Comparison

Abstract

The level of uncertainty during quantification of hazardous elements/properties of waste-derived products is 19 affected by sub-sampling. Understanding sources of variability in sub-sampling can lead to more accurate risk 20 quantification and effective compliance statistics. Here, we investigate a sub-sampling scheme for the 21 characterisation of solid recovered fuel (SRF) - an example of an inherently heterogeneous mixture containing 22 hazardous properties. We used statistically designed experiments (DoE) (nested balanced ANOVA) to quantify 23 uncertainty arising from material properties, sub-sampling plan and analysis. This was compared with the 24 theoretically estimated uncertainty via theory of sampling (ToS). The sub-sampling scheme derives 25 representative analytical results for relatively uniformly dispersed properties (moisture, ash, and calorific 26 content: RSD ≤ 6.1%). Much higher uncertainty was recorded for the less uniformly dispersed chlorine (Cl) 27 (RSD: 18.2%), but not considerably affecting SRF classification. The ToS formula overestimates the uncertainty 28 from sub-sampling stages without shredding, possibly due to considering uncertainty being proportional to the 29 cube of particle size (FE ∝ d 3 ), which may not always apply e.g. for flat waste fragments. The relative 30 contribution of sub-sampling stages to the overall uncertainty differs by property, contrary to what ToS 31 stipulates. Therefore, the ToS approach needs adaptation for quantitative application in sub-sampling of waste- 32 derived materials. 33