Simulating Atmospheric Radiation to Test Passive Radiative Cooling Materials

Passive radiative cooling (PRC) is a natural process in which surfaces radiate heat to outer space through the 8–14 µm transparent atmospheric window. Recently, a new class of materials has emerged, which can generate sub-ambient cooling when exposed to the sky, even under direct solar illumination. To achieve this effect, these materials combine high solar reflectance and strong thermal infrared emissivity. It is estimated that 10% of global greenhouse gas emissions are related to cooling buildings and environments. PRC materials provide a renewable and electricity-free method to cool down an object and could be an efficient alternative to conventional systems. However, their outdoor testing is subject to significant uncertainty due to variable atmospheric conditions and lack of accessible methods to estimate the important contribution of downwelling atmospheric irradiance. To fill this gap, the PaRaMetriC project is developing a metrological framework to classify and improve reproducibility in the comparison of PRC materials. It also focuses on characterizing the properties of PRC materials and develops modeling methods, setting standards for quality control, and allowing long-term effectiveness to be evaluated. To assess material performance and model their behavior at multiple scales (from in-field testing setups to buildings and up to urban areas) it is critical to consider realistic atmospheric conditions. To date, in fact, downwelling atmospheric irradiance and transmittance are not measured during the testing of PRC materials, and often simply extrapolated using heuristic models based on ground level readings of air temperature and humidity. Conversely, accounting for the full vertical distribution of these quantities, and the presence of distinct types of clouds could help explain many of the striking PRC performance inconsistencies reported in the literature. In this contribution, we present a set of simulations of the downwelling infrared radiation resolved in spectral bands, together with atmospheric variables, to be used as tool in this context, and show results of the on-going modeling work towards the release of a publicly available tool to generate data relative to different dates, regions, and climatic conditions.