Weather Conditions Research Articles

A self‐cooling self‐humidifying mosquito carrier backpack for transporting live adult mosquitoes on foot over long distances under challenging field conditions

AbstractIt is often necessary to use motorised transport to move live mosquitoes from distant field collection points into a central insectary, so that their behavioural and/or physiological phenotypes can be assessed under carefully controlled conditions. However, a survey of heritable insecticide susceptibility traits among wild‐caught Anopheles arabiensis mosquitoes, collected across an extensive study area composed largely of wilderness in southern Tanzania, necessitated that live mosquitoes were carried on foot over distances up to 25 km per day because most of the area was impassable by car, motorcycle or even bicycle during the rains. A self‐cooling, self‐humidifying carrier backpack was therefore developed that allows live adult mosquito specimens to be transported across rugged miombo woodland and floodplain terrain throughout the year. This wettable backpack was fabricated from stitched Tanzanian kitenge cotton fabric and polyvinyl chloride–coated fibreglass netting that allows easy circulation of air in and out. An outer cover flap made of cotton towelling embedded inside a kitenge envelope overhangs the fibreglass netting upper body of the bag, to protect mosquitoes from direct sunlight, and can be soaked with water to maintain low temperature and high humidity inside. Mean survival of insectary‐reared female An. arabiensis transported through nine different mobile camps inside the 509 km2 Ifakara‐Lupiro‐Mang'ula wildlife management area (ILUMA WMA), over up to 143 km and 25 days, was statistically indistinguishable from those left in the field insectary over the same period. Although considerable variance of survival was observed between different batches of mosquitoes from the insectary and between individual cups of mosquitoes, the different levels and positions inside the backpack had no influence on this outcome. Temperature and humidity inside the backpack were maintained at standard insectary conditions throughout, despite much more extreme conditions immediately outside. When the backpack was used to transport wild An. arabiensis and Anopheles quadriannulatus across a much larger study area of >4000 km2, encompassing the ILUMA WMA, some nearby villages and adjacent parts of Nyerere National Park (NNP), it achieved a mean survival rate of 58.2% (95% confidence interval 47.5–68.2). Encouragingly, no difference in survival was observed between ILUMA WMA and NNP even though transport back from NNP involves much longer distances, sometimes involving lengthy journeys by car or boat. Overall, this mosquito carrier backpack prototype appears to represent a viable and effective method for transporting live wild‐caught mosquitoes on foot across otherwise impassable terrain under challenging weather conditions with minimal detrimental impact on their survival.

Integrating Thermal Infrared Imaging and Weather Data for Short-Term Prediction of Building Envelope Thermal Appearance

This study presents a novel deep-learning framework for predicting the thermal appearance of building envelopes under varying weather conditions based on a new dataset collected using a thermal infrared camera at 10 min intervals over a one-and-a-half-year period. Unlike existing studies that rely on simulated data or physical models that do not always accurately reflect the complex heat transfer processes in real buildings, we have collected a large dataset showing how a building behaves under different climatic conditions. We propose a novel deep-learning approach that integrates weather data and thermal imagery to predict the temperature distribution on the building façade for the next 24 and 48 h. The model uses a state-of-the-art recurrent neural network architecture, PredRNN V2, with an action conditioning mechanism to incorporate weather forecasting data into the prediction process. We evaluate this approach in terms of average accuracy, prediction accuracy in specific regions, and visual-perceptual performance of the images. The proposed framework achieves a prediction accuracy of 1.5 °C (root mean square error—RMSE) for the 24 h prediction and 2.04 °C (RMSE) for the 48 h prediction, outperforming baseline models in terms of temperature prediction accuracy and structural similarity of the predicted images.

