Desenvolvimento de uma base de dados regionalizada para avaliação de ciclo de vida social e simulação de estudo de caso

Abstract

Social Life Cycle Assessment - ACV-S - is a technique for calculating potential social impacts of products and organizations. This technique can use generic data, for example, from country or sector, obtained from public data sources; and/or specific data from an organization, obtained from stakeholders at the place of interest for the study. Both types of data have challenges for collection and use: generic data can be so aggregated that it doesn't represent the specific case, and specific data takes a lot of resources to obtain. Moreover, in LCA-S a lot of data is needed to properly represent a system, since the results are obtained from qualitative and/or quantitative data, sometimes compared with each other. This difficulty was also found in a study conducted in 2017 by the Gyro Laboratory, from the Federal Technological University of Paraná for the O Boticário Group and with the support of the UN Environment and CNPq Life Cycle Initiative: the results obtained from the base data for ACV-S were limited due to the lack of regionalized data for evaluation of two Brazilian regions, São Paulo and Bahia. This proves that the lack of an adequate database makes it difficult to carry out studies in the area. Therefore, this paper aims to develop a database for LCA-S, covering the subcategory Fair Salary, at the level of Brazilian regions, with the indicators living wage, minimum wage and sector wage. From the evaluation of data sources through the Pedigree Matrix, the RAIS publication, from the Ministry of Labor and Employment, with data on the salary by sector; state, national, decrees and news for minimum wage data; and life wage data from the values ​​calculated monthly by DIEESE were selected. The data were calculated and organized with the R language to form the elaborated base, grouping data by states in the rows and by sectors in the columns, using CBO and CNAE codes. The results showed significant differences between states and regions, which reinforces the need for a regionalized database. Thus, a simulation was made to produce one dollar of ethanol for the states of Bahia and São Paulo, using auxiliary data and the elaborated base. The results showed that the states have different performances regarding the Fair Wage indicators analyzed, and the one that obtained the best results regarding the number of workers analyzed was Bahia, but it was also possible to identify wage differences between races and genders. For future work, it is especially recommended to use a larger number of CBO or CNAE codes to express the life cycle of a product, to get results closer to reality and to avoid the lack of data of the data source used to compose the database.