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Comparison of CO2, CH4 and N2O soil-atmosphere exchange measured in static chambers with cavity ring-down spectroscopy and gas chromatography
... For both light and dark measurements, the MDF in our study was, on average, 0.015 ± 0.001 µmol m −2 h −1 . This is lower than the reported 0.18 µmol m −2 h −1 MDF rates in other nutrient-poor ecosystems by Christiansen et al. (2015) (Table 1). ...
... Our analyses of the chamber closure time confirm this: during dark measurements and over all measurement periods, we found that the uptake rate at 3-5 minutes were greatest, and decreased with every minute of added chamber closure time 315 (Fig. 5). In contrast to this, as mentioned above, more than 40% of the fluxes were below the MDF at 3-minute closure time, confirming that these very short closure times may result in higher uncertainties of flux estimates due to fewer sample points (Christiansen et al., 2015). It is, therefore, crucial to consider the precision of the instruments used in the field to identify the best-suited chamber closure time. ...
... For dark measurements, we suggest shorter chamber closure times of 3-5 min. These findings are in line with other studies (Cowan et al., 2014;Kroon et al., 2008;Christiansen et al., 2015) but confirm, for the first time, that these recommendations are applicable to nutrient-poor ecosystems. ...
Nitrous oxide (N2O) is the third most important greenhouse gas, with its atmospheric concentration rising from 273 parts per billion (ppb) to 336 ppb since 1800, primarily due to agricultural activities. However, nutrient-poor natural soils, including those in the sub-Arctic, also emit and consume N2O. These soils have not been studied extensively, partly due to challenges in reliably detecting low fluxes. Methodological limitations were largely influenced by the available instrumentation; the lack of portable gas analysers for N2O with adequate accuracy led researchers to rely on manual air sampling from closed flux chambers, followed by laboratory analysis using gas chromatographs (GC). In this study, we utilized a fast-responding portable gas analyser (PGA; Aeris N2O/CO2) combined with a custom manual chamber system, which includes both transparent (light) and opaque (dark) measurements, to effectively measure low N2O fluxes from a nutrient-poor sub-Arctic peatland. We assessed the analyser's performance under low-flux conditions, evaluated the effects of chamber closure times, and compared linear and non-linear models for quantifying concentration gradients. Additionally, we analyzed flux rates based on high-frequency in situ observations against a method that randomly selects discrete samples from the full time series, simulating a GC-based approach. Our results indicate that the PGA can reliably detect and compute low N2O flux rates, averaging 12.9 ± 28.4 nmol m⁻² h⁻¹ under light conditions and -46.1 ± 38.2 nmol m⁻² h⁻¹ under dark conditions, depending on chamber closure time. The majority of fluxes (88 % for light and 74 % for dark measurements) exceeded the minimum detectable flux (MDF), which was 14.5 ± 1.05 nmol m⁻² h⁻¹ for light and 14.7 ± 1.08 nmol m⁻² h⁻¹ for dark measurements. Our comparison of chamber closure times (3–10 minutes) showed that a 3-minute closure may be inadequate for capturing low N2O fluxes during light measurements, while closure times of 4–10 minutes yield more reliable results. For dark measurements, where N2O uptake peaked with shorter closure times, we recommend a closure time of 3–5 minutes unless data are limited; in such cases, longer times may help capture fluxes above the MDF. In our study, all N2O fluxes were calculated using the non-linear model or corresponded with the linear model when data exhibited a linear distribution. Compared to PGA-based flux calculations, GC simulations underestimated N2O fluxes when using 3–6 samples. Therefore, we conclude that fast-responding analysers may be more suitable for measuring low N2O fluxes, enhancing our understanding of the complex dynamics of N2O emissions.
... Soils exchange substantial amounts of CO 2 and CH 4 with the atmosphere (Bond-Lamberty and Thomson 2010, IPCC 2023, and our understanding of soil greenhouse gas (GHG) budgets and the processes governing them is underpinned by gas flux measurements (Bahn et al. 2010, Bond-Lamberty and Thomson 2010, Oertel et al. 2016. Accurate estimation of GHG flux rates and dynamics is therefore important, and while there is a plethora of techniques available for GHG flux measurements, each comes with its own caveats and limitations (Bastviken et al. 2022, Christiansen et al. 2015, Davidson et al. 2002. ...
... Non-steady-state chambers (Livingston and Hutchinson 1995) are commonly used for soil GHG flux measurements and remain a relatively cheap and logistically advantageous method due to low weight and power consumption. While the use of non-steady-state chambers is often treated as a distinct gas flux measurement method, it includes a diversity of chambers and can be used with a range of gas analyzers and therefore varies in terms of acquisition and running costs, instrument precision and user competence needed for adequate usage (Bastviken et al. 2022, Christiansen et al. 2015, Pihlatie et al. 2013, Pumpanen et al. 2004). The multitude of choices to be madefrom technical choices on chamber design, soil collar insertion depth and statistical models to research strategy choices on experimental designhas generated a significant body of literature discussing potential pitfalls and biases , Kreyling et al. 2018, Pavelka et al. 2018). ...
... Lastly, we examined the proportion of estimated flux rates lower than the calculated minimum detectable flux, as defined by Christiansen et al. (2015), for all chamber closure periods. The minimum detectable flux is a function of the chamber closure period length and may therefore be important to consider when making choices on what chamber closure period(s) to apply. ...
Non-steady-state chambers are often used for greenhouse gas flux measurements, and while there are recommendations on how long to keep the chamber closed, it is less investigated to what extent the length of the chamber closure period affects the estimated flux rates and which closure periods may provide the most accurate linear and non-linear flux estimates. Previous studies have shown that the closure of non-steady-state chambers induces a non-linear concentration development inside the chamber, even across short chamber closure periods, and that both linear and non-linear flux estimates are impacted by the chamber closure period itself. Based on 3,159 individual soil CO2 and CH4 flux measurements, we analyzed how linear regression and Hutchinson and Mosier (1981) modeled flux estimates are affected by the length of the chamber closure period by increasing it in increments of 30 sec, with a minimum and maximum chamber closure period of 60 and 300 sec, respectively. Across all detected flux measurements, the effect of chamber closure period length varied between 1.4–8.0 % for linear regression estimates and between 0.4–17.8 % for Hutchinson–Mosier estimates, and the largest effect sizes were observed in high flux regions. While both linear regression and Hutchinson–Mosier based estimates decreased as the chamber closure period increased, we observed a clear convergence of flux estimates as shorter and longer chamber closure periods were used for linear regression and Hutchinson–Mosier based estimation, respectively. This suggests using closure periods as short as possible for linear regression flux estimation or ensuring long-enough closure periods to observe a stabilization of Hutchinson–Mosier flux estimates over time. This analysis was based on soil flux measurements, but because the perturbation of the concentration gradient is related to the non-steady-state chamber technique rather than the measured ecosystem component, our results have implications for all flux measurements conducted with non-steady-state chambers.
... All fluxes are reported with ± standard error. The detection limit of the fluxes was calculated using the minimum detectable flux (MDF) method presented in Christiansen et al., (2015) using a pressure of 1000 hPa and 10 • C and with an accuracy of the GC instrument of 50 ppb for CH 4 (Bruker, 2010). ...
... The number of gas samples used for flux estimates has been recognized as the largest source of error for chamber measurements (Levy et al., 2011), and as this was used in this study, it should reduce the uncertainty of the linear regression fit used for the calculation of CH 4 fluxes (Cowan et al., 2021). However, although five gas samples were conducted, the detection limit of CH 4 reported by Christiansen et al., (2015) where much higher (3.5 µmol m 2 h − 1 corresponding to ~10 g CH 4 -C ha − 1 day − 1 ). Possibly, the shorter closing time of 30 minutes by Christiansen et al., (2015) has negatively influenced the MDF. ...
... However, although five gas samples were conducted, the detection limit of CH 4 reported by Christiansen et al., (2015) where much higher (3.5 µmol m 2 h − 1 corresponding to ~10 g CH 4 -C ha − 1 day − 1 ). Possibly, the shorter closing time of 30 minutes by Christiansen et al., (2015) has negatively influenced the MDF. ...
... For example, a GC coupled to an electron capture detector (GC-ECD) has been used for NO 2 and SF 6 , while a GC coupled to a flame ionization detector (GC-FID) has been used for carbon-containing gases such as CH 4 , CO 2 , and CO. However, there are only a few studies in which multiple gases in soil are analyzed using a single GC system, e.g., NO 2 , CO 2 , and CH 4 (Christiansen et al., 2015;Brannon et al., 2016); NO 2 , CO 2 , CH 4 , and CO (van der Laan et al., 2009); and NO 2 , CO 2 , CH 4 , CO, and SF 6 (Lopez et al., 2015). Although these studies claimed that multiple soil gases were measured using by a single GC system, several sub-GC systems optimized for different target gases (e.g., GC-ECD, GC-FID with different columns and settings) were integrated into a single GC system. ...
... The recently advanced optical technique of cavity ringdown spectroscopy enables simultaneous measurement of multiple GHGs (NO 2 , CO 2 , and CH 4 ) from soils; it has been successfully applied for simultaneous gas flux measurements of multiple GHGs with a temporal resolution of minutes to tens of minutes (Christiansen et al., 2015;Brannon et al., 2016;Lebegue et al., 2016;Barba et al., 2019;Courtois et al., 2019). Despite the advantages of cavity ring-down spectroscopy, its application is limited to GHGs because infrared absorption wavelengths of gases often overlap and experience interference with other gases. ...
... The minimum detectable flux (MDF) of each soil gas can be estimated based on the derivations by Courtois et al. (2019) originally developed by Christiansen et al. (2015) and Nickerson (2016) as ...
