A novel quantitative ecological and microbial risk assessment methodology: theory and applications
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFPE |
Texto Completo: | https://repositorio.ufpe.br/handle/123456789/17633 |
Resumo: | 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. |
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DUARTE, Heitor de Oliveirahttp://lattes.cnpq.br/3317807243271215http://lattes.cnpq.br/7731672359030872DROGUETT, Enrique Andrés López2016-08-05T15:07:47Z2016-08-05T15:07:47Z2016-03-18https://repositorio.ufpe.br/handle/123456789/17633The 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.CNPqO 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.engUniversidade Federal de PernambucoPrograma de Pos Graduacao em Engenharia de ProducaoUFPEBrasilAttribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessAvaliação quantitativa de riscoAnálise de riscos ecológicosAnálise de riscos microbianosModelagem ecológicaAcidentes marítimosQuantitative risk assessmentEcological risk assessmentMicrobial risk assessmentEcological modelingMaritime accidentsA novel quantitative ecological and microbial risk assessment methodology: theory and applicationsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisdoutoradoreponame:Repositório Institucional da UFPEinstname:Universidade Federal de Pernambuco (UFPE)instacron:UFPETHUMBNAIL20160404 Tese final Duarte catalogada formato digital.pdf.jpg20160404 Tese final Duarte catalogada formato digital.pdf.jpgGenerated Thumbnailimage/jpeg1306https://repositorio.ufpe.br/bitstream/123456789/17633/5/20160404%20Tese%20final%20Duarte%20catalogada%20formato%20digital.pdf.jpg5695e1627be817077f5f027967efe808MD55ORIGINAL20160404 Tese final Duarte catalogada formato digital.pdf20160404 Tese final Duarte catalogada formato digital.pdfapplication/pdf4026733https://repositorio.ufpe.br/bitstream/123456789/17633/1/20160404%20Tese%20final%20Duarte%20catalogada%20formato%20digital.pdfd6ac5259ffcea51116ee53e1ba8c164aMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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dc.title.pt_BR.fl_str_mv |
A novel quantitative ecological and microbial risk assessment methodology: theory and applications |
title |
A novel quantitative ecological and microbial risk assessment methodology: theory and applications |
spellingShingle |
A novel quantitative ecological and microbial risk assessment methodology: theory and applications DUARTE, Heitor de Oliveira 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 |
title_short |
A novel quantitative ecological and microbial risk assessment methodology: theory and applications |
title_full |
A novel quantitative ecological and microbial risk assessment methodology: theory and applications |
title_fullStr |
A novel quantitative ecological and microbial risk assessment methodology: theory and applications |
title_full_unstemmed |
A novel quantitative ecological and microbial risk assessment methodology: theory and applications |
title_sort |
A novel quantitative ecological and microbial risk assessment methodology: theory and applications |
author |
DUARTE, Heitor de Oliveira |
author_facet |
DUARTE, Heitor de Oliveira |
author_role |
author |
dc.contributor.authorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/3317807243271215 |
dc.contributor.advisorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/7731672359030872 |
dc.contributor.author.fl_str_mv |
DUARTE, Heitor de Oliveira |
dc.contributor.advisor1.fl_str_mv |
DROGUETT, Enrique Andrés López |
contributor_str_mv |
DROGUETT, Enrique Andrés López |
dc.subject.por.fl_str_mv |
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 |
topic |
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 |
description |
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. |
publishDate |
2016 |
dc.date.accessioned.fl_str_mv |
2016-08-05T15:07:47Z |
dc.date.available.fl_str_mv |
2016-08-05T15:07:47Z |
dc.date.issued.fl_str_mv |
2016-03-18 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufpe.br/handle/123456789/17633 |
url |
https://repositorio.ufpe.br/handle/123456789/17633 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Pernambuco |
dc.publisher.program.fl_str_mv |
Programa de Pos Graduacao em Engenharia de Producao |
dc.publisher.initials.fl_str_mv |
UFPE |
dc.publisher.country.fl_str_mv |
Brasil |
publisher.none.fl_str_mv |
Universidade Federal de Pernambuco |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFPE instname:Universidade Federal de Pernambuco (UFPE) instacron:UFPE |
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Universidade Federal de Pernambuco (UFPE) |
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UFPE |
institution |
UFPE |
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Repositório Institucional da UFPE |
collection |
Repositório Institucional da UFPE |
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