Enhancement of ANN-based wind power forecasting by modification of surface roughness parameterization over complex terrain.

Wind energy plays an important role in the sustainable energy transition towards a low-carbon society. Proper assessment of wind energy resources and accurate wind energy prediction are essential prerequisites for balancing electricity supply and demand. However, these remain challenging, especially for onshore wind farms over complex terrains, owing to the interplay between surface heterogeneities and intermittent turbulent flows in the planetary boundary layer. This study aimed to improve wind characteristic assessment and medium-term wind power forecasts over complex hilly terrain using a numerical weather prediction (NWP) model. The NWP model reproduced the wind speed distribution, duration, and spatio-temporal variabilities of the observed hub-height wind speed at 24 wind turbines in onshore wind farms when incorporating more realistic surface roughness effects, such as the subgrid-scale topography, roughness sublayer, and canopy height. This study also emphasizes the good features for machine learning that represent heterogeneities in the surface roughness elements in the atmospheric model. We showed that medium-term forecasting using the NWP model output and a simple artificial neural network (ANN) improved day-ahead wind power forecasts by 14% in terms of annual normalized mean absolute error. Our results suggest that better parameterizations of surface friction in atmospheric models are important for wind power forecasting and resource assessment using NWP models, especially when combined with machine learning techniques, and shed light on onshore wind power forecasting and wind energy assessment in mountainous regions.

Changes in planned and unplanned canopy openings are linked in Europe's forests.

Canopy openings are increasing in Europe's forests, yet the contributions of anthropogenic and ecological agents of disturbance to this increase remain debated. Here we attribute the root cause of all stand-replacing canopy disturbances identified for Europe in the period 1986-2020 from Landsat data (417,000 km²), distinguishing between planned and unplanned canopy openings (i.e., disturbance by human land use versus by wind, bark beetles, and wildfire). We show that canopy openings by humans dominate the European forest disturbance regime, accounting for 82% of the area disturbed. Both planned and unplanned canopy openings increased in the early 21st century (+24% and +30% relative to the late 20th century). Their changes are linked, with simultaneous increases in planned and unplanned canopy openings on 68% of Europe's forest area. We conclude that an important direction for tackling disturbance change in policy and management is to break the link between planned and unplanned canopy openings in Europe's forests.

An exploration of meteorological effects on PM2.5 air quality in several provinces and cities in Vietnam.

Linking meteorology and air pollutants is a key challenge. The study investigated meteorological effects on PM2.5 concentration using the advanced convergent cross mapping method, utilizing hourly PM2.5 concentration and six meteorological factors across eight provinces and cities in Vietnam. Results demonstrated that temperature (ρ = 0.30) and radiation (ρ = 0.30) produced the highest effects, followed by humidity (ρ = 0.28) and wind speed (ρ = 0.24), while pressure (ρ = 0.22) and wind direction (ρ = 0.17) produced the weakest effects on PM2.5 concentration. Comparing the ρ values showed that temperature, wind speed, and wind direction had greater impacts on PM2.5 concentration during the dry season whereas radiation had a more influence during the wet season; Southern stations experienced larger meteorological effects. Temperature, humidity, pressure, and wind direction had both positive and negative influences on PM2.5 concentration, while radiation and wind speed mostly had negative influences. During PM2.5 pollution episodes, there was more contribution of meteorological effects on PM2.5 concentration indicated by ρ values. At contaminated levels, humidity (ρ = 0.45) was the most dominant factor affecting PM2.5 concentration, followed by temperature (ρ = 0.41) and radiation (ρ = 0.40). Pollution episodes were pointed out to be more prevalent under higher humidity, higher pressure, lower temperature, lower radiation, and lower wind speed. The ρ calculation also revealed that lower temperature, lower radiation, and higher humidity greatly accelerated each other under pollution episodes, further enhancing PM2.5 concentration. The findings contributed to the literature on meteorology and air pollution interaction.

