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Published online 16 November 2005
Published in Vadose Zone J 4:1161-1169 (2005)
DOI: 10.2136/vzj2004.0164
© 2005 Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
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ORIGINAL RESEARCH

Continuous Soil Carbon Dioxide and Oxygen Measurements and Estimation of Gradient-Based Gaseous Flux

Vasile E. Turcua, Scott B. Jonesa and Dani Orb,*

a Department of Plants, Soils, and Biometeorology, Utah State University, Logan, UT 84322
b Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06269
* Corresponding author (dani{at}engr.uconn.edu)

Received 18 November 2004.



   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 THEORETICAL CONSIDERATIONS
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
The magnitude and dynamics of soil gaseous fluxes play critical roles in the global gas balance; yet, these processes are not captured at sufficient temporal resolution by standard methods based on periodic sampling and surface chamber measurements. A novel method for continuous measurement of soil surface gas fluxes based on subsurface CO2 and O2 concentration gradient measurements was developed. We tested the gradient-based method under steady- and transient-state soil water content and temperature conditions and compared results with a state-of-the-art surface chamber CO2 flux system. The new aspects of the method include fast-response sensors installed in the soil profile providing continuous record of concentration gradients coupled with concurrent estimates of water content-dependent gaseous diffusion coefficient enabling calculation of surface gaseous fluxes. Low-cost infrared sensors were used for CO2 concentration measurements, and galvanic cells for O2 measurements. An imposed CO2 concentration gradient in a dry soil column resulted in a quasilinear CO2 concentration profile and surface CO2 flux in agreement with chamber-measured fluxes. A series of continuous concentration measurements under variable water content conditions and wetting events showed agreement with surface chamber measurements. Within several days of surface wetting, soil CO2 concentrations attained 10 mL L–1, one order of magnitude higher than ambient concentrations, whereas O2 concentrations decreased. The gradient-based approach minimizes soil surface perturbations and provides insights into subsurface soil CO2 and O2 dynamics and the distribution and magnitude of soil respiration processes as related to soil environmental factors. The subsurface gradient-based measurement system represents an order-of-magnitude reduction in cost compared with research-grade surface chamber devices.

Abbreviations: IRGA, Infra-Red Gas Analyzer


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
THEORETICAL CONSIDERATIONS
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
IT HAS BEEN ESTIMATED that globally, soil contains approximately 2.6 x 1029 prokaryotic cells (compared with 1.2 x 1029 in the open ocean water and sediments), concentrated in a relatively small volume on the earth skin (soil volume 1.2 x 1014 m3 vs. 1020 m3 for open ocean), making the unsaturated zone the richest compartment of prokaryotic life on Earth (Whitman et al., 1998). This abundance of microbial life combined with all higher plants, makes soil the major component in the ecosystem carbon balance, with a carbon stock of 2 Terra-tons (Grace, 2001).

