Comparison of CO2, CH4 and N2O soil-atmosphere exchange measured in static chambers with cavity ring-down spectroscopy and gas chromatography

ArticleinAgricultural and Forest Meteorology 211 · October 2015with 1,355 Reads
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    Precise and rapid analyses of greenhouse gases (GHGs) will advance understanding of the net climatic forcing of coastal marsh ecosystems. We examined the ability of a cavity ring down spectroscopy (CRDS) analyzer (Model G2508, Picarro) to measure carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes in real-time from coastal marshes through comparisons with a Shimadzu GC-2014 (GC) in a marsh mesocosm experiment and with a similar laser-based N2O analyzer (Model N2O/CO, Los Gatos Research) in both mesocosm and field experiments. Minimum (analytical) detectable fluxes for all gases were more than one order of magnitude lower for the Picarro than the GC. In mesocosms, the Picarro analyzer detected several CO2, CH4, and N2O fluxes that the GC could not, but larger N2O fluxes (218-409 µmol m⁻² h⁻¹) were similar between analyzers. Minimum detectable fluxes for the Picarro were 1 order of magnitude higher than the Los Gatos analyzer for N2O. The Picarro and Los Gatos N2O fluxes (3-132 µmol m⁻² h⁻¹) differed in two mesocosm nitrogen addition experiments, but were similar in a mesocosm with larger N2O fluxes (326-491 µmol m⁻² h⁻¹). In a field comparison, Picarro and Los Gatos N2O fluxes (13 ± µmol m⁻² h⁻¹) differed in plots receiving low nitrogen loads but were similar in plots with higher nitrogen loads and fluxes roughly double in magnitude. Both the Picarro and Los Gatos analyzers offer efficient and precise alternatives to GCbased methods, but the former uniquely enables simultaneous measurements of three major GHGs in coastal marshes.
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  • Thesis
    Arctic ecosystems are undergoing rapid changes in response to a global increase in mean air temperature. The projections for the end of the century across regions further indicate that the Arctic will experience the largest increases in air temperature, especially during winter and spring time. This may lead to changes in winter snow precipitation regimes, growing season length, nutrient cycling and plant community composition. As a consequence, the carbon (C) balance of the Arctic may be altered and this could trigger a positive feedback on the global climate. This thesis addresses two aspects of ecosystem dynamics in the Arctic: i) soil methane (CH4) oxidation in dry heath tundra and barren soils and ii) root dynamics in wetlands. These aspects play an important role in the C cycling of the Arctic, and yet their contribution to the net C balance at present and future climatic conditions remains unclear. Changes in climatic regimes may alter key environmental drivers of both CH4 and root dynamics and manipulations in situ, which take into account these aspects, will help improving our understanding of climate change effects on tundra ecosystems. Field measurements were carried out during the growing season in Disko Island, West Greenland, and CH4 and root dynamics were investigated in response to experimentally increased winter snow precipitation, summer warming and their interaction. A large CH4 oxidation capacity was observed at both the dry heath and barren soils at ambient conditions. Soil moisture exerted a strong control on the oxidative process and increases in this parameter were coupled with decreased soil CH4 uptake rates and reduced soil temperature sensitivity. Accordingly, at the dry heath winter snow accumulation led to an early season decrease in CH4 oxidation rates linked to increased soil moisture after thawing. On the other hand, a response to experimental air/soil warming was observed in the late season when increased soil CH4 oxidation was coupled to increased soil temperature. These results suggested that future CH4 dynamics in arctic upland soils will be strongly influenced by changes in soil hydrology. Thereby, drier and warmer soil conditions will possibly enhance the CH4 sink capacity of dry tundra ecosystems, which cover large areas of the Arctic and in turn could play a central role in offsetting CH4 emissions from wetlands. However, soil CH4 oxidation rates in dry arctic tundra are regulated by complex dynamics, including both soil hydrology and temperature, but also the active biomass of the microbial communities carrying out the reaction. All those factors should be taken into account when modeling the responses of soil CH4 dynamics to climate changes. The observations on root dynamics at the wetland showed that fine root productivity was significantly reduced by increased winter snow precipitation, due to the delayed onset of the growing season and possibly increased nutrient cycling. Total root number, length and maximum growth positively responded to experimental air warming, especially in the deeper soil layers. This effect was explained as an indirect response to increased canopy temperature, which enhanced above-ground activity and it further suggested that future summer warming could potentially increase below-ground C allocation. Seasonal trends of root growth, analyzed with minirhizotrons, improved our limited knowledge on root phenology and showed that the growing season continues longer below- than above- ground. Over time, changes in air temperature and precipitation regimes may lead to shifts in plant community composition and roots depth with consequences for the net ecosystem C balance. The results presented in this thesis describe the initial (one year of manipulations) and rapid responses of root dynamics to changes in climatic conditions and long-term observations will be needed to better understand their contribution to the future net C balance of the Arctic.
