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Because kappa number cannot accurately represent the lignin content in the pulp after alkaline extraction, lead to the excessive dosage of bleaching chemicals added and the pollutant content increases. In order to accurately determine the dosage of bleaching agent, reduce pollutant emissions, a prediction model of lignin content of pulp was established by analyzing the correlation between lignin content and alkaline extraction conditions in this paper. The results show that the established soft sensor model can accurately measure lignin content, it is helpful to determine the amount of bleaching agent more accurately, reduce pollutant generation after pulp bleaching.

Development of paper industry has been restricted by resources, energy and environment deeply; further reducing energy consumption becomes an urgent problem to be solved. In this paper, the calculating model of steam consumption in bleaching process is established under the premise of ensuring product quality and controlling bleaching cost. Then, an optimization model for minimizing steam consumption is constructed. Compared with before optimization, the steam consumption of the optimized bleaching system reduced by 19.48% (0.5014 t/adt) at a loss of 0.11% brightness (0.1 ISO%) and 5.17% viscosity (33 mL/g). The amount of chemicals should be increased to ensure the quality of the pulp while decreasing the bleaching temperature to reduce steam consumption, the cost of bleaching pulp has decreased by 1.62% (3.19 USD/adt) after optimization. The verification experiments showed all the pulp quality indices can meet the requirements of bleached pulp.

This study describes the optimization of a eucalyptus elemental chlorine-free (ECF) bleach plant to reduce adsorbable organic halogen (AOX). The correlations between operating conditions of each stage and pulp quality indices as well as the AOX content in wastewater are analyzed, taking an ECF bleaching technology (D0EpPD1) as an example. The calculation models of pulp quality indices and AOX content in wastewater are established. Then, an optimization model aiming at minimizing AOX emission is structured. The model shows a good simulation effect because the errors between the calculated and experimental values are within 6.3%. By analyzing the impact of various operating conditions on AOX emissions, it was found that chlorine dioxide reduced in the D0 stage has the greatest impact on AOX. The optimization results show that AOX can be reduced from 90.84 to 79.58 kg/h, a decrease of 12.5%. The verification experiment results based on the optimized operating conditions showed that the experimental results are in good agreement with the calculated results of the optimization model, and the effect of reducing AOX based on the optimization model is obvious.