Environ. Sci. Technol. 2000, 34, 3296-3302
Estimating Methane Emissions from Dairy Cattle Housed in a Barn and Feedlot Using an Atmospheric Tracer SAMUEL K. KAHARABATA* AND PETER H. SCHUEPP Department Natural Resource Sciences, McGill UniversitysMacdonald Campus, Ste-Anne-de-Bellevue, Quebec H9X 3V9, Canada, and Centre for Climate and Global Change Research (C2GCR), McGill University, Montreal, Quebec H3A 2K6, Canada RAYMOND L. DESJARDINS Research Branch, Agriculture and Agri-Food Canada, Ottawa, Ontario, K1A 0C6, Canada
Methane emissions from a barn and feedlot/paddock housing dairy cattle were estimated using a tracer gas (SF6) to simulate the dispersion of CH4. The tracer gas was released from 16 point sources distributed within the barn or feedlot to simulate the CH4 sources (cows). Using a two-dimensional (y, z) sampling grid, the observed downwind SF6/CH4 crosswind concentration field was integrated to give the portion of the SF6/CH4 plume that was captured by the sampling grid. Assuming that both SF6 and CH4 underwent similar turbulent atmospheric transport, the ratio of the respective captured plumes was then used to estimate the emission strength of methane from the known release rate of SF6. The predicted source strength of CH4 from the barn was within 6% of the estimate made using a different technique whereby the entire barn was used as an enclosed chamber. The methane emissions predicted in the barn and feedlot experiments were 542 (( 30%) L CH4 d-1 cow-1 and 631 (( 30%) L CH4 d-1 cow-1, respectively. Using census data on the population of dairy cattle in Canada, a national estimate of 0.245 (( 50%) Tg CH4 yr-1 was made.
Introduction Being ruminants, dairy cattle are known emitters of methane (CH4), a potent greenhouse gas (GHG). Although there has been considerable work done in estimating CH4 emissions from cattle (1), such efforts have not necessarily focused on acquiring emissions under typical farm management practices. Therefore, significant uncertainties may exist in the regional inventories of CH4 emissions from cattle. Several methods have been used to measure CH4 emissions from cows. Johnson and Johnson (1) gave a good critical review of the current status of techniques in estimating emissions. These range from metabolic prediction equations, with varying degrees of success, to the more promising tracer gas release methods and complete herd enclosure mass-balance techniques. * Correspondingauthorphone: (416)486-6215;e-mail: skaharabata@ globalserve.net. Present address: Research Branch, Agriculture and Agri-Food Canada, Ottawa, Ontario K1A 0C6, Canada. 3296
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For individual animals, such as free ranging steers, CH4 production per animal has been estimated by a tracer ratio method where controlled sulfur hexafluoride (SF6) tracer gas was released in the rumen of the animal. The eructed gases were collected at the mouth of the animal and then analyzed for the two gases to estimate CH4 production (2-4). For free ranging animals that are fairly well separated from each other, this method is effective. However, for high densities of cows per given area such as a paddock or barn, contamination of the sampled air from other nearby animals (sources) cannot be avoided, and therefore reliable estimates would be more difficult to achieve. For such cases, an outdoor mass balance technique has been used successfully to estimate CH4 emissions from free roaming cattle in fenced-in pastures (5). This method required an elaborate two-dimensional sampling grid along all sides of the feedlot/paddock and detailed micrometeorological observations to estimate incoming and outgoing gas fluxes. The reliability of the approach was tested by releasing known quantities of CO2. Recently, both CH4 and CO2 production have been accurately monitored from dairy cows housed in typical barns in Canada (6) and Germany (7) using a mass balance technique. Both studies gave similar production ranges corrected for the manure contribution present in the barn. For these studies, sophisticated monitoring systems were installed to continuously sample air at every ventilation intake and exhaust outlet and in manure pits below the floor. These air samples were then analyzed online for CH4 and CO2 concentrations. The method was tested by releasing known quantities of a tracer gas: SF6 in the German study (7) and CH4 while the herd was removed from the barn in the Canadian experiment (6). Animals experienced normal barn conditions in both studies. Because individual barns generally have a unique distribution of ventilation exhaust outlets and intakes, such a monitoring system is limited in its portability and ease of use in other barns. This reduces its effectiveness in developing a statistical database of GHG emissions from different types of barns/farm buildings and under different farm practices. As such, use of