Linking problems with solutions: Biomass waste is where most needed to mitigate energy demand during tropical nights

Abstract

As climate projections indicate a rise in extreme heat events during the 21st century, the earlier occurrence of tropical nights (daily minimum temperature > 20 °C) is expected to intensify indoor thermal discomfort and increase cooling-related energy demand. Biomass waste offers a potential clean energy alternative, yet its effective deployment requires spatially explicit assessments of both cooling needs and biomass resource availability. This study leverages the high spatial resolution capabilities of the SDGSAT-1 Thermal Infrared Sensor (TIS) to characterize the spatial distribution of the first tropical night during 2023 across a Mediterranean climate change hotspot. We derived the SDGSAT-1 TIS-based RI2 thermal radiation index to map fine-scale thermal heterogeneity and integrated these remote sensing products into a Bayesian time-to-event survival framework to quantify how urban thermal properties influence the hazard rate of tropical night occurrence. Additionally, spatially explicit municipal biomass-based energy density estimates were coupled with model outputs to assess the alignment between thermal exposure and renewable energy potential. Results reveal pronounced spatial gradients, with populated coastal areas and major inland urban centers exhibiting the earliest tropical nights, followed by a progressive inland expansion. The RI2 index showed a significant negative association with the timing of the first tropical night, corresponding to a 17% reduction in the baseline hazard rate, and highlighting the cooling influence of vegetated surfaces and water bodies captured by SDGSAT-1 TIS. Earlier tropical nights were concentrated in thermally intense built-up environments. Importantly, populated locations with high energy density spatially coincided with areas experiencing early tropical nights. These findings demonstrate the value of SDGSAT-1 TIS fine-scale data for urban heat hazard modeling and illustrate how satellite-derived products can support evidence-based planning for sustainable cooling and energy resilience.