<p>Despite the fact that natural disasters have always existed, the number and intensity of natural disasters have increased. Progress has been made in preparing for natural disasters, but the consequences are still severe. This study takes on the task of identifying the features that make schools more vulnerable to natural disasters. Using a simple OLS (N=387). The study analyses the effect of natural disasters on school closures. Using six different disasters as our study area, we capture different demographic and socioeconomic features of a school impacted by natural disaster at different geographic levels: the individual school, the school district, and the Public Use Microdata Area (PUMA). The regression results show that factors such as increased disaster severity, higher levels of poverty, and larger numbers of at-risk individuals within a puma have significant positive associations with an increase in the number of days a school closes. At a practical level, understanding the impact of a disaster on school closure can depend on multiple factors and is important for local, state and federal governments. Policies must be implemented by local communities throughout the nation to increase community resilience. By understanding vulnerability factors adequately, their impact on school closure can be mitigated by increasing appropriate preparedness, efficient recovery strategies, evacuation strategies, and interpersonal awareness. Climate change and its effects, present and future, is a major concern for the whole world. Our efforts to understand and seek solutions to prevent and limit the damages rendered by natural disasters are critical to an effort to reduce the impacts of climate change in the U.S. and other affected countries. </p>

In February 2022 the Intergovernmental panel on climate change (IPCC) published a report indicating that wildfires may become more frequent as climate changes keeps progressing. The last few years we have witnessed devastating consequences due to wildfires around the world. In 2014 Sweden was affected by one of the biggest wildfires in modern history when a total of 15 000 hectares burned down. This study investigates how municipalities in Sweden work with crisis management against wildfires. Data was collected in a questionnaire sent out to municipalities as a web-survey. The questionnaire included questions about the municipality´s ability to handle a higher frequency of wildfires and if their risk and vulnerability analysis includes wildfires. The overall response rate was 52 % (151/290) and more than half of the municipalities answered that wildfires are included in their risk and vulnerability analysis, and they think they can manage a higher frequency of wildfires. It was not possible to identify a difference in crisis management between small (&lt;16 000) and large (&gt;16 000) municipalities, and municipalities located in the southern and northern parts of Sweden, respectively. What can be seen as worrying is that there are municipalities that do not have the capacity to handle an increase in wildfires. Economics are named one of the main reasons municipalities do not prioritize these issues. Due to the development with rising temperatures and more frequent wildfires in the world, forest fires will probably be a topical research area onwards.

The damage assessment caused by floods, earthquakes, hurricanes among others phenomenons in the world are analyzed with methodologies such as "Vulnerability curves". In Peru, disasters caused by hyperconcentrated flows are alarming due to a climatic variability such as the "El Nio Costero"phenomenon. Therefore, this research has developed vulnerability curves for 1 and 2-story confined masonry buildings in Urb. San Idelfonso, Ica - Peru; linking the variables: flow depth, associated with the event produced by heavy rains at the top of the "Quebrada Cansas"caused by the "El Nio Costero"phenomenon in 2017, and the percentage of the damage based on the methodology of the United States Army Corps of Engineers (USACE), whose formula is the repair value and total building value. The monetary amounts and items of the buildings are obtained from the RM 415-2017-VIVIENDA of the Ministry of Housing, Construction and Sanitation of Peru. The process consisted of hydrological modeling in HEC-HMS, hydraulic modeling in FLO-2D, damage percentage estimate and vulnerability curves production. Finally, the vulnerability curves for hyperconcentrated flows were contrasted with similar studies regarding curves for flooding and debris flow. The results of the investigation showed that the "El Nio Costero"phenomenon in 2017 had an economic impact of at least 1.3 million soles in Urb. San Idelfonso. In addition, at least 24 buildings had a complete damage and 21 buildings an extensive damage.

