Volume 19 Issue 4

Forest and biomass resource utilization for bioenergy and bioproducts is crucial for mitigating climate change and promoting a sustainable bioeconomy. Given that the biomass supply chain is a complex system, one of the most concerning issues is selecting and using appropriate modeling and analytical technologies to optimize the advantages of multi-feedstock biomass supply chains. Machine learning (ML) can enhance biomass supply chain management (BSCM) efficiency and sustainability. It can address the complexities in cultivation, harvesting, preprocessing, storage, transportation, and conversion. ML workflows involve data collection, preprocessing, model training, and optimization, using algorithms for prediction and decision-making. Accurate supply and demand forecasting via ML improves production planning and inventory management. Despite its potential, ML applications in BSCM need to deal with challenges such as data availability and quality, interpretability of models, and their generalization capabilities. Overcoming such challenges requires interdisciplinary efforts in data management and model development to fully leverage ML’s applicability.

The US and the EU have adopted contrasting pathways in their pursuit of increased sustainability. This editorial highlights such contrasts with respect to paper and nonwovens products. The American way, at least at the federal level, depends on consumer input, which can have an impact on corporate decisions and practices. Progress with respect to sustainability in the European Union has a higher reliance upon regulations. Each approach has merits as well as deficiencies. A regulation-dependent approach sometimes just moves problems to other parts of the world. A consumer-driven approach does not have a good way to deal with a need for systematic change, such as systems to recycle textile and nonwoven materials. It follows that a combined approach, involving both consumer demand and regulations, can be recommended as a most effective path forward. In addition, applications of artificial intelligence have potential to reconcile societal needs with future industrial practices.

Lignin, a subject of extensive study in academies and industries, is known for its natural abundance, biodegradability, and potential to be transformed into biochemicals and biomaterials. However, the original biomass and extraction treatments, such as kraft pulping and the organosolv process, significantly influence its chemical structure, leading to variations in reactivity. Unfortunately, many scientific publications fail to provide comprehensive lignin property descriptions, which hampers experiment reproducibility and literature comparison. This, in turn, hinders fundamental studies and scientific advancements. This editorial aims to address this issue by advocating for including lignin characteristics in scientific papers when possible.

In recent years, lignocellulosic materials have become regarded as attractive and noteworthy natural resources owing to their renewability, recyclability, easy processability, abundance, biodegradability, and low cost. The developments in nanotechnology have opened new doors in the field of bio-based nanosensor technology, which is utilized in electronics, optical products, communication, automotive, packaging, tissue engineering, biomedical, textile, etc. This paper mainly focuses on the usage of lignocellulosic materials in nanosensors.

Trees represent a cherished treasure for each nation. They provide a living, soulful, and earthly material, wood, which most often survives millennia and embellishes our everyday life. Wood can be transformed into valuable pieces of art under skilled hands and tools through carving. In Romania, wood is omnipresent in each milepost of people’s life journey from birth to death. It becomes a true and empathic companion of both happy and sad events. Wood teaches us to focus on the present moment and to let go of stressful thoughts and feelings. It is a real valuable “good” in our life.

This editorial draws a parallel between important papermaking innovations that were implemented by Mahatma Gandhi and some more recent ventures in papermaking in India. Both of these examples share common themes of fostering the skills of local people, using local resources, and contributing to a better future. A key insight is the scaling of the equipment to be well matched with the size of the production team and enabling a broad range of product grades. The case study considered introduces a modern twist – using papermaking to achieve circularity in the production of textiles. As in the early days of European papermaking, once again waste textile products are serving as the primary source of material.