A novel quantitative ecological and microbial risk assessment methodology: theory and applications

• Ano de defesa: 2016
• Autor(a) principal: DUARTE, Heitor de Oliveira
• Orientador(a): DROGUETT, Enrique Andrés López
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Pernambuco
• Programa de Pós-Graduação: Programa de Pos Graduacao em Engenharia de Producao
• País: Brasil
• Palavras-chave em Português: Avaliação quantitativa de risco; Análise de riscos ecológicos; Análise de riscos microbianos; Modelagem ecológica; Acidentes marítimos; Quantitative risk assessment; Ecological risk assessment; Microbial risk assessment; Ecological modeling; Maritime accidents
• Link de acesso: https://repositorio.ufpe.br/handle/123456789/17633

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.