Global Natural Disasters Research Articles

Speak up! brands’ responsiveness matters: consumer reactions to brand communications in the early stages of a crisis

PurposeIn an effort to provide insights that nurture the future of brand relationships, this paper aims to examine the impact of brand communications on consumption behavior during critical events that significantly impact the marketplace. Specifically, this research focuses on external crises (i.e. global health crises, natural disasters and regional conflicts) beyond the control of the corporations that govern brands. It does so by exploring the most effective brand communication strategies at the onset of a crisis when brands may shift promotional content to more sensitive, crisis-related content as a means to connect with consumers. Furthermore, this paper seeks to understand which consumer segment will benefit most from brands’ crisis-related content.Design/methodology/approachThis research introduces two empirical studies (combined sample = 490), using student and online participant samples.FindingsResults from this work demonstrate that at the onset of a crisis, consumers’ attitudes, brand engagement, and self-brand connections significantly increase after visualizing crisis-related versus noncrisis-related brand messages. Results also reveal that consumers who feel less socially connected will react more favorably to brand communications that contain crisis-related content (i.e. informative or emotional content related to the crisis) than non-crisis-related content (i.e. marketing content aimed to promote and advertise the brand, product and/or services).Research limitations/implicationsWhile the effect of crisis communications on consumption behavior and the moderating effect of social connections is explored, the underlying mechanism of these effects is not investigated in this study. Therefore, future research might consider evaluating the mechanisms that drive these effects.Practical implicationsThis work builds on past research to help establish that during early critical times, marketing managers should include crisis-related content in their communications, which will increase consumers’ positive reactions toward the brand.Social implicationsAnother implication of this work is that it underscores the significance of crisis-related brand communications as an inclusive practice because these are particularly well-received among vulnerable consumer segments, such as those who feel less socially connected during critical times.Originality/valueProactive communication strategies allow brands to better manage external critical challenges. As brands navigate a postpandemic marketplace, this research highlights the adaptations that managers can make to their communication strategies at peak uncertain times, such as the earlier stages of an external crisis.

Forest figures of the past (and present): Consequences on the future of settling with/in forests of the Garhwal Himalayas, India

This research unfolds the notion of ‘settling with/in forests,’ shaped by the dynamic environmental and socio-political interactions in India’s Garhwal Himalayas. Garhwal’s forests perform diverse ecosystem functions that characterise the regional landscape. Settling with/in forests is fundamental to Himalayan communities as, directly and/or indirectly, forests structure the ecology, livelihoods, settlements, and seasonal mobilities across the mountainous landscape. Today, Garhwal’s forests are endangered by the cascading impacts of global warming, increasing urbanisation, natural disasters, and extensive infrastructure construction. Using a “thick description” approach, the research seeks to examine the intertwined layers of forests, local habitats, practices, and institutions, provide insight into the region’s unique environmental history, and identify the challenges associated with settling with/ in forests. The research combines fieldwork, archival materials, and interpretive mapping to examine a case study in the Garhwal Himalayas.The findings highlight the conflicts and coexistence of State policies and non-state adaptations, as well as the vulnerability of the region’s forests to climatic stress and future anthropogenic change. The forests of Garhwal are critical to the larger Himalayan ecology, and the research findings point the way forward for developing potential adaptations that strengthen the concept of settling with/in forests.

Life cycle energy consumption prediction based on an extended system boundary with the Bi-LSTM model: An empirical study of China