Radiation Limits the Yield Potential of Main Crops Under Selected Agrivoltaic Designs—A Case Study of a New Shading Simulation Method

Agrivoltaics (APVs) represent a growing technology in Europe that enables the co-location of energy and food production in the same field. Photosynthesis requires photosynthetic active radiation, which is reduced by the shadows cast on crops by APV panels. The design of the module rows, material, and field orientation significantly influences the radiation distribution on the ground. In this context, we introduce an innovative approach for the effective simulation of the shading effects of various APV designs. We performed an extensive sensitivity analysis of the photovoltaic (PV) geometry influence on the ground-incident radiation and crop growth of selected cultivars. Simulations (2013–2021) for three representative arable crops in eastern Austria (winter wheat, spring barley, and maize) and seven different APV designs that only limited to the shading effect showed that maize and spring barley experienced the greatest annual above-ground biomass and grain yield reduction (up to 25%), with significant differences between the APV design and the weather conditions. While spring barley had similar decreases within the years, maize was characterized by high variability. Winter wheat had only up to a 10% reduction due to shading and a reduced photosynthetic performance. Cold/humid/cloudy weather during the growing season had more negative yield effects under APVs than dry/hot periods, particularly for summer crops such as maize. The lowest grain yield decline was achieved for all three crops in the APV design in which the modules were oriented to the east at a height of 5 m and mounted on trackers with an inclination of +/−50°. This scenario also resulted in the highest land equivalent ratios (LERs), with values above 1.06. The correct use of a tracker on APV fields is crucial for optimizing agricultural yields and electricity production.

Cultivation and Potential for Biomass Production for Energy and Seed Purposes of Tall Wheatgrass (Agropyron elongatum (Host) Beauv.) Under Sandy Soil and Temperate Climate Conditions

An experiment was conducted to analyse the potential for obtaining biomass for energy purposes and tall wheatgrass (TWG) seeds grown under conditions of varying pre-sowing fertilisation with compost and mineral fertilisation with nitrogen on sandy soils. Field trials were conducted between 2012 and 2015. The study factors were compost from municipal green areas with I-doses of 0, 10 and 20 Mg∙ha−1 added before sowing and nitrogen II-doses of 0, 40, 80 and 120 kg∙ha−1 added each year in the form of ammonium nitrate. During the experiment conducted on sandy soils, a favourable effect of fertilisation on the morphological parameters of above-ground vegetative and generative parts was found. The experiment resulted in high dry matter yields (DMYs) in the range of 9.08–31.38 Mg∙ha−1 and high seed yields (SYs) (635 kg∙ha−1 to as much as 2397 kg∙ha−1), which depended on the applied fertilisation variant. The applied levels of compost fertilisation had a positive effect on the obtained dry matter yields (DMYs) and SY. Analysing the effect of the applied doses of mineral nitrogen fertilisation (40, 80 and 120 kg∙ha−1) on the dry matter yield of TWG under sandy soil conditions, it should be noted that this factor significantly increased the DMY and SY in all years of the study. At the same time, the response of plants to this factor of the study over the years varied and depended on weather conditions. The high energy yield (192.50 GJ∙ha−1–408.93 GJ∙ha−1) closely related to the high DMY indicates the high suitability of TWG as a new grass species under temperate climate conditions grown for biomass energy production and the possibility to harvest seeds when adequately cultivated.

Variation in diurnal and nocturnal movements distances revealed in wintering dabbling ducks in the Mississippi Alluvial Valley

Movement of waterfowl during winter is central to resource acquisition and mortality avoidance, despite the imminent risk to survival and overall fitness induced by hunting disturbance and energy expenditure. Weather and other environmental conditions may influence movement by altering resource needs, in which ducks must balance the trade‐offs of resource acquisition and risk management. We compared how environmental factors influenced total daily diurnal and nocturnal movement distances of three dabbling duck species wintering in the Mississippi Alluvial Valley. We estimated total daily diurnal and nocturnal movement distances of green‐winged teal (Anas crecca; n = 51), American wigeon (Mareca americana; n = 38), and mallards (Anas platyrhynchos; n = 31) using backpack transmitters during the winter period of February–November 2020–2021 and 2021–2022. We used linear mixed effects models to model the influence of weather, hunt season, day of season, and sex on total diurnal and nocturnal movement distances by species. Green‐winged teal moved 7.7% further during the nocturnal period (x̅ = 3.38 km; SE = 0.32; p < 0.001) than during the diurnal period (x̅ = 3.13 km SE = 0.10), while American wigeon and mallards moved 36.6% (x̅ = 4.95 km; SE = 0.20; p < 0.001) and 28.1% (x̅ = 4.39 km; SE = 0.23; p < 0.001) further during the diurnal period than the nocturnal period (x̅ = 3.42 km, SE = 0.28 and x̅ = 3.31 km, SE = 0.22), respectively. Fine‐scale movement distances during the diurnal period were weakly associated with environmental covariates for all species. Conversely, moon illumination influenced nocturnal movement distances for all species. Nightly movement distances of mallards increased by 2.1 times from new to full moon during the hunting season. Conversely, there were no changes in nocturnal movement distance during pre‐hunt and post‐hunt periods when hunting disturbance was absent. In the face of intensifying environmental pressures on movement patterns in dabbling duck populations, this research demonstrates a behavioral response to moon illumination as a mechanism for moving about the landscape for resource acquisition in the presence of human disturbances that induce risk, such as hunting.