a technique in which the farm building is treated as a single source may prove more practical. During periods of comfortable outdoor temperatures in Canada, nonlactating (dry) heifers are usually kept in an outdoor enclosure such as a feedlot or paddock. These animals experience different environmental and physiological conditions from the barn environment which can affect CH4 emissions. The size of these feedlots depends on the physical size of the farm. Some are large, in which case CH4 emissions can be effectively estimated using the tracer technique for individual animals. Others are more compact, have shelters, and are more aerodynamically opaque. For any given year, it is estimated that on average 20% of the dairy herd on a typical Canadian farm are dry (8). This is a significant population, so that a reliable estimate of CH4 emissions under such conditions is necessary. For a spatially integrated estimate of CH4 emissions, SF6 can be released from multiple point sources simulating the distribution of CH4 sources and downwind concentrations of both gases measured in order to estimate the CH4 source strength by the tracer ratio method (9). Although this approach has not been used frequently in determining GHG emissions from agricultural sources, it has seen some use in determining emissions from other sources (e.g., refs 10 and 11) and, overall, has been found to simplify experimental procedures while giving reliable estimates of CH4 emissions (9, 11). In this study we present estimates of CH4 emission 10.1021/es990578c CCC: $19.00
2000 American Chemical Society Published on Web 06/30/2000
from a feedlot and barn housing dairy cattle using the tracer ratio method. The estimated CH4 production from the entire population of dairy cattle in Canada is then given.
Experimental Methods If two gases were released simultaneously from the same source, one of known source strength (SF6) and the other of unknown strength (CH4), and assuming that the turbulent eddies responsible for the diffusion of SF6 are the same as those for CH4, then a simple concentration to source strength ratio method can be used to estimate the unknown source strength
Q(CH4) )
Q(SF6)C(CH4) C(SF6)
(1)
Q(SF6) is the known source strength of SF6, C is the measured downwind concentration above background levels of either the tracer or methane, and Q(CH4) is the unknown source strength for methane. Q can be in m3 of scalar s-1 or kg s-1, depending upon whether C is expressed in volume or mass of tracer gas per volume of air. For cases where the downwind crosswind concentration profile of the tracer is not coincident with that of CH4 or the variability in the C(CH4)/C(SF6) ratio between the different crosswind (lateral) sampling positions is large, then the crosswind integrated concentrations (CIC) can be used (10). In the case where the crosswind concentration profile is measured at more than one height, the CIC can be integrated with respect to height z so that
Q(CH4) )
∫∫C(CH )dy dz ∫∫C(SF )dy dz
Q(SF6)
4
(2)
6
where y is the crosswind displacement. Equation 2 relates the two-dimensional crosswind fractions of the dispersing SF6 and CH4 plumes to their respective source strengths. Turbulent diffusion dominates molecular diffusion in the atmospheric transport of trace gases so that density differences between SF6 (6.25 kg m-3) and CH4 (0.68 kg m-3) are negligible in the dispersion of the two gases in air. SF6 has found widespread use as a passive tracer in studies ranging from the investigation of building ventilation efficiency to the dispersion of pollutants in the atmospheric boundarylayer. Kaharabata et al. (9) briefly summarized the use and effectiveness of SF6 as a tracer for atmospheric pollutants and found that in controlled wind tunnel experiments SF6 acted as a realistic tracer for CO2 under forced convection, irrespective of the tracer’s release configuration that simulated the CO2 area source. During July and August of 1996, concentration profiles of CH4 and SF6 were measured downwind of a typical dairy barn and a feedlot/paddock housing lactating and dry Holstein heifers, respectively. The barn (barn 210) was located at the Greenbelt Experimental Farm of the Centre for Food and Animal Research, Agriculture and Agri-Food Canada, Ottawa, Ontario. The dimensions of the barn were 95 m (l) × 20.4 m (w) × 4.5 m (h). It originally housed 240 lactating cows, but during the experiment only 90 cows were present in the west wing of the barn; each animal had an average weight of ∼600 kg. The west wing, which was used in the experiment described by Kinsman et al. (6), was also used as the CH4 source for this study. The dairy cattle were fed a diet of total mixed ratio (TMR), protein and mineral concentrate at 0700 and 1600 h, and 1-2 kg per cow of long stemmed hay (timothy and alfalfa, 1:1) at 1300 h. Milking took place twice a day at 0530-0800 h and 1545-1730 h. A tower on barn 210 was equipped with a Gill anemometer/
