Evaluating an eddy covariance technique to estimate point-source emissions and its potential application to grazing cattle

Coates, Trevor; Flesch, Thomas K.; McGinn, S. M.; Charmley, E.; Chen, Deli

doi:10.1016/j.agrformet.2016.12.026

Cited by 25 publications

(19 citation statements)

References 31 publications

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“…receptor (measurement) distance to sources less than 500 m) using the combination of inverse dispersion modelling with either concentration or flux measurements is a widespread method, especially in the agricultural sector (e.g. Coates et al, 2017;Felber et al, 2015;Laubach et al, 2008;Laubach et al, 2012;Loubet et al, 2010;Sintermann et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Accounting for Field-Scale Dry Deposition in Backward Lagrangian Stochastic Dispersion Modelling of NH<sub>3</sub> Emissions

Häni¹,

Fléchard²,

Neftel³

et al. 2018

Preprint

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A controlled ammonia (NH3) release experiment was performed at a grassland site to quantify the effect of dry deposition, at the field scale between the source and the receptors (NH3 measurement locations), on the estimates of emission rates by means of inverse dispersion modelling. NH3 was released for 3 hours at a constant rate of Q = 6.29 mg s−1 from a grid of 36 orifices spread over an area of 250 m2. The increase in line-integrated NH3 concentration was measured with open-path optical miniDOAS devices at different locations downwind of the artificial source. Using a backward Lagrangian stochastic (bLS) dispersion model (bLSmodelR), the fraction of the modelled release rate to the emitted NH3 (QbLS/Q) was calculated from the measurements of the individual instruments. QbLS/Q was found to be systematically lower than 1, on average between 0.69 and 0.91, depending on the location of the receptor. We hypothesized that NH3 dry deposition to grass and soil surfaces was the main factor responsible for the observed depletion of NH3 between source and receptor. A dry deposition algorithm based on a deposition velocity approach was included in the bLS modelling. Model deposition velocities were evaluated from a ‘big‑leaf’ canopy resistance analogy. Canopy resistances (generally termed Rc) that provided QbLS/Q = 1 ranged from 75 to 290 s m−1, showing that surface removal of NH3 by dry deposition can plausibly explain the original underestimation of QbLS/Q. The inclusion of a dry deposition process in dispersion modelling is crucial for emission estimates, which are based on concentration measurements of depositing tracers downwind of homogeneous area sources or heterogeneously distributed hot spots, such as e.g. urine patches on pastures in the case of NH3.

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Section: Introductionmentioning

confidence: 99%

Accounting for Field-Scale Dry Deposition in Backward Lagrangian Stochastic Dispersion Modelling of NH<sub>3</sub> Emissions

Häni¹,

Fléchard²,

Neftel³

et al. 2018

Preprint

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“…Elevated fluxes could also reflect greater uncertainty in estimates during the morning hours. Coates et al (2017), using EC, found that the LS model estimates of a gas release were less accurate in the morning hours due to changing stability conditions and less certain wind flow, compared with afternoon periods when the turbulent structure of the atmosphere was more consistent.…”

Section: Resultsmentioning

confidence: 99%

“…Cattle emission estimates were obtained by using the footprint calculation described by Coates et al (2017) to interpret the relationship between the EC‐derived flux and emissions occurring at the animal locations. This calculation is based on the LS atmospheric dispersion model described by Flesch et al (2004).…”

Section: Methodsmentioning

confidence: 99%

“…Coates et al (2017) showed that a footprint analysis based on a Lagrangian stochastic (LS) dispersion model could accurately determine the relationship between the calculated landscape flux and the emission rate from a set of eight point sources randomly configured like a small cattle herd. The goal of the present study was to use this LS model approach to interpret EC‐derived CH 4 fluxes from a cattle‐grazed landscape and estimate cattle emissions.…”