Global warming and natural disasters have wreaked havoc on Earth these days. Energy conservation has been a priority under social development pressure, especially in the building sector. Energy consumption prediction serves as a vital tool for effective building energy management, guiding energy policy making and services distribution. However, despite the application of advanced technologies, achieving accurate energy consumption prediction still faces challenges due to potential influencing factors. This study aims to explore previously unidentified factors to enhance building energy consumption prediction accuracy. An extended life cycle energy boundary of buildings including embodied, operational, and mobile energies is proposed. To optimize the prediction processes, a hybrid Life Cycle Assessment (LCA) approach and a non-linear Bidirectional Long Short-Term Memory (Bi-LSTM) model are combined. An empirical study was conducted to predict the life cycle energy consumption of urban residential buildings in China by 2035. Results show: (1) life cycle energy consumption increased dramatically from 195.837 (±11.77) Mtce in 2000 to 1151.69 (±80.38) Mtce in 2022, but then achieved a slow decline to 796.998 ((±51.46)) Mtce by 2035; (2) there were four significant development stages in the residential field: rapid growth (2000–2010), sharp growth (2010–2018), slow growth (2018–2022), and stable fall (2022–2035); (3) mobile energy related to building location accounted for up to 28% of total energy consumption, and daily commuting is its largest emitter. However, calculation errors caused by diverse data sources and the fundamental model itself need to be addressed later. This study provides an original pathway of combining LCA with a non-linear model to improve energy consumption prediction and the completed primary historical data to help local governments’ energy decision-making.

Is the number of global natural disasters increasing?

ABSTRACT We analyze temporal trends in the number of natural disasters reported since 1900 in the Emergency Events Database (EM-DAT) from the Center for Research on the Epidemiology of Disasters (CRED). Visual inspection suggests three distinct phases: first, a linear upward trend to around mid-century followed by rapid growth to the turn of the new century, and thereafter a decreasing trend to 2022. These observations are supported by piecewise regression analyses that identify three breakpoints (1922, 1975, 2002), with the most recent subperiod 2002–2022 characterized by a significant decline in number of events. A similar pattern over time is exhibited by contemporaneous number of geophysical disasters – volcanoes, earthquakes, dry landslides – which, by their nature, are not significantly influenced by climate or anthropogenic factors. We conclude that the patterns observed are largely attributable to progressively better reporting of natural disaster events, with the EM-DAT dataset now regarded as relatively complete since ∼2000. The above result sits in marked contradiction to earlier analyses by two UN bodies (FAO andUNDRR), which predicts an increasing number of natural disasters and impacts in concert with global warming. Our analyses strongly refute this assertion as well as extrapolations published by UNDRR based on this claim.

Toward reframing brain-social dynamics: current assumptions and future challenges.

Evolutionary analyses suggest that the human social brain and sociality appeared together. The two fundamental tools that accelerated the concurrent emergence of the social brain and sociality include learning and plasticity. The prevailing core idea is that the primate brain and the cortex in particular became reorganised over the course of evolution to facilitate dynamic adaptation to ongoing changes in physical and social environments. Encouraged by computational or survival demands or even by instinctual drives for living in social groups, the brain eventually learned how to learn from social experience via its massive plastic capacity. A fundamental framework for modeling these orchestrated dynamic responses is that social plasticity relies upon neuroplasticity. In the present article, we first provide a glimpse into the concepts of plasticity, experience, with emphasis on social experience. We then acknowledge and integrate the current theoretical concepts to highlight five key intertwined assumptions within social neuroscience that underlie empirical approaches for explaining the brain-social dynamics. We suggest that this epistemological view provides key insights into the ontology of current conceptual frameworks driving future research to successfully deal with new challenges and possible caveats in favour of the formulation of novel assumptions. In the light of contemporary societal challenges, such as global pandemics, natural disasters, violent conflict, and other human tragedies, discovering the mechanisms of social brain plasticity will provide new approaches to support adaptive brain plasticity and social resilience.

