Statistical quantification of sub-sampling representativeness and uncertainty for waste-derived solid recovered fuel (SRF): Comparison with theory of sampling (ToS)

摘要

The level of uncertainty during quantification of hazardous elements/properties of waste-derived products is affected by sub-sampling. Understanding sources of variability in sub-sampling can lead to more accurate risk quantification and effective compliance statistics. Here, we investigate a sub-sampling scheme for the characterisation of solid recovered fuel (SRF) - an example of an inherently heterogeneous mixture containing hazardous properties. We used statistically designed experiments (DoE) (nested balanced ANOVA) to quantify uncertainty arising from material properties, sub-sampling plan and analysis. This was compared with the theoretically estimated uncertainty via theory of sampling (ToS). The sub-sampling scheme derives representative analytical results for relatively uniformly dispersed properties (moisture, ash, and calorific content: RSD <= 6.1 %). Much higher uncertainty was recorded for the less uniformly dispersed chlorine (Cl) (RSD: 18.2 %), but not considerably affecting SRF classification. The ToS formula overestimates the uncertainty from sub-sampling stages without shredding, possibly due to considering uncertainty being proportional to the cube of particle size (FE proportional to d(3)L), which may not always apply e.g. for flat waste fragments. The relative contribution of sub-sampling stages to the overall uncertainty differs by property, contrary to what ToS stipulates. Therefore, the ToS approach needs adaptation for quantitative application in sub-sampling of waste-derived materials.