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confidence: 99%

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Applicability of Eddy Covariance to Estimate Methane Emissions from Grazing Cattle

et al. 2018

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Grazing systems represent a significant source of enteric methane (CH), but available techniques for quantifying herd scale emissions are limited. This study explores the capability of an eddy covariance (EC) measurement system for long-term monitoring of CH emissions from grazing cattle. Measurements were made in two pasture settings: in the center of a large grazing paddock, and near a watering point where animals congregated during the day. Cattle positions were monitored through time-lapse images, and this information was used with a Lagrangian stochastic dispersion model to interpret EC fluxes and derive per-animal CH emission rates. Initial grazing paddock measurements were challenged by the rapid movement of cattle across the measurement footprint, but a feed supplement placed upwind of the measurements helped retain animals within the footprint, allowing emission estimates for 20% of the recorded daytime fluxes. At the water point, >50% of the flux measurement periods included cattle emissions. Overall, cattle emissions for the paddock site were higher (253 g CH m adult equivalent [AE] d, SD = 75) and more variable than emissions at the water point (158 g CH AE d, SD = 34). Combining results from both sites gave a CH production of 0.43 g kg body weight, which is in range of other reported emissions from grazing animals. With an understanding of animal behavior to allow the most effective use of tower placement, the combination of an EC measurement platform and a Lagrangian stochastic model could have practical applications for long-term monitoring of fluxes in grazing environments.

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“…Estimation of trace gas emission from confined source areas on a local scale (i.e., receptor (measurement) distance to sources less than 500 m) using the combination of inverse dispersion modelling with either concentration or flux measurements is a widespread method, especially in the agricultural sector (e.g., [1][2][3][4][5][6]). …”

Section: Introductionmentioning

confidence: 99%

Accounting for Field-Scale Dry Deposition in Backward Lagrangian Stochastic Dispersion Modelling of NH3 Emissions

et al. 2018

View full text Add to dashboard Cite

Abstract:A controlled ammonia (NH 3 ) release experiment was performed at a grassland site. The aim was to quantify the effect of dry deposition between the source and the receptors (NH 3 measurement locations) on emission rate estimates by means of inverse dispersion modelling. NH 3 was released for three hours at a constant rate of Q = 6.29 mg s −1 from a grid of 36 orifices spread over an area of 250 m 2 . The increase in line-integrated NH 3 concentration was measured with open-path optical miniDOAS devices at different locations downwind of the artificial source. Using a backward Lagrangian stochastic (bLS) dispersion model (bLSmodelR), the fraction of the modelled release rate to the emitted NH 3 (Q bLS /Q) was calculated from the measurements of the individual instruments. Q bLS /Q was found to be systematically lower than 1, on average between 0.69 and 0.91, depending on the location of the receptor. We hypothesized that NH 3 dry deposition to grass and soil surfaces was the main factor responsible for the observed depletion of NH 3 between source and receptor. A dry deposition algorithm based on a deposition velocity approach was included in the bLS modelling. Model deposition velocities were evaluated from a 'big-leaf' canopy resistance analogy. Canopy resistances (generally termed R c ) that provided Q bLS /Q = 1 ranged from 75 to 290 s m −1 , showing that surface removal of NH 3 by dry deposition can plausibly explain the original underestimation of Q bLS /Q. The inclusion of a dry deposition process in dispersion modelling is crucial for emission estimates, which are based on concentration measurements of depositing tracers downwind of homogeneous area sources or heterogeneously-distributed hot spots, such as, e.g., urine patches on pastures in the case of NH 3 .

show abstract

Evaluating an eddy covariance technique to estimate point-source emissions and its potential application to grazing cattle

Cited by 25 publications

References 31 publications

Accounting for Field-Scale Dry Deposition in Backward Lagrangian Stochastic Dispersion Modelling of NH<sub>3</sub> Emissions

Accounting for Field-Scale Dry Deposition in Backward Lagrangian Stochastic Dispersion Modelling of NH<sub>3</sub> Emissions

Applicability of Eddy Covariance to Estimate Methane Emissions from Grazing Cattle

Accounting for Field-Scale Dry Deposition in Backward Lagrangian Stochastic Dispersion Modelling of NH3 Emissions

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