Nowadays more and more new chemicals are used for numerous technologies and ap-plications by diverse chemical, plastic processing and other companies. Are all such companies fit to manage and solve chemical breakdowns, extraordinary events and critical or even emergency situations? Surely a very interesting question. Therefore I have decided for my study to analyse a crisis management system of a plastic processing company located in the City of Liban, region Hradec Kralove. Current status of coordination of the integrated rescue system (hereinafter referred to as the "IZS"). Classification of hazardous chemical substances. Simulating of extraordinary events using the software tool TerEx with respect to diverse chemicals operated by and within the Company. Evaluation of selected chemical substances according to hazards induced. Risk analysis, Analysis of occurrance of extraordinary events like e. g. windstorm, fire or escape of dangerous chemical substance, disconnecting of supply medium (heat, energy, power, water) and their treatment. Methods of actions at threat of bomb attack. Determination whether the IZS coordination including of the documentation elaborated are satisfactory with respect to the plastic processing company as well as with respect to successful mastering of extraordinary and emergency situations. Crisis management of business economics and economic distress.

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No. of bitstreams: 1 VASCONCELLOS_A_DISSERTACAO MAP_2018.pdf: 1858630 bytes, checksum: dc774167c754f93f9f1c1d976d048442 (MD5) Previous issue date: 2018-06-13 / Objetivo: Esta pesquisa pretende investigar as contribuições da Fundação Oswaldo Cruz (Fiocruz), enquanto instituição federal de pesquisa em saúde pública de referência nacional e internacional, para as políticas públicas voltadas à redução do risco de desastres no contexto das mudanças climáticas no horizonte da Agenda 2030 para o Desenvolvimento Sustentável. Metodologia: A pesquisa utilizou o método descritivo analítico com pesquisa e análise documental para a investigação dos marcos referencias das políticas públicas globais e nacionais para os quatro conceitos-chave abordados no referencial teórico: mudança climática, redução do risco de desastres, saúde e clima e desenvolvimento sustentável; e também para as análises da Agenda 2030, como plataforma para as políticas públicas de redução dos riscos de desastres, e da contribuição da Fiocruz para essas políticas. Adicionalmente, foram utilizadas as entrevistas semiestruturadas para a coleta de dados de dois dispositivos da Fiocruz, Observatório de Clima e Saúde e CEPEDES, selecionados como os de maior contribuição institucional à temática dos desastres no contexto das mudanças climáticas. Resultados: Foi constatado que a Fiocruz contribui para as políticas públicas de redução do risco de desastres, nacionais e locais, e que a redução do risco de desastres está inserida na Agenda 2030 e que sua temática é transversal à cinco Objetivos para o Desenvolvimento Sustentável (ODS). Além disso, concluiu que a Estratégia Fiocruz para Agenda 2030 ainda é muito incipiente e que deve incluir em suas ações as contribuições do Observatório de Clima e Saúde e do CEPEDES e, com isso, trabalhar a saúde na Agenda para além do ODS 3. Limitações: A incerteza dos indicadores dos ODS trabalhados na Agenda 2030 brasileira serem os definitivos, por esta ainda estar em processo de interiorização e ter aprofundado a análise da contribuição da Fiocruz para as políticas de redução do risco de desastres apenas para dois dispositivos institucionais. Aplicabilidade do trabalho: A pesquisa estruturou as metas e indicadores da Agenda 2030 relacionados à redução do risco de desastres e identificou a necessidade de melhoria de alguns indicadores e mesmo a criação de novos mais efetivos para a apropriação da Agenda 2030 para as políticas públicas para redução do risco de desastres. Contribuições para a sociedade: A pesquisa confirmou a importância do envolvimento do setor saúde no enfrentamento da redução dos riscos de desastres e apresentou seus principais impactos sobre a saúde humana. Originalidade: Relacionar os impactos dos desastres e da mudança climática sobre a saúde com os Objetivos do Desenvolvimento Sustentável (ODS) da Agenda 2030 brasileira. / Purpose: This research intends to investigate the contributions of the Oswaldo Cruz Foundation (Fiocruz), as a federal public health research institution of national and international reference, for public policies aimed at reducing the risk of disasters in the context of climate change under Agenda 2030 for Sustainable Development. Methodology: The research used the analytical descriptive method with research and documentary analysis to investigate the benchmarks of global and national public policies for the four key concepts addressed in the theoretical framework: climate change, disaster risk reduction, health and climate and sustainable development; and also for the analysis of Agenda 2030, as a platform for public policies to reduce disaster risks, and Fiocruz's contribution to these policies. In addition, semi-structured interviews were used to collect data from two devices from Fiocruz, Climate and Health Observatory and CEPEDES, selected as the ones with the greatest institutional contribution to the issue of disasters in the context of climate change. Findings: It has been shown that Fiocruz contributes to public policies for national and local disaster risk reduction and that disaster risk reduction is part of Agenda 2030 and that this theme is transversal to the five Sustainable Development Objectives (ODS). In addition, it concluded that