Quantifying NH3 Emissions in Naturally Ventilated Dairy Barns: A Decade of Methodological Advancements and Challenges

The quantification of ammonia (NH3) emissions from naturally ventilated dairy barns (NVBs) represents a complex measurement system challenge, where airflow variability, sensor configuration, and climatic conditions interact to determine overall uncertainty [1-2]. Although several studies have been conducted in recent years on dairy farms, monitoring emissions remains challenging as there is no universally validated Standard Reference Method (SRM), which limits comparability and scalability [3-4]. Moreover, there is a growing need for long-term monitoring systems capable of quantifying emissions accounting for seasonal variability and routine husbandry practices. This study presents an integrated technical and bibliometric analysis of measurement strategies adopted in NVBs over the last decade, focusing on methodological evolution, uncertainty propagation, and climatic representativeness. A geographical analysis of 81 peer-reviewed studies reveals a strong concentration of research activity in Northern and Central Europe, while Mediterranean systems (Italy, Spain, Portugal combined <10%) and warm-climate regions remain underrepresented. Most represented protocols are optimized for ridge-ventilated cubicle barns under temperate climates and may not be directly transferable to Mediterranean barns characterized by large lateral openings, mixed wind–buoyancy regimes, high solar loads, and weaker winter thermal gradients. Temporal analysis of methodological adoption shows clear consolidation around two dominant approaches: CO2 mass balance and direct airflow measurement using distributed anemometers. The first approach represents 37% of ap-plications, followed by direct airflow measurements with anemometers (21%). Modelling approaches are showing in-creasing adoption, including computational fluid dynamics (10%), wind tunnel studies (6%), and numerical or semi-mechanistic models (~5%), which are demonstrating their value as supporting tools. The CO2 balance method maintains stable application across years due to scalability and operational simplicity, whereas direct airflow measurement with anemometers promises to be SMR for validation of more feasible protocols and equivalent methods. Emission factors (EFs) reported in the dataset range between 0 and 2.4 g h⁻¹ LU⁻¹, with coefficients of variation approaching 50%, and part of this variability may be attributable to measurement configuration. Developing robust and scalable monitoring frameworks therefore requires structure-sensitive and climate-adaptable measurement protocols that explicitly account for specific external climate conditions, barn geometry, ventilation re-gime, and management practices, as these factors fundamentally influence airflow dynamics, pollutant dispersion, and overall measurement uncertainty.