Seasonal ammonia emissions from an intensive beef cattle feedlot in Victoria Australia

Ammonia (NH3) emitted from concentrated animal feeding operations can cause environmental and health problems, and indirectly contribute to greenhouse gas emissions. Cattle feedlots are known to be large sources of NH3, but few studies have documented seasonal emissions from Australian feedlots. We conducted two field campaigns to measure NH3 emissions from an intensive beef cattle feedlot in southeast Australia, and these results were combined with previous measurements at the same feedlot to document seasonal variations in emissions and to derive annual feedlot emission factors (EFs). Emission rates were calculated with an inverse dispersion modelling (IDM) technique, based on NH3 concentrations measured at the feedlot with open-path lasers (OPLs). The average area emission rates in spring, summer, autumn and winter were 90.5, 167.4, 96.2 and 86.8 μg NH3 m-2 s-1 from the cattle pens, and 22.5, 18.1, 7.7 and 20.7 μg NH3 m-2 s-1 from the manure stockpile area, respectively. The total per-animal EFs ranged from 126.0 (autumn) to 190.2 g NH3 animal-1 d-1 (summer), representing a loss of 47.5-64.6% of the fed N. Seasonal variations in emissions were related to air temperature. Slight changes in crude protein content of the cattle diet may also have impacted seasonal variability. Taking seasonal variations into consideration, the average feedlot EF was 160.4 g NH3 animal-1 d-1, with 90% of the emissions coming from the cattle pens. Extrapolating the EF to all feedlot cattle in the country, the direct NH3 emissions from Australian feedlots amount to 65.2 Gg NH3 annually, or 3.7% of the national total. Our study benchmarks seasonal and annual EFs and N losses for Australian commercial feedlots, and provides a baseline for extrapolating the impacts of mitigation efforts.

Ammonia emissions and dispersion from broiler production

Ammonia (NH₃ ) has been used as a target gas for nuisance complaints to restrict or close poultry operations near encroaching rural development. There are conflicting data on NH₃ emissions from broiler production across the United States. The purpose of this research is to compare emission rates from a Georgia broiler operation across seasons and with other geographical areas in the United States. Comparison of seasonal and geographical emission rates showed large seasonal variation in NH₃ emissions for eastern U.S. sites but little seasonal variation in the semi-arid region of the United States. Differences in production management practices, ambient temperature, and animal density did not appear to explain differences in emissions between regions; however, the climatic influence of ambient humidity and litter management practices are thought to be key factors in the generation of emissions.

Micrometeorological Methods for Measuring Methane Emission Reduction at Beef Cattle Feedlots: Evaluation of 3-Nitrooxypropanol Feed Additive

It is highly desirable to test agricultural emission mitigation strategies in a whole-farm environment to ensure that all aspects of management and production operations are included. However, the large spatial scale of commercial operations makes the dual measurements of control and treatment(s) difficult. We evaluated the application of two micrometeorological methods, a novel concentration ratio method and an inverse dispersion method, where both were used to measure methane (CH) emission reductions in cattle fed the compound 3-nitrooxypropanol compared with cattle fed just the basal diet. In total, there were 1344 cattle used that were located in six pens (∼222 animals per pen). Three adjacent pens to the east and three to the west were designated as the treatment and control blocks, respectively. Underlying the emission reduction method was the assumption of site symmetry between the treatment and control pen blocks in the feedlot. There was, on average, a large CH emission reduction of ∼70% (±18%) due to the additive as found by both micrometeorological methods. Both methods also show a change in the diel distribution (peak emissions after initial morning feeding) and seasonal pattern (a decrease in emission reduction of 7.5 and 26.1% over 90 d). The simplicity of the developed concentration ratio method is expected to have applications for evaluating other mitigation strategies at large commercial scales (e.g., the application of manure additives to pens to reduce odors and ammonia emissions).

Applicability of Eddy Covariance to Estimate Methane Emissions from Grazing Cattle

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.

