Open-path eddy covariance measurements of ammonia fluxes from a beef cattle feedlot

Sun, Kang; Tao, Lei; Miller, D. J.; Zondlo, M. A.; Shonkwiler, K. B.; Nash, C M; Ham, Jay M.

doi:10.1016/j.agrformet.2015.06.007

Cited by 60 publications

(48 citation statements)

References 46 publications

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“…At this time resolution, the measurements are in good agreement with a linear fit yielding a slope of 0.990 with intercept of 1.7 ppb (R 2 = 0.92). A similar comparison of ammonia plume measurements between open-path laser absorption (WMS) and a commercial closed-path CRDS analyzer has been reported by Sun et al [28]. As is the case in our data comparison (Fig.…”

Section: Field Demonstrationsupporting

confidence: 80%

“…Wavelength modulation spectroscopy (WMS) with a cylindrical multi-pass cell has been used by Miller et al [27] with sensitivity of 0.15 ppb at 10 Hz and a large dynamic response spanning concentrations from sub-ppb to several ppm. An extension of this work also showed the possibility of eddycovariance measurements for flux determination [28].…”

Section: Introductionmentioning

confidence: 96%

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Open-path cavity ring-down spectroscopy sensor for atmospheric ammonia

2016

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eutrophication and acidification of soils which lead to forest extinction and decline in biological diversity [3,4]. Ammonia also readily reacts with atmospheric species such as sulfuric acid (H 2 SO 4 ), nitric acid (HNO 3 ), and hydrochloric acid (HCl) to form fine particulate matter (PM 2.5 ) which can have harmful effects on human health [5]. The particles also cause haze which lead to visibility reduction and affect global radiation budgets [6][7][8]. Two major sources of ammonia are emissions resulting from domestic animals, and from motor vehicle combustion, meaning that most of the ammonia emitted to the atmosphere is directly or indirectly anthropogenic [9]. In spite of the importance of ammonia in the atmosphere, measurement of atmospheric ammonia concentrations and its regional variations have been relatively limited due to two important reasons:(1) Ambient concentrations are low and vary widely, and (2) ammonia is a sticky gas that introduces significant inlet challenges for typical closed-path instruments [8,10,11].We are primarily interested in ammonia emissions from concentrated animal feeding operations (CAFOs), such as feedlots and dairies, and in particular we seek to develop sensors for study of ammonia emissions and bidirectional fluxes and deposition [12,13]. Key sensor requirements are ppb level precision, and time response on the order of seconds, in order to measure turbulent (near-field) plumes that have concentrations typically ranging from 10 to 100 s of ppb. As will be discussed herein, widely used closedpath ammonia laser sensors typically have time response of ~30 s. While adequate for some applications, improving the time response to ~1 s would greatly benefit applications including: (1) moving toward widely used eddy-covariance methods that provide flux information [14], (2) quantifying fluxes from high emission transient/episodic events lasting for seconds to 10 s of seconds, e.g., manure handling/application, barn flushouts at dairies, and top dress application Abstract An open-path cavity ring-down spectroscopy (CRDS) sensor has been developed for measurement of atmospheric ammonia (NH 3 ) and represents the first use of open-path CRDS in the mid-infrared region. The sensor uses a continuous-wave distributed feedback quantum cascade laser at 10.33 μm to target strong absorption features. The optical cavity is constructed with two high-reflectivity mirrors (R = 0.9995). The open-path configuration removes inlet effects, which are very challenging for closed-path instruments, and can be enabling for compact, low-power designs. Sensor performance was validated in the laboratory by measuring known concentrations in a closed-path configuration. The open-path configuration was validated by comparison against a commercial closed-path CRDS instrument for outdoor measurements at a small feed lot. Ammonia concentrations from the two instruments showed good agreement with slope of 0.990 (R 2 = 0.92), for 5-min averages. The precision of the open-path instrument was found from Allan varianc...

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Section: Field Demonstrationsupporting

confidence: 80%

Section: Introductionmentioning

confidence: 96%

Open-path cavity ring-down spectroscopy sensor for atmospheric ammonia

2016

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“…When representing each Level 2 observation as a spatial sensitivity distribution (the actual instrument spatial response function or a smoother version of it), A(j) and B(j) can be calculated at high spatial and temporal resolution cattle CAFOs and the NH 3 hot spots seen from space confirms that they are the dominant source of atmospheric NH 3 in this region. The overall abundance of NH 3 is significantly higher at warmer temperatures, in agreement with the previous in-situ 10 quantification of CAFO NH 3 emissions in the same region (Sun et al, 2015b).…”

supporting

confidence: 79%

A physics-based approach to oversample multi-satellite, multi-species observations to a common grid

