently, we provide a synthesis of the existing data and its analysis to draw reasonable conclusions that can aid in the development of suitable strategies to achieve the worldwide goal of adapting to and mitigating the adverse impacts of climate change.

Numerical simulation of dust deposition characteristics of photovoltaic arrays taking into account the effect of the row spacing of photovoltaic modules

Dust deposition on the surfaces of Photovoltaic (PV) arrays during their operation markedly affects their power generation efficiency. Previous research has overlooked the impact of the row spacing of PV modules on the actual dust deposition on PV arrays. This study investigates the dust deposition process and its behavior on PV arrays considering variations in row spacings, inlet wind speeds, dust particle sizes, and dust particle counts. By employing commercial Computational Fluid Dynamics (CFD) software, incorporating the SST k-ω turbulence model and discrete particle model, numerical simulations were performed to analyze the airflow field, dust particle trajectories, dust deposition patterns, and deposition rates on the PV array through grid-independent verification and numerical validation. At the same time, we performed a comparative analysis of the deposition rate considering the rebound of dust particles on the PV module surface versus the case where rebound is not considered. Results revealed that the maximum dust deposition rates at different inlet wind speeds were 6.84 %, 8.84 %, 11.0 %, and 14.6 %, corresponding to dust sizes of 50 μm, 100 μm, 120 μm, and 300 μm, respectively. Smaller dust particles exhibited lower deposition rates, while larger particles were influenced more by mass inertia and gravity, leading to predominant deposition on the front row of PV modules. Larger dust particles are more likely to deposit primarily on the front row of PV modules in a PV array. The tilt angles of 30°, 45°, and 60° were chosen to study the effects of different tilt angles on the dust deposition of PV arrays, and the results show that the dust deposition rate decreases as the tilt angle increases, and it is worth noting that the larger the tilt angle, the larger the dust deposition rate is when the dust particles are especially small as 5 μm. When wind speeds are low and dust particles are small, the dust deposition rate gradually rises as the row spacing increases. However, at higher wind speeds with small dust particles, the row spacing has minimal impact on the dust deposition rate. Conversely, with larger dust particles, increasing the row spacing results in a lower dust deposition rate. These findings underscore the significance of optimizing PV array design for enhanced power generation efficiency.

Understanding environmental drivers and trends in chlorophyll-a and related factors across equatorial Indian Ocean regions: implications for marine ecosystem dynamics and vulnerability

ABSTRACT We estimated the concentration of Chlorophyll-a (Chl-a) along with physical and biological factors including sea surface temperature (SST), wind speed and concentration of nitrate and phosphate in the Western, Central and Eastern Equatorial Indian Oceans (WEIO, CEIO and EEIO) using data from the Copernicus Marine Service and ERA-5 for the years 1994 to 2019. Our results show that along with the concentration of Chl-a, nitrate and phosphate have decreased, and sea surface temperature has increased in the EEIO. Due to coastal upwelling off the coast of Somalia and offshore Ekman transport throughout the summer, the southwest monsoon caused a significant increase in concentrations of Chl-a, nitrate, phosphate and wind speed in WEIO during June-July-August-September (JJAS) and October-November-December (OND). SST decreased at this time and deeper water interacted with surface water, increasing biological production. In EEIO, the upwelling zone is primarily maintained by wind-induced divergence throughout the year, whereas stratification in winter prevented surface Chl-a increase. High wind speed and low SST led to increased productivity in WEIO. Comparison of EEIO with WEIO and CEIO demonstrates low levels of Chl-a, phosphate and nitrate. The trends signify that these oceanic zones are highly vulnerable to developing into ecological deserts in the near future.

Energy and exergy analysis of an innovative solar system for hydrothermal carbonization process using photovoltaic solar panels

