Modeling ammonia emissions from broiler litter with a dynamic flow ...
An ASABE Meeting Presentation Paper Number: 074090
Modeling ammonia emissions from broiler litter with a dynamic flow-through chamber system Zifei Liu, Ph.D. Student, Graduate Research Assistant Lingjuan Wang, Ph.D., Assistant professor David B. Beasley, Ph.D., P.E., Professor Department of Biological and Agricultural Engineering, North Carolina State University, Raleigh, NC 27695-7625
Edgar O. Oviedo, DVM, Ph. D., Assistant professor Department of Poultry Science, North Carolina State University, Raleigh, NC 27695-7608
Written for presentation at the 2007 ASABE Annual International Meeting Sponsored by ASABE Minneapolis Convention Center Minneapolis, Minnesota 17 - 20 June 2007 Abstract. This paper reports some preliminary efforts to evaluate effects of various influencing factors on ammonia emissions from broiler (meat chicken) houses, and to develop mathematical emission model(s) so that ammonia emissions can be predicted under given conditions. A statistical model was developed based on measurements of ammonia emissions from broiler litter in a dynamic flow-through chamber system. The model inputs include the litter total kjeldahl nitrogen (TKN) content, litter pH value, litter moisture content, litter carbon content, the mass transfer coefficient and ventilation rate. Under the designed operating condition, the mass transfer coefficient has been estimated to have an average value of 8.59 m/h. The model results showed that ammonia emission flux increased with increasing litter TKN content, pH, litter moisture content, mass transfer coefficient and ventilation rate (air flow rate), and decreased with increasing litter carbon content. The model was most sensitive to litter pH value than to other input variables. Keywords. Ammonia, Emission model, Broiler litter, Dynamic flow-through chamber
The authors are solely responsible for the content of this technical presentation. The technical presentation does not necessarily reflect the official position of the American Society of Agricultural and Biological Engineers (ASABE), and its printing and distribution does not constitute an endorsement of views which may be expressed. Technical presentations are not subject to the formal peer review process by ASABE editorial committees; therefore, they are not to be presented as refereed publications. Citation of this work should state that it is from an ASABE meeting paper. EXAMPLE: Author's Last Name, Initials. 2007. Title of Presentation. ASABE Paper No. 07xxxx. St. Joseph, Mich.: ASABE. For information about securing permission to reprint or reproduce a technical presentation, please contact ASABE at [email protected] or 269-429-0300 (2950 Niles Road, St. Joseph, MI 49085-9659 USA).
Introduction Ammonia is considered the most harmful gas in broiler chicken housing (Carlile, 1984). The importance of ammonia emissions from animal feeding operations (AFOs) has been well recognized (Van der Hoek, 1991; Zhao et al., 1994; Sutton et al., 1995; Aneja et al., 2000; Arogo et al., 2001; Hutchings et al., 2001; Lee and Park, 2002; Battye et al., 2003; Hyde et al., 2003; Xin et al., 2003; Wheeler et al., 2003; Liang et al., 2003; and Gates et al., 2004). However, the contributions of ammonia emission from large poultry operations to the national emission inventory have not been properly documented. Accurate estimation of ammonia emission rate from individual operations or sources is important and yet a challenging task for both regulatory agencies and animal producers. Numerous studies have been reported throughout the world on ammonia emissions from broiler houses, and wide variations have been found among different studies. The differences in ammonia emission fluxes from broiler houses under different conditions have been reported as high as 55 fold (Redwine et al., 2002). Variations in ammonia emissions result from the dependence of ammonia emissions on seasonal and regional conditions, house design, and management practices. Broiler chickens are normally raised on litter made up of wheat straw or wood shavings above an earthen floor. The litter serves as manure absorbance. The mixture of litter and manure represents the most significant source of ammonia emissions. The mechanisms related to ammonia emissions from manure involve many processes and have been summarized by Ni (1999). Theoretically, the processes involved in ammonia emissions from litter based manure include conversion of uric acid to urea, hydrolysis of urea, enzymatic and microbial generation of ammonia, partitioning between the adsorbed and dissolved phase ammonia, the chemistry of ammonia in aqueous solution, partitioning between solid/aqueous phase and gaseous phase ammonia, and the convective mass transfer of ammonia gas from the surface into the free air stream. Factors that may influence ammonia emissions from broiler litter include: air and litter temperature, ventilation rate, air velocity, litter pH, litter nitrogen content, and litter moisture content. Determining ammonia emissions is both expensive and difficult using currently available technologies for measuring ammonia concentrations and ventilation airflow rates under commercial broiler house conditions. In order to improve the accuracy and simplicity of estimating ammonia emissions, development of emission models is desired. Emission models allow users to calculate site-specific emissions, using the local design and operating parameters. Emission models can also be used to quantify and evaluate the effectiveness of various emission control strategies. Evaluating effects of these control strategies on emissions from livestock buildings for full-scale operations can be quite expensive and labor intensive using current measurement methodologies (NRC, 2003). The influences of management factors and litter conditions on ammonia emission have been documented (Nicholson et al., 2004; Redwine et al., 2002; Reece et al., 1985; Elliot and Collins, 1982; Elwinger and Svensson, 1996; Carr et al. 1990; Brewer and Costello, 1999), but they have not been adequately incorporated into current emission models. Much work remains to be done because of the number of variables in practice. Further evaluation of these variables is needed for enhanced understanding of the wide variation in ammonia emission rates. The research objectives of this study are to evaluate the effects of various influencing factors on ammonia emissions from broiler litter, and to develop a mathematical emission model so that ammonia emissions can be predicted under given conditions.