Chapter 1 – This paper analyzes the effects of extreme temperature on manufacturing output using a dataset covering the universe of manufacturing establishments in Canada from 2004 to 2012. Extreme temperature can affect manufacturing activity directly through its impact on labour productivity and indirectly through a change in demand for products. Using a panel fixed effects method, our results suggest a non linear relationship between outdoor extreme temperature and manufacturing output. Each day where outdoor mean temperatures are below -18◦C or above 24◦C reduces annual manufacturing output by 0.18% and 0.11%, respectively, relative to a day with mean temperature between 12 to 18◦C. In a typical year, extreme temperatures, as measured by the number of days below -18◦C or above 24◦C, reduce annual manufacturing output by 2.2%, with extreme hot temperatures contributing the most to this impact. Given the predicted change in climate for the mid and end of century, we predict annual manufacturing output losses due to extreme temperature to range between 2.8 to 3.7% in mid-century and 3.7 to 7.2% in end of century. Chapter 2 – In May 2011, the municipality of Slave Lake, Alberta was hit by a devastating wildfire; the second costliest natural disaster in Canada at the time. In this study, we use longitudinal income tax data from 2004-2018, to analyze the short, medium, and long-term effect of this wildfire on incomes, and related outcomes. This paper contributes to the very limited literature examining the economic effects of natural disasters on individuals. It also contributes to the discussion about the cost of natural disasters and highlights an important cost often excluded in published reports of natural disasters. Our results suggest that this event led to a decrease in total income mainly explained by a drop in employment income. Evidence of an intensive margin effect, whereby individuals are more likely to report lower earnings conditional on paid employment, is found. We also find evidence for an extensive margin effect, in which the employment rate falls for individuals over 55 years old. Chapter 3 – How do firms in the manufacturing sector respond to voluntary energy conservation program? Using data covering the universe of manufacturing firms in Canada over the period 2004 to 2012, we estimate the effectiveness of the Canadian Industry Program for Energy Conservation, the flagship federal government energy conservation program targeted at large industrial firms. We use a difference-in-difference approach, coupled with coarsened exact matching, to estimate the effect of this program on firms energy intensity, output, as well as productivity. Our results suggest that the program does not significantly affect the energy intensity of participating firms compared to non-participating firms. We also find no evidence that participant firms perform differently from non-participant firms in term of total productivity or total production. Our study results add to the evidence that voluntary programs play a limited role in transforming energy and environmental outcomes.

Research has shown that unless global greenhouse gas emissions are reduced by 45% by 2030 the global warming could rise with 1,5 °C and increase the risk of floods. This is due to an intensification of extreme weather events and rising sea levels. Thus, the purpose of this study was to examine the flood preparedness in Swedish municipalities to get a better understanding how flood management was performed in practice and what obstacles municipalities may face. In addition to this, the study also aimed to see if preparedness differed between municipalities based on geographical location, flood risk classification or population. The study was conducted as a questionnaire that was sent out to all 290 municipalities in Sweden. The result indicated that a majority (89%) of the municipalities that participated (142) took floods into account in their risk and vulnerability analysis. Actions against floods were mainly focused on preventive and technical methods as well as increased cooperation. This study could not prove any differences in the flood preparedness based on geographical location, flood risk classification or population. Factors that posed limitations in municipalities abilities to effectively manage floods were lack of resources, restrictions in allocation of responsibilities or property rights. Areas of improvement that were noticed were that actions against floods could focus more on the municipalities ability to recover and learn from a flood event, as well as improvements in bridging the gap between the private and public sector to obtain a more cohesive preparedness capacity.

Flood risk management in the U.S. has contributed to overdevelopment in at-risk areas, increases in flood losses over time, significant deficits in federal emergency programs, and inequitable outcomes to households and communities. Addressing these issues in a cost-effective and socially equitable manner relies on the ability of policy analysts to identify and understand complex interactions that characterize coupled natural-human systems, and tools for accurate estimates of the risks that arise from these interactions. This dissertation addresses this need by developing and investigating a flood risk analysis system that integrates data on property locations, assessments and transactions, high resolution flood hazard models, and flood risk policy and impacts across the coterminous United States. We focus on the degree to which markets accurately value their exposure to flooding and its impacts, and the accuracy of procedures and tools to estimate flood losses. In the first chapter, we identify heterogeneous valuation of storm risk in the Florida Keys that depends on the presence of structural defense and proximity to damaged homes after Hurricane Irma. This result suggests that stranded assets, properties with increasing vulnerability to storms but unable to rebuild structures and recover wealth, and overvalued assets at risk, which raise disaster costs, can occur simultaneously. This runs counter to the common framing of competing drivers of observed market valuation. In the second, we show that conventional methods employed in flood loss assessments to achieve large spatial scales introduce large aggregation bias by sacrificing spatial resolution in inputs. This investigation adds important context to published risk assessments and highlights opportunities to improve flood loss estimation uncertainty quantification which can support more cost effective and equitable management. In the final chapter, we conduct a nationwide study to contrast the predictive accuracy of predominantly used U.S. agency flood damage prediction models and empirical alternatives using data on 846 K observed flood losses to single-family homes from 446 flood events. We find that U.S. agency models mischaracterize the relationships of losses at the lowest low and high inundation depths, for high-valued structures, and structures with basements. Evaluated alternatives improve mean accuracy on these dimensions. In extrapolation to 72.4 M single-family homes in the U.S., these differences translate into markedly different predictions of U.S.-wide flood damages to single-family homes. The results from this dissertation provide an improved empirical foundation for flood risk management that relies on the valuation and estimation of flood risk from county to continental scales.

