The SMOG project has as its main objective the development of a comprehensive service for monitoring pollutant and greenhouse gases generated by human activity, with the aim of providing accurate and timely information to public administrations, legislators, and certification companies. This service seeks to ensure that emissions remain within acceptable limits for public health and the quality of urban and natural environments, as well as to minimize the effects of climate change. Nitrogen dioxide (NO₂) is established as the main indicator, with its monitoring and dispersion in urban and industrial areas being used as a relevant case study for the development and verification of the technological functionalities of the service.
To achieve an increase in spatial sampling, the project is based on the development of mobile devices equipped with low-cost sensors, preferably electrochemical for gases and optical particle counters (OPC) for PM, which can be integrated into vehicles. A critical aspect is the calibration and validation of these mobile sensors. This will be carried out using a mass spectrometry system at the CTTC-UPC laboratory, complemented by data from high-precision fixed stations (such as the Terrassa station), thus ensuring the reliability of the readings. These precise measurements are essential for the subsequent validation of gas dispersion models.
Another technological pillar is the development of dispersion models. The feasibility of including satellite images, such as those obtained from missions like Sentinel-5P (TROPOMI) and future micro-satellite constellations (Open Constellation), is being investigated to obtain pollution data. In parallel, gas dispersion models are being developed based on computational fluid dynamics and mass transfer (CFD/HT) techniques, using high-performance computing (HPC) and the CTTC’s TermoFluids library, to simulate contaminant diffusion with high precision. These advanced models will be used to calibrate artificial intelligence (AI)-based prediction models from Lobelia, which aim to provide high-resolution, low-latency urban air quality mapping.
Finally, the project foresees the development of a Data Management and Interoperability System to integrate and manage heterogeneous data (satellite images, fixed and mobile sensors), with the goal of facilitating access to information and generating high value-added services. The success of the project, measured by indicators such as a reduction in uncertainty in gas prediction (NO₂ RMSE from 13 to 9 µg/m³) and an improvement in satellite temporal resolution (from 1 day to 3 hours), will enable the creation of new business models, better adaptation to and mitigation of climate change, and the generation of jobs and new investments.