Detection and validation of common noctule bats (Nyctalus noctula) with a pulse radar and acoustic monitoring in the proximity of an onshore wind turbine.

This paper presents the results of bats detected with marine radar and their validation with acoustic detectors in the vicinity of a wind turbine with a hub height of 120 m. Bat detectors are widely used by researchers, even though the common acoustic detectors can cover only a relatively small volume. In contrast, radar technology can overcome this shortcoming by offering a large detection volume, fully covering the rotor-swept areas of modern wind turbines. Our study focused on the common noctule bats (Nyctalus noctula). The measurement setup consisted of a portable X-band pulse radar with a modified radar antenna, a clutter shielding fence, and an acoustic bat detector installed in the wind turbine's nacelle. The radar's detection range was evaluated using an analytical simulation model. We developed a methodology based on a strict set of criteria for selecting suitable radar data, acoustic data and identified bat tracks. By applying this methodology, the study data was limited to time intervals with an average duration of 48 s, which is equal to approximately 20 radar images. For these time intervals, 323 bat tracks were identified. The most common bat speed was extracted to be between 9 and 10 m/s, matching the values found in the literature. Of the 323 identified bat tracks passed within 80 m of the acoustic detector, 32% had the potential to be associated with bat calls due to their timing, directionality, and distance to the acoustic bat detector. The remaining 68% passed within the studied radar detection volume but out of the detection volume of the acoustic bat detector. A comparison of recorded radar echoes with the expected simulated values indicated that the in-flight radar cross-section of recorded common noctule bats was mostly between 1.0 and 5.0 cm2, which is consistent with the values found in the literature for similar sized wildlife.

Environmental variables driving horseshoe crab spawning behavior in a microtidal lagoon in Florida.

The timing of American horseshoe crab (Limulus polyphemus) spawning behavior along the coast of Florida (United States) is generally associated with the highest tides during the spring and fall lunar cycles. All Florida estuaries support horseshoe crab populations, but tidal characteristics vary markedly among locations, which may influence the timing of horseshoe crab spawning behavior. The Indian River Lagoon is a large microtidal estuary on Florida's east coast. Given the microtidal nature of the lagoon, it is unclear which environmental factors affect horseshoe spawning. In 2019, volunteers of Florida Horseshoe Crab Watch conducted daily surveys at two sites in the northern Indian River Lagoon during peak spawning months (February-April). During each survey, volunteers counted all spawning horseshoe crabs and recorded environmental variables, including water temperature, air temperature, wind speed, wind direction, salinity, and tide height. We developed a suite of negative-binomial regression models to quantify relationships between the number of spawning horseshoe crabs and environmental factors. Modeling results indicated a positive relationship between onshore wind speed and number of spawning horseshoe crabs. Our study suggests that in the absence of tidal cues, onshore wind speed may be an important driver of horseshoe crab spawning activity in microtidal estuarine systems.

Risk-sensitive response of soaring birds to crosswind over dangerous sea highlights age-specific differences in migratory performance.

Challenges imposed by geographical barriers during migration are selective agents for animals. Juvenile soaring landbirds often cross large water bodies along their migratory path, where they lack updraft support and are vulnerable to harsh weather. However, the consequences of inexperience in accomplishing these water crossings remain largely unquantified. To address this knowledge gap, we tracked the movements of juvenile and adult black kites Milvus migrans over the Strait of Gibraltar using high-frequency tracking devices in variable crosswind conditions. We found that juveniles crossed under higher crosswind speeds and at wider sections of the strait compared with adults during easterly winds, which represent a high risk owing to their high speed and steady direction towards the Atlantic Ocean. Juveniles also drifted extensively with easterly winds, contrasting with adults who strongly compensated for lateral displacement through flapping. Age differences were inconspicuous during winds with a west crosswind speed component, as well as for airspeed modulation in all wind conditions. We suggest that the suboptimal sea-crossing behaviour of juvenile black kites may impact their survival rates, either by increasing chances of drowning owing to exhaustion or by depleting critical energy reserves needed to accomplish their first migration.