Using renewable energy is a solution to combat environmental problems; in this context, hydrothermal carbonization is an excellent method for converting biomass into solid fuels. However, this process is energy-intensive. Systems utilizing parabolic trough solar collectors proposed in the literature present some limitations and challenges. Therefore, to overcome this issue, a novel conception combining photovoltaic solar panels and a batch reactor with a heating collar has been proposed. It was experimentally investigated and subjected to energy and exergy analyses. The experimental results showed that subcritical conditions (220 °C temperature and 40 bar pressure) were achieved. The chemical exergy of the biomass increased from 19.89 MJ/kg to 29.2 MJ/kg for the hydrochar. Due to dehydration and decarboxylation, the O/C and H/C atomic ratios decreased over time, and the hydrochar properties approximated lignite. The solar panel system achieved average energy and exergy efficiencies of 14 % and 15 %, respectively, with high thermal exergy destruction of 825.94 kWh under higher wind speeds and cell temperatures, resulting in a total entropy of 1.4 kW/K. The system's Improvement Potential ranged from 15 kW to 23 kW. The results demonstrate the feasibility of this innovative system to achieve the necessary conditions for HTC in an environmentally friendly manner.

A simplified approach to modeling temperature dynamics in photovoltaic systems – Validation, case studies, and parametric analysis

This paper presents a simplified theoretical model for analyzing the temperature dynamics of photovoltaic (PV) modules. The model is built on an energy balance approach, considering solar irradiation as the primary energy input. It accounts for the conversion of solar power into electricity and the storage of thermal energy within the PV module, which subsequently increases the PV temperature leading to decay in its electrical efficiency. Heat loss from the top and bottom surfaces of the module, with variations for cooling techniques, is also included. The model is validated against three different experimental studies, demonstrating good agreement with the experimental temperature variations, with a maximum discrepancy ranging from 4 % to 16 %. This simplified model is then applied to two case studies: one representing typical daytime conditions and another simulating cold weather events. By comparing the PV temperature dynamics between the model and the experimental data, it is shown that the model accurately captures the dynamic response of the PV temperatures to changes in solar irradiation and ambient temperatures. Moreover, a parametric analysis is conducted to investigate the effects of key parameters on PV temperature and efficiency. Higher cooling rates from the bottom surface significantly boost electric power output, aligning closely with solar irradiance variations. Enhanced upper surface cooling, through increased convection, reduces PV temperature and thereby improves electric efficiency and power production. The PV temperature increases quasi-linearly with ambient temperature, especially at lower wind speeds, and decreases with higher wind speeds, eventually stabilizing at high values. Additionally, both ambient temperature and solar irradiance contribute to rising PV temperatures, with ambient temperature having a slightly greater effect. These findings underscore the critical role of cooling techniques in optimizing PV performance amidst varying environmental conditions.

Dynamic swatch testing of liquid aerosols in a laboratory-sized recirculating wind tunnel

Chemical warfare agents (CWAs) pose a threat as gaseous substances and as liquid aerosols, necessitating chemical warfare-protective clothing for soldiers. The paramount consideration lies in the effectiveness of the clothing as a barrier against the pertinent CWAs. This paper presents a dynamic swatch test method aimed at evaluating the performance of such clothing against liquid-phase aerosol penetration. Central to the methodology is a specialized test cell designed to rotate to the left and right, integrated within a laboratory wind tunnel, replicating mission-relevant conditions with varying wind speeds. Utilizing di(2-ethylhexyl) sebacate particles as liquid aerosols, tests were conducted at wind speeds of 1.0, 3.0, and 5.0 m/s. Penetration assessment relied on analyzing particle counts downstream and upstream of the fabric, with preliminary studies showing that higher wind speeds and fabric air permeabilities increase penetration at an equivalent face velocity of 5.0 cm/s. Interestingly, penetration decreased when fabric samples were subjected to rotation. The system and methodology devised demonstrated consistent and repeatable results, offering valuable insights into optimizing the effectiveness of chemical warfare-protective clothing. This research contributes to advancing methodologies for testing protective clothing, crucial for ensuring the safety of military personnel in hazardous environments.

Spatiotemporal variability and underlying large‐scale atmospheric mechanisms causing the change in the Black Sea surface temperature and associated extreme precipitation events in the northeastern of Turkiye

