持续性
木材加工
自然资源
生物多样性
气候变化
资产(计算机安全)
生化工程
业务
环境资源管理
自然资源经济学
环境科学
生态学
计算机科学
工程类
经济
计算机安全
生物
作者
Mark Schubert,Guido Panzarasa,Ingo Burgert
出处
期刊:Chemical Reviews
[American Chemical Society]
日期:2022-12-19
卷期号:123 (5): 1889-1924
被引量:16
标识
DOI:10.1021/acs.chemrev.2c00360
摘要
Wood is a renewable resource with excellent qualities and the potential to become a key element of a future bioeconomy. The increasing environmental awareness and drive to achieve sustainability is leading to a resurgence of research on wood materials. Nevertheless, the global climate changes and associated consequences will soon challenge the wood-value chains in several regions (e.g., central Europe). To cope with these challenges, it is necessary to rethink the current practice of wood sourcing and transformation. The goal of this review is to address the intrinsic natural diversity of wood, from its origin to its technological consequences for the present and future manufacturing of wood products. So far, industrial processes have been optimized to repress the variability of wood properties, enabling more efficient processing and production of reliable products. However, the need to preserve biodiversity and the impact of climate change on forests call for new wood processing techniques and green chemistry protocols for wood modification as enabling factors necessary for managing a more diverse wood provision in the future. This article discusses the past developments that have resulted in the current wood value chains and provides a perspective about how natural variability could be turned into an asset for making truly sustainable wood products. After briefly introducing the chemical and structural complexity of wood, the methods conventionally adopted for industrial homogenization and modification of wood are discussed in relation to their evolution toward increased sustainability. Finally, a perspective is given on technological potentials of machine learning techniques and of novel functional wood materials. Here the main message is that through a combination of sustainable forestry, adherence to green chemistry principles and adapted processes based on machine learning, the wood industry could not only overcome current challenges but also thrive in the near future despite the awaiting challenges.
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