Sampling and analysis of coarsely shredded mixed commercial waste. Part II: particle size-dependent element determination

S A Viczek,L Kandlbauer,A Aldrian,R Sarc,K Khodier

doi:10.1007/s13762-021-03567-w

S A Viczek, L Kandlbauer + Show 3 more

Open Access

https://doi.org/10.1007/s13762-021-03567-w

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Abstract

In contemporary waste management, sampling of waste is essential whenever a specific parameter needs to be determined. Although sensor-based continuous analysis methods are being developed and enhanced, many parameters still require conventional analytics. Therefore, sampling procedures that provide representative samples of waste streams and enable sufficiently accurate analysis results are crucial. While Part I estimated the relative sampling variabilities for material classes in a replication experiment, Part II focuses on relative sampling variabilities for 30 chemical elements and the lower heating value of the same samples, i.e., 10 composite samples screened to yield 9 particle size classes (< 5 mm–400 mm). Variabilities < 20% were achieved for 39% of element-particle size class combinations but ranged up to 203.5%. When calculated for the original composite samples, variabilities < 20% were found for 57% of the analysis parameters. High variabilities were observed for elements that are expectedly subject to high constitutional heterogeneity. Besides depending on the element, relative sampling variabilities were found to depend on particle size and the mass of the particle size fraction in the sample. Furthermore, Part I and Part II results were combined, and the correlations between material composition and element concentrations in the particle size classes were interpreted and discussed. For interpretation purposes, log-ratios were calculated from the material compositions. They were used to build a regression model predicting element concentration based on material composition only. In most cases, a prediction accuracy of ± 20% of the expected value was reached, implying that a mathematical relationship exists.

Highlights

The assessment of the quality and the categorization of waste are usually based on various analytical results
In contrast to the loss of dust, the increment preparation error (IPE) caused by water loss does not influence analysis results for chemical elements as they refer to mg/kg dry mass (DM)
While the applied procedure gives good results for some parameters, relative sampling variability (RSV) range up to 203.5% for others. This may be linked to the high distributional and constitutional heterogeneity caused by the industrial applications of the chemical elements and their compounds, leading to a high minimum possible errors (MPE) for these elements

Summary

Introduction

The assessment of the quality and the categorization of waste are usually based on various analytical results. While the propagation of uncertainties in all process steps leads to a general variance of the analysis results (Krämer et al 2016), the contribution of primary sampling to the measurement uncertainty and variability is often dominant (Ellison and Williams 2012; Esbensen and Julius 2009; Ramsey et al 2019). For this reason, reliable and representative sampling is crucial. Various sampling standards exist, the sampling quality can still be influenced by on-site circumstances (e.g., the possibility to take the sample from the falling stream or a stationary pile)

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