Industrial Wastes and Waste Dumps, Sampling and Analysis

Abstract

Abstract Industrial sites where residuals and wastes, such as slags, ashes, dust, and sludges, have been dumped are essential parts of the environment and of the economic structure. The amount of waste produced, distributed, and deposited is constantly increasing. The wastes can contain hazardous components that pollute and endanger the environment, but they can also consist of valuable materials, which are a source of secondary raw materials. To assess the environmental risk caused by the waste or to calculate the economic benefit of dumped material, a reliable knowledge of the waste composition is required. Waste management experience has regularly shown that conflicts and lawsuits are the result if the composition of the waste materials is difficult to determine reliably. Investigations carried out by different institutions and persons, or by the same personnel under varying conditions, will often have different results. The measuring technology and the measuring methods cannot be the only reasons for that. Nowadays, it is possible to accurately determine chemical components in any natural concentration, and there is no problem in distinguishing the size and shape of particles down to the nanometer scale. The problems are created because the wastes are mixtures of particles and lumps that vary in size and shape as well as in chemical composition and physical properties. A waste dump with a varied production history and dumping conditions, with chemical reactions or physical changes occurring after dumping, will be heterogeneous as a rule. Therefore, the evaluation of any dump of industrial waste materials is quite difficult. To ensure that the results of evaluation are comparable, certain regulations of investigation must be followed. According to the delivery, the wastes are classified into material streams (stationary, moving, or free falling), heaps delivered within containers and vehicles, and free‐standing heaps. As it is economically unjustifiable to investigate the entire waste dump, subsets of material (called samples) must be taken from the stream, the container, or the heap in order to determine the measurements of interest. In doing this, measuring results are obtained, which differ from the true (but unknown) waste composition. If the investigation is carried out strictly according to the rules, the differences that exist at any step of investigation (called measuring deviations or deviations caused by measurement) are random and unavoidable. The standard deviation of these measuring deviations, i.e. the square root of the respective variance, characterizes the specific uncertainty in waste characterization (called uncertainty of measurement, measuring uncertainty, measurement uncertainty, or mean deviation of the measured results from the true value) that must be accepted. The total uncertainty of a characterization procedure is calculated as the square root of the sum of the respective variances caused by the different steps of investigation from taking samples up to instrumental analysis and subsequent data analysis. The aim of waste characterization is to determine the waste composition by sampling as reliably as necessarily and at prescribed or minimal costs. To ensure this, certain rules have to be followed that control planning the sampling, handling of the samples such as preservation and preparation by splitting and reducing, instrumental measurement in the laboratory, and, finally, statistical evaluation of measuring results. Nevertheless, rather a lot of avoidable errors can be made that waste characterization systematically falsify. Such errors (called systematic errors, systematic deviations caused by measurement) are frequently caused by unobjective sampling and improper handling of the sample material. In addition, a false estimation can also be made by evaluating reliable data using unsuitable statistical methods. Thus, the term ‘error’ suggests an imperfect and avoidable action or a controllable result. The present contribution takes up this problem. First, an industrial waste dump and a mercury‐contaminated site were chosen as examples, and proven sampling regulations were applied. The applicability of known statistical and geostatistical methods developed for homogeneous granular bulk solids and uniformly contaminated soils to the evaluation of extremely heterogeneous waste dumps and no uniformly contaminated industrial sites is shown. After that, mathematical modeling of granular mixtures and statistical methods were applied to control the input of recycling products obtained by processing of industrial wastes. Verification of specific sampling concepts and risk assessment were essential parts of the problems considered. Electronics scrap and recycled broken glass from bottles and pots were chosen as examples.