Steady as they hover: kinematics of kestrel wing and tail morphing during hovering flights.

Wind-hovering birds exhibit remarkable steadiness in flight, achieved through the morphing of their wings and tail. We analysed the kinematics of two nankeen kestrels (Falco cenchroides) engaged in steady wind-hovering flights in a smooth flow wind tunnel. Motion-tracking cameras were used to capture the movements of the birds as they maintained their position. The motion of the birds' head and body, and the morphing motions of their wings and tail were tracked and analysed using correlation methods. The results revealed that wing sweep, representing the flexion/extension movement of the wing, played a significant role in wing motion. Additionally, correlations between different independent degrees of freedom (DoF), including wing and tail coupling, were observed. These kinematic couplings indicate balancing of forces and moments necessary for steady wind hovering. Variation in flight behaviour between the two birds highlighted the redundancy of DoF and the versatility of wing morphing in achieving control. This study provides insights into fixed-wing craft flight control from the avian world and may inspire novel flight control strategies for future fixed-wing aircraft.

Do offshore wind farms promote the expansion and proliferation of non-indigenous invertebrate species?

Based on a search of publications in the scientific literature as well as international reports available online, I draw up a list of 25 documents which include cross-references to the terms offshore wind farms (OFW), and non-indigenous species (NIS). This review shows that no relationship has yet been clearly established between the implementation of OFWs and the colonization of NIS on turbine foundations and scour protections. Evidence for such an effect needs to be documented and confirmed in the future.

Natural Seismic Event Analysis Based on Signal and Source Characteristics from two Experiments in Antarctica.

This study presents geophysical data from two passive seismic measurements conducted at two different sites in Antarctica. We analyzed the signals mainly in the frequency domain through the multitaper method to extract some spectral characteristics of the signals that would have been out of reach through the usual FFT approach. The power spectral density of the signals carries information about the processes that generated them, allowing its correlation with their source origin and type, either natural or anthropogenic. We deal with three different source types: calving, wind, and anthropogenic origins. The former is closely related to glacier dynamics, being modulated by the prevailing atmospheric processes. At both locations the wind noise is prevalent, complicating the analysis of other events like calving. We have used data classification, estimation of the source azimuth, and seismic apparent velocity to demonstrate the viability of using geophysical methods to study glacier elastic parameters and dynamics. Moreover, the calving rate can yield a wider and more independent understanding of glacier hydrodynamics and may help to estimate the future response of the polar areas to a changing environment.

Assessing the accuracy of spectral indices obtained from Sentinel images using field research to estimate land degradation.

Wind erosion resulting from soil degradation is a significant problem in Iran's Baluchistan region. This study evaluated the accuracy of remote sensing models in assessing degradation severity through field studies. Sentinel-2 Multispectral Imager's (MSI) Level-1C satellite data was used to map Rutak's degradation severity in Saravan. The relationship between surface albedo and spectral indices (NDVI, SAVI, MSAVI, BSI, TGSI) was assessed. Linear regression establishes correlations between the albedo and each index, producing a degradation severity map categorized into five classes based on albedo and spectral indices. Accuracy was tested with 100 ground control points and field observations. The Mann-Whitney U-Test compares remote sensing models with field data. Results showed no significant difference (P > 0.05) between NDVI, SAVI, and MSAVI models with field data, while BSI and TGSI models exhibited significant differences (P ≤ 0.001). The best model, BSI-NDVI, achieves a regression coefficient of 0.86. This study demonstrates the advantage of remote sensing technology for mapping and monitoring degraded areas, providing valuable insights into land degradation assessment in Baluchistan. By accurately identifying severity levels, informed interventions can be implemented to mitigate wind erosion and combat soil degradation in the region.

Wind power density in areas of Northeastern Brazil from Regional Climate Models for a recent past.

