Compounded wind gusts and maximum temperature via semiparametric copula in the risk assessments of power blackouts and air conditioning demands for major cities in Canada.

A semiparametric copula joint framework was proposed to model wind gust speed (WGS) and maximum temperature (MT) in Canada, using Gaussian kernel density estimation (GKDE) with parametric copulas. Their joint probability estimates allow for a better understanding of the risk of power blackouts and the demand for air conditioning in the community. The bivariate framework used two extreme sample groups to define extreme pairs at different time lags, i.e., 0 to ± 3 days, annual maximum WGS (AMWGS) and corresponding MT and annual highest MT (AHMT) and corresponding WGS. A thorough model performance comparison indicated that GKDE outperformed the parametric models in defining the marginal distribution of selected univariate series. Significant positive correlations were observed among extreme pairs, except for Calgary and Halifax stations, with inconsistent correlation variations based on selected cities and lag time. Various parametric 2-D copulas were selected to model the dependence structure of bivariate pairs at different time lags for selected stations. AMWGS or AHMT events, when considered independently, would be stressful for all stations due to high estimated quantiles with low univariate RPs. The bivariate events exhibited lower AND-joint RPs with moderate to high design quantiles, indicating a higher risk of power blackouts and heightened air-conditioning demands, which varied inconsistently with time lags across the station. The bivariate AMWGS and corresponding MT events would be stressful in Regina, Quebec City, Ottawa, and Edmonton, while AHMT and corresponding WGS events in Toronto, Regina, and Montreal. Conversely, Vancouver poses a lower risk of joint action of pairs AHMT and corresponding WGS events. These hazard statistics can help in better planning for community well-being during extreme weather.

Multi-objective energy management in a renewable and EV-integrated microgrid using an iterative map-based self-adaptive crystal structure algorithm.

The use of plug-in hybrid electric vehicles (PHEVs) provides a way to address energy and environmental issues. Integrating a large number of PHEVs with advanced control and storage capabilities can enhance the flexibility of the distribution grid. This study proposes an innovative energy management strategy (EMS) using an Iterative map-based self-adaptive crystal structure algorithm (SaCryStAl) specifically designed for microgrids with renewable energy sources (RESs) and PHEVs. The goal is to optimize multi-objective scheduling for a microgrid with wind turbines, micro-turbines, fuel cells, solar photovoltaic systems, and batteries to balance power and store excess energy. The aim is to minimize microgrid operating costs while considering environmental impacts. The optimization problem is framed as a multi-objective problem with nonlinear constraints, using fuzzy logic to aid decision-making. In the first scenario, the microgrid is optimized with all RESs installed within predetermined boundaries, in addition to grid connection. In the second scenario, the microgrid operates with a wind turbine at rated power. The third case study involves integrating plug-in hybrid electric vehicles (PHEVs) into the microgrid in three charging modes: coordinated, smart, and uncoordinated, utilizing standard and rated RES power. The SaCryStAl algorithm showed superior performance in operation cost, emissions, and execution time compared to traditional CryStAl and other recent optimization methods. The proposed SaCryStAl algorithm achieved optimal solutions in the first scenario for cost and emissions at 177.29 €ct and 469.92 kg, respectively, within a reasonable time frame. In the second scenario, it yielded optimal cost and emissions values of 112.02 €ct and 196.15 kg, respectively. Lastly, in the third scenario, the SaCryStAl algorithm achieves optimal cost values of 319.9301 €ct, 160.9827 €ct and 128.2815 €ct for uncoordinated charging, coordinated charging and smart charging modes respectively. Optimization results reveal that the proposed SaCryStAl outperformed other evolutionary optimization algorithms, such as differential evolution, CryStAl, Grey Wolf Optimizer, particle swarm optimization, and genetic algorithm, as confirmed through test cases.

Screening of voice and vocal tract changes in professional wind instrument players.

