Extreme climatic conditions, like heat waves or cold spells, associated to high concentrations of air pollutants are responsible for a broad range of effects on human health. Consequently, in the recent years, the question on how urban and peri-urban forests may improve both air quality and surface climate conditions at city-scale is receiving growing attention by scientists and policymakers, with previous studies demonstrating how nature-based solutions (NBS) may contribute to reduce the risk of population to be exposed to high pollutant levels and heat stress, preventing, thus, premature mortality. In this study we present a new modeling framework designed to simulate air quality and meteorological conditions from regional to urban scale, allowing thus to assess the impacts of both air pollution and heat stress on human health at urban level. To assess the model reliability, we evaluated the model's performances in reproducing several relevant meteorological, chemical, and biological variables. Results show how our modeling system can reliably reproduce the main meteorological, chemical, and biological variables over our study areas, thus this tool can be used to estimate the impact of air pollution and heat stress on human health. As an example of application, we show how common heat stress and air pollutant indices used for human health protection change when computed from regional to urban scale for the cities of Florence (Italy) and Aix en Provence (France). © 2024

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