wind vane and a thermocouple to record wind statistics and temperature at a 10 m height. Raw 1 s data were collected by a PC housed in the barn and directly analyzed to give 30 min averages. Adjacent buildings of similar dimensions were located 50-70 m away to the north and south of the barn and 35 m to the west. A pasture of approximately 500 m × 500 m was located immediately to the east. A schematic diagram of the relative positions of the barn and feedlot to the adjacent structures are shown in Figure 1a. In all, six release experiments were carried out at barn 210 over a period of 4 days, 18, 22, 25, and 29 July 1996; all were conducted between 1100 and 1500 h local time. The SF6 tracer was released from 16 points within the barn to simulate the distribution of animals (Figure 1b). Each point source had a source strength of 1.4 × 10-6 m3 SF6 s-1 for the first two experiments and 0.9 × 10-6 m3 SF6 s-1 for all other experiments. The SF6 was delivered by 3.175 mm ID (1/8") Tygon tubing and flow rate regulated using a Dwyer MMA22 air flowmeter (accuracy (4%). To eliminate the hazard of tubing interfering with normal barn cleaning procedures and the movement of animals and feeding machinery, all point sources were placed securely on the floor of the barn. Airflow velocity measured at ≈0.2 m above the floor (Kanomax Climomaster model 6511, hot-wire anemometer) were of the order of 0.1-0.3 m s-1. Velocities measured at ≈1-1.5 m were of the order of 1-3 m s-1 depending upon the measurement location. Air exchange was produced by the ventilation fans with output ranging from 4 to 7 m s-1 for the summer stages. The vertical velocity gradient would be expected to create adequate turbulent mixing and dispersion of the tracer. Air samples were taken outside of the barn using a series of aluminized polyethylene bags of 6 L capacity at the downwind distance of 34.5 m for the S winds prevailing during the experiments. Four crosswind sampling positions centered on the west wing of the barn were spaced evenly, 9 m apart, to sample air at 1 and 3 m heights. The crosswind dimension of the sampling grid was chosen to best capture the diffusing CH4/SF6 plume by considering the building width and estimated plume width at the downwind sampling position while minimizing any potential anomalies in the plume spread due to adjacent buildings. The width of the grid was hoped to encompass ∼50% or more of the plume width. It was estimated by arbitrarily assuming that a standard deviation of the wind direction σθ ≈ 0.349 rad (20°) would prevail, so that plume width σy ≈ σθX + building width. A σθ ≈ 20° was considered to be a typical fluctuation in wind direction during the day. Here X is the downwind distance of the sampling position from tracer source position. This expression was adapted from Pasquill and Smith (12) by assuming that the initial width of the plume was equivalent to the source (building) width. For the barn, the sampling grid width at 34.5 m was ∼48% of the plume spread. The downwind sampling distance was selected considering the crosswind sampling requirements and the influence of nearby buildings on plume dispersion. Since the greatest concentrations of a diffusing trace gas downwind from its source is found near the surface (12), the sampling heights were selected to take advantage of this. The heights were approximately logarithmically spaced and chosen to minimize possible anomalies that might be found in the concentration profiles as a result of the complex aerodynamic flow expected among the structures. Air was sampled via small vacuum pumps at a rate of 0.5 L min-1 for a duration of 10 min for each sampling set. The short sampling duration was used in order to maintain steady wind conditions and minimize significant shifts in wind direction, since this could adversely affect the portion of the SF6/CH4 plume “captured” by the sampling grid. The tracer was released for 15 min prior to the downwind sampling to VOL. 34, NO. 15, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 1. Schematic diagram of (a) the downwind sampling grid positions relative to barn 210 and the feedlot within the farm complex and (b) the SF6 point sources in barn 210 and feedlot. allow for concentrations within the barn to equilibrate. This period was deemed adequate since complete air exchange required ∼75 s under the summer ventilation stage. Upwind samples at 2 m height were also taken to determine background or incoming CH4 concentrations. The collected air samples were analyzed for SF6 and CH4 off-site (within 15 h) using a Rydock Scientific SF6 analyzer and a Shimadzu (model 8AIF) Gas Chromatograph (GC) equipped with a Poropak-Q column, respectively. The SF6 detector was calibrated using SF6/air balanced standards ((5% certified accuracy, Scott Marrin Inc.) with an overall uncertainty of ∼7%. The GC was calibrated using CH4/air balanced standards ((2% certified accuracy, Scott Speciality Gases) and gave an overall uncertainty of less than 6%. The on-line, real-time CH4 and CO2 monitoring system described in ref 6 was still operational during the series of our release experiments and gave continuous 30 min averages 3298