The primary methods for gaseous measurements within the soil include soil air sampling at different depths (Buyanowski and Wagner, 1983) and laboratory analysis of soil core samples (Cortassa et al., 2001). Measurements of surface CO2 flux are typically based on the "closed-chamber method" whereby surface flux is determined from changes in gas concentration within an enclosure on the soil surface (de Jong et al., 1979; Cropper et al., 1985; Drewitt et al., 2002). Commonly used chambers are portable devices such as the LiCor Li-6200 or Li-6400 systems (LiCor Inc., Lincoln, NE), which are capable of measuring soil CO2 fluxes using high accuracy research-grade instrumentation (Dugas, 1993). The closed chambers are static or dynamic, where gas is pumped from the chamber to an external Infra-Red Gas Analyzer (IRGA). Open dynamic systems use a continuous flow of gas through the chamber and determine soil CO2 flux by the difference of CO2 concentration at the inlet to the chamber and the outlet. A comparison of different chamber types (Norman et al., 1997) shows that systematic errors are associated with all of these different methods and correction factors are needed. Among the primary limitations of soil chamber measurements are the lack of continuous observations, manual setup, and impact on soil surface boundary conditions that could alter the nature of the diffusive flux (Davidson et al., 2002). Attempts to improve temporal coverage (de Jong et al., 1979; Cropper et al., 1985; Freijer and Bouten, 1991) by continuous air pumping from the enclosure to a gas analyzer resulted in significant alteration of the soil–atmosphere boundary conditions due to variations in air pressures within the chamber (Lund et al., 1999) and perturbation of natural conditions on the soil surface (e.g., gas concentration gradients, precipitation, radiation). In recent years, researchers developed automated surface chamber measurements capable of capturing short-term changes in soil respiration. Such systems were developed for customized experiments (Ambus and Robertson, 1998; Liang et al., 2003) or by specialized companies (i.e., LiCor 8500 system). However, these quasi-continuous systems are still limited to surface CO2 fluxes lacking details regarding subsurface CO2 dynamics. The urgent need for continuous determination of soil CO2 flux and associated concentration profiles for extended periods is widely recognized as a key to reliable integration of total CO2 exchange between soil and the atmosphere (Parkin and Kaspar, 2004).

The gradient-based approach demonstrating the feasibility of gaseous flux estimations from in situ CO2 and O2 concentrations and water content measurements was described previously (Mitchell et al., 1999; Jones et al., 2000). The availability of new fast-response sensors provides continuous measurements of soil CO2 concentration and enables dynamic observation of soil CO2 evolution with respect to ambient variables such as soil temperature (Tang et al., 2003).

The objectives of this study were (i) to introduce and test a new approach of the gradient-based measurement method for continuous monitoring of temporal and vertical variations of soil CO2 and O2 concentrations driven by diurnal soil temperature variations and changes in water content and (ii) to compare the gradient-based soil CO2 flux determination with standard soil-chamber measurements. In the proposed method, CO2 and O2 sensors are installed across the soil profile, providing continuous measurements. Additionally, the method is capable of capturing and estimating near-surface CO2 and O2 fluxes without altering soil surface conditions, when measured concentration gradients are coupled with information regarding soil diffusivity. The work presented here highlights the advantage of this continuous method for surface CO2 and O2 flux estimation and discusses the drawbacks and uncertainties in the methodology.

Imposing a constant CO2 concentration gradient at the two ends of an air-dry soil column, where microbial activity can be assumed negligible and soil gas diffusivity constant, should lead to a linear distribution of CO2 concentration within the profile. We used this simple test to observe the comparison between the gradient-based CO2 flux and the soil-chamber flux under steady-state conditions. Following this, we tested the gradient method in moist soil, since soil water content plays an important role in enhancing CO2 production in soils (Wildung et al., 1975; Zak et al., 1999). In addition to increasing microbial activity, wetting processes can result in a decrease of soil air-filled porosity and consequently a reduction in the soil gaseous diffusion coefficient. Hence, increased CO2 production in the subsurface may not be immediately observable at the soil surface because of reduced gaseous diffusion. Accurate assessment of soil gas diffusivity is the main drawback of using concentration gradients for calculation of surface flux, especially during transient water content conditions. The highly dynamic nature of soil water content during wetting may generate a nonuniform profile of the air-filled porosity with depth. Therefore, estimation of soil gas diffusivity from an average air-filled porosity is not adequate. We suggest it is critical to determine air-filled porosity for each discrete soil layer, where the wettest horizontal layer, having the lowest air-filled porosity, dictates the limiting gas diffusion coefficient for the whole soil profile. In the section on theory below, we will introduce the harmonically averaged air-filled porosity for the soil profile. This approach provides the appropriate estimation of soil diffusivity, yielding the best estimate of surface CO2 flux. We compared these fluxes with soil chamber–measured CO2 fluxes at the soil surface to demonstrate the reliability of the gradient-based approach.

