Methodology paper - Composition data collection and consolidation

The FutuRaM project aims to develop the Urban Mine Platform, a comprehensive knowledge base on the availability and recoverability of secondary raw materials across the European Union, Iceland, Norway, Switzerland, and the United Kingdom. The project focuses on six main waste streams: waste batteries, end-of-life vehicles, waste electrical and electronic equipment, construction and demolition waste from buildings and wind turbines, slags and ashes, and mining waste. These waste streams represent significant sources of critical and strategic raw materials. To estimate the availability of secondary raw materials from 2010 to 2050 under different scenarios, the project develops stock, flow, and recovery models based on detailed composition data. This data describes the structure of products, their components and material fractions, and elemental content, providing essential insights into the quantity, distribution, and potential recovery of critical raw materials in waste streams. The aim of milestone 23 of the FutuRaM project is to provide consolidated composition datasets for all waste streams that can be used for subsequent stock and flow and recovery modelling as well as for recoverability and secondary raw material assessment. The FutuRaM composition data structure distinguishes between hierarchical layers within a waste stock or flow. Each layer in the hierarchy is composed of the entities of the previous one. This hierarchical structure enables a systematic and scalable description of composition across diverse waste streams. To better reflect the varying characteristics of the waste streams, the composition data model employs two distinct approaches, a product-centric approach and a deposit-centric approach. Based on this structure, composition data was collected using specifically developed templates enabling the collection of data according to the composition data model from various sources. For the consolidation of the collected raw data, a harmonized method was developed in order to transform the scattered raw data into consistent and generic datasets with the average composition of relevant products (or product groups) and waste stocks and flows. Data points with different data structures and levels of detail can be combined into generic compositions for products and waste stocks and flows by transforming them into the desired data structure and defining appropriate levels of detail. This methodology paper provides an overview of the composition data collection for each waste stream. The consolidation method is described and specifications for each waste stream illustrated. Challenges during the process are highlighted and recommendations for further improvement of the processes are provided. Furthermore, in this methodology paper, the considerations regarding future composition and composition data validation are presented.