Intestinal Parasites and Hematological Parameters in Children Living in Ambatoboeny District, Madagascar

Madagascar is one of the poorest countries in the world. The country’s extreme weather conditions, poor sanitation, and weak economy facilitate the spread of parasitic diseases. Infections with intestinal parasites are particularly dangerous for children because they can cause malnutrition and anemia, which, in turn, have a negative effect on children’s cognitive functions and physical development. The aim of the present study was to analyze the prevalence of intestinal parasites and to assess hematological parameters in a group of children living in northern Madagascar. The screening was conducted in May 2024 in the Clinique Medicale Beyzym in Manerinerina, the Ambatoboeny district. It involved a sample of 208 children aged 0–17 years. Single stool samples were collected from all study participants. The samples were fixed in SAF fixative and then transported from Africa to Europe for further diagnostics at the Department of Epidemiology and Tropical Medicine, the Military Institute of Medicine–the National Research Institute in Poland. First, the samples were analyzed by light microscopy methods using three different diagnostic techniques (direct smear, decantation with distilled water, and the Fülleborn method). Next, they were tested by molecular biology methods (real-time PCR). Blood samples for the assessment of hematological parameters were collected at the healthcare center in Madagascar. The prevalence of intestinal parasites in the study sample was 61.5%. Helminths were found in 15.2% of the investigated children, and Giardia intestinalis (20.5%) was found to be the most prevalent parasite in the study population. Most infections were caused by potentially pathogenic stramenopila Blastocystis spp. (32.0%). Mean Hb, HCT, MCV, MCH, and MCHC levels in the study participants were below normal values. However, no correlation was found between the presence of a parasitic infection and low hematological parameters, which are a clinical sign of anemia. High rates of infections with intestinal parasites in children living in northern Madagascar support the necessity to introduce long-term preventive measures, which would limit the spread of parasitic diseases in the Malagasy population. Low hematological parameters in non-infected children may be indicative of persistent malnutrition or infection with other parasites, e.g., malaria or schistosomiasis.

Organic fertilizer integrated with marine waste derived CaCO3 nanocarrier system: A focus on enhanced yield and quality in tomato cultivation

Tomatoes are rich in lycopene, β-carotene, ascorbic acid and other mineral sources including phosphorus, potassium, zinc, magnesium and iron. Major constraints in tomato cultivation were high cost, poor cultivation due to adverse weather conditions, pest attacks, microbial infections and nutritional deficiency complications. Conventional fertilizers, pesticides, fungicides and growth regulators are effective at higher concentration, which induces specific toxic effects on soil fertility, plant yield and also affects the health status of humans, animals and soil associated microbes. The use of organic fertilizers to meet the soil nutrient demand increases the acidity of soil affecting plant growth, which turned the focus of researchers towards nanofertilizer. The present study focuses on synthesis of marine waste derived CaCO3 nanoparticles formulated with azadirachtin and panchakavya emulsion to develop a CaCO3 nanofertilizer. CaCO3 nanofertilizer developed through this study was investigated for its material properties and behavioral traits. Further, the in-vitro antifungal impact of the CaCO3 nanofertilizer was examined, and it was sprayed on tomato plants via foliar spray. CaCO3 nanofertilizer effectively inhibited fusarium wilt causing plant fungal pathogen and also exhibited enhanced growth and yield of tomatoes against pest attack and nutritional deficiency with effect to foliar treatment. Also, CaCO3 nanofertilizer enhanced the total carotenoid level and essential nutritional minerals in fruit yield of tomatoes. Overall, fabricated CaCO3 nanofertilizer exhibits synergistic role of fertilizer, pesticide, fungicide and growth regulator in tomato cultivation. It suggests that, CaCO3 nanofertilizer generated from renewable biowaste will become the innovative platform for sustainable agriculture.

