Air Quality Forecasting : Turning Environmental Data into Actionable Insigh

From national forecasting systems to digital twins and AI-enhanced modelling, air quality forecasting is becoming an increasingly powerful tool for decision-makers. Today, organisations need more than monitoring alone. They need the ability to predict future air quality conditions and the associated impacts and consequences, assess the impact of policy interventions and investment decisions, and take proactive action to protect communities and the environment.

At SUEZ Air & Climate, we are helping cities, utilities and governments move beyond measuring air pollution to forecasting and scenario assessment. By combining atmospheric science, digital technologies, Earth Observation and advanced modelling, we are delivering tools that support better environmental decisions at local, regional and national scales. Recent projects highlight how forecasting capabilities are evolving to meet a wide range of air quality challenges.

One example is CyberItaly, an ambitious initiative to build a digital twin of Italy. As part of the project, advanced air quality models are being used to rapidly assess the impact of traffic and urban planning strategies before they are implemented in the real world. Using innovative modelling techniques, decision-makers can test scenarios such as traffic restrictions, pedestrian zones or uptake of electric vehicles and understand how air quality is likely to respond. This enables evidence-based policy development, helping authorities evaluate measures before committing resources to implementation.

In the Kingdom of Saudi Arabia, SUEZ delivered the National Air Quality Modelling and Forecasting System on behalf of the National Center for Environmental Compliance (NCEC), supporting the management of air quality across the country. Operational since 2022, the system provides comprehensive forecasting capabilities from national scale coverage down to street-level resolution in six major cities, including Riyadh, Jeddah, Mecca, Yanbu, Dammam and Medina. By integrating advanced atmospheric modelling, forecasting and environmental data, the platform enables authorities to anticipate air quality events, assess potential impacts and support informed decision-making. Following the programme’s success, SUEZ was selected in 2026 to upgrade the system, continue operations and maintenance, and enhance industrial incident response through an Emergency Response System.

In Kuwait, SUEZ Air & Climate has supported the development of KAQFS, the country's operational air quality forecasting system. Running automatically every night, the system combines meteorological forecasts, emissions inventories and state-of-the-art atmospheric models to predict pollution levels across the country up to three days in advance. Covering the entire territory at a resolution of one kilometre, KAQFS provides daily air quality maps and indicators that support both government decision-making and public information. By complementing fixed monitoring stations with predictive insight, the system helps authorities anticipate pollution events and respond more effectively.

Meanwhile, in Hanoi, work is underway to develop an integrated air quality forecasting chain that links regional forecasting with detailed urban-scale modelling. The project has a particular focus on supporting the assessment of Low Emission Zones (LEZs), an increasingly important tool for improving urban air quality. By combining large-scale forecasts with street-level modelling and scenario analysis, the system will help planners understand how different transport policies could affect pollution levels across the city. The result will be a powerful decision-support platform capable of informing future sustainable mobility strategies.

Innovation is also being driven through European research initiatives. Within the CLEAR-EO project, SUEZ Air & Climate teams are developing new approaches that combine satellite observations, atmospheric modelling and machine learning to improve air quality forecasts. By integrating data from Sentinel Earth Observation satellites with deterministic air quality models such as CHIMERE and ground-based measurements, the project aims to generate more accurate forecasts and deeper environmental insight. Demonstrated in the Marseille region of France, this work showcases the growing role that artificial intelligence and satellite data can play in environmental management.  

While these projects vary in scale and application, they share a common objective: transforming environmental data into actionable information. Whether supporting national forecasting systems, evaluating future policy scenarios, planning Low Emission Zones or enhancing predictions through AI, air quality forecasting is helping organisations make smarter decisions.

As cities and governments face increasing pressure to improve air quality, protect public health and meet sustainability goals, forecasting capabilities will continue to play a critical role. By combining advanced modelling, Earth Observation, machine learning and digital twin technologies, SUEZ Air & Climate is helping organisations better understand, predict and manage air quality challenges both today and in the future.