We developed a mass spectrometric soil-gas flux measurement system using a portable high-resolution multi-turn time-of-flight mass spectrometer, called MULTUM, and we combined it with an automated soil-gas flux chamber for the continuous field measurement of multiple gas concentrations with a high temporal resolution. The developed system continuously measures the concentrations of four different atmospheric gases (NO2, CH4, CO2, and field soil–atmosphere flux measurements of greenhouse gases (NO2, O2) ranging over 6 orders of magnitude at one time using a single gas sample. The measurements are performed every 2.5 min with an analytical precision (2 standard deviations) of ±34 ppbv for NO2; ±170 ppbv, CH4; ±16 ppmv, CO2; and ±0.60 vol %, O2 at their atmospheric concentrations. The developed system was used for the continuous field soil–atmosphere flux measurements of greenhouse gases (NO2, CH4, and CO2) and O2 with a 1 h resolution. The minimum quantitative fluxes (2 standard deviations) were estimated via a simulation as 70.2 µgNm-2h-1 for NO2; 139 µgCm-2h-1, CH4; 11.7 mg C m-2 h-1, CO2; and 9.8 g O2 m-2 h-1, O2. The estimated minimum detectable fluxes (2 standard deviations) were 17.2 µgNm-2h-1 for NO2; 35.4 µgCm-2h-1, CH4; 2.6 mg C m-2 h-1, CO2; and 2.9 g O2 m-2 h-1, O2. The developed system was deployed at the university farm of the Ehime University (Matsuyama, Ehime, Japan) for a field observation over 5 d. An abrupt increase in NO2 flux from 70 to 682 µgNm-2h-1 was observed a few hours after the first rainfall, whereas no obvious increase was observed in CO2 flux. No abrupt NO2 flux change was observed in succeeding rainfall events, and the observed temporal responses at the first rainfall were different from those observed in a laboratory experiment. The observed differences in temporal flux variation for each gas component show that gas production processes and their responses for each gas component in the soil are different. The results of this study indicate that continuous multiple gas concentration and flux measurements can be employed as a powerful tool for tracking and understanding underlying biological and physicochemical processes in the soil by measuring more tracer gases such as volatile organic carbon, reactive nitrogen, and noble gases, and by exploiting the broad versatility of mass spectrometry in detecting a broad range of gas species.
... This includes streamlined selection of optimal chamber closure periods, straightforward identification of concentration change linearity, and consequently, facile spotting of potential artefacts . Conclusively, developing a reproducible flux calculation procedure, accommodating criteria such as minimum detectable flux (MDF) (Christiansen et al., 2015;Nickerson, 2016), and facilitating proper selection between linear and nonlinear methods, is crucial . ...
... However, if the concentration change is small during chamber closure, the reliability of the flux estimates decreases . MDF, a metric developed by Christiansen et al. (2015), determines the lower limit for flux rates that can be detected with a given measurement precision and closure duration. To be more appropriate for highfrequency measurements, Nickerson (2016) updated the MDF metric by also considering the sampling frequency as shown in Equation 4: ...
Non-steady-state chambers are widely employed for quantifying soil emissions of CO2, CH4, and N2O. Automated non-steady-state (a-NSS) soil chambers, when coupled with online gas analysers, offer the ability to capture high-frequency measurements of greenhouse gas (GHG) fluxes. While these
sampling systems provide valuable insights into GHG emissions, they present post-measurement challenges, including the management of extensive datasets, intricate flux calculations, and considerations for temporal upscaling. In this study, a computationally efficient algorithm was developed to compute
instantaneous fluxes and estimate diel flux patterns using continuous, high-resolution data obtained from an a-NSS sampling system. Applied to a 38-day dataset, the algorithm captured concurrent field measurements of CO2, CH4,
and N2O fluxes. The automated sampling system enables the acquisition of high-frequency data, allowing the detection of episodic gas flux events. By using shape-constrained additive models, a median percentage deviation (bias) of -1.031 and -4.340% was achieved for CO2 and N2O fluxes, respectively.
Simpson's rule allowed for efficient upscale from instantaneous to diel flux values. As a result, the proposed algorithm can rapidly and simultaneously calculate CO2, CH4, and N2O fluxes, providing both instantaneous and diel values directly from raw, high-temporal-resolution data. These advancements
significantly contribute to the field of GHG flux measurement, enhancing both the efficiency and accuracy of calculations for a-NSS soil chambers and deepening our understanding of GHG emissions and their temporal dynamics.
... Sedge-covered, water-saturated wetlands are located in topographic depressions and cover only 14% of the area 21,22 . Uplands and wetlands have distinct redox conditions and patterns of CH 4 production, upon traditional, low frequency (weekly) chamber measurements using manual air sampling and long (>30 min) closure times 29 . Importantly, high-frequency and high-accuracy flux measurements may provide insights into previously unexplored temporal dynamics (for example, night time versus daytime) of atmospheric CH 4 uptake by Arctic soils. ...
... The recent development of field-deployable, high-accuracy gas analysers has made it possible to reliably measure real-time CH 4 concentration changes of <1 ppb. Such high precision allows short (<5 min) closure times with chamber methods, preventing temperature and humidity artefacts from affecting the natural gas diffusion gradient 28,29 . Pairing high-accuracy analysers with automated chambers can generate hourly flux measurements, matching the temporal scale at which many abiotic flux drivers vary (for example, temperature, soil moisture and solar radiation). ...
Arctic wetlands are known methane (CH4) emitters but recent studies
suggest that the Arctic CH4 sink strength may be underestimated. Here we
explore the capacity of well-drained Arctic soils to consume atmospheric
CH4 using >40,000 hourly flux observations and spatially distributed flux
measurements from 4 sites and 14 surface types. While consumption of
atmospheric CH 4 occurred at all sites at rates of 0.092 ± 0.011 mgCH 4 m−2 h−1
(mean ± s.e.), CH 4 uptake displayed distinct diel and seasonal patterns
reflecting ecosystem respiration. Combining in situ flux data with laboratory
investigations and a machine learning approach, we find biotic drivers to
be highly important. Soil moisture outweighed temperature as an abiotic
control and higher CH4 uptake was linked to increased availability of labile
carbon. Our findings imply that soil drying and enhanced nutrient supply
will promote CH4 uptake by Arctic soils, providing a negative feedback to
global climate change.
... The major advantage of these techniques is their ability to carry out high frequency measurements of a number of trace gases simultaneously. With CRDS, spectra can be obtained roughly every 2 s (Christiansen et al., 2015), generating 15-30 times more data points per flux measurement than traditional "manual" chamber-based flux measurements. The simultaneous development of automated chambers, which allow for continuous and unmonitored operation via chamber-management software (such as EosAnalyze-AC, Eosense, Nova Scotia, Canada or SoilFluxPro, LI-COR Biosciences, Nebraska, United States), has created the ability to conduct pseudo-continuous in situ flux measurements capable of five or more individual N 2 O flux measurements per hour (Diefenderfer et al., 2018;Hemes et al., 2019). ...
... The deployment of automated chambers using fast response spectroscopic methods (i.e., CRDS, FTIR, among others) further increases the potential frequency of soil GHG fluxes. These methods also have a number of advantages over manual GC flux measurements (Christiansen et al., 2015;Brannon et al., 2016;Lebegue et al., 2016;Keane et al., 2018;O'Connell et al., 2018;Barba et al., 2019;Courtois et al., 2019;Anthony and Silver, 2021). Current CRDS automated chamber system flux measurement time is about 10 min, at least a third shorter than previous automated chamber systems (Table 1). ...
Soil nitrous oxide (N2O) emissions are an important driver of climate change and are a major mechanism of labile nitrogen (N) loss from terrestrial ecosystems. Evidence increasingly suggests that locations on the landscape that experience biogeochemical fluxes disproportionate to the surrounding matrix (hot spots) and time periods that show disproportionately high fluxes relative to the background (hot moments) strongly influence landscape-scale soil N2O emissions. However, substantial uncertainties remain regarding how to measure and model where and when these extreme soil N2O fluxes occur. High-frequency datasets of soil N2O fluxes are newly possible due to advancements in field-ready instrumentation that uses cavity ring-down spectroscopy (CRDS). Here, we outline the opportunities and challenges that are provided by the deployment of this field-based instrumentation and the collection of high-frequency soil N2O flux datasets. While there are substantial challenges associated with automated CRDS systems, there are also opportunities to utilize these near-continuous data to constrain our understanding of dynamics of the terrestrial N cycle across space and time. Finally, we propose future research directions exploring the influence of hot moments of N2O emissions on the N cycle, particularly considering the gaps surrounding how global change forces are likely to alter N dynamics in the future.
... Moreover, the unique Picarro algorithm can automatically correct the error of the CO 2 concentration caused by the water vapor [47]. Therefore, the Piccaro analyzer has been widely used for measuring soil carbon efflux as reported by many studies [29,[48][49][50]. ...
... One week before each measurement, the aboveground plants were removed, and the chamber was inserted directly into the soil to a depth of about 1-3 cm. The FCO 2 concentrations were recorded with intervals of 1-s, and the measuring process at each sampling site lasted for 2-5 min with five repetitions [49]. The final FCO 2 concentration of each spot was obtained by the repeated measurements, and the soil efflux is calculated by the slope of the linear regression of CO 2 concentration with time. ...
The CO2 efflux from forest soil (FCO2) is one of the largest components of the global carbon cycle. Accurate estimation of FCO2 can help us better understand the carbon cycle in forested areas and precisely predict future climate change. However, the scarcity of field-measured FCO2 data in the subtropical forested area greatly limits our understanding of FCO2 dynamics at regional and global scales. This study used an automatic cavity ring-down spectrophotometer (CRDS) analyzer to measure FCO2 in a typical subtropical forest of southern China in the dry season. We found that the measured FCO2 at two experimental areas experienced similar temporal trends in the dry season and reached the minima around December, whereas the mean FCO2 differed apparently across the two areas (9.05 vs. 5.03 g C m−2 day−1) during the dry season. Moreover, we found that both abiotic (soil temperature and moisture) and biotic (vegetation productivity) factors are significantly and positively correlated, respectively, with the FCO2 variation during the study period. Furthermore, a machine-learning random forest model (RF model) that incorporates remote sensing data is developed and used to predict the FCO2 pattern in the subtropical forest, and the topographic effects on spatiotemporal patterns of FCO2 were further investigated. The model evaluation indicated that the proposed model illustrated high prediction accuracy for the training and testing dataset. Based on the proposed model, the spatiotemporal patterns of FCO2 in the forested watershed that encloses the two monitoring sites were mapped. Results showed that the spatial distribution of FCO2 is obviously affected by topography: the high FCO2 values mainly occur in relatively high altitudinal areas, in slopes of 10–25◦, and in sunny slopes. The results emphasized that future studies should consider topographical effects when simulating FCO2 in subtropical forests. Overall, our study unraveled the spatiotemporal variations of FCO2 and their driving factors in a subtropical forest of southern China in the dry season, and demonstrated that the proposed RF model in combination with remote sensing data can be a useful tool for predicting FCO2 in forested areas, particularly in subtropical and tropical forest ecosystems.