2
Experimental setup Dynamic flow-through chamber system Due to high uncertainties in measuring ammonia emissions on the farm scale and bio-security limitations to accessing a commercial farm, this research was conducted in well-controlled laboratory facilities. A dynamic flow-through chamber system was designed for this ammonia emissions model development study to evaluate model components individually or in designed combinations. The dynamic flow-through chamber system is shown in Figure 1. The chamber body has a cylindrical shape with bottom diameter (inside measurements) of 40.0 cm (15.75 inches) and height of 39.4 cm (15.5 inches). Broiler litter samples were put on the bottom of the chamber and a vacuum pump was used to draw air through the chamber at designed flow rate via flow controllers (Gilmont Shielded Industrial Flow meter, accuracy ±5%). Before entering the chamber, ambient air passed through an activated carbon filter so that background ammonia was removed. A motor driven stainless steel impeller mixed the air inside the chamber and promoted desired convective conditions. The dynamic chamber system, with the continuous stirring provided by the impeller, met the necessary criteria for performance as a continuously stirred tank reactor (CSTR) (Aneja, 1976). The entire chamber body was made of stainless steel, and Teflon tubing was used to minimize the loss of ammonia. Ammonia concentration in the chamber was measured by a Thermo Environmental Instruments (TEI) chemiluminescence ammonia analyzer (Model 17C). Vent
Motor
Ambient air
Flow controller
Pump
Impeller
Carbon filter
NH3 free air
Flux Chamber NH3
The NH3 analyzer
Litter
Data logger Data logger
ECH2O moisture sensor
Figure 1. The dynamic flow-through chamber system for measuring ammonia emission from broiler litter The ammonia fluxes from the litter surface inside the chamber can be calculated using the following equation: d[C]/dt = QC0/V + JA/V – QC/V
(1)
In which, C : ammonia mass concentration in the chamber, mg m-3; Q : flow rate of the carrier gas through the chamber, m3 h-1; C0: ammonia concentration in the carrier gas stream, mg m-3;
3
V : volume of the chamber, m3; J : ammonia emission flux, mg m-2 h-1; A: chamber bottom surface area, m2. Since background ammonia was removed from the carrier gas, C0=0. At steady state, d[C]/dt=0. Therefore, the ammonia emission flux J can be obtained from the following equation: (2)
J = (Q/A) Cg, chamber In which, Cg, chamber is the ammonia concentration in the chamber at steady state.
The dynamic flow-through chamber was built to simulate the convective conditions in an actual broiler house. The ventilation rate and air velocity at the litter surface has been recognized as two important factors that affect ammonia emissions. Based on the ventilation rates reported by Lacey et al. (2003) and Guiziou & Beline (2005), the air residence time has been estimated in the range of 59 to 191 seconds for a tunnel-ventilated broiler house in Texas and in the range of 260 to 36000 seconds for a broiler house in France. The ventilation rates of the chamber (air flow rates through the chamber) in this reported preliminary study were set from 10.0 to 74.0L/min, which caused residence time of air in the chamber to be 40 to 300 seconds. Although the ventilation rates can vary widely in practice, Brewer and Costello (1999) reported that the mean air speed at a 25 cm height is 0.24 m/s with a standard deviation of 0.14 m/s in a typical broiler house. In a tunnel-ventilated broiler house, air velocity at the litter surface is believed to be higher, but no reported data has been found. In this reported study, a hotwire anemometer was placed at about 2.5 cm height above the litter surface in the chamber to measure air velocity profile in the chamber. It was found that, the RPM of the stirring impeller was the only significant factor that determines the air velocity at the litter surface when the ventilation rate (air flow rate) of chamber was less than or equal to 74 L/min. Therefore, in the chamber system, ventilation rate and air velocity at the litter surface can be set independently. At 110 RPM, the air velocity at the litter surface was measured in the range from 0.10 to 0.99 m/s at various distances from the center to the wall of the chamber. The wind profile in the chamber is shown in Table 1. Table 1 Air velocity at the litter surface in the chamber (RPM=110) Distance from center of the chamber (inches)
0
2.5
5.0
7.5
10.0
12.5
15.0
Air velocity (m/s)
0.10
0.37
0.64
0.80
0.93
0.99
0.95
Litter samples and ammonia measurements Litter samples at various ages were taken from three commercial broiler farms in North Carolina. These broiler farms had similar management practices: the grow-out period was 56-60 days (per flock) with two weeks of clean-out time. The litter material used by these farms consisted of wood shavings. Each litter sample was randomly taken from multiple locations of a broiler house during the clean-out period. The samples were stored in airtight buckets in an airconditioned laboratory with temperature around 22 oC. For each test, 3000 gram litter samples were put on the chamber bottom with a depth of about 5 cm. The ammonia analyzer measured ammonia concentrations in the chamber continuously and a HOBO data logger was used to record the ammonia analyzer measurements at oneminute intervals. The ammonia concentration in chamber was defined as steady state once the variation in concentration was less than 0.5 ppm in ten minutes. Each measurement of steady-
4
state ammonia concentration was obtained after the litter was remixed and the chamber reached a new steady state. For each test, three replicate measurements were taken. 100 gram litter samples were taken for solids analyses before and after each test. The solids analyses include total kjeldahl nitrogen (TKN), total ammoniac nitrogen content (TAN), moisture content, pH, total nitrogen content and total carbon content. The solids analyses were conducted in the Environmental Analysis Laboratory of in the Department of Biological and Agricultural Engineering (BAE) at NC State University following EPA standard methods. Statistic analysis indicated that there were no significant differences between the analysis results before and after each test. An ECH2O moisture sensor (EC5) was used to monitor litter moisture contents continuously which also confirmed that moisture remained relatively constant during the tests. The room temperatures were kept at 22 oC during all of the tests.
