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- Publications & Research
- Publication #160
Material Flow Analysis of plastic products in Austria - Emphasis on data uncertainties in consumption sectors and solid waste management
- Material Flow Analysis of plastic products in Austria - Emphasis on data uncertainties in consumption sectors and solid waste management
- Julia Feketitsch
- Hanno Buchner
- Jakob Lederer
- David Laner
- Johann Fellner
- Journal Article
- Material flow analysis (MFA) is about gathering, harmonizing and analyzing data on physical flows and stocks
from different sources with varying qualities. Paucity of data is typical for regional material flow studies,
causing considerable uncertainty about MFA input data and model results. The aim of this paper was to illustrate
an approach for estimating uncertainties of input data and material flows of the Austrian plastics household. The
input and output flows of the consumption sectors of the Austrian plastics household were analyzed according to
their uncertainty and serve as an example of using uncertainty ranges to indicate the quality of material flow
estimates and their respective source(s).
By distinguishing basic and additional uncertainty as elements of the total uncertainty, it was possible to
consider different quality aspects of the data. The basic uncertainty refers to natural or random variability in the
data and the additional uncertainty is due to low quality of the data (the reported value may not be representative
for the value of interest).
For the presented case study, we found, that the resulting uncertainty ranges are well suited to indicate the
quality of MFA data: the poorer the quality of the data (or the harder to elevate the mass flow) the higher is the
value for the total uncertainty. The presented approach allows for a more transparent and consistent
characterization of uncertainties within regional MFA studies. However, further studies are necessary to
investigate the effect of using different mathematical concepts in conjunction with the presented approach or to
evaluate the robustness of the resulting uncertainty estimates.
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