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The increase in industrial production and energy consumption has led to excessive exploitation of non-renewable resources, resulting in serious environmental problems such as greenhouse gas emissions. In response, there's a growing investment in renewable energies such as hydroelectric, wind, and solar power. However, these sources are unable to fully meet demand, leading to imbalances between consumption and production. An emerging solution to this challenge is green hydrogen, produced from clean sources, reducing dependence on fossil fuels and mitigating greenhouse gas emissions. The S-LCA methodology presented in the UNEP/SETAC Guidelines for the Social Life Cycle Assessment of is applied to the production of green hydrogen via the electrolytic separation of water using a proton exchange electrolyser. The process involves the extraction and processing of raw materials from the electrolyser, BOP and reverse osmosis system, the manufacture of the systems and the production of green hydrogen. The data from each stage is inventoried and entered into the PSILCA v.3.1 and SHDB 2022FV5 databases, integrated into the SimaPro software version 9.3.0.2, enabling a complete analysis of the social impacts associated with the production of green hydrogen. The data was evaluated considering 3 stakeholder categories: workers, value chain actors, society and local community. The results indicate that the extraction and processing of raw materials for the electrolyser was the primary stage responsible for the social impacts in both databases. However, the electrolyser manufacturing stage was the main contributor to the indicators "weekly working hours per employee" and "union density" in the PSILCA database. Nafion® and Iridium were identified as the major contributors among components in both databases. The study highlights the significant role played by countries like China and South Africa in social impacts, particularly in the extraction and processing of raw materials. Despite this, Portugal emerged as the largest contributor to five out of fourteen indicators in the PSILCA database, while its contributions in the SHDB database were less than 7%. Moreover, a comparison between the two databases revealed that PSILCA exhibited a greater distribution of results across various stages, components, and countries assessed, whereas SHDB showed more centralized results. The observed discrepancies between the results obtained from different databases can be attributed to three main factors: the input-output database utilized in each S-LCA tool, the assumed risk levels for each indicator, and the equivalence between indicators and subcategories. This exploratory study offers valuable insights for guiding strategic decisions regarding the social component of sustainability, providing a detailed understanding of the social impacts associated with the specific case of green hydrogen production in a planned hub in Portugal.
Reis et al. (Tue,) studied this question.