Model structure Although different theories of mass transfer have been used in the models of ammonia emissions (Hashimoto and Ludington, 1971; Olesen and Sommer, 1993), the resulting mass transfer equations were often in a similar form. The general mass transfer flux equation can be expressed as, J = Km (Cg, 0- Cg, ∞)
(3)
In which, J: emission flux, mgN m-2 h-1; Km: mass transfer coefficient, m h-1; Cg, 0: gas phase ammonia concentration at the emission surface, mgN m-3; Cg, ∞: concentration of gas phase ammonia in the free air stream, mgN m-3. Most of the published ammonia emission models use this equation as the core equation (Ni, 1998), and sub-models were developed to serve this core. In an open field, Cg, ∞ is often very low and can be neglected. In animal houses, this concentration can be too high to be negligible, and it is dependent on the ventilation rate. In the dynamic flow-through chamber system, the general mass transfer flux equation can be expressed as, J = Km (Cg, 0- Cg, chamber)
(4)
Combining equations 4 and 2, which was derived from mass balance approach, the following equation is obtained, (Q/A) Cg, chamber = Km (Cg, 0- Cg, chamber)
(5)
Cg, chamber = Km(Km+Q/A)-1 Cg, 0
(6)
So,
Combining equations 6 and 2, the core emission flux model is obtained as follows: J = ((Q/A)-1+Km-1)-1Cg, 0
(7)
Emission fluxes J can be expressed by multiplying Cg, 0 with an overall emission coefficient Ke. J = Ke * Cg, 0
(8)
In this case, the emission coefficient Ke has units of velocity, and it is determined by ventilation rate (air flow rate) Q, emission surface area A and the mass transfer coefficient Km as following.
5
Ke = [(Q/A)-1 + Km -1]-1
(9)
Influence of ventilation rate Q and the mass transfer coefficient Km on emission flux depends on the relative magnitude of Q/A and Km, which is summarized in Table 2. Table 2 Influence of the relative magnitude of Q/A and Km Controlling factor When Q/A >> Km
Ke ≈ Km
When Q/A > Km, therefore, Km was the controlling factor, and ammonia flux was more sensitive to Km than to Q as shown in Table 4. Relative sensitivity of litter carbon content is negative because ammonia flux was negatively related with litter carbon content. Table 4 Relative sensitivity Sr for ammonia emission flux from litter with respect to litter TKN content, litter pH, litter moisture content, litter total carbon content, the mass transfer coefficient Km and the ventilation rate Q TKN content Range (μg/g) 32000-34000 34000-36000 36000-38000 38000-40000 40000-42000 42000-44000 44000-46000 46000-48000 48000-50000 50000-52000 52000-54000
pH Sr 1.73 1.45 1.24 1.08 0.96 0.86 0.78 0.71 0.65 0.60 0.56
Range 6.2-6.4 6.4-6.6 6.6-6.8 6.8-7.0 7.0-7.2 7.2-7.4 7.4-7.6 7.6-7.8 7.8-8.0 8.0-8.2 8.2-8.4
Sr 2.34 3.32 4.54 5.95 7.43 8.85 10.05 10.92 11.34 11.21 10.41
Moisture content Range (%) Sr 15-20 0.69 20-25 0.57 25-30 0.49 30-35 0.42 35-40 0.37 40-45 0.33 45-50 0.28 50-55 0.25 55-60 0.21 60-65 0.18 65-70 0.14
11
54000-56000 56000-58000 58000-60000
0.52 0.49 0.46
Total carbon content Range (%) Sr 28-30 -0.30 30-32 -0.36 32-34 -0.42 34-36 -0.49 36-38 -0.58 38-40 -0.67 40-42 -0.78 42-44 -0.91 44-46 -1.05
8.4-8.6 8.6-8.8 8.8-9.0 Km Range (m/h) 2-4 4-6 6-8 8-10 10-12 12-14 14-16 16-18 18-20
8.79 6.22 2.73
70-75 75-80 80-85
0.11 0.07 0.04
Sr 0.99 0.99 0.98 0.97 0.97 0.96 0.96 0.95 0.94
Q Range (L/min) 1-5 5-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80
Sr 0.39 0.14 0.08 0.04 0.03 0.02 0.02 0.02 0.01
Note: Litter TKN content, litter moisture content and total carbon content are all expressed on a dry basis.