Sun¹,

Zhu²,

Cady‐Pereira³

et al. 2018

Preprint

Self Cite

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Abstract.Satellite remote sensing of the Earth's atmospheric composition usually samples irregularly in space and time, and many applications require spatially and temporally averaging the satellite observations (Level 2) to a regular grid (Level 3). When averaging Level 2 data over a long time period to a target Level 3 grid significantly finer than Level 2 pixels, this process is referred to as "oversampling". An agile, physics-based oversampling approach is developed to represent each satellite obser-5 vation as a sensitivity distribution on the ground, instead of a point or a polygon as assumed in previous approaches. This sensitivity distribution can be determined by the spatial response function of each satellite sensor. A generalized 2-D super Gaussian function is proposed to characterize the spatial response functions of both imaging grating spectrometers (e.g., OMI, OMPS, and TROPOMI) and scanning Fourier transform spectrometers (e.g., GOSAT, IASI and CrIS). Synthetic OMI and IASI observations were generated to compare the errors due to simplifying satellite fields of view (FOV) as polygons (tessellation 10 error) and the errors due to discretizing the smooth spatial response function on a finite grid (discretization error). The balance between these two error sources depends on the target grid resolution, the ground size of FOV, and the smoothness of spatial response functions. Explicit consideration of the spatial response function is favorable for high resolution oversampling and smoother spatial response. For OMI, it is beneficial to oversample using the spatial response functions for grid resolutions finer than ∼16 km. The generalized 2-D super Gaussian function also enables smoothing of the Level 3 results by decreasing the 15 shape-determining exponents, useful for high noise level or sparse satellite datasets. This physical oversampling is applied to OMI NO 2 products and IASI NH 3 products, showing substantially improved visualization of trace gas distribution and local gradients.1 Atmos. Meas. Tech. Discuss., https://doi

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“…However, characterising these emissions at the field scale requires complex experimental design and most of the time also requires the use of large fields (Ferrara et al, 2016(Ferrara et al, , 2012Flechard and Fowler, 1998;Loubet et al, 2012;Sintermann et al, 2011b;Spirig et al, 2010;Sun et al, 2015;Whitehead et al, 2008). Especially useful for measuring ammonia losses are methods that can deal with small-and medium-scale fields (20-50 m on the side) that are commonly used in agronomic trials.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a new inference method for estimating ammonia volatilisation from multiple agronomic plots

Loubet¹,

Carozzi²,

Voylokov³

et al. 2018

Biogeosciences

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Abstract. Tropospheric ammonia (NH 3 ) is a threat to the environment and human health and is mainly emitted by agriculture. Ammonia volatilisation following application of nitrogen in the field accounts for more than 40 % of the total NH 3 emissions in France. This represents a major loss of nitrogen use efficiency which needs to be reduced by appropriate agricultural practices. In this study we evaluate a novel method to infer NH 3 volatilisation from small agronomic plots consisting of multiple treatments with repetition. The method is based on the combination of a set of NH 3 diffusion sensors exposed for durations of 3 h to 1 week and a shortrange atmospheric dispersion model, used to retrieve the emissions from each plot. The method is evaluated by mimicking NH 3 emissions from an ensemble of nine plots with a resistance analogue-compensation point-surface exchange scheme over a yearly meteorological database separated into 28-day periods. A multifactorial simulation scheme is used to test the effects of sensor numbers and heights, plot dimensions, source strengths, and background concentrations on the quality of the inference method. We further demonstrate by theoretical considerations in the case of an isolated plot that inferring emissions with diffusion sensors integrating over daily periods will always lead to underestimations due to correlations between emissions and atmospheric transfer. We evaluated these underestimations as −8 % ± 6 % of the emissions for a typical western European climate. For multiple plots, we find that this method would lead to median underestimations of −16 % with an interquartile [−8-22 %] for two treatments differing by a factor of up to 20 and a control treatment with no emissions. We further evaluate the methodology for varying background concentrations and NH 3 emissions patterns and demonstrate the low sensitivity of the method to these factors. The method was also tested in a real case and proved to provide sound evaluations of NH 3 losses from surface applied and incorporated slurry. We hence showed that this novel method should be robust and suitable for estimating NH 3 emissions from agronomic plots. We believe that the method could be further improved by using Bayesian inference and inferring surface concentrations rather than surface fluxes. Validating against controlled source is also a remaining challenge.

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Open-path eddy covariance measurements of ammonia fluxes from a beef cattle feedlot

Cited by 60 publications

References 46 publications

Open-path cavity ring-down spectroscopy sensor for atmospheric ammonia

Open-path cavity ring-down spectroscopy sensor for atmospheric ammonia

A physics-based approach to oversample multi-satellite, multi-species observations to a common grid

Evaluation of a new inference method for estimating ammonia volatilisation from multiple agronomic plots

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