The risk impacts of global natural and technological disasters

This research develops an expected risk model and estimates risk impacts of single or multiple disasters in terms of human fatality, injury, affected, and economic damage for nearly 200 nations. Both natural hazards, including geophysical, meteorological, hydrological, and technological disasters, such as industrial, transport, and structural, are considered. Relevant measures of expected risk, such as standard deviation, coefficient of variance, range, and rank are also calculated to assess a country's overall risk. Social-economic-physical factors from the World Development Index developed by the United Nations (UN) are then regressed with occurrences and risks of natural and tech disasters to seek plausible associations. The results show that (1) the model performs reasonably well in fitting observed and modeled risks and risk impacts, relatively better for natural disaster and affected people and economic damage; (2) while natural disasters are far more risky than tech ones in total risk impacts; specific risks for subgroups of natural or tech disasters vary widely in magnitude and by country; (3) high natural and/or tech risks concentrate in a small number of countries, such as China, India, Bangladesh in Asia; U.S., Mexico, Canada in North America; Turkey, Russia, France, Germany in Europe, and Algeria, Egypt, and Ethiopia in Africa, which are relatively large in population, fast in development, or advanced in industrialization; yet (4) high risk deviations per unit risk impacts reveal that many small, developing, and tech backward countries need to prepare even more for both natural and tech disasters. Finally, (5) while many country-level development factors, together with disaster occurrence, are statistically significant, only some can provide weak predictability of disaster risk impacts under robust regression. The research findings provide useful risk references to countries for resilient national policies for disaster preparation, mitigation, and recovery.

The influence of information and communication technologies on disaster relief operations: a case of Cyclone Idai in Zimbabwe

PurposeThere has been an avalanche of global natural disasters in recent times. In recent years approximately 210 million people were affected, an estimated economic cost of US$153bn was incurred and 68,000 deaths were recorded. This was a work up call that made it imperative for humanitarian actors to impetuously adopt information and communication technologies (ICTs) to timeously assist affected populations in disaster prevention, mitigation response and recovery However, the use of ICTs in the humanitarian field is still at its infancy in most third world countries. The purpose of this study was, therefore, to evaluate the utilization of ICTs in humanitarian relief operations associated with Cyclone Idai in Zimbabwe.Design/methodology/approachUsing a pragmatic approach, the study gathered data using semistructured questionnaires that were triangulated with interviews of humanitarian staff that were involved in Cyclone Idai relief efforts.FindingsAn observed suboptimal utilization of ICTs was further disadvantaged by the inequitable distribution of communication infrastructure. However, despite the suboptimal usage, there was a significant positive influence of ICT adoption on effectiveness, efficiency and flexibility in humanitarian relief operations.Originality/valueOptimal use of ICTs has the potential to revolutionize humanitarian supply chain management. A smooth transition to new technologies is recommended in which personnel are given professional development opportunities on a regular basis.

DMP: Analysis of global emissions and natural disasters from 1960 to 2021

DMP: Analysis of global emissions and natural disasters from 1960 to 2021

Effect of Low Temperature on Insecticidal Protein Contents of Cotton (Gossypium herbaceum L.) in the Boll Shell and Its Physiological Mechanism.

Low temperature is the main factor for global natural disasters affecting the growth and distribution of plants, and cotton may be affected by low temperature and cold damage at all growth stages. In addition, the insecticidal resistance of cultivars has been reported to perform poorly or unstably due to adverse environments. The present study aimed to investigate the impact of low temperature on the levels of insecticidal protein in Bacillus thuringiensis (Bt) transgenic cotton plants during the peak boll stage. To achieve this, two Bt cotton cultivars, Sikang1 (SK1) and Sikang3 (SK3), were subjected to different temperature regimes and durations. The findings of the study demonstrated that the expression of insecticidal protein in the boll shell of Bt transgenic cotton plants was significantly inhibited under low-temperature stress. Specifically, in 2020, compared to the CK (27 °C), the insecticidal protein content in the boll shell of SK3 decreased by 28.19% after a 48 h of a 16 °C temperature. These results suggest that low-temperature stress can negatively impact the expression of insecticidal protein in Bt transgenic cotton, highlighting the need for appropriate measures to minimize its adverse effects on cotton production. In addition, the threshold temperature that leads to a significant decrease in the content of insecticidal proteins symbolizes an upward trend as the duration of stress prolongs. Decreased Bt protein content at low temperatures is associated with changes in the N metabolism. The present study revealed a significant positive correlation between the levels of glutamate oxaloacetate transaminase (GOT) and glutamate pyruvate transaminase (GPT) activities, as well as in the soluble protein levels in the boll shell and the content of the Bt protein. On the other hand, a significant negative correlation was observed between the levels of free amino acids, peptidase, and protease activities, as well as of Bt protein content. These findings suggest that, in Bt cotton production, it is crucial to remain vigilant of prolonged low-temperature disasters, which last for over 12 h and drop below 17-20 °C during the peak boll stage. Such conditions may reduce insecticidal resistance, leading to substantial economic losses.