... Using the Pearson correlation coefficient and the coefficient of determination for comparing two or more quantitative methods is a generally preferred approach in the field of N2O research. Comparisons of different methods for N2O analysis made in the literature most commonly used orthogonal and linear regression Brümmer et al., 2017;Tallec et al., 2019), Students t-tests (Christiansen et al., 2015) or were based on raw data (Savage et al., 2014). However, correlation studies as such have limitations when assessing the comparability between two methods since a correlation analysis only identifies the relationship between two variables, not the difference (Giavarina, 2015). ...
... Overall, it was demonstrated that suitable statistical methods have to be adopted when formally assessing the agreement and difference (not only the correlation) between two quantitative methods of measurement, in this case, QCL and GC. Previous comparisons made in the literature commonly based on orthogonal and linear regression Brümmer et al., 2017;Tallec et al., 2019), Students t-tests (Christiansen et al., 2015) or raw data (Savage et al., 2014); but to assess the comparability of a standard and a new method, agreement and bioequivalence statistics are recommended in addition to these other approaches. ...
... Proper operation of the CRDS was checked by measuring the N 2 O concentration of an ultrapure air cylinder and the concentration of a standard gas (0.45 µmol N 2 O mol −1 gas in air) with an uncertainty of 3%, at the beginning and end of each sampling day. The minimum detectable flux (MDF), 0.128 µg N 2 O-N kg −1 soil h −1 , was calculated following Christiansen et al. (2015) for the headspace volume of 0.001 5 m 3 (after subtracting the volume occupied by the pot), a dry soil weight of 0.95 kg, and a chamber mean air temperature of 23 • C. The quantification limit, 0.384 µg N 2 O-N kg −1 soil h −1 , was set to three times the MDF. The flux of N 2 O (F, µg N 2 O-N kg −1 soil h −1 ) was calculated using the following equation: ...
... The change of N 2 O in the headspace was evaluated using a second-order polynomial fit, with the obtained concentration vs. enclosure time. The flux at the time of coverage (t = 0) was estimated using the slope, i.e., derivative of the polynomial function (Christiansen et al., 2015). The parameter η was evaluated with temperature and pressure recorded during the sampling of the pot, and the calculated volume, taking into account the volume of the chamber, the volume occupied by the pots, the system of hoses, and the equipment cavity. ...
In the tropics, frequent nitrogen (N) fertilization of grazing areas can potentially increase nitrous oxide (N2O) emissions. The application of nitrification inhibitors has been reported as an effective management practice for potentially reducing N loss from the soil-plant system and improving N use efficiency (NUE). The aim of this study was to determine the effect of the co-application of nitrapyrin (a nitrification inhibitor, NI) and urea in a tropical Andosol on the behavior of N and the emissions of N2O from autotrophic and heterotrophic nitrification. A greenhouse experiment was performed using a soil (pH 5.9, organic matter content 78 g kg–1, and N 5.6 g kg–1) sown with Cynodon nlemfuensis at 60% water-filled pore space to quantify total N2O emissions, N2O derived from fertilizer, soil ammonium (NH4⁺) and nitrate (NO3–), and NUE. The study included treatments that received deionized water only (control, CK) and two doses of ¹⁵N-enriched urea (65 (UR) and 129 mg N kg–1 (UD)) without or with 350 g nitrapyrin for each 100 kg N (UR + NI and UD + NI). No significant differences were observed in soil NH+ content between the UR and UR + NI treatments, probably because of soil mineralization and immobilization (influenced by high soil organic matter content). Nitrapyrin application failed to maintain a stable pool of labeled NO3⁻ due to the additional NO⁻ produced by heterotrophic nitrification, which is not effectively inhibited by nitrapyrin. After 56 d, N2O emissions in UR (0.51 ± 0.12 mg N2O-N kg–1) and UR + NI (0.45 ± 0.13 mg N2O-N kg–1) were not significantly different; by contrast, emissions were 36.3% lower in UD + NI than in UD. It was concluded that the soil organic N mineralization and heterotrophic nitrification are the main processes of NH4⁺ and NO3– production. Additionally, it was found that N2O emissions were partially a consequence of the direct oxidation of the soil's organic N via heterotrophic nitrification coupled to denitrification. Finally, the results suggest that nitrapyrin would likely exert significant mitigation on N2O emissions only if a substantial N surplus exists in soils with high organic matter content.
... Our method is a simple extension of the statistics of regression; some other methods to estimate uncertainty in chamber studies have been ad hoc and inconsistent. The minimum detectable flux (MDF) method for flux chambers reported in Christiansen et al. (2015) does not include sample size in its calculation, thus the calculated MDF for a measurement with two samples (n = 2) is erroneously the same as a measurement with n > 1000. The analytical uncertainty (as calculated using Equation 2) represents the lower bound on the possible uncertainty in flux measurements from a given system. ...
Flux chamber methodologies are used at the global scale to measure the exchange of trace gases between terrestrial surfaces (soils) and the atmosphere. These methods evolved as a simplistic necessity to measure gas fluxes from a time when gas analysers were limited in capability and costs were prohibitively high, since which thousands of studies have deployed a wide variety of chamber methodologies to build vast datasets of soil fluxes. However, analytical limitations of the methods are often overlooked and are poorly understood by the flux community, leading to confusion and misreporting of observations in some cases. In recent years, the number of commercial suppliers of gas analysers claiming to be capable of measuring trace gas fluxes from chambers has drastically increased, with a myriad of analysers (and low-cost sensors) now on offer with a wide variety of capabilities. While chamber designs and the capabilities of analysers vary by orders of magnitude, the rudimentary analytical uncertainties of individual flux measurements can still be standardised for direct comparison of methods. This study aims to serve as a guide to calculate the analytical uncertainty of chamber flux methodologies in a standardised way for direct comparisons. We provide comparisons of a variety of chamber measurement methodologies (closed static and dynamic chamber methods) to highlight the impact of analytical noise, chamber size, enclosure time and number of gas samples. With the associated tools, researchers, commercial suppliers and other stakeholders in the flux community can easily estimate the limitations of a particular methodology to establish and tailor the suitability of particular chambers and instruments to experimental requirements.
... All sensors and main components are found at the table 1. Also, the PCB design and schematics are found at the repository (Kobayashi, 2025 After considering the chamber design and sensors, we can start integrating both, and the minimal detectable flux, which was proposed by Christiansen et al. (2015), provides what is the expected lower limit for the soil gas flux rates that can be detected. The minimal detectable flux (MDF) considers different characteristics, such as the analytical accuracy of the sensor, the chamber's volume and surface area, and the total chamber closure time. ...
Monitoring soil gas fluxes is essential for understanding greenhouse gas dynamics within the critical zone. One commonly used method involves chamber-based methods which enables the quantification of soil gas fluxes on a specific point at the soil-atmosphere interface. However, point measurements often limit the representativeness of the field-scale processes due to the large spatio-temporal variability of climatic, hydrological, pedological, or ecological factors controlling its dynamics. Additionally, commercial chambers often prohibits deployment over sufficient representative area due to expensive operational and purchase costs. Although low-cost and open-source designs have recently emerged in the literature, solutions enabling adaptability to field-site characteristics and design validation are still lacking. To address these challenges, we propose here a low-cost, parametric soil gas flux system that can be adapted to logistical and field constraints while allowing high-frequency measurement resolution. Alongside the open-design hardware, we also developed software to facilitate automatic data acquisition and processing. We conducted laboratory investigations to evaluate both the sensor and chamber-design integration. Thus, we can address the data assurance from low-cost systems even with different parametric configurations. Finally, our approach demonstrate low-cost solutions enable the democratization of these systems by having a framework that can be adaptable for different study sites.
... Only one participant remarked that the magnitude in CH 4 variations needs to be compared to the instrument precision to decide whether a measurement can be classified as a "zero flux". This approach gets closest to computing the minimum detectable flux (MDF) introduced by Christiansen et al. (2015) and refined by Nickerson (2016) to assess the quality of low flux estimates. Contrary to the 910 approaches of most survey participants, Maier et al. (2022) recommend to not discard or set to zero fluxes estimates below the MDF. ...
Methane is an important greenhouse gas but the magnitude of global emissions in particular from natural sources remain highly uncertain. To estimate methane emissions on large spatial scales, methane flux data sets from field measurements collected and processed by many different researchers must be combined. We hypothesize that considerable uncertainty might be introduced into such data synthesis products by the many different approaches used to collect, process and quality control chamber measurements of methane fluxes within the flux community. Existing guidelines on chamber measurements promote more standardized measurement and processing techniques but to our knowledge, so far, no study has investigated which methods are actually used within the flux community. Therefore, we aimed to identify major differences between the approaches for chamber methane fluxes used by different researchers. We conducted an expert survey to collect information on chamber-based methane flux measurements, including field sites, research questions, measurement setups and routines as well as data processing and quality control of data. We received 36 responses from researchers in North America, Europe, and Asia which indicated that 80 % of respondents have adopted high-frequency, multi-gas analyzers with most measurement times falling between 2 and 5 minutes. Most but not all of the respondents use recommended chamber designs, including such as airtight sealing, fans, and a pressure vent. We asked about the participants’ approach to quality control and presented a standardized set of methane concentrations from observed flux measurements, then included this information for flux calculations. The responses showed broad disagreement among the experts on processes resulting in nonlinear methane concentration increases. Based on the expert responses, we estimated an uncertainty of 28 % introduced by different researchers deciding differently on discarding vs. accepting a measurement when processing a representative data set of chamber measurement. Different researchers choosing different time periods within the same measurement for flux calculation caused an additional uncertainty of 17 %. Our study highlights the need to understand drivers of the patterns visible from high-resolution analyzers and standardized procedures and guidelines for future chamber methane flux measurements. This is highly important to reliably quantify methane fluxes all over the world.
... MS has relatively high sensitivity and makes it possible to detect multiple gases, which is mainly a problem for gas chromatography [154]. It has almost no problems of interference sensing of gases, which is a feature of some optical methods, e.g., cavity ringdown spectroscopy [155]. ...
In this review article, the main techniques for spectroscopic studies of gases in field conditions are considered. The issues related to the study of gas emissions from soils and the determination of their concentrations are analysed. The main types of spectroscopy used in portable devices for soil gas analysis, along with their design features and sampling approaches, are provided. Various studies aimed at optimising the operation of devices for analysing gases emitted from the soil, taking into account agronomic, agrochemical, and ecological specifics, are also presented. The effect of using different types of lasers and reflecting elements on the accuracy of optical measurements and the sensitivity to various substances in the gases is analysed.