Investments in renewable energy sources are increasing in several countries, especially in wind energy, as a response to global climate change caused by the burning of fossil fuels for electricity generation. Thus, it is important to evaluate the Regional Climate Models that simulate wind speed and wind power density in promising areas for this type of energy generation with the least uncertainty in recent past, which is essential for the implementation of wind farms. Therefore, this research aims to calculate the wind power density from Regional Climate Models in areas at Northeast of Brazil from 1986 to 2005. Initially, the ECMWF-ERA5 reanalysis data was validated against observed data obtained from Xavier. The results were satisfactory, showing a strong correlation in areas of Ceará and Rio Grande do Norte (except during the SON season), and some differences in relation to the wind intensity registered by observed data, particularly during the JJA season. Then, the Regional Climate Models RegCM4.7, RCA4 and Remo2009 were validated against the ECMWF-ERA5 reanalysis data, with all models successfully representing the wind speed pattern, especially from December to May. Four specific areas in Northeast of Brazil were selected for further study. In these areas, the RCMs simulations were evaluated to identify the RCM with the best statistical indices and consequently the lowest associated uncertainty for each area. The selected RCMs were: RegCM4.7_HadGEM2 (northern coastal of Ceará and northern coastal of Rio Grande do Norte) and RCA4_Miroc (Borborema and Central Bahia). Finally, the wind power density was calculated from the selected RCM for each area. The northern regions of Rio Grande do Norte and Ceará exhibited the highest wind power density.

Dynamics of Noctiluca scintillans blooms: A 20-year study in Jangmok Bay, Korea.

This 20-year study (2001-2020) conducted in Jangmok Bay, Korea, assessed the intricate relationships between environmental factors and Noctiluca scintillans blooms. Granger causality tests and PCA analysis were used to assess the impact of sea surface temperature (SST), salinity, dissolved oxygen (DO) concentration, wind patterns, rainfall, and chlorophyll-a (Chl-a) concentration on bloom dynamics. The results revealed significant, albeit delayed, influences of these variables on bloom occurrence, with SST exhibiting a notable 2-month lag and salinity a 1-month lag in their impact. Additionally, the analysis highlighted the significant roles of phosphate, ammonium, and silicate, which influenced N. scintillans blooms with lags of 1 to 3 months. The PCA demonstrates how SST and wind speed during spring and summer, along with wind direction and salinity in winter, significantly impact N. scintillans blooms. We noted not only an increase in large-scale N. scintillans blooms but also a cyclical pattern of occurrence every 3 years. These findings underscore the synergistic effects of environmental factors, highlighting the complex interplay between SST, salinity, DO concentration, and weather conditions to influence bloom patterns. This research enhances our understanding of harmful algal blooms (HABs), emphasizing the importance of a comprehensive approach that considers multiple interconnected environmental variables for predicting and managing N. scintillans blooms.

Deeper and stronger North Atlantic Gyre during the Last Glacial Maximum.

Subtropical gyre (STG) depth and strength are controlled by wind stress curl and surface buoyancy forcing1,2. Modern hydrographic data reveal that the STG extends to a depth of about 1 km in the Northwest Atlantic, with its maximum depth defined by the base of the subtropical thermocline. Despite the likelihood of greater wind stress curl and surface buoyancy loss during the Last Glacial Maximum (LGM)3, previous work suggests minimal change in the depth of the glacial STG4. Here we show a sharp glacial water mass boundary between 33° N and 36° N extending down to between 2.0 and 2.5 km-approximately 1 km deeper than today. Our findings arise from benthic foraminiferal δ18O profiles from sediment cores in two depth transects at Cape Hatteras (36-39° N) and Blake Outer Ridge (29-34° N) in the Northwest Atlantic. This result suggests that the STG, including the Gulf Stream, was deeper and stronger during the LGM than at present, which we attribute to increased glacial wind stress curl, as supported by climate model simulations, as well as greater glacial production of denser subtropical mode waters (STMWs). Our data suggest (1) that subtropical waters probably contributed to the geochemical signature of what is conventionally identified as Glacial North Atlantic Intermediate Water (GNAIW)5-7 and (2) the STG helped sustain continued buoyancy loss, water mass conversion and northwards meridional heat transport (MHT) in the glacial North Atlantic.

A comprehensive review of sustainable solutions for reusing wind turbine blade waste materials.

