Quantification of nitrous oxide (N2O) emissions in a managed grassland following nitrogen fertilisation: A comparative analysis of cumulative emissions determined by automated and manual chamber methods

Abstract

Accurate quantification of nitrous oxide (N 2 O) emissions from grasslands remains challenging owing to their episodic, spatially heterogeneous and diurnally variable nature. This study compared automated chamber (AC) and manual chamber (MC) methods to evaluate the influence of chamber methodology on N 2 O emissions following nitrogen (N) fertilisation. A field experiment was conducted on a perennial ryegrass ( Lolium perenne ) sward using 16 plots arranged in four replicate blocks, with paired AC and MC installed in each plot. Nitrogen fertilisers were applied in five equal splits of 40 kg N ha −1 , giving a total of 200 kg N ha −1 yr −1 , and fluxes were monitored for eight months. During the measurement period, N 2 O fluxes showed pronounced temporal variability, including sub-daily fluctuations and hot moments following fertilisation, particularly when N inputs coincided with increases in soil moisture or dry–rewetting transitions. Daily N 2 O N fluxes ranged from -0.52 to 191.47 g ha −1 d −1 for AC and -1.64 to 95.21 g ha −1 d −1 for MC. Although both methods captured similar seasonal dynamics, AC detected more hot moments and low-magnitude fluxes than MC. Cumulative N 2 O N emissions and partial emission factors ( 𝐸 ⁢ 𝐹 𝑝 ) were on average 52 % and 74 % higher, respectively, for AC than MC. These discrepancies may partly reflect differences in headspace mixing, enclosure duration, analytical sensitivity and flux-calculation approaches. Diurnal variability and sampling time influenced daily N 2 O N estimates, but no fixed sampling hour represented the 24 h AC-derived daily mean, particularly during hot-moment days. Simulated MC sampling schemes revealed that sampling frequency influenced cumulative emissions more than sampling hour, with hybrid schemes combining routine background sampling and intensified event-period sampling providing the best overall balance between daily error and relative bias in cumulative N 2 O emissions. Overall, this study shows that method selection influences N 2 O estimates and that high-resolution measurements can inform MC sampling design, EF development and Tier 2 inventories.