A re-examination of closed flux chamber methods for the measurement of trace gas emissions from soils to the atmosphere

The most widely used method for measuring the emission of a trace gas such as N₂O from soil to the atmosphere involves the accumulation of the gas under closed chambers followed by sampling and analysis (by gas chromatography or infrared methods). These chambers can affect the gas exchange, and so improved designs have been proposed. We have tested their performance. One design includes a vent tube to allow ambient pressure fluctuations to occur also inside the chamber. We tested it against a sealed version on two different grassland sites during N₂O peak emissions in spring 1997. On a welldrained soil with a fairly large air permeability vented chambers yielded fluxes as much as five times those of sealed chambers, depending on wind speed. By contrast, on a heavier and wetter soil with smaller air permeability vented chambers averaged only 88% of the fluxes observed with sealed chambers. The effects of venting cannot be explained solely on the basis of mean pressure differences inside and outside the chamber. It seems more likely that wind blowing over the vent depressurizes the chamber (Venturi effect), resulting in significant gas flow from the more permeable soil into the interior of the chamber. The opposite trend for the less permeable soil suggests that diffusion losses through the vent tube are greater than the increase in concentration due to soil gas flow. Venting can create larger errors than the ones it is supposed to overcome.     

Wind velocity perturbation of soil respiration measurements using closed dynamic chambers

Soil respiration measurements performed with closed dynamic chambers are very sensitive to pressure differences inside and outside the chamber: differences as small as 1 Pa can induce errors that are of the same magnitude as the flux itself. The problem is usually solved by adding a vent to the experimental set-up. However, although this may give acceptable results in most cases, it is not effective at sites that are very exposed to wind. At the CarboEurope–IP agricultural site of Lonzée (Belgium), on bare soil, we used a vent composed of a vertical tube whose upper end was placed between two horizontal plates. Whilst this system worked properly in low-wind conditions, it led to a significant flux over-estimation (up to 300%) under strong wind conditions. We analysed the causes of this error and attributed it to a dynamic pressure effect at the vent, leading to air aspiration from within the chamber. We suggest that this is because the wind at the vent level was not the same as that experienced in the chamber, because of the large vertical wind speed gradient close to the soil. Another vent geometry was then proposed that positioned the vent at the chamber level. This new design was tested on both manual and automatically operated chambers. It was found to be efficient in windy conditions as most of the artificial correlation between soil respiration measurements and wind speed had disappeared.     

影响静态箱检测开放式气体排放源N2O排放通量的关键因子

为研究影响静态箱检测开放式气体排放源氧化亚氮(N2O)排放通量的关键因子,以提高静态箱检测气体排放通量的准确性,该文在实验室条件下,探究了箱体配置(有无通气孔、有无风扇)和检测条件(不同密闭时间:30、40、50和60 min;不同排放源表面风速:0、0.5、1.0、1.5和2.0 m/s)对300 mm(直径)×300 mm(高度)(D300 mm×H300 mm)的静态箱检测N2O排放通量准确性的影响规律。结果表明,不同配置的静态箱测量结果偏差率随时间的变化趋势均相同,其中有通气孔和风扇的箱体在不同风速下的检测稳定性较好,检测准确性最高。当排放源表面风速为0~2 m/s时,风扇对静态箱检测准确性无显著性影响,排放源表面的风主要通过通气孔影响静态箱的检测准确性。静态箱检测的气体排放通量与实际排放通量的偏差率随排放源表面风速和箱体密闭时间的增加而显著降低。该试验推荐在排放源表面风速小于2 m/s的无粪便堆积的奶牛运动场以及排放源介质相似的开放式气体排放系统中使用有通气孔和风扇的静态箱对N2O排放通量进行检测,密闭50 min。     

Quantification of uncertainty in trace gas fluxes measured by the static chamber method

Fluxes of methane (CH₄) and nitrous oxide (N₂O) are commonly measured with closed static chambers. Here, we analyse several of the uncertainties inherent in these measurements, including the accuracy of calibration gases, repeatability of the concentration measurements, choice of model used to calculate the flux and lack of fit to the model, as well as inaccuracies in measurements of sampling time, temperature, pressure and chamber volume. In an analysis of almost 1000 flux measurements from six sites in the UK, the choice of model for calculating the flux and model lack‐of‐fit were the largest sources of uncertainty. The analysis provides confidence intervals based on the measurement errors, which are typically 20%. Our best estimate, using the best‐fitting model, but substituting the linear model in the case of concave fits, gave a mean flux that is 25% greater than that calculated with the linear model. The best‐fit non‐linear model provided a better (convex) fit to the data than linear regression in 36% of the measurements. We demonstrate a method to balance the number of gas samples per chamber (n_samples) and the number of chambers, so as to minimize the total uncertainty in the estimate of the mean flux for a site with a fixed number of gas samples. The standard error generally decreased over the available range in n_samples, suggesting that more samples per chamber (at the expense of proportionally fewer chambers) would improve estimates of the mean flux at these sites.     