Ammonia Emission from a Beef Cattle Feedlot and Its Local Dry Deposition and Re-Emission

Ammonia (NH) volatized from livestock manure is affiliated with ecosystem and human health concerns and decreased fertilizer value of manure and can also be an indirect source of greenhouse gas. Beef cattle feedlots, where thousands of cattle are grouped together to enable greater control of feed management and production, are hot spots in the agricultural landscape for NH emissions. Quantifying the feedlot NH emissions is a difficult task, partly due to the reactive nature of NH within and surrounding the feedlot. Our study used a dispersion model coupled to field measurements to derive NH emissions from a feedlot in southern Alberta, Canada. The average feedlot NH emission was 50 μg m s (85 g animal d), which coincides with a low dietary crude protein content. At a location 165 m east of the feedlot, a flux gradient (FG) technique measured an average NH deposition of 12.0 μg m s (west wind) and 5.3 μg m s (east wind). Ammonia FG emission averaged 1 μg m s with east winds, whereas no NH emission was found for west wind. Using soil-captured NH, there was a decrease in deposition with distance from the feedlot (50% over 200 m). Collectively, the results of this study provide insight into the dynamics of NH in the agricultural landscape and illustrate the need for NH mitigation to improve the environmental and economic sustainability of cattle feedlots.

A Snapshot of Greenhouse Gas Emissions from a Cattle Feedlot

Beef cattle feedlots emit large amounts of the greenhouse gases (GHG) methane (CH) and nitrous oxide (NO), as well as ammonia (NH), which contributes to NO emission when NH is deposited to land. However, there is a lack of simultaneous, in situ, and nondisturbed measurements of the major GHG gas components from beef cattle feedlots, or measurements from different feedlot sources. A short-term campaign at a beef cattle feedlot in Victoria, Australia, quantified CH, NO, and NH emissions from the feedlot pens, manure stockpiles, and surface run-off pond. Open-path Fourier transform infrared (OP-FTIR) spectrometers and open-path lasers (OP-Laser) were used with an inverse-dispersion technique to estimate emissions. Daily average emissions of CH, NO, and NH were 132 (± 2.3 SE), 0, and 117 (± 4.5 SE) g animal d from the pens and 22 (± 0.7 SE), 2 (± 0.2 SE), and 9 (± 0.6 SE) g animal d from the manure stockpiles. Emissions of CH and NH from the run-off pond were less than 0.5 g animal d. Extrapolating these results to the feedlot population of cattle across Australia would mean that feedlots contribute approximately 2% of the agricultural GHG emissions and 2.7% of livestock sector emissions, lower than a previous estimate of 3.5%.

Evaluating dispersion modeling options to estimate methane emissions from grazing beef cattle

Enteric methane (CH) emission from cattle is a source of greenhouse gas and is an energy loss that contributes to production inefficiency for cattle. Direct measurements of enteric CH emissions are useful to quantify the magnitude and variation and to evaluate mitigation of this important greenhouse gas source. The objectives of this study were to evaluate the impact of stocking density of cattle and source configuration (i.e., point source vs. area source and elevation of area source) on CH emissions from grazing beef cattle in Queensland, Australia. This was accomplished using nonintrusive atmospheric measurements and a gas dispersion model. The average measured CH emission for the point and area source was between 240 and 250 g animal d over the entire study. There was no difference ( > 0.05) in emission when using an elevated area source (0.5 m) or a ground area source (0 m). For the point-source configuration, there was a difference in CH emission due to stocking density; likewise, some differences existed for the area-source emissions. This study demonstrates the flexibility of the area-source configuration of the dispersion model to estimate CH emissions even at a low stocking density.

Optimal sensor locations for the backward lagrangian stochastic technique in measuring lagoon gas emission

This study evaluated the impact of gas concentration and wind sensor locations on the accuracy of measuring gas emission rates from a lagoon environment using the backward Lagrangian stochastic (bLS) inverse-dispersion technique. Path-integrated concentrations (PICs) and three-dimensional (3D) wind vector data were collected at different locations within the lagoon landscape. A floating 45 m × 45 m perforated pipe network on an irrigation pond was used as a synthetic distributed emission source for the controlled release of methane. A total of 961 15-min datasets were collected under different atmospheric stability conditions over a 2-yr period. The PIC location had a significant impact on the accuracy of the bLS technique. The location of the 3D sonic anemometer was generally not a factor for the measured accuracies with the PIC positioned on the downwind berm. The PICs across the middle of the pond consistently produced the lowest accuracy with any of the 3D anemometer locations (<69% accuracy). The PICs located on the downwind berm consistently yielded the best bLS accuracy regardless of whether the 3D sonic anemometer was located on the upwind, side, or downwind berm (accuracies ranged from 79 to 108%). The accuracies of the emission measurements with the berm PIC-berm 3D setting were statistically similar to that found in a more ideal homogeneous grass field. Considering the practical difficulties of setting up equipment and the accuracies associated with various sensor locations, we recommend that wind and concentration sensors be located on the downwind berm.