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of emissions by the entire herd. Exhaust and intake ventilation rates and the corresponding CH4 concentrations in the air from these exhaust/intake ports were recorded during our experiments. The rate of CH4 emission from the barn, as estimated from this system, was determined by calculating the total CH4 output rate due to the exhaust fans and subtracting the total incoming CH4 from the intake vents. This gave us the opportunity to compare our estimates with those calculated using the ventilation monitoring system. The feedlot chosen for the experiment was approximately 50 m to the NW of the barn. It had dimensions of 110 m (l) × 33 m (w). It was divided into four quadrants with a central shelter (with no walls) of maximum height 4.0 m giving coverage to approximately 40% of each quadrant. Animal population was fairly evenly divided into the quadrants with a total of 147 heifers. The nearest buildings in the S to NW sectors were 100-200 m away. In the N to SE sector, four
barns similar in dimension to barn 210 were located 18-50 m away. The major axis of both barn 210 and the feedlot was perpendicular to the 145°/325° direction. The prevailing wind directions during the experiments were clockwise from between E and N (i.e., never from the NE sector), which gave a fetch ranging from 500 m to approximately 1.5 km of open fields interspersed with low height barns beyond the cluster of barns and feedlot. The farm complex site was situated on 1130 ha of farm land and open fields, which provided the forage and grains for the animals housed in the research complex. The area surrounding the complex consisted of low rise housing and commercial developments (13). During 1996, operations were coming to an end at the research farm, and the only cattle in the sector where the study took place were the ones housed in the feedlot and barn 210. Seven release experiments were carried out over 2 days, August 6 and 16, 1996; all were conducted between 1000 and 1500 h (local time). The same 16 point SF6 release apparatus was used at the feedlot (see Figure 1b). Each point source had a source strength of 0.7 × 10-6 m3 SF6 s-1 for all seven experiments. To eliminate the danger of animals attempting to ingest the delivery tubing, the hazard of tubing interfering with normal movement and feeding activities of animals, and the potential for blockage/damage of the delivery tubing by trampling, it was necessary to secure all point sources along the upwind perimeter of each feedlot quadrant. Since turbulent mixing increases significantly to the lee of bluff bodies and enhances plume spread development (14, 15), the complex structure of the feedlot was assumed to ensure adequate mixing of the tracer with the emitted CH4. Wind tunnel studies on the pressure distributions along the top and bottom faces of a canopy roof (similar to the shelter of the feedlot) reported by ref 16 showed positive pressure coefficients along the windward half of the roof while the leeward half experienced a mean negative coefficient. Although the flow characteristics under the roof were not discussed in ref 16, we can speculate from the distribution of the pressure coefficients that rolling vortices were being generated under the roof. Such recirculation would rapidly mix any passive scalar emitted or transported into that region and reduce the influence that scalar source height and distribution may have on plume downwash. Air samples were taken using the same sampling procedure and setup/apparatus as in the barn experiments at downwind distances from the edge of the feedlot of 20 m for S prevailing winds (two out of seven experiments) and 14 m for W winds (five out of seven experiments). Different downwind sampling distances were used depending upon prevailing wind direction because of the influence on air flow by nearby barns. The four sampling positions centered on the feedlot were spaced evenly, 23 m apart, for both S and W winds. This resulted in the sampling grid being ∼59% and 90% of the estimated plume width, respectively. SF6 was released for 10 min prior to the downwind sampling to allow turbulent mixing of the tracer to approach a steady-state condition. Upwind samples at 2 m height were also taken to determine background or incoming concentrations of CH4. The collected air samples were analyzed for SF6 and CH4 off-site using the previously described SF6 analyzer and GC, respectively. Cattle in the feedlot were also fed a diet of TMR at 0800 and 1600 h with a constant supply of hay (in the form of large bails in each quadrant).
