Geophysical Disasters Research Articles

Incompleteness of natural disaster data and its implications on the interpretation of trends

ABSTRACT We use data from a leading global database, primarily the reported numbers of fatal ‘hydrological’, ‘meteorological’ and ‘geophysical’ disasters and associated fatalities, to elucidate long-term trends in natural disaster impact. There are very strong upward trends in the number of reported disasters. However, we show that these trends are strongly biased by progressively improving reporting. We apply well-established methods based on analysing evolving differences in the patterns of large (many fatalities) to small (fewer fatalities) events to assess and quantify this bias. For all disaster types investigated, the long-term (multi-decade) true number of disasters appears to be unexpectedly stable over time. There was, however, a clear temporary increase between 1980 and 1990 for hydrological and meteorological disasters. Importantly, there has been a large long-term decline in total fatalities reported for weather-related disasters, attributable to very effective mitigation for larger disasters. Probably due to improved mitigation rather than reduced hazard, data for the most recent decades shows a systematic decrease in the number of larger (more fatality) weather-related disasters compared to smaller ones. In contrast, for the geophysical disasters, predominantly earthquakes, the relative numbers of larger versus smaller disasters, are fairly constant, as are total fatalities.

Understanding spatiotemporal variation of social vulnerabilities from longitudinal hurricane-pandemic data: A multilevel model of the Covid-19 pandemic during hurricane Sally in Florida

An important question in the context of compound disasters is the degree to which geophysical disasters amplify the transmission of infectious diseases during pandemics and how this relationship is influenced by the social vulnerability of affected populations. This article proposes a spatiotemporal modeling approach to understand spatially varying social, demographic and health drivers of vulnerability during pandemics co-occurring with geophysical hazards. A multilevel mixed-effects model is developed to investigate the dynamic association between census tract-level Covid-19 case count trajectories co-occurring with a hurricane and demographic, socioeconomic and health factors. A state-level analysis is conducted to identify the distinct geographical regions in which significant changes are seen in the infection count trends due to the hurricane. A subsequent region-level analysis is performed to describe, at a higher spatial resolution, the impact of social vulnerability on the infection count trajectories at a community level. The method provides an approach to systematically study the effects of compound hazards and distinct patterns of infectious disease spread during hurricanes by quantifying (1) dynamic associations between infection counts and social factors and (2) spatial heterogeneities of these associations between communities. A case study for modeling the spatiotemporal variation of social vulnerability with data from Covid-19 pandemic and Hurricane Sally in Florida is presented to illustrate the application of the approach.

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.

Vulnerability assessment of an existing hospital structure towards earthquake in New Delhi, India: A case study

In the present scenarios, the increase rate of earthquakes all over the world is becoming a challenging problem. Also, from the studies conducted by international organizations, it had been noticed that with increase in the occurrence of geophysical disasters, their magnitude had also been increasing with an alarming rate. One of the most important structures which are to be designed and analyzed with the most optimum earthquake – resistant design is of hospitals as they are not only considered to be as a caring aid, but also a curing unit to the society in case of calamities. This study involves considering an existing hospital structure located in the capital city of India, New Delhi (Zone IV). The existing hospital structure is analyzed for determination of the weak structural members during seismic action in ETABS 2019. Pushover Analysis is considered for the determination of effects of seismic forces on the structural elements of the hospital structure. IS 1893: 2016 Codal Provisions had been used for considering seismic loading on the hospital structure. Also, the most efficient section in resisting the earthquake forces is determined.

Impact of Disasters on Older Adult Cancer Outcomes: A Scoping Review.

There is an urgent need to address the growing global cancer burden in the context of complex disaster events, which both disrupt access to oncology care and facilitate carcinogenic exposures. Older adults (65 years and older) are a growing population with multifaceted care needs, making them especially vulnerable to disasters. The objective of this scoping review is to characterize the state of the literature concerning older adult cancer-related outcomes and oncologic care after a disaster event. A search was conducted in PubMed and Web of Science. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for scoping reviews, articles were extracted and screened for inclusion. Eligible articles were summarized using descriptive and thematic analyses. Thirty-five studies met all criteria for full-text review. The majority focused on technological disasters (60%, n = 21), followed by climate-amplified disasters (28.6%, n = 10) and geophysical disasters (11.4%, n = 4). Thematic analysis classified the current evidence into three major categories: (1) studies concerned with carcinogenic exposure and cancer incidence related to the disaster event, (2) studies examining changes in access to cancer care and cancer treatment disruptions as a result of the disaster event, and (3) studies exploring the psychosocial experiences of patients with cancer affected by a disaster event. Few studies focused on older adults specifically, and most of the current evidence focuses on disasters in the United States or Japan. Older adult cancer outcomes after a disaster event are understudied. Current evidence suggests that disasters worsen cancer-related outcomes among older adults by disrupting continuity of care and access to timely treatment. There is a need for prospective longitudinal studies following older adult populations postdisaster and studies focused on disasters in low- and middle-income country contexts.

