The safe operating space for greenhouse gas emissions from buildings

Abstract Purpose This paper proposes a model for estimating a regenerative greenhouse gas (GHG) emission budget for buildings, aligned with the planetary boundary for climate change. The model enables benchmarking of building-related emissions to a scientifically grounded threshold by converting radiative forcing into CO 2 -equivalents. The research addresses the question: What is the maximum annual GHG emission per square meter of floor area that enables regeneration back to the safe operating space behind the planetary boundaries? Methods The paper introduces a model to calculate an annual regenerative GHG budget per building based on planetary-scale sustainability thresholds. Two methods are used to estimate the global safe operating space for emissions: (1) a weighted average of substance-specific contributions updated with AR6 data and (2) characterisation factors derived from the Planetary Boundaries framework. These budgets are downscaled to the individual and service level using egalitarian and utilitarian allocation principles, illustrated via the ‘dwelling’ service. Sensitivity analyses explore the impact of input assumptions, including greenhouse gas data, allocation ethics, and political adjustments. Uncertainty in emission data and model assumptions—especially regarding CH 4 radiative efficiency and downscaling choices—are evaluated to inform the robustness of the proposed framework. Results and discussion The model yields a wide range of permissible GHG budgets (2.35–3.79 Gt CO₂-eq./year), depending on the method and assumptions applied. For a 128-m 2 residential building housing four people, the estimated annual regenerative budget is ~ 2.1 kg CO₂-eq./m 2 , varying significantly with the selected global budget, allocation principle, and population assumption. Method 1 proved more sensitive to GHG input updates, notably methane’s revised radiative efficiency in AR6. Subjective choices, including allocation ethics and political acceleration/deceleration of climate action, substantially influence outcomes. This reveals both the potential and complexity of applying planetary thresholds in building assessments. Conclusions The proposed model enables alignment of building life cycle assessments with the planetary boundary for climate change. However, it is highly sensitive to assumptions on input data, allocation principles, and political considerations. Despite these uncertainties, the model offers a transparent, science-based approach for setting regenerative emission targets in the built environment. Recommendations We recommend adopting conservative input assumptions (e.g., 95% confidence intervals), an egalitarian per capita approach to downscaling, and utilitarian proxies (e.g., consumption expenditure) for service allocation. Future model updates should incorporate new scientific insights (e.g., IPCC data) and evolving ethical considerations. The political adjustment factor should be used to transparently communicate trade-offs between risk and transition speed in climate policy for buildings.