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    1. Greenhouse gas (GHG) emissions from livestock contribute significantly to global warming, and a reduction of this source of emissions is crucial in achieving the goal of mitigating global warming. 2. CO2 and CH4 emissions from dung pats were analysed by means of a mesocosm experiment in a Mediterranean ecosystem. The experiment consisted of a total of 30 mesocosms distributed across three treatments: a well‐preserved, undisturbed dung beetle assemblage associated with organic livestock; a dung beetle assemblage that was impoverished as a result of the long‐term use of veterinary medical products; and a control treatment without dung beetles. 3. Corrections related to insect respiration allow researchers to provide more precise measurements of CO2 emissions from dung, especially in the initial and final phases of dung exposure, when the percentage of CO2 emitted by dung beetles can become greater than the emissions from the dung pats themselves. 4. The effects of dung beetles on CO2 and CH4 emissions are much more accentuated in warm‐temperate conditions than in northern temperate areas previously studied. Mediterranean assemblages remove and spread dung faster and more effectively than do northern dung beetle assemblages characterised by a lower functional richness and beetle abundance and biomass. 5. From a livestock management viewpoint, mesocosms representing areas with impoverished dung beetle assemblages, due to the long‐term use of veterinary medical products, such as ivermectin, emitted 1.6‐ and 2.8‐fold higher total CO2 and CH4, respectively, than mesocosms mimicking sites with untreated livestock. Dung beetle assemblages that were impoverished due to the long‐term use of ivermectin emitted 1.6‐ and 2.8‐fold higher total CO2 and CH4, respectively, than assemblages mimicking sites with untreated livestock. Mediterranean assemblages remove and spread dung faster and more effectively than do northern dung beetle assemblages characterised by a lower functional richness and beetle abundance and biomass. Corrections related to insect respiration allow researchers to provide more precise measurements of CO2 emissions from dung, especially in the initial and final phases of dung exposure.
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    Full-text available
    This letter provides an overview of the available measurement techniques for nitrous oxide (N2O) flux measurement. It is presented to aid the choice of the most appropriate methods for different situations. Nitrous oxide is a very potent greenhouse gas; the effect of 1 kg of N2O is estimated to be equivalent to 300 kg of CO2. Emissions of N2O from the soil have a larger uncertainty compared to other greenhouse gases. Important reasons for this are low atmospheric concentration levels and enormous spatial and temporal variability. Traditionally such small increases are measured by chambers and analyzed by gas chromatography. Spatial and temporal resolution is poor, but costs are low. To detect emissions at the field scale and high temporal resolution, differences at tens of ppt levels need to be resolved. Reliable instruments are now available to measure N2O by a range of micrometeorological methods, but at high financial cost. Although chambers are effective in identifying processes and treatment effects and mitigation, the future lies with the more versatile high frequency and high sensitivity sensors.
  • Simultaneous soil flux measurements of five gases – N2O
    • D Fleck
    • Y He
    • C Alexander
    • G Jacobson
    • K L Cunningham
    Fleck, D., He, Y., Alexander, C., Jacobson, G., Cunningham, K.L., 2013. Simultaneous soil flux measurements of five gases – N2O, CH4, CO2, NH3, and H2O – with the Picarro G2508 1–11. Picarro Inc., Santa Clara, CA, USA. Available at: <https:// picarro.app.box.com/s/z2gpj3hpl11xye9csz6mdpixltc1i5hl> (accessed 02.04.15).
  • Simultaneous soil flux measurements of five gases-N2O, CH4, CO2, NH3, and H2O-with the Picarro G2508 1-11
    • D Fleck
    • Y He
    • C Alexander
    • G Jacobson
    • K L Cunningham
    Fleck, D., He, Y., Alexander, C., Jacobson, G., Cunningham, K.L., 2013. Simultaneous soil flux measurements of five gases-N2O, CH4, CO2, NH3, and H2O-with the Picarro G2508 1-11. Picarro Inc., Santa Clara, CA, USA. Available at: <https:// picarro.app.box.com/s/z2gpj3hpl11xye9csz6mdpixltc1i5hl> (accessed 02.04.15).