Conclusion A statistical model was developed to estimate ammonia emission flux from broiler litter based on experimental results from a dynamic flow-through chamber system. The model inputs include the litter TKN content, litter pH value, litter moisture content, litter carbon content, the mass transfer coefficient Km and ventilation rate Q. Under the designed operating condition, the mass transfer coefficient Km has been estimated to have an average value of 8.59 m/h. The model results showed that ammonia emission flux increased with litter increasing TKN content, pH, litter moisture content, mass transfer coefficient and ventilation rate, and decreased with increasing litter carbon content. The model was most sensitive to litter pH value than to other input variables. Experiments are continuing in an effort to develop a model to estimate the mass transfer coefficient Km at various surface air velocities. The future work will also include model validation with more data from laboratory experiments, as well as field measurements.
References Aneja, V.P., 1976. Dynamic studies of ammonia uptake by selected plant species under flow reactor conditions. Ph. D. Thesis, NC State University. Raleigh, NC, p. 216. Aneja, V.P., J.P. Chauhan and J.T. Walker. 2000. Characterization of atmospheric ammonia emissions from swine waste storage and treatment lagoons. Journal of Geophysical Research 105, 11535-11545. Arogo, J. P. W. Westerman, A. J. Heber, W. P. Robarge and J. J. Classen. 2001. Ammonia in animal production. Paper No. 01-4089, present at the 2001 ASAE Annual International Meeting in Sacramento, CA, St. Joseph, MI. Battye, W., V. P. Aneja and P. A. Roelle. 2003. Evaluation and improvement of ammonia emissions inventories. Atmospheric Environment 37(27): 3873-3883. Carlile, F. S. 1984. Ammonia in poultry houses: A literature review. World’s Poultry Science J. 40: 99–113.
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Carr, L.E. F. W. Wheaton and L. W. Douglas. 1990. Empirical models to determine ammonia concentrations from broiler chicken litter. Transaction of the ASAE, Vol. 33(4): 13371342 Brewer, S.K. and T.A. Costello. 1999. In situ measurement of ammonia volatilization from broiler litter using an enclosed air chamber. Transaction of ASAE, Vol. 42(5), 1415-1422. Elliott, H.A. and N. E. Collins. 1982. Factors affecting ammonia release in broiler houses. Trans. ASAE 25(2): 413–424. Elwinger K. and L. Svensson. 1996. Effect of dietary protein content, litter and drinker types on ammonia emission from broiler house. Journal of Agricultural Engineering Research, 64, 197-208 Gates, R. S., K. D. Casey, E. F. Wheeler, H. Xin, A. J. Pescatore, J. L. Zajaczkowski, J. R. Bicudo, P. A. Topper, Y. Liang and M. Ford. 2004. Broiler house ammonia emissions: U.S. baseline data. Proc of Multi-State Poultry Feeding and Nutrition and Health and Management Conference and Degussa Corporation's Technical Symposium. May 25-27, 2004. Indianapolis, IN. Available at http://www.bae.uky.edu/ifafs/timeline.htm. Guiziou, F. and F. Beline. 2005. In situ measurement of ammonia and green house gas emissions from broiler houses in France. Bioresource Technology, 96, 203-207. Hashimoto A G and D. C. Ludington. 1971. Ammonia desorption from concentrated chicken manure slurries. Livestock Waste Management and Pollution Abatement, Proceedings of the International Symposium on Livestock Wastes. St. Joseph, MI: ASAE, , 117-121. Hutchings, N. J., S. G. Sommer, J. M. Andersen and W. A. H. Asman. 2001. A detailed ammonia emission inventory for Denmark. Atmospheric Environment 35(11): 1959-1968. Hyde, B. P., O. T. Carton, P. O'Toole and T. H. Misselbrook. 2003. A new inventory of ammonia emissions from Irish agriculture. Atmospheric Environment 37(1): 55-62. Kamin, H., J.C. Barber, S.I. Brown, C.C. Delwiche, D. Grosjean, J.M. Hales, J.L.W. Knapp, E.R. Lemon, C.S. Martens, A.H. Niden,; R.P. Wilson and J.A. Frazier. 1979. Ammonia. Baltimore: University Park Press Lacey, R.E., J.S. Redwine and C.B. Parnell, Jr. 2003. Particulate matter and ammonia emission factors for tunnel-ventilated broiler production houses in the Southern U.S. Transactions of ASAE, Vol. 46(4): 1203-1214. Lee, Y. H. and S. U. Park. 2002. Estimation of ammonia emission in South Korea. Water Air and Soil Pollution 135(1-4): 23-37. Liang Y., H. Xin, A. Tanaka, S. H. Lee, H. Li, E. F. Wheeler, R. S. Gates, J. S. Zajaczkowski, P. Topper and K. D. Casey. 2003. Ammonia emissions from U.S. poultry houses: Part II Layer houses. Pp: 147-158, Proceedings of Third International Conference on Air Pollution from Agricultural Operations, Raleigh, NC. Liang, Z. S., P. W. Westman, J. Arogo. 2002. Modeling ammonia emission from swine anaerobic lagoons. Transaction of ASAE, Vol. 45(3), 787-798. National Research Council (NRC). 2003. Air emissions from Animal Feeding Operations: Current Knowledge, Future Needs. National Academies Press, Washington, DC. Ni, J. 1999. Mechanistic models of ammonia release from liquid manure: a review. J. Agric. Engng Res. 72, 1-17. Nicholson, F.A., B. J. Chambers, A. W. Walker. 2004. Ammonia emissions from broiler litter and laying hen manure management systems, Biosystems Engineering, 89(2), 175-185. Olesen J E and S.G. Sommer. 1993. Modelling e¤ects of wind speed and surface cover on ammonia volatilization from stored pig slurry. Atmospheric Environment. Part A. General Topics, 27(16), 2567-2574. 13
