SEASONAL EMISSIONS OF AMMONIA AND METHANE FROM A HOG WASTE LAGOON WITH
BIOACTIVE COVER
David Natschke,' Ram A. Hashmonay,1 Keith Wagoner,' D. Bruce Harris,2 Edgar L. Thompson, Jr.,2 and Chester A.
Vogel"'
1 ARCADIS G&M, Inc., P.O. Box 13109, Research Triangle Park, NC 27709
:U.S. EPA, ORD. NRMRL, Mail Drop 61, Research Triangle Park, NC 27711
ABSTRACT
Plane-integrated (PI) open-path Fourier transform infrared spectrometry (OP-FTIR) has been used to measure the
flux of ammonia and methane from a hog waste lagoon before and after the installation of a bioactive cover. A
computed tomography algorithm using a smoothed basis function converts the measured PI concentrations into a
plume profile. Simultaneously collected wind data are integrated across the plume to yield the emission flux.
Seasonal data are reported, beginning with summer data collected before and after the cover installation through the
following spring. Emission data from the naturally ventilated finishing barn feeding this lagoon are also presented.
INTRODUCTION
Several methods have been developed and applied (Scotto et al.. 1991; Minnich et al., 1992; Milton, et al., 1995;
Piccot et al.. 1994, 1996; Kirchgessner et al., 1993; Simpson and Kagan, 1990; Whitcraft and Wood, 1990; and
Hashmonay and Yost., 1999a) to estimate emission rates from fugitive sources such as landfills (Milton et al., 1995),
coal mines (Picot et al., 1994; Kirchgessner et al., 1993), or water treatment plants (Simpson and Kagan, 1990;
Hashmonay ct al. 1999a), using path-integrated optical remote sensing (Pl-ORS) technologies. All previous
methodologies combine downwind path-integrated concentration (PIC) data, wind measurements, and plume
dispersion modeling to retrieve the total emission rate. Recently, an innovative computed tomography (CT)
technique was proposed (Hashmonay and Yost, 1999a) and evaluated (Hashmonay et al., 1998; Hashmonay et al.,
2001), which applies the smooth basis function minimization (SBFM) method (Hashmonay et al., 1999b; Price,
1999; and Drescher et al., 1996) to the beam data in conjunction with measured wind data, to estimate the total flux
from the area source. The approach combines PIC data acquired with any PI-ORS technique and CT data analysis.
Moreover, this approach is independent of dispersion model assumptions. In this study, an OP-FTIR instrument
sampled PICs along five radial beam paths, in a vertical plane downwind from the lagoon source.
Emissions from animal waste lagoons have increased as production has shifted from the family farm to concentrated
industrial operations. Air emissions of interest include greenhouse gases, particularly methane, and fine particle
precursors (ammonia). The test site is a 0.3-hectare (0.75-acre) lagoon serving a single 980-head finishing barn. The
lagoon is being used to test the effectiveness of a bioactive cover for controlling ammonia emissions. The cover
consists of a punched polyester felt fabric held afloat by recycled closed-cell polyethylene foam blocks upon which a
thin layer of zeolite is spread. Bacteria that form colonies within the zeolite use the ammonia as the food source.
EXPERIMENTAL SETUP
The setup of the beam geometry and upwind area source in this experiment is illustrated in Figure 1. The beam geometry
is in a vertical plane downwind from the lagoon area source. The beam geometry consists of five beam paths, three
scanning the OP-FTIR device to ground level retroreflectors, and two slanted beam paths scanning to elevated (5 and 9
m heights) retroreflectors mounted on a tower. Establishing this plane across the plume allows measurement of the flux
through it (Hashmonay and Yost, 1999b). North is parallel to the y-axis. A Midac OP-FTIR mounted on an EPA-
designed and -built two-axis scanner moves among the beam paths. The spectral data are collected following EPA
guidelines (KPA. 1996). Spectral interpretation and quality assurance follow techniques developed specifically for open-

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path spectrometry (Childers el ai, 2001). Each path is sampled for 1 minute per scan with the total sampling period at
least 20 minutes long to minimize data variations and to allow a buildup of an approximate Gaussian plume. Ethylene is
released from the southeast corner of the barn to indicate scans containing barn emissions, which are not used in the
analysis. Wind speed and direction data are collected and averaged over the same time interval.
~ Retroreflectors
Finishing Barn
Lagoon
Wind Vecto
Scanning
OP-FTIR
Figure 1. Field Configuration and OP-FTIR Beam Geometry
GENERAL PRINCIPLES
To illustrate this technique consider Figure 2, which presents the cross-section of a plume overlaid with the optical
configuration for vertical scanning. The five retroreflectors may be thought of as defining a vertical 3x3 matrix,
which encloses all, or a majority of the plume. For convenience. Figure 2 is presented with cells of even size. This
is not a prerequisite of the method. Table 1 presents a synthetic data set of cell-by-cell averaged concentrations
corresponding to the plume in Figure 2.

