Impact Of Weather Conditions Research Articles

Crop formation and green mass quality of maize under the conditions of central agroclimatic region of Komi Republic

In the field experiment on the area of 100 m2 the impact of weather conditions on green mass formation and chemical composition of early ripe three-line maizehybrid DorkaMGT grown in the central agroclimatic region of the Komi Republic was studied. According tothe data of three vegetation seasons (2018-2020), the maize plants can form up to 56.5 t/ha green mass in the northern non-black earth region withthe sum of average daily active temperatures over 10 °C (GDD10) of about 1500 °C and a hydrothermal coefficient (HTC) of about 2. The decrease in GDD10 of 30 % and moderate precipitation (HTC = 2.3) resulted in a proportional decrease in green mass yield. During the growing season with abundant precipitation (HTC = 4), the production potential efficiency of maize plants fell significantly as evidenced by a decrease in yield by more than 4 times. The average yield of green mass over 3 years was 35.5 t/ha. No significant effects of vegetation conditions on the content of basic chemical elements and nutrients (sugars, protein) in plant biomasshave been revealed. The rate of visible photosynthesis of maize leaves reached 13-14 pmol CO2 / (m2s) during the period of intensive vegetative growth (phase of five leaves) and decreased during the transition to generative development (“heading of panicle” phase). In general, the data obtained indicate the possibility of growing early ripe maize hybrid Dorka MGT in the central agroclimatic region of the Komi Republic to obtain high-quality green feed and silage.

The impact of weather conditions in different years on the biochemical composition of linseed oil

Background. Linseed oil is a versatile product with varying biochemical composition. Linseed breeding is aimed at producing cultivars with different chemical properties in their oil. The crop is widespread but the environment has a great effect on its fatty acid biosynthesis.Materials and methods. The impact of weather conditions on the variations in fatty acids composition was studied. Twenty linseed cultivars and accessions of diverse origin and with varying oil composition from the VIR collection were grown in Tomsk Province in 2016–2018. The content of 15 fatty acids (lauric, myristic, palmitic, palmitoleic, margaric, stearic, oleic, cis-vaccenic, linoleic, linolenic, arachidic, eicosenic, arachido nic, behenic, and lignoceric) was assessed in linseed oil using gas–liquid chromatography.Results. The tested material presented a wide diversity of genes controlling different steps of fatty acids biosynthesis and genetic mechanisms involved in the responses to the changing environment. The analysis of variance proved that the content of oleic, linoleic, linolenic and lignoceric acids was controlled solely by the genotype. The content of palmitic and stearic acids was influenced by both the genotype and environment. The synthesis of lauric and cis-vaccenic acids was significantly affected by the weather. Practically all acids, except linoleic and linolenic ones, showed a very high random variation, which in our experiment included genotype × environment interaction. The accessions differed in the range of variation in their characters under diffe rent conditions. There was no definite regularity in the hanges of fatty acid content in the tested genotypes during 3 years.Conclusion. The assessed genotypes probably possess different regulatory mechanisms for fatty acid biosynthesis. Thus, they present a diverse stock for further investigations into fatty acid biosynthesis and for the development of new linseed cultivars widely adaptable to environmental conditions.

Weather as a potential cause of regional differences in the dynamics of COVID-19 transmission in Poland: implications for epidemic forecasting.

COVID‑19 is an infectious disease caused by SARS-CoV-2. Little is known on the impact of weather conditions on the transmission of COVID‑19. We aimed to assess correlations between 6 different meteorologic parameters and the transmission dynamics of the COVID‑19 pandemic in 16 administrative regions (voivodeships) of Poland. Data for analysis were obtained from epidemiologic reports of the Polish Ministry of Health. For each voivodeship, one synoptic station was selected to provide meteorologic data on daily maximum and minimum temperatures, variability of daily temperature, sunshine duration, relative humidity, and wind speed. The periods with significant weather impact were determined using multiple linear regression. Cross‑correlation function (CCF) and random forest models were used to assess correlations between meteorologic parameters and the incidence of COVID‑19 as well as the number of hospitalizations for COVID‑19. In all voivodeships, the incidence of new COVID‑19 cases correlated with relative humidity (CCF = 0.41), daily maximum temperature (CCF = -0.41), variability of daily temperature (CCF = -0.40), and sunshine duration (CCF = 0.35). For all parameters, a similar time lag of 10 to 14 days was noted. There were no significant correlations for wind speed in most voivodeships. The risk of hospitalization for COVID‑19 correlated with daily maximum temperature (CCF = -0.48; time lag, 10 days) and sunshine duration (CCF = -0.45; time lag, 10 days). The delayed effects of the meteorologic factors on the incidence of COVID‑19 and the risk of hospitalization for COVID‑19 were observed. In each voivodeship, the dynamics of COVID‑19 transmission was most strongly affected by relative humidity and daily maximum temperature.