By 2050, approximately 43 million tons of wind-turbine blade (WTB) waste materials will have accumulated, emphasizing the critical importance of effective waste management strategies for WTBs at the end of their life cycle to ensure sustainability. Comparing current WTB waste management methods, reuse emerges as a highly-sustainable method that can also serve as a sustainable solution to environmental challenges, including global warming and natural resource depletion associated with civil engineering activities. This paper presents a comprehensive review of sustainable solutions for reusing WTB waste materials in civil engineering applications. Repurposing WTB waste materials as structural elements in housing, urban furniture, recreational facilities, and slow-traffic infrastructure can be a viable option. WTB waste can also be utilized in powder, fiber, and aggregate forms as an eco-friendly material for construction and pavement (e.g., mortar, concrete, asphalt) to replace cement and natural resource aggregates while meeting necessary strength and performance standards. Through a detailed analysis of reusing WTB waste materials, economic and environmental challenges are also discussed. According to the findings, the properties of mortar, concrete, and asphalt can be affected by the type, shape, and content of fibers, polymers, and impurities present in the blades, as well as the cutting direction. Furthermore, while reuse is considered a sustainable end-of-life (EoL) option for WTB waste management from both economic and environmental perspectives, further research is required to fully understand the environmental consequences of this method.

Assessing spatial heterogeneity of nutrient loads in a large shallow lake using a lattice Boltzmann water quality model.

Nutrient loads in lakes are spatially heterogeneous, but current spatial analysis method are mainly zonal, making them subjective and uncertain. This study proposes a high-resolution model for assessing spatial differences in nutrient loads based on the lattice Boltzmann method. The model was applied to Dongping Lake in China. Firstly, the contribution rates of four influencing factors, including water transfer, inflow, wind, and internal load, were calculated at different locations in the lake. Then, their proportionate contributions during different intervals to the whole lake area were calculated. Finally, the cumulative load could be calculated for any location within the lake. The validation showed that the model simulated hydrodynamics and water quality well, with relative errors between the simulated and measured water quality data smaller than 0.45. Wind increased the nutrient loads in most parts of the lake. The loads tended to accumulate in the east central area where high-frequency circulation patterns were present. Overall, the proposed water quality model based on the lattice Boltzmann method was able to simulate seven indexes. Therefore, this model represents a useful tool for thoroughly assessing nutrient load distributions in large shallow lakes and could help refine lake restoration management.

Mapping the natural disturbance risk to protective forests across the European Alps.

Mountain forests play an essential role in protecting people and infrastructure from natural hazards. However, forests are currently experiencing an increasing rate of natural disturbances (including windthrows, bark beetle outbreaks and forest fires) that may jeopardize their capacity to provide this ecosystem service in the future. Here, we mapped the risk to forests' protective service across the European Alps by integrating the risk components of hazard (in this case, the probability of a disturbance occurring), exposure (the proportion of forests that protect people or infrastructure), and vulnerability (the probability that the forests lose their protective structure after a disturbance). We combined satellite-based data on forest disturbances from 1986 to 2020 with data on key forest structural characteristics (cover and height) from spaceborne lidar (GEDI), and used ensemble models to predict disturbance probabilities and post-disturbance forest structure based on topographic and climatic predictors. Wind and bark beetles are dominant natural disturbance agents in the Alps, with a mean annual probability of occurrence of 0.05%, while forest fires were less likely (mean annual probability <0.01%), except in the south-western Alps. After a disturbance, over 40% of forests maintained their protective structure, highlighting the important role of residual living or dead trees. Within 30 years after wind and bark beetle disturbance, 61% of forests were likely to either maintain or recover their protective structure. Vulnerability to fires was higher, with 51% of forest still lacking sufficient protective structure 30 years after fire. Fire vulnerability was especially pronounced at dry sites, which also had a high fire hazard. Combining hazard and vulnerability with the exposure of protective forests we identified 186 Alpine municipalities with a high risk to protective forests due to wind and bark beetles, and 117 with a high fire risk. Mapping the disturbance risk to ecosystem services can help identify priority areas for increasing preparedness and managing forests towards lower susceptibility under an intensifying disturbance regime.

Contrasting seasonal responses to wind in migrating songbirds on a globally important flyway.

