Impact Of Adverse Weather Conditions Research Articles

Effect of solar radiation and full spectrum artificial sun light drying on the drying characteristics, ultra-structural and textural properties of white radish (Raphanus sativus L.)

Traditional sun drying has long been employed as a method for preserving radishes (Raphanus sativus L.) However, it suffers from various uncertainties, including weather-related factors such as rain and cloudy days, the pressing issue of climatic change can lead to an impact on the traditional drying process and texture of radish. In this research, the full spectrum artificial sunlight drying (FSASLD) has been implemented to simulate the traditional open sun drying of white radish slices which helps to prevent hygienic issues and unstable climatic conditions. Water activity (Aw) was measured and observed to decrease from 0.89 to 0.60 under both drying methods, indicating the removal of moisture from radish cells. Mathematical modelling and color kinetics models were studied with respect to drying time. Texture Profile Analysis (TPA) was employed to assess hardness, and results showed an increase in hardness following both SD (1018.24 g to 1327.67 g) and FSASLD (1018.24 g to 1731.04 g) salt treated radish slices. These findings suggest that FSASLD can serve as a viable alternative to the conventional drying method and contributes to agricultural innovation and the food industry, reducing drying time significantly from 270 min to 200 min and minimizing the impact of adverse weather conditions and interference from animals and microorganisms.

Effectiveness of Foliar Top Dressing of Flax with the Drug Controlit-Si on Different Backgrounds of Mineral Nutrition in the Conditions of the Central Non-Chernozem

The responsiveness of flax to mineral fertilizers and foliar top dressing with an aqueous solution of the drug Controlfit-Si on sod-podzolic medium loamy soil was studied. It is shown that the reaction of flax to mineral fertilizers depended on the hydrothermal environmental conditions, doses and the ratio of nutrients. Excessive humidity and arid conditions negatively affected the productivity of crops. Foliar top dressing of plants with the drug Controlfit-Si leveled the negative impact of adverse weather conditions, increased the responsiveness of plants to mineral fertilizers, contributed to a more complete use of nutrients from fertilizers. On average, for 3 years on the backgrounds of full mineral fertilizer, top dressing increased the yield of flax straw by 25–30% with the best effect against the background of N48P48K48 (4.03 t/ha). Top dressing did not have a positive effect on the yield of flax seeds. It took 13.8 kg N, 5.9 kg P2O5 and 10.7 kg K2O to form 1 ton of flax crop with the appropriate amount of seeds, regardless of plant nutrition conditions.

Meteorological causes of air accidents

This paper is devoted to analysis and statistical summarization of data on air accidents, incidents, and serious incidents, where meteorological factors contributed to their development or directly caused the specific aviation event. The aim of this paper is to raise awareness about current issues related to the impact of adverse weather conditions and specific factors on aviation, despite the continuous development of technological and informational aspects. There were applied final reports from official internet sources, namely the Air Accidents Investigation Institute of the Czech Republic and the Ministry of Transport of the Slovak Republic, especially the Aviation and Maritime Investigation Authority. Those official reports were used for the implementation of statistical processing and detailed analysis of aviation accidents in the territory of the Czech and Slovak Republic.

Evaluating the Operational Efficiency of a Combined Tillage Cultivator

Introduction. At present, the use of combined machines and aggregates makes it possible to significantly reduce the time for tillage, while ensuring the required quality. Combining operations in these machines also reduces the impact of adverse weather conditions on the performance of technological processes. The use of combined machines makes it possible to fully load large tractors, especially on the land plot of a small area, where working with wide web units is difficult. The combination of technological operations is most advantageous for intensive farming in fields free of weeds. Therefore, the development of technologies and means of mechanization, which allow preparing soil with high quality and the least energy and material costs, is an important task. The purpose of the study is to evaluate the efficiency of a combined cultivator for surface tillage and improve the quality of its work. Materials and Methods. Based on numerous studies and requirements for tillage machines with elastic struts, a combined cultivator for surface tillage has been developed. To assess the efficiency and study the cultivator performance, a multifactorial experiment of the first order was conducted. Traction resistance of the cultivator section and soil crumbling (fraction size from 0 to 25 mm) were taken as optimization parameters. Results. The use of an experimental cultivator, in comparison with serial ones, allows reducing the tractive resistance by 10–15%, and improving the quality of soil crumbling by 5–6%. Discussion and Conclusion. The conducted experimental studies have proved the developed combined cultivator to be effective. The use of this cultivator leads to a reduction in energy consumption and improvement of the quality of tillage.