Effects of Rainfall Variability on Maize Production in Migori County, Kenya

Maize is the main staple food crop in Kenya and is of vital concern to agricultural policy decisions, food security, and the overall development of the sector and the economy. It is also the dominant staple food crop in Migori-County. However, there has been a declining trend in maize production among farmers in the study area threatening household food security. This study was conducted in Migori County using cross sectional survey research design. A sample size of 384 households was selected through stratified and systematic sampling techniques though just 310 households accepted to be interviewed. Data was collected using a structured questionnaire. Validated secondary weather data for the period 2011-2023 was obtained from the Migori Meteorological Station. The collected data was entered into SPSS software, version 20, and analysed using both descriptive and inferential statistical methods. The results indicated that 60% of households have an adequate food supply, while 40% face food shortages. Further, there was a strong positive and significant relationship between maize production (yield) and annual weather conditions from 2018 to 2023 (r = 0.845, p = 0.05). This indicates that changes in weather patterns, such as rainfall and temperature, had a significant influence on maize yields during the study period. Hence, farmers should be encouraged to use income from cash crops to purchase food stocks and engage in non-farm activities as alternative income sources to mitigate the effects of rainfall variability and climate change on food security.

A Multi-Tiered Collaborative Network for Optical Remote Sensing Fine-Grained Ship Detection in Foggy Conditions

Ship target detection faces the challenges of complex and changing environments combined with the varied characteristics of ship targets. In practical applications, the complexity of meteorological conditions, uncertainty of lighting, and the diversity of ship target characteristics can affect the accuracy and efficiency of ship target detection algorithms. Most existing target detection methods perform well in conditions of a general scenario but underperform in complex conditions. In this study, a collaborative network for target detection under foggy weather conditions is proposed, aiming to achieve improved accuracy while satisfying the need for real-time detection. First, a collaborative block was designed and SCConv and PCA modules were introduced to enhance the detection of low-quality images. Second, the PAN + FPN structure was adopted to take full advantage of its lightweight and efficient features. Finally, four detection heads were used to enhance the performance. In addition to this, a dataset for foggy ship detection was constructed based on ShipRSImageNet, and the mAP on the dataset reached 48.7%. The detection speed reached 33.3 frames per second (FPS), which is ultimately comparable to YOLOF. It shows that the model proposed has good detection effectiveness for remote sensing ship images during low-contrast foggy days.

A geometric model with stochastic error for abnormal motion detection of portal crane bucket grab

Abnormal swing angle detection of bucket grabs is crucial for efficient harbor operations. In this study, we develop a practically convenient swing angle detection method for crane operation, requiring only a single standard surveillance camera at the fly-jib head, without the need for sophisticated sensors or markers on the payload. Specifically, our algorithm takes the video images from the camera as input. Next, a fine-tuned ‘the fifth version of the You Only Look Once algorithm’ (YOLOv5) model is used to automatically detect the position of the bucket grab on the image plane. Subsequently, a novel geometric model is constructed, which takes the pixel position of the bucket grab, the steel rope length provided by the Programmable Logic Controller (PLC) system, and the optical lens information of the camera into consideration. The key parameters of this geometric model are statistically estimated by a novel iterative algorithm. Once the key parameters are estimated, the algorithm can automatically detect swing angles from video streams. Being analytically simple, the computation of our algorithm is fast, as it takes about 0.01 s to process one single image generated by the surveillance camera. Therefore, we are able to obtain an accurate and fast estimation of the swing angle of an operating crane in real-time applications. Simulation studies are conducted to validate the model and algorithm. Real video examples from Qingdao Seaport under various weather conditions are analyzed to demonstrate its practical performance.

Introducing CHiDO-A No Code Genomic Prediction software implementation for the characterization and integration of driven omics.

