A statistical approach to surface renewal: The virtual chamber concept

Abstract

Abstract In the stable conditions prevailing at night, concentrations of emitted gases (e.g., radon [Rn], carbon dioxide [CO2], methane [CH4], ammonia [NH3], and nitrous oxide [N2O]) build up at the surface, with intermittent interruptions due to the passage of packets of turbulence. The applicability of conventional experimental methods is then questionable. Here, a statistical approach is proposed, in which micrometeorological field data are used to replicate the likely characteristics of a chamber experiment, yielding estimates of surface fluxes at the surface itself with reduced requirement for adequate fetch. Application of the virtual chamber methodology to two recent field studies is explored: (a) a study of nocturnal CO2 emission from a farmland area in Ohio in 2015; and (b) an investigation of NH3 effluxes from a crop previously treated with urea ammonium nitrate (UAN) in Illinois in 2014. For both datasets, the virtual chamber approach yields results in general agreement with eddy covariance (EC) data.