Effects Of Weather Research Articles

Vulnerability assessment of landslides along the Yunnan section of the Northern Tropic of Cancer based on fuzzy evidence weight model

AbstractFrequent geological disasters pose significant threats to both human lives and property. High-risk landslides, with features such as rapid occurrence, wide distribution, and strong destructiveness, are of particular concern. To investigate the distribution characteristics and threat range of landslides, the Yunnan section of the Northern Tropic of Cancer was selected as the study area. Based on the fuzzy evidence weight model and using a grid size of 1000 m × 1000 m as the study unit, a vulnerability assessment of landslides along the Northern Tropic of Cancer in Yunnan was conducted. This assessment involved constructing a set of 13 evaluation indicator factors from three aspects: geological environment, geographical environment, and human engineering activities. The assessment results were subsequently subjected to precision verification. The results are as follows: (1) The overall vulnerability of landslides in the Yunnan section of the Northern Tropic of Cancer is moderate, covering an area of 25,968.79 km2. This area constitutes the largest proportion, accounting for 46.30% of the entire study area and is primarily distributed in counties such as Yanshan, Funing, and Shuangjiang. The highly vulnerable area covers 15,942.27 km2, representing 28.43% of the total study area. This region is mainly distributed in counties such as Gejiu, Yuanjiang, and Mojiang. (2) The main triggering factors for landslides are twofold: first, large-scale slope instability caused by excavation in human engineering activities, leading to extensive unstable slopes affected by long-term weathering and gravitational effects. Second, soil erosion resulting from land cultivation leads to the collapse and sliding of weathered and fragmented rocks under the influence of heavy rainfall and water erosion. During routine geological disaster patrols, special attention should be given to these factors, with a focus on implementing engineering measures in areas with more fragile geological environments. (3) Precision verification of the assessment results was conducted using both receiver operating characteristic (ROC) curves and Success rate curves. The area under the curve (AUC) values for the success rate curve and ROC curve were 0.85 and 0.74, respectively. The verification results showed high accuracy and feasibility of the evaluation method.

Perspectives on total phosphorus response in rivers: Examining the influence of rainfall extremes and post-dry rainfall

Eutrophication is a significant environmental problem caused by nutrient loads from both point and non-point sources. Weather variables, particularly precipitation, affect the concentration of nutrients in water bodies, particularly those from non-point sources, in two contrasting ways. Heavy precipitation causes surface runoff which transports pollutants to rivers and increases nutrient concentration. Conversely, increased river flow can dilute the concentration, lowering it. This study investigates the impact of extreme precipitation, prolonged precipitation, and precipitation after a dry period on the total phosphorus concentration in the Moehne and Erft rivers in Germany, given the projected increase in frequency of extreme precipitation events and long drought periods due to climate change. The study comprises two parts: selecting extreme weather days from 2001 to 2021 and comparing observed Total Phosphorus concentrations with estimated concentrations derived from Generalized Additive Models and linear regression based on the discharge-concentration relationship. Changes in river TP concentration in response to continuous precipitation and precipitation after a dry period were also studied. Our results showed that during wet extreme and post-dry period rainfall events, TP concentration consistently surpassed expected values, underscoring the profound influence of intense rainfall on nutrient mobilization. However, we observed the impact of continuous rainfall to be non-unidirectional. Our work is distinguished by three key innovations: 1) addressing limitations in studying the effects of extreme weather on water quality due to limited temporal resolution, 2) incorporating both linear and non-linear modeling approaches for discharge-concentration relationships, and 3) performing a comprehensive analysis of temporal and spatial patterns of Total Phosphorus concentrations in response to varying rainfall patterns.