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    A variety of chamber methodologies have been developed in an attempt to accurately measure the rate of soil CO2 respiration. However, the degree to which these methods perturb and misread the soil signal is poorly understood. One source of error in particular is the introduction of lateral diffusion due to the disturbance of the steady-state CO2 concentrations. The addition of soil collars to the chamber system attempts to address this perturbation, but may induce additional errors from the increased disturbance. Using a numerical three-dimensional (3D) soil-atmosphere diffusion model, we have undertaken a comprehensive and comparative study of existing static and dynamic chambers. Specifically, we are examining the 3D diffusion errors associated with each method and opportunities for correction. The impacts of collar length and diffusion parameters on lateral diffusion around the instruments are quantified to provide insight into obtaining more accurate soil respiration estimates. Results suggest that while each method can approximate the true flux in low diffusivity environments, the associated errors can be large and vary substantially in their sensitivity to both method-specific and environmental parameters. In some cases, factors such as collar length and soil diffusivity are coupled in their effects on accuracy.
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    Arctic soils are known to be important methane (CH4) consumers and sources. This study integrates in situ fluxes of CH4 between upland and wetland soils with potential rates of CH4 oxidation and production as well as abundance and diversity of the methanotrophs and methanogens measured with pyrosequencing of 16S DNA and rRNA fragments in soil and permafrost layers. Here, the spatial patterns of in situ CH4 fluxes for a 2,000 years old Arctic landscape in West Greenland reveal similar CH4 uptake rates (−4 ± 0.3 μmol m−2 h−1) as in other Arctic sites, but lower CH4 emissions (14 ± 1.5 μmol m−2 h−1) at wetland sites compared to other Arctic wetlands. Potential CH4 oxidation was similar for upland and wetland soils, but the wetter soils produced more CH4 in active and permafrost layers. Accordingly, the abundance of methanogenic archaea was highest in wetland soils. The methanotrophic community also differed between upland and wetland soils, with predominant activity of Type II methanotrophs in the active layer for upland soils, but only Type I methanotrophs for the wetland. In the permafrost of upland and wetland soils, activity of the methanotrophs belonging to Type I and Type II as well as methanogens were detected. This study indicates that the magnitude of CH4 oxidation and the direction of the flux, i.e. uptake or emission, are linked to different methanotrophic communities in upland and wetland soils. Also, the observed link between production/consumption rates and the microbial abundance and activity indicates that the age of an Arctic landscape is not important for the CH4 consumption but can be very important for CH4 production. Considering the prevalence of dry landscapes and contrasting ages of high Arctic soils, our results highlight that well-drained soils should not be overlooked as an important component of Arctic net CH4 budget.
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    A dynamic chamber method was developed to measure fluxes of N2O from soils with greater accuracy than previously possible, through the use of a quantum cascade laser (QCL). The dynamic method was compared with the conventional static chamber method, where samples are analysed subsequently on a gas chromatograph. Results suggest that the dynamic method is capable of measuring soil N2O fluxes with an uncertainty of typically less than 1–2 µg N2O-N m−2 hour−1 (0.24–0.48 g N2O-N ha−1 day−1), much less than the conventional static chamber method, because of the greater precision and temporal resolution of the QCL. The continuous record of N2O and CO2 concentration at 1 Hz during chamber closure provides an insight into the effects that enclosure time and the use of different regression methods may introduce when employed with static chamber systems similar in design. Results suggest that long enclosure times can contribute significantly to uncertainty in chamber flux measurements. Non-linear models are less influenced by effects of long enclosure time, but even these do not always adequately describe the observed concentrations when enclosure time exceeds 10 minutes, especially with large fluxes.
  • Article
    Estimating total N2O emission from agricultural soils is associated with considerable uncertainty due to the very large spatial variability of the fluxes. Thus characterizing the range of variations is of great interest. Modeling N2O fluxes remains challenging, especially at the within-field scale. The aim of this study was to test the ability of a simple process-based model, NOE (Nitrous Oxide Emission), to simulate N2O at scales finer than the field. Six field studies including 30–49 measurements of chamber N2O fluxes and ancillary variables were conducted in a barley/wheat field on hydromorphous soils. Three studies were made on surfaces of ∼10 m2 (defined as the local scale), and three studies along a 150-m transect (defined as the transect scale). First, the model was tested deterministically for predicting the flux spatial patterns, i.e., to try to reproduce the high flux points. Then the denitrification part of the model was tested stochastically for simulating the flux distributions by randomly generating input variables from the measured frequency distributions (Monte Carlo simulation). Measured fluxes were comprised between 0 and 1.5 mg N h−1 m−2. The deterministic prediction of spatial patterns provided a good match with measurements in 1 of the 6 studied cases, in a transect study. Denitrification was assessed to be the main source of N2O in 5 of the 6 cases and the model satisfactorily simulated frequency distributions in 4 cases out of 5, 2 at the local scale and 2 at the transect scale. Thus this study suggests that simple process-based models such as NOE, combined to Monte Carlo methods, can be used to improve simulation of the skewed frequency distributions of N2O fluxes and provide valuable information about the range of spatial variations in N2O fluxes.