Impact of Weather Conditions on the Operation of Power Unit Cooling Towers 905 MWe

The paper presents the results of measurements and calculations concerning the influence of weather conditions on the operation of wet cooling towers of 905 MWe units of the Opole Power Plant (Poland). The research concerned the influence of temperature and relative humidity of air, wind and power unit load on the water temperature at the outlet from the cooling tower, the level of water cooling, cooling efficiency and cooling water losses. In the cooling water loss, the evaporation loss stream and the drift loss stream were distinguished. In the analyzed operating conditions of the power unit, for example, an increase in Tamb air by 5 °C (from 20–22 °C to 25–27 °C) causes an increase in temperature at the outlet of the cooling tower by 3–4 °C. The influence of air temperature and humidity on the level of water cooling ΔTw and cooling efficiency ε were also found. In the case of ΔTw, the effect is in the order of 0.1–0.2 °C and results from the change in cooling water temperature and the heat exchange in the condenser. The ε value is influenced by air temperature and humidity, which determine the wet bulb temperature value. Within the range of power changes of the unit from 400 to 900 MWe, the evaporated water stream m˙ev, depending on the environmental conditions, increases from 400–600 tons/h to the value of 1000–1400 tons/h. It was determined that in the case of the average power of the unit at the level of 576.6 MWe, the average values of the evaporation and drift streams were respectively 0.78% and 0.15% of the cooling water stream. Using statistical methods, it was found that the influence of wind on the level of water cooling, cooling efficiency and cooling water losses was statistically significant.

Impact of weather conditions and building design on contaminant infiltration from crawl spaces in Swedish schools\u2014Numerical modeling using Monte Carlo method

Some Swedish school buildings built in the 1960s and 1970s experience indoor air quality problems, where the contaminants are suspected to come from the crawl space underneath the building. The poor indoor air quality causes discomfort among pupils and teachers. Installing an exhaust fan to maintain a negative pressure difference in the crawl space relative to indoors or increasing the ventilation in the classroom are two examples of common measures taken to improve the indoor air quality. However, these measures are not always effective, and sometimes the school building has to be demolished. The relation between pressure distribution, contaminant concentration in the classroom, outdoor temperature, wind, mechanical ventilation, and air leakage distribution is complex. A better understanding of these relations is crucial for making decisions on the most efficient measure to improve the indoor air quality. In this paper, a model for contaminant infiltration from the crawl space is used together with the Monte Carlo method to study these relations. Simulations are performed for several cases where different building shapes, building orientations, shielding conditions, and geographical locations are simulated. Results show, for example, that for a building with an imbalanced ventilation system, air is leaking from the crawl space to the classroom for the majority of cases and that concentration levels in the classroom are usually the highest during mild and calm days.

Impact of weather conditions on cheetah monitoring with scat detection dogs

AbstractKnowledge on cheetah population densities across their current range is limited. Therefore, new and efficient assessment tools are needed to gain more knowledge on species distribution, ecology and behaviour. Scat detection dogs have emerged as an efficient and non-invasive method to monitor elusive and vulnerable animal species, like cheetahs, due to the dog’s superior olfactory system. However, the success of locating scat using detection dogs can be significantly improved under suitable weather conditions. We examined the impact of temperature, humidity and wind speed on detection rates of scat from cheetahs during a scat detection dog survey in Northern Kenya. We found that average wind speed positively influences the scat detection rate of detection dogs working on leash. Humidity showed no significant influence. Temperature showed a strong negative correlation with humidity and thus was excluded from our model analyses. While it is likely that wind speed is especially invalid for dogs working off leash, this study did not demonstrate this. Wind speed could thus influence the success of monitoring cheetahs or other target species. Our findings help to improve the survey and thus maximise the coverage of study area and the collection of target samples of elusive and rare species.

