1. Introduction

The transition to a circular economy (CE) is high on the agenda of many governments (Rijksoverheid, 2016; SITRA, 2016; Yuan et al., 2006;) and international institutions such as the EU and UN (European Commission, 2021; UNECE, 2021) as a means to realize a more sustainable economy. For example, the Dutch government aims to reach 50% circularity in 2030 and fully transform to a circular economy by 2050. At its core CE is a sustainability concept focusing on resource productivity (Blomsma and Brennan, 2017), specifically by reducing resource use, reusing materials and products (Kirchherr et al., 2017), and by substituting hazardous and non-renewable materials with more sustainable alternatives.

The transition to a CE calls for monitoring of material flows at the macro-economic level. Various indicators, tools and methods have been developed for this purpose (e.g., Geng et al., 2012; Jacobi et al., 2018; Mayer et al., 2019; Moriguchi, 2007; Aguilar-Hernandez et al., 2019). This diversity in itself is a challenge as these indicators lack comparability. Furthermore, most databases underlying such studies were developed on an ad hoc basis and therefore have not resulted in consistent time series (e.g., Merciai and Schmidt, 2018). Many material flow indicators (e.g., waste streams, reuse of materials) are disconnected from economic indicators (e.g., value added, employment) while circular economy monitoring inherently necessitates integration of such indicators.

Based on the monitoring challenges outlined above, Statistics Netherlands asked itself the following question: How can existing statistical data be integrated into a consistent database to monitor material flows in the Dutch economy? This question was addressed by developing the Material Flow Monitor database (MFM) which is now one of the pillars of Dutch circular economy monitoring efforts (see Hanemaaijer et al., 2021). The MFM is essentially a Physical Supply and Use Table (P-SUT). It is based on existing national economic-environmental accounting statistics and updated every two years to monitor developments of the material flows. It is used to monitor material flows in the Dutch economy and to calculate circular economy and bio-economy indicators.

In this study, we describe the steps and data used to compile the Dutch MFM and showcase the possibilities and limitations of using this state-of-the-art national MFM at different aggregation levels. Section 2 briefly reviews earlier work by the academic community and by Statistics Netherlands on which the MFM builds conceptually. Section 3 follows, explaining the principles and datasets used to create the MFM. Section 4 then showcases the potential of this database with a case study of the MFM for monitoring the bio-economy. Finally, section 5 discusses the possibilities and limitations of the MFM and draws conclusions.