Waste is often reported as a management problem. Emissions are reported as a climate problem. This episode is about what happens when those two are finally treated as the same system. We dive into the Frontiers Planet Prize National Champion-Awarded Global Waste Sector Dataset (1990–2050), a harmonized resource spanning historical data through mid-century projections that explicitly links municipal solid waste generation to greenhouse gas emissions, while tying both back to the socioeconomic forces that drive them. Developed by Hoy, Woon, Chin, Fan, Yoo, and an international consortium of researchers, the dataset is framed not as a single study outcome, but as durable research infrastructure designed for reuse, comparison, and modeling. At its core, the dataset connects population growth and PPP-adjusted economic development to physical waste generation, then traces how that waste translates into carbon dioxide, methane, and nitrous oxide emissions through different treatment pathways. Historical data from major public sources—including the World Bank, OECD, Eurostat, and UNFCCC national reports—is rigorously harmonized before being extended into the future using Shared Socioeconomic Pathways (SSPs). Methodologically, the project is notable for how seriously it treats system complexity. Historical waste generation is reconstructed using fixed-effects panel regression to control for country-specific characteristics, while future emissions are modeled using country-level machine learning ensembles that capture nonlinear relationships—particularly critical for methane, whose climate impact is handled using GWP-STAR rather than conventional metrics. The result is a dataset that allows researchers to do more than track growth. It supports cross-country benchmarking, long-term decoupling analysis, and exploration of how waste management choices shape near- and long-term climate outcomes. By keeping waste generation and emissions structurally linked, the dataset avoids the common pitfall of treating climate impacts as detached from material flows. The authors are also explicit about the limits: national-scale resolution only, scenario-dependent futures, no explicit uncertainty intervals, and uneven country coverage driven by historical data availability. These constraints are documented as part of the dataset’s context, reinforcing responsible reuse rather than obscuring uncertainty. Delivered through a FAIR²-aligned data portal with persistent identifiers, rich metadata, and machine-actionable structure, this resource is designed to move directly into lifecycle assessment, climate modeling, and AI-driven analysis. If you’re interested in understanding waste not just as an output of consumption, but as a measurable driver of emissions across decades—and in how economic development, infrastructure, and climate impacts intersect at national scale—this episode offers a clear, integrated starting point. Hoy, Z.X., Woon, K.S., Chin, W.C., Fan, Y.V., & Yoo, S.J. (2025). Global Waste Sector Dataset (1990–2050): Scenario-Based Projections of Generation, Emissions, and Socioeconomic Drivers. Front. Environ. Sci., section Environmental Economics and Management. Data article: https://doi.org/10.3389/fenvs.2025.1717992. FAIR² Data portal: https://doi.org/10.71728/senscience.k2f7-p5v9. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit senscience.substack.com