PURPOSE: Playing wind instruments is a strenuous task on the larynx, predisposing players to voice disorders. This study aims to evaluate potential vocal symptoms and vocal tract alterations in professional wind instrumentalists. METHODS: In this cross-sectional study, 26 male military subjects were interviewed, completed the voice handicap index (VHI) -10 questionnaire, and subjected to auditory-perceptual assessment, neck examination, rigid laryngostroboscopy and flexible nasofiberoscopy both before and during instrument playing. RESULTS: All participants had vocal fatigue symptoms, around one-quarter complained of voice change, one-quarter complained of shortness of breath while or after performing, and one-third complained of neck symptoms. The average score of VHI-10 was 16.2 ± 6.5, and approximately three-quarters of participants scored above the cut-off point. There were no significant correlations between age, years of instrument playing, average hours of daily practice, and VHI-10. Participants with neck symptoms had significantly higher VHI-10 scores. Those (around one-fifth) with an external neck swelling during Valsalva maneuver had a significantly higher VHI-10 score. Dysphonia, mainly mild and of strained, leaky quality, was detected in almost one-third of participants. While the instrument was being played, the vocal folds were somewhat adducted, and the vocal tract became more compressed as the task became more demanding. The most frequent observations in the vocal tract examination were hyperemia of the vocal folds or all over the laryngeal and pharyngeal mucosa, excessive secretions over the vocal folds, signs of hyperadduction, arytenoid edema, and phonatory waste. CONCLUSION: Wind instrumentalists frequently experience voice disorders, which necessitate further care and investigation.

Oceanic seabirds chase tropical cyclones.

In late summer and autumn, the passage of intense tropical cyclones can profoundly perturb oceanic and coastal ecosystems. Direct negative effects on individuals and marine communities can be dramatic, especially in the coastal zone,1,2,3,4 but cyclones can also enhance pelagic primary and secondary production.5,6,7,8,9 However, cyclone impacts on open ocean marine life remain poorly understood. Here, we investigate their effects on the foraging movements of a wide-ranging higher predator, the Desertas petrel (Pterodroma deserta), in the mid-latitude North Atlantic during hurricane season. Contrary to previously studied pelagic seabirds in tropical and mid-latitude regions,10,11 Desertas petrels did not avoid cyclones by altering course, nor did they seek calmer conditions within the cyclone eye. Approximately one-third of petrels tracked from their breeding colony interacted with approaching cyclones. Upon encountering strong winds, the birds reduced ground speed, likely by spending less time in flight. A quarter of birds followed cyclone wakes for days and over thousands of kilometers, a behavior documented here for the first time. Within these wakes, tailwind support was higher than along alternative routes. Furthermore, at the mesoscale (hours-weeks and hundreds of kilometers), sea surface temperature dropped and surface chlorophyll sharply increased, suggesting direct effects on ocean stratification, primary production, and therefore presumably prey abundance and accessibility for surface-feeding petrels. We therefore hypothesize that cyclone wakes provide both predictably favorable wind conditions and foraging opportunities. As such, cyclones may have positive net effects on the demography of many mid-latitude pelagic seabirds and, likely, other marine top-predators.

Assessment of wind energy resource in the western region of Somaliland.

As the population of Somaliland continues to grow rapidly, the demand for electricity is anticipated to rise exponentially over the next few decades. The provision of reliable and cost-effective electricity service is at the core of the economic and social development of Somaliland. Wind energy might offer a sustainable solution to the exceptionally high electricity prices. In this study, a techno-economic assessment of the wind energy potential in some parts of the western region of Somaliland is performed. Measured data of wind speed and wind direction for three sites around the capital city of Hargeisa are utilized to characterize the resource using Weibull distribution functions. Technical and economic performances of several commercial wind turbines are examined. Out of the three sites, Xumba Weyne stands out as the most favorable site for wind energy harnessing with average annual power and energy densities at 80 m hub height of 317 kW/m2 and 2782 kWh/m2, respectively. Wind turbines installed in Xumba Weyne yielded the lowest levelized cost of electricity (LCOE) of not more than 0.07 $/kWh, shortest payback times (i.e., less than 7.2 years) with minimum return on investment (ROI) of approximately 150%.

Experimental investigation of multi-step airfoils in low Reynolds numbers applications.

