AERQ: Leveraging IoT and HPC for Urban Air Quality Monitoring

Emerging technologies such as the Internet of Things (IoT), big data, mobile devices, high-performance computing, and advanced modeling are reshaping urban management. When integrated with conventional tools, these innovations enable smarter governance—particularly in air quality control—improving public health and quality of life. Yet, urban expansion driven by economic growth continues to worsen pollution and its health impacts. This study presents AERQ, a decision support system (DSS) designed to address urban air quality challenges through real-time sensor data and the AERMOD dispersion model. Applied to Cagliari (Italy), AERQ is used to evaluate key traffic-related pollutants (CO, PM, NO2) and simulate mitigation scenarios. Results are delivered via a user-friendly web-based platform for policymakers, technicians, and citizens. AERQ supports data-driven planning and near real-time responses, demonstrating the potential of integrated digital tools for sustainable urban governance. In the case study, it achieved 10 m spatial and 1 h temporal resolution, while reducing simulation time by 99%—delivering detailed five-year scenarios in just 15 h.