Digital Diplomacy and Social Media Networks: Contemporary Practices of Innovation in Foreign Policy

Introduction. The article is devoted to contemporary digital diplomacy, which is implemented within the framework of social networks. Unlike traditional diplomacy digital one operates in a different communicative space where blogs, electronic media and global social networks are the key communication channels. Using these tools allows digital diplomacy actors to influence events and communities in other countries. Methods and materials. Method of mixing qualitative and quantitative data, hashtag-analysis, comparative analysis of the social networks’ messages and accounts were able to understand the dynamics and interactions in social networks, engagement and possibilities of institutional and private actors in digital diplomacy. Analysis. In the 2000s foreign policy and public diplomacy began forming based on data on the mood of users of social networks and their preferences in politics. Thanks to this, digital diplomacy may well become one of the innovative tools for resolving modern global problems. Digital diplomacy, as a new method and the tool for implementing foreign policy, contributes to the effective functioning of departments and ministries of foreign affairs, their response to the needs of citizens, to emerging challenges and threats to state security, like a global epidemic or natural disasters. Using digital tools, it is possible to shape the norms of communication, interaction and decision-making by which diplomats perform their work, modifying the diplomatic process. Besides this digital diplomacy increases the attractiveness of the state in the eyes of the world community. Results. Based on a comparative analysis study of the content of social networks, it could be concluded that over almost a decade, from the 2010s to the 2020s, digital diplomacy has developed from a “soft power” mechanism to a method of information warfare and propaganda which involves artificial intelligence tools and big data. But this is predominantly characteristic of technologically developed countries. It is possible to conclude about future co-existence of traditional and digital diplomacies in a new hybrid variety. Authors’ contribution. In this article Liudmila M. Reshetnikova has contributed Introduction, Research Methods, Analysis and Results sections: identified risks and threats to digital diplomacy, analyzed the development of the soft power methods, identified features and tools of digital diplomacy. Irina M. Samokhina has contributed Analysis and Results sections: analyzed social networks and digital infrastructure for digital diplomacy and diplomatic activity, contemporary computer tools for learning about social networks.

CHILDREN’S RIGHTS AND ACCESS TO HEALTH CARE

Children have the right to health, to life, to protection and to special care and attention from their parents and from the community in which they live. A number of international acts regulate and regulate these rights, and the national legislation in the country confirms and guarantees them.A pilot survey on children’s and their parents’ awareness of children’s rights in Bulgaria and their access to health care was conducted among 201 parents, in the period 01.12.2021-01.01.2022. Respondents were asked whether they were aware of children’s rights, whether they encountered obstacles to realizing their right to health, as well as whether, in their opinion, children have real access to health care in the country. More than 50% indicate that they are familiar with children’s rights, 64.7% answer that children in the country have real access to health care, but 44% share that they encountered certain obstacles when realizing their right to health.Issues concerning children, their rights and their access to health care affect the interests of individual families, of a given nation, but also of the entire society globally. There are positive trends around the world regarding children’s access to health care, but these rights depend not only on the individual and on national legislations, but also on global political decisions and natural disasters that cause refugee flows and put countries in front of new challenges.