Climate change represents a significant challenge to global food security by altering environmental conditions critical to crop growth. Plant breeders can play a key role in mitigating these challenges by developing more resilient crop varieties; however, these efforts require significant investments in resources and time. In response, it is imperative to use current technologies that assimilate large biological and environmental datasets into predictive models to accelerate the research, development, and release of new improved varieties that can be more resilient to the increasingly variable climatic conditions. Leveraging large and diverse datasets can improve the characterization of phenotypic responses due to environmental stimuli and genomic pulses. A better characterization of these signals holds the potential to enhance our ability to predict trait performance under changes in weather and/or soil conditions with high precision. This paper introduces characterization and integration of driven omics (CHiDO), an easy-to-use, no-code platform designed to integrate diverse omics datasets and effectively model their interactions. With its flexibility to integrate and process datasets, CHiDO's intuitive interface allows users to explore historical data, formulate hypotheses, and optimize data collection strategies for future scenarios. The platform's mission emphasizes global accessibility, democratizing statistical solutions for situations where professional ability in data processing and data analysis is not available.

U-Space Contingency Management Based on Enhanced Mission Description

Loss of communication, low battery, or bad weather conditions (like high-speed wind) are currently managed by performing a return to launch (RTL) point maneuver. However, the execution of this procedure can pose a safety threat since it has not been considered within the mission planning process. This work proposes an advanced management of contingency events based on the integration of a new U-space service that enhances mission description. The proposed new service, deeply linked to demand capacity balance and strategic deconfliction services, assigns alternative safe landing spots by analyzing the planned mission. Two potential solutions are characterized (distinguished primarily by the number of contingency vertiports assigned): contingency management based on the assignment of a single alternative vertiport to each mission (static) or the allocation of a set of different contingency vertiports that are valid during certain time intervals. It is proven that this enhanced mission planning could ensure that U-space volumes operate in an ultra-safe system conditions while facing these unforeseen events, highlighting its importance in high-risk scenarios like urban air mobility deployments.

Impact of Harvest Delay and Barley Variety on Grain Nutritional Composition and Mycotoxin Contamination

This study investigated the effects of delayed harvesting, varying meteorological conditions, and barley variety on Fusarium spp. infection rates, nutritional composition, and mycotoxin contamination in barley grains. Field experiments were conducted from 2020 to 2022 and involved two barley varieties: ‘Laureate’ for malting and ‘Luokė’ for feed. The results indicated that the dominant Fusarium species isolated were F. avenaceum, F. culmorum, F. poae, F. sporotrichioides, F. tricinctum, and F. equiseti. These tended to increase in number with delayed harvest times and were more prevalent during harvest periods of higher precipitation (p < 0.05). Malting barley had higher starch and lower protein content compared to feed barley (p < 0.05). Delayed harvesting generally increased dry matter, crude fat, and crude ash contents while decreasing crude protein, zinc, and iron contents (p < 0.05). Mycotoxin analysis revealed significant differences under specific weather conditions. HT-2 toxin levels were higher under slightly warmer and wetter conditions during flowering, with harvest conditions similar to the long-term average. Zearalenone levels increased with dry, warm growing seasons followed by rainy harvests. Nivalenol and enniatin levels increased with rainy growing seasons and dry, warm harvests. Deoxynivalenol concentrations did not reach the limit of quantification throughout the study. No consistent trend was observed for higher contamination in any specific barley variety (p > 0.05). The strongest correlations between mycotoxins and nutritional value indicators were observed with less-studied mycotoxins, such as nivalenol and enniatins, which exhibited negative correlations with crude protein (p < 0.01), crude fat (p < 0.05), and zinc (p < 0.01), and positive correlations with crude ash (p < 0.05) and phosphorus (p < 0.01).

A prospective study analyzing the use of free public sunscreen dispensers.