Redwine, J.S., R.E. Lacey, S. Mukhtar, and J.B. Carey. 2002. Concentration and emissions of ammonia and particulate matter in tunnel-ventilated broiler houses under summer conditions in Texas. Transactions of ASAE, Vol. 45(4): 1101-1109. Reece, F.N., B. D. Lott and B. J. Bates. 1985. The performance of a computerized system for control of broiler-house environment. Poult. Sci. 64:261-265 Sutton, M. A., C. J. Place, M. Eager, D. Fowler and R. I. Smith. 1995. Assessment of the magnitude of ammonia emissions in the United Kingdom. Atmospheric Environment 29(12): 1393-1411. Svensson, L and M. Ferm. 1993. Mass transfer coefficient and equilibrium concentration as key factors in a new approach to estimate ammonia emission from livestock manure, Joournal of Agricultural Engineering Research. 56, 1-11. Van der Hoek, K. W. 1991. Emission factors for ammonia in The Netherlands. IIASA Workshop on Ammonia Emissions in Europe: Emission Factors and Abatement Costs, Luxemburg, Austria. Welty J R., C. E. Wicks, R. E. Wilson. 1984. Fundamentals of Momentum, Heat, and Mass Transfer. 3 edn. New York: Wiley. Wheeler, E. F., K. D. Casey, J. D. Zajaczkowski, P. A. Topper, R. S. Gates, H. Xin, Y. Liang and A. Tanaka. 2003. Ammonia emissions from U.S. poultry houses: Part III - Broiler houses. Pp: 159-166, Proceedings of Third International Conference on Air Pollution from Agricultural Operations, Raleigh, NC. Xin, H., Y. Liang, A. Tanaka, R. S. Gates, E. F. Wheeler, K. D. Casey, A. J. Heber, J. Ni and H. Li. 2003. Ammonia emissions from U.S. poultry houses: Part I – Measurement system and techniques. Pp: 106-115, Proceedings of Third International Conference on Air Pollution from Agricultural Operations, Raleigh, NC. Zerihun, D., J. Feyen, and J. M. Reddy. 1996. Sensitivity analysis of furrow–irrigation performance parameters. J. Irrigation and Drainage Eng. 122(1): 49–57 Zhang R. H.1992. Degradation of swine manure and a computer model for predicting the desorption rate of ammonia from an under-floor pit. PhD dissertation. Library, University of Illinois, Urbana IL. Zhao, D. W. and A. P. Wang. 1994. Estimation of anthropogenic ammonia emissions in Asia. Atmospheric Environment 28(4): 689-694.
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Modeling ammonia emissions from broiler litter with a dynamic flow-through chamber system Zifei Liu, Ph.D. Student, Graduate Research Assistant Lingjuan Wang, Ph.D., Assistant professor David B. Beasley, Ph.D., P.E., Professor Department of Biological and Agricultural Engineering, North Carolina State University, Raleigh, NC 27695-7625
Edgar O. Oviedo, DVM, Ph. D., Assistant professor Department of Poultry Science, North Carolina State University, Raleigh, NC 27695-7608
Written for presentation at the 2007 ASABE Annual International Meeting Sponsored by ASABE Minneapolis Convention Center Minneapolis, Minnesota 17 - 20 June 2007 Abstract. This paper reports some preliminary efforts to evaluate effects of various influencing factors on ammonia emissions from broiler (meat chicken) houses, and to develop mathematical emission model(s) so that ammonia emissions can be predicted under given conditions. A statistical model was developed based on measurements of ammonia emissions from broiler litter in a dynamic flow-through chamber system. The model inputs include the litter total kjeldahl nitrogen (TKN) content, litter pH value, litter moisture content, litter carbon content, the mass transfer coefficient and ventilation rate. Under the designed operating condition, the mass transfer coefficient has been estimated to have an average value of 8.59 m/h. The model results showed that ammonia emission flux increased with increasing litter TKN content, pH, litter moisture content, mass transfer coefficient and ventilation rate (air flow rate), and decreased with increasing litter carbon content. The model was most sensitive to litter pH value than to other input variables. Keywords. Ammonia, Emission model, Broiler litter, Dynamic flow-through chamber
The authors are solely responsible for the content of this technical presentation. The technical presentation does not necessarily reflect the official position of the American Society of Agricultural and Biological Engineers (ASABE), and its printing and distribution does not constitute an endorsement of views which may be expressed. Technical presentations are not subject to the formal peer review process by ASABE editorial committees; therefore, they are not to be presented as refereed publications. Citation of this work should state that it is from an ASABE meeting paper. EXAMPLE: Author's Last Name, Initials. 2007. Title of Presentation. ASABE Paper No. 07xxxx. St. Joseph, Mich.: ASABE. For information about securing permission to reprint or reproduce a technical presentation, please contact ASABE at [email protected] or 269-429-0300 (2950 Niles Road, St. Joseph, MI 49085-9659 USA).
