A complete framework of predicting the attributes of sea clutter under different operational conditions, specified by wind speed, wind direction, grazing angle, and polarization, is proposed for the first time. This framework is composed of empirical spectra to characterize sea-surface profiles under different wind speeds, the Monte Carlo method to generate realizations of sea-surface profiles, the physical-optics method to compute the normalized radar cross-sections (NRCSs) from individual sea-surface realizations, and regression of NRCS data (sea clutter) with an empirical probability density function (PDF) characterized by a few statistical parameters. JONSWAP and Hwang ocean-wave spectra are adopted to generate realizations of sea-surface profiles at low and high wind speeds, respectively. The probability density functions of NRCSs are regressed with K and Weibull distributions, each characterized by two parameters. The probability density functions in the outlier regions of weak and strong signals are regressed with a power-law distribution, each characterized by an index. The statistical parameters and power-law indices of the K and Weibull distributions are derived for the first time under different operational conditions. The study reveals succinct information of sea clutter that can be used to improve the radar performance in a wide variety of complicated ocean environments. The proposed framework can be used as a reference or guidelines for designing future measurement tasks to enhance the existing empirical models on ocean-wave spectra, normalized radar cross-sections, and so on.

The joint probability density function of wind speed and wind direction serves as the mathematical basis for directional wind energy assessment. In this study, a nonparametric joint probability estimation system for wind velocity and direction based on copulas is proposed and empirically investigated in Inner Mongolia, China. Optimal bandwidth algorithms and transformation techniques are used to determine the nonparametric copula method. Various parameter copula models and models without considering dependency relationships are introduced and compared with this approach. The results indicate a significant advantage of employing the nonparametric copula model for fitting joint probability distributions of both wind speed and wind direction, as well as conducting correlation analyses. By utilizing the proposed KDE-COP-CV model, it becomes possible to accurately and reliably analyze how wind power density fluctuates in relation to wind direction. This study reveals the researched region possesses abundant wind resources, with the highest wind power density being highly dependent on wind direction at maximum speeds. Wind resources in selected regions of Inner Mongolia are predominantly concentrated in the northwest and west directions. These findings can contribute to improving the accuracy of micro-siting for wind farms, as well as optimizing the design and capacity of wind turbine generators.

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.

The cultivation of cashew crops carries numerous economic advantages, and countries worldwide that produce this crop face a high demand. The effects of wind speed and wind direction on crop yield prediction using proficient deep learning algorithms are less emphasized or researched. We propose a combination of advanced deep learning techniques, specifically focusing on long short-term memory (LSTM) and random forest models. We intend to enhance this ensemble model using dynamic time warping (DTW) to assess the spatiotemporal data (wind speed and wind direction) similarities within Jaman North, Jaman South, and Wenchi with their respective production yield. In the Bono region of Ghana, these three areas are crucial for cashew production. The LSTM-DTW-RF model with wind speed and wind direction achieved an R2 score of 0.847 and the LSTM-RF model without these two key features R2 score of (0.74). Both models were evaluated using the augmented Dickey-Fuller (ADF) test, which is commonly used in time series analysis to assess stationarity, where the LSTM-DTW-RF achieved a 90% level of confidence, while LSTM-RF attained an 87.99% level. Among the three municipalities, Jaman South had the highest evaluation scores for the model, with an RMSE of 0.883, an R2 of 0.835, and an MBE of 0.212 when comparing actual and predicted values for Wenchi. In terms of the annual average wind direction, Jaman North recorded (270.5 SW°), Jaman South recorded (274.8 SW°), and Wenchi recorded (272.6 SW°). The DTW similarity distance for the annual average wind speed across these regions fell within specific ranges: Jaman North (±25.72), Jaman South (±25.89), and Wenchi (±26.04). Following the DTW similarity evaluation, Jaman North demonstrated superior performance in wind speed, while Wenchi excelled in wind direction. This underscores the potential efficiency of DTW when incorporated into the analysis of environmental factors affecting crop yields, given its invariant nature. The results obtained can guide further exploration of DTW variations in combination with other machine learning models to predict higher cashew yields. Additionally, these findings emphasize the significance of wind speed and direction in vertical farming, contributing to informed decisions for sustainable agricultural growth and development.

