The cellulose resource matrix

The emerging biobased economy is causing shifts from mineral fossil oil based resources towards renewable resources. Because of market mechanisms, current and new industries utilising renewable commodities, will attempt to secure their supply of resources. Cellulose is among these commodities, where large scale competition can be expected and already is observed for the traditional industries such as the paper industry. Cellulose and lignocellulosic raw materials (like wood and non-wood fibre crops) are being utilised in many industrial sectors. Due to the initiated transition towards biobased economy, these raw materials are intensively investigated also for new applications such as 2nd generation biofuels and 'green' chemicals and materials production (Clark, 2007; Lange, 2007; Petrus & Noordermeer, 2006; Ragauskas et al., 2006; Regalbuto, 2009). As lignocellulosic raw materials are available in variable quantities and qualities, unnecessary competition can be avoided via the choice of suitable raw materials for a target application. For example, utilisation of cellulose as carbohydrate source for ethanol production (Kabir Kazi et al., 2010) avoids the discussed competition with easier digestible carbohydrates (sugars, starch) deprived from the food supply chain. Also for cellulose use as a biopolymer several different competing markets can be distinguished. It is clear that these applications and markets will be influenced by large volume shifts. The world will have to reckon with the increase of competition and feedstock shortage (land use/biodiversity) (van Dam, de Klerk-Engels, Struik, & Rabbinge, 2005). It is of interest - in the context of sustainable development of the bioeconomy - to categorize the already available and emerging lignocellulosic resources in a matrix structure. When composing such "cellulose resource matrix" attention should be given to the quality aspects as well as to the available quantities and practical possibilities of processing the feedstock and the performance in the end-application. The cellulose resource matrix should become a practical tool for stakeholders to make choices regarding raw materials, process or market. Although there is a vast amount of scientific and economic information available on cellulose and lignocellulosic resources, the accessibility for the interested layman or entrepreneur is very difficult and the relevance of the numerous details in the larger context is limited. Translation of science to practical accessible information with modern data management and data integration tools is a challenge. Therefore, a detailed matrix structure was composed in which the different elements or entries of the matrix were identified and a tentative rough set up was made. The inventory includes current commodities and new cellulose containing and raw materials as well as exotic sources and specialties. Important chemical and physical properties of the different raw materials were identified for the use in processes and products. When available, the market data such as price and availability were recorded. Established and innovative cellulose extraction and refining processes were reviewed. The demands on the raw material for suitable processing were collected. Processing parameters known to affect the cellulose properties were listed. Current and expected emerging markets were surveyed as well as their different demands on cellulose raw materials and processes. The setting up of the cellulose matrix as a practical tool requires two steps Firstly, the reduction of the needed data by clustering of the characteristics of raw materials, processes and markets and secondly, the building of a database that can provide the answers to the questions from stakeholders with an indicative character. This paper describes the steps taken to achieve the defined clusters of most relevant and characteristic properties. These data can be expanded where required. More detailed specification can be obtained from the background literature and handbooks. Where gaps of information are identified, the research questions can be defined that will require further investigation. (C) 2012 Elsevier Ltd. All rights reserved