Optimization of offshore wind farm inspection paths based on K-means-GA.

As global demand for offshore wind energy continues to rise, the imperative to enhance the profitability of wind power projects and reduce their operational costs becomes increasingly urgent. This study proposes an innovative approach to optimize the inspection routes of offshore wind farms, which integrates the K-means clustering algorithm and genetic algorithm (GA). In this paper, the inspection route planning problem is formulated as a multiple traveling salesman problem (mTSP), and the advantages of the K-means clustering algorithm in distance similarity are utilized to effectively group the positions of wind turbines, thereby optimizing the inspection schedule for vessels. Subsequently, by harnessing the powerful optimization capability and robustness of genetic algorithms, further refinement is conducted to search for the optimal inspection routes, aiming to achieve cost reduction objectives. The results of simulation experiments demonstrate the effectiveness of this integrated approach. Compared to traditional genetic algorithms, the inspection route length has been significantly reduced, from 93 kilometers to 79.36 kilometers. Simultaneously, operational costs have also experienced a notable decrease, dropping from 141,500 Chinese Yuan to 125,600 Chinese Yuan.

Windthrow causes declines in carbohydrate and phenolic concentrations and increased monoterpene emission in Norway spruce.

With the increasing frequencies of extreme weather events caused by climate change, the risk of forest damage from insect attacks grows. Storms and droughts can damage and weaken trees, reduce tree vigour and defence capacity and thus provide host trees that can be successfully attacked by damaging insects, as often observed in Norway spruce stands attacked by the Eurasian spruce bark beetle Ips typographus. Following storms, partially uprooted trees with grounded crowns suffer reduced water uptake and carbon assimilation, which may lower their vigour and decrease their ability to defend against insect attack. We conducted in situ measurements on windthrown and standing control trees to determine the concentrations of non-structural carbohydrates (NSCs), of phenolic defences and volatile monoterpene emissions. These are the main storage and defence compounds responsible for beetle´s pioneer success and host tree selection. Our results show that while sugar and phenolic concentrations of standing trees remained rather constant over a 4-month period, windthrown trees experienced a decrease of 78% and 37% of sugar and phenolic concentrations, respectively. This strong decline was especially pronounced for fructose (-83%) and glucose (-85%) and for taxifolin (-50.1%). Windthrown trees emitted 25 times greater monoterpene concentrations than standing trees, in particular alpha-pinene (23 times greater), beta-pinene (27 times greater) and 3-carene (90 times greater). We conclude that windthrown trees exhibited reduced resources of anti-herbivore and anti-pathogen defence compounds needed for the response to herbivore attack. The enhanced emission rates of volatile terpenes from windthrown trees may provide olfactory cues during bark beetle early swarming related to altered tree defences. Our results contribute to the knowledge of fallen trees vigour and their defence capacity during the first months after the wind-throw disturbance. Yet, the influence of different emission rates and profiles on bark beetle behaviour and host selection requires further investigation.

ICEEMDAN-Informer-GWO: a hybrid model for accurate wind speed prediction.

Extensive research has been diligently conducted on wind energy technologies in response to pressing global environmental challenges and the growing demand for energy. Accurate wind speed predictions are crucial for the effective integration of large wind power systems. This study presents a novel and hybrid framework called ICEEMDAN-Informer-GWO, which combines three components to enhance the accuracy of wind speed predictions. The improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) component improves the decomposition of wind speed data, the Informer model provides computationally efficient wind speed predictions, and the grey wolf optimisation (GWO) algorithm optimises the parameters of the Informer model to achieve superior performance. Three different sets of wind speed prediction (WSP) models and wind farm data from Block Island, Gulf Coast, and Garden City are used to thoroughly assess the proposed hybrid framework. This evaluation focusses on WSP for three specific time horizons: 5 minutes, 30 minutes, and 1 hour ahead. The results obtained from the three conducted experiments conclusively demonstrate that the proposed hybrid framework exhibits superior performance, leading to statistically significant improvements across all three time horizons.