The effects of habitat, weather, and raptors on northern bobwhite abundance at multiple spatial scales

AbstractRangelands in the southwestern United States represent a current stronghold for northern bobwhite (Colinus virginianus); however, bobwhite populations in rangelands exhibit extreme inter‐annual variability in abundance in relation to fluctuating weather patterns. Recent declining bobwhite population trends within this region have led to the supposition that landscape‐scale processes, such as habitat loss and fragmentation and predation from increased raptor abundance, may be acting in conjunction with weather to reduce bobwhite populations. Our objective was to determine the relative effects of these factors on bobwhite populations in the rangeland environments of Texas and Oklahoma, USA. We obtained publicly available datasets for bobwhite counts (Breeding Bird Survey, state‐agency roadside counts), weather (PRISM), land cover (National Land Cover Database), and raptors (Christmas Bird Counts) for 3 5‐year periods (1990–1994, 1999–2003, 2009–2013). Data were collected at route and landscape scales based on routes within the Rio Grande Plains region of Texas and the Central Mixed Grass Prairie region of Texas and Oklahoma. We used generalized linear mixed models with a backward selection approach to determine top models for each dataset based on scale and ecoregion. Covariate relationships with bobwhite abundance followed expected patterns, with positive relationships with habitat, precipitation, and minimum temperatures and negative relationships with maximum temperatures and raptor abundance. Weather variables were the factors most consistently selected within both regions, while minimum winter temperature was overall the top variable. These relationships occurred within a landscape still containing relatively vast amounts of unfragmented bobwhite habitat (>60% rangeland; >15 million ha). Management within these regions should be focused on retaining habitat at a broad scale, while managing for suitable cover at a local scale to help mitigate weather effects.

A Systematic Review of Effects on ACL Injury of Soccer Shoe Outsoles, Soccer Playing Field Surfaces, and Outsole–Surface Interface

Soccer is a sport with a high incidence of injuries. The most common injury occurs when the anterior cruciate ligament of the knee has undergone a sprain, strain, or partial or total rupture. Besides fitness factors (e.g., proprioception, balance and strength capabilities), a principal cause of ACL injuries is sport shoes and playing surfaces. Especially with the emergence of artificial surfaces (rubbers, turfs, concrete, asphalt, red turf), the ACL injuries dramatically increase. The cost of ACL injuries is high both in terms of career termination and in social and economic costs. Thus, it is necessary to understand the impact of sport shoes and playing surfaces on the ACL and how it can be mitigated. The present literature review followed the PRISMA methodology to identify the major biomechanical factors influencing the behavior of surfaces and shoes in relation to the ACL damage. Fifty-eight papers were identified. After reviewing the mechanism of injuries, we identified several distinct factors: type of outsole and mechanical arrangement of the outsoles; shear forces; characteristics of artificial turf surfaces; effect of weather on artificial surface aging and change in mechanical characteristics; outsole/ground interface; and the frictional, tractional and rotational forces in the pathogenesis of ACL injuries in soccer.

Ecological and comparative analysis of the influence of the weather factor under the combined effect of heliomagnetic storms (HMS) on the vegetative balance of boys of different ages