Research in computing-intensive simulations for nature-oriented civil-engineering and related scientific fields, using machine learning and big data: an overview of open problems

This article presents a taxonomy and represents a repository of open problems in computing for numerically and logically intensive problems in a number of disciplines that have to synergize for the best performance of simulation-based feasibility studies on nature-oriented engineering in general and civil engineering in particular. Topics include but are not limited to: Nature-based construction, genomics supporting nature-based construction, earthquake engineering, and other types of geophysical disaster prevention activities, as well as the studies of processes and materials of interest for the above. In all these fields, problems are discussed that generate huge amounts of Big Data and are characterized with mathematically highly complex Iterative Algorithms. In the domain of applications, it has been stressed that problems could be made less computationally demanding if the number of computing iterations is made smaller (with the help of Artificial Intelligence or Conditional Algorithms), or if each computing iteration is made shorter in time (with the help of Data Filtration and Data Quantization). In the domain of computing, it has been stressed that computing could be made more powerful if the implementation technology is changed (Si, GaAs, etc.…), or if the computing paradigm is changed (Control Flow, Data Flow, etc.…).

Consequences of “natural” disasters on aquatic life and habitats

“Natural” disasters (also known as geophysical disasters) involve physical processes that have a direct or indirect impact on humans. These events occur rapidly and may have severe consequences for resident flora and fauna as their habitat undergoes dramatic and sudden change. Although most studies have focused on the impact of natural disasters on humans and terrestrial systems, geophysical disasters can also impact aquatic ecosystems. Here, we provide a synthesis on the effects of the most common and destructive geophysical disasters on aquatic systems (life and habitat). Our approach spanned realms (i.e., freshwater, estuarine, and marine) and taxa (i.e., plants, vertebrates, invertebrates, and microbes) and included floods, droughts, wildfires, hurricanes/cyclones/typhoons, tornadoes, dust storms, ice storms, avalanches (snow), landslides, volcanic eruptions, earthquakes (including limnic eruptions), tsunamis, and cosmic events. Many geophysical disasters have dramatic effects on aquatic systems. The evidence base is somewhat limited for some natural disasters because transient events (e.g., tornadoes and floods) are difficult to study. Most natural disaster studies focus on geology/geomorphology and hazard assessment for humans and infrastructure. However, the destruction of aquatic systems can impact humans indirectly through loss of food security, cultural services, or livelihoods. Many geophysical disasters interact in complex ways (e.g., wildfires often lead to landslides and flooding) and can be magnified or otherwise mediated by human activities. Our synthesis reveals that geophysical events influence aquatic ecosystems, often in negative ways, yet systems can be resilient provided that effects are not compounded by anthropogenic stressors. It is difficult to predict or prevent geophysical disasters but understanding how aquatic ecosystems are influenced by geophysical events is important given the inherent connection between peoples and aquatic ecosystems.

The Annual Global Incidence Rate of Extreme Weather Event Disasters Appears Positively Correlated with World GDP, 1961-2020.

This study compared the per capita annual global incidence rate of disasters caused by natural hazards with the annual world real gross domestic product, GDP (per global capita), as reported during 1961 through 2020. Sixty (60) values for the world real GDP per global capita (in constant 2015 $USD) were compared to corresponding annual values for global incidence rates for five natural disaster subgroups and then for a total of twelve individual disaster types that comprise the subgroups; each expressed as an annual global incidence rate (in terms of annual incidence per 100,000 persons). Calculations of multiple linear regression, ANOVA, and Pearson's correlation coefficient were performed for comparing population-adjusted values for GDP to corresponding values. Four out of five hydrological and meteorological disasters were found to have a positive correlation with GDP. Results of the analysis revealed a relatively high degree of correlation between world GDP and the annual incidence of flood and storm disasters (P = 6.21 × 10-10 and P = 4.23 × 10-4, respectively). The annual incidence of heat waves and cold weather disasters also appeared to correlate with GDP (P = .002 and P = .019, respectively). In comparison, wet landslides indicated no such correlation (P = .862). No significant associations were found among the seven other individual biological, climatological, and geophysical disasters and GDP. The global incidence of four extreme weather (hydrometeorological) disasters appear to be positively associated with world real GDP during 1961-2020. These findings contradict previous postulates that the risk of disaster incidence is inversely associated with the capacity of the population.