Next, we present basic theoretical considerations and key assumptions, followed by a description of the experimental setup and methodology and a discussion of measurements obtained using the gradient-based and standard soil-chamber methods.


   THEORETICAL CONSIDERATIONS
TOP
 ABSTRACT
 INTRODUCTION
 THEORETICAL CONSIDERATIONS
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Diffusion along concentration gradients is the primary mechanism for gaseous transport in soils. In most soils, pressure gradients are negligible means of gaseous transport (Glinski and Stepniewski, 1985; Hillel, 1998). Thus, measurement of CO2 and O2 concentration profiles in soil may be used to estimate gaseous fluxes (de Jong and Schappert, 1972) according to Fick's Law:

[1]
where J is the flux of gas species, Ds = Ds({phi},{theta}) is the soil gas diffusion coefficient that varies with soil porosity {phi} and volumetric water content {theta}, C is the gas concentration, and z is depth. For flux determination, the gradient is approximated by discrete differences {Delta}C and {Delta}z.

Soil Gaseous Diffusion Coefficient
For a dry porous medium, the gaseous diffusion coefficient is often expressed as a function of the porosity of the medium, such as in the expression proposed by Millington (1959):

[2]
where Da is the diffusion coefficient of gas species in free air, where Da {approx} 1.64 x 10–5 m2 s–1 for CO2 and Da {approx} 1.98 x 10–5 m2 s–1 for O2 (Hillel, 1998) at standard conditions of temperature (25°C) and pressure (1025.13 kPa). Variations of Da with temperature and molar fraction (Jaynes and Rogowski, 1983) are neglected in this study. For wet soils, the fraction of air-filled porosity determines the soil gaseous diffusion coefficient. Many expressions have been proposed to relate soil water content {theta} or air content to gaseous diffusion, and a recent review of field and laboratory determined diffusivities (Werner et al., 2004) pointed to the following simple relationship proposed by Moldrup et al. (2000) as the best predictor of gaseous diffusion coefficient as a function of air-filled porosity not only for sieved and repacked soils but also for in situ measurements:

[3]

An important aspect associated with measurements and calculations of gaseous fluxes in field soils is the role of spatial variations in textural properties in a soil profile and nonuniform vertical distribution of soil water content. Variations in these attributes, especially soil water content, which is highly variable but assumed uniform horizontally, affect the calculations of an effective gaseous diffusion coefficient for flux estimation in a given soil layer. The effective diffusion coefficient for a layered nonuniform soil profile follows a similar calculation as for the effective hydraulic conductivity for flow perpendicular to layering based on harmonic averaging of individual conductivities (or diffusivity) of each layer:

[4]
where Ds is the equivalent (effective) soil diffusion coefficient for the entire spatial domain, Dsk({theta}k) represents soil gaseous diffusivity for a discrete layer k of thickness {Delta}z, and water content {theta}k; n is the total number of layers within the domain (for soil porosity that varies with depth, Dsk({theta}k,{phi}k) is required in Eq. [4]). Note that this necessitates more detailed information regarding water content vertical distribution than is provided by simple mass balance models or by vertically averaged water content measurements.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 THEORETICAL CONSIDERATIONS
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
A new generation of commercially available sensors enables simple and reliable in situ measurements of CO2 and O2 concentrations. For CO2 measurements, we used Vaisala GMD20 analyzers (Vaisala Inc., Woburn, MA) based on a Single-Beam Dual Wavelength infrared absorption method and silicon CARBOCAP sensor technology (Fig. 1) . Each signal pulse is compared with a reference signal obtained under the same conditions of temperature and humidity, ensuring a response independent of ambient conditions. The sensors provide a linear response within 1 min of variation in CO2 concentration over a preset range (for dry soils we used a calibration span of 0–5000 µL L–1, whereas for moist soils we used 0–20000 µL L–1) with an accuracy of ±30 µL L–1 +2% of reading. The choice of sensor calibration was guided by the depth of sensor installation and expected moisture content. A stable 24-V power supply is required by the sensors that output an analog voltage or current. The sensor's relatively small dimensions (length = 140 mm; diameter = 15 mm) facilitates simple deployment within a soil profile. Oxygen concentrations were measured using galvanic cell sensors KE-25 (Figaro Inc., Glenview, IL). These low cost, long-life ({approx}5 yr) sensors require no power input and provide a rapid ({approx}12 s) and linear analog response to variations in oxygen concentration. Independent measurements of soil surface CO2 fluxes were obtained using a standard Li6400 portable soil chamber (Li-Cor Inc.). A PVC collar installed directly above the subsurface sensors in the soil surface provided physical support of the soil chamber during measurements. Soil water content was determined with a CS-615 reflectometer (Campbell Scientific, Logan, UT), which averaged water content over the length of the 30-cm rods. The sensor was calibrated using gravimetric water content measurements in the Millville silt loam soil (coarse-silty, carbonatic, mesic Typic Haploxeroll).