Despite the extensive scientific data available on the impact of meteorological and heliogeophysical factors on the health and physiological parameters of the organism, the ecological role and biological nature of the mechanisms of their interaction remain unclear. The need to choose an integrated approach to the study of the Space–Earth–Human system is obvious and justified because it is based on the idea of using modern technologies and channels for obtaining and disseminating information about the impact of space weather, variability of the atmosphere, electromagnetic and gravitational fields, anthropogenic pollution and other environmental parameters that requires effective and rapid solution. It has been established that the body’s response to various stressful influences is largely determined by the ratio of the tone of the sympathetic and parasympathetic divisions of the autonomic nervous system. It is the autonomic nervous system (ANS) and, above all, its sympathetic division that plays a special role in the formation of adaptive reactions of the body, the development of meteorological reactions, i.e. the autonomic nervous system is the primary site of meteorological influences that cause shifts in its balance. Determination of vegetative status and direction of vegetative activity in boys’ organism was carried out by means of functional and vegetative diagnostics by V. Makats’ method. We examined 151 boys, including 49 boys aged 7–11 years and 102 — aged 12–15 years, FVD was carried out in the morning at 10.00–11.00. Since the state of the autonomic nervous system is decisive in the development of meteotropic reactions, the data of the study of vegetative tone in sunny and cloudy weather under the combined influence of heliomagnetic storms (HMS) were analysed, favourable and unfavourable weather conditions for the body were determined and the state of adaptive health of the examined children was determined. It was found that under the influence of heliometeorological factors on the organism of practically healthy young boys, agerelated peculiarities of meteorological variability are observed. The most sensitive to changes in weather and climatic conditions under the combined influence of HMS was the group of primary school age boys (PSA) aged 7–11 years, who showed maximum deviations in the activity of functional systems from the age norm, and the least sensitive was the group of boys aged 12–15 years. When analysing the influence of changes in weather conditions on the body of boys by the vegetative coefficient (kV), it was found that at the norm of kAv 0.95–1.05, it increased maximally when exposed to sunny weather and amounted to 1.12 in the revealed state of vegetative balance. In a healthy organism, changes in physiological processes and functional activity of systems under the influence of such a factor as changes in boys’ PSA, which indicates a pronounced sympathicotonia, and in boys’ ASA 0.93, respectively, which indicates a slight parasympathicotonia. The effects of cloudy weather on the body in both groups, even with the combined effect of HMB, are easily compensated for, and a special role in this belongs to the autonomic nervous system, whose activity ensures an adequate response of the body to the effects of environmental factors. Knowledge about meteosensitivity and meteorological reactions is necessary for the development of both preventive and therapeutic measures aimed at increasing nonspecific resistance and adaptation mechanisms of the body, normalising the function of organs and systems as a basis for normal reactions to adverse environmental changes. Environmental factors, including meteorological factors, are directly related to human life and health. Each of the meteorological elements has its own biological significance. This raises the question of the impact of solar activity, weather, atmospheric conditions, and, above all, anthropogenic pollution and other environmental parameters on human health, which naturally requires a quantitative approach to risk assessment and the development of necessary management decisions.

Campgrounds and climate change: An extreme weather event study for nature-based entrepreneurship

Entrepreneurship researchers have focused primarily on climate change mitigation. The physical effects of climate and weather on venture performance remain understudied. Accordingly, we introduce climatology to the entrepreneurship literature to quantitatively investigate the impacts of extreme weather events (i.e., tropical stormforced winds) on nature-based entrepreneurial performance. We operationalize our extreme weather event study at three coastal, entrepreneurial campgrounds that observed 12 tropical storm-forced events between 2007 and 2016. When controlling for institutional and other fixed effects, there were short-term but no long-term performance disruptions. Findings suggest adaptive and mitigative capacities are possible among nature-based entrepreneurial ventures experiencing extreme weather events. Thus, a key insight is the resilience of RV campgrounds to tropical-storm forced winds, the focal weather extreme.

Energetical effect of electrochromic glazing on the double-skin façade of the building in different climates

Today, energy has an essential role in the world’s future, and managing its consumption can be very influential and crucial in human life. Most of the energy consumption in any country is related to building. The aim of writing this article is to investigate the effect of combining electrochromic glazing and double skin facades. For this purpose, a double skin facade building with simple glass and a building in which electrochromic is used in the second layer of the facade were compared. These buildings were designed by Design Builder. The results demonstrated significant reductions in energy consumption in the second case. To study the effect of weather on the performance of this system, four cities in Iran with diverse climates have been selected. The energy consumption of cooling, heating, lighting, electricity, and gas utilization of the same building in different climates was studied. Using electrochromic glazing in the double-skin facade reduced the annual electrical consumption of the entire building by up to 3.5% for hot_humid weather. Also, the total annual gas consumption of the building was reduced up to 22.7% for hot and dry weather.