Methane emissions from a swine manure tank in western Canada

Flesch, T. K., Vergé, X. P. C., Desjardins, R. L. and Worth, D. 2013. Methane emissions from a swine manure tank in western Canada. Can. J. Anim. Sci. 93: 159–169. The emission rate of methane (CH4) to the atmosphere was measured from a concrete manure tank at a farrow-to-finish swine facility in western Canada. Measurements were made during four seasonal campaigns using a bLS inverse-dispersion technique. Emission rates were highest in summer and lowest in winter, with intermediate rates in spring and fall. Annual emissions were estimated at 7600 kg CH4, or 6.3 kg CH4 m−2 of tank surface area. Site-specific factors used for estimating CH4 emissions were calculated from our measurements. A simple methane conversion factor, used by the Intergovernmental Panel on Climate Change to relate emissions to the volatile solids content of the manure, was calculated as 0.23. This value may be unrepresentatively high due to the long duration (15 mo) that manure was stored in the tank. A more sophisticated calculation methodology considers the influence of manure storage duration and temperature, and includes a critical management design practices (MDP) factor. The MDP factor was calculated as 0.31 for our tank. This MDP value implies that emissions from our manure tank were lower than expected given the results from other studies.

The effect of biofuel production on swine farm methane and ammonia emissions

Methane (CH) and ammonia (NH3) are emitted to the atmosphere during anaerobic processing of organic matter, and both gases have detrimental environmental effects. Methane conversion to biofuel production has been suggested to reduce CH4 emissions from animal manure processing systems. The purpose of this research is to evaluate the change in CH4 and NH3 emissions in an animal feeding operation due to biofuel production from the animal manure. Gas emissions were measured from swine farms differing only in their manure-management treatment systems (conventional vs. biofuel). By removing organic matter (i.e., carbon) from the biofuel farms' manure-processing lagoons, average annual CH4 emissions were decreased by 47% compared with the conventional farm. This represents a net 44% decrease in global warming potential (CO2 equivalent) by gases emitted from the biofuel farms compared with conventional farms. However, because of the reduction of methanogenesis and its reduced effect on the chemical conversion of ammonium (NH4+) to dinitrogen (N2) gas, NH3 emissions in the biofuel farms increased by 46% over the conventional farms. These studies show that what is considered an environmentally friendly technology had mixed results and that all components of a system should be studied when making changes to existing systems.

Coarse particulate matter emissions from cattle feedlots in Australia

Open cattle feedlots are a source of air pollutants that include particular matter (PM). Over 24 h, exposure to ambient concentrations of 50 microg m(-3) of the coarse-sized fraction PM (aerodynamic diameter <10 microm [PM(10)]) is recognized as a health concern for humans. The objective of our study was to document PM(10) concentration and emissions at two cattle feedlots in Australia over several days in summer. Two automated samplers were used to monitor the background and in-feedlot PM(10) concentrations. At the in-feedlot location, the PM(10) emission was calculated using a dispersion model. Our measurements revealed that the 24-h PM(10) concentrations on some of the days approached or exceeded the health criteria threshold of 50 microg m(-3) used in Australia. A key factor responsible for the generation of PM(10) was the increased activity of cattle in the evening that coincided with peak concentrations of PM(10) (maximum, 792 microg m(-3)) between 1930 and 2000 h. Rain coincided with a severe decline in PM(10) concentration and emission. A dispersion model used in our study estimated the emission of PM(10) between 31 and 60 g animal(-1) d(-1). These data contribute to needed information on PM(10) associated with livestock to develop results-based environmental policy.

Performance of a dispersion model to estimate methane loss from cattle in pens

Accurate measurements of enteric methane (CH(4)) emissions from cattle (Bos taurus) are necessary to improve emission coefficients used in national emissions inventories, and to evaluate mitigation strategies. Our study was conducted to evaluate a novel approach that allowed near continuous CH(4) measurement from beef cattle confined in pens. The backward Lagrangian Stochastic (bLS) dispersion technique was used in conjunction with global position system (GPS) information from individual animals, to evaluate CH(4) emissions from pens of cattle. The dispersion technique was compared to estimates of CH(4) production using the SF(6) tracer technique. Sixty growing beef cattle were fed a diet containing 60% barley silage (dry matter basis) supplemented with either barley (Hordeum vulgare L.) grain or corn (Zea mays L.) distillers dried grains. The results show that daily CH(4) emissions were about 7% lower for the dispersion technique than for the tracer technique (185 vs. 199 g CH(4) animal(-1) d(-1)). The precision of the dispersion technique, relative to the SF(6) tracer technique, expressed by the Pearson coefficient was 0.76; the relative accuracy given by the concordance coefficient was 0.69. The bLS dispersion technique was able to detect differences (P < 0.05) due to diet and has the added advantage of measuring the pattern of CH(4) production during the 24-h period, with emissions ranging from 161 to 279 g CH(4) animal(-1) d(-1). Configuring the cattle as point sources resulted in more accurate CH(4) emissions than assuming a uniform area release from the pen surface. The results indicate that the bLS dispersion technique using cattle as point sources can be used to accurately measure enteric CH(4) from cattle and to evaluate the impact of dietary mitigation strategies.