Introduction Ammonia is considered the most harmful gas in broiler chicken housing (Carlile, 1984). The importance of ammonia emissions from animal feeding operations (AFOs) has been well recognized (Van der Hoek, 1991; Zhao et al., 1994; Sutton et al., 1995; Aneja et al., 2000; Arogo et al., 2001; Hutchings et al., 2001; Lee and Park, 2002; Battye et al., 2003; Hyde et al., 2003; Xin et al., 2003; Wheeler et al., 2003; Liang et al., 2003; and Gates et al., 2004). However, the contributions of ammonia emission from large poultry operations to the national emission inventory have not been properly documented. Accurate estimation of ammonia emission rate from individual operations or sources is important and yet a challenging task for both regulatory agencies and animal producers. Numerous studies have been reported throughout the world on ammonia emissions from broiler houses, and wide variations have been found among different studies. The differences in ammonia emission fluxes from broiler houses under different conditions have been reported as high as 55 fold (Redwine et al., 2002). Variations in ammonia emissions result from the dependence of ammonia emissions on seasonal and regional conditions, house design, and management practices. Broiler chickens are normally raised on litter made up of wheat straw or wood shavings above an earthen floor. The litter serves as manure absorbance. The mixture of litter and manure represents the most significant source of ammonia emissions. The mechanisms related to ammonia emissions from manure involve many processes and have been summarized by Ni (1999). Theoretically, the processes involved in ammonia emissions from litter based manure include conversion of uric acid to urea, hydrolysis of urea, enzymatic and microbial generation of ammonia, partitioning between the adsorbed and dissolved phase ammonia, the chemistry of ammonia in aqueous solution, partitioning between solid/aqueous phase and gaseous phase ammonia, and the convective mass transfer of ammonia gas from the surface into the free air stream. Factors that may influence ammonia emissions from broiler litter include: air and litter temperature, ventilation rate, air velocity, litter pH, litter nitrogen content, and litter moisture content. Determining ammonia emissions is both expensive and difficult using currently available technologies for measuring ammonia concentrations and ventilation airflow rates under commercial broiler house conditions. In order to improve the accuracy and simplicity of estimating ammonia emissions, development of emission models is desired. Emission models allow users to calculate site-specific emissions, using the local design and operating parameters. Emission models can also be used to quantify and evaluate the effectiveness of various emission control strategies. Evaluating effects of these control strategies on emissions from livestock buildings for full-scale operations can be quite expensive and labor intensive using current measurement methodologies (NRC, 2003). The influences of management factors and litter conditions on ammonia emission have been documented (Nicholson et al., 2004; Redwine et al., 2002; Reece et al., 1985; Elliot and Collins, 1982; Elwinger and Svensson, 1996; Carr et al. 1990; Brewer and Costello, 1999), but they have not been adequately incorporated into current emission models. Much work remains to be done because of the number of variables in practice. Further evaluation of these variables is needed for enhanced understanding of the wide variation in ammonia emission rates. The research objectives of this study are to evaluate the effects of various influencing factors on ammonia emissions from broiler litter, and to develop a mathematical emission model so that ammonia emissions can be predicted under given conditions.