the Fiocruz Strategy for Agenda 2030 is still very incipient and that it should include in its actions the contributions of the Climate and Health Observatory and CEPEDES and, should work on health in the Agenda beyond ODS 3. Research limitations: The uncertainty of the ODS indicators worked on in the Brazilian Agenda 2030 are the definitive ones, as it is still in the process of internalization and has deepened the analysis of the contribution of Fiocruz to the policies of disaster risk reduction only for two institutional devices. Practical implications: The research structured the goals and indicators of Agenda 2030 related to disaster risk reduction and identified the need for improvement of some indicators and even the creation of new ones more effective for the appropriation of Agenda 2030 for public policies for disaster risk reduction. Social implications: The research confirmed the importance of the involvement of the health sector in addressing disaster risk reduction and presented its main impacts on human health. Originality: Relate the impacts of disasters and climate change on health with the Sustainable Development Objectives (ODS) of the Brazilian Agenda 2030.

Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第14224号 / 工博第3008号 / 新制||工||1446(附属図書館) / 26542 / UT51-2008-Q693 / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 岡田 憲夫, 教授 小林 潔司, 教授 多々納 裕一 / 学位規則第4条第1項該当

MURP / Department of Urban and Regional Planning / Disaster is posing serious threats to both human lives, infrastructure and the environment at large. Greater Tzaneen Municipality (GTM) is one of the many municipalities that suffer from flood related disasters. Lack of integration between Disaster Risk Reduction (DRR) and spatial planning has compounded the disaster risk situation in the municipality. This study sought to investigate the prospects of integrating spatial planning with disaster risk reduction in flood prone areas of GTM. The study is guided by three research objectives. First, the study sought to analyse spatial planning attributes that can be valorised for DRR in flood prone areas; Secondly, it sought to analyse spatial planning factors that define vulnerability attributes of households occupying flood prone areas. Finally, the study sought to perform a cluster analytical creation of a typology of households whose resilience to flooding could be enhanced through spatial planning. Twenty-five flood prone areas were analysed on the basis of four main flood vulnerability attributes. In order to identify such vulnerability attributes, the study borrowed critical insights from literatures on flood vulnerability, spatial planning and DRR. Such a critical review of literature was complemented by the use of pattern matching as a qualitative research instrument. Quantitative that was gathered using a structured observation checklist. Quantitative data generated was first subjected to various statistical tests that included Normality and Reliability Tests. Common measures of Normality test used included measures of skewness, kurtosis and the use of Normal Q-Q plots. To assess flood vulnerability, Hierarchical Cluster Analysis (HCA) was used. HCA was used to identify clusters of flood prone areas which had common characteristics in terms of the four main study constructs proposed by the study which included the physical/engineering, socio-economic, ecological/natural and political or governance conditions characterizing each area. HCA was then used to identify main clusters exhibiting similar characteristics and the associated level of vulnerability of such of communities occupying such clusters. Study results revealed 2 main clusters of flood prone areas whose differences lay in interactions that existed between the physical/engineering, socio-economic, ecological/natural and political or governance conditions characterizing each area. Such clusters depicted 2 levels of vulnerability that is high, and moderate. A number of opportunities and constraints were generated using the SWOT matrix strategy with the main results showing that spatial planning elements characterizing flood prone areas could be transformed into critical urban risk management options for DRR. This is because a spatial planning elements were found to have a direct influences on critical factors of DRR such as location of activities. The study concluded by recommending a number of spatial planning strategies that can be vaporized for DRR. Such strategies are systematically aligned to the unique vulnerability context conditions associated with the two flood vulnerability solution arrived at using HCA. / NRF

While early relocation is not makeable, disaster risk reduction seems to be the most effective tool to decrease the impact of a disaster. This case study focuses on three UNDRR frameworks as they appear to be the greatest instance of international documents referring to disaster risk reduction (DRR). Especially, this research examines the representation of women within these frameworks and how their portrayal in DRR has changed over the last two decades. To do so, a critical discourse analysis of the three UNDRR frameworks is conducted. This study benefits from a social vulnerability approach and further engages with the Feminist Political Ecology theory. The analysis finds that even though women are increasingly represented in the frameworks, their roles as active participants remain negligible. Their knowledge and interest are still not recognised as valuable in DRR. Rather, women seem to be employed as tools to include more gender-sensitive programmes. This study recommends a greater and more complex emphasis on women in future DRR policies.

