A numerical evaluation of chamber methods for determining gas fluxes

Abstract

Mathematical simulations of nitrous

CO<sub>2</sub> flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression

“…However, most studies concerning this issue were conducted for the gas exchange of bare soil surfaces. Matthias et al (1978) showed for numerical simulations of closed chamber experiments with closure times of 20 min that N 2 O emissions could be underestimated by as much as 55% by linear regression. Quadratic regression still underestimated the real fluxes by up to 25%.…”

“…Sources of errors are (1) inaccurate determination of the headspace volume (Livingston and Hutchinson, 1995), (2) leakage directly at the chamber components or via the underlying soil pore space (Hutchinson and Livingston, 2001;Livingston et al, 2006), (3) temperature changes of the soil and the atmosphere beneath the chamber (Wagner and Reicosky, 1992;Drösler, 2005), (4) artificial water vapour accumulation which depletes the CO 2 concentration and might influence the stomata regulation of plants (Welles et al, 2001), (5) disturbance of pressure gradients across the soil-atmosphere interface by soil compression or insufficient pressure relief during chamber setting (Hutchinson and Livingston, 2001;Livingston et al, 2006), (6) suppression of the natural pressure fluctuations (Hutchinson and Mosier, 1981;Conen and Smith, 1998;Hutchinson and Livingston, 2001), (7) alteration or even elimination of advection and turbulence and thus modification of the diffusion resistance of the soil-or plant-atmosphere boundary layer (Hanson et al, 1993;Le Dantec et al, 1999, Hutchinson et al, 2000Denmead and Reicosky, 2003;Reicosky, 2003), and (8) the concentration build-up or reduction within the chamber headspace that inherently disturbs the underlying concentration gradients that were in effect prior to chamber deployment (e.g. Matthias et al, 1978;Hutchinson et al, 2000;Livingston et al, 2006). This study focuses on the latter problem, which can lead to serious bias of CO 2 fluxes if not accounted for, even if all other potential errors were kept at minimum.…”

Theory and Laboratory Study of a Tall Passive Chamber for Measuring Gas Fluxes at Soil Surface

“…24,25 The solution of eqs 10, 11, and 12 is (13) Thus, the mass of the target chemical in gaseous phase (M gas ) residing in the soil layer at the end of each individual test is (14) where a is the volumetric air content of the soil layer, A s is the cross-section area of the soil layer, and L is the length of the soil layer. The mass in the sorbed phase (M sorbed ) can be estimated using the following equation: (15) where ρ is the bulk density of the air-dried soil layer. Thus, the total mass residing in the soil layer at the end of each test (M r-total ) is M r-total = M gas + M sorbed (16) Using eqs 14,15,16, and the test data, we estimate M r-total to be 0.114 mg, 0.092 mg, 0.049 mg, and 0.055 mg for Tests MC-1, MC-2, MB-1, and MB-2, respectively.…”

“…The mass in the sorbed phase (M sorbed ) can be estimated using the following equation: (15) where ρ is the bulk density of the air-dried soil layer. Thus, the total mass residing in the soil layer at the end of each test (M r-total ) is M r-total = M gas + M sorbed (16) Using eqs 14,15,16, and the test data, we estimate M r-total to be 0.114 mg, 0.092 mg, 0.049 mg, and 0.055 mg for Tests MC-1, MC-2, MB-1, and MB-2, respectively. These estimates alter the mass recoveries in Table 1 We considered degradation loss only for that portion of the chemical sorbed in the soil layer.…”

“…6,8 There have also been studies and applications of nonlinear models, which do not require the first two assumptions for the linear model as mentioned above. [15][16][17] In comparison to emissions of many soil trace gases, emissions of VOCs from anthropogenic sources have some unique features. First, the soil surface areas of VOC emissions are often limited in size.…”