Weather Effects on Herbaceous Yields: Wyoming Big Sagebrush Steppe, Southeastern Oregon

Weather Effects on Herbaceous Yields: Wyoming Big Sagebrush Steppe, Southeastern Oregon

Global Inversion of Lunar Surface Oxides by Adding Chang’e-5 Samples

The chemical distribution on the lunar surface results from the combined effects of both endogenic and exogenic geological processes. Exploring global maps of chemical composition helps to gain insights into the compositional variation among three major geological units, unraveling the geological evolution of the Moon. The existing oxide abundance maps were obtained from spectral images of remote sensing and geochemical data from samples returned by Apollo and Luna, missing the chemical characteristics of the Moon’s late critical period. In this study, by adding geochemical data from Chang’e (CE)-5 lunar samples, we construct inversion models between the Christiansen feature (CF) and oxide abundance of lunar samples using the particle swarm optimization–extreme gradient boosting (PSO-XGBoost) algorithm. Then, new global oxide maps (Al2O3, CaO, FeO, and MgO) and Mg# with the resolution of 32 pixels/degree (ppd) were produced, which reduced the space weathering effect to some extent. The PSO-XGBoost models were compared with partial least square regression (PLSR) models and four previous results, indicating that PSO-XGBoost models possess the capability to effectively describe nonlinear relationships between CF and oxide abundance. Furthermore, the average contents of our results and the Diviner results for 21 major maria demonstrate high correlations, with R2 of 0.95, 0.82, 0.95, and 0.86, respectively. In addition, a new Mg# map was generated, which reveals different magmatic evolutionary processes in the three geologic units.

Quantifying risks of lane-changing behavior in highways with vehicle trajectory data under different driving environments

Improper lane-changing behavior may have a great impact on the safety of the surrounding vehicles, and accurate risk assessment of lane-changing behavior can detect improper lane-changing behavior. Many existing risk assessment methods are based on the traditional minimum safe distance model as the theoretical foundation, not taking into account the effects of different weather and road conditions. Moreover, the initially calculated safe lane-changing distance through the model is generally the limit safety distance, which deviates to some extent from the initial distance maintained when the vehicle begins to change lanes during the actual driving process. The ratio of these two distances can reflect the degree of risk between the changing vehicle and its neighboring vehicles during lane-changing. For this reason, a lane-changing safety coefficient is defined and lane-changing risk assessment model based on the hyperbolic tangent function is constructed by combining the change characteristics of this coefficient. An environmental adjustment factor was introduced into the model to consider the influence of different driving weather and road conditions on the lane-changing risk assessment. Then, based on survey data from the survey questionnaire, the weights of the influencing factors were determined by using the hierarchical analysis method, and the environmental adjustment factor in the model was calibrated by using the fuzzy comprehensive assessment method. Finally, to verify the effectiveness of the model, the lane-changing trajectories of 373 vehicles were extracted from the HighD dataset. The risk assessment value of lane-changing was calculated by using the constructed model and was classified into high-risk, medium-risk and low-risk by using the K-means++ clustering algorithm. Various evaluation results were compared with the evaluation results from the expert evaluation method and the classical risk evaluation indexes, and the evaluation results are basically the same, which verifies the effectiveness of the lane-changing risk model established.

Multi-agent system architecture for winter road maintenance: a real Spanish case study

Road safety remains a critical issue in contemporary society, where the sudden deterioration of road conditions due to weather-related natural phenomena poses significant risks. These abrupt changes can lead to severe safety hazards on the roads, making real-time monitoring and control essential for maintaining road safety. In this context, technological advancements, especially in sensor networks and intelligent systems, play a fundamental role in efficiently managing these challenges. This study introduces an innovative approach that leverages a sophisticated sensor platform coupled with a multi-agent system. This integration facilitates the collection, processing, and analysis of data to preemptively determine the appropriate chemical treatments for roads during severe winter conditions. By employing advanced data analysis and machine learning techniques within a multi-agent framework, the system can predict and respond to adverse weather effects swiftly and with a high degree of accuracy. The proposed system has undergone rigorous testing in a real-world environment, which has verified its operational effectiveness. The results from the deployment of the multi-agent architecture and its predictive capabilities are encouraging, suggesting that this approach could significantly enhance road safety in extreme weather conditions. Furthermore, the proposed architecture allows the system to evolve and scale over time. This paper details the design and implementation of the system, discusses the results of its field tests, and explores potential improvements.