A comprehensive approach to soil‐atmosphere trace‐gas flux estimation with static chambers

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 ).     

Closed chamber systems underestimate soil CO2 efflux

Chamber systems are widely used to measure soil CO₂ efflux, using either a closed or an open gas exchange methodology. In comparisons between these two methods fluxes measured with closed systems are often found to be around 10% less than those measured with open systems. One reason why closed chambers might systematically underestimate the true efflux rate is that the effective chamber volume is larger than the volume of the chamber alone, i.e. it includes the volume of air‐filled spaces in the soil. In tests carried out in a northern forest, this error resulted in a closed chamber underestimating the true efflux by up to 30%, with an average underestimation of around 10%.     

A modified McIntyre and Phillip approach to measure top‐soil gas diffusivity in‐situ

The McIntyre and Phillip method yields the product of a gas‐diffusion coefficient (D_S) and the gas‐filled proportion of soil volume ε. Until now, ε had to be measured independently from soil cores in order to obtain D_S. To avoid soil sampling, we broke up chamber measurement results by means of an empirical relationship D_S= f(ε). In contrast to an exclusive use of such an empirical relationship, this approach is advantageous in that the site‐specific information concerning pore continuity is integrated into the result. Another modification involves the use of a non‐linear regression technique, which fits the unknown parameters of the mechanistic dilution function of the tracer gas to the measured values. In this way, the independent measurement of chamber clearance with a ruler could be replaced with an estimation based on the dilution function. We could then show, by means of a Monte Carlo simulation, that the exponential parameter of the dilution function contributes to the highest error of the diffusion coefficient estimation from the 6 input parameters. We then compared the results of the following methods at 6 sites. The methods included: (a) the approach described above, (b) the laboratory measurement on soil cores, and (c) the original McIntyre and Philip method. This method is a combination of in‐situ chamber measurement and laboratory measurement of the air‐filled soil fraction. We did not detect any significant differences in the means of our method (a) in any of the aforementioned cases, as well as in the laboratory measurement (b). Deviations between individual measurements could be attributed to differences in spatial integration. These deviations are a result of scale‐dependent spatial heterogeneity and thereby provide site‐specific information on soil structure.     

An explanation of linear increases in gas concentration under closed chambers used to measure gas exchange between soil and the atmosphere

Earlier models describing the accumulation of gases under closed chambers are based on the assumption of a constant concentration source that does not change during the time of chamber deployment. A new model is proposed which is based on the assumption of a constant production source, and takes into account possible changes in gas concentrations at the source during chamber deployment. Using N₂O as an example, simulations have been carried out for different source strength and depth, diffusivities and air porosities. The main finding was a chamber‐induced increase in gas concentrations in the upper part of the soil profile, including the depth where the N₂O source is located. The increase started immediately after chamber closure. Nevertheless, fluxes calculated from increasing concentrations within the chamber's headspace were always less than those expected under undisturbed conditions, i.e. in the absence of a chamber. This was due to a proportion of the gas produced being stored within the soil profile while the chamber was in place. The discrepancy caused by this effect increased with increasing air‐filled porosity and decreasing height of the chamber, and a procedure for correcting chamber flux measurements accordingly is proposed. The increase in soil gas concentrations after chamber closure was confirmed in a laboratory experiment.     

Optimizing the use of open chambers to measure ammonia volatilization in field plots amended with urea

Measuring ammonia(NH₃)volatilization from urea-fertilized soils is crucial for evaluation of practices that reduce gaseous nitrogen(N)losses in agriculture.The small area of chambers used for NH₃volatilization measurements compared with the size of field plots may cause significant errors if inadequate sampling strategies are adopted.Our aims were:i)to investigate the effect of using multiple open chambers on the variability in the measurement of NH₃volatilization in urea-amended field plots and ii)to define the critical period of NH₃-N losses during which the concentration of sampling effort is capable of reducing uncertainty.The use of only one chamber covering 0.015%of the plot(51.84 m²)generates a value of NH₃-N loss within an expected margin of error of 30%around the true mean.To reduce the error margin by half(15%),3–7 chambers were required with a mean of 5 chambers per plot.Concentrating the sampling efforts in the first two weeks after urea application,which is usually the most critical period of N losses and associated errors,represents an efficient strategy to lessen uncertainty in the measurements of NH₃volatilization.This strategy enhances the power of detection of NH₃-N loss abatement in field experiments using chambers.     