PhD (Geography) / Department of Geography and Geo-Information Sciences / Malaria is a climate-change concatenated biological hazard that may, like any other natural hazard, can lead to a disaster if there is a failure in handling emergencies or risks. A holistic solution for malaria mitigation can be provided when indigenous knowledge is complemented with scientific knowledge. Malaria remains a challenge in South Africa and Limpopo province is the highest burdened malaria-endemic region. Specifically, Vhembe District is the highest burdened followed by Mopani District (Raman et al., 2016). This research sought to mitigate malaria transmissions in Mopani District through the integration of indigenous and scientific knowledge. The study was carried out in Mopani District of South Africa and 4 municipalities were involved. These are Ba-Phalaborwa, Greater Tzaneen, Greater Letaba, and Maruleng. A pragmatism philosophy was adopted hence the study took a mixed approach (sequential multiphase design). Data was collected from 381 selected participants through in-depth interviews, a survey and a focus group discussion. Participants for the in-depth interviews were obtained through snowballing and selected randomly for the survey, while for the focus group discussion purposive sampling was used. The study applied constructivist grounded theory to analyze qualitative data and to generate theory. Statistical Package for Social Sciences version 23.0 was used for quantitative data. Based on empirical findings, it was concluded that temperature and rainfall among other various factors exacerbate malaria transmission in the study area. Results of the study also show that people in Mopani District predict the malaria season onset by forecasting rainfall using various indigenous knowledge based indicators. The rainfall indicators mentioned by participants in the study were used in the developed early warning system. An Early warning system is an essential tool that builds the capacities of communities so that they can reduce their vulnerability to hazards or disasters. In the design of the system, Apache Cordova, JDK 1.8, Node JS, and XAMPP software were used. The study recommends malaria management and control key stakeholders to adopt the developed early warning system as a further mitigation strategy to the problem of malaria transmission in Mopani District. / NRF

[pt] Esta dissertação apresenta uma abordagem baseada em dados para o problema de predição de desastres recorrentes em países em desenvolvimento. Métodos de aprendizado de máquina supervisionado são usados para treinar classificadores que visam prever se uma família seria afetada por ameaças climáticas recorrentes (um classificador é treinado para cada perigo natural). A abordagem desenvolvida é válida para perigos naturais recorrentes que afetam um país e permite que os gerentes de risco de desastres direcionem suas operações com mais conhecimento. Além disso, a avaliação preditiva permite que os gerentes entendam os impulsionadores dessas previsões, levando à formulação proativa de políticas e planejamento de operações para mitigar riscos e preparar comunidades para desastres recorrentes. A metodologia proposta foi aplicada ao estudo de caso do Peru, onde foram treinados classificadores para ondas de frio, inundações e deslizamentos de terra. No caso das ondas de frio, o classificador tem 73,82% de precisão. A pesquisa descobriu que famílias pobres em áreas rurais são vulneráveis a desastres relacionados a ondas de frio e precisam de intervenção humanitária proativa. Famílias vulneráveis têm infraestrutura urbana precária, incluindo trilhas, caminhos, postes de iluminação e redes de água e drenagem. O papel do seguro saúde, estado de saúde e educação é menor. Domicílios com membros doentes levam a maiores probabilidades de serem afetados por ondas de frio. Maior realização educacional do chefe da família está associada a uma menor probabilidade de ser afetado por ondas de frio. No caso das inundações, o classificador tem 82.57% de precisão. Certas condições urbanas podem tornar as famílias rurais mais suscetíveis a inundações, como acesso à água potável, postes de iluminação e redes de drenagem. Possuir um computador ou laptop diminui a probabilidade de ser afetado por inundações, enquanto possuir uma bicicleta e ser chefiado por indivíduos