Prevalence of different diseases and growth performance of broilers vary with environmental variation

Abstract Broiler meat is known for its nutritional value, widespread availability, and low price. However, broilers are sensitive to environmental conditions and need a specific environment for optimum production. Global warming and natural disasters are important obstacles to broiler production. Therefore, we conducted this study during analysed the years 2019, 2020, and 2021, to reveal the broiler production status throughout the year in a subtropical region. The study area included Noakhali and Lakshimpur, located in the southern part of Bangladesh. We selected 10 smallholder broiler farms following specific conditions and collected information at the end of each month for analysis. The body weight of broilers was significantly lower in July than in other months. However, the mortality was significantly lower in July than in other months of the year. Nonetheless, the prevalence of viral disease was higher in the winter season (December, January and February). Although, the prevalence of metabolic diseases was higher in October, a high prevalence of bacterial disease was found in April. These results suggest that high temperatures decrease broiler performance while broilers are more susceptible to viral disease in the winter season.

Construction of an Integrated Drought Monitoring Model Based on Deep Learning Algorithms

Drought is one of the major global natural disasters, and appropriate monitoring systems are essential to reveal drought trends. In this regard, deep learning is a very promising approach for characterizing the non-linear nature of drought factors. We used multi-source remote sensing data such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Climate Hazards Group Infrared Precipitation with Station (CHIRPS) data to integrate drought impact factors such as precipitation, vegetation, temperature, and soil moisture. The application of convolutional long short-term memory (ConvLSTM) to construct an integrated drought monitoring model was proposed and tested, using the Xinjiang Uygur Autonomous Region as an example. To better compare the monitoring performance of ConvLSTM models, three other classical deep learning models and three classical machine learning models were also used for comparison. The results show that the composite drought index (CDI) output by the ConvLSTM model had a consistent high correlation with the drought rating of the multi-scale standardized precipitation evapotranspiration index (SPEI). The correlation coefficients between the CDI and the multi-scale standardized precipitation index (SPI) were all above 0.5 (p < 0.01), which was highly significant, and the correlation coefficient between CDI-1 and the monthly soil relative humidity at a 10 cm depth was above 0.45 (p < 0.01), which was well correlated. In addition, the spatial distribution of the CDI-6 simulated by the model was highly correlated with the degree of drought expressed by the SPEI-6 observations at the stations. This study provides a new approach for integrated regional drought monitoring.

Global Natural Disasters: An Earthquake Assessment

Global Natural Disasters: An Earthquake Assessment

Global Natural Disasters: An Earthquake Assessment

Global Natural Disasters: An Earthquake Assessment

Mechanistic Analysis and Numerical Simulation of the 2021 Post‐Fire Debris Flow in Xiangjiao Catchment, China

AbstractWildfires are becoming a global natural disaster under climate change. A worthwhile concern is that the rainfall thresholds that trigger debris flows in catchments affected by recent wildfires are much lower than those that trigger debris flows in catchments with similar environments but that have not experienced wildfires. In this study, we investigated a major post‐fire debris flow event in Xiangjiao catchment triggered by heavy rainfall in 2021. Through the combination of field observation, laboratory experiments and several numerical models (rainfall interception, infiltration, erosion and runoff models), the physical mechanistic analysis and numerical simulation of the post‐fire debris flow in Xiangjiao catchment was carried out. Results show that the simulated deposited area, erosion depth, and the occurrence time of debris‐flow initiation correlate well with the actual situation. It is demonstrated that the numerical simulation method used in this study can be used to effectively describe the characteristics of the initial and propagation stages of the post‐fire debris flow generated by runoff and provide important insights and guidance for the prediction and prevention of debris‐flow disasters in catchments affected by wildfire.

Carbon emissions modeling for smarter carbon footprint decisions: A systematic review

Climate change and environmental deterioration due to greenhouse gas emissions are a major concern around the globe today. This article aims to highlight how various authors have carried out carbon emissions modeling for smarter carbon footprint management and also proffer solutions to the greenhouse gas emissions issue, which is giving rise to global warming and natural disasters across the globe. This study makes use of the Systematic Literature Review (SLR) methodology for identifying, analyzing, and synthesizing articles published from 2015 to 2020, a period of 6 years, on the topic of carbon emissions modeling. The SLR results indicated that there has been a rising interest in the issue of carbon emissions from the period of 2015 to 2020, as seen by the evolution of publications in the area. This can be explained by the increased incidence of natural disasters occurring as a result of the global warming phenomenon due to greenhouse gas emissions. The various ways in which different models have been used for carbon emission analysis and management have been described, while explaining various means by which greenhouse gas emissions can be curtailed to stop the alarming rate of global warming and maintain a sustainable and habitable planet for all.