Effects of extreme meteorological factors and high air pollutant concentrations on the incidence of hand, foot and mouth disease in Jining, China.

Background: The evidence on the effects of extreme meteorological conditions and high air pollution levels on incidence of hand, foot and mouth disease (HFMD) is limited. Moreover, results of the available studies are inconsistent. Further investigations are imperative to elucidate the specific issue. Methods: Data on the daily cases of HFMD, meteorological factors and air pollution were obtained from 2017 to 2022 in Jining City. We employed distributed lag nonlinear model (DLNM) incorporated with Poisson regression to explore the impacts of extreme meteorological conditions and air pollution on HFMD incidence. Results: We found that there were nonlinear relationships between temperature, wind speed, PM2.5, SO2, O3 and HFMD. The cumulative risk of extreme high temperature was higher at the 95th percentile (P95th) than at the 90th percentile(P90th), and the RR values for both reached their maximum at 10-day lag (P95th RR = 1.880 (1.261-2.804), P90th RR = 1.787 (1.244-2.569)), the hazardous effect of extreme low temperatures on HFMD is faster than that of extreme high temperatures. The cumulative effect of extreme low wind speeds reached its maximum at 14-day lag (P95th RR = 1.702 (1.389-2.085), P90th RR = 1.498(1.283-1.750)). The cumulative effect of PM2.5 concentration at the P90th was largest at 14-day lag (RR = 1.637 (1.069-2.506)), and the cumulative effect at the P95th was largest at 10-day lag (RR = 1.569 (1.021-2.411)). High SO2 concentration at the P95th at 14-day lag was associated with higher risk for HFMD (RR: 1.425 (1.001-2.030)). Conclusion: Our findings suggest that high temperature, low wind speed, and high concentrations of PM2.5 and SO2 are associated with an increased risk of HFMD. This study not only adds insights to the understanding of the impact of extreme meteorological conditions and high levels of air pollutants on HFMD incidence but also holds practical significance for the development and enhancement of an early warning system for HFMD.

Distribution of common pipistrelle (Pipistrellus pipistrellus) activity is altered by airflow disruption generated by wind turbines.

The mechanisms underlying bat and bird activity peaks (attraction) or losses (avoidance) near wind turbines remain unknown. Yet, understanding them would be a major lever to limit the resulting habitat loss and fatalities. Given that bat activity is strongly related to airflows, we hypothesized that airflow disturbances generated leeward (downwind) of operating wind turbines-via the so-called wake effect-make this area less favorable for bats, due to increased flight costs, decreased maneuverability and possibly lower prey abundance. To test this hypothesis, we quantified Pipistrellus pipistrellus activity acoustically at 361 site-nights in western France in June on a longitudinal distance gradient from the wind turbine and on a circular azimuth gradient of wind incidence angle, calculated from the prevailing wind direction of the night. We show that P. pipistrellus avoid the wake area, as less activity was detected leeward of turbines than windward (upwind) at relatively moderate and high wind speeds. Furthermore, we found that P. pipistrellus response to wind turbine (attraction and avoidance) depended on the angle from the wake area. These findings are consistent with the hypothesis that changes in airflows around operating wind turbines can strongly impact the way bats use habitats up to at least 1500 m from the turbines, and thus should prompt the consideration of prevailing winds in wind energy planning. Based on the evidence we present here, we strongly recommend avoiding configurations involving the installation of a turbine between the origin of prevailing winds and important habitats for bats, such as hedgerows, water or woodlands.

Performance enhancement of short-term wind speed forecasting model using Realtime data.