Analysing repeated measurements in soil monitoring and experimentation

Field monitoring, leaching studies, and experimentation in soil biology are often now being done non‐destructively using fixed installations so that measurements are made repeatedly on the same units. The resulting data for each unit (suction cup, lysimeter, incubation chamber) constitute a time series in which there may be autocorrelation. The usual methods of statistical analysis, such as the analysis of variance, must be modified or replaced by more suitable ones to take account of the possible correlation. This paper describes the split‐plot design of such experiments, shows how to assess the variance–covariance matrix of residuals for uniformity by the Greenhouse–Geisser statistic, and shows how to use this statistic to adjust the degrees of freedom in a formal test of significance. It also describes more recent methods. Ante‐dependence analysis identifies the extent of the temporal correlation in the data and provides approximate significance tests for the treatments. Alternatively, the paper also shows how the traditional analysis of variance may be replaced by a restricted maximum likelihood analysis which gives Wald statistics. The techniques are illustrated with data on CO₂ evolved from soil incubated for 75 days in closed chambers, during which time the gas was measured on 24 occasions to give time series for three replicates of each combination of two soils (limed and unlimed) and three types of ryegrass amendment. An ante‐dependence structure (extending to ninth order) weakened the usual significance test within the subunit stratum. The Wald statistics showed that there was, nevertheless, a strong interaction between the treatments and time.     

Small lateral air pressure gradients generated by a large chamber system have a strong effect on CO2 transport in soil

Gas transport in soils is usually assumed to be purely diffusive, although several studies have shown that non-diffusive processes can significantly enhance soil gas transport. These processes include barometric air pressure changes, wind-induced pressure pumping and static air pressure fields generated by wind interacting with obstacles. The associated pressure gradients in the soil can cause advective gas fluxes that are much larger than diffusive fluxes. However, the contributions of the respective transport processes are difficult to separate. We developed a large chamber system to simulate pressure fields and investigate their influence on soil gas transport. The chamber consists of four subspaces in which pressure is regulated by fans that blow air in or out of the chamber. With this setup, we conducted experiments with oscillating and static pressure fields. CO₂ concentrations were measured along two soil profiles beneath the chamber. We found a significant relationship between static lateral pressure gradients and the change in the CO₂ profiles (R² = 0.53; p-value <2e-16). Even small pressure gradients between −1 and 1 Pa relative to ambient pressure resulted in an increase or decrease in CO₂ concentrations of 8% on average in the upper soil, indicating advective flow of air in the pore space. Positive pressure gradients resulted in decreasing, negative pressure gradients in increasing CO₂ concentrations. The concentration changes were probably caused by an advective flow field in the soil beneath the chamber generated by the pressure gradients. No effect of oscillating pressure fields was observed in this study. The results indicate that static lateral pressure gradients have a substantial impact on soil gas transport and therefore are an important driver of gas exchange between soil and atmosphere. Lateral pressure gradients in a comparable range can be induced under windy conditions when wind interacts with terrain features. They can also be caused by chambers used for flux measurements at high wind speed or by fans used for head-space mixing within the chambers, which yields biased flux estimates.     

Optimizing chamber methods for measuring nitrous oxide emissions from plot‐based agricultural experiments

Nitrous oxide emissions (N₂O) from agricultural land are spatially and temporally variable. Most emission measurements are made with small (? 1 m² area) static chambers. We used N₂O chamber data collected from multiple field experiments across different geo‐climatic zones in the UK and from a range of nitrogen treatments to quantify uncertainties associated with flux measurements. Data were analysed to assess the spatial variability of fluxes, the degree of linearity of headspace N₂O accumulation and the robustness of using ambient air N₂O concentrations as a surrogate for sampling immediately after closure (T₀). Data showed differences of up to more than 50‐fold between the maximum and minimum N₂O flux from five chambers within one plot on a single sampling occasion, and that reliability of flux measurements increased with greater numbers of chambers. In more than 90% of the 1970 cases where linearity of headspace N₂O accumulation was measured (with four or more sampling points), linear accumulation was observed; however, where non‐linear accumulation was seen this could result in a 26% under‐estimate of the flux. Statistical analysis demonstrated that the use of ambient air as a surrogate for T₀ headspace samples did not result in any consistent bias in calculated fluxes. Spatial variability has the potential to result in erroneous flux estimates if not taken into account, and generally introduces a far larger uncertainty into the calculated flux (commonly orders of magnitude more) than any uncertainties introduced through reduced headspace sampling or assumption of linearity of headspace accumulation. Hence, when deploying finite resources, maximizing chamber numbers should be given priority over maximizing the number of headspace samplings per enclosure period.     

