Aerodynamic flux-gradient measurements of ammonia over four spring seasons in grazed grassland: Environmental drivers, methodological challenges and uncertainties

Abstract

Understanding the factors controlling surface-atmosphere exchange of ammonia (NH3) in grazed grasslands is crucial for improving atmospheric models and addressing environmental concerns associated with reactive nitrogen. This study presents high-resolution NH3 flux data collected during four spring campaigns (2021-2024) at an intensively managed grassland site in Northwestern France, using the aerodynamic gradient method (AGM) alongside continuous monitoring of environmental variables and agricultural management. AGM-derived half-hourly NH3 fluxes exhibited distinctive patterns: (i) high variability during grazing from -113 (deposition) to +3205 (emission) ng NH3 m-2 s-1, influenced by meteorology, grazing livestock density, and vegetation and soil dynamics; (ii) strong diurnal patterns and day-to-day variability; and (iii) transient volatilisation peaks following slurry applications (up to 10 235 ng NH3 m-2 s-1). Grazing-induced emission fluxes often persisted for up to 1-2 weeks following cattle departure. Relative random uncertainties associated with AGM flux measurements typically ranged from 15 % to 70 %, based on errors in vertical concentration gradient slopes and variables related to turbulence and stability. Additional methodological limitations and systematic uncertainties are discussed, in particular errors associated with fundamental AGM assumptions and flux footprint attribution in a rotational grazing setup. The mean overall cattle head-based emission factor (EF) was 6.5 g NH3-N cow-1 grazing d-1 but varied considerably between grazing events, from 1 to 23 g NH3-N cow-1 grazing d-1, reflecting the interplay between livestock management and environmental factors. This study highlights the importance of long-term, continuous, high-resolution measurements to document the large variability in grazing-induced NH3 fluxes. The findings also underscore the need for refining bi-directional exchange models that integrate physics (meteorology, turbulence), environmental biogeochemistry (the fate of excreted nitrogen in the soil), biology (dynamic vegetation processes) and pasture management (grazing intensity) in grazed grassland systems.