The ever-increasing demand for electricity has presented a grave threat to traditional energy sources, which are finite, rapidly depleting, and have a detrimental environmental impact. These shortcomings of conventional energy resources have caused the globe to switch from traditional to renewable energy sources. Wind power significantly contributes to carbon-free energy because it is widely accessible, inexpensive, and produces no harmful emissions. Better and more efficient renewable wind power production relies on accurate wind speed predictions. Accurate short-term wind speed forecasting is essential for effectively handling unsteady wind power generation and ensuring that wind turbines operate safely. The significant stochastic nature of the wind speed and its dynamic unpredictability makes it difficult to forecast. This paper develops a hybrid model, L-LG-S, for precise short-term wind speed forecasting to address problems in wind speed forecasting. In this research, state-of-the-art machine learning and deep learning algorithms employed in wind speed forecasting are compared with the proposed approach. The effectiveness of the proposed hybrid model is tested using real-world wind speed data from a wind turbine located in the city of Karachi, Pakistan. Moreover, the mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE) are used as accuracy evaluation indices. Experimental results show that the proposed model outperforms the state-of-the-art legacy models in terms of accuracy for short-term wind speed in training, validation and test predictions by 98% respectively.

Damage to tropical forests caused by cyclones is driven by wind speed but mediated by topographical exposure and tree characteristics.

Each year, an average of 45 tropical cyclones affect coastal areas and potentially impact forests. The proportion of the most intense cyclones has increased over the past four decades and is predicted to continue to do so. Yet, it remains uncertain how topographical exposure and tree characteristics can mediate the damage caused by increasing wind speed. Here, we compiled empirical data on the damage caused by 11 cyclones occurring over the past 40 years, from 74 forest plots representing tropical regions worldwide, encompassing field data for 22,176 trees and 815 species. We reconstructed the wind structure of those tropical cyclones to estimate the maximum sustained wind speed (MSW) and wind direction at the studied plots. Then, we used a causal inference framework combined with Bayesian generalised linear mixed models to understand and quantify the causal effects of MSW, topographical exposure to wind (EXP), tree size (DBH) and species wood density (ρ) on the proportion of damaged trees at the community level, and on the probability of snapping or uprooting at the tree level. The probability of snapping or uprooting at the tree level and, hence, the proportion of damaged trees at the community level, increased with increasing MSW, and with increasing EXP accentuating the damaging effects of cyclones, in particular at higher wind speeds. Higher ρ decreased the probability of snapping and to a lesser extent of uprooting. Larger trees tended to have lower probabilities of snapping but increased probabilities of uprooting. Importantly, the effect of ρ decreasing the probabilities of snapping was more marked for smaller than larger trees and was further accentuated at higher MSW. Our work emphasises how local topography, tree size and species wood density together mediate cyclone damage to tropical forests, facilitating better predictions of the impacts of such disturbances in an increasingly windier world.

Adaptivity of a leaf-inspired wind energy harvester with respect to wind speed and direction.

Environmental wind is a random phenomenon in both speed and direction, though it can be forecasted to some extent. An example of that is a gust which is an abrupt, but short-time change in wind speed and direction. Being a free and clean source for small-scale energy scavenging, attraction of wind is rapidly growing in the world of energy harvesters. In this paper, a leaf-like flapping wind energy harvester is introduced as the base structure in which a short-span airfoil is attached to the free end of a double-deck cantilever beam. A flap mechanism inspired by scales on sharks' skin and a tail mechanism inspired by birds' horizontal tail are proposed for integration to the base harvester to make it adaptive with respect to wind speed and direction, respectively. The use of the flap mechanism increases the leaf flapping frequency by +2.1 to +11.5 Hz at wind speeds of 1.5 to 6.0 m s-1. Therefore, since the output power of a vibrational harvester is a function of vibration frequency, a figure of merit or an efficiency parameter related to the output power will increase, as well. On the other hand, if there is a misalignment between the harvester's heading and wind direction due to change of the latter one, the harvesting performance deteriorates. Although the base harvester can realign in certain ranges of sideslip angle at each wind speed, when the tail mechanism is integrated into that, it broadens the range of realignable sideslip angles at all the investigated wind speeds by up to 80∘.