Movement of nitrogen and carbon from a septic system drainfield

A septic system drainfield that had been in use for 6 yr was instrumented to study the vertical and horizontal movement of N and C. The original system was designed so that the effluent from the septic tank could be deverted to either of two parallel leaching trenches. Each trench contained three precast leaching chambers (1.22 m×2.44 m×0.3 m) placed end to end at a depth of 1.4 m. Since installation each trench had been used alternately for 6 mo periods. In each of the 2 yr of this study, effluent began to pond in the leaching chamber within 24 h after the effluent was directed to that trench. Approximately 100 days were required to develop a quasi steady state with respect to the depth of ponding and concentrations of N and C in the soil solution. In both years of the study about 25% of the influent-N was mineralized. However, in the first year very little nitrification occurred while in the second year essentially all of the NH₄ in the soil profile was nitrified and moved without apparent loss to the groundwater. These differences in N transformation appeared to be indirectly controlled by rainfall with 50% less precipitation received in the second than in the first year.     

Method for 14C‐labeling maize field plots and assessment of label uniformity within plots

Abstract

There is increasing interest in use of isotopic tracers to study nutrient liberation and transformation in plant tissues and soils. We developed a technique for pulse‐labeling plants in the field with ¹⁴C. Spatial distribution of radioactivity was measured in plots of maize (Zea mays L.) plants exposed to ¹⁴CO₂. Two clear polyvinyl chambers measuring 1 m wide × 2 m long × 1 m high were used to ¹⁴C‐ label maize plants in conventional tillage and no‐tillage treatments. A closed loop in‐line with a pump allowed injection of ¹⁴CO₂ and unlabeled CO₂, and subsampling through an infrared gas analyzer. Cooling and mixing of the air within the chambers was achieved through the use of a free‐standing automobile radiator with fan placed in the center of each plot. The specific activities of leaf tips differed by an order of magnitude among maize plants within the plot. Tillage and time after labeling within the first 48 h had no significant effect on specific activity of maize plants. Plant activity significantly differed by row. The row closest to the inlet and along the edge of the chamber was significantly lower in several plots. Despite differences among leaf tip specific activities, total aboveground activity was uniform within the plot. Plant allometry and plant sampling immediately after labeling would help in correcting for within chamber variability in future field labeling studies.     

柴油机燃烧室的系统设计方法研究与应用

为使柴油机燃烧室设计走向系统化和正规化,提出了柴油机燃烧室系统设计的概念。通过对因子处理方法和响应分析方法的梳理总结了9种因子-响应组合方法,选取其中1个燃烧室设计方法进行方法展示。此方法以一款四气门直喷式柴油机作为研究对象,建立了缸内气体瞬态流动模型,以缸内气体流速和湍流动能作为评价标准,在压缩比基本保持不变的前提下,对比分析了缩口率分别为16.4%、6.1%、9.8%、9.8%且底面凸台形状不同的A、B、C、D 4种ω型燃烧室对缸内流场的影响。研究结果表明,燃烧室几何结构对柴油机进气阶段和压缩阶段前期的缸内气流运动影响较小,对压缩阶段后期缸内气流运动影响显著。在上止点前后20°曲轴转角区段,底面凸台呈锥形的C型燃烧室的平均挤流速度、逆挤流速度比底面凸台呈球形的D型燃烧室分别高25.2%、26.4%;缩口率为16.4%的A型燃烧室内气体平均湍流动能比缩口率为9.8%的D型燃烧室高25.4%。与底面凸台呈椭球形的A型和呈球形的D型燃烧室相比,底面凸台呈45°锥形的B、C型燃烧室在湍流动能强度和逆挤流强度方面的保持性更好。该文研究结果可为柴油机燃烧室结构设计和优化提供参考。     

