Small methane emissions from pasture observed with eddy covariance and flux-gradient methods: are they real or artefacts?

Measuring eddy covariance fluxes of ozone with a slow-response analyser

Surface fluxes of sensible heat and latent energy are important in many atmospheric processes and can be measured with reasonable accuracy over homogeneous surfaces. Direct measurements of turbulent fluxes such as sensible heat and latent energy, which are components of the shortened energy balance, are usually achieved by the eddy covariance (EC) method, which is considered the standard method for sensible heat and latent energy flux measurement and basically involves the use of single-point measurements from EC instruments mounted on a mast. However, the application of the EC method is often problematic. In this paper, results of the EC and surface layer scintillometer (SLS) estimations of sensible heat flux for different atmospheric stability conditions, namely, unstable, and near-neutral atmospheric stability conditions are presented. The aim of the study was to assess sensible heat flux measurements obtained by SLS, which relies on Monin-Obukhov Similarity Theory (MOST) and therefore assumes stationarity and homogeneity of the surface where measurements are taken with those obtained using the EC method for different stability conditions and different times (seasons) of the year. Statistical analysis of the data reveals a seasonal trend in the sensible heat flux, F h comparisons between the two measurement methods. There seems to be better agreement in the measurements obtained by the two methods, as noted by higher correlation coefficients and t-values, obtained in warm summer period from November to December during unstable atmospheric conditions while lower agreement in the values are recorded in the cold months of June and August. Also noted is a slight bias in the SLS measurement of F h compared to the EC measurements. The bias in SLS F h measurements is noticed for unstable atmospheric conditions whereas the EC method seems to record slightly greater values when the atmospheric condition is near-neutral. However the agreement between the F h values measured by the two measurement methods is still good. The agreement is even more remarkable considering that the EC method is a point measurement method depending on the covariance between w and sonic temperature T whereas the SLS method is an areal-averaging method that depends on MOST and therefore also on z−d. The inner scale length l o values measured by the SLS method are larger in the evening and night-time when the atmospheric condition is stable than during the daytime when the atmosphere is mainly unstable. This can be attributed to greater turbulent mixing during the unstable atmospheric condition compared to low turbulent mixing when the atmosphere is mainly stable. As for the agreement in the sensible heat flux values measured by the EC and SLS methods, there is no distinct or consistent pattern. Vegetation height also seems to slightly influence the agreement in the F h measurements obtained by the two methods (EC and SLS) as is noticed from the slope values. In general, the slope values approach 1 with increasing vegetation height for both unstable and near-neutral atmospheric conditions, although there are exceptions especially for the month of November.

Abstract. We determine the net land to atmosphere flux of carbon in Russia, including Ukraine, Belarus and Kazakhstan, using inventory-based, eddy covariance, and inversion methods. Our high boundary estimate is −342 Tg C yr−1 from the eddy covariance method, and this is close to the upper bounds of the inventory-based Land Ecosystem Assessment and inverse models estimates. A lower boundary estimate is provided at −1350 Tg C yr−1 from the inversion models. The average of the three methods is −613.5 Tg C yr−1. The methane emission is estimated separately at 41.4 Tg C yr−1. These three methods agree well within their respective error bounds. There is thus good consistency between bottom-up and top-down methods. The forests of Russia primarily cause the net atmosphere to land flux (−692 Tg C yr−1 from the LEA. It remains however remarkable that the three methods provide such close estimates (−615, −662, −554 Tg C yr–1) for net biome production (NBP), given the inherent uncertainties in all of the approaches. The lack of recent forest inventories, the few eddy covariance sites and associated uncertainty with upscaling and undersampling of concentrations for the inversions are among the prime causes of the uncertainty. The dynamic global vegetation models (DGVMs) suggest a much lower uptake at −91 Tg C yr−1, and we argue that this is caused by a high estimate of heterotrophic respiration compared to other methods.

