RespireAire develops artificial intelligence tools and data resources to improve how air quality is monitored, analyzed and . By combining large volumes of observations with advanced AI models and atmospheric simulations, the project provides precise, high-resolution air quality information to benefit public health, environmental research and policy-making.

Problem

Air pollution has major consequences for both human health and ecosystems, but its efficient control is constrained by the limited information used to monitor air pollution and the high computing cost of modern air quality models. Due to the gaps in data, unreliable measurements and expensive simulations, it is difficult to accurately evaluate air quality conditions and design effective mitigation strategies at local and regional scales.

Solution

RespireAire improves how air quality is assessed across Spain by combining air quality measurements, advanced atmospheric models and artificial intelligence. The project starts by collecting and checking monitoring data to ensure it is reliable. Since full atmospheric simulations are computationally expensive, RespireAire trains AI models to approximate the simulations’ behavior and produce similar results, much faster. By combining real measurements and fast AI models, RespireAire creates detailed air quality maps and analysis that help authorities and researchers better monitor pollution and plan actions to reduce it.