4.6 Article

Study on Efficient Removal Method of Fine Particulate Dust in Green Metallurgy Process

期刊

PROCESSES
卷 11, 期 9, 页码 -

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MDPI
DOI: 10.3390/pr11092573

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green metallurgy; chemical agglomeration; fine particulate dust

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This study investigates the efficiency of a chemical agglomeration pretreatment method using xanthan gum, konjac gum, and their mixtures for the removal of fine particles in the flue gases of the metallurgy process. The results show that the mixed solution of 1 g/L mixed gum and 0.5 g/L SDS has the most significant effect on increasing the particle size of fine dust particles and achieving the best removal effect. The optimized parameters for maximum removal efficiency are 1 g/L mixed gum concentration, 0.4 MPa pressure, and 10 m/s flue gas velocity.
In order to solve the problem of the low removal efficiency of fine particles in the flue gases of the metallurgy process, a chemical agglomeration pretreatment method was studied. The coagulant solution of xanthan gum, konjac gum, and their mixtures was selected to research the reunion effects of and the efficiency of gravitational dust removal of fine dust in the gas of the converter flue using a self-built experimental platform. Moreover, the effects of wetting agent type, dust concentration, pressure, and flue gas velocity on the fine grain removal efficiency were investigated. The results showed that the mixed solution of 1 g/L mixed gum and 0.5 g/L SDS had the most obvious effect on the particle size increasing of fine dust particles and the best removal effect when the flue gas velocity was 10 m/s. There was a peak particle size of 85.32 mu m increased about eight times larger, and the removal efficiencies reached 51.46% for PM2.5 and 53.13% for PM10. The Box-Behnken experimental design combined with a response surface analysis method was used to optimize the parameters of the mixed gum concentration, pressure, and flue gas velocity. The optimal removal conditions were 1 g/L, 0.4 MPa, and 10 m/s. The results of this study can provide efficient methods and technical support for pre-processing and efficient removal of fine particles in heavy-polluting industries such as steel making. This will promote the green development of the metallurgical industry.

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