The level of expertise required to operate and maintained the system is very high. Thus the transfer of technology, even accompanied by capacity building actions, is not suitable. The consortium is now in contact with third-parties that could potentially act as “exploiter”. The partners would provide expertise through service contracts with the exploiter(s).

Depending on its available resources and level of expertise, the future exploiters may decide to take over the activities at different stages of the value-chains.

The system is up and running. Adaptations may be needed to meet the requirements of the co-exploiter.

The dust forecast component’s replicability lies in its reliance on established models like CAMS, SILAM, and MONARCH. These models are well-documented, open-source, and extensively validated, enabling easy adoption by air quality management entities worldwide. The data products, including AOD, surface concentration, deposition, and solar irradiance, can be integrated into existing air quality monitoring systems, enhancing predictive capabilities. The multi-model ensemble approach ensures robustness across different regions, facilitating adaptation to various geographical contexts.

The replicability of the fire smoke forecast component is grounded in the use of globally recognized models such as IS4FIRES-SILAM and WRF-Chem. These models incorporate proven tracking methods and are well-documented, making them accessible to air quality professionals globally. The focus on CO and PM2.5, key indicators of fire impact, enables straightforward integration into existing air quality management frameworks. This component’s use of operational approaches ensures familiarity for adoption, while its provision of localized fire-induced CO and PM2.5 concentration information enhances the ability to assess and respond to wildfire effects.