2
Experimental setup Dynamic flow-through chamber system Due to high uncertainties in measuring ammonia emissions on the farm scale and bio-security limitations to accessing a commercial farm, this research was conducted in well-controlled laboratory facilities. A dynamic flow-through chamber system was designed for this ammonia emissions model development study to evaluate model components individually or in designed combinations. The dynamic flow-through chamber system is shown in Figure 1. The chamber body has a cylindrical shape with bottom diameter (inside measurements) of 40.0 cm (15.75 inches) and height of 39.4 cm (15.5 inches). Broiler litter samples were put on the bottom of the chamber and a vacuum pump was used to draw air through the chamber at designed flow rate via flow controllers (Gilmont Shielded Industrial Flow meter, accuracy ±5%). Before entering the chamber, ambient air passed through an activated carbon filter so that background ammonia was removed. A motor driven stainless steel impeller mixed the air inside the chamber and promoted desired convective conditions. The dynamic chamber system, with the continuous stirring provided by the impeller, met the necessary criteria for performance as a continuously stirred tank reactor (CSTR) (Aneja, 1976). The entire chamber body was made of stainless steel, and Teflon tubing was used to minimize the loss of ammonia. Ammonia concentration in the chamber was measured by a Thermo Environmental Instruments (TEI) chemiluminescence ammonia analyzer (Model 17C). Vent
Motor
Ambient air
Flow controller
Pump
Impeller
Carbon filter
NH3 free air
Flux Chamber NH3
The NH3 analyzer
Litter
Data logger Data logger
ECH2O moisture sensor
Figure 1. The dynamic flow-through chamber system for measuring ammonia emission from broiler litter The ammonia fluxes from the litter surface inside the chamber can be calculated using the following equation: d[C]/dt = QC0/V + JA/V – QC/V
(1)
In which, C : ammonia mass concentration in the chamber, mg m-3; Q : flow rate of the carrier gas through the chamber, m3 h-1; C0: ammonia concentration in the carrier gas stream, mg m-3;
3
V : volume of the chamber, m3; J : ammonia emission flux, mg m-2 h-1; A: chamber bottom surface area, m2. Since background ammonia was removed from the carrier gas, C0=0. At steady state, d[C]/dt=0. Therefore, the ammonia emission flux J can be obtained from the following equation: (2)
J = (Q/A) Cg, chamber In which, Cg, chamber is the ammonia concentration in the chamber at steady state.
The dynamic flow-through chamber was built to simulate the convective conditions in an actual broiler house. The ventilation rate and air velocity at the litter surface has been recognized as two important factors that affect ammonia emissions. Based on the ventilation rates reported by Lacey et al. (2003) and Guiziou & Beline (2005), the air residence time has been estimated in the range of 59 to 191 seconds for a tunnel-ventilated broiler house in Texas and in the range of 260 to 36000 seconds for a broiler house in France. The ventilation rates of the chamber (air flow rates through the chamber) in this reported preliminary study were set from 10.0 to 74.0L/min, which caused residence time of air in the chamber to be 40 to 300 seconds. Although the ventilation rates can vary widely in practice, Brewer and Costello (1999) reported that the mean air speed at a 25 cm height is 0.24 m/s with a standard deviation of 0.14 m/s in a typical broiler house. In a tunnel-ventilated broiler house, air velocity at the litter surface is believed to be higher, but no reported data has been found. In this reported study, a hotwire anemometer was placed at about 2.5 cm height above the litter surface in the chamber to measure air velocity profile in the chamber. It was found that, the RPM of the stirring impeller was the only significant factor that determines the air velocity at the litter surface when the ventilation rate (air flow rate) of chamber was less than or equal to 74 L/min. Therefore, in the chamber system, ventilation rate and air velocity at the litter surface can be set independently. At 110 RPM, the air velocity at the litter surface was measured in the range from 0.10 to 0.99 m/s at various distances from the center to the wall of the chamber. The wind profile in the chamber is shown in Table 1. Table 1 Air velocity at the litter surface in the chamber (RPM=110) Distance from center of the chamber (inches)
0
2.5
5.0
7.5
10.0
12.5
15.0
Air velocity (m/s)
0.10
0.37
0.64
0.80
0.93
0.99
0.95
Litter samples and ammonia measurements Litter samples at various ages were taken from three commercial broiler farms in North Carolina. These broiler farms had similar management practices: the grow-out period was 56-60 days (per flock) with two weeks of clean-out time. The litter material used by these farms consisted of wood shavings. Each litter sample was randomly taken from multiple locations of a broiler house during the clean-out period. The samples were stored in airtight buckets in an airconditioned laboratory with temperature around 22 oC. For each test, 3000 gram litter samples were put on the chamber bottom with a depth of about 5 cm. The ammonia analyzer measured ammonia concentrations in the chamber continuously and a HOBO data logger was used to record the ammonia analyzer measurements at oneminute intervals. The ammonia concentration in chamber was defined as steady state once the variation in concentration was less than 0.5 ppm in ten minutes. Each measurement of steady-
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state ammonia concentration was obtained after the litter was remixed and the chamber reached a new steady state. For each test, three replicate measurements were taken. 100 gram litter samples were taken for solids analyses before and after each test. The solids analyses include total kjeldahl nitrogen (TKN), total ammoniac nitrogen content (TAN), moisture content, pH, total nitrogen content and total carbon content. The solids analyses were conducted in the Environmental Analysis Laboratory of in the Department of Biological and Agricultural Engineering (BAE) at NC State University following EPA standard methods. Statistic analysis indicated that there were no significant differences between the analysis results before and after each test. An ECH2O moisture sensor (EC5) was used to monitor litter moisture contents continuously which also confirmed that moisture remained relatively constant during the tests. The room temperatures were kept at 22 oC during all of the tests.
