A carregar...
Publicação
Integração de riscos climáticos futuros em análise locacional de ativos: aplicação em usinas fotovoltaicas no Ceará, Brasil
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 6.86 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
As mudanças climáticas ampliam os riscos físicos de empreendimentos de grande porte, enquanto o licenciamento ambiental brasileiro passa a incorporar exigências climáticas. É neste contexto que esta dissertação desenvolve uma metodologia integrada de apoio à decisão para a identificação de áreas prioritárias à instalação de empreendimentos de grande porte, combinando análise de adequabilidade locacional multicritério com avaliação prospectiva de riscos físicos associados a perigos climáticos, e traduzida em perdas econômicas esperadas. A metodologia é aplicada a um estudo de caso no Ceará para identificar áreas prioritárias para usinas fotovoltaicas centralizadas. A análise locacional integrou 21 variáveis ambientais, sociais, logísticas e técnicas numa grade de 300 m, utilizando funções de pertinência fuzzy agregadas pela Média Geométrica com ponderação IQRBOW. As áreas no percentil 99 do Índice de Adequabilidade e com mais de 450 hectares foram identificadas como Áreas Candidatas (AOIs), totalizando 16 polígonos submetidos à análise de risco climático. A validade do modelo foi evidenciada pela convergência com projetos reais: 65% das usinas fotovoltaicas em operação ou planejamento no Ceará estão em regiões de adequabilidade Alta ou Muito Alta. A avaliação de risco climático para as 16 AOIs estruturou-se na abordagem perigo-exposiçãovulnerabilidade do IPCC, em dois cenários de emissões e três horizontes temporais. Para o estresse térmico, variáveis do dataset CLIMBra foram transformadas em temperatura operacional do módulo, convertidas em perda de eficiência e integradas em perdas econômicas pela plataforma CLIMADA. Para a inundação, séries anuais do modelo CaMa-Flood foram traduzidas em dano físico por curva profundidade-dano e em perda econômica pelo custo de reposição do ativo. Para o incêndio, o modelo de Risco de Fogo do INPE foi adaptado para projeções até 2070, com dano estrutural baseado em registros históricos de focos na Caatinga e perdas econômicas calculadas sobre o CAPEX da usina. Os três perigos revelaram naturezas distintas: o estresse térmico constitui um risco sistêmico regional, com perdas econômicas projetadas entre 1,5% e 2,6% da receita anual; a inundação é determinada por condicionantes geomorfológicos, com apenas três AOIs apresentando risco econômico significativo; e o incêndio é dominado pelo histórico local de focos, com pouca sensibilidade à variação entre cenários climáticos futuros. A integração pelo ELECTRE III produziu ordenação consistente nos seis contextos climáticos, com cinco áreas ocupando sistematicamente as melhores posições. O framework é replicável noutros territórios e tipologias de empreendimento, respondendo à crescente demanda por metodologias que integrem análise locacional e risco climático.
Climate change increases the physical risks faced by large-scale projects, while Brazil's environmental licensing framework is increasingly incorporating climaterelated requirements. In this context, this dissertation develops an integrated decisionsupport methodology for identifying priority areas for large-scale projects, combining GIS-based multicriteria land suitability analysis with prospective assessment of physical risks associated with multiple climate hazards, conducted at the asset level, across multiple scenarios and time horizons, and translated into expected economic losses. The methodology is demonstrated through a case study in the state of Ceará aimed at identifying priority areas for centralized solar photovoltaic power plants. The location analysis integrated 21 environmental, social, logistical and technical variables over a 300 m grid covering the entire territory of Ceará, using fuzzy membership functions aggregated by the Weighted Geometric Mean with IQRBOW weighting. Areas in the 99th percentile of the suitability index and larger than 450 hectares were identified as Candidate Areas (AOIs), totaling 16 polygons submitted to climate risk assessment. Model validity was evidenced by convergence with real projects: 65% of solar photovoltaic plants in operation or planning in Ceará are located in High or Very High suitability regions. Climate risk assessment for the 16 AOIs was structured around the IPCC hazard-exposure-vulnerability framework, under two emission scenarios and three time horizons. For thermal stress, CLIMBra dataset variables were transformed into module operating temperature, converted into efficiency losses and integrated into economic losses using the CLIMADA platform. For flooding, annual series from the CaMa-Flood model were translated into physical damage using a depth-damage curve and into economic losses based on asset replacement cost. For fire, the INPE Fire Risk model was adapted for projections up to 2070, with structural damage based on historical fire records in the Caatinga and economic losses calculated on the plant's CAPEX. The three hazards revealed distinct natures: thermal stress constitutes a systemic regional risk, with projected economic losses between 1.5% and 2.6% of annual revenue; flooding is determined by geomorphological conditions, with only three AOIs presenting significant economic risk; and fire is dominated by local historical fire patterns, with little sensitivity to variation between future climate scenarios. Integration by ELECTRE III produced a consistent ranking across the six climate contexts, with five areas systematically occupying the best positions. The framework is replicable across other territories and project typologies, addressing the growing demand for methodologies that integrate locational analysis and climate risk assessment.
Climate change increases the physical risks faced by large-scale projects, while Brazil's environmental licensing framework is increasingly incorporating climaterelated requirements. In this context, this dissertation develops an integrated decisionsupport methodology for identifying priority areas for large-scale projects, combining GIS-based multicriteria land suitability analysis with prospective assessment of physical risks associated with multiple climate hazards, conducted at the asset level, across multiple scenarios and time horizons, and translated into expected economic losses. The methodology is demonstrated through a case study in the state of Ceará aimed at identifying priority areas for centralized solar photovoltaic power plants. The location analysis integrated 21 environmental, social, logistical and technical variables over a 300 m grid covering the entire territory of Ceará, using fuzzy membership functions aggregated by the Weighted Geometric Mean with IQRBOW weighting. Areas in the 99th percentile of the suitability index and larger than 450 hectares were identified as Candidate Areas (AOIs), totaling 16 polygons submitted to climate risk assessment. Model validity was evidenced by convergence with real projects: 65% of solar photovoltaic plants in operation or planning in Ceará are located in High or Very High suitability regions. Climate risk assessment for the 16 AOIs was structured around the IPCC hazard-exposure-vulnerability framework, under two emission scenarios and three time horizons. For thermal stress, CLIMBra dataset variables were transformed into module operating temperature, converted into efficiency losses and integrated into economic losses using the CLIMADA platform. For flooding, annual series from the CaMa-Flood model were translated into physical damage using a depth-damage curve and into economic losses based on asset replacement cost. For fire, the INPE Fire Risk model was adapted for projections up to 2070, with structural damage based on historical fire records in the Caatinga and economic losses calculated on the plant's CAPEX. The three hazards revealed distinct natures: thermal stress constitutes a systemic regional risk, with projected economic losses between 1.5% and 2.6% of annual revenue; flooding is determined by geomorphological conditions, with only three AOIs presenting significant economic risk; and fire is dominated by local historical fire patterns, with little sensitivity to variation between future climate scenarios. Integration by ELECTRE III produced a consistent ranking across the six climate contexts, with five areas systematically occupying the best positions. The framework is replicable across other territories and project typologies, addressing the growing demand for methodologies that integrate locational analysis and climate risk assessment.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Geographic Information Systems and Science, specialization in Geospatial Data Science
Palavras-chave
Análise locacional risco climático usinas fotovoltaicas lógica fuzzy GIS-MCDM CLIMADA estresse térmico inundação incêndio Ceará land suitability analysis climate risk solar photovoltaic plants fuzzy logic thermal stress flooding fire