Knowledge-based policy making in the field of bio-based economy needs two elements: (i) a monitoring system for assessing the historical developments of bio-based industry and (ii) foresight capacities to provide prospects for the bio-based industry in the future and how it can contribute to achieving different targets. However, significant knowledge gaps in both areas exist, especially regarding the markets of bio-based materials in general and bio-based chemicals in particular. Against this background, a new consistent framework for the representation of the value chains of bio-based materials in the EU and its Member States is developed, i.e., BioMAT. This article aims to present the BioMAT database which (i) is used to track historical developments in the markets for bio-based chemicals and the demand for feedstocks and (ii) enables the construction of the BioMAT model to make future projections. The developed BioMAT database compilation procedure is described in detail. Results reveal that the production of bio-based chemicals in the EU reached 43 million tons or 14% of the total output volume of the organic chemical industry in 2018. The main application of bio-based chemicals is biofuels, followed by agrochemicals and surfactants. The main feedstocks are plant oils and starch.

Modelling is an important tool to support policy-making. A review of the existing bioeconomy modelling capacity indicates that most models focus on agriculture, forestry, and connected sectors of food, energy, and wood and paper products. Future development of bioeconomy modelling capacities should focus on including bio-based products such as textiles and plastics, and especially chemicals and pharmaceuticals. To address such gaps in existing capacities, the BioMonitor Model Toolbox has been developed; it is composed of five improved bioeconomy models to support policy-makers in executing consistent, coherent, and longer-term strategies with desirable consequences for multiple objectives. Further model development needs to consider key processes such as technological change (or innovation), circularity, consumer behaviour, climate change, and biodiversity. Whereas concepts like circularity could be included in existing models with reasonable effort, other important concepts require the development of new models that build on emerging modelling techniques.