This study was a year-long longitudinal qualitative research project using the case study of Mayfield, KY after the catastrophic tornado event that impacted their community on December 10, 2021. Oral histories were collected from 18 participants who lived in or were closely connected to Mayfield at the six month and 1.5 year marks after the disaster. Later, after the oral histories were archived and made available to the public, the transcripts were used to extract the crisis narratives from the oral histories and the data was thematically analyzed using the existing theory and theoretical framework of Narratives of Crisis: Telling Stories of Ruin and Renewal by Seeger and Sellnow (2016). The themes were analyzed to better understand how crisis narratives change over time and to determine if there were differences between the leadership of Mayfield and their stakeholders, the public. A major finding in this area was the intertwining of one of more themes within the same passage of narrative, including the intertwining of traditionally competing themes. This extends the theory of Narratives of Crisis. The Discourse of Renewal by Ulmer and Sellnow (2002) was also used to analyze how narratives may differ between those in the community who are considered leaders, and those who represent a general cross-section of the community. The major finding in this analysis was the lack of up-to-date information between leaders and the public. By not creating a bridge of communication, many of the successful steps taken by leaders may not have reached their intended audience. One of the components of the Discourse of Renewal, organizational learning, was specifically used to find lessons learned discussed by community leaders in Mayfield, and to explore how these learned lessons can be applied for practitioners to better understand disaster recovery and renewal in the future.

Natural disasters exert a profound impact on the world population. In 2012, natural disasters affected 106 million people, forcing over 31.7 million people to leave their homes. Climate change has intensified natural disasters, resulting in more catastrophic events and making extreme weather more difficult to predict. Understanding and predicting human movements plays a critical role in disaster evacuation, response and relief. Researchers have developed different methodologies and applied several models to study human mobility patterns, including random walks, Lévy flight, and Brownian walks. However, the extent to which these models may apply to perturbed human mobility patterns during disasters and the associated implications for improving disaster evacuation, response and relief efforts is lacking. My PhD research aims to address the limitation in human mobility research and gain a ground truth understanding of human mobility patterns under the influence of natural disasters. The research contains three interdependent projects. In the first project, I developed a novel data collecting system. The system can be used to collect large scale data of human mobility from large online social networking platforms. By analyzing both the general characteristics of the collected data and conducting a case study in NYC, I confirmed that the data collecting system is a viable venue to collect empirical data for human mobility research. My second project examined human mobility patterns in NYC under the influence of Hurricane Sandy. Using the data collecting system developed in the first project, I collected 12 days of human mobility data from NYC. The data set contains movements during and several days after the strike of Hurricane Sandy. The results showed that human mobility was strongly perturbed by Hurricane Sandy, but meanwhile inherent resilience was observed in human movements. In the third project, I extended my research to fifteen additional natural disasters from five categories. Using over 3.5 million data entries of human movement, I found that while human mobility still followed the Lévy flight model during these disaster events, extremely powerful natural disasters could break the correlation between human mobility in steady states and perturbation states and thus destroy the inherent resilience in human mobility. The overall findings have significant implications in improving understanding and predicting human mobility under the influence of natural disasters and extreme events. / Ph. D.

Catastrophes are usually seen as a threat to a country’s stability and progress. Some countries are regarded as prepared to face them and ready to deal with the consequences, but still, a disaster is always presented at the very least as an inconvenience. Contrary to this line of thinking, this dissertation shows that catastrophes can present an opportunity for state-building. Catastrophes, and the profound sense of insecurity they cause, force institutions to demonstrate their adeptness, or change. Specifically, catastrophes challenge state power because they test its basic role as protector from physical harm. Consequently, when disaster happens the state is put to the test. States that arise triumphant from this challenge may use the opportunity to increase its strength and develop new capacities.

Thesis (Ph.D.)--Mississippi State University. Department of Counseling and Educational Psychology. / Title from title screen. Includes bibliographical references.