Band 79, Heft 9 - Special Issue: The 17th European Workshop on Lignocellulosics and Pulp (EWLP), Turku/Åbo, Finland, August 26–30, 2024; Issue Editors: Chunlin Xu, Merima Hasani and Monica Ek

This study explores the potential of nitrogen-enriched lignins produced via ammoxidation – a process combining oxidation and nitrogen incorporation with ammonia (NH 3 ) and oxygen (O 2 ) – to improve wood fibres as sustainable peat alternatives in horticultural substrates. Organocell lignin (OCL) and kraft lignin (KL) were assessed, focusing on the effect of ammoxidation conditions on total nitrogen and amide nitrogen incorporation using OCL as a reference. Total nitrogen content in nitrogen-enriched KL (NKL) reached 6.3 % under 60 bar oxygen pressure, but amide nitrogen remained low (0.64 %), indicating challenges in optimizing this nitrogen type. Attempts to selectively increase amide nitrogen through reaction adjustments proved unfeasible. First cultivation tests showed 2 % nitrogen-enriched OCL (NOCL) enhanced plant growth in substrates with 50 % and 100 % wood fibres compared to lignin-free controls. Adding 10 % NOCL improved growth in peat-free substrates, though less effectively than the 2 % concentration. Conversely, NKL had no notable effect in 50 % wood-fibre substrates and negatively affected 100 % wood-fibre substrates. The results underscore the importance of modifying lignin reactivity prior to ammoxidation to boost amide nitrogen incorporation, offering insights into the viability of wood fibres as peat substitutes in horticulture.

Crude tall oil contains many valuable chemicals such as fatty acids and terpenes which can be used for the production of bio-based plastics, adhesives and paints. In addition to the widely used vacuum distillation process, crude tall oil can also be upgraded using supercritical CO 2 (scCO 2 ) extraction. However, research on the extraction of crude tall oil with scCO 2 is still very limited. The main factors influencing scCO 2 extraction are temperature, scCO 2 density and the contact time between scCO 2 and the feedstock. The influence of temperature and contact time was therefore investigated in this study. Extraction vessels with different volumes and different scCO 2 flows were used for this purpose. Increasing the temperature at the same scCO 2 density is decisive for increasing the yield. The yield decreases if the contact time is too low, as the scCO 2 cannot be fully saturated. GC-MS/FID analysis of the extracts and the residue shows a change in the extract composition over time and an enrichment of fatty acids in the extract and of diterpenoids in the residue.

Cellulose has inherent properties that are both hydrophilic and water-insoluble, which can create challenges in certain technical applications. One solution to these challenges is derivatization, however, the crystalline structure of cellulose limits its chemical reactivity. This study explores the reactivity of highly swollen cellulose produced by dissolving and reprecipitating microcrystalline cellulose. This extreme swelling of cellulose is expected to increase the accessibility and reactivity, however, upon drying the cellulose becomes hard and inflexible a phenomenon known as hornification. Different drying methods were used to overcome the problems of hornification, including freeze-drying, acetone-drying, and drying with glycerol as a spacer. The samples were carboxymethylated and the degree of substitution (DS) was used to assess reactivity, with freeze-dried samples showing the highest DS. The findings suggest that preserving the swollen structure through appropriate drying methods enhances cellulose reactivity, offering potential improvements in industrial cellulose ether production.

Extractives in wood, despite being vital in plant survival in adverse environmental conditions, can cause issues in pulping and papermaking, leading to significant financial losses within the forest industry. Conventional analysis is time consuming due to the challenging sample preparation, data interpretation and complex nature of extractives. There is a clear need for the development of a quick, non-destructive method for on-line pulp extractives monitoring. In this work, a machine learning-supported procedure for classification and prediction of extractives based on near infrared (NIR) and Raman spectroscopies was proposed. To avoid the influence of many variables, the method was developed and validated using a model compound approach, where cellulose was spiked with model extractives compounds. The accuracy of sample classification depending on the extractive added was 92.4 % based on NIR. The accuracy of classification of six samples containing different concentrations of the model compound using NIR data was 89.5 %. Partial least squares calibration model applied to pretreated NIR spectra yielded R 2 and root standard error of 0.78 and 0.35, respectively This means that the method could be used for non-selective quick estimation of extractive content with potential application to forest industry in process and fiber quality control in pulp and paper.