This study evaluates the impact of sunscreen dispensers in increasing sunscreen usage and awareness in Summerside, Prince Edward Island, Canada. In June 2022, three touchless sunscreen dispensers offering free Health Canada-approved SPF 30 sunscreen were installed in areas of high pedestrian traffic. A team of four city workers gathered observational data over a 17-day span between July and August 2022. Seven days of monitoring took place at the city ballpark, seven at a children's park, and three at the city beachfront boardwalk. In total, 1202 individuals were observed near the dispensers, of whom 209 utilized the dispensers, yielding a usage rate of 17.4 per 100 persons. The usage rate varied by location, with the children's park recording a higher average (40.0 users per 100 persons), and was also weather-dependent, with increased usage on sunny days (average of 52.2 users per 100 persons). The majority of users were classified with a Fitzpatrick skin type of I or II. The sunscreen bags, designed for 2000 applications, did not require refilling during the observation period. The QR code associated with the dispensers was scanned 14 times. The findings of this study indicate that installing sunscreen dispensers in public spaces may increase the frequency of sunscreen application. Both the location of the dispensers and the perception of weather conditions seem to impact usage rates.

The influence of meteorological conditions of the Non-Chernozem zone on the phytosanitary condition of grain bean crops

There is a tendency to expand the area of bean cultivation in the northern direction, which is due to climatic changes and breeding achievements. There are 191 varieties of beans registered in the state register of breeding achievements approved for use, of which 31 varieties are recommended for cultivation in the belt between 50° and 60° latitude. The relevance of bean cultivation in the Non-Chernozem zone is increasing. This is due to the increased demand for beans, which are characterized by high nutritional value. Also, this crop is promising as an alternative in grain crop rotations. The study of the phytosanitary condition of bean plants in potentially new cultivation regions in order to develop a crop protection system is of interest. The promotion of crops to new territories is inevitably accompanied by phytosanitary risks, which have been little studied due to insufficient information about bean diseases. The literature provides an assessment of potential threats. However, their manifestation is closely related to the climatic and weather conditions of the growing season. The analysis of the interrelationships of the phytosanitary condition of crops with the temperature and humidity regimes of the bean growing period is relevant.

Deciphering decadal urban ozone trends from historical records since 1980

Abstract Ozone pollution is a major environmental threat to human health. Timely assessment of ozone trends is crucial for informing environmental policy. Here we show that for the most recent decade (2013–2022) in the Northern Hemisphere, warm-season (April-September) mean daily 8-h average maximum (MDA8) ozone increases much faster in urban regions with top ozone levels (mainly in North China Plain, 1.2 ± 1.3 ppbv year−1) than that in other low-ozone regions (0.2 ± 0.9 ppbv year−1). These trends widen the ozone differences across urban regions, and increase extreme pollution levels and health threats from a global perspective. Comparison of historical trends in different urban regions reveals that, ozone increases in China during 2013–2022 differ in magnitude and mechanisms from historical periods in other regions since 1980. This reflects a unique chemical environment characterized by exceptionally high nitrogen oxides and aerosol concentrations, where reducing ozone precursor emissions leads to substantial ozone increase. Ozone increase in China has slowed down in 2018–2022 compared to 2013–2017, driven by ongoing emission reductions but with ozone-favorable weather conditions. Historical ozone evolution in Japan and South Korea indicates that ozone increases should be suppressed with continuous emission reduction. Increasing temperature and associated wildfires have also reversed ozone decreases in the US and Europe with anthropogenic ozone control slowing down in recent decades.

Not only cold but also heat: the effect of maternal exposure to high temperatures during gestation on neonatal mortality in pre-transitional Casalguidi, 1819–1859

Consideration of weather and the environment is becoming increasingly prominent in the field of historical demography. Early studies on infant mortality have paved the way for this type of analysis, shedding light on the significant impact of cold weather conditions on child survival. However, recent research on contemporary populations has drawn attention to the increased risk of adverse birth outcomes due to maternal exposure to heat during pregnancy. The present study aims to validate this finding in a pre-transitional population, specifically focusing on its effects on neonatal mortality. To our knowledge, this analysis is being applied to such populations for the first time, with the goal of exploring whether factors other than cold winters may have also influenced mortality mechanisms during this crucial life stage in historical populations. The results show that heat exposure significantly affected early neonatal mortality, and they also reveal that the susceptibility window was limited to the second trimester of gestation. Temperature-related risks of death were influenced by the tie the family had to the land, with sharecroppers being at the lowest risk. This finding was attributed more to cultural elements associated with the value of children within this social group than to purely economic factors related to living conditions.

