A risk assessment model (MAcRisk) have been developed to forecast the probability and the risk of maritime accidents on Bosphorus. Accident archives of Undersecretariat Maritime Affairs Search and Rescue Department, weather conditions data of Turkish State Meteorological Service and bathymetry and current maps of Office of Navigation, Hydrography and Oceanography have been used to prepare the model input and to forecast the accident probability. Accident data has been compiled according to stated sub-regions on Bosphorus and event type of accidents such as collision, grounding, capsizing, fire and other. All data that could be obtained are used to clarify the relationship on accident reasons. An artificial neural network model has been developed to forecast the maritime accidents in Bosphorus.

This thesis focuses on the significance of distributive space for understanding capitalist forms of spatio-temporality. It argues that the distributive phase of commodity mobilities has remained a relatively under-represented aspect of social theory, especially in the context of cultural and social geography. The extant work that has focused on distribution tends to be confined to the areas of economic and transport geography. The thesis aims to address the importance of this space for understanding the formations of late capitalist modernity, particularly its role as a specific, but networked space between production and consumption. Significantly the work addresses the 'construction' of this space by focus sing on the substantive case study of containerisation. In doing so it engages with global commodity mobilities in the form of intermodal shipping containers, and their attendant logistical infrastructure. The research critically considers the spatial and temporal apparatuses that have been developed to organise and order the mobilities of the containers; including the design and development of the object itself, alongside a range of logistics and supply chain management strategies. In theoretical terms an important influence on the research has been Michel Serres' work on the interlacing of order and disorder. Given this, a simultaneous focus of the research deals with the immanent presence of disorder in these systemic environments; thus reflecting an intellectual engagement with theoretical work in the areas of turbulence, complexity theory, assemblage theory and Serres' work on the parasite. Substantively this aspect of the research has been determined by considering the place of the accident within networks and systems, alongside the 'tactical-logistics' of smuggling practices. 3

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-08-05T15:07:47Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) 20160404 Tese final Duarte catalogada formato digital.pdf: 4026733 bytes, checksum: d6ac5259ffcea51116ee53e1ba8c164a (MD5) / Made available in DSpace on 2016-08-05T15:07:47Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) 20160404 Tese final Duarte catalogada formato digital.pdf: 4026733 bytes, checksum: d6ac5259ffcea51116ee53e1ba8c164a (MD5) Previous issue date: 2016-03-18 / CNPq / The environment is a complex system where human, ecological environment (e.g., plants, animals, microbes), materials (eg, pollutants, medical), and meteorological/oceanographic conditions interact. The human impact has potential to cause significant damage to the ecological environment (e.g., potential oil spills on the coast cause risk to coastal ecosystems, tuna industrial fishing cause risk to sharks that are bycaught). Similarly, the human impact may turn against the human itself by favoring the growth of populations of unwanted species (e.g., poor sanitation favors the growth of microbial populations that cause risk of an excessive proportion of sick humans). Therefore, it has been demanded an efficient method of quantifying the risks in systems where plant, animals or microbes populations are involved in order to give support to risk management in environmental issues, fisheries management and public health. First, this paper proposes a methodology capable of quantifying ecological risks (i.e., likelihood of adverse effects on the ecosystem, in the long term, due to exposure to stressors such as chemical, fishing, etc.) or microbial risks (i.e., likelihood of adverse effects in humans, in the long term, due to exposure to microbial pathogens). It uses population modeling to simulate future changes in populations of ecologically important species (e.g., fish, corals, sharks), or undesirable (e.g., parasites), under conditional scenarios simulating the influence humans impacting and/or managing the risks. The risk is calculated in terms of probability of extinction or decline, explosion or growth of these populations over time. Second, the methodology is applied to four case studies in Brazil. Each of them have their specific conclusions, as follows. (1) Ecological Risk Assessment caused by potential maritime accidents in