Urban mobility, air pollution, and climate change are critical concerns in contemporary city planning. This study presents the development and application of MAITEC®, a digital twin model designed to assess and enhance mobility and air quality within urban centers. The digital twin is designed to transform collected data into actionable insights, enabling informed decision-making by visualizing relevant consolidated data and identifying areas for intervention. By integrating data from the SUMO, MOVES, and AERMODE software, MAITEC® accurately simulates traffic flow, vehicular emissions, and pollutant ground concentration, including CO, CO2, HC, NOx, PM2.5, and PM10. The application of MAITEC® to the Tec District (Monterrey, Mexico) revealed significant emissions contributions from commercial trucks and passenger vehicles, with the highest levels of CO2 emissions attributed to public buses and commercial trucks. By calibrating emission factors based on real-world RSD emission measurements and traffic with real vehicle operating conditions obtained via OBD, we ensured the model's accuracy and relevance to the study area. The results indicate areas of opportunity for improving urban mobility, such as promoting intermodality, reducing vehicle infrastructure, and enhancing pedestrian accessibility. This research underscores the importance of up-to-date, high-quality data for effective simulation and offers actionable insights for policymakers aiming to foster sustainable urban development. The findings of this study validate the efficacy of the MAITEC® tool and highlight its potential for broader applications in urban mobility and environmental impact assessments.