Biogeographical barriers to gene flow are central to plant phylogeography. In East Asia, plant distribution is greatly influenced by two phylogeographic breaks, the Mekong-Salween Divide and Tanaka-Kaiyong Line, however, few studies have investigated how these barriers affect the genetic diversity of species that are distributed across both. Here we used 14 microsatellite loci and four chloroplast DNA fragments to examine genetic diversity and distribution patterns of 49 populations of Populus rotundifolia, a species that spans both the Mekong-Salween Divide and the Tanaka-Kaiyong Line in southwestern China. Demographic and migration hypotheses were tested using coalescent-based approaches. Limited historical gene flow was observed between the western and eastern groups of P. rotundifolia, but substantial flow occurred across both the Mekong-Salween Divide and Tanaka-Kaiyong Line, manifesting in clear admixture and high genetic diversity in the central group. Wind-borne pollen and seeds may have facilitated the dispersal of P. rotundifolia following prevalent northwest winds in the spring. We also found that the Hengduan Mountains, where multiple genetic barriers were detected, acted on the whole as a barrier between the western and eastern groups of P. rotundifolia. Ecological niche modeling suggested that P. rotundifolia has undergone range expansion since the last glacial maximum, and demographic reconstruction indicated an earlier population expansion around 600 Ka. The phylogeographic pattern of P. rotundifolia reflects the interplay of biological traits, wind patterns, barriers, niche differentiation, and Quaternary climate history. This study emphasizes the need for multiple lines of evidence in understanding the Quaternary evolution of plants in topographically complex areas.

The Sistan region in Southeastern Iran is one of the world\'s most sensitive areas when it comes to sandstorms and wind erosion. One of the most influential factors in interpreting sandstorms is sand drift potential (DP), which is directly related to wind speed. Accurately, monitoring this phenomenon is still being determined, considering various temporal scales. Therefore, the main aim of this research is to analyze the trend of DP on monthly and annual scales. Our results showed that monthly variations of DP reached the highest and lowest values in July (609 VU) and January (47 VU), respectively. Blowing sand predominantly moved southeast, and the directional index fluctuated from 0.88 to 0.94. The annual DP was measured equal to 2700 VU, signifying a relatively high value when compared to other arid regions worldwide. The trend analysis results obtained from the Mann-Kendall test revealed both positive trends during the period 1987-2001 and negative ones from 2002 to 2016). However, the positive trend was found statistically insignificant. Furthermore, Sen\'s slope test results demonstrated that a negative trend could be observed with a steeper slope during July, September, and August, while a positive trend could be observed with a steeper pitch during November, December, and June. We recommend that land managers and stakeholders involved in controlling blowing sand using biological and physical methods should consider these trends in the Sistan region. Implementing nature-based solutions or control strategies should focus on these temporal sequences.

California Leafy Green Products Handler Marketing Agreement (LGMA) established food safety metrics with guidance recommendations of 366 m (1,200 feet) and 1,609 m (1 mile) distances between production fields of leafy greens and a concentrated animal feeding operation (CAFO) containing >1,000 and >80,000 head of cattle, respectively. This study evaluated the effect of these distance metrics and environmental factors on the occurrence of airborneEscherichia coliin proximity to seven commercial beef cattle feedlots located in Imperial Valley, California. A total of 168 air samples were collected from seven beef cattle feedlots during March and April 2020, which were the months implicated in the 2018 Yuma Arizona lettuce outbreak of E. coli O157:H7. The distance between air sampling sites and the edge of the feedlot ranged from ∼0 to ∼2,200 m (∼1.3 mile), with each sample comprised of 1,000 L of processed air taken at a 1.2 m elevation over a 10-minute duration. E. colicolonies were enumerated on CHROMagar ECC selective agar and confirmed with conventional PCR. Meteorological data (air temperature, wind speed, wind direction, relative humidity) were collectedin situ. The prevalence and mean concentration ofE. coliwere 6.55% (11/168) and 0.09 CFU per 1,000 L of air, with positive samples limited to within 37 m (120 ft) of the feedlot.Based on logistic regression, the odds of airborne E. coli detection were associated with little to no wind and close proximity to a feedlot. This pilot study found limited dispersal of airborne E. coli in proximity to commercial feedlots in Imperial Valley, with light-to-no wind and proximity within 37 m of a feedlot significant factor-associated airborne E. coli in this produce-growing region of California.