Prevalence and risk factors for Anaplasma marginale seropositivity in cattle in California

Bovine anaplasmosis, a tick-borne disease caused by Anaplasma marginale, imposes considerable economic bur­den on cattle industries throughout the world. Clinical signs of bovine anaplasmosis include fever, weight loss, lethargy, jaundice, abortion and death. The severity of the disease in­creases with age, and calves under 1 year of age generally do not progress to clinical disease or develop mild disease. Once infected, cattle remain persistently infected carriers for life. Climate change and drought conditions may affect the distri­bution and prevalence of tick populations and tick-borne dis­eases and re-evaluating the seroprevalence of Anaplasma would provide a better understanding of the disease dynamics in California. To our knowledge, there has been no updated study regarding the distribution of Anaplasma infection status in California since 2008, and the information on weather factors related to the disease is also limited. There is an urgent need to evaluate the prevalence of Anaplasma infection in different regions of California. The goal of this study is to estimate the seroprevalence of Anaplasma infection in California cattle over time, and the specific goal is to identify potential risk factors for infection including animal demographics, region, Anaplasma seroprevalence of wild ruminants, Dermacentor tick species presence, and weather effects.

How does heavy haze weather impact operational efficiency? An empirical study of Chinese manufacturing firms

Global warming has escalated the frequency of extreme climate events. Considering the escalating severity of air pollution, investigating its potential to cause operational problems is of value. Some studies have explored air pollution's effects from individual perspectives, including emotions, attitudes, and decision-making behaviors. Yet, the influence of heavy haze weather on firm performance from an operations management viewpoint remains uninvestigated. This study seeks to address this research gap. Utilizing a longitudinal dataset from 2255 manufacturing firms between 2014 and 2020, this study empirically examines heavy haze weather's impact on operational efficiency. Three contingency categories are identified: strategic positioning, structural contingency, and institutional factors. The findings suggest that heavy haze weather adversely impacts operational efficiency, notably for firms with cost leadership strategies and high labor productivity, whereas such effect can weaken in the firms with process standardization and governmental environment inspection. Enhancing the understanding about the effect of heavy haze weather on operational performance, these findings offer strategic insights for firms to mitigate heavy haze weather and provide empirical support for government to make environmental policy-making.

Revolutionary Design and Optimization of Railway Electrification Overhead Equipment in High-Altitude Tunnels: A Case Study of the Magnificent T-80 Tunnel

Railway electrification systems are critical for modernizing railway infrastructure, enhancing efficiency, and reducing environmental impact to obtain zero emissions targets. In high-altitude regions, such as mountainous terrains, unique challenges arise due to extreme weather conditions, terrain complexities, and operational requirements. This case study focuses on the innovative and optimized design of overhead equipment (OHE) for railway electrification in high-altitude tunnels, presenting a comprehensive analysis of the planning, design, and implementation process for 25kV AC Overhead equipment. The study begins with an overview of significant considerations in designing 25kV AC OHE systems for high-altitude tunnels, including altitude effects on electrical performance, weather effects, structural safety checks, fire scenarios, vibration effects, and tunnel bolt drilling for OHE equipment installation. It also covers aspects such as the selection of auto tensioning devices, electrical clearances, and earthing & bonding according to railway/EN/IEC standards. Also, the paper examines the monetary feasibility and environmental sustainability of the proposed OHE design, emphasizing the importance of life-cycle cost analysis and environmental impact valuation. It underscores the significance of adopting a holistic approach that balances technical requirements, operational efficiency, and environmental stewardship in railway electrification projects.

Agromet Advisories to Mitigate the Effects of Aberrant Weather in Himachal Pradesh

