A network of 32 case studies was defined and farm specifications collected to ensure representative coverage of systems and regional conditions. A harmonised sampling and analytical protocol was implemented to enable comparability of measurements across countries, including shared QA/QC rules, metadata templates and inter-laboratory alignment where relevant. Two seasonal campaigns were launched: Season 1 produced 30 manure, 77 soil and 26 water samples; Season 2 has so far added 7 manure and 13 water samples. Microbiological analyses of pathogens and antimicrobial-resistant bacteria were completed for all collected samples. Antibiotics were quantified in manure and soil samples (water quantification is ongoing). In parallel, farm questionnaires are being used to parameterise models of air emissions and management practices. A systematic evidence synthesis following PRISMA principles was initiated (27,379 records screened; 13,762 retained for further assessment).
A TRL3–6 laboratory and pilot demonstration framework was established to test mitigation strategies along the full manure-management chain using aligned methods and common performance indicators (efficiency, robustness, costs and operational constraints). The portfolio includes housing-level interventions (e.g. additives and dietary protein management), anaerobic digestion optimisation (including amendments such as biochar/zeolites, co-digestion and enhanced removal of antibiotics and antimicrobial-resistance determinants), biological nitrogen removal processes (nitrification–denitrification and anammox), nutrient/ammonia recovery (stripping, membrane and electro-processes), biomass-based valorisation routes (microalgae and purple phototrophic bacteria), and drying and soil-application validation across different soils and crops. Compliance checks are being performed for recovered products against relevant EU fertiliser requirements.
The modelling backbone was advanced to support robust comparison of options and hotspot identification. This includes mechanistic process models (combining flux-balance approaches with metabolic data), scenario models for leaching and soil/water contamination, and an LCA structure to benchmark technologies and practices. The assessment framework is being extended towards simplified, prospective and time-dependent applications, with uncertainty/sensitivity analyses to reflect variability across location, climate, production system and manure/feed characteristics. Data structures, interfaces and information flows have been defined to enable subsequent integration of experimental and modelling results into the online DSS.
