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

Abstract

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 μm 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.

Sustainable Countermeasures for Skin Health Improvement for Green Consumers: The Utilization of Hsian-Tsao during Global Warming

“…Moreover, plants that live in shaded areas in alpine regions cannot survive in high temperatures, while plants that live in areas with high temperatures, such as deserts, have relatively high heat resistance. With this in mind, heat-resistant components that can be used to prepare for global warming in the face of environmental problems are needed [25][26][27][28][29][30][31][32].…”