Unveiling the role of chemical composition in dust-induced degradation of radiative cooling surfaces

Radiative cooling offers a zero-energy pathway to meet global cooling demands. However, its deployment is critically hampered by performance degradation from dust accumulation. Current models, which primarily consider dust deposition density, fail to capture the complex and composition-dependent nature of this degradation, leading to inaccurate performance predictions and suboptimal maintenance strategies. This study closes that critical knowledge gap by employing a Monte Carlo Ray Tracing (MCRT) model to quantify how key dust constituents (SiO₂, Al₂O₃, Fe₂O₃, C, and H₂O) uniquely impact performance. Our findings reveal a dichotomy in degradation mechanisms: low-absorption components (SiO₂, Al₂O₃, H₂O) induce a near-linear decrease in net cooling power, whereas high-absorption components (Fe₂O₃, C) exert an exponential influence. This effect is remarkably pronounced: an increase in Fe₂O₃ content from 0 % to just 5 % can catastrophically shift a dust-laden surface (5 g/m²) from a net cooling state (24.35 W/m²) to a net heating state (-10.2 W/m²). To translate these insights into a practical tool, we developed empirical correlations that predict performance loss as a function of dust characteristics. This work provides the mechanism-level understanding to accurately forecast the real-world performance of radiative cooling systems and enables the design of cost-effective cleaning strategies tailored to local environmental conditions.