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  		Fig. 1. Detailed view of sensor arrangement showing the combination of CO2–O2 sensors and the thermocouple inserted into the soil profile.

 
We compared two methods for estimating soil gas diffusivity for the 0- to 8-cm soil layer. First, using Eq. [3], we obtained a diffusivity value based on an average water content for the soil layer as measured with the reflectometer. This value was inserted in Eq. [1] to yield an average surface CO2 flux denoted as Jav. In the second approach, we used values of water content for each 2-cm soil layer to determine harmonically averaged diffusivity using Eq. [4] with the resulting surface CO2 flux denoted as Jh. For this situation we assumed a binary gas system.

Steady-State CO2 Flux Measurements in Soil Columns
For preliminary tests of the gradient method we used a dry soil column uniformly packed with Kidman soil (coarse-silty, carbonatic, mesic Typic Haploxeroll). The bottom boundary of the column was maintained using a constant, low pressure (<10 Pa) flow rate of calibration-grade CO2 exiting through a large diameter (2.5 cm) outlet tube. The exhaust tube exited the room to avoid buildup of CO2 in the laboratory. The fixed CO2 concentration gradient resulted in steady-state flux through the soil column. The experimental setup is depicted in Fig. 2 , where the horizontal placement of two CO2 sensors inside the sand column is shown at 9 and 24.5 cm below the surface, respectively. Measurements were made for two different CO2 concentrations at the bottom of the soil column, each leading to different concentration profiles in the column and different CO2 flux at the surface (Table 1). For each case, the surface CO2 flux was estimated based on the concentration gradient and diffusion coefficient in dry sand and was periodically and independently measured using the soil chamber. To minimize perturbation at the surface of the soil column, we installed the soil chamber for only short measurement periods lasting <5 min. Gas diffusion coefficients were determined based on soil porosity using Eq. [2] and [3] and assuming that water content was negligible in the air-dried soil.



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  		Fig. 2. Laboratory soil column showing experimental setup for steady-state CO2 flux determinations. Measured surface soil chamber fluxes were compared with calculated fluxes obtained from the gradient method (Table 1).

 

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  		Table 1. Carbon dioxide measurements in a column of dry sandy soil under steady-state conditions.

