Agriculture is a productive sector that, together with forestry and other land use, produces approximately 21% of global GHG emissions1. Accurate measurement of agricultural soil GHG emissions is key not only to establish the proper role determination of agroecosystems as both source and sink in climate change2, but also to define appropriate and effective mitigation strategies within the framework of the Paris agreement targets.
Emission fluxes of the two most important GHGs produced by agricultural soils (i.e., N2O and CH4) are measurable by either micrometeorological methods or the closed-chamber technique3. The vast majority of studies reporting data on GHG emissions from soils over the past three decades applied the closed-chamber technique4,5 that was first described in 19266. Several efforts have been made to fine-tune the technique, and overcome all sources of experimental artifact and bias7,8,9,10,11,12,13,14. Specific protocols, compiled at different times, aimed to standardize the methodologies15,16,17,18,19, and scientific attempts are still underway to establish the best practices for employing the technique and minimizing bias in flux estimates.
The static closed-chamber technique, whose application to paddy soils is described in this paper, relies on the diffusion theory and provides the enclosure of a known volume of air above a portion of soil surface for a precise period. During the enclosure, CH4 and N2O molecules migrate by diffusion along a natural concentration gradient from soil pore air, where they are produced by specific microorganisms (methanogens in the case of CH4; nitrifiers and denitrifiers for N2O), to the air enclosed within chamber headspace, eventually through the flooding water or the plant aerenchyma. The concentrations of the two gases within the chamber headspace increase over time, and occurrence of these increases provides for flux estimates.
With respect to the micrometeorological methods, closed chamber measurements are often preferred for differing land use types and ecosystems when studying GHG fluxes at the plot scale, because they are not encumbered by a large homogenous field2 or high logistical and investment requirements20. Moreover, they allow the simultaneous analysis of manipulated experiments, such as different agronomical practices or other field treatments12,21. Finally, the technique allows identification of the relationships among ecosystem properties, processes, and fluxes. Alternatively, two main drawbacks of the technique include the relatively inefficient exploration of spatial and temporal heterogeneity, and the effects of soil disturbance due to chamber deployment22. However, these detriments can, at least partially, be overcome with: proper chamber design (to minimize soil disturbance), adoption of a sufficient number of replicates (to explore spatial variability), and automated system use that permits intensification of the frequency of daily measurements (to account for diurnal variability) or regular (same time of day) measurement (to omit the effect of temperature in residual variability).
A first application of the method to a paddy field dates back to the early 80's23, and the main peculiarities of its use with respect to upland fields are the presence of flooding water on soil and the need to include plants within the headspace during chamber enclosure. As carefully described in this paper, the first trait implies the need for specific systems to prevent water disturbance during measurement events, to avoid flux overestimates caused by turbulence-induced enhancement of gas diffusion through flooding water. The second essential trait is to account for gas transport through rice aerenchyma, representing up to 90% of emitted CH424, which requires proper devices to include plants during measurement events.