Work

A New Conservative Approach for Statistical Data Analysis in Surveying for Trace Elements in Solid Waste Ponds

Year: 2025

Type: article

Abstract: Solid waste treatment and resourceization critically depend on waste characterization. Heavy metals and critical raw materials are found as trace elements in solid waste dumps. Their reliable quantification plays a critical role for decision risk regarding effective waste management. Reliable quantification of trace elements is a very difficult issue. Hence, the paper addresses a new conservative approach for data analysis in screening for trace element in waste dumps. We propose a theoretical model for statistical data interpretation to overcome the drawbacks of the conventional approaches that are based on unproved hypotheses, like binomial, Poisson or Gaussian distributions of the particles carrying the analyte. Our model addresses concentration values close to the limit of quantification (LOQ) of an analytical method. The model fills the gap of data analysis in case where a set of laboratory outcomes are uniform distributed. Our approach cope with results reported as lower than LOQ. The model was applied on XRFS results carried on tailings to emphasize the differences among classic, robust and conservative data analyses. Classical analyses overestimate the concentration values and sub-evaluate the associated uncertainties which enhances the decision risk. The paper demonstrates that conservative approach is mandatory in case of screening for trace elements if concentration values are uniform distributed. The model can be applied to any solid waste dump, regardless the analytical method used for trace element screening.

Source: Applied Sciences

DOI: 10.3390/app15084246