Weather is a pivotal factor in agricultural production, influencing crop growth, disease and pest occurrences, water and fertilizer needs, and the effectiveness of cultural and preventive measures. Extreme weather events can cause physiological stress, physical damage, soil erosion, and crop quality degradation. In India, agriculture's vulnerability to adverse weather is a significant concern, with natural disasters like floods, droughts, and cyclones leading to crop failure, food insecurity, and economic impacts. To mitigate these challenges, Agrometeorological Advisory Services (AAS) play a crucial role in providing farmers with weather-based advisories to manage agricultural risks. The Integrated Agro-Meteorological Advisory Service (IAAS), run by the Indian Ministry of Earth Sciences and the India Meteorological Department (IMD), offers district-level weather forecasts and agromet advisories to support farmers in adapting to weather fluctuations. These advisories cover various weather-related risks, including cold injury and frost, high temperatures, wind damage, hailstorms, and floods. Sample advisories suggest measures like irrigation for frost protection, mulching to reduce heat stress, and shelter belts to mitigate wind damage. Effective dissemination of advisories involves communication through electronic media, Krishi Vigyan Kendras (Agriculture Science Centres), and Kisan (Farmer) Call Centres. Thrust areas for enhancing AAS include improved scientific understanding, advanced monitoring and prediction of severe weather events, satellite-based communication technologies, and real-time forecasting. By integrating these strategies, farmers can better prepare for extreme weather and mitigate its impact on agriculture.

Monitoring insect numbers and biodiversity with a vertical-beam entomological radar.

Concerns about perceived widespread declines in insect numbers have led to recognition of a requirement for long-term monitoring of insect biodiversity. Here we examine whether an existing, radar-based, insect monitoring system developed for research on insect migration could be adapted to this role. The radar detects individual larger (greater than 10 mg) insects flying at heights of 150-2550 m and estimates their size and mass. It operates automatically and almost continuously through both day and night. Accumulation of data over a 'half-month' (approx. 15 days) averages out weather effects and broadens the source area of the wind-borne observation sample. Insect counts are scaled or interpolated to compensate for missed observations; adjustment for variation of detectability with range and insect size is also possible. Size distributions for individual days and nights exhibit distinct peaks, representing different insect types, and Simpson and Shannon-Wiener indices of biodiversity are calculated from these. Half-month count, biomass and index statistics exhibit variations associated with the annual cycle and year to year changes that can be attributed to drought and periods of high rainfall. While species-based biodiversity measures cannot be provided, the radar's capacity to estimate insect biomass over a wide area indicates utility for tracking insect population sizes. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Shifts in controls and abundance of particulate and mineral-associated organic matter fractions among subfield yield stability zones

Abstract. Spatiotemporal yield heterogeneity presents a significant challenge to agricultural sustainability efforts and can strain the economic viability of farming operations. Increasing soil organic matter (SOM) has been associated with increased crop productivity, as well as the mitigation of yield variability across time and space. Observations at the regional scale have indicated decreases in yield variability with increasing SOM. However, the mechanisms by which this variability is reduced remain poorly understood, especially at the farm scale. To better understand the relationship between SOM and yield heterogeneity, we examined its distribution between particulate organic matter (POM) and mineral-associated organic matter (MAOM) at the subfield scale within nine farms located in the central United States. We expected that the highest SOM concentrations would be found in stable, high-yielding zones and that the SOM pool in these areas would have a higher proportion of POM relative to other areas in the field. In contrast to our predictions, we found that unstable yield areas had significantly higher SOM than stable yield areas and that there was no significant difference in the relative contribution of POM to total SOM across different yield stability zones. Our results further indicate that MAOM abundance was primarily explained by interactions between crop productivity and edaphic properties such as texture, which varied amongst stability zones. However, we were unable to link POM abundance to soil properties or cropping system characteristics. Instead, we posit that POM dynamics in these systems may be controlled by differences in decomposition patterns between stable and unstable yield zones. Our results show that, at the subfield scale, increasing SOM may not directly confer increased yield stability. Instead, in fields with high spatiotemporal yield heterogeneity, SOM stocks may be determined by interactive effects of topography, weather, and soil characteristics on crop productivity and SOM decomposition. These findings suggest that POM has the potential to be a useful indicator of yield stability, with higher POM stocks in unstable zones, and highlights the need to consider these factors during soil sampling campaigns, especially when attempting to quantify farm-scale soil C stocks.

Trends in childhood leukemia incidence in urban countries and their relation to environmental factors, including space weather.