Wideband Gain Enhancement of a Dual-Polarized MIMO Vehicular Antenna

A compact dual-polarized multiple-input-multiple- output (MIMO) Vivaldi antenna with a wide bandwidth, high gain, and high isolation is proposed for wireless communications in intelligent Internet of Vehicles (IoV). It consists of four identical orthogonally-crossed Vivaldi radiators, crossed-fishbone-shaped slot, metasurface lens, parasitic stubs, electromagnetic (EM) wave reflector, and three-dimensional (3D) printed radome with dielectric resonator (DR) array. These functional modules jointly contribute to optimized antenna performance. Four identical antenna elements are rotationally symmetrical. To reduce the inter-element mutual coupling, the crossed-fishbone-shaped slot is etched to reduce the surface current flowing in adjacent radiators. To raise the gain, the metasurface lens, parasitic stubs, and DR array are loaded to guide the EM wave in the frontward radiation. An EM wave reflector located underneath the Vivaldi radiators could increase the boresight gain and reduce the influence of the vehicle body on the antenna performance. Diversity performance analysis indicates the proposed antenna could offer better MIMO capability. Besides, the impact of weather conditions on the antenna is analyzed. As a proof of concept, an expanded 8-element antenna array prototype is designed, fabricated, and tested. A good agreement is observed between measured and simulated results. It achieves an -10-dB impedance bandwidth of 7.55-22.85 GHz (100.66% FBW) with port isolation of higher than 18.05 dB. The realized gain is 6.98-11.54 dBi, and the radiation efficiency is 85.05-90.27%. The proposed antenna could be used in wireless communications between vehicles and the satellite/infrastructure.

Impact of weather conditions, seasonality and moonlight on the use of artificial canopy bridges by nocturnal arboreal mammals

Natural and artificial canopy bridges can be used to mitigate the effects of habitat fragmentation. Understanding the ecological factors that influence bridge use is imperative to the effective design and placement of this potential conservation intervention. Moonlight, seasonality and weather may influence the cost and risk of using bridges, potentially reducing their effectiveness. We installed five artificial waterline bridges and, between 2017 and 2019, monitored via camera trapping their use by Javan palm civets Paradoxurus musanga javanicus and Javan slow lorises Nycticebus javanicus. We used a weather station to record microclimate data (temperature and relative humidity) and calculated the illumination percentage of the moon. We tested the influence of moon luminosity, relative humidity, seasonality (Julian day) and temperature on the frequency of bridge use via Generalised Additive Models. Camera traps captured 938 instances of bridge use by civets, which was significantly lower than the reference value at moon luminosity > 90%, temperatures > 20 °C, humidity > 90%, and during the drier period (May–July). Camera traps captured 1036 instances of bridge use by lorises, which was significantly lower than the reference value during the drier period and higher than the reference value at temperatures > 20 °C. Lorises showed peaks in bridge use close to sunset and sunrise whereas civets showed peaks around 2 h after sunset and 2 h before sunrise. Our study illustrates the utility of simple-to-construct bridges by two sympatric nocturnal mammals facing severe habitat loss, with bridge use differing between those species according to abiotic factors. In particular, less use by both taxa during the drier season could suggest modifying placement of bridges or providing another intervention during that time. Camera traps were an excellent mechanism to record these differences and to validate the importance of the bridges, including during inclement weather and dark nights, when observations would be more difficult for human observers. By understanding the influence that abiotic factors have on the use of artificial bridges, we can improve bridge placement and construction to encourage use by a variety of species, particularly those threatened by habitat fragmentation.

Berth allocation problem with uncertain vessel handling times considering weather conditions

The vessel handling times at container terminals can be inevitably affected by weather conditions. This study proposes a berth allocation problem (BAP) with vessel handling time uncertainty considering the impact of weather conditions, which is seldom considered in the previous studies on BAPs. A two-stage optimization method, which focuses on the evaluation of vessel handling time under different weather conditions, is developed for addressing our BAP. In stage I, we determine the vessel handling times considering the influence of weather conditions. Based on the vessel handling times obtained in stage I, stage II presents a mixed-integer programming (MIP) model for solving the BAP. Moreover, an efficient particle swarm optimization algorithm embedded with machine learning approach is devised for solving the BAP model in large-scale problem cases. Numerical experiments are carried out to assess the effectiveness of the proposed model and the efficiency of the proposed algorithm.