Estimating gas emissions from multiple sources using a backward Lagrangian stochastic model

Manure storage tanks and animals in barns are important agricultural sources of methane. To examine the possibility of using an inverse dispersion technique based on a backward Lagrangian Stochastic (bLS) model to quantify methane (CH4) emissions from multiple on-farm sources, a series of tests were carried out with four possible source configurations and three controlled area sources. The simulated configurations were: (C1) three spatially separate ground-level sources, (C2) three spatially separate sources with wind-flow disturbance, (C3) three adjacent ground-level sources to simulate a group of adjacent sources with different emission rates, and (C4) a configuration with a ground level and two elevated sources. For multiple ground-level sources without flow obstructions (C1 and C3), we can use the condition number (K, the ratio of the uncertainty in the calculated emission rate to the uncertainty in the predicted ratio of concentration to emission rate) to evaluate the applicability of this inverse dispersion technique and a preliminary threshold of K <10 is recommended. For multiple sources with wind disturbance (C2) or an even more complex configuration including ground level and elevated sources (C4), a low kappa is not sufficient to provide reasonable discrete and total emission rates. The effect of flow obstructions can be neglected as long as the distance between the source and the measurement location is greater than approximately 10 times the height of the flow obstructions. This study shows that the bLS model has the potential to provide accurate discrete emission rates from multiple on-farm emissions of gases provided that certain conditions are met.

Quantifying ammonia emissions from a cattle feedlot using a dispersion model

Livestock manure is a significant source of ammonia (NH3) emissions. In the atmosphere, NH3 is a precursor to the formation of fine aerosols that contribute to poor air quality associated with human health. Other environmental issues result when NH3 is deposited to land and water. Our study documented the quantity of NH3 emitted from a feedlot housing growing beef cattle. The study was conducted between June and October 2006 at a feedlot with a one-time capacity of 22,500 cattle located in southern Alberta, Canada. A backward Lagrangian stochastic (bLS) inverse-dispersion technique was used to calculate NH3 emissions, based on measurements of NH3 concentration (open-path laser) and wind (sonic anemometer) taken above the interior of the feedlot. There was an average of 3146 kg NH3 d(-1) lost from the entire feedlot, equivalent to 84 microg NH3 m(-2) s(-1) or 140 g NH3 head(-1) d(-1). The NH3 emissions correlated with sensible heat flux (r2 = 0.84) and to a lesser extent the wind speed (r2 = 0.56). There was also evidence that rain suppressed the NH3 emission. Quantifying NH3 emission and dispersion from farms is essential to show the impact of farm management on reducing NH3-related environmental issues.

An approach for measuring methane emissions from whole farms

Estimates of enteric methane (CH4) emissions from ruminants are typically measured by confining animals in large chambers, using head hoods or masks, or by a ratiometric technique involving sampling respired air of the animal. These techniques are not appropriate to evaluate large-scale farm emissions and the variability between farms that may be partly attributed to different farm management. This study describes the application of an inverse-dispersion technique to calculate farm emissions in a controlled tracer-release experiment. Our study was conducted at a commercial dairy farm in southern Alberta, Canada (total of 321 cattle, including 152 lactating dairy cows). Sulfur hexafluoride (SF6) and CH4 were released from 10 outlet locations (barn and open pens) using mass-flow controllers. A Lagrangian stochastic (LS) dispersion model was then used to infer farm emissions from downwind gas concentrations. Concentrations of SF6 and CH4 were measured by gas chromatography analysis and open path lasers, respectively. Wind statistics were measured with a three-dimensional sonic anemometer. Comparing the inferred emissions with the known release rate showed we recovered 86% of the released CH4 and 100% of the released SF6. The location of the concentration observations downwind of the farm was critically important to the success of this technique.