... The mean ± SD R 2 for stem and forest floor fluxes was 0.96 ± 0.15 and 0.98 ± 0.03 for CO 2 , 0.31 ± 0.30 and 0.86 ± 0.18 for CH 4 , and 0.37 ± 0.33 and 0.42 ± 0.32 for N 2 O respectively. We evaluated the quality of flux estimates using the minimum detectable flux (MDF) (Christiansen et al., 2015;Nickerson, 2016 ...
Tree stems exchange greenhouse gases with the atmosphere but the magnitude, variability and drivers of these fluxes remain poorly understood. Here, we report stem fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in a boreal riparian forest, and investigate their spatiotemporal variability and ecosystem level importance. For two years, we measured CO2 and CH4 fluxes on a monthly basis in 14 spruces (Picea abies) and 14 birches (Betula pendula) growing near a headwater stream affected by historic ditching. We also measured N2O fluxes on three occasions. All tree stems were net emitters of CO2 and CH4, while N2O fluxes were around zero. CO2 fluxes correlated strongly with air temperature and peaked in summer. CH4 fluxes correlated modestly with air temperature and solar radiation and peaked in late winter and summer. Trees with larger stem diameter emitted more CO2 and less CH4 and trees closer to the stream emitted more CO2 and CH4. The CO2 and CH4 fluxes did not differ between spruce and birch, but correlations of CO2 fluxes with stem diameter and distance to stream differed between the tree species. The absence of vertical trends in CO2 and CH4 fluxes along the stems and their low correlation with groundwater levels and soil CO2 and CH4 partial pressures suggest tree internal production as the primary source of stem emissions. At the ecosystem level, the stem CO2, CH4 and N2O emissions represented 52 ± 16 % of the forest floor CO2 emissions and 3 ± 1 % and 11 ± 40 % of the forest floor CH4 and N2O uptake, respectively, during the snow-free period (median ± SE). The six month snow-cover period contributed 11 ± 45 % and 40 ± 29 % to annual stem CO2 and CH4 emissions, respectively. Overall, the stem gas fluxes were more typical for upland rather than wetland ecosystems likely due to historic ditching and subsequent groundwater level decrease.
... To convert the CH 4 and N 2 O emissions into CO 2 equivalents, multiplication factors were used of 27 and 273 respectively (global warming potential over a 100-year time frame [27]). Fluxes of CO 2 , CH 4 and N 2 O below the minimum detectable flux (13.3, 2.4 and 151.9 mg CO 2 -eq m -2 day -1 for CO 2 , CH 4 and N 2 O, respectively) were denoted as 0 [28,29]. Measurements that were not useable due to sharp spikes in GHGs as a result of ebullition were counted as ebullition events. ...
Wastewater treatment plants (WWTPs) are a point source of nutrients, emit greenhouse gases (GHGs), and produce large volumes of excess sludge. The use of aquatic organisms may be an alternative to the technical post-treatment of WWTP effluent, as they play an important role in nutrient dynamics and carbon balance in natural ecosystems. The aim of this study was therefore to assess the performance of an experimental wastewater-treatment cascade of bioturbating macroinvertebrates and floating plants in terms of sludge degradation, nutrient removal and lowering GHG emission. To this end, a full-factorial experiment was designed, using a recirculating cascade with a WWTP sludge compartment with or without bioturbating Chironomus riparius larvae, and an effluent container with or without the floating plant Azolla filiculoides, resulting in four treatments. To calculate the nitrogen (N), phosphorus (P) and carbon (C) mass balance of this system, the N, P and C concentrations in the effluent, biomass production, and sludge degradation, as well as the N, P and C content of all compartments in the cascade were measured during the 26-day experiment. The presence of Chironomus led to an increased sludge degradation of 44% compared to 25% in the control, a 1.4 times decreased transport of P from the sludge and a 2.4 times increased transport of N out of the sludge, either into Chironomus biomass or into the water column. Furthermore, Chironomus activity decreased methane emissions by 92%. The presence of Azolla resulted in a 15% lower P concentration in the effluent than in the control treatment, and a CO2 uptake of 1.13 kg ha⁻¹ day⁻¹. These additive effects of Chironomus and Azolla resulted in an almost two times higher sludge degradation, and an almost two times lower P concentration in the effluent. This is the first study that shows that a bio-based cascade can strongly reduce GHG and P emissions simultaneously during the combined polishing of wastewater sludge and effluent, benefitting from the additive effects of the presence of both macrophytes and invertebrates. In addition to the microbial based treatment steps already employed on WWTPs, the integration of higher organisms in the treatment process expands the WWTP based ecosystem and allows for the inclusion of macroinvertebrate and macrophyte mediated processes. Applying macroinvertebrate-plant cascades may therefore be a promising tool to tackle the present and future challenges of WWTPs.
... Our results are consistent with observations in European forests that indicate substantially higher CH 4 oxidation rates in stands with a high broadleaf component compared to conifer monocultures (Borken et al., 2003;Borken and Beese, 2006;Degelmann et al., 2009). Additionally, measurements presented here are some of the first to utilize rapid off-axis integrated cavity output spectroscopy with pressure-equilibrated cuvette systems in boreal forests that address biases arising from static chamber sampling methods (Christiansen et al., 2015). ...
... The limit of flux detection for this system was approximately 10 −4 and 10 −2 μmol m −2 s −1 for nitrous oxide and carbon dioxide, respectively. 33 Flux from each location was normalized to the surface area of the flux chamber for surface measurements or the cross-sectional area of the well casing for well measurements (Table S1). ...
... We utilized the dynamic chamber method (Pavelka et al., 2018) to determine CO 2 and N 2 O emissions. Gas concentration measurements were carried out by a Picarro G2508 (Picarro, US) multigas analyzer attached to the soil columns creating incubation chambers (Christiansen et al., 2015). The gas incubation time was set at 10 min and emissions were estimated based on the initial and incubated concentrations by a linear equation (Dencső et al., 2021). ...
... For this reason, they have been widely used in the field of environmental research. 15,16 Laser instruments require a continuous throughput of an autogas sampler module to realise in situ continuous δ 13 C and CO 2 concentration monitoring or estimate soil microbial respiration (SR). ...
Rationale: Soil microbial heterotrophic C‐CO 2 respiration is important for C cycling. Soil CO 2 differentiation and quantification are vital for understanding soil C cycling and CO 2 emission mitigation. Presently, soil microbial respiration (SR) quantification models are based on native soil organic matter (SOM) and require consistent monitoring of δ ¹³ C and CO 2 .
Methods: We present a new apparatus for achieving in situ soil static chamber incubation and simultaneous CO 2 and δ ¹³ C monitoring by cavity ring‐down spectroscopy (CRDS) coupled with a soil culture and gas introduction module (SCGIM) with multi‐channel. After a meticulous five‐point inter‐calibration, the repeatability of CO 2 and δ ¹³ C values by using CRDS‐SCGIM were determined, and compared with those obtained using gas chromatography (GC) and isotope ratio mass spectrometry (IRMS), respectively. We examined the method regarding quantifying SR with various concentrations and enrichment of glucose and then applied it to investigate the responses of SR to the addition of different exogenous organic materials (glucose and rice residues) into paddy soils during a 21‐day incubation.
Results: The CRDS‐SCGIM CO 2 and δ ¹³ C measurements were conducted with high precision (< 1.0 µmol/mol and 1‰, respectively). The optimal sampling interval and the amount added were not exceeded 4 h and 200 mg C/100 g dry soil in a 1 L incubation bottle, respectively; the ¹³ C‐enrichment of 3%–7% was appropriate. The total SR rates observed were 0.6–4.2 µL/h/g and the exogenous organic materials induced ‐49%–28% of priming effects in native SOM mineralisation.
Conclusions: Our results show that CRDS‐SCGIM is a method suitable for the quantification of soil microbial CO 2 respiration, requiring less extensive lab resources than GC/IRMS.
... We measured the N 2 O and NH 3 emissions of each soil column with a PICARRO G2508 (PICARRO, Santa Clara, CA, USA) multigas analyzer [48] based on the dynamic chamber method [49]. The gas incubation time was set at 13 min and emissions were estimated using linear equations. ...
Greenhouse gas (GHG) emissions from agricultural soils can accelerate climate change, therefore, different soil fertilization techniques should be assessed before application to reduce GHG emissions. Pig slurry applications can greatly influence soil carbon dioxide (CO2), nitrous oxide (N2O), and ammonia (NH3) emissions of arable fields; thus, it is important to find site-specific techniques to lessen any negative environmental impacts. In this study, we examined the short-term effect of pig slurry application techniques of spreading and injection on soil greenhouse gas and NH3 emissions under different irrigation amounts. We used the dynamic chamber method with in-situ gas analyzers. Our study showed that there were elevated emissions during the first week after slurry application; however, the difference between GHG emissions of spreading and injection treatments were not significant. Elevated GHG emissions (213–338% and 250–594% in the case of CO2 and N2O emissions, respectively) were observed under dry circumstances compared to irrigated treatments, as well as significantly higher NH3 emissions occurred for surface spreading under non-irrigated (dry) circumstances compared to other treatments. There were no statistically significant differences between the soil chemistry of different application techniques. However, pig slurry increased the available nitrogen forms (ammonium- and nitrate-nitrogen), which caused N2O and NH3 peaks regardless of treatment type. Leachate chemistry was more affected by irrigation strategies than application techniques. Our study highlights the importance of soil conditions at the time of application, rather than the application technique for fertilization using pig slurry.
... It is important to know the sensitivity of the experimental set-up and to know MDF. Fluxes below the MDF value are not necessarily zero, but they cannot be detected with the required statistical confidence (Christiansen et al., 2015;Nickerson, 2016 deployment period of the chamber, t c , and the sampling periodicity p s , but also on the dimensions of the applied chamber system such as the chamber height (V ch /A) (Equation 4): ...
Soils represent a major global source and sink of greenhouse gases (GHGs). Many studies of GHG fluxes between soil, plant and atmosphere rely on chamber measurements. Different chamber techniques have been developed over the last decades, each characterised by different requirements and limitations. In this manuscript, we focus on the non‐steady‐state technique which is widely used for manual measurements but also in automatic systems. Although the measurement method appears very simple, experience gained over the years shows that there are many details which have to be taken into account to obtain reliable measurement results.
