Global Waste Sector Dataset (1990–2050): Generation, Emissions, and Socioeconomic Drivers

Strategy planning for global climate goals requires structured, multisectoral data linking environmental pressures with socioeconomic drivers across time and geography. However, internationally harmonized, machine-actionable datasets integrating waste generation, waste-related greenhouse gas (GHG) emissions, and socioeconomic indicators remain scarce. This study provides a harmonized, AI-ready dataset to support global analyses of municipal solid waste (MSW) and associated emissions. This FAIR² dataset provides historical (1990–2020) and forecasted (2021–2050) national-level data for 43 countries, covering MSW generation, CO₂, CH₄, and N₂O emissions, GDP per capita (PPP), and population. Forecasts were generated using an ensemble of fixed-effects regression models and artificial neural networks informed by economic and demographic trends. By linking MSW, emissions, and socioeconomic drivers within a standardized structure, the dataset enables analyses including benchmarking, equity assessments, and decoupling analysis. While limited to national aggregates and subject to scenario uncertainty, the dataset complies with FAIR² principles, supporting reuse and traceability.