This study provides a detailed analysis of the aerodynamic performance of various airfoil configurations, focusing on lift coefficient, stall characteristics, and maximum lift-to-drag ratio. The investigation includes the NACA23012C profile and configurations with different step geometries, ranging from one-step to five-step designs. Experimental measurements were conducted using a well-equipped aerodynamic laboratory, Institute of Aviation Engineering and Technology (IAET), Giza, Egypt. The lab features a wind tunnel, propeller test rig, and data acquisition system. The experiments were conducted meticulously to ensure accuracy and reproducibility, with a standardized method employed for uncertainty analysis. The results reveal distinct aerodynamic behaviors among the different configurations, highlighting the significant impact of design variations on aerodynamic performance. Notably, the three-step configuration consistently exhibited high performance, with a competitive or superior lift coefficient across a range of Reynolds numbers, showing an improvement of up to 35.1 %. Similarly, the four-step configuration demonstrated substantial increases in lift-to-drag ratios, reaching up to 53.2 %, while the five-step configuration exhibited varying trends with a minimum drag coefficient. The study also investigated stall characteristics and sensitivity to Reynolds numbers, revealing the complex trade-offs inherent in airfoil design. The findings provide valuable insights into optimizing airfoil performance under different operational conditions. Additionally, the adoption of two and three stepped airfoils resulted in significant reductions in blade material and associated costs for turbine blades.

Portable and affordable cold air plasma source with optimized bactericidal effect.

The paper reports a low-cost handheld source of a cold air plasma intended for biomedical applications that can be made by anyone (detailed technical information and a step-by-step guide for creating the NTP source are provided). The plasma source employs a 1.4 W corona discharge in the needle-to-cone electrode configuration and is an extremely simple device, consisting basically of two electrodes and a cheap power supply. To achieve the best bactericidal effect, the plasma source has been optimized on Escherichia coli. The bactericidal ability of the plasma source was further tested on a wide range of microorganisms: Staphylococcus aureus as a representative of gram-positive bacteria, Pseudomonas aeruginosa as gram-negative bacteria, Candida albicans as yeasts, Trichophyton interdigitale as microfungi, and Deinococcus radiodurans as a representative of extremophilic bacteria resistant to many DNA-damaging agents, including ultraviolet and ionizing radiation. The testing showed that the plasma source inactivates all the microorganisms tested in several minutes (up to 105-107 CFU depending on a microorganism), proving its effectiveness against a wide spectrum of pathogens, in particular microfungi, yeasts, gram-positive and gram-negative bacteria. Studies of long-lived reactive species such as ozone, nitrogen oxides, hydrogen peroxide, nitrite, and nitrate revealed a strong correlation between ozone and the bactericidal effect, indicating that the bactericidal effect should generally be attributed to reactive oxygen species. This is the first comprehensive study of the bactericidal effect of a corona discharge in air and the formation of long-lived reactive species by the discharge, depending on both the interelectrode distance and the discharge current.

Unveiling Afghanistan's wind and hydrogen potential: a comparative study.

Given the detrimental environmental impacts of fossil fuels, there is a gradual worldwide shift towards renewable energy sources. Wind power, renowned for its cost-effectiveness and simplicity, has been widely embraced. Despite Afghanistan facing significant challenges in its energy sector, its considerable wind energy potential offers a chance to mitigate some of these issues. This study employed a multi-criteria decision-making approach to evaluate potential wind-hydrogen project sites in Afghanistan, encompassing economic, technical, social, risk, and environmental considerations. Five criteria and sub-criteria for wind-hydrogen project implementation were analyzed using the Step-wise Weight Assessment Ratio Analysis (SWARA) method. The Weighted Aggregated Sum Product Assessment (WASPAS), Additive Ratio Assessment (ARAS), Evaluation based on Distance from Average Solution (EDAS), and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) methods were then applied to prioritize provinces for wind-hydrogen project implementation. The analysis found that the Duration of the Payback Period and Levelized Cost of Electricity (LCOE) with weight of 6.6% and 5.6% were critical sub-criteria. Farah, Herat, and Nimroz emerged as Afghanistan's most promising provinces for wind-hydrogen energy development. In Farah, utilizing 900-kW turbines, it is feasible to generate 2679.8 MWh of electricity and produce 43.4 tons of hydrogen annually, with a Levelized Cost of Electricity of 0.0690 $/kWh and Levelized Cost of Hydrogen of 1.747 $/kg.