This manuscript aims to share lessons learnt and pass on experiences in order to assist the reader with possible questions or unexpected challenges, ranging from the planning of the design of studies and chambers to the practical handling of the chambers and the quality assurance of the gas and data analysis. This concise introduction refers to a more extensive Best Practice Guideline initiated by the Working Group Soil Gases ( AG Bodengase ) of the German Soil Science Society ( Deutsche Bodenkundliche Gesellschaft ). The intention was to collect and aggregate the expertise of different working groups in the research field. As a compendium, this Best Practice Guideline is intended to help both beginners and experts to meet the practical and theoretical challenges of measuring soil gas fluxes with non‐steady‐state chamber systems and to improve the quality of the individual flux measurements and thus entire GHG studies by reducing sources of uncertainty and error.
... Fluxes below the MDF value are not necessarily zero, but they cannot be detected with the required statistical confidence, and this information should be considered during data analysis. Christiansen et al. (2015) developed a concept of MDF, which was modified by Nickerson (2016) to include online measurements. MDF depends mainly on the analytical precision of the instrument, PInstrument, the deployment duration of the chamber, Dclosed, and the sampling periodicity psampling, but also on the dimensions of the applied chamber system and further physical parameters, such as the molecular mass of the respective gas, M, the mean chamber headspace air pressure, Pair, and temperature during deployment, Tair, as well as the chamber headspace volume Vh and basal area A (Eq.9.1). ...
... The authors in [21] addressed the difficulties and challenges associated with installing gas chambers in rice fields and they also investigated the lifetime of these gas chambers. The authors of [22] have developed a CH 4 measurement system in which the collection of gas samples was done on a weekly basis. Due to the large time interval between each gas sample, this system could not monitor GHGs dynamics thoroughly. ...
Greenhouse gas (GHG) emissions from rice fields have huge effects on climate change. Low-cost systems and management practices to quantify and reduce GHGs emission rates are needed to achieve a better climate. The typical GHGs estimation processes are expensive and mainly depend on high-cost laboratory equipment. This study introduces a low-cost sensor-based GHG sampling and estimation system for rice fields. For this, a fully automatic gas chamber with a sensor-integrated gas accumulator and quantifier unit was designed and implemented to study its performance in the estimation efficiency of greenhouse gases (CH4, N2O, and CO2) from rice fields for two crop seasons. For each crop season, three paddy plots were prepared at the experimental site and then subjected to different irrigation methods (continuous flooding (CF), intermittent flooding (IF), and controlled intermittent flooding (CIF)) and fertilizer treatments to study the production and emission rates of GHGs throughout the crop growing season at regular intervals. A weather station was installed on the site to record the seasonal temperature and rainfall events. The seasonal total CH4 emission was affected by the effects of irrigation treatments. The mean CH4 emission in the CIF field was smaller than in other treatments. CH4 and N2O emission peaks were high during the vegetative and reproductive phases of rice growth, respectively. The results indicated that CIF treatment is most suitable in terms of rice productivity and higher water use efficiency. The application of nitrogen fertilizers produced some peaks in N2O emissions. On the whole, the proposed low-cost GHGs estimation system performed well during both crop seasons and it was found that the adaption of CIF treatment in rice fields could significantly reduce GHG emissions and increase rice productivity. The research results also suggested some mitigation strategies that could reduce the production of GHGs from rice fields.
... Supplementary Materials: The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/nitrogen3010010/s1, Figure S1: Detail of DCS and DWM technique; Figure S2: Summary of diel variation of N 2 O fluxes; Figure S3: Visual of decay curve fitting for annual N 2 O estimate; Figure S4: Clay size fraction by depth and field; Figure S5: Summary of individual regression results for input variables into multiple linear regression; Figure S6: Plot of N balance versus N 2 O emissions; Table S1: N 2 O seasonally-based annual estimate details; Table S2: CH 4 seasonally-based annual estimate details; Table S3: USDA soil textural class description; Table S4: Soil characterization results; Table S5: Summary of minimal detectable flux calculations; Table S6: Summary results of multiple linear regression model. References [63][64][65][66] ...
Drainage water management (DWM), also known as controlled drainage, is a best management practice (BMP) deployed on drainage ditches with demonstrated success at reducing dissolved nitrogen export from agricultural fields. By slowing discharge from agricultural ditches, subsequent anaerobic soil conditions provide an environment for nitrate to be reduced via denitrification. Despite this success, incomplete denitrification might increase nitrous oxide (N2O) emissions and more reducing conditions might increase methanogenesis, resulting in increased methane (CH4) emissions. These two gases, N2O and CH4, are potent greenhouse gases (GHG) and N2O also depletes stratospheric ozone. This potential pollution swapping of nitrate reduction for GHG production could negatively impact the desirability of this BMP. We conducted three years of static chamber measurements of GHG emissions from the soil surface in farm plots with and without DWM in a corn–soybean rotation on the Delmarva Peninsula. We found that DWM raised the water table at the drainage ditch edge, but had no statistically significant effect on water-filled pore space in the field soil surface. Nor did we find a significant effect of DWM on GHG emissions. These findings are encouraging and suggest that, at least for this farm site, DWM can be used to remove nitrate without a significant tradeoff of increased GHG emissions.
... Nitrous oxide (N2O) samples were taken with a static box and analyzed with gas chromatography (Christiansen et al., 2015). Eleven sampling events were conducted during the whole growth period. ...
To investigate the effects of maize/legume intercropping on soil N2O emissions, six treatments were tested in the North China Plain: maize, M120 (N application rate 120 kg ha-1); maize, M240 (N application rate 240 kg ha-1); soybean (Glycine max), SS (120 kg ha-1); maize/soybean intercropping, MS (120 kg ha-1); peanut (Arachis hypogaea), PP (120 kg ha-1); and maize/peanut intercropping, MP (120 kg ha-1). The amounts of inorganic nitrogen for the 0-20 cm soil in MS were 24.0%, 5.3%, and 29.3% lower than in SS, M120, and M240, respectively (P < 0.05). The total N2O emissions ranged from 0.41 ± 0.09 to 0.98 ± 0.14 kg ha-1. MP and MS were statistically different at the 95% confidence level, whereas MP produced the least N2O emissions at 0.41 kg ha-1. The seasonal cumulative N2O emissions and global warming potential in MS and MP were also significantly lower than those in the other three monoculture treatments (P < 0.001). The results demonstrated that maize/legume intercropping can increase the N uptake of crops and reduce the amount of soil inorganic nitrogen and N2O emissions, thereby, ensuring the sustainability of the agricultural environment.
... Then three models (linear, quadratic, and exponential) were fitted for each sample and gas species to characterize the variation of gas concentrations across time and the 'best model' was selected based on AIC scores. Flux estimations for each of the gases were then calculated using the following equation [61]: ...
Switchgrass is a deep-rooted perennial native to the US prairies and an attractive feedstock for bioenergy production; when cultivated on marginal soils it can provide a potential mechanism to sequester and accumulate soil carbon (C). However, the impacts of switchgrass establishment on soil biotic/abiotic properties are poorly understood. Additionally, few studies have reported the effects of switchgrass cultivation on marginal lands that have low soil nutrient quality (N/P) or in areas that have experienced high rates of soil erosion. Here, we report a comparative analyses of soil greenhouse gases (GHG), soil chemistry, and microbial communities in two contrasting soil types (with or without switchgrass) over 17 months (1428 soil samples). These soils are highly eroded, ‘Dust Bowl’ remnant field sites in southern Oklahoma, USA. Our results revealed that soil C significantly increased at the sandy-loam (SL) site, but not at the clay-loam (CL) site. Significantly higher CO2 flux was observed from the CL switchgrass site, along with reduced microbial diversity (both alpha and beta). Strikingly, methane (CH4) consumption was significantly reduced by an estimated 39 and 47% at the SL and CL switchgrass sites, respectively. Together, our results suggest that soil C stocks and GHG fluxes are distinctly different at highly degraded sites when switchgrass has been cultivated, implying that carbon balance considerations should be accounted for to fully evaluate the sustainability of deep-rooted perennial grass cultivation in marginal lands.
... CRDS uses a single-frequency laser and a photodetector to create a continuous traveling light wave. It is able to detect small amounts of light through its three-mirror cavity and emit an amplified signal correlated to the frequency inside the cavity 5,7 . Compared with the traditional method of Gas Chromatography (GC), CRDS overall has performed better than GHG and has a more consistent linear response with CO2 5 . ...
The state of California is investing in anaerobic digesters to reduce methane emissions from agriculture. However, little is known about the impact of anaerobic digesters on nitrous oxide (N2O) and carbon dioxide (CO2) emissions from soils after land application of digestate. The purpose of this study was to compare soil CO2 and N2O emission fluxes from anaerobic digestate treatment in conjunction with manure, manure treatment, and a control group without treatment on agricultural soils from two dairy farms. In addition to comparing treatments and sites, we tested the effects of temperature at either 23°C or 28°C to compare predicted future average temperatures. Soil samples were placed in mason jars with 18 jars per location: three manure treatments x 2, temperatures x 3 replications per treatment, and incubated for six weeks according to the temperature treatment. Soils were watered once a week to maintain 65% water holding capacity. Cavity ring-down spectrometers were used to collect gas emissions in a closed-loop system, and elemental analyzers were used to evaluate soil and treatment nutrient composition. We hypothesized that three main variables — manure, lower temperatures, and soils with low-nutrient content in conjunction with anaerobic diges- tate would all lead to lower emissions. Anaerobic digestate has been found to reduce greenhouse gas emissions while also being a nutrient-rich energy source. Microbial soil communities are also more active in warmer temperatures, which may increase the production of gas emissions. Overall, the results were inconclusive for either argument.
... Conservative CH 4 and CO 2 effluxes were calculated with linear curve fitting of chamber closure time vs. concentration in SoilFluxPro (LI-COR Biosciences; Forde et al., 2018; Sihota et al., 2013). The minimum detectable efflux (MDF) was calculated with conservative detector analytical accuracies taken to be ΔC = 0.2 ppm for CH 4 and ΔC = 1 ppm for CO 2 , which is consistent with similar measurements at controlled injection gas migration study sites (Table S1; Christiansen et al., 2015;Forde et al., 2019aForde et al., , 2019b. Manufacturer-reported instrumental accuracies are <2 ppb for CH 4 (Los Gatos Research) and <1 ppm for CO 2 (LI-COR Inc). ...
