Removal of hexenuronic acids by extended oxygen delignification of high-kappa eucalyptus kraft pulp
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Eraldo Antonio Bonfatti Júnior
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Francides Gomes da Silva Júnior
Abstract
The presence of hexenuronic acids (HexAs) in kraft pulp interferes with bleaching by increasing the consumption of bleaching chemicals and compromising brightness stability. This study investigated the removal of HexAs during the extended oxygen delignification of eucalyptus kraft pulp with a high initial kappa number (64). Response surface methodology was used to evaluate the effects of temperature (80, 100, 120 and 140 °C) and alkali charge (15, 30, 45 and 60 kg t−1), both individually and interactively, under three conditions: without additives, with 0.05 % anthraquinone, and with 0.05 % ethanol (based on oven-dry pulp weight). The initial HexAs content (20.09 μmol g−1) was significantly reduced under severe conditions, especially in the presence of ethanol, which achieved a maximum reduction of 11.69 μmol g−1 (58.2 %). The removal of HexAs showed a strong dependence on the interaction between temperature and alkali charge, and the observed trends mirrored those of residual lignin, suggesting a similar response to the oxidative alkaline conditions. Among the treatments, ethanol was the most effective, whereas anthraquinone resulted in a limited reduction in HexAs content. These findings highlight the potential of optimized oxygen delignification for effectively reducing HexAs levels.
Funding source: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) [partial funding]
Award Identifier / Grant number: Finance Code 001
Acknowledgements
The authors thank the team of the Laboratory of Chemistry, Pulp and Energy (LQCE/ESALQ/USP) for their valuable support during the development of this research.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved it submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001.
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Data availability: The raw data can be obtained on request from the corresponding author.
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