Photonic Sensor for Multiple Targets Detection under Adverse Weather Conditions in Autonomous Vehicles

Detection and tracing of multiple targets in a real-time scenario, particularly in the urban setup under adverse atmospheric conditions, has become a major challenge for autonomous vehicles (AVs). Photonic radars have emerged as promising candidates for Avs to realize via the recognition of traffic patterns, navigation, lane detection, self-parking, etc. In this work we developed a direct detection-based, frequency-modulated photonic radar to detect multiple stationary targets using four different transmission channels multiplexed over a single free space channel via wavelength division multiplexing (WDM). Additionally, the performance of the proposed photonic radar was examined under the impact of adverse weather conditions, such as rain and fog. The reported results in terms of received power and signal-to-noise ratio (SNR) showed successful detection of all the targets with bandwidths of 1 GHz and 4 GHz. The proposed system was also tested for range resolution of targets at 150 m and 6.75 cm resolution with 4 GHz bandwidth was reported, while resolution of 50 cm was reported with 1 GHz of bandwidth.

Assessing the Impact of Meteorological Conditions on Outpatient Visits for Childhood Respiratory Diseases in Urumqi, China.

The aims of this study were to explore the impact of meteorological factors on respiratory diseases in children and to provide recommendations to local governments and health agencies to prevent respiratory diseases. The exposure-lag effect between meteorological factors and the number of outpatients was investigated by constructing a distributed lag nonlinear model. Both high and low temperature will increase the risk of respiratory diseases in children, but low temperatures have a stronger effect compared with high temperatures (except for bronchopneumonia). High and low wind speeds can adversely affect respiratory diseases in children. Temperature and wind speed have an effect on children's respiratory diseases in Urumqi, and this effect has a time lag. Attention should be paid to the impact of adverse weather conditions on children's health.

Modeling the Impact of Weather Conditions on Pedestrian Injury Counts Using LASSO-Based Poisson Model

Statistical models for measuring the impact of adverse weather conditions on pedestrian injuries are of great importance for enhancing road safety measures. The development of these models in the presence of high collinearity among the weather conditions poses a real challenge in practice. The collinearity among these conditions may result in underestimation of the regression coefficients of the regression model, and hence inconsistency regarding the impact of the weather conditions on the pedestrian injuries counts. This paper presents a methodology through which the penalization-based regression is applied to model the impact of weather conditions on pedestrian injury in the presence of a high level of collinearity among these conditions. More specifically, the methodology integrates both the least absolute shrinkage squared operator (Lasso) with the cross-validation approach. The statistical performance of the proposed methodology is assessed through an analytical comparison involving the standard Poisson regression, Poisson generalized linear model (Poisson-GzLM), and Ridge penalized regression model. The mean squared error (MSE) was used as a criterion of comparison. In terms of the MSE, the Lasso-based Poisson generalized linear model (Lasso-GzLM) revealed an advantage over the other regression models. Moreover, the study revealed that weather conditions involved in this study are of insignificant impact on pedestrian injury counts.