 
Dynamic CO2 Flux Measurements in Greenhouse Soil Columns
A large container 1.20 m tall with a horizontal cross-sectional area of 0.6 m2 was filled with air-dry Millville silt loam soil. A 25-cm-diameter PVC pipe was placed on the soil surface, and the soil was carefully excavated from the circular area delimited by the inner edge of the pipe, leaving the surrounding soil with minimal disturbance. The pipe was driven gradually into the soil during excavation until it reached the desired depth of 30 cm. A plastic disc was then placed at the bottom of the cavity and sealed with silicone. A 2.5-cm-diameter auger was used to bore a horizontal sensor cavity into the soil through the predrilled holes in the large PVC pipe wall where sensors were installed (Fig. 3) . In 2001, for experiments with two sets of sensors (11 d), these were installed at depths of 8 and 22 cm. In 2002 (7 d), we used three sets of sensors installed at 4, 8, and 22 cm. Each measurement depth was instrumented with a pair of CO2 and O2 sensors. The sensors were mounted end to end inside of a PVC tube (2.5 cm in diameter and 20 cm long) with a gap between gas entry ports and a series of slits in the bottom of the PVC tube to allow unhindered gas exchange as seen in Fig. 1. A copper-constantan thermocouple was enclosed within the same head space for soil air temperature measurement. During the experiments, the nonvegetated soil was wetted periodically by applying known amounts of water at the soil surface (1–2 mm per application). Sensor outputs were logged by a CSI-21x datalogger (Campbell Scientific) and stored as 10-min averages. A collar for closed-chamber periodic measurements was installed in the soil surface directly above the gradient-based sensor bank. Surface CO2 efflux was measured daily with the closed-chamber device for comparison to fluxes determined from the gradient-based approach.



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  		Fig. 3. Cut-away of the experimental apparatus showing the sealed 25-cm-diameter PVC pipe used to house the sensors and datalogger. The soil chamber collar is placed directly above the gradient-based sensors, and a soil moisture sensor installed obliquely averages water content over the 0- to 15-cm depth.

 
The gradient-based CO2 surface flux was determined using Fick's first law of gas diffusion presented above. The near-surface atmospheric CO2 concentration can be affected by advective, diffusive, and thermally induced processes. Several measurements were made to determine the aboveground CO2 concentration in atmospheric air, using the Li-Cor 6400 IRGA. The soil chamber was laid on its side on the soil surface, and concentration of CO2 entering the chamber was monitored (LI-6400 instruction manual). The concentrations averaged 380 ± 20 µL L–1 for low soil water contents and 380 ± 50 µL L–1 for wetter soil. These variations in surface CO2 concentration equate to a <1% error in CO2 flux calculation. We assumed that the CO2 concentration at depth z = 0 was equal with the concentration in the soil chamber during these initial measurements. The CO2 concentration at depth z, Cz, was obtained via direct measurement with the sensors described previously. For this study, all the surface flux data presented were obtained by calculating the concentration gradient between the surface and a depth of 8 cm. The information from sensors at deeper depths was used to observe subsurface CO2 concentration dynamics. When concentrations lower in the profile fall below near-surface peak measurement, downward flux of CO2 is likely to occur.

We used the numerical simulation model Hydrus-2D (Simunek et al., 1999) to determine vertical and temporal water content distributions, subject to known water flux input at the surface and predefined soil hydraulic properties given in Mmolawa and Or (2003). The simulation domain was considered a one-dimensional vertical soil column, of 70-cm depth, with uniform soil characteristics, and with the observation nodes for simulation outputs at 1, 3, 5, ..., 19 cm below the soil surface. The lower boundary condition was set as a free drainage condition while the upper boundary condition for water flow was specified as a variable flux condition (e.g., irrigation, evaporation), where the flux of water was obtained from the wetting record during the experiments. The entire soil surface was uniformly sprinkled with water using a 1-L volume. Each wetting event recorded included the amount of water per unit area per time of wetting providing the input surface water flux information for both 2001 and 2002 experiments.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 THEORETICAL CONSIDERATIONS
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
Steady-State CO2 Flux Measurements in Soil Columns
Imposing a constant CO2 concentration gradient at the two ends of an air-dry soil column (where microbial activity was assumed negligible) should produce a linear gradient CO2 concentration within the profile as confirmed by the results in Fig. 4 . The gradient-based flux estimates were in good agreement with soil chamber measurements obtained at the soil surface (Table 1). These simple tests in a dry soil (uniform diffusion coefficient) with negligible CO2 production demonstrate the gradient-based method's ability to provide estimates of gaseous flux based on soil CO2 concentration measurements and known concentrations within the soil profile.