A comparison of methods for determining forest evapotranspiration and its components: sap-flow, soil water budget, eddy covariance and catchment water balance

Flux gradient, eddy covariance and relaxed eddy accumulation methods were applied to measure CH4 and N2O emissions from peatlands and arable land respectively. Measurements of N2O emission by eddy covariance using tunable diode laser spectroscopy provided fluxes ranging from 2 to 60 µ mol N2O m-2 h-1 with a mean value of 22 µ mol N2O m-2 h-1 from 320 h of continuous measurements. Fluxes of CH4 measured above peatland in Caithness (U.K.) during May and June 1993 by eddy covariance and relaxed eddy accumulation methods were in the range 70 to 120 µ mol CH4 m-2 h-1 with means of 14.7 µ mol CH4 m -2 h-1 and 22.7 µ mol CH4 m-2 h-1 respectively. Emissions of CH4 from peatland changed with water table depth and soil temperature; increasing from 25 |Amol CH4 m-2 h-1 at 5% pool area to 50 p.mol CH4 m-2 h-1 with 30% within the flux footprint occupied by pools. A temperature response of 4.9 (xmol CH4 m-2 h-1 °C-1 in the range 6-12 °C was also observed. The close similarity in average CH4 emission fluxes reported for wetlands in Caithness, Hudson Bay and Alaska in the range 11 to 40 jamol CH4 m-2 h-1 suggests that earlier estimates of CH4 emission from high latitude wetlands were too large or that the area of high latitudes contributing to CH4 emission has been seriously underestimated.

Autumnal fluxes of CH4 and CO2 from Mediterranean reed wetland based on eddy covariance and chamber methods

Evapotranspiration over a Japanese cypress forest. II. Comparison of the eddy covariance and water budget methods

Fluxes of methane, CH4, were measured with the eddy covariance (EC) method at a small boreal lake in Sweden. The mean CH4 flux during the growing season of 2013 was 20.1 nmol m−2 s−1 and the median flux was 16 nmol m−2 s−1 (corresponding to 1.7 mmol m−2 d−1 and 1.4 mmol m−2 d−1). Monthly mean values of CH4 flux measured with the EC method were compared with fluxes measured with floating chambers (FC) and were in average 62% higher over the whole study period. The difference was greatest in April partly because EC, but not FC, accounted for fluxes due to ice melt and a subsequent lake mixing event. A footprint analysis revealed that the EC footprint included primarily the shallow side of the lake with a major inlet. This inlet harbors emergent macrophytes that can mediate high CH4 fluxes. The difference between measured EC and FC fluxes can hence be explained by different footprint areas, where the EC system “sees” the part of the lake presumably releasing higher amounts of CH4. EC also provides more frequent measurements than FC and hence more likely captures ebullition events. This study shows that small lakes have CH4 fluxes that are highly variable in time and space. Based on our findings we suggest to measure CH4 fluxes from lakes as continuously as possible and to aim for covering as much of the lakes surface as possible, independently of the selected measuring technique.

Greenhouse gas flux monitoring in ecosystems is mostly conducted by closed chamber and eddy covariance techniques. To determine the relevance of the two methods in rice paddy fields at different growing stages, closed chamber (CC) and eddy covariance (EC) methods were used to measure the methane (CH4) fluxes in a flooded rice paddy field. Intensive monitoring using the CC method was conducted at 30, 60 and 90 days after transplanting (DAT) and after harvest (AHV). An EC tower was installed at the centre of the experimental site to provide continuous measurements during the rice cropping season. The CC method resulted in CH4 flux averages that were 58%, 81%, 94% and 57% higher than those measured by the EC method at 30, 60 and 90 DAT and after harvest (AHV), respectively. A footprint analysis showed that the area covered by the EC method in this study included non-homogeneous land use types. The different strengths and weaknesses of the CC and EC methods can complement each other, and the use of both methods together leads to a better understanding of CH4 emissions from paddy fields.