Enhanced Performance Analysis of 10 Gbit/s–10 GHz OFDM-Based Radio over FSO Transmission System Incorporating ODSB and OSSB Modulation Schemes

Abstract The exponential rise in the demand for channel bandwidth over the last few years has lead to the problem of spectrum congestion in conventional radio frequency (RF)-based wireless communication systems. Radio over free space optics (RoFSO) provides an effective solution to tackle the problem of spectrum congestion due to its many merits including license-free bandwidth, quick and low-cost installation, cost-effectiveness, and highly secure transmission links. The high-speed data transmission capabilities and immunity to electromagnetic and RF interference makes it a suitable candidate for the development of future 5 G networks. This work focuses on the designing and performance analysis of 10 Gbit/s–10 GHz orthogonal frequency division multiplexing (OFDM) based RoFSO link under the impact of different environmental effects. Also, the performance of the proposed RoFSO link has been compared for different modulation schemes viz. optical dual sideband (ODSB) and optical single sideband (OSSB). Further, we propose an enhanced detection technique deploying Square root module (SRm) at the receiver terminal for link reach enhancement under the impact of adverse weather conditions.

The Impact of Adverse Weather Conditions on Autonomous Vehicles: How Rain, Snow, Fog, and Hail Affect the Performance of a Self-Driving Car

Recently, the development of autonomous vehicles and intelligent driver assistance systems has drawn a significant amount of attention from the general public. One of the most critical issues in the development of autonomous vehicles and driver assistance systems is their poor performance under adverse weather conditions, such as rain, snow, fog, and hail. However, no current study provides a systematic and unified review of the effect that weather has on the various types of sensors used in autonomous vehicles. In this article, we first present a literature review about the impact of adverse weather conditions on state-ofthe-art sensors, such as lidar, GPS, camera, and radar. Then, we characterize the effect of rainfall on millimeter-wave (mmwave) radar, which considers both the rain attenuation and the backscatter effects. Our simulation results show that the detection range of mm-wave radar can be reduced by up to 45% under severe rainfall conditions. Moreover, the rain backscatter effect is significantly different for targets with different radar cross-section (RCS) areas.

INFLUENCE OF FOLIAR FERTILIZATION OF WINTER WHEAT WITH WATER SOLUBLE COMPOUND FERTILIZER WITH MICROELEMENTS "POLY-FEED" FOR YIELD AND QUALITY GRAIN IN THE CONDITIONS OF THE ORYOL REGION

Often in the soils of crop rotations of grain crops, including on black soil, the content of mobile forms of copper, manganese, zinc and other trace elements is low. Improving the efficiency of making micronutrients for grain crops and determining the best ways and doses of their introduction are topical issues that need to be addressed in order to increase the productivity of crops. The purpose of research is to identify the effectiveness of the use of water soluble compound fertilizer with microelements of the company “Haifa Chemicals” in the technology of growing winter wheat on leached chernozem under conditions of the Oryol Region. Field production experiments were established in 2017-2018 on the basis of Orlovsky Leader LLC Branch №5” located in Livensky district. Field experience with the use of Haifa Chemicals products: Poly-Feed micronutrients 19-19-19 + 1MgO + ME and Poly-Feed 6-15-38 + 3 + ME was laid on soft winter wheat varieties Moskovskaya-56.The control variant was the basic technological scheme used in the household for carrying out leaf dressings with mineral fertilizers together with the organic fertilizer Gumostim. As a result of the research, it has been established that the use of double foliar feeding water soluble compound fertilizer with microelements Poly-Feed 19-19-19 + 1MgO + ME in the tillering stage and at the end of flowering and a single Poly-Feed 6-15-38 + 3 + IU in the subflag phase - flag leaf, increases the height of the plants, as well as the productive characteristics of the ear: the size of the ear, the number of grains in the ear, the mass of grains and their best quality, which in general provides a reliable increase in the yield of grain of winter wheat. At the same time, it was found that, due to leaf feeding, the impact of adverse weather conditions under which the development of winter wheat plants took place in 2018 and their productive properties were laid was leveled out. Due to relatively low additional costs, the use of complex fertilizers of the Poly-Feed brand for winter wheat is economically feasible and can bring additional economic income: based on the maximum level of minimum prices for the grain of the 2018 harvest, it will be 2.07-2.28 thousand rubles / ha regarding base technology. Thus, water-soluble fertilizers, which include Poly-Feed company "Haifa Chemicals" are recommended to domestic agricultural producers for mass introduction in practice of the technology of intensive sheet nutrition of grain and other crops.

