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Empirical Modeling for Effects of Emerging Pretreatment Methods on Anaerobic Digestion of Pulp Mill Biosolids

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Effects of microwave and ultrasound pretreatment methods were investigated on solubilization and anaerobic digestion of waste sludges from a pulp mill wastewater treatment plant (WWTP). Batch anaerobic digesters were used to stabilize pretreated waste activated sludge (WAS) and mixed sludge (primary sludge + WAS). Results on effects of sludge type (WAS and mixed sludge), microwave temperature (in a range of 50–175°C), sonication time (15–90 min), and anaerobic digester temperature [mesophilic (35 ± 2°C) and thermophilic (55 ± 2°C)] were investigated on sludge solubilization and methane production in multi-level factorial statistical designs. Analysis of variance (ANOVA) showed that all the main effects (microwave temperature, sludge type and digestion temperature) and two–way interactions had significant (p-value < 0.05) effects on cumulative methane production relative to control (not pretreated) digesters (CMPr) at high microwave temperatures (i.e., 150 – 175°C). On the other hand, at lower microwave temperatures (i.e., 50, 75, and 100°C), pretreatments did not significantly improve the CMPr. During the sonication pretreatment, sonication time and digestion temperature significantly affected the CMPr with a p-value < 0.05. Variance analysis also determined that, for both pretreatment methods, the most important factor affecting the sludge solubilization, indicated by relative to control soluble to total chemical oxygen demand ratio (SCOD/TCODr), was the sludge type. To select a pretreatment method and the operational condition that maximize both the solubilization and methane recovery, a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was applied and it was concluded that mesophilic anaerobic digestion of WAS irradiated at 125°C resulted in optimal pretreatment scenario with SCOD/TCODr and CMPr of 6.1, and 1.7, respectively.

Keywords: Sludge pretreatment; anaerobic digestion; empirical modeling; microwave; multiple attribute decision making; pulp and paper industry; ultrasound

Document Type: Research Article


Publication date: 2011-01-01

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