Providing a framework for post-disaster resilience factors in buildings and infrastructure from end-users’ perspectives: case study in Caribbean island states

Purpose The purpose of this paper is to elicit the expectations for resilient post-disaster rebuilds from Caribbean project end-users. In anticipation of future climatological, meteorological, hydrological or geophysical disasters disaster, key stakeholders can articulate and incorporate strategies for resilience development, thus leading to improved end-users’ satisfaction and confidence. Design/methodology/approach This paper engages the results of a systematic literature review that identified 24 empirical resilience factors for post-disaster reconstruction projects. These factors informed a semi-structured questionnaire to elicit the perspectives of Caribbean end-users on a seven-point Likert scale. The quantitative analysis of both factor ranking and principal component analysis was performed to identify correlations and provides further interpretations on the desires of the end-users for resilient rebuilds. Findings The results presented in this paper highlight the collective perspectives on the Caribbean end-users on what they perceived to be aiding more resilient reconstruction projects. They identified reconstruction designs mindful of future hazards, policies that aid climate change mitigation, active assessment of key structures, readily available funding sources and ensuring stakeholder’s unbiased interest as the top-most empirical factors. Factor analysis suggested collaborations with inclusive training and multi-stakeholder engagement, critical infrastructure indexing and effective governance as the critical resilience development factors. Originality/value To the best of the authors’ knowledge, this paper is first of its kind to explore the perspective of the Caribbean people regarding disaster reconstruction projects. It addresses developmental avenues for measurement indicators towards resilience monitoring and improvement. Additionally, the perspectives can provide construction industry professionals with tools for improved operational resilience objective-setting guidance, for Caribbean construction.

Tsunami Potential Prediction using Seismic Features and Artificial Neural Network for Tsunami Early Warning System

Tsunamis are categorized as geophysical disasters because tectonic earthquakes triggered most of their occurrences. The high number of deaths due to tsunami catastrophe has made many countries develop a tsunami early warning system (TEWS), especially countries prone to tectonic earthquakes. One of the crucial subsystems in a TEWS is the tsunami potential prediction subsystem. To provide an early warning of tsunami, the prediction must be carried out based on early observation of the seismic event before the tsunami. In this short time of computation, the calculation of seismic parameters can only produce some roughly estimated features. Hence, a proper inference method that can decide accurate predictions upon the features is urgently needed for the TEWS. Some existing TEWSs are using rule-based inference to decide the prediction and often overestimate the prediction of tsunami potential. This study tries to develop a tsunami-potential prediction system using the machine learning approach as its inference method. Seismic features extracted from P-wave seismic signals are used as input data for learning and classification using a backpropagation artificial neural network (ANN). The accuracy result is then validated by K-fold cross-validation. Our simulation results show that the utilization of backpropagation ANN has given better accuracy in tsunami prediction compared to one of the existing TEWS that does not use machine learning for its prediction. At least for some seismic events that occurred during 2010-2017, the proposed system results in fewer overestimated predictions than the existing TEWS referred.

Reasons Why Geomagnetic Field Generation is Physically Impossible in Earth’s Fluid Core