Parametric Ordinal Logistic Regression and Non-Parametric Decision Tree Approaches for Assessing the Impact of Weather Conditions on Driver Speed Selection Using Naturalistic Driving Data

The impact of adverse weather conditions on transportation operation and safety is the focus of many studies; however, comprehensive research detailing the differences in driving behavior and performance during adverse conditions is limited. Many previous studies utilized aggregate traffic and weather data (e.g., average speed, headway, and global weather information) to formulate conclusions about the impact of weather on network operation and safety; however, research into specific factors associated with driver performance and behavior are notably absent. A novel approach, presented in this paper, fills this gap by considering disaggregate trajectory-level data available through the SHRP2 Naturalistic Driving Study and Roadway Information Database. Parametric ordinal logistic regression and non-parametric classification tree modeling were utilized to better understand speed selection behavior in adverse weather conditions. The results indicate that the most important factors impacting driver speed selection are weather conditions, traffic conditions, and the posted speed limit. Moreover, it was found that drivers are more likely to significantly reduce their speed in snowy weather conditions, as compared with other adverse weather conditions (such as rain and fog). The purpose of this study was to gather insights into driver speed preferences in different weather conditions, such that efficient logic can be introduced for a realistic variable speed limit system—aimed at maximizing speed compliance and reducing speed variations. This study provides valuable information related to drivers’ interaction with real-time changes in roadway and weather conditions, leading to a better understanding of the effectiveness of operational countermeasures.

Quantifying the impact of adverse weather conditions on road network performance

Adverse weather conditions regularly lead to severe congestion and large travel time delays on road networks all over the world. Different climate scenarios indicate that in the future adverse weather conditions are likely to become more frequent, last longer and will be more extreme. Although climate mitigation measures are being taken, it remains important to investigate how adverse weather events will affect the performance of the road network in the future. The main objective of this paper is to give an overview of how the impact of adverse weather conditions and adaptation measures on road network performance can be quantified. A literature review has been performed to show what is empirically known about the impact of adverse weather conditions on the road network performance. Furthermore, available methods to quantify the impact of adverse weather conditions and adaptation measures on the road network performance for future situations are reviewed. As an example, a case study for the municipality of Rotterdam has been carried out that shows how a combination of models can be used to analyse which links in the road network are most vulnerable for increasingly severe local weather related disturbances. The results of the case study allow local authorities to decide whether or not they need to take adaptation measures.

Zimbabwe: Staff Report for the 2016 Article IV Consultation and the Third Review of the Staff-Monitored Program-Press Release; Staff Report; and Statement by the Executive Director for Zimbabwe

This paper discusses recent developments, outlook, and risks related to the economy of Zimbabwe. Zimbabwe’s economic difficulties have deepened. GDP growth slowed significantly to 1.1 percent in 2015, mainly because of the impact of adverse weather conditions on agricultural output, and power generation. The current account balance improved in 2015, because of lower prices for oil imports, subdued economic activity, and fiscal consolidation efforts. Fiscal performance in 2015 was better than programmed, despite the adverse macroeconomic environment. Despite spending pressures to mitigate the impact of the drought, the authorities remain committed to fiscal discipline; they target a primary cash deficit of 0.2 percent of GDP for 2016.

Can Agrometeorological Indices of Adverse Weather Conditions Help to Improve Yield Prediction by Crop Models?