Well integrity failure resulting in migration of natural gas outside of the surface casing can cause atmospheric greenhouse gas emissions and groundwater quality impacts from existing and historic energy wells. Spatial and temporal variability in gas migration can result in errors in detection (i.e., presence/absence) and efflux estimations. This field-based case study used automated dynamic closed chambers to record repeated (∼every 18 min) CO2 and CH4 efflux measurements over a two-week period around a single petroleum production well in Alberta, Canada. Long-term efflux measurements supplemented soil gas compositional and isotopic characterization, along with surface concentration measurements. Effluxes were spatially concentrated around the wellhead and only occasionally detectable more than a few meters away. Estimated total emissions attributable to gas migration ranged from 48 to 466 g CH4 d⁻¹ (or 0.07–0.7 m³ CH4 d⁻¹). Methane effluxes and concentrations were temporally variable on second-to-hourly and diel scales. Multivariate stepwise regression analysis indicates that multiple meteorological factors, particularly wind speed and air temperature, were related to the temporal variability. Despite temporal variability, elevated concentrations and effluxes were consistently detectable around the well. Major soil gas composition suggests that gas migration near the wellhead causes advective displacement of soil gas, while more distal measurements are indicative of episodic and diffusion-dominated transport. Values of ¹³C–CO2 and ¹³C–CH4 samples were consistent with CH4 oxidation within the unsaturated zone. Although these results reflect a single well, the findings are salient to gas migration detection and emission estimation efforts.
Publication available from: https://doi.org/10.1016/j.apr.2021.101094
Approved manuscript available from: https://doi.org/10.1002/essoar.10507208.1
... This step was carried out using the SPSS software, and the results were visualized with the Origin software. The temperature sensitivity of R s (Q 10 ) was calculated using Eqs. 2 and 3 (Christiansen et al. 2015). ...
Temperature sensitivity of respiration of forest soils is important for its responses to climate warming and for the accurate assessment of soil carbon budget. The sensitivity of temperature ( T i ) to soil respiration rate ( R s ), and Q 10 defined by e 10(ln Rs −ln a )/ Ti has been used extensively for indicating the sensitivity of soil respiration. The soil respiration under a larch ( Larix gmelinii ) forest in the northern Daxing’an Mountains, Northeast China was observed in situ from April to September, 2019 using the dynamic chamber method. Air temperatures ( T air ), soil surface temperatures ( T 0cm ), soil temperatures at depths of 5 and 10 cm ( T 5cm and T 10cm , respectively), and soil-surface water vapor concentrations were monitored at the same time. The results show a significant monthly variability in soil respiration rate in the growing season (April–September). The Q 10 at the surface and at depths of 5 and 10 cm was estimated at 5.6, 6.3, and 7.2, respectively. The Q 10@10 cm over the period of surface soil thawing ( Q 10@10 cm, thaw = 36.89) were significantly higher than that of the growing season ( Q 10@10 cm, growth = 3.82). Furthermore, the R s in the early stage of near-surface soil thawing and in the middle of the growing season is more sensitive to changes in soil temperatures. Soil temperature is thus the dominant factor for season variations in soil respiration, but rainfall is the main controller for short-term fluctuations in respiration. Thus, the higher sensitivity of soil respiration to temperature ( Q 10 ) is found in the middle part of the growing season. The monthly and seasonal Q 10 values better reflect the responsiveness of soil respiration to changes in hydrometeorology and ground freeze-thaw processes. This study may help assess the stability of the soil carbon pool and strength of carbon fluxes in the larch forested permafrost regions in the northern Daxing’an Mountains.
... Recommendations for a more comprehensive assessment of the effect of microplastics on greenhouse gas fluxes Our monitoring approach entailed high-frequency measurements; this is necessary to obtain precise results for trace gas emissions [28,[68][69][70][71][72]. Future endeavors aimed at quantifying trace gas flux responses to microplastic addition should also rely on such measurements. ...
Microplastics may affect soil ecosystem functioning in critical ways, with previously documented effects including changes in soil structure and water dynamics; this suggests that microbial populations and the processes they mediate could also be affected. Given the importance for global carbon and nitrogen cycle and greenhouse warming potential, we here experimentally examined potential effects of plastic microfiber additions on CO 2 and N 2 O greenhouse gas fluxes. We carried out a fully factorial laboratory experiment with the factors presence of microplastic fibers (0.4% w/w) and addition of urea fertilizer (100 mg N kg − 1 ) using one target soil. The conditions in an intensively N-fertilized arable soil were simulated by adding biogas digestate at the beginning of the incubation to all samples. We continuously monitored CO 2 and N 2 O emissions from soil before and after urea application using a custom-built flow-through steady-state system, and we assessed soil properties, including soil structure. Microplastics affected soil properties, notably increasing soil aggregate water-stability and pneumatic conductivity, and caused changes in the dynamics and overall level of emission of both gases, but in opposite directions: overall fluxes of CO 2 were increased by microplastic presence, whereas N 2 O emission were decreased, a pattern that was intensified following urea addition. This divergent response is explained by effects of microplastic on soil structure, with the increased air permeability likely improving O 2 supply: this will have stimulated CO 2 production, since mineralization benefits from better aeration. Increased O 2 would at the same time have inhibited denitrification, a process contributing to N 2 O emissions, thus likely explaining the decrease in the latter. Our results clearly suggest that microplastic consequences for greenhouse gas emissions should become an integral part of future impact assessments, and that to understand such responses, soil structure should be assessed.
... For each GHG, the minimum detectable flux (MDF) for highfrequency measurements was estimated as follows (Christiansen et al., 2015;Nickerson, 2016): ...
Tree stems and soils can act as sources and sinks for the greenhouse gases (GHG) carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Since both uptake and emission capacities can be large, especially in tropical rainforests, accurate assessments of the magnitudes and temporal variations of stem and soil GHG fluxes are required.
We designed a new flexible stem chamber system for continuously measuring GHG fluxes in a French Guianese rainforest. Here, we describe this new system, which is connected to an automated soil GHG flux system, and discuss measurement uncertainty and potential error sources.
In line with findings for soil GHG flux estimates, we demonstrated that lengthening the stem chamber closure time was required for accurate estimates of tree stem CH4 and N2O flux but not tree stem CO2 flux. The instrumented stem was a net source of CO2 and CH4 and a weak sink of N2O.
Our experimental setup operated successfully in situ and provided continuous tree and soil GHG measurements at a high temporal resolution over an 11‐month period. This automated system is a major step forward in the measurement of GHG fluxes in stems and the atmosphere concurrently with soil GHG fluxes in tropical forest ecosystems.
... where δCn gas /δt is the change of N 2 O or CH 4 concentration in the headspace (µmol gas mol headspace air −1 ) in time (h). This change was calculated using an exponential fit of concentration data as dry mole fraction vs. enclosure time and evaluating its slope by the time derivative at t = 0 (Christiansen et al., 2015). ...
The application of dairy farm effluents (DFE) without previous treatment in paddocks was intensified due to the approval of this practice in Costa Rican legislation since 2012. Applying DFE instead of synthetic N fertilizer in grasslands is an opportunity to reach a circular economy; however, this practice increases the risk of emissions of nitrous oxide (N2O), methane (CH4), and ammonia (NH3), which contribute to global warming. A field experiment was carried out using a permanent grassland (90% Star grass and 10% Kikuyo grass) to simultaneously assess the effect of nitrapyrin on yield-scaled emissions of NH3, CH4, and N2O. The experiment lasted for 5 months in 2017, based on a randomized complete block design, including three treatments of control (CK) without N application, surface application of DFE with nitrapyrin (SNI), and without nitrapyrin (S). Total N applied was 149 ± 12 kg N ha−1 for both S and SNI treatments split into five applications. CH4 emissions from S, SNI, and CK showed a high temporal variation. Daily fluxes of CH4 from SNI were significantly lower than those of S in August (P < 0.05). Cumulative emissions of CH4, the majority produced in the soil, ranged from 4 to 168 g ha−1 for S, and from −13 to 88 g ha−1 for SNI. The ratio between the N2O cumulative emissions and the N applied as DFE were 1.6 ± 0.5 and 1.7 ± 0.2% for S and SNI, respectively. NH3 volatilization potential was very low (i.e., 0.6 ± 0.2% of the N applied). Under the prevailing experimental conditions, no significant difference between yield-scaled NH3 and N2O emissions were found between S and SNI, suggesting that nitrapyrin may not be a viable mitigation option for gaseous N losses from DFE application in Costa Rican grasslands in rainy season.
... While our automated, in situ approach relying on gas equilibration devices is now well established Webb et al. 2016), N 2 O observations may also be quantified using gas chromatography. A comparison study between a Cavitary Ring Down Spectrometer and Gas Chromatograph instrument fitted with Electron Capture Detector found minimal differences in N 2 O measurement accuracy and precision against a range of N 2 O standards in both laboratory and in situ environments (Christiansen et al. 2015). ...
Coastal waterways can be significant sources of the potent greenhouse gas nitrous oxide (N 2 O) due to nitrogen inputs and eutrophication. Here, we quantify groundwater derived N 2 O inputs and atmospheric emissions within a modified urban embayment (Sydney Harbour, Australia). Overall, we found low N 2 O saturation (91-171%) and air-water fluxes (−2.2 to 24.6 μmol m −2 d −1). Concentrations were highest in upstream brackish areas and a commercial/industrial subembayment. Dissolved inorganic nitrogen concentrations were low and inversely correlated to N 2 O throughout the harbor. N 2 O surface water dynamics were apparently driven by saline submarine groundwater discharge, as quantified by the radioisotope tracer radon-222. Groundwater discharge was highest within the embayments and mangrove-lined upper estuary. While groundwater was a net N 2 O source to surface waters, two upstream sub-embayments featured groundwater N 2 O concentrations lower than surface water, suggesting a sink driven by surface waters recirculating in intertidal sediments. Surface-water N 2 O was undersaturated within one upstream embayment, likely due to N 2 O consumption within sediments. Contrastingly, the downstream embayments featured higher groundwater N 2 O and accounted for 45% AE 21% of the groundwater N 2 O flux. Sydney Harbour was a net source of N 2 O to the atmosphere (mean 0.6 AE 0.3 μmol m −2 d −1) with larger N 2 O fluxes occurring from relatively small areas. N 2 O emissions (expressed in CO 2 equilivents) were equivalent to 17% of CO 2 emission estimates from previous studies. The low N 2 O emissions in Sydney Harbour contrast with other modified estuaries which often emit higher N 2 O fluxes due to larger nitrogen inputs.
... The latter is of importance because a reduction in enclosure time minimises negative effects resulting from the use of a closed static chamber. Christiansen et al. (2015) investigated the relationship between enclosure time and instrument precision and introduced the concept of minimum detectable flux (MDF) to determine the lower limit of flux rates that can be achieved with a given measurement precision (Eq. 2.7): ...