Results and Discussion There was a relatively large variation in the measured SF6 and above-background CH4 concentrations between the four crosswind sampling positions downwind of barn 210. The variability in above-background concentrations between experiments at each crosswind position was greater toward one end of the sampling grid due to building edge effects
(Figure 2a). Where applicable, the CH4 concentrations will henceforth mean the above-background CH4 concentrations. Wind was generally from directions greater than 145° (the orientation perpendicular to the barn and the crosswind sampling grid). The C(CH4)/C(SF6) ratios at each crosswind sampling positions differed on average from -35% to +42% of the mean C(CH4)/C(SF6) among each experiment at the barn. This difference appeared to be connected to the greater sensitivity in SF6 measurements than CH4. The relatively high background concentration in CH4 (compared to the near negligible background SF6 concentrations) resulted in low CH4 concentrations attributed to the barn; therefore, the differences in CH4 concentrations along the crosswind positions were not as great as that for SF6. Because of this variability, the CH4 source strength was estimated using eq 2. Mean Q(CH4) calculated from the concentration measurements was 6.7 × 10-4 ( 0.9 × 10-4 m3 CH4 s-1. The standard deviation from the mean was ∼34%. The 30 min emissions from the entire herd (corresponding to the sampling periods), calculated from the continuous (24 h) real-time on-line ventilation sampling system (6), gave a mean of 6.3 × 10-4 ( 0.2 × 10-4 m3 CH4 s-1. This is within 6% of our estimate, and this good agreement provided a degree of confidence in our method. The effect of the angle of attack of the mean wind direction to the barn/sampling setup on the calculated source strengths is unknown due to the limited number of experiments that were performed (Table 1). Wind was never perpendicular to the barn/sampling setup (0° angle of attack), as seen in Table 1. Because of the small differences between background and plume concentrations in CH4, it is possible that the different angles of attack by the wind may have transported spatially variable crosswind background CH4 concentrations that were not exactly accounted for. Although Lamb et al. (11) did not specifically examine the effects of wind direction on emission estimates, since sampling was always done along the plume width, their study of colocated and noncollocated SF6/CH4 sources implied that as long as equivalent portions of both plumes were sampled/captured, accurate back-calculation of the source strength could be achieved. In our study, the concentration profile (for both SF6 and CH4), measured when the angle of attack was at a maximum (49°), showed no significant difference from that measured when the angle was at a minimum (5°) (Figure 2b). Furthermore, there was no significant difference between the shapes of the concentration profiles for the two gases under the different wind directions that were observed during the experiments, even though differences were seen between the crosswind concentration ratios. Therefore, for the angles of attack experienced during our sampling periods, the sampling grid was considered effective in capturing the diffusing plumes. For the herd in barn 210, Kinsman et al. (6) observed a strong diurnal trend in CH4 production over a 112 day period that followed the feeding/digesting and resting cycles. Examining the daily emission cycles using the online ventilation monitoring system during our experimental period, as a first approximation, between 2300 and 0700 h, emissions were on average ∼70% of those during the active period of 0800-2200 h. Since our experiments were conducted between the hours of 1100 and 1500 h during the peak emission period, it was assumed that estimated Q(CH4) was representative of the active period in the cycle. The calculated mean emission, considering the diurnal variation, was 576 ( 80 L CH4 d-1 cow-1. This is within the estimated range of CH4 emissions per animal uncorrected for manure contribution made by ref 6 (436-721 L CH4 d-1 cow-1) and comparable to that measured by ref 7 (521-530 L CH4 d-1 cow-1). Manure in the barn is a potential source for CH4. The contribution to the measured CH4 by manure on the barn VOL. 34, NO. 15, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 2. The above-background concentration profiles of 1 SD about the mean for all experiments at the barn (a) and for all 14 m downwind experiments at the feedlot (c); profiles measured during maximum and minimum angles of attack by the wind at the barn (b) and feedlot (d); values in parentheses are angles of attack in degrees. Maximum angle of attack at the feedlot occurred at the 14 m downwind position and the minimum angle of attack occurred at the 20 m downwind position.
TABLE 1. Calculated Source Strength from Barn Using Ventilation Monitoring System (VMS) and Tracer Gas Experiments Q(CH4) (10-4 m3 CH4 s-1) expt no.