Assessing the Influence of Occupancy Factors on Energy Performance in US Small Office Buildings

Office buildings are responsible for about 35% of the total electricity in the US and over 70% of building energy consumption occurs during occupancy periods. Therefore, understanding occupancy behavior is crucial for reducing building energy consumption. However, given the stochastic nature of occupant behavior, identifying which occupancy parameters have the most impact on energy consumption poses a considerable challenge. This study aims to investigate and quantify the impact of various occupancy parameters on the energy performance of a US small-sized office building using an EnergyPlus-based nationwide energy simulation. First, dynamic occupancy schedules are created based on different occupancy parameters using an agent-based model. Next, the generated dynamic occupancy schedules are integrated into a small office building model from the Department of Energy’s prototypes. This creates a dataset of occupancy parameters and building energy performance across various climate zones. Finally, various feature selection and statistical analysis methods are applied to the generated dataset. This helps identify significant occupancy parameters and quantify their impact on building energy performance across different climate zones. According to the results of the study, buildings located in cool marine, mixed marine, and warm marine climate zones had lower total energy consumption compared to other zones. Additionally, feature selection methods identified “Occupant Density” as the primary significant variable impacting energy consumption, across all climate zones. These findings offer valuable insights into the influential occupancy parameters across various climate zones, highlighting the importance of tailoring occupancy schedules to enhance energy efficiency. They provide practical guidance that can be directly applied to optimize energy consumption and achieve significant energy savings in small office settings with different weather conditions.

On the issue of forecasting crop yields for the purposes of adaptive landscape agriculture

Long-term monitoring (1998–2023) of the yield of clover-timothy grass stands of the first year of use was carried out in order to find patterns of influence of landscape environmental conditions on it in various agroclimatic conditions. The research was conducted within the moraine hill located at the Gubino VNIIMZ agro-testing site in the Tver region. Soil-forming rocks are two-membered deposits consisting of an upper layer composed of relatively light rocks, underlain by moraine bouldery loam. The grass stands were exploited without fertilizers in a single-cut mode on a field divided into 120 plots. Using regression analysis, the influence of landscape and soil environment factors was determined: relief, physical and agrochemical properties of soils on grass yield, as well as the dependence of the degree of this impact on climatic conditions. It was found that the yield of perennial grasses is most strongly influenced by various fractions of the granulometric composition of soils – from stones to dust (up to 16 % of its variability) and the altitude of the location (up to 38 %), since the thermal and water-air characteristics of soils and vegetation largely depend on them. Terrain characteristics such as steepness and curvature of the surface have a minor impact on grass yield (up to 12 %). The degree of influence of agro-landscape environmental factors on the growth of grasses is largely regulated by fluctuations in weather conditions. “Climate scenarios” of a specific factor – sets of weather parameters under which its effect on the production process of a crop is manifested – in the years of sowing and mowing, as a rule, do not differ fundamentally. Knowing the nature of the influence of climatic factors allows us to more accurately predict crop yields within an agricultural landscape and, thus, optimize the location of crops on the territory of a particular farm.

The Use of Laser Sensing for Solving Meteorological Problems Related to Researching and Ensuring the Safety of Space Flights

This paper is devoted to the issue of using laser (lidar) sensing to determine wind speed and direction when solving practical problems during the analysis of meteorological conditions in the area around spaceports. This issue is relevant both for making decisions on the possibility of a safe launch of a launch vehicle and for conducting search and rescue operations using groups of manned and unmanned aerial vehicles. Based on numerical and experimental modeling, it is shown that lidars provide highly accurate measurements of wind speed profiles and allow for the determination of weak wind shear in vertical and horizontal directions. This paper proposes a method for determining the main parameters of lidar sensing (range, resolution, detectability, etc.), which allows for the capabilities of this technology in solving the practical problems of meteorological monitoring to be predicted. Of particular interest in this article are experimental modeling data verifying the proposed calculation methods and the experimental determination of the capabilities of lidar diagnostics. This paper summarizes the data from multi-month experiments measuring wind speed in clear weather conditions when other means of remote diagnostics are ineffective. As a result of the experiments, a statistical distribution of the maximum range of wind speed measurement in normal weather conditions with natural variation in the concentration of scattering particles in the atmosphere was obtained. This article also discusses the possibility of combining lidars and meteorological radars for the meteorological support of flights.