Purpose: prevention of occupational risks and reduction of the negative impact on the health of workers of industrial flue gases, along with the improvement of environmental safety thanks to mathematical modeling regarding the rationalization of technological indicators of sulfur removal at production enterprises. Design / methodology / approach: the use of regression analysis is implemented as the main research method. Conclusions: a multifactorial mathematical model of the dependence of the degree of reduction of the content of sulfur dioxide in gaseous products on the technological parameters of flue gas filtration was built using industrial data. This makes it possible to rationalize the technological parameters of production with further regulation of the sulfur dioxide purification process to increase its efficiency. Achieving a reduction in flue gas pollution with sulfur dioxide contributes to reducing the harmful effects on the health of workers, preventing occupational risks, and increasing the level of environmental safety. Limitations / implications of the research: the interrelationship of desulfurization production parameters was investigated in certain intervals according to the features of the technological process, which determines the corresponding limitations of the use of the constructed mathematical model. Practical consequences: the interrelationship of technological indicators of industrial production is determined, which allows adjusting the value of the degree of purification of flue gases from sulfur dioxide when changing the technological parameters of filtration with the establishment of the most favorable conditions. The obtained results can be used to improve the production process of enterprises whose activities are accompanied by gaseous emissions: metallurgical plants, thermal power plants, etc. Originality / value: a multifactorial mathematical model of the dependence of the degree of purification of flue gases from sulfur dioxide on the technological parameters of the industrial process was built. The obtained results were presented in the form of a multivariate regression equation. On the basis of the obtained dependence, for a better visual perception, graphs were constructed in the form of surfaces, respectively, for some of the studied technological parameters.
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