Periodic Reporting for period 1 - NUTRITIVE (INNOVATIVE DECISION-MAKING TOOL FOR DEFINING THE MOST SUITABLE MANURE MANAGEMENT STRATEGIES TO ACHIEVE A SUSTAINABLE LIVESTOCK FARMING SYSTEM DURING THE WHOLE VALUE CHAIN)
Período documentado: 2024-06-01 hasta 2025-11-30
The European Green Deal calls for a transition towards more sustainable agriculture and food systems. Livestock production is economically and socially important, but manure management remains a major environmental hotspot. Along the manure-management chain, emissions of greenhouse gases and air pollutants (notably CH4, N2O and NH3) contribute to climate change and air-quality impacts, while inadequate storage and application can lead to nutrient losses and soil and water contamination. Beyond nutrients, manure may also transport emerging contaminants such as heavy metals, antibiotic residues, antimicrobial-resistant bacteria/genes and pathogens. Although numerous mitigation options exist, evidence on field performance, industrial viability, cost and feasibility is still fragmented across regions and production systems, and guidance is often not sufficiently tailored to farm conditions or aligned across regulatory levels.
NUTRITIVE addresses these gaps by developing a practical decision support system (DSS) that identifies the most efficient and sustainable manure-management strategy for a given livestock farm. The project will: (i) build an up-to-date inventory of practices, emissions and contamination risks; (ii) evaluate circular, innovative and cost-effective mitigation and valorisation options across the manure chain; (iii) optimise integrated strategies under realistic constraints; (iv) assess performance across environmental, economic and social dimensions; (v) produce simplified life-cycle assessment (LCA) models suitable for uptake; and (vi) translate results into technical guidelines and evidence-based policy recommendations. The consortium brings together 18 partners from 8 EU countries plus 4 partners from China and will work with more than 35 farms across multiple climate zones.
NUTRITIVE addresses these gaps by developing a practical decision support system (DSS) that identifies the most efficient and sustainable manure-management strategy for a given livestock farm. The project will: (i) build an up-to-date inventory of practices, emissions and contamination risks; (ii) evaluate circular, innovative and cost-effective mitigation and valorisation options across the manure chain; (iii) optimise integrated strategies under realistic constraints; (iv) assess performance across environmental, economic and social dimensions; (v) produce simplified life-cycle assessment (LCA) models suitable for uptake; and (vi) translate results into technical guidelines and evidence-based policy recommendations. The consortium brings together 18 partners from 8 EU countries plus 4 partners from China and will work with more than 35 farms across multiple climate zones.
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.
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.
Comparable, farm-relevant evidence on manure-management solutions is often limited by heterogeneous monitoring, non-aligned metrics and partial coverage of pollutants and scales. NUTRITIVE advances beyond the state of the art by delivering: harmonised EU-wide datasets for air, soil and water impacts under real farm conditions; an integrated portfolio of circular, cost-effective solutions that address conventional pollutants while explicitly accounting for emerging contaminants; predictive, mechanistic (non-black-box) bioprocess models coupled with improved fate/transport modelling for nutrients, pathogens and antibiotics under long-term, climate-aware scenarios; extended LCA methods including time-dependent and future-scenario approaches, simplified models for practical deployment, and links to social and economic performance; and a consistent integration pathway into a DSS capable of identifying best available techniques not entailing excessive costs (BATNEECs) across livestock types and regional contexts. Common indicators and aligned datasets enable cross-option ranking and clearer understanding of trade-offs between emission reduction, resource recovery and feasibility.