Measurement of microclimates in a warming world: problems and solutions.

As the world warms, it will be tempting to relate the biological responses of terrestrial animals to air temperature. But air temperature typically plays a lesser role in the heat exchange of those animals than does radiant heat. Under radiant load, animals can gain heat even when body surface temperature exceeds air temperature. However, animals can buffer the impacts of radiant heat exposure: burrows and other refuges may block solar radiant heat fully, but trees and agricultural shelters provide only partial relief. For animals that can do so effectively, evaporative cooling will be used to dissipate body heat. Evaporative cooling is dependent directly on the water vapour pressure difference between the body surface and immediate surroundings, but only indirectly on relative humidity. High relative humidity at high air temperature implies a high water vapour pressure, but evaporation into air with 100% relative humidity is not impossible. Evaporation is enhanced by wind, but the wind speed reported by meteorological services is not that experienced by animals; instead, the wind, air temperature, humidity and radiation experienced is that of the animal's microclimate. In this Commentary, we discuss how microclimate should be quantified to ensure accurate assessment of an animal's thermal environment. We propose that the microclimate metric of dry heat load to which the biological responses of animals should be related is black-globe temperature measured on or near the animal, and not air temperature. Finally, when analysing those responses, the metric of humidity should be water vapour pressure, not relative humidity.

Addressing ocean planning challenges in a highly crowded sea space: a case study for the regional sea of Catalonia (Western Mediterranean).

Background: This study performs an exploratory analysis of current-future sustainability challenges for ocean planning for the regional seas of Catalonia located in the Western Mediterranean (Spain). Methods: To address the challenges we develop an Maritime Spatial Planning (MSP)-oriented geodatabase of maritime activities and deploy three spatial models: 1) an analysis of regional contribution to the 30% protection commitment with Biodiversity Strategy 2030; 2) a spatial Maritime Use Conflict (MUC) analysis to address current and future maritime activities interactions and 3) the StressorGenerator QGIS application to locate current and anticipate future sea areas of highest anthropogenic stress. Results & Conclusions: Results show that the i) study area is one of the most protected sea areas in the Mediterranean (44-51% of sea space protected); ii) anthropogenic stressors are highest in 1-4 nautical miles coastal areas, where maritime activities agglomerate, in the Gulf of Roses and Gulf of Saint Jordi. iii) According to the available datasets commercial fishery is causing highest conflict score inside protected areas. Potential new aquaculture sites are causing highest conflict in Internal Waters and the high potential areas for energy cause comparably low to negligible spatial conflicts with other uses. We discuss the added value of performing regional MSP exercises and define five challenges for regional ocean sustainability, namely: Marine protection beyond percentage, offshore wind energy: a new space demand, crowded coastal areas, multi-level governance of the regional sea and MSP knowledge gaps.

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.

A Study on Predicting the Deviation of Jet Trajectory Falling Point under the Influence of Random Wind.

As one of the main external factors affecting the fire extinguishing accuracy of sprinkler systems, it is necessary to analyze and study random wind. However, in practical applications, there is little research on the impact of random wind on sprinkler fire extinguishing points. To address this issue, a new random wind acquisition system was constructed in this paper, and a method for predicting jet trajectory falling points in Random Forest (RF) under the influence of random wind was proposed, and compared with the commonly used prediction model Support Vector Machine (SVM). The method in this article reduces the error in the x direction of the 50 m prediction result from 2.11 m to 1.53 m, the error in the y direction from 0.64 m to 0.6 m, and the total mean absolute error (MAE) from 31.3 to 23.5. Simultaneously, predict the falling points of jet trajectory at different distances under the influence of random wind, to demonstrate the feasibility of the proposed method in practical applications. The experimental results show that the system and method proposed in this article can effectively improve the influence of random wind on the falling points of a jet trajectory. In summary, the image acquisition system and error prediction method proposed in this article have many potential applications in fire extinguishing.