Expression responses of XTH genes in tomato and potato to environmental mechanical forces: focus on behavior in response to rainfall, wind and touch.

Rainfall, wind and touch, as mechanical forces, were mimicked on 6-week-old soil-grown tomato and potato under controlled conditions. Expression level changes of xyloglucan endotransglucosylase/hydrolase genes (XTHs) of tomato (Solanum lycopersicum L. cv. Micro Tom; SlXTHs) and potato (Solanum tuberosum L. cv. Desirée; StXTHs) were analyzed in response to these mechanical forces. Transcription intensity of every SlXTHs of tomato was altered in response to rainfall, while the expression intensity of 72% and 64% of SlXTHs was modified by wind and touch, respectively. Ninety-one percent of StXTHs (32 out of 35) in potato responded to the rainfall, while 49% and 66% of the StXTHs were responsive to the wind and touch treatments, respectively. As previously demonstrated, all StXTHs were responsive to ultrasound treatment, and all were sensitive to one or more of the environmental mechanical factors examined in the current study. To our best knowledge, this is the first study to demonstrate that these ubiquitous mechanical environmental cues, such as rainfall, wind and touch, influence the transcription of most XTHs examined in both species.

A life cycle assessment of the laboratory-scale oxidative liquefaction as the chemical recycling method of the end-of-life wind turbine blades.

According to the latest reports, estimated values of 50,000-66 000 t of end-of-life wind turbine blades (WTB) are expected to be decommissioned in Europe in 2025-2030, posing a significant threat from the environmental and waste management perspectives. This study aims to present the preliminary Life Cycle Assessment (LCA) with sensitivity and uncertainty analysis of the lab-scale oxidative liquefaction process of the WTB, as the original method to recover the high-quality glass fibers with simultaneous production of the secondary chemicals: phenols, ketones, acids, and fatty acids, from the oxidation of the epoxy resin from the polymer matrix. The LCA is based on the experimental results of the oxidative liquefaction process carried out on a laboratory scale using a Parr 500 ml batch reactor, at two different conditions sets for the functional unit (FU) of 1 kg of treated WTB. Each of the analyzed scenarios resulted in higher impact indicators compared to the landfilling. The highest quality fibers were obtained at 350 °C and 40 wt % H2O2 content resulted in 5.52 ± 1.20 kgCO2 eq Climate change impact and 97.8 ± 20.6 MJ of Resource use, fossil per kg of recycled WTB. The lowest quality fiber recovered in char, yet well separated from the matrix obtained at 250 °C and the lowest H2O2 content resulted in 0.0953 ± 0.487 kgCO2 eq Climate change impact and 8.84 ± 7.90 MJ of Resource use, fossil per kg of recycled WTB. The hot spot and sensitivity analysis indicated, that the oxidizer for the process - hydrogen peroxide, when acquired as a shelf product causes a significant burden on the whole process, with sensitivity ratios on the total impact indicators varying across the categories from 0.56 to 0.99. Substitution of H2O2 with theoretical 0-input oxidizer allowed to significantly lower environmental load of the recycling process, which in all of the analyzed scenarios presented environmental benefits compared to landfilling with recovery of the glass fiber and secondary chemicals.

Beneath the blades: Marine wind farms support parts of local biodiversity - a systematic review.