During spring migration, nocturnal migrants attempt to minimize their travel time to reach their breeding grounds early. However, how they behave and respond to unfavourable conditions during their springtime travels is much less understood. In this study, we reveal the effects of atmospheric factors on nocturnal bird migration under adverse conditions during spring and autumn, based on one of the most detailed bird migration studies globally, using radar data from 13 deployments over a period of seven years (2014-2020) in the Levant region. Using ERA5 reanalysis data, we found that migratory birds maintain similar ground speeds in both autumn and spring migrations, but during spring, when encountering unfavourable winds, they put more effort into maintaining their travel speed by increasing self-powered airspeed by 18%. Moreover, we report for the first time that spring migrants showed less selectivity to wind conditions and migrated even under unfavourable headwind and crosswind conditions. Interestingly, we discovered that temperature was the most important weather parameter, such that warm weather substantially increased migration intensities in both seasons. Our results enhance our understanding of bird migration over the Levant region, one of the world's largest and most important migration flyways, and the factors controlling it. This information is essential for predicting bird migration, which-especially under the ongoing anthropogenic changes-is of high importance.

An artificial gorilla troops optimizer for stochastic unit commitment problem solution incorporating solar, wind, and load uncertainties.

The unit commitment (UC) optimization issue is a vital issue in the operation and management of power systems. In recent years, the significant inroads of renewable energy (RE) resources, especially wind power and solar energy generation systems, into power systems have led to a huge increment in levels of uncertainty in power systems. Consequently, solution the UC is being more complicated. In this work, the UC problem solution is addressed using the Artificial Gorilla Troops Optimizer (GTO) for three cases including solving the UC at deterministic state, solving the UC under uncertainties of system and sources with and without RE sources. The uncertainty modelling of the load and RE sources (wind power and solar energy) are made through representing each uncertain variable with a suitable probability density function (PDF) and then the Monte Carlo Simulation (MCS) method is employed to generate a large number of scenarios then a scenario reduction technique known as backward reduction algorithm (BRA) is applied to establish a meaningful overall interpretation of the results. The results show that the overall cost per day is reduced from 0.2181% to 3.7528% at the deterministic state. In addition to that the overall cost reduction per day is 19.23% with integration of the RE resources. According to the results analysis, the main findings from this work are that the GTO is a powerful optimizer in addressing the deterministic UC problem with better cost and faster convergence curve and that RE resources help greatly in running cost saving. Also uncertainty consideration makes the system more reliable and realistic.

An in-depth study of the oxidative liquefaction process for polymeric waste reduction and chemical production from wind turbine blades and personal protective equipment used in the medical field.

An in-depth study of the oxidative liquefaction process has been provided to degrade the polymeric waste from personal protective equipment (PPEs) and wind turbine blades (WTBs). Thermogravimetric investigations demonstrate that WTBs have three prominent peaks throughout the degradation, whereas PPEs display solitary peak features. Experiments are carried out employing specific experimental design approaches, namely the Central Composite Face-Centered Plan (CCF) for WTBs and the Central Composition Design with Fractional Factorial Design for PPEs in a batch-type reactor at temperature ranges of 250-350 °C, pressures of 20-40 bar, residence times of 30-90 min, H2O2 concentrations of 15-45 %, and waste/liquid ratios of 5-25 % for WTBs. These values were 200-300 °C, 30 bar, 45 min, 30-60 % and 5-7 % for PPE. A detailed comparison has been provided in the context of total polymer degradation (TPD) for PPE and WTBs. Liquid products from both types of wastes after the oxidative liquefaction process are subjected to gas chromatography with flame ionization detection (GC-FID) to identify the existence of oxygenated chemical compounds (OCCs). For WTBs, TPD was 20-49 % and this value was 55-96 % for PPE while the OCC yield for WTBs (36.31 g/kg - 210.59 g/kg) and PPEs (39.93 g/kg - 212.66 g/kg) was also calculated. Detailed optimization of experimental plans was carried out by performing the analysis of variance (ANOVA) and optimization goals were maximum TPD and OCCs yields against the minimum energy consumption, though a considerable amount of complex polymer waste can be reduced and high concentrations of OCC can be achieved, which could be applied for commercial and environmental benefits.

Recovering high-quality glass fibers from end-of-life wind turbine blades through swelling-assisted low-temperature pyrolysis.