casados aumenta. Inundações são mais comuns em assentamentos urbanos menos desenvolvidos do que em famílias rurais isoladas. No caso dos deslizamentos de terra, o classificador tem 88.85% de precisão, e é segue uma lógica diferente do das inundações. A importância na previsão é mais uniformemente distribuída entre as características consideradas no aprendizado do classificador. Assim, o impacto de um recurso individual na previsão é pequeno. A riqueza a longo prazo parece ser mais crítica: a probabilidade de ser afetado por um deslizamento é menor para famílias com certos aparelhos e materiais domésticos de construção. Comunidades rurais são mais afetadas por deslizamentos, especialmente aquelas localizadas em altitudes mais elevadas e maiores distâncias das cidades e mercados. O impacto marginal médio da altitude é não linear. Os classificadores fornecem um método inteligente baseado em dados que economiza recursos garantindo precisão. Além disso, a pesquisa fornece diretrizes para abordar a eficiência na distribuição da ajuda, como formulações de localização da instalação e roteamento de veículos. Os resultados da pesquisa têm várias implicações gerenciais, então os autores convocam à ação gestores de risco de desastres e outros interessados relevantes. Desastres recorrentes desafiam toda a humanidade. / [en] This dissertation presents a data-driven approach to the problem of predicting recurrent disasters in developing countries. Supervised machine learning methods are used to train classifiers that aim to predict whether a household would be affected by recurrent climate threats (one classifier is trained for each natural hazard). The approach developed is valid for recurrent natural hazards affecting a country and allows disaster risk managers to target their operations with more knowledge. In addition, predictive assessment allows managers to understand the drivers of these predictions, leading to proactive policy formulation and operations planning to mitigate risks and prepare communities for recurring disasters. The proposed methodology was applied to the case study of Peru, where classifiers were trained for cold waves, floods, and landslides. In the case of cold waves, the classifier was 73.82% accurate. The research found that low-income families in rural areas are vulnerable to cold wave related disasters and need proactive humanitarian intervention. Vulnerable families have poor urban infrastructure, including footpaths, roads, lampposts, and water and drainage networks. The role of health insurance, health status, and education is minor. Households with sick members are more likely to be affected by cold waves. Higher educational attainment of the head of the household is associated with a lower probability of being affected by cold snaps.In the case of flooding, the classifier is 82.57% accurate. Certain urban conditions, such as access to drinking water, lampposts, and drainage networks, can make rural households more susceptible to flooding. Owning a computer or laptop decreases the likelihood of being affected by flooding while owning a bicycle and being headed by married individuals increases it. Flooding is more common in less developed urban settlements than isolated rural families.In the case of landslides, the classifier is 88.85% accurate and follows a different logic than that of floods. The importance of the prediction is more evenly distributed among the features considered when learning the classifier. Thus, the impact of an individual feature on the prediction is small. Long-term wealth is more critical: the probability of being affected by a landslide is lower for families with specific appliances and household building materials. Rural communities are more affected by landslides, especially those located at higher altitudes and greater distances from cities and markets. The average marginal impact of altitude is non-linear.The classifiers provide an intelligent data-driven method that saves resources by ensuring accuracy. In addition, the research provides guidelines for addressing efficiency in aid distribution, such as facility location formulations and vehicle routing.The research results have several managerial implications, so the authors call for action from disaster risk managers and other relevant stakeholders. Recurrent disasters challenge all of humanity.