The impact of adverse weather conditions (AWCs) on crop production is random in both time and space and depends on factors such as severity, previous agrometeorological conditions, and plant vulnerability at a specific crop development stage. Any exclusion or improper treatment of any of these factors can cause crop models to produce significant under- or overestimates of yield. The analysis presented in this paper focuses on a range of agrometeorological indices (AMI) related to AWCs that might affect real yield as well as simulated yield. For this purpose, the analysis addressed four indicators of extreme temperatures and three indicators of dry conditions during the growth period of maize and winter wheat in Austria, Croatia, Serbia, Slovakia, and Sweden. It is shown that increases in the number and intensity of AWCs cannot be unambiguously associated with increased deviations in simulated yields. The identified correlations indicate an increase in modeling uncertainty. This finding represents important information for the crop modeling community. Additionally, it opens a window of opportunity for a statistical (“event scenario”) approach based on correlations between agrometeorological indices of AWCs and crop yield data series. This approach can provide scenarios for certain locations, crop types, and AWC patterns and, therefore, improve yield forecasting in the presence of AWCs.

The impact of precipitation on land interfacility transport times.

Timely transfer of patients among facilities within a regionalized critical-care system remains a large obstacle to effective patient care. For medical transport systems where dispatchers are responsible for planning these interfacility transfers, accurate estimates of interfacility transfer times play a large role in planning and resource-allocation decisions. However, the impact of adverse weather conditions on transfer times is not well understood. Precipitation negatively impacts driving conditions and can decrease free-flow speeds and increase travel times. The objective of this research was to quantify and model the effects of different precipitation types on land travel times for interfacility patient transfers. It was hypothesized that the effects of precipitation would accumulate as the distance of the transfer increased, and they would differ based on the type of precipitation. Urgent and emergent interfacility transfers carried out by the medical transport system in Ontario from 2005 through 2011 were linked to Environment Canada's (Gatineau, Quebec, Canada) climate data. Two linear models were built to estimate travel times based on precipitation type and driving distance: one for transfers between cities (intercity) and another for transfers within a city (intracity). Precipitation affected both transfer types. For intercity transfers, the magnitude of the delays increased as driving distance increased. For median-distance intercity transfers (48 km), snow produced delays of approximately 9.1% (3.1 minutes), while rain produced delays of 8.4% (2.9 minutes). For intracity transfers, the magnitude of delays attributed to precipitation did not depend on distance driven. Transfers in rain were 8.6% longer (1.7 minutes) compared to no precipitation, whereas only statistically marginal effects were observed for snow. Precipitation increases the duration of interfacility land ambulance travel times by eight percent to ten percent. For transfers between cities, snow is associated with the longest delays (versus rain), but for transfers within a single city, rain is associated with the longest delays.

The impact of precipitation on speed–flow relationships along a UK motorway corridor

Although the fundamental traffic diagram provides the characteristics of a typical road traffic speed–flow relationship, little consideration has been given to the impact of adverse weather conditions on the relationship and the subsequent impact on local speed–flow. For the first time, this study uses precipitation radar along with a state-of-the art traffic information system to ascertain the relationship between speed–flow and precipitation on a UK transport corridor at the local (junction to junction) scale. It is evident that precipitation causes a significant reduction in speed and maximum flow on many links of the corridor as well as a downward reduction in the overall speed-flow relationship. With increased instances of heavy precipitation predicted in the UK as a result of climate change, these findings highlight the subsequent impact on journey travel times and associated economic costs.

Impact of Saturation Flow Changes on Performance of Traffic Lanes at Signalised Intersections

The paper presents analysis of saturation flow variability in traffic signal cycles during periods of congestion on the basis of empirical measurements. The purpose of this study was to investigate the impact of adverse weather conditions on the capacity of entry lanes. The empirical research was conducted in period 2007 – 2009 in three Polish cities. Investigated were lane groups with through traffic and geometrical characteristics corresponding to basic conditions in calculation methods and focused on detailed analyses of departure headways between vehicles, especially during the middle interval of the green signal of variable length, depending on drivers’ behaviour. It was shown that saturation flow in traffic signal cycles at individual intersections is a random variable which can be described by gamma or normal distribution. Measurements’ results show noticeable impact of different weather conditions on the saturation flow. The last part shows regression analyses which were conducted to accommodate numerous saturation flow determinants. The paper presents practical, aggregated models for prediction of basic saturation flow together with a proposed scale of efficiency of driver's behaviour, which is largely determined by traffic conditions. Simulation research enabled the authors to determine capacity variability and its impact on traffic performance (delay and vehicle queues). © 2011 Published by Elsevier Ltd.