Adjuvant use for the management of pesticide drift, leaching and runoff.

Adjuvants are included in many pesticide spray mixtures to enhance the performance of the applied chemical. Many adjuvants which modify the emulsion or extensional viscosity of the tank-mixture have been found to offer benefits in drift management, primarily by eliminating or reducing the 'Fine' droplets included in the spray with diameters <100-200 µm that can move off-target in unfavorable conditions during ground, airblast and aerial pesticide applications. Among wind tunnel and field studies conducted around the world, there is consensus that while some adjuvants are effective for drift management, the performance varies on a case-by-case basis, requiring verification for each adjuvant which could be achieved through a programme such as certification based on showing a reduction in Fine droplets and/or a reduction in airborne drift. These can be measured in wind tunnel studies according to international standards. This article provides a review of the current science in this subject area, from the approaches to data collection to a review of existing data and regulatory application for encouraging and rewarding the use of appropriate adjuvants that have been demonstrated to reduce airborne spray drift potential and therefore the size of no-spray buffer zones appropriate to protect nontarget sensitive areas from drift exposure. Some adjuvants can offer the same reduction in drift as offered by hooded sprayer retrofits. A drift reduction programme based on adjuvant use could include testing candidate adjuvants for their effect on droplet size and reduction in Fine droplets when sprayed through reference nozzles and compared against sprays without the adjuvant. Testing could also be based alternatively on measurements of drift potential on collectors such as monofilament line in wind tunnel or field studies. Once shown to be effective in reducing 'Fines' or spray drift, adjuvants could be certified and then referenced on pesticide labels and/or regulatory or best management practice schemes to encourage their use and offer reductions in use restrictions or no-spray buffer zone sizes based on drift management. Studies have shown that some adjuvants can reduce pesticide leaching into soils and contamination of groundwater, as well as runoff of active ingredients from plants into the environment. Performance depends on the adjuvant type, the pesticide with which it is used, the soil or plant type, the timing and mass of water input from rainfall and climatic factors. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Boosting prairie dog optimizer for optimal planning of multiple wind turbine and photovoltaic distributed generators in distribution networks considering different dynamic load models.

Deploying distributed generators (DGs) supplied by renewable energy resources poses a significant challenge for efficient power grid operation. The proper sizing and placement of DGs, specifically photovoltaics (PVs) and wind turbines (WTs), remain crucial due to the uncertain characteristics of renewable energy. To overcome these challenges, this study explores an enhanced version of a meta-heuristic technique called the prairie dog optimizer (PDO). The modified prairie dogs optimizer (mPDO) incorporates a novel exploration phase inspired by the slime mold algorithm (SMA) food approach. The mPDO algorithm is proposed to analyze the substantial effects of different dynamic load characteristics on the performance of the distribution networks and the designing of the PV-based and WT-based DGs. The optimization problem incorporates various operational constraints to mitigate energy loss in the distribution networks. Further, the study addresses uncertainties related to the random characteristics of PV and WT power outputs by employing appropriate probability distributions. The mPDO algorithm is evaluated using cec2020 benchmark suit test functions and rigorous statistical analysis to mathematically measure its success rate and efficacy while considering different type of optimization problems. The developed mPDO algorithm is applied to incorporate both PV and WT units, individually and simultaneously, into the IEEE 69-bus distribution network. This is achieved considering residential, commercial, industrial, and mixed time-varying voltage-dependent load demands. The efficacy of the modified algorithm is demonstrated using the standard benchmark functions, and a comparative analysis is conducted with the original PDO and other well-known algorithms, utilizing various statistical metrics. The numerical findings emphasize the significant influence of load type and time-varying generation in DG planning. Moreover, the mPDO algorithm beats the alternatives and improves distributed generators' technical advantages across all examined scenarios.

Boosting cuckoo optimization algorithm via Gaussian mixture model for optimal power flow problem in a hybrid power system with solar and wind renewable energies.

