Suggested CitationĪll material on this site has been provided by the respective publishers and authors. This article met the requirements for a gold‐gold data openness badge described at. However, the scarcity, documentation, and quality of input data are key limitations for more accurate and detailed end‐use shares. Despite mixed results, combining MIOT‐based end‐use shares with industry shipments and auxiliary country‐level data could enable improved temporal, geographical, and end‐use resolution. For EXIOBASE3, we find good fit for some countries and materials, but substantial mismatches for others. In many cases, the temporal trend of MIOT‐derived end‐use shares roughly agrees with industry shipments. We find mixed results regarding the fit between end‐use shares derived from industry shipments and MIOTs: for detailed national data, we find good fit for some materials (e.g., aluminum), while others deviate strongly (e.g., steel). In closing, we conclude on 12 points for improved end‐use shares. To better match MIOT and dMFA system definitions, we propose the end‐use transfer method, which re‐routes specific intermediate outputs to final demand in MIOTs. ![]() Herein, we comparatively apply these methods to the United States, drawing on detailed national data, as well as the multi‐regional input–output model EXIOBASE3. ![]() Therefore, in part 1 of this work, we reviewed five methods to derive material end‐use shares which use industry shipment data in physical units and monetary input–output tables (MIOTs). Momentarily, studies on inflow‐driven, dynamic material flow analysis (dMFA) extrapolate scarce information on material end‐use shares (i.e., ratios that split economy‐wide material consumption to different end‐use products) for single countries and years across longer time periods and global regions. Modeling pathways toward sustainable production and consumption requires improved spatio‐temporal and material coverage of end‐use product stocks.
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