AbstractSea surface temperature (SST) has an important local and remote influence on global climate through the distribution and transport of heat and moisture. As a result of climate forcing, significant changes occur in the SSTs, which result in many natural disasters such as supercharged storms, higher wind speeds, heavier precipitation and flooding. This study investigates the spatiotemporal changes and underlying atmospheric mechanisms of the Black Sea (BLS) surface temperature. For this purpose, National Oceanicand Atmospheric Administration (NOAA) high‐resolution SST data (0.25°), which were verified with buoy observations, were used for the period 1982–2021. To investigate the circulation impacts, the relationship between North Atlantic Oscillation and East Atlantic/West Russia (EA/WR) phases and SSTs of the western BLS (WBLS) and eastern BLS (EBLS) was analysed. According to the results, SST values increased from 1.64°C (in winter) to 2.52°C (in summer) during the 40‐year period. Significant SST increases are shown in the EBLS during the summer and fall months. Statistically significant negative correlations (p &lt; 0.05) were found between EA/WR and winter (r = −0.57) and summer (r = −0.56) SSTs in the EBLS. During winter, surface high located in the eastern Anatolia causes southerly winds, which blows from the terrestrial areas to the EBLS and result in above‐normal SST values. During summer (under negative EA/WR phases), the Azores high‐pressure centre extends to the Balkan Peninsula and WBLS and as a consequence, a significant amount of moisture associated with high sea surface temperature (&gt;27°C, above‐normal 2.0°C) develops low‐level moisture convergence. Proper synoptic conditions, strong instability conditions between the surface and upper levels, and orographic forcing enable the occurrence of convective cloud cells. The movement of these cells to the northeastern part of Turkiye by strong northwesterly winds causes extreme precipitation and associated flash‐flood events in a limited area where land–sea interaction occurs (i.e., Artvin, Rize and Hopa provinces of Turkiye).

Effects of Wind Speed on Size-Dependent Morphology and Composition of Sea Spray Aerosols.

Variable wind speeds over the ocean can have a significant impact on the formation mechanism and physical-chemical properties of sea spray aerosols (SSA), which in turn influence their climate-relevant impacts. Herein, for the first time, we investigate the effects of wind speed on size-dependent morphology and composition of individual nascent SSA generated from wind-wave interactions of natural seawater within a wind-wave channel as a function of size and their particle-to-particle variability. Filter-based thermal optical analysis, atomic force microscopy (AFM), AFM infrared spectroscopy (AFM-IR), and scanning electron microscopy (SEM) were employed in this regard. This study focuses on SSA with sizes within 0.04-1.8 μm generated at two wind speeds: 10 m/s, representing a wind lull scenario over the ocean, and 19 m/s, indicative of the wind speeds encountered in stormy conditions. Filter-based measurements revealed a reduction of the organic mass fraction as the wind speed increases. AFM imaging at 20% relative humidity of individual SSA identified six main morphologies: prism-like, rounded, core-shell, rod, rod inclusion core-shell, and aggregates. At 10 m/s, most SSA were rounded, while at 19 m/s, core-shells became predominant. Based on AFM-IR, rounded SSA at both wind speeds had similar composition, mainly composed of aliphatic and oxygenated species, whereas the shells of core-shells displayed more oxygenated organics at 19 m/s and more aliphatic organics at 10 m/s. Collectively, our observations can be attributed to the disruption of the sea surface microlayer film structure at higher wind speeds. The findings reveal a significant impact of wind speed on morphology and composition of SSA, which should be accounted for accurate assessment of their climate effects.

Quantitative analysis of aeolian dust incidence and diagnosis using a dynamic Bayesian network model: A case study of estuary area in central Taiwan

The presence of high concentrations of PM10 in aeolian dust within the estuary area of central Taiwan has been a focal point for air quality protection and remediation efforts over the past 15 years. This study explores the quantitative analysis of aeolian dust occurrences concerning various levels of PM10 concentration, aiming to offer early warning information to local communities and government agencies. Employing Dynamic Bayesian network (DBN) models, the research interrelates conditional probability dependencies among air quality and meteorological factors monitored in the downstream area of the Jhuoshuei River, predicting the probability distribution of aeolian dust events. The constructed DBNs demonstrate the inference of probability distributions of meteorological factors' states based on PM10 concentrations, enabling diagnostic analysis of meteorological conditions during high PM10 concentration dust events. The DBN models exhibit robust predictive ability, achieving an overall accuracy of 85.72% in validation and 85.8% in testing, with high discriminatory capacity that the area under the receiver operating characteristic curve (AUC) values of 0.924 and 0.915 during validation and testing, respectively. Sensitivity analysis highlights wind direction, wind speed, relative humidity as significant factors affecting PM10 concentrations. The probability of low PM10 concentrations was notably higher compared to higher concentrations, indicating effective aeolian dust remediation efforts. However, attention is warranted toward the 10% incidence of aeolian dust events deemed unhealthy or hazardous to human health. Diagnosis of meteorological conditions during high PM10 concentration events suggests low temperature, high wind speeds, and dry conditions, particularly with northeastern or southwestern winds, as conducive factors. This study underscores the physical relationship between meteorological factors and PM10 concentrations, employing DBNs to consider temporal relationships and uncertainties in data, aligning with human health impact standards proposed by the Ministry of Environment. Future research should incorporate soil and land surface conditions to provide a more comprehensive understanding of aeolian dust dynamics and mitigation strategies.

