Significance of international life cycle data in South African extended producer responsibility

Abstract

The South African extended producer’s responsibility has made cradle-to-grave life cycle assessments a mandatory requirement for the paper and paper packaging industry. This is an intensive undertaking that requires a lot of data and time if primary data sets were to be created. The aim was to evaluate the applicability of using secondary and modified data sets in the life cycle assessment to speed up the process and reduce the amount of primary data required, with white-lined chipboard as the case study. Four white-lined chipboard data sets were used, a South African data set created from local industry data, a European data set from the Ecoinvent database and two modified European data sets, Scenario 1 and Scenario 2, to better represent the South African landscape. On an inventory level, the results indicated that the goal, scope and objective of the local and European life cycle assessments were similar, with minor differences. On an impact assessment level, the South African data had a much higher impact compared to the European data. This was mainly due to their reliance on fossil fuels for energy and electricity. On an uncertainty level, the uncertainty of the South African data was much higher, but this was due to the uncertainty related to the adjusted pedigree matrix and the cumulative nature of uncertainty in the life cycle inventory tiers. The results indicated that modified data sets with a base data set that has a similar goal and scope to the original South African study, and in which the data entries, data values and uncertainties are adjusted to match the South African process more closely would suffice.

Significance:

• International life cycle inventory data can be used to conduct local life cycle assessments provided that some minor modifications are made.
• In the South African context, the use of coal in the electric grid and boilers has the largest influence on the life cycle assessment outcomes.
• On a life cycle impact assessment (LCIA) level, uncertainty is cumulative, resulting in high uncertainty scores even if the variability of primary data (life cycle inventory level) is low.