Leukemia is the most common cancer in children. Its incidence has been increasing worldwide since 1910th, suggesting the presence of common sources of the disease, most likely related to people's lifestyle and environment. Understanding the relationship between childhood leukemia and environmental conditions is critical to preventing the disease. This discussion article examines established potentially-carcinogenic environmental factors, such as vehicle emissions and fires, alongside space weather-related parameters like cosmic rays and the geomagnetic field. To discern the primary contributor, we analyze trends and annual variations in leukemia incidence among 0-14-year-olds in the United States, Canada, Australia, and Russia from 1990 to 2018. Comparisons are drawn with the number of vehicles (representing gasoline emissions) and fire-affected land areas (indicative of fire-related pollutants), with novel data for Russia introduced for the first time. While childhood leukemia incidence is rising in all countries under study, the rate of increase in Russia is twice that of other nations, possibly due to a delayed surge in the country's vehicle fleet compared to others. This trend in Russia may offer insights into past leukemia levels in the USA, Canada, and Australia. Our findings highlight vehicular emissions as the most substantial environmental hazard for children among the factors examined. We also advocate for the consideration of potential modulation of carcinogenic effects arising from variations in cosmic ray intensity, as well as the protective role of the geomagnetic field. To support the idea, we provide examples of potential space weather effects at both local and global scales. The additional analysis includes statistical data from 49 countries and underscores the significance of the magnetic field dip in the South Atlantic Anomaly in contributing to a peak in childhood leukemia incidence in Peru, Ecuador and Chile. We emphasize the importance of collectively assessing all potentially carcinogenic factors for the successful future predictions of childhood leukemia risk in each country.

Proposal of a practical stability probability model for cut slopes reflecting characteristics of weathering and angle of stratification

This research evaluates the stability of cut slopes, considering the effects of weathering and the angle of stratification. Incorporating both a weathering degree index and a factor of safety, we developed a novel formula to assess the temporal deterioration of cut slopes. Utilizing this formula, logistic regression was conducted to ascertain cut slope stability. We used the Hierarchical Bayesian model to refine the parameters of the logistic regression function, culminating in the formulation of a comprehensive slope stability probability prediction model. The model’s predicted stability probabilities for diverse cut slopes exhibited a compelling congruence with empirical data upon validation. Importantly, this approach provides expressway management authorities with a tool to preliminarily assess whether longstanding in-service cut slopes require intervention or stabilization measures.

Powerless in the storm: Severe weather-driven power outages in New York State, 2017–2020

The vulnerability of the power grid to severe weather events is a critical issue as climate change is expected to increase extreme events, which can damage components of the power grid and/or lessen electrical power supply, resulting in power outages. However, largely due to an absence of granular spatiotemporal outage data, we lack a robust understanding of how severe weather-driven outages, their community impacts, and their durations distribute across space and socioeconomic vulnerability. Here, we pair hourly power outage data in electrical power operating localities (n = 1865) throughout NYS with urbanicity, CDC Social Vulnerability Index, and hourly weather (temperature, precipitation, wind speed, lightning strike, snowfall) data. We used these data to characterize the impact of extreme weather events on power outages from 2017–2020, while considering neighborhood vulnerability factors. Specifically, we assess (a) the lagged effect of severe weather on power outages, (b) common combinations of severe weather types contributing to outages, (c) the spatial distribution of the severe weather-driven outages, and (d) disparities in severe weather-driven outages by degree of community social vulnerability. We found that across NYS, 39.9% of all outages co-occurred with severe weather. However, certain regions, including eastern Queens, upper Manhattan and the Bronx of NYC, the Hudson Valley, and Adirondack regions were more burdened with severe weather-driven outages. Using targeted maximum likelihood estimation, we found that the frequency of heat-, precipitation-, and wind-driven outages disproportionately impacted vulnerable communities in NYC. When comparing durations of outages, we found that in rural regions, precipitation- and snow-driven outages lasted the longest in vulnerable communities. Under a shifting climate, anticipated increases in power outages will differentially burden communities due to regional heterogeneity in severe weather event severity, grid preparedness, and population socioeconomic profiles/vulnerabilities. As such, policymakers must consider these characteristics to inform equitable grid management and improvements.