VMS
Q(CH4)
angle of attack
1 2 3 4 5 6 mean SD
6.47 6.52 6.62 5.83 6.48 6.36 6.38 0.26
4.47 8.37 6.12 6.01 4.3 10.75 6.67 2.26
+35° +49° +21° +39° +28° -5°
TABLE 2. Calculated Source Strength Q(CH4) from the Feedlota Q(CH4) (10-4 m3 CH4 s-1) expt no. 1 2 3 4 5 6 7 mean SD
20 m
14 m
20 m
14 m
+12° +12°
17.48 13.2
15.34 3.02
angle of attack
12.14 22.31 7.37 7.73 9.54 11.82 6.16
+46° +46° +21° +21° +60°
a Combined mean at 14 and 20 m ) 12.8 × 10-4 m3 CH s-1, SD ) 4 5.0 × 10-4 m3 CH4 s-1.
floor, in the gutters, and in the holding tank below the barn was estimated at 6% for barn 210 (6). Although only 90 animals were present during this experiment as opposed to the 118 when the study in ref 6 was performed, the proportional contribution by manure should remain the same. Assuming this to be true, our estimated CH4 emissions using the tracer technique from only the animals was 542 ( 75 L CH4 d-1 cow-1. Propagating the errors associated with the SF6 source strength, and the SF6 and CH4 concentrations throughout the calculations, and considering the standard error in the estimate, the overall uncertainty in the estimate was ∼30%. For the feedlot experiments, there was a greater variation in the measured SF6 and CH4 concentrations between the four crosswind sampling positions than at the barn. Higher concentrations were measured toward one end of the sampling grid than the other due to the angle of attack by the wind (Figure 2c). The concentration ratios at each crosswind sampling position differed on average from -40% to +65% of the mean C(CH4)/C(SF6) among each experiment at the feedlot. As with the barn experiments, this variability was connected to the different sensitivities in SF6 and CH4 measurements, and the CH4 source strength was also estimated using eq 2. The calculated mean emission rate from the feedlot-housed cattle at the combined 14 and 20 m downwind positions was 12.8 × 10-4 ( 1.9 × 10-4 m3 CH4 s-1 (Table 2). The standard deviation from the mean was of the order of 39% and of similar magnitude to that of the barn experiments. The influence of the angle of attack by the wind on the estimated source strengths is again unknown due to the limited number of experiments carried out (Table 2). The concentration profile (for both SF6 and CH4), measured when the angle of attack was at a maximum (60°), was significantly different from that measured when the angle was at a minimum (12°) (Figure 2d). However, there was no significant difference between the shapes of the concentration profiles for the two gases during each particular wind direction indicated above nor during any given experiment.
The differences between the concentration ratios at each crosswind position did not affect the overall similarity between the SF6 and CH4 concentration profiles. Therefore, for the angles of attack experienced during our sampling periods at the feedlot, the sampling grid was considered effective in capturing the diffusing plumes. Since nonlactating cows from barn 210 populated the feedlot and similar feeding schedules were maintained, the observed diurnal trend in CH4 emissions in the barn (6) was assumed to hold for these animals as well and similar approximations to the trend described above for barn emissions were made. The calculated mean emission was 678 ( 101 L CH4 d-1 cow-1. Manure in the feedlot/paddock is also a potential source of CH4. It has been estimated that up to 100 µg CH4 min-1 were being emitted by cow pies produced by free ranging cattle during summer months (17). The emission range depended upon the degree of desiccation experienced by the cow pie. Since no CH4 flux measurements were available from the manure in the feedlot, as a first approximation we assumed a mean emission of 50 µg CH4 min-1, and a nondesiccated surface area of 0.05 m2 (diameter of 0.25 m) per cow pie. The emission from manure assuming total surface coverage of the feedlot floor (3360 m2) would then be approximately 4.8 kg CH4 d-1 ≈ 7.1 m3 CH4 d-1. This is approximately 7% of the calculated emissions. This is not an unreasonable assumption since it is of the same order of magnitude as the contribution estimated in ref 6. The floor of the feedlot was always completely covered with manure since minimal manure management was practiced at the feedlot. Applying this correction, due to the contribution by manure to the overall CH4 production, gave an estimated 631 ( 94 L CH4 d-1 cow-1. Overall uncertainty after propagating all errors was ∼30%. This estimate for the feedlot cattle is roughly 16% greater than that for the barn population; however, there was no significant difference (at all R e 0.1 levels) between the two estimated emissions. No significant difference was found as well (for R e 0.05 levels) between the estimated emissions from the feedlot and the estimate made using the barn ventilation monitoring system. Our value is also within the range reported by ref 6. Dry heifers are known to produce less CH4 than lactating cows (7). However, greater CH4 emissions may have occurred because of the greater intake of hay which has a high cell wall fiber content (1) and the influence of outdoor conditions on the physiology of the cows (which were predominantly in the nonsheltered areas of the feedlot). Using our method, there was less variation in the emissions from the barn than from the feedlot (Tables 1 and 2). This suggests that emissions may have been more intermittent (as in natural systems) from the feedlot than from the barn. The barn ventilation system would tend to mix the internal air resulting in a more spatially homogeneous and temporally steady (relative to our sampling periods) concentration of CH4 in the ventilated air. The estimated