D5.1 Initial preparatory and testing report in case studies

This deliverable, D5.1, is produced as the result of the first set of actions implemented within Tasks T5.1 to T5.5. It consolidates the information obtained from preparatory and ongoing testing activities across several key areas: the detection methods developed in WP1, the risk assessment and mapping methodology from WP4, the online sensor system from WP2, the AI-assisted platform also from WP4, and the MCDA framework from WP3. The report details the testing and validation of innovative analytical techniques for characterizing urban runoff pollutants, the refinement of risk assessment models through the integration of new field data, the evaluation of an online monitoring system under real-world conditions, and the deployment of an AI-driven decision support platform. Early findings indicate that the advanced detection methods have significantly improved our understanding of the pollutants present in urban runoff, while initial sensor tests reveal that further refinements in communication and system adjustments are necessary to address the complexities of natural samples. In addition, the risk assessment activities have provided valuable insights for model calibration, and the integration of GIS and real-time data underscores the need for standardized metadata and robust sensor connectivity.