Effects of Wind Speed and Heat Flux on De-Icing Characteristics of Wind Turbine Blade Airfoil Surface

The icing on wind turbines reduces their aerodynamic performance and can cause other safety issues. Accordingly, in this paper, the de-icing characteristics of a wind turbine blade airfoil under different conditions are investigated using numerical simulation. The findings indicate that when the de-icing time is 10 s, the peak ice thickness on the leading edge of the airfoil surface decreases from 0.28 mm to 0.068 mm and from 0.77 mm to 0.45 mm at low (5 m/s) and high (15 m/s) wind speeds, respectively. This is due to the fact that the ice melting rate is much greater than the icing rate at low wind speeds, while the icing rate increases at high wind speeds. When the de-icing time is 20 s, ice accretion on the leading edge of the airfoil is completely melted. At a low heat flux (8000 W/m2) and high heat flux (12,000 W/m2), the peak ice thickness decreases by 31.2% and 64.9%, respectively. With an increase in de-icing time and heat flux, the peak thickness of runback ice increases. This is due to an increase in runback ice as a result of more ice melting on the leading edge of the airfoil. The surface temperature in the ice-free area is significantly higher than that in the ice-melting area, due to high thermal resistance in the ice-free area. This study will provide guidance for the thermal distribution and coating layout of a wind turbine blade airfoil to make the anti-/de-icing technology more efficient and energy-saving.

Microbially induced calcium carbonate precipitation to combat desertification: A field application experiment

Combating desertification and recovering vegetation can help resolve global ecological problems. Microbially induced calcium carbonate precipitation is a natural and widespread phenomenon that has been a green and efficient approach for environmental issues. However, long-term field experiments are lacking and microbially induced calcium carbonate precipitation biological routes for desert restoration is unclear. Therefore, we investigated soil wind erosion resistance and soil characteristics via mixed methodology involving field and laboratory experiments and revealed the biological route. Our objective was to evaluate sand fixation efficiency and clarify the biological route. Results demonstrated that (1) microbially induced calcium carbonate precipitation produced sand cement, increased soil hardness, and changed soil characteristics. (2) Compared with CK, 25%, 50% and 75% treatments (MICP treatment from low to high concentration) reduced soil loss by 34.93%, 31.62% and 51.93%, respectively, and wind erosion decreased by 69.09%–77.27% at highest wind speed. (3) The 75% treatment had the greatest effect on wind erosion resistance. (4) Microbial activity changes the mechanism of wind erosion which meteorological effects change from direct to indirect after treatment. These results can address challenges and overcome the natural disadvantages of microbially induced calcium carbonate precipitation and contribute to technologies for combating desertification using soil microbial approaches.

Air quality in a revitalized special economic zone at the center of an urban monocentric agglomeration

In this study, we have examined the air quality within a revitalized, post-industrial urban area in Łódź, Poland. The use of Dron technology with mobile measurement equipment allowed for accurate assessment of air quality (particulate matter and gaseous pollutants) and factors influencing air quality (wind speed and direction) on a local scale in an area of 0.18 km2 and altitudes from 2 to 50 m. The results show that the revitalization carried out in the Lodz special economic zone area contributed to eliminate internal air pollution emitters through the use of ecological and effective heat sources. The exceedances permissible concentration values were local, and concerned mainly the higher measurement zones of the troposphere (more than 30 m above ground level). In the case of gaseous pollutants, higher wind speeds were associated with a decrease in the concentration of SO2 and an increase in H2S concentration. In both cases, the wind contributed to the occurrence of local areas of accumulation of these gaseous pollutants in the spaces between buildings or wooded areas.