emissions listed in Table 2 for the 14 m sampling position are for observations made between 10 and 12 h local time (experiments 3-7). They can be considered as a continuous record of emission from feedlot cows during the 2 h period and indicate the fluctuations in emission over that period. Taking experiments 5-7 at the feedlot (Table 2) which gave emission estimates that were relatively steady compared to experiments 3 and 4 (which may have coincided with above average herd eruction), the estimated emission from each cow would be ∼ 404 L CH4 d-1 cow-1 (considering the diurnal trend and removing the contribution from manure). This is ∼ 75% of the mean emission from the barn population. Half of our experiments may have coincided with episodes of increased eruction by either the entire feedlot population or by a significant subset resulting in the daily emission rates being possibly overestimated. Sampling at the feedlot did VOL. 34, NO. 15, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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not coincide with feeding times; however, there was a constant supply of hay resulting in animals intermittently eating. A greater number of sampling periods during each experimental day may have better identified the intermittent fluctuation in emissions resulting in improved daily emission estimates. Although the estimated contribution by manure in the feedlot was comparable to that for the barn, it may have been significantly underestimated. If the assumed contribution by manure was increased by a factor of 2, then the above estimate based on experiments 5-7 would be ∼375 L CH4 d-1 cow-1. To determine CH4 emissions from the manure, the experiment can be performed without the cattle population in the feedlot. Although the magnitude of emissions per cow may be high compared to nondairy cattle (240-290 L CH4 d-1 cow-1 (1)), it is in proportion to the relative size difference between our population of cows (weight ∼ 600 kg) and that of nondairy cows in North America (∼330 kg (1)). Based on the above analysis, we can consider that the range of emissions from the feedlot cows during our experiment was 375-630 L CH4 d-1 cow-1. Provided that both the SF6 and CH4 plumes were coincident and “captured” by the downwind sampling grid, no meteorological observations were necessary in order to make a good approximation of the true source strength. The tracer ratio method provided a reliable method of estimating CH4 emissions from the barn housing dairy cattle under prevailing atmospheric conditions. The technique was also sensitive enough to capture the intermittent fluctuations in emissions from the feedlot housed cattle. One serious limitation of the method occurs when wind velocities are low such as during stable nighttime conditions. This results in an underdeveloped SF6/CH4 plume as found in a manure tank study by Kaharabata et al. (9). To overcome this limitation, experiments can be conducted during “windy” nights with adequate turbulent mixing, usually found when weather systems are approaching. The experiment can also be halted during periods of low wind velocities to avoid sampling poorly dispersed or developed plumes. The diurnal trend in emissions can be measured by following the above criteria during the nighttime observations. Dairy livestock inventory figures (18) were used to calculate the annual methane emissions for Canada. There was a large uncertainty in the typical daily emission from animals in the feedlot as a result of the unknown contribution to emissions by the manure on the feedlot floor, the possibility that sampling occurred during periods of enhanced eruction, and the possibly greater emission of CH4 due to the continuous consumption of hay. We therefore assumed that the emission rate of 542 ((30%) L CH4 d-1 cow-1, estimated for the barn population, was applicable to the entire population of dairy cattle housed in both barns and feedlots. This value was within the range that was estimated to have occurred at the feedlot. The total Canadian emission was then estimated at ∼0.245 Tg CH4 yr-1. Our uncertainty of (30% in the daily emissions can be considered as a minimum uncertainty for the national emission estimate. Since differences in the size (age) of the animal, feed quality, and climate (season) has significant effects on the production of CH4 by the cow (1), we cannot define a possible range in the uncertainty without additional observations across the different agroecozones of Canada. However, by taking the lower emissions of beef steers as a reference point, we might conclude that the uncertainty has a possible upper bound of (50%. Our annual emission is comparable to the 0.211 Tg CH4 yr-1 estimated by ref 19 for similar sources and accounts for approximately 32% of the total emission by domestic animals. For all domestic animal sources in Canada both refs 19 and 20 arrived at estimates of 0.655 and 0.668 Tg CH4 yr-1, respectively. 3302
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Although only a limited set of experiments were conducted, the relative success of the method recommends it as a potentially valuable tool in estimating GHG emissions from structures embedded in complex aerodynamic flows. The ease of deployment with respect to time compared to other methods, the economy of materials and instruments used, and the portability of the method make its use attractive especially when a reliable database of GHG emission strengths across different regions is needed for country-wide budget estimates. This is necessary if national emission figures are to avoid the inherent dangers of extrapolating from too small a number of local measurements.