  • Article
    A new procedure (HMR) for soil-atmosphere trace-gas flux estimation with static chambers is presented. It classifies data series into three categories according to criteria based on the application of a particular non-linear model and provides statistical data analyses for all categories. The two main categories are non-linear and linear concentration data, for which data are analysed by, respectively, the non-linear model and linear regression. The third category is represented by concentration data within the range of experimental error, or noise, from sites with no significant flux. Data in this category may be analysed by linear regression or simply classified as no flux. The particular non-linear model has been selected among alternatives because its exponential curvature generally fits non-linear static chamber concentration data well, and because it can be proven, mathematically, to be robust against horizontal gas transport through the soil or leaks in the chamber. The application of the HMR procedure is demonstrated on 244 data series of nitrous oxide accumulation over time. On average, 47% of these data were non-linear, with an average flux increase over linear regression of 52%. The classification and analysis of data with a small signal-to-noise ratio requires special attention, and it is demonstrated how diagnostic graphical plots may be used to select the appropriate data analysis. The HMR procedure has been implemented as a free add-on package for the free software R and is available for download through CRAN (http://www.r-project.org).
  • Soil Greenhouse Gas Flux Measurements with Automated and Manual Static Chambers, Forced Diffusion Chamber, and Concentration Profiles [WWW Document] Available at: <https
    • L Ruan
    • P Oikawa
    • M Géli
    • J Verfaillie
    • C Sturtevant
    • S Knox
    • N Nickerson
    • G Macarthur
    • C Creelman
    • N Saad
    • K Alstad
    • C Arata
    • D Baldocchi
    • W Silver
    Ruan, L., Oikawa, P., Géli, M., Verfaillie, J., Sturtevant, C., Knox, S., Nickerson, N., MacArthur, G., Creelman, C., Saad, N., Alstad, K., Arata, C., Baldocchi, D., Silver, W., 2014. Soil Greenhouse Gas Flux Measurements with Automated and Manual Static Chambers, Forced Diffusion Chamber, and Concentration Profiles [WWW Document]. Available at: <https://agu.confex.com/agu/fm14/ meetingapp.cgi#Paper/11901> (accessed 02.04.15).
  • Article
    Quantifying the nitrous oxide (N2O) and nitric oxide (NO) fluxes emitted from croplands remains a major challenge. Field measurements in different climates, soil and agricultural conditions are still scarce and emissions are generally assessed from a small number of measurements. In this study, we report continuously measured N2O and NO fluxes with a high temporal resolution over a 2-year crop sequence of barley and maize in northern France. Measurements were carried out using 6 automatic chambers at a rate of 16 mean flux measurements per day. Additional laboratory measurements on soil cores were conducted to study the response of NO and N2O emissions to environmental conditions.
  • Article
    Full-text available
    Closed (non-steady state) chamber measurements are often used to determine the gas exchange of N2O. Many researchers have addressed the underestimation of the emission estimates obtained from closed chamber measurements when using linear regression methods. However, the linear regression method is still usually applied to derive the flux. The importance of using non-linear regression methods is demonstrated with data from four fertilizing events each consisting of 1 month of automatic chamber measurements at Cabauw in the Netherlands in the period from July 2005 to July 2006. It is presented that the cumulative emission estimates with the exponential regression method are close to the cumulative emissions estimates with the intercept method. The linear estimates differ by up to 60% of the estimates with the exponential method. The performance of each method is validated using a C2H6 tracer and a goodness-of-fit analysis. The goodness-of-fit is much better for the exponential than the linear regression method. The systematic error due to linear regression is of the same order as the estimated uncertainty due to temporal variation. Therefore, closed-chamber data should be tested for non-linearity and an appropriate method should be used to calculate the flux.