Core Ideas Aerodynamic methods can be used to gap‐fill Bowen ratio energy balance micrometeorological measurements. Eddy covariance and Bowen ratio energy balance methods agree during turbulent daytime conditions. Measuring nighttime net ecosystem exchange is challenging using turbulence‐based micrometeorology. There is a need to understand the potential benefits of using the biotechnology waste by‐product from manufacturing as a fertilizer replacement in agriculture, by quantifying the economic value for the farmer and measuring the environmental impact. Measuring CO2 emissions can be used to assess environmental impact, including three widely used micrometeorological methodologies: (i) the Bowen Ratio Energy Balance (BREB), (ii) aerodynamic flux‐gradient theory, and (iii) eddy covariance (EC). As a first step in quantifying benefits of applying biotechnology waste in agriculture, a detailed examination of these three methods was conducted to understand their effectiveness in quantifying CO2 emissions for this specific circumstance. The study measured micrometeorological properties over a field planted to maize (Zea mays L. var. indentata), one plot treated with biotechnology waste applied as a nutrient amendment, and one plot treated with a typical farmer fertilizer practice. Carbon dioxide flux measurements took place over 1 yr, using both BREB and EC systems. The aerodynamic method was used to gap‐fill BREB system measurements, and those flux estimates were compared with estimates produced separately by the aerodynamic and EC methods. All methods found greater emissions over the biotechnology waste application. The aerodynamic method CO2 flux estimates were considerably greater than both the EC and a combined BREB‐aerodynamic approach. During the day, the EC and BREB methods agree. At night, the aerodynamic approach detects and accounts for buildup of CO2 at the surface during stable periods. The BREB systems combined with aerodynamic approaches provide alternate methods to EC in examining micrometeorological properties near the surface.

Accurate evapotranspiration, ET, data are crucial for irrigation management projects, especially in drought prone regions. Evapotranspiration rates can be estimated by micrometeorological methods and the energy balance equation, soil depletion techniques, mass exchange methods, or by using weighting lysimeters. These methods usually are expensive, difficult to operate, and some of them present problems for measurements in heterogeneous vegetation. Therefore, the search for accurate methods for estimating ET fluxes using low-cost, transportable and robust instrumentations is a subject of interest. The eddy covariance (EC) method is the commonly used micrometeorological technique providing direct measurements of latent heat flux (or evapotranspiration). It adopts a sonic anemometer to measure high-frequency vertical wind speed fluctuations about the mean and an infrared gas analyzer to measure high frequency water concentration fluctuations. These fluctuations are paired to determine the mean covariance of the wind speed and humidity fluctuations about the mean to directly estimate latent heat flux (LE). In the EC method, the sensible heat flux is also estimated using the covariance of the fluctuation in vertical wind speed and variations in temperature about their means. While the preferred method for measuring turbulent fluxes is the eddy covariance (EC) method, the lack of closure is unresolved and a full guidance on experimental set up and raw data processing is still unavailable. Other energy balance approaches, such as the Bowen ratio and aerodynamic methods, have a sound theoretical basis and can be highly accurate for some surfaces under acceptable conditions. Biometeorological measurements and theory identified large, organized eddies embedded in turbulent flow, called “coherent structures” as the entities which exchange water vapour, heat, and other scalars between the atmosphere and plant communities. Based on these studies, a new method for estimating scalar fluxes called “Surface Renewal (SR)” was proposed by Paw U and Brunet (1991). Surface Renewal (SR) theory in conjunction with the analysis of the observed ramp-like patterns in the scalar traces provides an advantageous method for estimating the surface flux density of a scalar. The method was tested with air temperature data recorded over various crop canopies. Results of the studies (Snyder et al., 1996; Spano et al., 1997; Consoli et al., 2006; Castellvi et al., 2008) have demonstrated good SR performance in terms of flux densities estimation, well correlated with EC measurements. The approach has the advantages to (i) require as input

Chapter 16 - Micrometeorology: (i) Turbulent Transfer, Profiles, and Fluxes

Effective greenhouse gas mitigation strategies in the agricultural sector are crucial for reducing emissions. Methane (CH4) emissions associated with agriculture are predominantly the result of enteric fermentation from ruminant production systems. Accurate measurement of these emissions is essential for assessing environmental impacts and developing effective mitigation strategies. The eddy covariance (EC) method is widely used to measure trace gas and energy fluxes and has since also been adapted to measure enteric CH4 emissions from grazing ruminants effectively. This study combined EC measurements of CH4 emissions from pasture-based Jersey cows with milk production, feed intake data and CH4 prediction equations during four measurement campaigns between September and November 2022 in northern Germany. Cows’ distance relative to the EC station was controlled by a specialized fencing system and its effect on the measured CH4 fluxes was adjusted by means of footprint (FP) flux allocation based on a two-dimensional FP model. The EC method presented very low daily emissions of 205 g CH4 cow−1 day−1, below the estimations based on the Intergovernmental Panel on Climate Change (IPCC) Tier 2 default values and other equations based on feed intake and feed quality parameters. The results of this study indicated that the EC method, in combination with a specialized fencing design, is an appropriate method to measure enteric CH4 emissions of dairy cows in pasture-based systems. Moreover, this study showed that a comprehensive dataset of animal-related data is a practical tool to contextualize the results.