Variations in the Diurnal Flux of Greenhouse Gases from Soil and Optimizing the Sampling Protocol for Closed Static Chambers

There is no standardized method for the sampling of greenhouse gas fluxes from soil. Two methods are primarily used: closed dynamic chamber (CDC) and closed static chamber (CSC) systems. The most complex and costly are the CDC systems, which can sample gases in situ. However, the low-cost CSC systems are being increasingly used in which the gas samples are collected manually and analyzed off-site at a later date. Given their growing popularity, it is important to optimize the sampling procedure of the CSC systems to ensure that the measurements are both repeatable and representative. Samples from a commercial potato crop were collected in the morning and afternoon at 0, 15, 30, 60, 90, and 120 min after the chambers were closed, and the concentrations of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) were determined using gas chromatography. The concentrations of CO₂ and N₂O inside chambers increased linearly over time, whereas the concentration of CH₄ remained constant. The fluxes of CO₂ and N₂O from soil were greater in the afternoon than the morning, whereas the flux of CH₄ was greater in the morning. For longer-term single-point soil flux monitoring using CSCs with a volume of 6.3 L, it is recommended that samples are collected in the morning at 0, 30, and 60 min after chambers are closed. This approach will ensure that the concentration of the gases are representative and will allow for a high level of repeatability and certainty in the results.     

A simple method for determination of ammonium in semimicro‐Kjeldahl analysis of soils and plant materials using a block digester

Abstract

A simple method for determination of ammonium in semimicro‐Kjeldahl analysis of soils and plant materials using a Tecator or Technicon 40‐tube block digester is described. It involves use of an inexpensive steam distillation apparatus that permits direct distillation of ammonium from the tubes used for Kjeldahl digestion in 40‐tube block digesters. The method is rapid and precise, and it gives results that agree closely with those obtained by the customary method of ammonium N analysis involving transfer of the Kjeldahl digest before distillation.     

Non-linearity and error in modelling soil processes

Error in models and their inputs can be propagated to outputs. This is important for modelling soil processes because soil properties used as parameters commonly contain error in the statistical sense, that is, variation. Model error can be assessed by validation procedures, but tests are needed for the propagation of (statistical) error from input to output. Input error interacts with non‐linearity in the model such that it contributes to the mean of the output as well as its error. This can lead to seriously incorrect results if input error is ignored when a non‐linear model is used, as is demonstrated for the Arrhenius equation. Tests for non‐linearity and error propagation are suggested. The simplest test for non‐linearity is a graph of the output against the input. This can be supplemented if necessary by testing whether the mean of the output changes as the standard deviation of the input increases. The tests for error propagation examine whether error is suppressed or exaggerated as it is propagated through the model and whether changes in the error in one input influence the propagation of another. Applying these tests to a leaching model with rate and capacity parameters showed differences between the parameters, which emphasized that statements about non‐linearity must be for specific inputs and outputs. In particular, simulations of mean annual concentrations of solute in drainage and concentrations on individual days differed greatly in the amount of non‐linearity revealed and in the way error was propagated. This result is interpreted in terms of decoherence.     

吹扫式仿生嗅觉检测腔结构设计及流场性能模拟与试验

为了优选吹扫式仿生嗅觉检测腔流场结构,提高腔内流体速度分布均匀稳定性,以气体运动微分方程为基础,利用计算流体力学软件Fluent对检测腔内部流场进行了三维数值模拟,得到了设计工况条件下的气体流动特性,提出并分析比较了3种检测腔模型,同时将最优模型的模拟值与试验数据进行了对比分析。计算结果表明,检测腔结构影响腔内气体流速分布,多管道式检测腔在沿管道轴向0.035~0.049 m,气流速度变化存在平滑区,且稳定在0.018~0.268 m/s,能够满足检测工作条件,而线性排列式不存在平滑区,平行排列式平滑区速度范围仅为0.001~0.018 m/s;多管道式检测腔在流速均匀稳定性方面存在优势,气流速度最大偏差比和不均匀系数分别为0.830 6和0.292 0;同时,在数值模拟腔内气体置换时间中,3种检测腔经历时间分别为223.4、302.0和213.8 s,多管道式结构的时间数值最小说明气流响应快,工作效率高。多管道式结构模型能有效改善传感器数值检测的一致性,模型试验中传感器灵敏度检测数值标准差范围为0.153 5~0.428 3,变异系数分布在0.030 5~0.082 7。该研究可为仿生嗅觉检测腔结构的流场均匀性设计提供参考。