This paper presents a novel approach, the Gaussian Mixture Method-enhanced Cuckoo Optimization Algorithm (GMMCOA), designed to optimize power flow decision parameters, with a specific focus on minimizing fuel cost, emissions, network loss, and voltage deviation. GMMCOA integrates the strengths of COA and GMM while mitigating their individual limitations. While COA offers robust search capabilities, it suffers from initial parameter dependency and the risk of getting trapped in local optima. Conversely, GMM delivers high-speed performance but requires guidance to identify the best solution. By combining these methods, GMMCOA achieves an intelligent approach characterized by reduced parameter dependence and enhanced convergence speed. The effectiveness of GMMCOA is demonstrated through extensive testing on both the IEEE 30-bus and the large-scale 118-bus test systems. Notably, for the 118-bus test system, GMMCOA achieved a minimum cost of $129,534.7529 per hour and $103,382.9225 per hour in cases with and without the consideration of renewable energies, respectively, surpassing outcomes produced by alternative algorithms. Furthermore, the proposed method is benchmarked against the CEC 2017 test functions. Comparative analysis with state-of-the-art algorithms, under consistent conditions, highlights the superior performance of GMMCOA across various optimization functions. Remarkably, GMMCOA consistently outperforms its competitors, as evidenced by simulation results and Friedman examination outcomes. With its remarkable performance across diverse functions, GMMCOA emerges as the preferred choice for solving optimization problems, emphasizing its potential for real-world applications.

No increase of soil wind erosion with the establishment of center pivot irrigation system in Mu-Us sandy land.

Center Pivot Irrigation system (CPIs) is widely used in newly exploited arable land in sandy lands. These sandy lands are currently stable because of climate change and ecological restoration efforts since the beginning of the 21st century in northern China. The exploitation of these fixed sandy lands to arable land with CPIs may affect the soil wind erosion, yet it remains unknown. The temporal changes of CPIs and its effect on wind erosion module were analyzed and modeled from 2000 to 2020 in Mu-Us sandy land using satellite images and Revised Wind Erosion Equation (RWEQ). The establishment of CPIs started from 2010, boomed in 2015 and peaked in 2020. They were mainly transformed from woodland, grassland, and barren land near rivers in east and southeast, and from cropland in inter-dunes in west and southwest of Mu-Us sandy land. The temporal and spatial pattern of CPIs well aligns with the land consolidation and requisition-compensation balance policies. In most of the Mu-Us sandy land, the annual erosion module is <25 t ha-1 a-1. Despite great variation, the annual, Winter and Spring erosion module of the Mu-Us sandy land or in Otog Qian and Yuyang, the CPIs concentrated counties, all decreased during 2000-2019. Although, wind erosion module in CPIs was lower than the surrounding area, it increased in 2019 given the same climate conditions as in 2010. Our results suggest 1) the establishment of CPIs in Mu-Us sandy land greatly depends on the local policy and natural endowment, and 2) although the set-up of CPIs showed no impact on the wind erosion with CPIs accounting for <1 % of Mu-Us sandy land, post-harvest of CPIs should be carefully concerned to prevent soil wind erosion.

Identification of environmental, socioeconomic, water, sanitation, and hygiene (WaSH) factors associated with COVID-19 incidence in the Philippines: A nationwide modelling study.

Despite the implementation of non-pharmaceutical interventions, the threat of coronavirus disease 2019 (COVID-19) remains significant on a global scale. Identifying external factors contributing to its spread is crucial, especially given the World Health Organization's recommendation emphasizing access to water, sanitation, and hygiene as essential in curbing COVID-19. There is a notable discrepancy in access to sanitation facilities, particularly evident in low- and middle-income countries. However, there is a lack of quantitative assessments regarding these factors. This study examines various environmental, socioeconomic, water, sanitation, and hygiene factors and their associations with COVID-19 incidence. All regions in the Philippines were categorized into clusters based on socioeconomic factors. A conceptual structural equation model (SEM) was developed using domain knowledge. The best-fitting SEM for each cluster was determined, and associations between factors and COVID-19 incidence were estimated. The correlation analysis revealed that rainfall, minimum temperature, and relative humidity were positively correlated with weekly COVID-19 incidence in urban regions. Maximum temperature, mean temperature, wind speed, and wind direction were negatively correlated with weekly COVID-19 incidence in rural regions, with time lags of 0, 3, and 7 weeks. In urban regions (Cluster 1), factors such as urbanization rate (1.00), area (-0.93), and population (0.54) were found to be associated with weekly COVID-19 incidence. Conversely, in rural regions (Cluster 2), factors including area (0.17), basic sanitation (0.84), and wind direction (0.83) showed associations with weekly COVID-19 incidence. These factors were causally associated with a latent variable reflecting the hidden confounders associated with COVID-19 incidence. It is important to note that sanitation factors were associated only in rural regions. Improving access to sanitation facilities in rural regions of the Philippines is imperative to effectively mitigate disease transmission in future pandemics. Identification of the causal effect of unobserved confounders with COVID-19 incidence is recommended for future research.