Despite the importance for understanding the nature of the geomagnetic field, and especially its potential for radically disrupting modern civilization [1], virtually all scientific publications relating to it are based upon the false assumption that the geomagnetic field is generated in the Earth’s fluid core. By adhering to an outmoded paradigm, members of the geoscience community have potentially exposed humanity to globally devastating risks, leaving it unprepared for an inevitable geomagnetic field collapse.
 There is no scientific reason to believe that the geomagnetic field is generated within the fluid core. Convection is physically impossible in the fluid core due to its compression by the weight above and its inability to sustain an adverse temperature gradient. There is no evidence of ongoing inner core growth to provide energy to drive thermal convection or to cause compositional convection. Moreover, there is no mechanism to account for magnetic reversals and no means for magnetic seed-field production within the fluid core to initiate dynamo amplification.
 Earth’s nuclear georeactor, seat of the geomagnetic field, has none of the problems inherent in putative fluid-core geomagnetic field production. With a mass of about one ten-millionth that of the fluid core, georeactor sub-shell convection can potentially be disrupted by great planetary trauma, such as an asteroid impact, or by major solar outbursts or even by human activities, for example, by deliberate electromagnetic disturbance of the near-Earth environment, including the Van Allen belts. Furthermore, sub-shell convection disruption might trigger surface geophysical disasters, such as super-volcano eruptions [2-4].
 Scientists have a fundamental responsibility to tell the truth and to provide scientific understanding that benefits humanity.

Preface

IOP Conference Series: Earth and Environmental Science PAPER • OPEN ACCESS International Geography Seminar (IGEOS) 2019 PREFACE Globally, geophysical disasters - especially earthquakes - killed more people than any other type of natural hazard in the last 20 years with a cumulative number of around 747,000 fatalities. Natural disasters may manifest themselves with or without warning, while human-induced disasters are tangled with unsustainable anthropogenic activities in the built environment. Disasters take various forms such as earthquake, landslide, rainstorms, volcanic eruption windstorms, floods, ethno-religious crises, wildfires, explosions, terrorist?s attacks etc. The calamitous nature of these disasters therefore calls for their effective management. Extensive disasters were important because they can be used as learning opportunities to face the risk of routine disasters and the importance of continuous disaster learning at all times. The 3rd International Geography Seminar (IGEOS) “Increasing Disaster Literacy towards Resilient Comunities” was appointed to get input from various experts on the characteristics, problems and risk reduction efforts of various types of disasters.The 3rd International Geography Seminar (IGEOS) is a third international event organized in 2019 by the Department of Geography Education Universitas Sebelas Maret Solo in collaboration with the Department of Geography Education, Faculty of Social Science Education, Universitas Pendidikan Indonesia (UPI).We proudly announced that this proceeding is the result of discussion from 3rd IGEOS’ meeting of leading academic scientists, researchers and scholars on all aspects of geographical studies and practices. It also provides interdisciplinary discourses and the discussion of most recent innovations, trends and concerns as well as practical challenges and solutions adopted within this field.Praise be to Allah for the opportunity to organize and host this seminar. Furthermore, we would like to thank the the Rector of for their encouragement and support. We would also like to congratulate members of the organizing committee for their endless hard work and dedication as well as perseverance in making sure that this seminar is a success.The EditorsNandiPipit WijayantiChatarina MuryaniFauziah Che lehJunun SartohadiAhmad YaniAriff IsmailList of Committee and Conference Photographs are available in this pdf.

A review of risk analysis methods for natural disasters

Between 1998 and 2017, 1.3 million people were killed and another 4.4 billion were left injured, homeless, displaced, or in need of emergency assistance due to climate-related and geophysical disasters. A risk analysis of natural disasters is helpful not only for disaster prevention and reduction, but also in reducing economic and social losses. Currently, there are many methods for natural disaster risk analysis. Based on the uncertainty, unfavorable and future characteristics of natural disaster risk, this paper summarizes the methods for disaster risk analysis based on the scope of application, research results, and focus; it also clarifies the advantages and disadvantages of various methods, as well as the scope of application, to provide a reference for selecting and optimizing methods for future disaster risk analysis.

Upgrading destruction?