Due to the COVID-19 pandemic, lockdown restrictions were established around the world. Many studies have assessed whether these restrictions affected atmospheric pollution. Comparison between them is difficult as the periods of time considered are generally not the same and thus, different conclusions may be reached. Besides, most of them consider mean daily pollutant concentration, despite differences being observed according to the time of day. In this study, the hourly levels of PM10, PM2.5 and black carbon (BC) in an industrial suburban area in the north of Spain were analysed from May 2019 to June 2020 and compared with those from the literature, using the same period in each case. In general, the highest concentrations were reached when the wind direction came from the southwest (where a steelworks, a coal-fired power plant and other industries are located) and during the night-time, both before and during the lockdown. The highest concentrations of PM10, PM2.5 and BC were observed from December to February (on average: 45, 17 and 1.3 μg m-3, respectively). The decrease/increase in those pollutants levels during the lockdown were found to be highly dependent on the period considered. Indeed, PM10 can be found to decrease by up to 39% or increase by 12%; PM2.5 can decrease by 21% or increase by up to 36%; and BC, although it generally decreases (by up to 42%), can increase by 7.4%.

With continuous global warming, growing urban population density, and increasing compactness of urban buildings, VD (void deck) street design has become increasingly popular in city planning, especially in tropical countries. However, understanding on traffic pollutant dispersion inside the street canyons with VDs is still at early stage. This paper evaluates quantitatively the effects of VD location and wind direction on the ventilation and traffic pollutant exposure inside the street canyon with VDs. The results show that under seven wind directions (0°, 15°, 30°, 45°, 60°, 75°, and 90°), the VD provides higher ACH than that of the regular canyon, especially at high α (angle between the approaching wind and the canyon axis). Also, mean K (dimensionless pollutant concentration) values of the canyon wall and pedestrian respiration plane on one side where VD is located are significantly reduced compared to the regular canyon. Therefore, when VDs are at both buildings, both pedestrian respiration planes and walls have the lowest K values, thus providing the best living environment for pedestrians and near-road residents. In addition, as α increases, the K values on both respiration planes significantly decrease except for the leeward respiration plane of the canyon with the windward VD. These findings can help to design urban street canyons for mitigating traffic pollution risk and improving ventilation in tropical cities with frequently changing wind directions.

When a fire occurs in a street canyon, smoke recirculation is the most harmful factor to human beings inside the canyon, while the wind condition is an essential factor determining if the smoke is recirculated. This paper focuses on the wind direction\'s effect on buoyancy-driven fire smoke dispersion in a street canyon, which is innovative research since the effect of wind direction has not been reported before. In this study, an ideal street canyon model with a height-width ratio of 1 was established, and both the wind velocity and wind direction were changed to search for the critical point at which smoke recirculation occurs. The results show that with an increase in the wind direction angle (the angle of wind towards the direction of the street width), the smoke recirculation could be distinguished into three regimes, i.e., the \"fully re-circulation stage\", the \"semi re-circulation stage\", and the \"non-recirculation stage\". The critical recirculation velocity was increased with the increase in the wind direction angle, and new models regarding the critical wind velocity and the Froude number were proposed for different wind direction conditions.