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.

Air speed and direction affect metabolic and thermoregulatory responses during walking and running in a temperate environment.

Revisiting classical experiments on the impact of air resistance on metabolic rate, we aimed to overcome limitations of previous research, notably: low participant numbers (n=1-3), highly turbulent wind, and confounding effects of rising body temperature. In a custom-built wind tunnel with reduced turbulence, 14 participants (8 males, 6 females) walked (5 km.h-1) and ran on a treadmill (70%V̇O2max) at 0, 2, 4 and 6 m.s-1 headwind or tailwind in a counterbalanced design, with rest-breaks between each exposure to avoid rises in body core temperature. Oxygen consumption (V̇O2) exhibited strong linear relationships versus wind direction, dynamic pressure and air speed squared(Vwr2), lower in magnitude for headwind than tailwind. A moderate linear relationship was observed between heart rate, wind direction, dynamic pressure and Vwr2. Below 4 m⸱s-1, the effect of wind was well within inter- and intra-individual variation and equipment uncertainty, and only at wind speeds ≥4 m⸱s-1 did the differences in physiological responses reach statistical significance. Our data indicate that at running speeds below 4 m⸱s-1 (14.4 km/h), indoor treadmill and outdoor running are comparable in terms of the metabolic impact of air movement relative to the person. However, this does not extend to the thermoregulatory effect of wind, with outdoor running providing a higher cooling rate due to the self-generated wind created during running. By removing the confounding impact of core temperature rises, the observed effects of headwind were lower and those of tailwind larger than observed previously. In the context of middle-distance running, headwind created by running at 21.5 km.h-1 would result in a 2.2% increase of V̇O2. A relative tailwind of the same speed would lead to a 3.1% reduction.

Cyanobacterial biocrust alters soil physical properties reducing soil erosion and aerosol production.

Aerosol emission by wind erosion in the arid and semi-arid areas of the world, is of environmental and health significance. Different methods have been used to mitigate aerosol emission among which the biological methods may be the most efficient ones. Although previously investigated, more research is essential to determine how the use of exopolysaccharide (biocrust)-producing cyanobacteria may affect soil physical properties. The objective was to investigate the effects of the cyanobacteria, Microcoleus vaginatus ATHK43 (identified and registered by the NCBI accession number MW433686), on soil physical properties of a sandy soil 15, 30, 60, and 90 d after inoculation. The effects of cyanobacterial biocrust on soil properties including shear strength, soil resistance, aggregate stability (mean weight diameter (MWD) and geometric mean diameter (GMD)), and wind erosion were determined in trays using a wind tunnel. Cyanobacterial inoculation significantly increased MWD (0-1 cm depth, from 0.12 mm to 0.47 mm) and GMD (from 0.3 to 0.5 mm) after a period of 90 d. Biocrust production significantly decreased soil erosion from 55.7 kgm- 2 to 0.3 kgm- 2 (wind rate of 50 kmh- 1), and from 116.42 kgm- 2 to 0.6 kgm- 2 (wind rate of 90 kmh- 1) after 90 d. In conclusion, cyanobacterial biocrust can significantly improve soil physical properties in different parts of the world including the deserts, and reduce aerosol emission by mitigating the destructive effects of wind erosion on soil physical properties.