The recycling of end-of-life wind turbine blades has become a global environmental challenge driven by the rapid growth of wind power. Pyrolysis is a promising method for recovering glass fibers from these discarded blades, but traditional pyrolysis is often operated at high temperatures, which degrades the mechanical properties of recovered fibers. To address this issue, a swelling-assisted pyrolysis method was proposed to recover high-quality glass fibers from end-of-life wind turbine blades at low temperatures. The results confirmed that the decomposition of the resin matrix within the blade was significantly promoted at low temperatures in the swelling-assisted pyrolysis process, achieving a resin decomposition ratio of 76.8 % at 350 °C. This improvement was attributed to enhanced heat transfer and co-pyrolysis with acetic acid. Swelling could physically disrupt the cross-linked structure of the blade, creating a more porous and layered structure, thereby enhancing heat transfer during the pyrolysis process. Simultaneously, the co-pyrolysis with acetic acid could generate hydrogen radicals, which promoted the cracking of macromolecular oligomers into lighter products or gaseous alkanes. Consequently, the formation of pyrolysis char within the solid pyrolysis product was reduced, shortening the oxidation duration to 30 min. In comparison to traditional pyrolysis, the swelling-assisted pyrolysis process effectively suppressed the diffusion of surface defects over the recovered fibers, leading to promising improvements in their flexibility, elasticity, and mechanical properties, with tensile strength notably increased by 27.5 %. These findings provided valuable insights into recovering high-quality glass fibers from end-of-life wind turbine blades.

Similar experimental study on diffusion and distribution of diesel exhaust in confined space of a coal mine.

In the confined space of the underground coal mine, which is dominated by transportation lanes, explosion-proof diesel-powered trackless rubber-wheeled vehicles are becoming the main transportation equipment, and the exhaust gas produced by them is hazardous to the health of workers and pollutes the underground environment. In this experiment, a similar test platform is built to study the effects of wind speed, vehicle speed, and different wind directions on the diffusion characteristics of exhaust gas. In this paper, CO and SO2 are mainly studied. The results show that the diffusion of CO and SO2 gas is similar and the maximum SO2 concentration only accounts for 11.4% of the CO concentration. Exhaust gas is better diluted by increasing the wind speed and vehicle speed, respectively. Downwind is affected by the reverse wind flow and diffuses to the driver's position, which is easy to cause occupational diseases. When the wind is a headwind, the exhaust gases spread upwards and make a circumvention movement, gathering at the top. When the wind speed and vehicle speed are both 0.6 m/s, the CO concentration corresponds to the change trend of the Lorentz function when the wind is downwind and the CO concentration corresponds to the change trend of the BiDoseResp function when the wind is headwind. The study of exhaust gas diffusion characteristics is of great significance for the subsequent purification of the air in the restricted mine space and the protection of the workers' occupational health.

Ecological and human health impact assessments based on long-term monitoring of soil PAHs near a coal-fired power plant.

The combustion of coal in power plants releases significant amounts of polycyclic aromatic hydrocarbons (PAHs), which are highly toxic and carcinogenic. This study assesses the ecological and human health impacts of PAHs contamination from a coal-fired power plant over 8 years. The monitoring site selection considered the distance from the power plant and the prevailing wind direction in the investigated area. The results reveal that, during the monitoring period, PAH levels increased on average by 43%, 61%, and 37% in the zone of the prevailing wind direction, in the area proximate to the power plant, and the zone distant from it, respectively. The site, which has a radius of 4.5 km in the prevailing wind direction, exhibited the highest ecological and human health impacts. Additionally, a strong correlation was observed between environmental and human health impacts, depending on the distance from the power plant, particularly in areas with the prevailing wind direction. These insights contribute to a comprehensive understanding of the intricate dynamics linking power plant emissions, PAHs contamination, and their far-reaching consequences on the environment and human health.

Windy events detection in big bioacoustics datasets using a pre-trained Convolutional Neural Network.

