Predicting and alleviating urban heat stress for early adolescents: an integrated environmental and physiological study

With the increasing frequency of extreme heat events and the intensification of the urban heat island effect, thermal safety for children in outdoor urban environments has become a critical concern. Traditional heat stress indicators have limited applicability for early adolescents, leading to ambiguous predictions. Using experimental data collected from 36 junior high school students (aged 12 ± 1 years) in Nanning, China, from June to August 2024, we introduced an enhanced two-node model integrated with a genetic algorithm to predict and mitigate heat stress. Through real-time monitoring of core/skin temperatures and microclimate data via wireless sensors and a mobile thermal comfort device, four key physiological parameters in the model were optimized. The optimized model improved the predictive accuracy for group trends in skin and core temperatures, reducing the RMSE by 76.07% and 75.86%, respectively. Furthermore, by incorporating six spatial scenarios with different shading conditions and underlying surfaces into ENVI-met, the model quantitatively revealed significant effects of various environmental factors on the body temperature changes of early adolescents (p < 0.05). This study lays a theoretical foundation for evidence-based child-friendly design strategies and provides scientific support for protecting adolescents’ health in the context of climate change.