From June 15th to 17th, the Social Life Cycle Assessment (SLCA) conference 2020 took place in online format, after it needed to be shifted from the original face-to-face format. Posters were presented in Twitter, presentations were prerecorded in video format, and live sessions with keynote speakers and discussions were hold every afternoon.

GreenDelta participated with two presentations, yet available on our YouTube channel.

Andreas Ciroth introduced the direct calculation approach that was developed as a new and unique feature for the PSILCA v3 database in his presentation “A direct quantification of indicators in social LCA – beyond worker hours”. This approach enables users to perform social LCA calculations without the step of using worker hours as an activity variable. The worker hours have been a commonly accepted method in Social LCA to aggregate results across processes, they come with some shortcomings regarding interpretation, though. Andreas explained the idea behind the new direct approach and showed some examples in openLCA, using PSILCA. The direct calculation is based on a normalization of the results. This step can be conducted in openLCA by applying a Python script that comes with the manual of PSILCA v3.

The second presentation was hold by Cristina Vilabrille Paz and is about the “Influence of potential impacts of novel mining technologies on the Social License to Operate”. She presented the methodology that we propose to analyze relevant factors influencing the social acceptance of mining activities – general factors as well as context specific ones. Additionally, she demonstrated how novel technologies in general, and specifically the ones proposed in the Horizon 2020 ITERAMS project may influence the social acceptance of a mining site. To test the methodology, and to identify context specific factors, she had carried out a case study in the mine “Cobre las Cruces” in South Spain. In the presentation she showed the followed data collection procedure and introduced the context specific factors found as relevant for this specific mine. However, further data analysis is needed.

Furthermore, it was great to see that some presented case studies were using PSILCA as database for their calculations, for example the case study on the SLCA of honey from the PESCARA University (Ioannis Arzoumanidis, Manuela D’ Eusanio, Maria Bianca Tragnone, and Luigia Petti). It is a cradle to gate study, in Italy. The functional unit of the study is 250 grams of honey in a glass jar. The subcategories selection was based on a cross-check considering the available indicators in the database that were also included in a previous study. For example, the indicators minimum and living wage, per month, were used to assess fair salary. Primary data were collected through questionnaires, and interviews to workers and local community. Additionally, data on working hours for the product system and costs inputs were collected. The impact assessment was performed with PSILCA. The social risks of different stages of the product system were identified, e.g. hives placement presents the highest social risk. The authors gave valuable feedback on the database and proposed a combination of the database with the Subcategory Assessment Method.