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High metal concentrations in the body’s biological substrates often result from a persistent, cumulative impact of adverse environmental conditions. This article considers the quantitative composition of human biological substrates as an indicator of the state of urban ecosystem components. Assessing the accumulation of metals in the body by directly measuring their concentrations in biological substrates is a multi-step analytical procedure. Here, a quick-and-easy method for determining metal concentrations in biological substrates based on a neural network algorithm was introduced. A complex neural network model was developed to enable the determination of metal inputs from the air and food-water system without the need for invasive sampling of biomaterials or too difficult processing and analysis of the samples obtained. The model also proved to be feasible in solving the inverse problems associated with the determination of metal thresholds in various components of urban ecosystems.
Tunakova et al. (Mon,) studied this question.
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