<p>In this study we compare turbulent energy fluxes obtained from eddy covariance (EC) (LI-7500A, LI-COR + Windmaster, Gill Instruments) and large aperture scintillometer (BLS900, Scintec) over an agricultural field (wheat field, straw and bare soil). As the EC method provides direct measurements of sensible heat (H<sub>EC</sub>) and latent heat (LE<sub>EC</sub>) fluxes we use it as a reference method. The EC method enables to determine fluxes within a footprint centered around the point of measurement in the middle of the field. The scintillometer provides an estimation of sensible heat flux (H<sub>SC</sub>), derived from air refractive index fluctuation integrated over the measurement path length, in this case 570 m diagonally across whole field. The reference measurements of the radiation balance components consist of 4-component net radiometer for net radiation (Rn) (NR01, Hukseflux), three soil heat flux plates for soil heat flux (G) monitoring (HFP01, Hukseflux), including thermocouples for quantification of the heat storage above the soil heat flux plates. The scintillometer-based latent heat (LE<sub>SC</sub>) is calculated as a residuum from available energy (Rn-G) and H<sub>SC</sub>, provided by scintillometer. The measurement of radiation balance components was located at the top of 3.5 m mast with the EC system, while the soil heat flux plates were collocated around in 5 cm depth. The site is a flat, rectangular agricultural field (app. 16.5 ha), in the north-eastern Austria, Danube river lowland (48.21N, 16.622E), sown with winter wheat during growing season 2019. The measurement campaign was established in February 2019 with aim for multi-seasonal monitoring. The EC measurement height is 2.7 m, the scintillometer transmitter and receiver are fixed on 4 m masts, facing towards each other from NW and SE corners of the field.</p><p>Comparison of the EC-based turbulent fluxes (H<sub>EC</sub>+LE<sub>EC</sub>) and the available energy (Rn-G) during the period March to Mid-June showed a very good agreement, resulting in the energy balance closure of 0.96 (R<sup>2 </sup>= 0.93). This suggest high accuracy and robustness of the measurement setup together with the ability of the EC method to capture all scales of eddies responsible for energy transport at this site. The comparison of methods indicates that H<sub>SC</sub> overestimated H<sub>EC</sub> by 10 % (R<sup>2 </sup>= 0.74) and LE<sub>SC</sub> underestimated LE<sub>EC</sub> by 13 % (R<sup>2 </sup>= 0.81). Related to Rn, the H<sub>EC</sub>, LE<sub>EC</sub> and G fluxes accounted for 22 % (R<sup>2 </sup>= 0.53), 59 % (R<sup>2 </sup>= 0.70) and 15% (R<sup>2 </sup>= 0.62) of the Rn flux, respectively. We assume that the combination of EC and scintillometer method has a potential to bring deeper insight into the analysis of the energy balance closure problem.</p>

Abstract. Understanding surface-atmosphere interactions is critical for environmental and meteorological studies. Sensible heat flux, a key component in this interaction, is typically measured using methods such as Eddy Covariance (EC) and Flux-Gradient (FG). The EC method, known for its high temporal resolution and direct measurement capabilities of wind speed, temperature, and humidity changes, requires the use of expensive and complex equipment, making it costly and challenging to implement. On the contrary, the FG method is more accessible and economical, relying on simpler instruments, but often lacks the precision of the EC method. To harness the benefits of both methods, this article uses the Multi-Layer Perceptron (MLP) machine learning method to enhance the accuracy of the FG method's sensible heat flux calculations. Through the MLP model, this paper aims to determine the optimal parameter settings for the specific measurement environment, thereby improving the FG methods accuracy. The data was measured from Guandu Village, Anhui Province, China. This research seeks to demonstrate that the trained MLP model can be applied to similar measurement environments, thus enhancing the FG method's applicability and precision.