Variation of Impact of Cold Temperature and Snowfall and Their Interaction on Traffic Volume

This paper presents a detailed investigation of highway traffic variations with severity of cold, the amount of snow, and various combinations of cold and snow intensities. Separate analyses for starting, middle, and ending months of winter seasons are conducted to study the variations in traffic-weather relationships within the winter season. The study is based on hourly traffic flow data from 350 permanent traffic counter sites located on the provincial highway system of Alberta, Canada, and weather data obtained from nearby Environment Canada weather stations, from 1995 to 2005. Multiple regression analysis is used in the modeling process. The model parameters include three sets of variables: the amount of snowfall as a quantitative variable, categorized cold as a dummy variable, and an interaction variable formed by the product of these two variables. The study results indicate that the association of highway traffic flow with cold and snow varies with day of week, hour of day, and severity of weather conditions. A reduction of 1% to 2% in traffic volume for each centimeter of snowfall is observed when the mean temperature is above 0°C. For the days with zero precipitation, reductions in traffic volume due to mild and severe cold are 1% and 31%, respectively. An additional reduction of 0.5% to 3% per centimeter of snowfall results when snowfall occurs during severe cold conditions. Study results show lesser impact of adverse weather conditions on traffic during severe winter months (mid-November to mid-March) and the months thereafter compared with early (starting) winter months.

The impact of adverse weather conditions on the propensity to change travel decisions: A survey of Brussels commuters

New developments in transportation systems and the increasing complexities of urban living are creating challenges and opportunities to comprehensively address transportation problems. The key to exploiting new opportunities lies in understanding how travelers would respond to changes in the transportation system. This study aims to understand traveler behavior under normal and unexpected travel conditions in real-life situations. The results of a comprehensive behavioral survey conducted in Brussels are reported. Commuters' mode, departure time and route selection decisions, and the factors that influence them, including travel conditions, personal and household characteristics, and situational constraints, are explored. The paper develops a deeper understanding of automobile commuters' response to adverse weather. Automobile commuters constitute more than 50% of the total sample ( N = 1218). They were asked about adverse weather impacts on their mode, route and departure time changes. Among those who changed their travel decisions in adverse weather (about 50%), more than one-quarter reported that adverse weather was either very important or important in changing their mode; and 60% changed their departure time due to adverse weather whereas 35% diverted to alternate routes. Furthermore, close to 75% kept themselves informed about weather through secondary information sources such as radio and television. To analyze relationships empirically, ordered probit models of mode and departure time were estimated. The models show that commuters change their travel patterns in systematic ways when adverse weather occurs. Finally, the implications of the survey results for dealing with adverse weather problems are discussed.

A Weather Index for Analysing Grain Yield Instability in China, 1952–81

This article applies standard regression techniques to examine the impact of adverse weather conditions on average grain yield per sown hectare in contemporary China. By isolating the weather impact I hope (a) to quantify the possible influence of frequent policy and organizational changes which have been so characteristic of Chinese agriculture since 1949; and (b) to show to what extent grain production in China has become more “weather-proof” after three decades of massive investment in water control and other modern inputs. I shall deal mainly with the long-term trends from 1952 to 1981, with special reference to the extraordinary 1959–61 period, during which total grain output and yield declined by an average of 21 and 12 per cent respectively (or 25 and 18 per cent for the two trough years of 1960 and 1961), measured against the benchmark year of 1957.