Pengaruh Edukasi Ular Tangga Mitigasi Banjir Terhadap Tingkat Pengetahuan Usia 10-12 Tahun Desa Beran Kismoyoso

The Global Natural Disaster Assessment Report (2019) recorded 49.31% of flood disasters in the world (United Nations Office for Disaster Risk Reduction, 2019. BNPB recorded 80% of people in the country who are at high risk of disasters, including 200 million people exposed to disaster risk with 107 million of them being of school age. During disasters, children are vulnerable to disease due to weak immune system and insufficient intake of nutritious food at the time of a disaster. Children lose social support, become traumatized. Knowing the effect of Flood mitigation education through snakes and ladders games on the level of knowledge of flood disaster mitigation Aged 10-12 Years Beran Kismoyoso Ngemplak Boyolali Village. This research is a type of quantitative research with the Pre-Experimental method with the One Group Pre-Test Post-Test Design approach. Sampling of 25 respondents using the Non Probability Sample sampling technique is saturated or all populations are used to be semple. The data collection technique uses a questionnaire with 25 questions related to self-rescue during flood disasters and knowledge about flood disasters. Wilcoxon's test results showed a p-value of 0.003<0.05 meaning that there was a difference in the average level of knowledge of flood disaster mitigation before and after being given the snakes and ladders game of flood disaster mitigation. Based on the results of the study, it shows that there is a significant influence of snakes and ladders game education in increasing knowledge of flood disaster mitigation in children aged 10-12 years in Beran Kismoyoso Ngemplak Boyolali Village.

Measurement of Power Grid Resilience Based on a Dynamic Inoperability Input–Output Model

The increase in global natural disasters, emergencies, and terrorist attacks brings great challenges to the flexible operation of power grids. The research on the flexibility of power grids becomes more and more important. At the same time, the rapid development of renewable energy and smart grids also provides new opportunities for research of flexible power grids. Based on the dynamic inoperability input–output model (DIIM), this study creatively uses the node transmission power to represent the relationship between nodes in the power grid and then studies the resilience measurement of the power grid. First, the significance of studying power grid resilience is discussed, and the absorption and recovery capacity of power grid resilience is described. Second, the power grid resilience measurement model based on the DIIM is established, and a theoretical analysis is carried out. Using the characteristics of inoperability, the power grid resilience is measured from the time aspect, and the characteristics of the model are analyzed at the same time. On the basis of theoretical analysis, this study also provides a control strategy to improve the grid resilience, which has good convenience and applicability. Finally, the theoretical analysis method is applied to a power grid example, and the correctness and effectiveness are verified. The measurement model can intuitively display the resilience characteristics of power grids and provide theoretical support for management and emergency response.

Optimization of Urban Shelter Locations Using Bi-Level Multi-Objective Location-Allocation Model.

Recently, global natural disasters have occurred frequently and caused serious damage. As an important urban space resource and public service facility, the reasonable planning and layout optimization of shelters is very important to reduce the disaster loss and improve the sustainable development of cities. Based on the review of location theory and models for shelter site selection, this study constructs a bi-level multi-objective location-allocation model, an accessibility, economy, and efficiency (AEE) model, based on sequential decision logic to maximize the economic sustainability and social utility. The model comprehensively considers factors such as the level of decision-making, the utilization efficiency, and capacity constraints of shelters. The gravity model is introduced to simulate the decision-making behavior of evacuees. A calculation example and its solution prove the high practicability and operability of the AEE model in an actual shelter site selection and construction investment, which can achieve the global optimization of evacuation time and the maximization of the use efficiency of the shelters under the financial constraints. It provides a scientific and effective decision-making method for the multi-objective location optimization problem of shelters.