Purpose The authors investigate natural disasters’ impact on manufacturing and services foreign direct investment (FDI), both, in contemporaneous and time-lag contexts. Manufacturing and services FDI account for different types of technology transfers, respectively, through tangible physical assets and intangible knowledge assets. This paper aims to hypothesize that natural disasters that have pronounced physical impact, have different effect on different sectoral FDI. Design/methodology/approach The authors merge a data set from emergency events database, which covers natural disasters occurrences with a sector-level data on FDI for 69 countries for the period 1980-2011, distinguishing between four different kinds of natural disasters such as meteorological, climate, hydrological and geophysical, as well as between different geographical regions. Findings Controlling for commonly accepted determinants of FDI, such as output growth, quality of institutions and natural resource abundance, the authors find that manufacturing FDI is negatively affected immediately after the disaster and positively in the longer run- a finding that is in unison with the “creative destruction” growth theory. Services FDI, on the other hand, do not show such pattern. Meteorological disasters have no effect on services FDI and climate and hydrological disasters have long-lasting negative effects. For both, manufacturing and services FDI, geophysical disasters have a positive impact on FDI in the long run. Research limitations/implications The study is limited to 69 countries for the period 1980-2011. Practical implications FDI bears tangible and intangible knowledge assets and provides means of financing, even in countries with under-developed banking systems and stock markets. FDI is impacted by climate change, manifested by intensifying and increase of frequency of natural disasters. Social implications Natural disasters destroy infrastructure and displace people. The rebuilding of infrastructure and intangible capital present an opportunity for upgrading. Originality/value This is the first study that analyzes the impact of natural disasters on sector-level FDI in a multicounty and regional context.

Cross-sectional sero-prevalence of tularemia among murine rodents of Nepal

In April of 2015, a massive earthquake and hundreds of aftershocks stroked entire country. Geophysical disasters not only create economic crisis but also cause changes in disease ecology. Tularemia is a zoonotic disease with range of pathogenicity in different animal species. This study was designed to identify the disease status of tularemia in different species of murine rodents of Chitwan District of Nepal. Once the rodents were recovered from metal traps, they were euthanized by injectable anesthesia overdose followed by cervical dislocation. Blood was collected from the heart, and serum was isolated. Presence of tularemia antibodies in the serum was tested by using immunochromatographic test kit containing bacterial lipopolysaccharides. Of the total 80 serum samples tested, 1 sample was found tularemia positive, i.e., apparent prevalence 1.25% (95% CI, i.e., normal approx. CL, − 1.18 to 3.68%) and the true prevalence 0.5024% (95% CI, i.e., Blacker CL, 0 to 5.45%). Likewise, 23.75% (95% CI, i.e., normal approx. CL, 14.42 to 33.08%) of the animals were found with a few to numerous whitish/grayish or yellowish foci and 13.75% (95% CI, i.e., normal approx. CL, 6.2 to 21.3%) of animals with cystic lesions in their liver parenchyma. The location’s prevalence was 3.70% for Bharatpur, while nil for the rest of the areas and the difference was statistically insignificant (*P > 0.05). This evidence of existence of Francisella tularensis in Nepal is expected to evoke public interest at different levels. Food and commodities contaminated with secretions and excretions of rats and mice are strongly suggested to avoid as a safety measure to rodents born infectious diseases.

Геотермический мониторинг как способ прогноза вулканических извержений и оценки геоэнергетических ресурсов

Geothermal monitoring is an effective tool for predicting volcanic eruptions, as well as for assessing the geothermal energy potential of geothermal areas. Increased magmatic activity, an indicator of which is the penetration of hot volcanic gases through faults, has been observed in recent years on the Elbrus volcano. Since Elbrus is a year-round resort of world importance, in order to control volcanic and seismic activity, forecast and reduce the risks of eruption and earthquakes, it is recommended to drill a observation well on the slope of Elbrus with the installation of an underground fiber-optic system for temperature and pressure monitoring. In combination with microseismic, gravimetric and inclinometric observations, satellite IR imaging and geochemical gas testing, the continuously obtained information on the thermodynamic conditions of the subsoil will provide a reliable complex for the operational forecast of natural geophysical disasters. Utilization of the geothermal energy of the magma chamber in the artificial circulation systems of small GeoPPs, water injection from the surface and obtaining superheated water and steam from producing wells will reduce the risks of eruption and at the same time provide the resort with environmentally friendly thermal and electric power. Technological justification for the construction of a GeoPP will also require exploratory drilling to the area of ​​hot rocks, therefore information on the distribution of temperature and pressure along the wellbore is doubly valuable. In geothermal fields that are under development, to assess the spatial heterogeneity of the filtration characteristics can be a useful method of “thermal interference testing” – as a complement or alternative to hydrodynamic interference testing. It is recommended to conduct such an experiment at the North Mutnovsky geothermal field.