  • Article
    The NitroEurope project aims to improve understanding of the nitrogen (N) cycle at the continental scale and quantify the major fluxes of reactive N by a combination of reactive N measurements and modelling activities. As part of the overall measurement strategy, a network of 13 flux 'super sites' (Level-3) has been established, covering European forest, arable, grassland and wetland sites, with the objective of quantifying the N budget at a high spatial resolution and temporal frequency for 4.5 years, and to estimate greenhouse gas budgets (N 2 O, CH 4 and CO 2). These sites are supported by a network of low-cost flux measurements (Level-2, 9 sites) and a network to infer reactive N fluxes at 58 sites (Level-1), for comparison with carbon (C) flux measurements. Measurements at the Level-3 sites include high resolution N 2 O, NO (also CH 4 , CO 2) fluxes, wet and dry N deposition, leaching of N and C and N transformations in plant, litter and soil. Results for the first 11 months (1.8.2006 to 30.6.2007) suggest that the grasslands are the largest source of N 2 O, that forests are the largest source of NO and sink of CH 4 and that N deposition rates influence NO and N 2 O fluxes in non-agricultural ecosystems. The NO and N 2 O emission ratio is influenced by soil type and precipitation. First budgets of reactive N entering and leaving the ecosystem and of net greenhouse gas exchange are outlined. Further information on rates of denitrification to N 2 and biological N 2 fixation is required to
  • Article
    Closed (non-steady state) chamber measurements are often used to determine the gas exchange of N2O. Many researchers have addressed the underestimation of the emission estimates obtained from closed chamber measurements when using linear regression methods. However, the linear regression method is still usually applied to derive the flux. The importance of using non-linear regression methods is demonstrated with data from four fertilizing events each consisting of 1month of automatic chamber measurements at Cabauw in the Netherlands in the period from July 2005 to July 2006. It is presented that the cumulative emission estimates with the exponential regression method are close to the cumulative emissions estimates with the intercept method. The linear estimates differ by up to 60% of the estimates with the exponential method. The performance of each method is validated using a C2H6 tracer and a goodness-of-fit analysis. The goodness-of-fit is much better for the exponential than the linear regression method. The systematic error due to linear regression is of the same order as the estimated uncertainty due to temporal variation. Therefore, closed-chamber data should be tested for non-linearity and an appropriate method should be used to calculate the flux.
  • Article
    In a successional range of sites on former arable land in Denmark and Scotland, CH4 oxidation rates took more than 100 y to reach pre-cultivation level. During the first 2–5 y following abandonment of agriculture, CH4 oxidation decreased slightly, eventually followed by an increase from 5–15 μg CH4 m−2 h−1 to a substantially higher rate of 100–150 μg CH4 m−2 h−1 in the oldest (200 y) woodlands.
  • Article
    To better understand the biotic and abiotic factors that control soil CO2 efflux, we compared seasonal and diurnal variations in simultaneously measured forest-floor CO2 effluxes and soil CO2 concentration profiles in a 54-year-old Douglas fir forest on the east coast of Vancouver Island. We used small solid-state infrared CO2 sensors for long-term continuous real-time measurement of CO2 concentrations at different depths, and measured half-hourly soil CO2 effluxes with an automated non-steady-state chamber. We describe a simple steady-state method to measure CO2 diffusivity in undisturbed soil cores. The method accounts for the CO2 production in the soil and uses an analytical solution to the diffusion equation. The diffusivity was related to air-filled porosity by a power law function, which was independent of soil depth. CO2 concentration at all depths increased with increase in soil temperature, likely due to a rise in CO2 production, and with increase in soil water content due to decreased diffusivity or increased CO2 production or both. It also increased with soil depth reaching almost 10 mmol mol−1 at the 50-cm depth. Annually, soil CO2 efflux was best described by an exponential function of soil temperature at the 5-cm depth, with the reference efflux at 10 °C (F10) of 2.6 μmol m−2 s−1 and the Q10 of 3.7. No evidence of displacement of CO2-rich soil air with rain was observed.
  • Article
    Full-text available
    Chamber methods for measuring trace gas fluxes are prone to errors resulting in large part from the alteration of near-surface concentration gradients. There is little information available, however, for quantifying these errors or determining how they vary with soil physical properties, chamber deployment methods, and flux calculation schemes. This study used numerical modeling to examine how these factors influence flux estimate errors in physically uniform and nonuniform soil profiles. Errors varied widely among profiles and flux calculation techniques. Soil profiles having identical predeployment fluxes but differing in water content and bulk density generated substantially different flux chamber data. A theoretical flux model that assumes physical uniformity performed relatively well in nonuniform soils but still generated substantial errors. For all flux models, errors were minimized with larger effective chamber heights (h) and shorter deployment times (DT). In light of these findings, recent studies that recommend minimizing h and extending DT to enhance nonlinearity of chamber data need to be reevaluated. It was also determined that random measurement error can result in skewed flux-estimate errors. Selection of chamber and flux calculation methods should consider the physical characteristics of the soil profile as well as measurement error. The techniques presented here can be used to develop soil- and method-specific error estimates.