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  		Fig. 4. Soil CO2 concentration profile measured in the laboratory under steady-state conditions in dry Kidman soil.

 
Dynamic CO2 Flux Measurements in Greenhouse Soil Columns
At the beginning of the 2001 and 2002 greenhouse experiments, CO2 and O2 concentrations in air-dried and repacked Millville silt loam soil remained near atmospheric values 1 wk before the first wetting event. Consistent with the assumption of negligible microbial CO2 production in dry soil, attempts to measure with the soil chamber confirmed that CO2 efflux was below detection limits during the same period. Upon wetting of the soil surface, the concentration of soil CO2 increased rapidly (Fig. 5a and 5b) whereas O2 concentration dropped, as depicted in Fig. 5c and 5d. These changes in CO2 and O2 concentration profiles are indicative of increased microbial respiration in the wet soil. The CO2 and O2 concentration profile became nonlinear on wetting, with the measured maximum CO2 concentration associated with the lowest O2 concentration. The increase of CO2 and decrease of O2 concentrations during the two experiments (Fig. 5a–5d) show a time delay at the 22-cm depth. This resulted from the retarded arrival of the wetting front that creates a large difference in soil water content from top to bottom. This creates a discrepancy in CO2 measured concentration at different depths. In the 2001 experiment, CO2 concentration at the 8-cm depth exceeded 9000 µL L–1, compared with normal atmospheric concentrations of {approx}380 µL L–1. The oxygen in the same soil layer was depleted to {approx}180 mL L–1 from its initial (atmospheric) value of 209 mL L–1. These values indicate the presence of a strong concentration gradient from the 8-cm layer toward the surface with upward flux of CO2 and downward O2 flux. Interestingly, sensors at 22 cm below the soil surface show lower CO2 concentrations and higher O2 concentrations than the 8-cm measurements, indicating the majority of microbial activity (CO2 source and O2 sink) occurred between the surface and the 22-cm depth. The resulting CO2 fluxes were driven both downward and upward from this "optimal" layer (e.g., wetter and warmer), with O2 being consumed from both directions. With the addition of a sensor at 4 cm in the 2002 experiment, we observed that CO2 concentrations in the wet soil profile were similar at the 4- and 8-cm depths, resulting in only a small CO2 concentration gradient between these two depths. This suggests the possibility of a broad layer of maximum CO2 production located within and perhaps surrounding the 4- to 8-cm depth. More detailed insight into this "active" zone would require a concentrated sensor array to better characterize the shape of the concentration profile and the resulting gradients driving diffusion both upward and downward.



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  		Fig. 5. Greenhouse measurements of (a, b) CO2 and (c, d) O2 gas concentrations and (e, f) soil temperatures measured at two or three depths in the soil profile, during the 2001 and 2002 greenhouse experiments. In 2001, between Days 4 and 7, no water was applied.

 
Effects of Variations in Water Content on Soil Gaseous Diffusion Coefficient
Water was applied on the soil surface in pulses as shown in Fig. 6a (for 2001) and 6b (for 2002). The amounts and application times were used as inputs for detailed simulations of water content distribution in the profile using the Hydrus-2D model. Simulated water content is presented in Fig. 6a and 6b for layers at depths of 0 to 2, 6 to 8, and 18 to 20 cm. Measured (average) soil water content is also shown for the 0- to 15-cm profile for comparison. Each water application is marked by a sharp increase in (simulated) surface layer water content followed by internal drainage into deeper layers. Vertically averaged water content measurements tend to smear the sharp increase in near-surface water content that acts as a throttle in controlling gaseous diffusion into and out of the soil. The importance of surface wetness in controlling diffusion processes is illustrated next.