Offshore wind energy developments in European waters are rapidly expanding to meet the increasing global demand for renewable energy. These developments provide new substrates for species colonisation, but also introduce changes in electromagnetic fields, noise levels, and hydrological conditions. Understanding how these man-made structures affect marine biodiversity across various species groups is crucial, yet our knowledge in this field remains incomplete. In this synthesis paper, based on 14 case studies conducted in northeastern Atlantic (North, Irish and Baltic seas), we aggregated species-level data on abundance, biomass, and other quantity proxies spanning the entire food chain from invertebrates to mammals, and compared these variables between wind farms and nearby control sites. Overall, our analysis revealed that in wind farm areas, species tend to occur at higher quantities than in control areas. Additionally, we noticed a slight trend where the positive effect of wind farms was more pronounced in newly established ones, gradually diminishing as wind farms aged. None of the tested covariates (depth, distance from coastline, years in commission) nor species' characteristics (habitat and spawning types, trophic level) showed statistical significance. When examining species groups individually, there was a tendency for wind farm areas to harbour higher quantities of polychaetes, echinoderms and demersal fishes. These findings suggest that wind farms contribute to the so-called reef-effect, providing shelter and food supplies to their inhabitants and acting as no-take-zones. Our results support the idea that wind farms could serve as zones of increased local biodiversity, potentially facilitating spillover effects to nearby areas for certain species groups. Further studies are necessary to gain a more comprehensive understanding of the adverse effects of wind farms on associated biodiversity, while also exploring avenues to amplify their positive impacts.

Research of biomimetic corrugation on the blade flutter suppression in large-scale wind turbine systems.

Aiming at the blade flutter of large horizontal-axis wind turbines, a method by utilizing biomimetic corrugation to suppress blade flutter is first proposed. By extracting the dragonfly wing corrugation, the biomimetic corrugation airfoil is constructed, finding that mapping corrugation to the airfoil pressure side has better aerodynamic performance. The influence of corrugation type, amplitudeλ, and intensity on airfoil flutter is analyzed using orthogonal experiment, which determines that theλhas the greatest influence on airfoil flutter. Based on the fluctuation range of the moment coefficient ΔCm, the optimal airfoil flutter suppression effect is obtained when the type is III,λ= 0.6, and intensity is denser (n= 13). The effective corrugation layout area in the chord direction is determined to be the leading edge, and the ΔCmof corrugation airfoil is reduced by 7.405%, compared to the original airfoil. The application of this corrugation to NREL 15 MW wind turbine 3D blades is studied, and the influence of corrugation layout length in the blade span direction on the suppressive effect is analyzed by fluid-structure interaction. It is found that when the layout length is 0.85 R, the safety marginSfreaches a maximum value of 0.3431 Hz, which is increased 2.940%. The results show that the biomimetic corrugated structure proposed in this paper can not only improve the aerodynamic performance by changing the local flow field on the surface of the blade, but also increase the structural stiffness of the blade itself, and achieve the effect of flutter suppression.

Comprehensive analysis of air pollution and the influence of meteorological factors: a case study of adiyaman province.

Adiyaman, a city recently affected by an earthquake, is facing significant air pollution challenges due to both anthropogenic activities and natural events. The sources of air pollution have been investigated using meteorological variables. Elevated southerly winds, especially prominent in spring and autumn, significantly contribute to dust transport, leading to a decline in local air quality as detected by the HYSPLIT model. Furthermore, using Suomi-NPP Thermal Anomaly satellite product, it is detected and analyzed for crop burning activities. Agricultural practices, including stubble burning, contribute to the exacerbation of PM10 pollution during the summer months, particularly when coupled with winds from all directions except the north. In fall and winter months, heating is identified as the primary cause of pollution. The city center located north of the station is the dominant source of pollution throughout all seasons. The study established the connection between air pollutants and meteorological variables. Furthermore, the Spearman correlation coefficients reveal associations between PM10 and SO2, indicating moderate positive correlations under pressure conditions (r = 0.35, 0.52). Conversely, a negative correlation is observed with windspeed (r = -0.35, -0.50), and temperature also exhibits a negative correlation (r = -0.39, -0.54). During atmospheric conditions with high pressure, PM10 and SO2 concentrations are respectively 41.2% and 117.2% higher. Furthermore, pollutant concentration levels are 29.2% and 53.3% higher on days with low winds. Last, practical strategies for mitigating air pollution have been thoroughly discussed and proposed. It is imperative that decision-makers engaged in city planning and renovation give careful consideration to the profound impact of air pollution on both public health and the environment, particularly in the aftermath of a recent major earthquake.