Impact of weather conditions and sowing method on seed performance of meadow clover in the Middle Urals

Seed production of perennial leguminous herbs, including meadow clover (Trifolium praténse), is complicated due to the natural and climatic conditions of the region. In Middle Urals, only two to three years out of ten are favorable for seed production. Estimation of influence of the hydrothermal regime of the growing season and the sowing method has been carried out in the experimental crop rotation of the Udmurt Research Institute of Agriculture, UdmFRC Ural Branch of the RAS with the seed grass stand of meadow diploid clover varieties Pelican and Trio, tetraploid variety Kudesnik It has been revealed that seed productivity of meadow clover on sod-podzolic medium loamy soil was more dependent on the prevailing hydrothermal regimes of vegetation periods, as well as on the variety’s ploidy. A relatively high seeds yield of the Pelican variety (2n) 444-593 kg/ha and Kudesnik variety (4n) 101-116 kg/ha was formed under conditions of insufficient and optimal moisture supply of the vegetation period with a hydrothermal coefficient of 0.67-1.41. With increase in hydrothermal coefficient p to 1.56-1.69, the seeds yield of the Trio variety (2n) decreased to 251-328 kg/ha, of the Kudesnik variety (4n) - to 77-91 kg/ha. Under the same conditions, according to the hydrothermal regime of vegetation, the Kudesnik clover variety formed a relatively larger number of stems and heads, however, the heads productivity was significantly inferior to diploid varieties, which ultimately affected its seed productivity. Sowing diploid varieties of meadow clover Pelican and Trio in the usual ordinary way (15 cm), tetraploid variety Kudesnik in a wide-row way (30 cm) allowed increasing seeds yield and thereby neutralizing the negative impact of weather factors. Sstudy of the seed formation features of meadow clover varieties differing in ploidy in contrasting agrometeorological conditions may be of interest in developing methods for optimizing their seed productivity.

Active learning strategy for high fidelity short-term data-driven building energy forecasting

The quality of a data-driven model is heavily dependent on the quality of data. Data from building operation often have data bias problems, which means that the data sample is collected in a way that some members of the intended data population are less likely to be included than others. Data-driven energy forecasting models built on such data hence are biased and could lead to large forecasting errors. Active learning— an effective method to defying data bias—is rarely studied or applied in the area of data-driven building energy forecasting modeling. This paper attempts to fill this gap and explores the application of active learning in data-driven building energy forecasting.The developed strategy in this paper efficiently generate informative training data within a time budget and uses block design to passively consider weather disturbances. The developed active learning strategy is applied and evaluated in both virtual and real-building testbeds against traditional data-driven methods. Via these virtual and real-building evaluation cases, we have demonstrated that the data bias problem typically exists in building operation data is resolved by applying the developed active learning strategy. Building energy forecasting models trained from data generated from the active learning strategy have shown improved performances in both model accuracy and model extendibility perspectives. The effectiveness of the block design module is also validated to effectively consider the impact of weather conditions on active learning design.

Impact of Weather Conditions on Airport Arrival Delay and Throughput

Weather events have a significant impact on airport arrival performance and may cause delays in operations and/or constraints in airport capacity. In Europe, almost half of all regulated airport traffic delay is due to adverse weather conditions. Moreover, the closer airports operate to their maximum capacity, the more severe is the impact of a capacity loss due to external events such as weather. Various weather uncertainties occurring during airport operations can significantly delay some arrival processes and cause network-wide effects on the overall Air Traffic Management (ATM) system. Quantifying the impact of weather is, therefore, a key feature to improve the decision-making process that enhances airport performance. It would allow airport operators to identify the relevant weather information needed, and help them decide on the appropriate actions to mitigate the consequences of adverse weather events. We present a methodology to evaluate the impact of adverse weather events on airport arrival performance (delay and throughput) and to define operational thresholds for significant weather conditions. Our results are computed from a dataset of over 750,000 flights on a major European hub and from local weather data during the period 2015-2018. We combine delay and capacity metrics at different airport operational stages for the arrival process (final approach, taxi-in and in-block). We introduce a new approach for modelling causal relationships between airport arrival performance indicators and meteorological events, which can be used to quantify the impact of weather in airport arrival conditions, predict the evolution of airport operational scenarios and support airport decision-making processes.