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  		Fig. 6. Measured (0–15 cm, dashed line) and Hydrus2D simulated (i.e., for 0–2, 6–8, and 18–20 cm depth) (a, b) soil water content and (c, d) estimated soil gas diffusivity for the 2001 and 2002 greenhouse experiments. (e, f) Surface CO2 flux determined using the gradient-based method (lines) and periodic soil chamber measurements (circles) are shown for both years. (g, h) Calculated near-surface O2 flux.

 
No water was applied between Days 4 and 7 in the 2001 experiment, allowing internal water redistribution and a decrease in surface water content. During this time, a decrease in the 8-cm CO2 concentration occurred, in parallel with an increase in O2 concentration at the same depth. These changes did not correlate with the steady increase in temperature (the CO2 decrease and O2 increase lasted for 2.5 d, while temperature oscillations are based on a daily cycle). These changes are better explained by higher surface layer gas diffusivity as the water evaporated and drained to deeper layers. Increased surface diffusivity allows a larger gas flux across the soil–atmosphere interface, reducing the "stored" CO2 from microbial production and increasing the supply of oxygen in the soil air (aeration). When wetting applications were resumed, a sharp decrease in surface gas diffusivity was followed by a buildup of soil CO2 concentration and a decrease of O2. A similar situation can be observed in the 2002 data, between Days 3 and 4 of the experiment, when no water was applied for more than 24 h.

Surface CO2 flux, Jav, was obtained using the average soil profile water content and is depicted in Fig. 6e and 6f (dashed line). The correlation between Jav and the soil chamber measured surface fluxes (circles) was poor, where Jav was about three times higher than the total CO2 fluxes measured with the soil chamber. This flux discrepancy is much larger than errors associated with the soil-chamber measurements. We reevaluated the possibility that soil gaseous diffusivity was overestimated using the average "bulk" air-filled porosity in calculations, disregarding spatial distribution of water in the soil profile. Gas diffusivity is controlled by the wettest soil layer, suggesting that harmonic averaging for diffusivity values would be required (Eq. [4]). Harmonically averaged diffusion coefficients were used to recalculate the surface CO2 flux Jh shown in Fig. 6c and 6d (thin dotted line). The harmonically averaged flux obtained using the same diffusion model but accounting for a layered water distribution is in better agreement with soil chamber surface CO2 fluxes during both years of measurements where peak fluxes occur just before irrigation. The frequent application of water resulted in a highly dynamic soil CO2 surface flux (Jh) that is not captured by the soil-chamber measurements, whereas the gradient method provides the missing flux information between consecutive soil-chamber measurements. For example, Fig. 6 shows the linkage between the dynamics of soil gaseous diffusivity and surface wetting and their impact on surface CO2 and O2 flux. We used flux values from Fig. 6f to calculate the cumulative C evolved from the soil surface during about 5 d via the gradient-based and soil-chamber methods. Integration of Jh, which captured the sudden reductions in flux following each surface wetting event, yielded 283 mmols CO2 m–2. Considering the soil-chamber measurements, nearly 50% more C (411 mmols CO2 m–2) was evolved. This suggests that for cases when soil-chamber measurements are made during peak flux periods (e.g., during high soil temperature or before irrigation) the total soil C balance may be overestimated if additional nonpeak periodic measurements are not included.

Near-surface oxygen flux was determined using the gradient method, based on similar principles, with data collected continuously at the 8-cm depth. Harmonically averaged air-filled porosities were used to determine the diffusion coefficient as for CO2, multiplied with a factor of 1.21 to account for the difference in Da values between CO2 and O2. The flux of oxygen into the soil (Fig. 6g and 6h) was much larger than CO2 flux out because of a larger gradient of oxygen recorded in the same soil layer (0–8 cm). This discrepancy may be partially explained by a larger solubility of CO2 than O2 in soil water ({approx}28 times higher for CO2; Paul and Clark, 1996) resulting in a smaller CO2 concentration gradient (Cortassa et al., 2001). Unfortunately, there was not an independent oxygen flux measurement available for comparison with the gradient method. Therefore, it is difficult to verify the gradient-based flux determination. Nevertheless, the estimation of O2 flux is valuable for soil-respiration studies (e.g., establishing respiratory quotient).

