Accounting for social impacts of environmental damage

1. Context Social LCA has focused in the past on worker conditions and to some extent on improving socio-economic conditions through added value. This is also reflected by the most comprehensive database, the SHDB. Although... [ view full abstract ]

1. Context
Social LCA has focused in the past on worker conditions and to some extent on improving socio-economic conditions through added value. This is also reflected by the most comprehensive database, the SHDB. Although environmental impacts are already accounted for in standard LCAs, they also affect human well-being beyond disease and mortality.
2. Objectives,
The main objective of this work is to test and evaluate how social risks can be combined with environmental impacts to have an additional dimension in the SLCA assessment that is not related to work hours, but accounts for adverse effects on social well-being of heavy pollution or destruction of natural environment.
3. Methodology/approach,
In order to account for environmental stressors in SLCA, we used the MRIO database Exiobase v2.2.2, which is to a large extent compatible with the GTAP MRIO model underlying the SHDB. Although there are some differences in sector and region resolution, the risk factors from the SHDB can be attributed to Exiobase sector and regions. Exiobase contains information on emissions and resource consumption (incl. Land and water use) for each Euro spent in these country-specific sectors (CSS). This allows accounting for impacts that affect well-being of the population and relate them to the social risks which are not specific to work conditions and therefore are not best accounted for by work hours. We select specific risks such as “Characterization of State Fragility Index” for which a high risk indicates that the government does not properly manage environmental impacts and therefore the population is supposedly more affected by environmental damage. In order to combine the different social risks we quantified risks on a numerical scale with different schemes to test sensitivity.
4. Findings and contributions.
We tested different sets of risk indicators and scales to link them to environmental impacts and applied it to textile case studies. The results have also been compared to social risks due to work hours, as provided by the SHDB, and made the two dimensions comparable by normalizing over the total annual impacts with and without risk weighting. The results showed that there is some correlation between work hours and environmentally induced social impacts, and the cotton production phase is dominating. For some processes with low work hours but high emissions (such as oversea shipping) social impacts due to environmental degradation are dominant. The method developed allows inclusion of an additional dimension affecting social well-being.