analyses on the assessment of 40 generic waste management scenarios.
However, only the global warming impact category was included
in this study.
The composition of waste influences the potential for recycling,
substitution of other heat and/or electricity sources, and biogas
production; it also influences the environmental impact from
incinerators and landfill. Waste composition is therefore potentially
very important for the outcome of LCAs of waste management
systems. Waste composition is defined by the weight
distribution between different fractions and the chemical composition
of each fraction. Uncertainty in both of these parameters can
influence the results. Riber et al. (2009) used two methods to decide
the chemical compositions of 48 material fractions in Danish
household waste, which are included in the LCA-waste tool
EASEWASTE (Kirkeby et al., 2006). We will, however, not discuss
uncertainty in chemical composition in this article, but concentrate
instead on uncertainty in the weight distribution between different
fractions.
Waste compositions are not usually described to the level of detail
found in the EASEWASTE software. Assessments are usually
based on municipality or company specific data, national average
data, or waste composition analysis. In Norway most municipalities
have recycling programmes, and the size of each sorted fraction
is reported annually. Dahlen et al. (2009) discussed the
many sources of uncertainty for such public data. They identified
sixteen sources of error and uncertainty in the interpretation of
official waste collection data in Sweden, and sorted them into four
main categories: general data problems, data uncertainties related