Selection of high-yielding varieties and hybrids of pan patty squash, determining their most favorable planting dates

In this article, the results of research on the cultivation of patty pan squash in the climatic conditions of Uzbekistan, Planting for different periods and its growth, development, yield, as well as the impact of weather conditions were presented. Squash is a one-year plant of the family of zucchini, mainly shrub, rarely found in the form of a whip. The results showed that average yield of “White-13” control was 16 tons/ha, and it was 17 tons/ha in “Solnyshko”. Furthermore, “NLO White” and “Umberall” had a high yield compared to the other varieties and hybrids, accounted for 15 tons/ha and 15.1 tons/ha, respectively. The highest average temperature during seed germination was found in 16 august, which was 30.3°C, whereas the lowest average temperature was 18.6°C in 1st April. The results showed that 4 days were required to reach 10% of seed germination in the period April 16 and May 1, however, 10% of seed germination in July 1 and 16th took 6 days. Furthermore, the least days for 75% of seed, germination was observed in the period of May 1, accounted for 8 days, and the rest of the period was the same.

Debris flows in Kresna Gorge (Bulgaria)-geomorphological characteristics and weather conditions

Over the last decades, numerous extreme climate events such as extreme temperatures, droughts, heavy precipitation, and storms associated with climate change have been recorded in many countries, including Bulgaria. As a result, geomorphological hazards such as landslides, debris flows, mudflows, high-speed soil erosion, etc. often occur on the territory of the country. The debris flow is one of the most common hazardous processes in small catchments of the main river basins in Bulgaria. The Kresna Gorge located in the middle part of Struma River valley is a typical area with such processes which often cause the damages to the E79 international highway. The purpose of the present study is to characterize debris flows in Kresna Gorge (southwestern part of Bulgaria) by comparative analysis between the two events (occurred on May 24, 2009 and July 28, 2019). In order to achieve the aim of the study the geomorphological features and flow type of 2019 event were identified and the results were compared with the previous publications which investigated the event on May 24, 2009. In the present paper, the sediments and the type of transportation of the investigated event (July 2019) were determined by grain-size and clast-shape analysis. The impact of weather conditions on debris flow occurrence was shown by the analysis of the synoptic conditions on the day before the event. The results of the study bring to clarifying the geological-geomorphological and meteorological factors for the occurrence of debris flow and are important for geomorphological hazard management.

Inkjet Printing of PEDOT:PSS Based Conductive Patterns for 3D Forming Applications.

This paper presents the formulation, inkjet printing, and vacuum forming of a conductive and stretchable polymer, poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), ink on a stretchable and transparent thermoplastic polyurethane (TPU) substrate. The formulation of the conductive and stretchable ink is achieved by combining PEDOT:PSS with additional solvents, to achieve the right inkjet properties for drop-on-demand (DoD) inkjet printing. A conductive pattern can be printed from the 21 µm orifice on a flexible and stretchable TPU substrate, with a linewidth down to 44 µm. The properties of the printed pattern, in terms of sheet resistance, morphology, transparency, impact of weather conditions, and stretching are investigated and show sheet resistances up to 45 Ohm/sq and transparencies as high as 95%, which is comparable to indium tin oxide (ITO). Moreover, in contrast to ITO, one-time stretching up to 40% can be achieved, increasing the sheet resistance up to 214 Ohm/sq only, showing the great potential of this ink for one-time stretching. Finally, as a proof of this one-time stretching, the printed samples are vacuum formed around a 3D object, still showing sufficient conductivity to be applied as a capacitive touch sensor.