Do natural catastrophes shake microfinance institutions? Using a new measure of MFI risk

Using financial data for more than 1000 microfinance institutions (MFIs) from about 80 developing and emerging market countries, I explore the impact of natural disasters on the financial fragility of these MFIs. For this purpose, I apply a two-stage approach. First, as MFI risk is a multifaceted concept, it is hard to capture by a single indicator. However, previous studies still depend mainly on single and arbitrary chosen measures. In contrast, my improved measure for MFI risk is constructed using factor analysis including 17 different financial risk measures. Factor analysis is a statistical data reduction technique used to explain variability among observed random variables in terms of fewer unobserved random variables called factors. In the second step, I use the factor scores obtained from the factor analysis as my dependent variable in a dynamic panel model. The main findings suggest that the financial risk faced by MFIs increases significantly when a major disaster strikes. In particular, hydro-meteorological disasters have a larger impact on the financial soundness of MFIs than climatic or geophysical disasters. Finally, it turns out that the effect of most natural disasters depends to some extent on the size and scope of the catastrophe, the level of economic development of a country and the kind of clients a particular MFI serves. Based on these results, I conclude that natural disasters are a serious threat to the solvency and liquidity of a MFI. Regulators should in particular monitor and stress test the impact of disasters on risk measures related to capital adequacy and asset quality.

Prioritization of hazard profile for Istanbul using Analytical Hierarchy Process

The compilation of the data for past disasters is vital for taking lessons from the past, investigating their reasons, preventing the loss in the future and for disaster planning-related works. In Turkey, especially in Istanbul which has a historical background of more than 8000 years, the demand for backdated disaster data increases to determine the dangers that the city is faced with and to analyze them. The purpose of our work is to develop a hazard profile identification model for Istanbul by using “Analytic Hierarchy Process.” Therefore, we searched for different types of disasters and hazard classifications in various national and international databases. We scrutinized the kinds of disasters, hazards and hazard characteristics that should be used for a proposed model. By examining “Istanbul’s 2000 Years of Disaster Database” and 100 years of Republic’s statistics prepared for Istanbul, we identified the disaster categories and criteria, ran the Analytic Hierarchy Process and created a hazard profile model for Istanbul. Consequently, we proved that the most important types of disasters that affect Istanbul are geophysical disasters followed by climatological, hydrological, meteorological and technological disasters. The work also shows us that the districts which have a high rate of the population such as Bagcilar, Kucukcekmece and Esenyurt are more vulnerable to these hazards.

The impact of natural disasters on energy consumption: An analysis of renewable and nonrenewable energy demand in the residential and industrial sectors

This study examines the impact of infrastructure‐damaging natural disasters (meteorological and geophysical disasters) on energy consumption differentiating by type of energy: residential versus industrial and nonrenewable versus renewable. We used a novel comprehensive unbalanced data set spanning 50 years (1961–2011) for up to 80 countries, which we group by level of development to reduce heterogeneity within the group. We applied an estimation method that takes into account the dynamics of the economic processes in the panel: the Blundell and Bond GMM estimator. For high‐income economies, which are also technologically the most advanced, we are able to demonstrate a positive impact on renewable energy use 5 years after the occurrence of a geophysical disaster. For low‐income economies, we observe positive effects on industrial energy consumption; for middle‐income countries, on residential energy consumption. © 2017 American Institute of Chemical Engineers Environ Prog, 37: 37–45, 2018

Climate Change Adaptation of the Hospitality Establishments in Southern Leyte, Philippines

Knowing the current status of Southern Leyte as a "Provincial Beauty in the Philippines that's Travel Worthy" and vulnerable to hazards and risks; it is also expected to be on top in championing actions towards climate change adaptation and embracing sustainability. The study focuses on the viability of selected hospitality industry establishments in Southern Leyte towards climate change adaptation. Data collection utilized researcher-made survey questionnaire. Using descriptive-correlational method, managers and owners of 13 Department of Tourism (DOT) identified hospitality industry establishments along the coastlines of Maasin City and Saint Bernard Southern Leyte were surveyed through purposive sampling. The simple percentage, weighted mean, and chi-square were among the statistical tools utilized throughout the study. Most of the provinces in Eastern Visayas were in little risk to geophysical disasters except Southern Leyte and Northern Samar. The establishments were implementing some of the green practices on solid waste management and energy conservation under the international agreements and national laws. Economically and environmentally, majority of the establishments partially complied with the IEMSD program. Regarding the sustainability of the institutions based on the IEMSD, economically and ecologically, the facilities were slightly sustainable. It indicates that majority of the services calls for more actions to be durable and be able to adapt to climate change.