A summary of comparisons between surface CO2 fluxes determined using the gradient-based method and closed-chamber measurements (Fig. 7) shows reasonable correlation between the two methods. The three outlier values of CO2 flux measured with the soil chamber at the end of the 2001 experiment were omitted in this graph because of suspected equipment failure during those measurements. The high surface CO2 flux measured at the beginning of the 2002 experiment (Fig. 6f) immediately after the initial wetting could be attributed to the effect of CO2 desorption from soil during water intrusion. With a tendency for underprediction of surface chamber measured fluxes (de Jong et al., 1979), the gradient-based method is in need of further study. The method offers a viable and valuable alternative to closed-chamber measurements by providing detailed temporal and spatial (soil profile) information on CO2 and O2 concentrations not available with surface chamber measurements. Our analysis of the gradient-based approach suggests successful application of this technique requires detailed information regarding water content distribution within the soil profile.



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  		Fig. 7. A 1:1 comparison of the soil surface CO2 flux measurement using the closed-chamber method vs. the proposed gradient-based method.

 

   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 THEORETICAL CONSIDERATIONS
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
A novel gradient-based measurement method for soil CO2 and O2 concentration and flux was developed and tested. The new aspects of this method are the use of newly available sensors capable of measuring continuous soil CO2 and O2 concentrations in situ, with minimum soil disturbance and detailed consideration of soil gas diffusivity for use in surface CO2 flux estimation. As a supplement and potential alternative to the standard soil surface chamber technique, the gradient method offers several advantages, including continuous monitoring and insights into the subsurface CO2 and O2 concentration dynamics and spatial distribution. Simultaneous measurements of oxygen concentrations and soil temperature at the same depth provide useful information about the correlation between soil respiration and temperature. A continuous surface CO2 flux determination is particularly important for capturing short-duration and often large CO2 fluxes occurring after rapid wetting (e.g., rainfall events in arid zones). Considering the minimal impact on surface conditions using the gradient method, surface CO2 fluxes are more reliably related to dynamics of environmental factors such as water content and temperature. However, abrupt changes in the near-surface soil water content above the top sensor may not be captured using the gradient method. The reduction in near-surface diffusivity and commensurate buildup of subsurface gaseous concentrations are more likely to be observed by the gradient method. The gradient method can be used for in situ continuous monitoring of soil respiration dynamics because it provides continuous and simultaneous data on CO2 and O2 concentrations in the soil profile. Consequently, information regarding soil microbial activity is not limited to CO2 production only, since consumption of O2 can also be observed yielding possible insights regarding soil respiration type (i.e., aerobic or anaerobic). The measurement of continuous subsurface gas concentration using this new method is a valuable tool for calibration of soil CO2 transport and production models and for improved understanding of biogeochemical phenomenology in the soil–atmosphere continuum. Accurate estimates of soil gas diffusivity required for gas flux calculation hinge on accurate spatial measurement of soil water content within the profile. We envision that the availability of more accurate and lower cost water content sensors installed adjacent to the gas sensor array will improve the accuracy and usefulness of the gradient-based method. Additionally, for known surface inputs (e.g., precipitation, evaporation), modeling coupled with measurements should improve surface CO2 flux estimates.


   ACKNOWLEDGMENTS
 
This research was funded by the National Science Foundation project DEB-9807097 and supported by the Utah Agricultural Experiment Station under UAES paper no. 7622. The authors thank Bill Mace, Brent Bingham, and Alan Mitchell for their assistance in this work.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 THEORETICAL CONSIDERATIONS
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 




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