Soft sensor model of adsorbable organic halogen based on bleached pulp quality indices

Abstract

Adsorbable organic halogen (AOX) produced during the bleaching process contains polychlorinated dibenzo-p-dioxins. To predict AOX in a timely and economical manner during pulp bleaching, a soft sensor model based on pulp quality indices was developed by analyzing the correlation between the AOX in the bleaching effluent and the whiteness, Kappa number, and intrinsic viscosity of the pulp. Variations of the main components during pulp bleaching were considered to determine their effects on wastewater AOX content. The results showed that the models can predict the AOX content of bleaching wastewater precisely and rapidly. The high relevant between pulp components and whiteness, Kappa number, and intrinsic viscosity allows the soft sensor model to predict AOX value without interference of components. The developed model has practical importance for monitoring AOX emissions and controlling pollution, which is essential for the global optimization of bleached pulp production cost, pulp quality, and environmental impact. Additionally, it adapts to the requirement of intelligent control of the bleaching process.