https://ineris.hal.science/ineris-03515268Hennebert, PierrePierreHennebertINERIS - Institut National de l'Environnement Industriel et des RisquesBeggio, GiovanniGiovanniBeggioUnipd - Università degli Studi di Padova = University of PaduaSize of a representative sample by rare particles in concentration and size (81)HAL CCSD2021[SDE] Environmental SciencesCivs, Gestionnaire2022-01-06 16:13:032022-11-25 19:07:322022-01-06 16:13:03enConference papers1The theory of representative sampling of granular waste in terms of number of particles has been developed for the particles rare in concentration, typical of skewed concentration distributions observed in waste. In the “number of particles” derived from binomial distribution and used in waste sampling standards and in the Gy’s Theory Of Sampling, the particle size and the particle concentration are not simultaneously and explicitly considered. Nevertheless, according to numerous publications with many wastes, the composition and material of large particles are different from the composition and material of small particles, but in practice it is not known or ignored for sampling. A solution is offered: to calculate the size of a representative sample with the rare particles in concentration and in size using the same theory of sampling with the number of particles, based on the statistical drawing of particles with binary properties (having or not having the property of interest: a given concentration, a given size…), as described by the binomial distribution (as in waste sampling standards). For a variability of analyses of 10%, the number of particles “n” in a representative sample should be 100/p, “p” being the frequency of rare particles (p≤1). The transformation of the number of particles into a mass is then done for rare particles in concentration (as in sampling standards) and in size (new proposition). The assessment of “p” is critical. This simple and statistically valid approach is presented compared with 5 real cases (from 12 samples) with homogeneous and heterogeneous particle composition and particle size distribution, and the results are assessed coherent. A practical solution for additives or substances in products and waste to assess p is proposed (p = concentration limit/functional concentration). The statistical power of published waste sampling plans (bottom ash, shredded plastics, lamps, mixed commercial waste) is assessed.