Several approaches exist for measuring greenhouse gases (GHGs), mainly CO 2 , N 2 O, and CH 4 , from soil surfaces. The principle methods that are used to measure GHG from agricultural sites are chamber-based techniques. Both open and closed chamber techniques are in use; however, the majority of field applications use closed chambers. The advantages and disadvantages of different chamber techniques and the principal steps of operation are described. An important part of determining the quality of the flux measurements is the storage and the transportation of the gas samples from the field to the laboratory where the analyses are carried out. Traditionally, analyses of GHGs are carried out via gas chromatographs (GCs). In recent years, optical analysers are becoming increasingly available; these are user-friendly machines and they provide a cost-effective alternative to GCs. Another technique which is still under development, but provides a potentially superior method, is Raman spectroscopy. Not only the GHGs, but also N 2 , can potentially be analysed if the precision of these techniques is increased in future development. An important part of this chapter deals with the analyses of the gas concentrations, the calculation of fluxes, and the required safety measures. Since non-upland agricultural lands (i.e. flooded paddy soils) are steadily increasing, a section is devoted to the specificities of GHG measurements in these ecosystems. Specialised techniques are also required for GHG measurements in aquatic systems (i.e. rivers), which are often affected by the transfer of nutrients from agricultural fields and therefore are an important indirect source of emission of GHGs. A simple, robust, and more precise methodof ammonia (NH 3 ) emission measurement is also described.
... The change of N 2 O concentration in the headspace was calculated by fitting the obtained concentration data as dry mole fraction in µmol mol −1 vs. enclosure time, using an exponential fit. The slope of this curve was evaluated by time derived at t = 0, that is assumed to represent the pre-deployment flux (Christiansen et al., 2015). The flux of N 2 O (F , µg m −2 h −1 ) was calculated as follows: ...
Urea is the most common nitrogen (N) fertilizer used in the tropics but it has the risk of high gaseous nitrogen (N) losses. Use of nitrification inhibitor has been suggested as a potential mitigation measure for gaseous N losses in N fertilizer-applied fields. In a field trial on a tropical Andosol pastureland in Costa Rica, gaseous emissions of ammonia (NH3) and nitrous oxide (N2O) and grass yield were quantified from plots treated with urea (U; 41.7 kg N ha–1 application–1) and urea plus the nitrification inhibitor nitrapyrin (U + NI; 41.7 kg N ha–1 application–1 and 350 g of nitrapyrin for each 100 kg of N applied) and control plots (without U and NI) over a six-month period (rainy season). Volatilization of NH3 (August to November) in U (7.4% ± 1.3% of N applied) and U + NI (8.1% ± 0.9% of N applied) were not significantly different (P > 0.05). Emissions of N2O in U and U + NI from June to November were significantly different (P < 0.05) only in October, when N2O emission in U + NI was higher than that in U. Yield and crude protein production of grass were significantly higher (P < 0.05) in U and U + NI than in the control plots, but they were not significantly different between U and U + NI. There was no significant difference in yield-scaled N2O emission between U (0.31 ± 0.10 g N kg–1 dry matter) and U + NI (0.47 ± 0.10 g N kg–1 dry matter). The results suggest that nitrapyrin is not a viable mitigation option for gaseous N losses under typical N fertilizer application practices of pasturelands at the study site.
... The change of N 2 O concentration in the headspace was calculated by fitting the obtained concentration data as dry mole fraction in µmol mol −1 vs. enclosure time, using an exponential fit. The slope of this curve was evaluated by time derived at t = 0, that is assumed to represent the pre-deployment flux (Christiansen et al., 2015). The flux of N 2 O (F , µg m −2 h −1 ) was calculated as follows: ...
Urea is the most common nitrogen (N) fertilizer used in the tropics but it has the risk of high gaseous nitrogen (N) losses. Use of nitrification inhibitor has been suggested as a potential mitigation measure for gaseous N losses in N fertilizer-applied fields. In a field trial on a tropical Andosol pastureland in Costa Rica, gaseous emissions of ammonia (NH3) and nitrous oxide (N2O) and grass yield were quantified from plots treated with urea (U; 41.7 kg N ha–1 application–1) and urea plus the nitrification inhibitor nitrapyrin (U + NI; 41.7 kg N ha–1 application–1 and 350 g of nitrapyrin for each 100 kg of N applied) and control plots (without U and NI) over a six-month period (rainy season). Volatilization of NH3 (August to November) in U (7.4% ± 1.3% of N applied) and U + NI (8.1% ± 0.9% of N applied) were not significantly different (P > 0.05). Emissions of N2O in U and U + NI from June to November were significantly different (P < 0.05) only in October, when N2O emission in U + NI was higher than that in U. Yield and crude protein production of grass were significantly higher (P < 0.05) in U and U + NI than in the control plots, but they were not significantly different between U and U + NI. There was no significant difference in yield-scaled N2O emission between U (0.31 ± 0.10 g N kg–1 dry matter) and U + NI (0.47 ± 0.10 g N kg–1 dry matter). The results suggest that nitrapyrin is not a viable mitigation option for gaseous N losses under typical N fertilizer application practices of pasturelands at the study site.
... this is necessary to obtain precise results for trace gas emissions 28,[68][69][70][71][72] . Future endeavors aimed at quantifying trace gas flux responses to microplastic addition should also rely on such measurements. ...
Microplastics may affect soil ecosystem functioning in critical ways, with previously documented effects including changes in soil structure and water dynamics; this suggests that microbial populations and the processes they mediate could also be affected. Given the importance for global carbon and nitrogen cycle and greenhouse warming potential, we here experimentally examined potential effects of plastic microfiber additions on CO2 and N2O greenhouse gas fluxes. We carried out a fully factorial laboratory experiment with the factors presence of microplastic fibers (0.4% w/w) and addition of urea fertilizer (100 mg N kg−1). The conditions in an intensively N-fertilized arable soil were simulated by adding biogas digestate at the beginning of the incubation to all samples. We continuously monitored CO2 and N2O emissions from soil before and after urea application using a custom-built flow-through steady-state system, and we assessed soil properties, including soil structure. Microplastics affected soil properties, notably increasing soil aggregate water-stability and pneumatic conductivity, and caused changes in the dynamics and overall level of emission of both gases, but in opposite directions: overall fluxes of CO2 were increased by microplastic presence, whereas N2O emission were decreased, a pattern that was intensified following urea addition. This divergent response is explained by effects of microplastic on soil structure, with the increased air permeability likely improving O2 supply: this will have stimulated CO2 production, since mineralization benefits from better aeration. Increased O2 would at the same time have inhibited denitrification, a process contributing to N2O emissions, thus likely explaining the decrease in the latter. Our results clearly suggest that microplastic consequences for greenhouse gas emissions should become an integral part of future impact assessments, and that to understand such responses, soil structure should be assessed.
... Using the Pearson correlation coefficient and the coefficient of determination for comparing two or more quantitative methods is a generally preferred approach in the field of N 2 O research. Comparisons of different methods for N 2 O analysis made in the literature most commonly use orthogonal (Jones et al., 2011) and linear regression (Cowan et al., 2014;Brümmer et al., 2017;Tallec et al., 2019), Student's t tests (Christiansen et al., 2015), or are based on raw data (Savage et al., 2014). However, correlation studies as such have limitations when assessing the comparability between two methods since a correlation analysis only identifies the relationship between two variables, not the difference (Gi- Figure 6. ...
The development of fast-response analysers for the measurement of nitrous oxide (N2O) has resulted in exciting opportunities for new experimental techniques beyond commonly used static chambers and gas chromatography (GC) analysis. For example, quantum cascade laser (QCL) absorption spectrometers are now being used with eddy covariance (EC) or automated chambers. However, using a field-based QCL EC system to also quantify N2O concentrations in gas samples taken from static chambers has not yet been explored. Gas samples from static chambers are often analysed by GC, a method that requires labour and time-consuming procedures off-site. Here, we developed a novel field-based injection technique that allowed the use of a single QCL for (1) micrometeorological EC and (2) immediate manual injection of headspace samples taken from static chambers. To test this approach across a range of low to high N2O concentrations and fluxes, we applied ammonium nitrate (AN) at 0, 300, 600 and 900 kg N ha-1 (AN0, AN300, AN600, AN900) to plots on a pasture soil. After analysis, calculated N2O fluxes from QCL (FN2O_QCL) were compared with fluxes determined by a standard method, i.e. laboratory-based GC (FN2O_GC). Subsequently, the comparability of QCL and GC data was tested using orthogonal regression, Bland–Altman and bioequivalence statistics. For AN-treated plots, mean cumulative N2O emissions across the 7 d campaign were 0.97 (AN300), 1.26 (AN600) and 2.00 kg N2O-N ha-1 (AN900) for FN2O_QCL and 0.99 (AN300), 1.31 (AN600) and 2.03 kg N2O-N ha-1 (AN900) for FN2O_GC. These FN2O_QCL and FN2O_GC were highly correlated (r=0.996, n=81) based on orthogonal regression, in agreement following the Bland–Altman approach (i.e. within ±1.96 standard deviation of the mean difference) and shown to be for all intents and purposes the same (i.e. equivalent). The FN2O_QCL and FN2O_GC derived under near-zero flux conditions (AN0) were weakly correlated (r=0.306, n=27) and not found to agree or to be equivalent. This was likely caused by the calculation of small, but apparent positive and negative, FN2O when in fact the actual flux was below the detection limit of static chambers. Our study demonstrated (1) that the capability of using one QCL to measure N2O at different scales, including manual injections, offers great potential to advance field measurements of N2O (and other greenhouse gases) in the future and (2) that suitable statistics have to be adopted when formally assessing the agreement and difference (not only the correlation) between two methods of measurement.
... With these settings (sampling rate, deployment time and analytical precision) and the chamber dimensions described below, the Minimum Detectable Flux (MDF) of the system is 9.2 x 10 -5 g of N-N 2 O ha -1 day -1 for deployment times of 20 minutes and 3.7 x 10 -4 g of N-N 2 O ha -1 day -1 for deployment times of 10 minutes. MDFs were computed following the method ofChristiansen, Outhwaite, & Smukler (2015).Four soil chambers were distributed over an area of approximately 40 m 2 . During the 2015 sampling seasons two chambers were placed between plant rows directly on top of the fertilization band and the other two directly on the row. ...
