Modeling and Optimization of Eucalyptus globulus Bark and Wood Delignification using Response Surface Methodology

Abstract

Statistical models and optimization of Eucalyptus globulus Labill. wood and bark delignification were achieved using response surface methodology (RSM). A central composite design was outlined to model the simultaneous influence of active alkali (AA), reaction temperature (T), and reaction time (t) on pulp yield (η) and kappa number (k) during the kraft pulping of wood and bark. Experimental results were fitted to a second-order polynomial with linear interaction of factors. The statistical models showed high coefficients of determination for both wood (R2η = 0.991, R2k = 0.975) and bark (R2η = 0.993, R2k = 0.984). Using these models, the optimum conditions to attain a pulp with the highest yield at an acceptable kappa number (below 17) were determined. For wood, the pulp yield was 51.6% (51.5% predicted) and the kappa number was 16.1 (16.9 predicted) under optimized conditions (AA = 21%, T = 151 oC, and t = 118 min). For bark, the pulp yield was 51.3% (51.0% predicted) and the kappa number was 19.4 (16.9 predicted) under optimized conditions (AA = 15%, T = 166 oC, and t = 114 min). The degree of polymerization (DP) of the carbohydrates for the optimized pulps, 1430 and 1151 for wood and bark, respectively, suggests low levels of polysaccharide degradation. The bark delignification showed similar behavior to wood.