Model structure Although different theories of mass transfer have been used in the models of ammonia emissions (Hashimoto and Ludington, 1971; Olesen and Sommer, 1993), the resulting mass transfer equations were often in a similar form. The general mass transfer flux equation can be expressed as, J = Km (Cg, 0- Cg, ∞)
(3)
In which, J: emission flux, mgN m-2 h-1; Km: mass transfer coefficient, m h-1; Cg, 0: gas phase ammonia concentration at the emission surface, mgN m-3; Cg, ∞: concentration of gas phase ammonia in the free air stream, mgN m-3. Most of the published ammonia emission models use this equation as the core equation (Ni, 1998), and sub-models were developed to serve this core. In an open field, Cg, ∞ is often very low and can be neglected. In animal houses, this concentration can be too high to be negligible, and it is dependent on the ventilation rate. In the dynamic flow-through chamber system, the general mass transfer flux equation can be expressed as, J = Km (Cg, 0- Cg, chamber)
(4)
Combining equations 4 and 2, which was derived from mass balance approach, the following equation is obtained, (Q/A) Cg, chamber = Km (Cg, 0- Cg, chamber)
(5)
Cg, chamber = Km(Km+Q/A)-1 Cg, 0
(6)
So,
Combining equations 6 and 2, the core emission flux model is obtained as follows: J = ((Q/A)-1+Km-1)-1Cg, 0
(7)
Emission fluxes J can be expressed by multiplying Cg, 0 with an overall emission coefficient Ke. J = Ke * Cg, 0
(8)
In this case, the emission coefficient Ke has units of velocity, and it is determined by ventilation rate (air flow rate) Q, emission surface area A and the mass transfer coefficient Km as following.
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Ke = [(Q/A)-1 + Km -1]-1
(9)
Influence of ventilation rate Q and the mass transfer coefficient Km on emission flux depends on the relative magnitude of Q/A and Km, which is summarized in Table 2. Table 2 Influence of the relative magnitude of Q/A and Km Controlling factor When Q/A >> Km
Ke ≈ Km
When Q/A > Km, therefore, Km was the controlling factor, and ammonia flux was more sensitive to Km than to Q as shown in Table 4. Relative sensitivity of litter carbon content is negative because ammonia flux was negatively related with litter carbon content. Table 4 Relative sensitivity Sr for ammonia emission flux from litter with respect to litter TKN content, litter pH, litter moisture content, litter total carbon content, the mass transfer coefficient Km and the ventilation rate Q TKN content Range (μg/g) 32000-34000 34000-36000 36000-38000 38000-40000 40000-42000 42000-44000 44000-46000 46000-48000 48000-50000 50000-52000 52000-54000
pH Sr 1.73 1.45 1.24 1.08 0.96 0.86 0.78 0.71 0.65 0.60 0.56
Range 6.2-6.4 6.4-6.6 6.6-6.8 6.8-7.0 7.0-7.2 7.2-7.4 7.4-7.6 7.6-7.8 7.8-8.0 8.0-8.2 8.2-8.4
Sr 2.34 3.32 4.54 5.95 7.43 8.85 10.05 10.92 11.34 11.21 10.41
Moisture content Range (%) Sr 15-20 0.69 20-25 0.57 25-30 0.49 30-35 0.42 35-40 0.37 40-45 0.33 45-50 0.28 50-55 0.25 55-60 0.21 60-65 0.18 65-70 0.14
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54000-56000 56000-58000 58000-60000
0.52 0.49 0.46
Total carbon content Range (%) Sr 28-30 -0.30 30-32 -0.36 32-34 -0.42 34-36 -0.49 36-38 -0.58 38-40 -0.67 40-42 -0.78 42-44 -0.91 44-46 -1.05
8.4-8.6 8.6-8.8 8.8-9.0 Km Range (m/h) 2-4 4-6 6-8 8-10 10-12 12-14 14-16 16-18 18-20
8.79 6.22 2.73
70-75 75-80 80-85
0.11 0.07 0.04
Sr 0.99 0.99 0.98 0.97 0.97 0.96 0.96 0.95 0.94
Q Range (L/min) 1-5 5-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80
Sr 0.39 0.14 0.08 0.04 0.03 0.02 0.02 0.02 0.01
Note: Litter TKN content, litter moisture content and total carbon content are all expressed on a dry basis.
Conclusion A statistical model was developed to estimate ammonia emission flux from broiler litter based on experimental results from a dynamic flow-through chamber system. The model inputs include the litter TKN content, litter pH value, litter moisture content, litter carbon content, the mass transfer coefficient Km and ventilation rate Q. Under the designed operating condition, the mass transfer coefficient Km has been estimated to have an average value of 8.59 m/h. The model results showed that ammonia emission flux increased with litter increasing TKN content, pH, litter moisture content, mass transfer coefficient and ventilation rate, and decreased with increasing litter carbon content. The model was most sensitive to litter pH value than to other input variables. Experiments are continuing in an effort to develop a model to estimate the mass transfer coefficient Km at various surface air velocities. The future work will also include model validation with more data from laboratory experiments, as well as field measurements.
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