the transportation of oil to the port of Suape. Conclusion: low but significant ecological risk. (2) Ecological Risk Assessment caused by potential maritime accidents in the passage of oil tankers nearby Fernando de Noronha. Conclusion: negligible ecological risk, although a more detailed analysis is required due to limited data. (3) Microbial Risk Assessment to Porto de Galinhas community inherent to sanitation and medical treatment program. Conclusion: high microbial risk, the current sanitation level is not enough to contain the spread of schistosomiasis disease, and periodic treatment of patients is not efficient to reduce risks significantly. (4) Ecological Risk Assessment of tuna industrial fishing in Brazilian waters. Conclusion: industrial tuna fishing does not cause significant risks to the population of Mako sharks in the South Atlantic Ocean. In each case study, several conditional scenarios were simulated for the next 100 years, including adverse scenarios and scenarios with risk control measures. Thus, it was possible to quantify the added risk caused by each adverse condition as well as the reduced risk caused by each control measure. In this way, the manager has objective information to prioritize scenarios and evaluate the cost-effectiveness of control measures. The general conclusion of this work is that the proposed methodology has proven to be practicable, useful and efficient. / O meio-ambiente é um sistema complexo onde interagem humanos, meio ecológico (e.g., plantas, animais, micróbios), materiais (e.g., poluentes, medicinais) e condições meteorológicas/oceanográficas. O impacto humano tem potencial para causar danos significativos ao meio ecológico (e.g., potenciais vazamentos de petróleo na costa causam risco ao ecossistema costeiro, pesca industrial de atum causa risco aos tubarões que são pescados por acidente). Similarmente, o impacto humano pode se voltar contra o próprio humano ao favorecer o crescimento de populações de espécies indesejáveis (e.g., saneamento básico precário favorece o crescimento de populações de micróbios que causam risco de haver uma excessiva parcela de humanos doentes). Portanto, tem sido demandado um método eficiente de quantificar os riscos inerentes a sistemas onde populações de plantas, animais ou micróbios estejam envolvidas, de forma a dar suporte para o gerenciamento dos riscos em problemas de gestão ambiental, gestão pesqueira e saúde pública. Em primeiro lugar, este trabalho propõe uma metodologia capaz de quantificar riscos ecológicos (i.e., probabilidade de ocorrência de efeitos adversos no ecossistema, no longo prazo, devido à exposição a estressores como químicos, pesca, entre outros) ou microbianos (i.e., probabilidade de ocorrência de efeitos adversos em humanos, no longo prazo, devido à exposição a patógenos microbianos). Utilizase a modelagem populacional para simular futuras mudanças nas populações de espécies ecologicamente importantes (e.g., peixes, corais), ou indesejáveis (e.g., parasitas), quando condicionadas a cenários que simulam a influência do humano causando impacto e/ou gerindo os riscos. O risco é calculado em termos de probabilidade de extinção ou declínio, explosão ou crescimento, dessas populações ao longo do tempo. Em segundo lugar, aplica-se a metodologia para avaliar o risco inerente a quatro estudos de caso no Brasil. Cada um deles tem sua conclusão específica, como segue. (1) Análise de Risco Ecológico causado por potenciais acidentes marítimos no transporte de petróleo para o porto de Suape. Conclusão: baixo risco ecológico, porém significativo. (2) Análise de Risco Ecológico causado por potenciais acidentes marítimos na passagem de navios petroleiros ao largo de Fernando de Noronha. Conclusão: risco ecológico negligenciável, mas uma análise mais detalhada é necessária devido à escassez de dados. (3) Análise de Risco Microbiano à comunidade de Porto de Galinhas inerentes ao sistema de saneamento básico e programa de tratamento medicinal. Conclusão: alto risco microbiano, o nível de saneamento básico atual não é suficiente para conter a proliferação da doença esquistossomose, e o tratamento periódico de doentes não é eficiente para reduzir os riscos significativamente. (4) Análise de Risco Ecológico causado pela pesca industrial de atum em águas brasileiras. Conclusão: a pesca industrial de atuns não causa riscos significativos à população de tubarões Mako no oceano Atlântico Sul. Em cada estudo de caso, foram simulados diversos cenários condicionais para os próximos 100 anos, incluindo cenários adversos e cenários com medidas de controle dos riscos. Assim, foi possível quantificar a adição do risco causada por cada cenário adverso e a redução do risco causada por cada medida de controle. Desta forma, o gestor tem informação objetiva para priorizar cenários e avaliar o custo-benefício das medidas de controle. A principal conclusão deste trabalho é que a metodologia proposta provou-se ser praticável, útil e eficiente.