Effectiveness and Adaptability of Energy Retrofit Measures in Chinese Public Buildings: A Large-Scale Empirical Analysis

Energy efficiency retrofits are widely promoted for public buildings, yet evidence from large-scale real-world projects remains limited compared with simulation-based assessments. This study leverages measured pre- and post-retrofit operational data from 530 public building retrofit projects across 11 provinces/municipalities in China to quantify realized energy-saving performance and screening-level cost-effectiveness across building types and climate zones. Wilcoxon and Kruskal–Wallis tests were employed to ensure statistical rigor. Retrofit measures were grouped into seven categories (e.g., HVAC, lighting, envelope, monitoring/management), and a median-based four-quadrant framework was employed to characterize investment–savings profiles by climate zone and building function. Across the full sample, mean energy use intensity decreased by 19.1%, with 99.2% of projects achieving positive savings. Savings varied markedly by building type: commercial and hotels achieved the highest savings intensities (26.5–28.0 kWh/(m2·a)), while education and cultural buildings generally showed lower gains, with some projects having < 10 kWh/(m2·a). Technology performance exhibited distinct climate and building suitability. Envelope retrofits were most effective in the Cold and Hot Summer–Cold Winter zones (13.30–22.06 kWh/(m2·a)) but yielded limited benefits in the Hot Summer–Warm Winter zone (~1.73 kWh/(m2·a)). HVAC and lighting upgrades delivered comparatively stable savings across climates and building types and dominated retrofit portfolios. Based on these findings, we propose a tiered strategy: prioritizing HVAC and envelope upgrades for high-load sectors while focusing on low-cost optimizations for educational facilities to mitigate investment risks. The findings provide large-scale empirical evidence to support climate- and building-specific retrofit prioritization and investment decision-making under real-world operating conditions.