Passive Acoustic Monitoring (PAM), which involves using autonomous record units for studying wildlife behaviour and distribution, often requires handling big acoustic datasets collected over extended periods. While these data offer invaluable insights about wildlife, their analysis can present challenges in dealing with geophonic sources. A major issue in the process of detection of target sounds is represented by wind-induced noise. This can lead to false positive detections, i.e., energy peaks due to wind gusts misclassified as biological sounds, or false negative, i.e., the wind noise masks the presence of biological sounds. Acoustic data dominated by wind noise makes the analysis of vocal activity unreliable, thus compromising the detection of target sounds and, subsequently, the interpretation of the results. Our work introduces a straightforward approach for detecting recordings affected by windy events using a pre-trained convolutional neural network. This process facilitates identifying wind-compromised data. We consider this dataset pre-processing crucial for ensuring the reliable use of PAM data. We implemented this preprocessing by leveraging YAMNet, a deep learning model for sound classification tasks. We evaluated YAMNet as-is ability to detect wind-induced noise and tested its performance in a Transfer Learning scenario by using our annotated data from the Stony Point Penguin Colony in South Africa. While the classification of YAMNet as-is achieved a precision of 0.71, and recall of 0.66, those metrics strongly improved after the training on our annotated dataset, reaching a precision of 0.91, and recall of 0.92, corresponding to a relative increment of >28 %. Our study demonstrates the promising application of YAMNet in the bioacoustics and ecoacoustics fields, addressing the need for wind-noise-free acoustic data. We released an open-access code that, combined with the efficiency and peak performance of YAMNet, can be used on standard laptops for a broad user base.

Response of chlorophyll-a to rainfall event in the basin of the South China sea: Statistical analysis.

Chlorophyll-a (Chl-a) is an essential ecological indicator, and affected by processes such as typhoons, mesoscale eddies, and Rossby waves. However, the impact of more frequent and widespread precipitation events on Chl-a seems to be overlooked. This study utilized remote sensing data and reanalysis data to investigate the response of Chl-a to 240 precipitation events in the central South China Sea from 2005 to 2019. The results indicate that precipitation events have a significant impact on Chl-a concentration. Following a precipitation event in 2019, the Chl-a concentration in the affected area increased by approximately 0.22 mg m-³ from the 3rd to the 7th day. The reasons for the increase in Chl-a concentration were the vertical mixing induced by wind stirring and the upwelling caused by wind stress curl, which transported nutrients to the euphotic zone, lowering the sea surface temperature and triggering a proliferation of phytoplankton. Additionally, dissolved nutrients in precipitation provided a nutrient source for Chl-a growth. The contributions of nutrient supply, wind speed, and wind stress curl to the increase in Chl-a concentration during precipitation events were 18%, 37%, and 45%, respectively. Precipitation events enhanced marine primary productivity, playing a crucial role in deepening our understanding of ocean-atmosphere interactions and their impact on marine ecosystem.

Spatial diffusion of potentially toxic elements in soils around non-ferrous metal mines.

This study focuses on the diffusion patterns of principal ore-forming elements (Pb and Zn) and associated elements (Cd, Cu, Cr, and As) in lead-zinc ore. Sampling points in upwind and downwind directions of lead-zinc ore areas at various densities (1 N/km2 - 4 N/km2) were categorized. This study analyzed the statistical relationship between the content of PTEs in the soil around lead-zinc ore and the source strength and dominant wind direction, constructed one-dimensional and two-dimensional diffusion model, and simulated the EER scope caused by PTEs. The findings indicate that: (1) concerning source strength, the content of PTEs in soils of high-density ore aggregation areas is significantly higher than in low-density ore aggregation areas. However, the impact of source strength decreases with decreasing ore grade, with a difference in Pb content of 1.71 times among principal ore-forming elements and almost consistent Cd content among associated elements. (2) Regarding the transport pathways, for most PTEs, the inverse proportion coefficients downwind are higher than upwind, approximately 1.18-3.63 times, indicating greater migration distances of PTEs downwind due to atmospheric dispersion. (3) By establishing a two-dimensional risk diffusion model, the study simulates the maximum radius of risk diffusion (r = 5.7 km), the 50% probability radius (r = 3.1 km), and the minimum radius (r = 0.8 km) based on the maximum, median, and minimum values statistically obtained from the EER. This study provides a scientific basis for implementing preventive measures for PTEs accumulation in soil within different pollution ranges. Different risk prevention and control measures should be adopted for PTEs accumulation in soil within the three ranges after cutting off pollution sources. Subsequent research should further investigate the impact and contribution of atmospheric transmission and surface runoff on the diffusion of PTEs in areas with high risk near lead-zinc ore.