Water scarcity in Brazil: part 2—uncertainty assessment in regionalized characterization factors

• Autor(a) principal: Alves, Kilvia de Freitas
• Data de Publicação: 2020
• Outros Autores: Andrade, Edilene Pereira, Savioli, José Paulo, Pastor, Amandine V, de Figueirêdo, Maria Cléa Brito, Ugaya, Cássia Maria Lie
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10451/49731

Purpose: Despite recommendations, uncertainty results are rarely incorporated in Life Cycle Assessment (LCA) studies, especially regarding characterization factors (CF). Part 1 of this study conducted AWARE CF regionalization for Brazil, concluding that the Semiarid region had maximum scarcity values. The goal of this study is to evaluate the uncertainties of regionalized AWARE CF in the Semiarid region. Methods: Data used to obtain the AWARE BR CF for Brazil were qualitatively and quantitatively assessed. An adapted Pedigree Matrix was adopted to assess qualitative uncertainties. Classical statistical analysis was used for quantitative uncertainty assessment, and 10,000 Monte Carlo simulations were computed for uncertainty propagation. Results and discussion: Qualitative results indicated that the natural flow’s parameter was very uncertain due to poor spatial correlation and low reliability, as it is based on empirical models. Quantitative results showed that water availability data, which had large temporal variability, typical of the Brazilian Semiarid region, was the main responsible for uncertainties in input data. Area uncertainty had a good performance in both qualitative and quantitative assessments. Regarding output data, moderate CF were found to be more uncertain, while more extreme CF exhibited lower variation, corroborating with previous analyses. Moreover, the adoption of shorter datasets led to a reduction in average and standard deviation values for CF. Conclusion: Findings from this study showed two important reasons why the quantitative and qualitative assessments should be conducted simultaneously. The first one was to avoid bias, as availability data and natural flow performed differently in each evaluation. The second one was to confirm results, as the area proved to be very little uncertain in both assessments. An adaptation of Pedigree Matrix and a penalty factor for missing data could be used as a base for quantitative uncertainty parameters for LCIA. Generating SD and k-factor was very positive in terms of results for AWARE method and comparison with other methods. Both indicators had similar results and led to a common conclusion: uncertainties are mainly low and very low for AWARE BR CF in the Semiarid region.