An input-output based framework to evaluate human labour in life cycle assessment

In LCA, the intrinsic dependence of productions to human labour (HL) activities is usually neglected, without providing any clear arguments. HL is not considered to be related to and affected by, changes to the functional unit, although this is evidently not the case. This research aims at investigating the relationship between HL and LCA and at developing an operational framework to assess the life cycle environmental impact of HL in LCA. System boundaries and functional unit (euro/working-hour) of HL were defined. Statistical datasets of household expenditures (HEs) allowed differentiating among human consumption behaviours and the definition of three HL types, based on different work skills: HL-1 (qualified worker), HL-2 (technician), and HL-3 (manual worker). The HEs framework of Luxembourg was used because of data availability and was then extended to other EU-27 countries. A comparative LCIA of the HLs types was carried out using an environmentally extended input-output model (EU-27). Afterwards, ten agri-food and industrial LCAs case studies were modified for hybrid LCAs, adding HL input to LCIs and using the ReCiPe midpoint method for LCIA. The LCIA comparison of HLs shows that HL-1 generates environmental impacts that are always greater than HL-2 and HL-3, e.g. 1 h of HL-1, which involves workers with the highest consumption of goods and services, does generate 0.52 kg CO2-eq, whereas HL-2 and HL-3 generate 0.46 and 0.41 kg CO2-eq, respectively. The impact of average HL is higher in EU countries with the highest HEs budgets, e.g. the average HL impact in Luxembourg is 28% to 79% higher than the corresponding HL impact in other EU-27 countries. Within the case studies, the HL significantly contributes to the total impact for several categories (e.g. fossil and ozone depletion up to 16% and 20%, respectively). Despite these important results, some limitations due to data and models used are investigated to suggest further methodological improvements. The integration of HL inputs to product LCIs can improve accuracy of the entire life cycle analysis, since no product would exist without direct and/or indirect HL. This leads considering humans at the same level of technological/economic activities that cause environmental damage, with humans being perceived as leading actors and explicitly responsible for the impacts. What remains an open question is how to account for non-physical information, such as knowledge/education/culture, which distinguish humans from machinery and are essential items for our future sustainable development.