Global Research Alliance N2 O chamber methodology guidelines: Statistical considerations, emission factor calculation, and data reporting.

Static chambers are often used for measuring nitrous oxide (N2 O) fluxes from soils, but statistical analysis of chamber data is challenged by the inherently heterogeneous nature of N2 O fluxes. Because N2 O chamber measurements are commonly used to assess N2 O mitigation strategies or to determine country-specific emission factors (EFs) for calculating national greenhouse gas inventories, it is important that statistical analysis of the data is sound and that EFs are robustly estimated. This paper is one of a series of articles that provide guidance on different aspects of N2 O chamber methodologies. Here, we discuss the challenges associated with statistical analysis of heterogeneous data, by summarizing statistical approaches used in recent publications and providing guidance on assessing normality and options for transforming data that follow a non-normal distribution. We also recommend minimum requirements for reporting of experimental and metadata of N2 O studies to ensure that the robustness of the results can be reliably evaluated. This includes detailed information on the experimental site, methodology and measurement procedures, gas analysis, data and statistical analyses, and approaches to generate EFs, as well as results of ancillary measurements. The reliability, robustness, and comparability of soil N2 O emissions data will be improved through (a) application, and reporting, of more rigorous methodological standards by researchers and (b) greater vigilance by reviewers and scientific editors to ensure that all necessary information is reported in scientific publications.

Global Research Alliance N2 O chamber methodology guidelines: Flux calculations.

A critical step in determining soil-to-atmosphere nitrous oxide (N2 O) exchange using non-steady-state chambers is converting collected gas concentration versus time data to flux values using a flux calculation (FC) scheme. It is well documented that different FC schemes can produce different flux estimates for a given set of data. Available schemes differ in their theoretical basis, computational requirements, and performance in terms of both accuracy and precision. Nonlinear schemes tend to increase accuracy compared with linear regression but can also decrease precision. The chamber bias correction method can be used if soil physical data are available, but this introduces additional sources of error. Here, the essential theoretical and practical aspects of the most commonly used FC schemes are described as a basis for their selection and use. A gold standard approach for application and selection of FC schemes is presented, as well as alternative approaches based on availability of soil physical property data and intensity of sample collection during each chamber deployment. Additional criteria for scheme selection are provided in the form of an error analysis tool that quantifies performance with respect to both accuracy and precision based on chamber dimensions and sampling duration, soil properties, and analytical measurement precision. Example error analyses are presented for hypothetical conditions illustrating how such analysis can be used to guide FC scheme selection, estimate bias, and inform design of chambers and sampling regimes.