Acknowledgments We would like to thank Ms. L. Wittebol who assisted in data collection and Messrs. H. Jackson and R. Kinsman of the Centre for Food and Animal Research, Agriculture and AgriFood Canada, for the unlimited use of barn 210 and its facilities. The project was funded by Agriculture and AgriFood Canada under the Green Plan Initiative.
Literature Cited (1) Johnson K. A.; Johnson D. E. J. An. Sci. 1995, 73, 2483. (2) Johnson K.; Huyler M.; Westberg H.; Lamb B.; Zimmerman P. Environ. Sci. Technol. 1994, 28, 359. (3) Lassey K. R.; Ulyatt M. J.; Martin R. J.; Walker C. F.; Shelton I. D. Atmos. Environ. 1997, 31, 2905. (4) McCaughey W. P.; Wittenberg K.; Corrigan D. Can. J. Anim. Sci. 1997, 77, 519. (5) Harper L. A.; Denmead O. T.; Freney J. R. Proceedings of the American Society of Agronomy, International Winter Meeting, Chicago Il; 1993. (6) Kinsman R.; Sauer F. D.; Jackson H. A.; Wolynetz M. S. J. Dairy Sci. 1995, 78, 2760. (7) Marik T.; Levin I. Global Biogeochem. Cycles 1996, 10, 413. (8) Hatcher, D. Programme d’analyse des troupeaux laitiers du Que´bec (PATLQ) Herd Summary Report for 1996; McGill University: Ste-Anne-de-Bellevue, Quebec, 1997. (9) Kaharabata S. K.; Schuepp P. H.; Desjardins R. L. Global Biogeochem. Cycles 1998, 12, 545. (10) Lamb B.; Westberg H.; Allwine G. Atmos. Environ. 1986, 20, 1. (11) Lamb B. K.; McManus J. B.; Shorter J. H.; Kolb C. E.; Mosher B.; Harriss R. C.; Allwine E.; Blaha D.; Howard T.; Guenther A.; Lott R. A.; Siverson R.; Westberg H.; Zimmerman P. Environ. Sci. Technol. 1995, 29, 1468. (12) Pasquill F.; Smith F. B. Atmospheric Diffusion; John Wiley & Sons: New York, 1983; pp 437. (13) Agriculture Canada. Animal Research Centre Research Farm; Ontario Region Research Branch: Ottawa, 1981. (14) Huber A. H. Atmos. Environ. 1991, 25, 1237. (15) Hoydysh W. G.; Dabberdt W. F. J. Wind Eng. Ind. Aerodyn. 1992, 41-44, 2785. (16) Ginger J. D.; Letchford C. W. J. Wind Eng. Ind. Aerodyn. 1992, 41-44, 1739. (17) Williams, D. J. Chemosphere 1993, 26, 179. (18) Statistics Canada. Livestock statistics as of July 1996; Statistics Canada Report, Cat 23-603-UPE; Ottawa, 1996. (19) Jaques A. P. Canada’s greenhouse gas emissions: estimates for 1990; Environment Canada Report, EPS 5/AP/4; Ottawa, 1992. (20) Specialists in Energy, Nuclear, and Environmental Sciences (SENES) Consultants Ltd. Study of greenhouse gas emissions from nonfossil fuel sources; Environment Canada Report 31443; Ottawa, 1994.
Received for review May 24, 1999. Revised manuscript received April 26, 2000. Accepted May 1, 2000. ES990578C