Manually sampling N2O soil fluxes is labor‐intensive and sampling frequencies are often insufficient to capture daily variation in N2O soil flux, compromising the accuracy of emission estimates. Knowledge of the diurnal fluctuations in N2O flux has been used to choose a sampling time that maximizes the accuracy of N2O flux estimates, thereby reducing the sampling frequency required, but results from previous studies are inconsistent. We analyzed N2O soil emissions measured quasi‐continuously over 3 yr in a highly fertilized (>200 kg N ha⁻¹) corn (Zea mays L.) system grown in southern Wisconsin. This is the first study of temporal variability in N2O flux that includes multiple difficult to measure peak emission events (“hot moments”) and estimates the relative contribution of hot moments to cumulative emissions. The relationship between the observed hourly average flux and the mean daily flux was assessed via linear regression of all measured data (≈22,000 fluxes) and data subsets grouped by magnitude. Diurnal variation in flux was closely associated with normalized flux size. During low‐emission periods, fluxes exhibited a diurnal pattern, where N2O flux measured at particular times of day, named “Preferred Measuring Times” (PMTs), were not significantly different from the mean daily flux. During high‐emission periods, N2O flux did not exhibit a diurnal pattern and there was no PMT. High‐emission periods included difficult to measure hot moments that did not exhibit a PMT and contributed up to 50% of the cumulative emissions; therefore, flux measurements with high temporal resolution were required to estimate cumulative emissions.
Nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2) are three major greenhouse gases (GHG), contributing more than 90% of global warming effects. Across land ecosystems, the source and sink patterns of these GHGs exhibit significant spatial and temporal variability. Field measurements of soil-atmosphere exchange fluxes provide valuable evidence for understanding local GHG dynamics and serve as a complement to comprehensive GHG assessments. While a lot of laboratory-based instruments can facilitate the determination of all three GHGs, few commercially available devices balance precision and portability for in situ flux measurements in remote regions. Here, we present a newly developed GHG analyzer (HT8850) based on a dual-laser spectroscopic system, which determines N2O, CH4, CO2 and H2O concurrently. With a size of 47 cm * 36 cm * 18 cm, a weight of 14.8 kg, and a power consumption below 100 W, this instrument maintains a good balance between portability/budget and precision/stability. With standard gas measurements in the laboratory, we found that the HT8850 has reasonable accuracy and fast response with an inflow rate of 0.5 L min-1. Based on the Allan deviation analysis, the 1σ-detection limits under static operation are 1.11 ppb, 2.38 ppb, 0.39 ppm and 6.95 ppm for N2O, CH4, CO2 and H2O measurements with a 10-second averaging time, respectively. In field application with the soil flux chamber, the analyzer demonstrated good potential in quantifying fluxes for the soil-atmosphere exchange of all three GHGs. Therefore, this compact and integrated spectroscopic analyzer offers a versatile solution for scientists interested in field flux measurements, likely contributing to the further development of in situ applications for GHG flux measurements.
Grassland ecosystems store significant amounts of organic carbon (C) and have the potential to function as a source or sink of greenhouse gases (GHGs) under different environmental conditions and management practices. However, the effects of management (clipping frequency and N fertilisation) on the GHGs remain uncertain. In this study, a field-based experiment with automated-lid gas exchange chambers was conducted to simultaneously measure different GHG fluxes (CO2, N2O, CH4), their overall global warming potential (GWP-100) impact, and net ecosystem exchange (NEE) from a grassland. The experiment had two clipping frequencies (simulating moderate and high grazing intensity) and two nitrogen (N) fertiliser treatments (0 and 40 kg N ha−1 year−1). The measurements were conducted during two periods (each approximately 2 weeks long) of varied temperature and moisture in early autumn. High clipping frequency caused higher daily NEE emissions, higher GWP-100 impact and lower photosynthesis; however, it did not significantly affect these parameters. Nitrogen fertilisation effects were lower than the clipping frequency treatment, but the impact on N2O fluxes was likely to be dependent on the time of N application. Methane (CH4) was predominantly controlled by soil moisture, whereas nitrous oxide (N2O) was more strongly affected by temperature. N2O emissions increased significantly after the break-point temperature of 20°C. Our results have highlighted the sensitivity of CH4 uptake and N2O emissions to environmental conditions, particularly their increase under warmer temperatures. The main contributor of GWP-100 impact in this study was CO2 emissions and uptake. For the observation period, the grassland was a small C sink. For a comprehensive understanding, longer-term studies spanning over several years are needed to accurately assess the impact of different management practices on GHG emissions.
Tidewater glaciers are highly vulnerable to climate change due to warming from both atmospheric and seawater sources. Most tidewater glaciers are rapidly retreating, but little is known about how glacial melting modifies coastal biogeochemical cycles. Here, we investigate carbonate and nutrient dynamics and fluxes in an expanding proglacial tidal lagoon connected to Europe's largest glacier in Iceland (Vatnajökull). The lagoon N:P:Si ratios (2:1:30) imply a system deficient in nitrogen. The large variations in the freshwater endmembers highlighted the complexity of resolving sources and transformations. The lagoon acted as a sink of dissolved inorganic carbon (DIC). Floating chamber incubations revealed a CO2 uptake of 26 ± 15 mmol m⁻² d⁻¹. Lagoon waters near the glacier had a 170% higher CO2 uptake than near the lagoon mouth, likely driven by primary production stimulated by nitrogen‐rich bottom water upwelling. The lateral DIC and total alkalinity (TA) flux rates (outwelling) from the lagoon to the ocean were −1.5 ± 0.1 (export to ocean) and 23 ± 5 mmol m⁻² d⁻¹ (import into the lagoon) respectively. All samples were undersaturated with respect to aragonite due to glacial meltwater dilution of TA and CO2 uptake. This implies dilution of oceanic alkalinity, lowering the nearshore buffering capacity against ocean acidification.
Anaerobic digester liquor (ADL) is a widely used alternative to mineral fertilizers, especially in the context of drip irrigation. However, differences in the manner in which drip irrigation systems are configured could alter the dynamics of the greenhouse gas emissions inherent in the use of ADL by the agricultural sector. Column experiments and structural equation modeling were used to explore the factors and pathways of drip irrigation methods (surface and subsurface drip irrigation) and substitution ratios of ADL (full, partial, and no substitution) on greenhouse gas emissions. The results showed that compared with surface drip irrigation, subsurface drip irrigation reduced daily and cumulative CO2 and N2O emissions but led to an increase in CH4 emissions. Similarly, substituting ADL for chemical fertilizers can also reduce greenhouse gas emissions, and when combined with subsurface drip irrigation, it can reduce the global warming potential (GWP) by up to approximately 50%. Over time, the contribution rates of the three greenhouse gases to the GWP remained essentially unchanged, mainly dominated by CO2 and N2O emissions. Drip irrigation methods and substitution ratios can drive differences in soil physiochemical properties. These differences directly or indirectly affect gas emission quantities and pathways. Soil water, carbon, and pores are important factors and mediators of gas-emission pathways. Overall, adopting the strategy of fully substituting subsurface drip irrigation of ADL for chemical fertilizer can significantly reduce greenhouse gas emissions and enhance the carbon sequestration effect.
Trees are known to be atmospheric methane (CH4) emitters. Little is known about seasonal dynamics of tree CH4 fluxes and relationships to environmental conditions. That prevents the correct estimation of net annual tree and forest CH4 exchange.
We aimed to explore the contribution of stem emissions to forest CH4 exchange. We determined seasonal CH4 fluxes of mature European beech (Fagus sylvatica) stems and adjacent soil in a typical temperate beech forest of the White Carpathians with high spatial heterogeneity in soil moisture.
The beech stems were net annual CH4 sources, whereas the soil was a net CH4 sink. High CH4 emitters showed clear seasonality in their stem CH4 emissions that followed stem CO2 efflux. Elevated CH4 fluxes were detected during the vegetation season. Observed high spatial variability in stem CH4 emissions was neither explicably by soil CH4 exchange nor by CH4 concentrations, water content, or temperature studied in soil profiles near each measured tree. The stem CH4 emissions offset the soil CH4 uptake by up to 46.5% and on average by 13% on stand level.
In Central Europe, widely grown beech contributes markedly to seasonal dynamics of ecosystem CH4 exchange. Its contribution should be included into forest greenhouse gas flux inventories.
A high-sensitive optical detection method was designed and developed at 7.8 μm mid-IR region by coupling a room-temperature operated continuous wave (cw) external-cavity quantum cascade laser (EC-QCL) with an astigmatic multipass cell. The detection strategy operates in the principle of wavelength modulation spectroscopy with second harmonic detection strategy (2f-WMS). We have shown that the methodology has the ability for simultaneous and real-time quantitative measurements of nitrous oxide (N2O) and methane (CH4) in ambient air and human exhaled breath in parts per billion (ppb) levels via an extremely narrow single QCL scan of ∼ 0.06 cm⁻¹. The high-resolution rotational-vibrational interference-free 2f-WMS spectra of CH4 and N2O centred at 1297.8192 cm⁻¹ and 1297.8314 cm⁻¹, respectively were simultaneously acquired with 0.20 s data acquisition time in the optimized experimental conditions. Minimum detection limits of 6 ppb for N2O and 30 ppb CH4 were achieved by the cw-EC-QCL based 2f-WMS detection method, thus opening its broad applications in environmental monitoring and non-invasive biomedical diagnostics.
The impact of drainage on the stability of peatland carbon sinks is well known; however, much less is understood regarding the way active management of the water‐table affects carbon balance. In this study, we determined the carbon balance in the Great Dismal Swamp, a large, forested peatland in the southeastern USA, which has been drained for over two hundred years and is now being restored through hydrologic management. We modeled future net ecosystem carbon balance over 100 years (2012 to 2112) using in situ field observations paired with simulations of water‐table depth. The three scenarios used in the model were baseline conditions, flooded/wet conditions, and drained/dry conditions, which represent a range of potential management actions and climate conditions at the Great Dismal Swamp. In the Baseline scenario, results show a carbon sink of 0.7 Tg, or an average annual rate of 0.23 Mg C/ha/yr. The Flooded/Wet scenario produced a net ecosystem carbon balance of 4.6 Tg C or an average annual rate of 1.06 Mg C/ha/yr. For the Drained/Dry scenario, under which no management was conducted, and typically dry conditions were assumed, the Great Dismal Swamp becomes a net carbon source at –2.07 Tg C or an average annual rate of –0.38 Mg C/ha/yr.
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.
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.
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.
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.
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.
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.
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).
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.
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
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.
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.
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.
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.
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).
Soil Greenhouse Gas Flux Measurements with Automated and Manual Static Chambers, Forced Diffusion Chamber, and Concentration Profiles
- 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).
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).