Impact of weather conditions and global warming on COVID-19 outbreak

Impact of weather conditions and global warming on COVID-19 outbreak

The impact of weather conditions on hazel pollen concentration in Sosnowiec (Poland) in 1997\u20132019

The goal of this study was to compare hazel pollen seasons in Sosnowiec in 1997–2019 and to analyse the impact of weather conditions on these seasons. The measurements were conducted using a volumetric method with a Burkard spore trap. The duration of pollen seasons was determined using the 98% method. SPI (Seasonal Pollen Index) was calculated as the sum of daily pollen concentrations in a given season. The measurements showed that high temperatures in January and February had an impact on the beginning of the hazel pollen season. They revealed that there are positive correlations with temperatures and sunshine hours long before the season, i.e. 210–180 days before. The daily hazel pollen concentration in Sosnowiec showed a positive and statistically significant correlation with air temperature, sunshine hours, and average and maximum wind speed. Negative correlation was demonstrated for snow cover depth and relative humidity of the air. Daily concentration levels depend also on the type of weather front as well as direction of air mass flow and its type. Variance analysis showed that the highest concentrations of hazel pollen grains were recorded when warm air moves from the south and south–western direction, whereas the lowest ones were noted for air moving from the east, south–east, north and north–east directions. Atmospheric precipitation, snow cover depth, and average, maximum, minimum and near-the-ground temperatures in the season also had an impact on the SPI of hazel pollen grains. High positive correlation coefficients were also observed in the case of thermal conditions, sunshine hours, relative humidity and precipitation from July to September in the year preceding a given pollen season. The duration of the hazel pollen season depends on precipitation, snow cover depth and temperature during a given season.

Impact of Weather Conditions on Travel Demand – The Most Common Research Methods and Applied Models

This paper presents an overview of the applied research methodologies and developed travel demand models that take weather impact into account. The paper deals with trip generation and modal split as elements of travel demand that best describe changes in the travel behaviour in different weather conditions. The authors herein emphasize the importance of research in local conditions in all climate zones, especially in areas where climate and modal split characteristics are different from those in common research areas. This review is designed as a brief guide on how the impact of weather can be explored in order to encourage conducting research even in the countries where there is no systematic traffic and travel data collection. The stated adaptation technique followed by the panel household travel surveys may be particularly appropriate for those countries. It is concluded that small budgets should not be considered an obstacle, because it is possible to draw reliable conclusions based even on small samples. Moreover, modern research methods enable a cheaper survey process together with the possibility of obtaining higher quality of results. The increasing popularity of research in this field should contribute to the creation of more resilient transport systems all over the world. A special contribution of this paper is the review of research studies carried out in central, western and southern Europe and not mentioned in any review paper before.

The Global Emergency of Novel Coronavirus (SARS-CoV-2): An Update of the Current Status and Forecasting.

Over the past two decades, there have been two major outbreaks where the crossover of animal Betacoronaviruses to humans has resulted in severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). In December 2019, a global public health concern started with the emergence of a new strain of coronavirus (SARS-CoV-2 or 2019 novel coronavirus, 2019-nCoV) which has rapidly spread all over the world from its origin in Wuhan, China. SARS-CoV-2 belongs to the Betacoronavirus genus, which includes human SARS-CoV, MERS and two other human coronaviruses (HCoVs), HCoV-OC43 and HCoV-HKU1. The fatality rate of SARS-CoV-2 is lower than the two previous coronavirus epidemics, but it is faster spreading and the large number of infected people with severe viral pneumonia and respiratory illness, showed SARS-CoV-2 to be highly contagious. Based on the current published evidence, herein we summarize the origin, genetics, epidemiology, clinical manifestations, preventions, diagnosis and up to date treatments of SARS-CoV-2 infections in comparison with those caused by SARS-CoV and MERS-CoV. Moreover, the possible impact of weather conditions on the transmission of SARS-CoV-2 is also discussed. Therefore, the aim of the present review is to reconsider the two previous pandemics and provide a reference for future studies as well as therapeutic approaches.

Correlation of the ambient dose equivalent rate and meteorological parameters

In this paper, the results of ambient dose equivalent rate measurements at different locations are presented. At every location measurements were performed twice a day, in the morning and afternoon. One of the aim of this study was to determine the impact of weather conditions on the ambient dose equivalent rate. Correlation between ambient dose equivalent rate values and the meteorological parameters such as temperature, pressure and relative humidity are analyzed. A moderate positive correlation was found between the ambient dose rate and pressure in the morning measurements. The average annual effective dose is calculated to be 0.105 mSv.