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1
2
3
Figure 2. Cross Section of Plume as Sparse Matrix
Table 1. CelI-Averaged Concentration (ppm) for Figure 2
The instrument, however, does not directly observe concentration as presented in
Table 1. Comparing Figures 1 and 2, it is easy to observe that each optical beam
traverses one or more cells. In fact, for each scan to a retroreflector, the signal is a
function of both the optical path and the concentration, in other words the PIC.
Equation 1:
Signal cc pathlength * concentration
Where the concentration is non-uniform, the observed signal will be the sum of the individual path segments times
the localized concentration.
Equation 2:
Signal cc pathlength t * concentration.
The result of this is that the observed signal is proportional to the total optical pathlength and the weighted average
concentration along that path. Table 2 presents calculated data as would be observed by the experimental setup of
Figure 1 for the synthetic data of Table 1. In Table 2, r is the optical pathlength, which is twice the physical
distance, and 0 is the scanning angle.
Table 2. Calculated Path-Integrated Concentration (PIC), ppm
The data in Table 2 are ready for immediate use in the SBFM,
described below. For purposes of understanding the method,
we may proceed further manually.
As described by Equation 2, the PIC for an individual cell may
be determined by difference and, since the pathlengths are
measurable by theodolite, the concentrations in individual
cells may be calculated. For example, the PIC for cell A3 is
simply the difference between mirror 3 and mirror 2, or 825.
The pathlength within cell A3 is also the difference between
mirrors 3 and 2, or 33. Therefore, the average concentration
within cell A3 is obtained by division: 25.

1
2
3
c
1
10
1
B
15
50
15
A
25
100
25
Mirror
Pathlength,
r (m)
e
PIC
1
33
0
825
2
66
0
4125
3
99
0
4950
4
100.6
10.30
3019
5
103.5
16.86
2207
3

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Clearly, with nine cells and five measurements, the matrix is sparsely determined, but we are unable to extend this
simplistic approach to all cells. For example, the optical path to mirror 4 passes through cells Al, B2, and B3.
While cell AI is known from other measurements, cells B2 and B3 are not separable. After cell Al's contribution is
removed, the averaged concentration is applied to both cells. Similar logic applies to the mirror 5 data.
At this stage the data looks like Table 3.
Table 3. Concentrations (ppm) from PIC Calculations

1
2
3
c

14.3
14.3
B
14.3
32,5
32.5
A
25
100
25
Figure 3 presents the above data graphically. Note that cell C1 is undefined rather than zero.
B
A

14.3
14.3
14.3
.32.5
32.5
25
100
25
B
A
oo
vD
^r
oo
Figure 3. Localized Concentration (ppm) Results
Recognizing that any plume originates from some source and is characterized by well-established physical processes,
it becomes both reasonable and desirable to improve the resolution of the above data through their fitting to some
function. The SBFM method used with a bivariate Gaussian has been well established (Hashmonay et al.. 2001;
Hashmonay and Yost, 1999b; Price, 1999; and Drescher ct al, 1996) for use in this work. Using the integrated form
of the function permits calculations to be performed directly from the PIC data. After the application of some
reasonable assumptions, this reduces to:
Equation 3:
G(r,£)
2jzayp
-exp<
'{rcosO - my}2
(r*sin0 —
21
cr,
4

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Where:
G is the Gaussian distribution,
r is the optical pathlength,
0 is the scanning angle, and
A, my, m,, oy, and a, are fitting variables corresponding to the maximum value, peak location in the horizontal
dimension, peak location in the vertical dimension, standard deviation in the horizontal dimension, and standard
deviation in the vertical dimension, respectively.
The SBFM searches for and optimizes the several parameters of Equation 3 through minimization of an error
function. In each iterative step of the SBFM-CT search procedure, the measured PIC values are compared with
estimated PIC values, calculated from the new set of parameters. In order to compute the estimated PIC values, the
basis function is integrated along the beam path's direction and length. The concordance correlation factor (CCF) is
used as a measure of the goodness-of-fit of the reconstructed concentrations with the measured PIC values.
Once the parameters of the function are found for a specific run, the concentration values are calculated for every
3x3 m square elementary unit in a vertical domain size of 99x15 m and then integrated incorporating wind speed
data at each height level to compute the flux. The concentration values are converted from parts per million by
volume to micrograms per cubic meter using the molecular weight of the gas and ambient temperature. Using wind
speed data in meters per second enables the calculation of the fluxes in grams per second.
RESULTS AND DISCUSSION
Average results over 2 hours of data collection for
methane and ammonia emission fluxes, from the
first field campaign prior to the installation of the
bioactive cover (July 2000), are given in Figure 4.
Both the methane and ammonia reconstructed
plumes are from the same data set. Table 4 presents
data reflecting the effects of both cover installation
and seasonal (temperature) variations. The results
from 7/11/00 are baseline measurements, prior to
cover installation. The emission of 96 kg
NHj/ha/day are more than the 57.6 kg/ha/day
calculated from Aneja et al. (2000) and the 2.9-10.5
kg/ha/day reported by Harper and Sharpe (1998).
The results from 8/16/00 are post-installation and
were obtained under similar temperature and wind
conditions. Comparing baseline with post-
installation, substantial reduction in ammonia
emission fluxes occurs between the two visits, while
the methane emission flux actually went up by 20%.
It is not clear whether the reduction in ammonia
release results from the bioactivity or just the reduction in Collection for Methane and Ammonia Emission
liquid surface area. It has been noted that the concentration Fluxes, from the First Field Campaign Prior to the
of nitrogen compounds increased in the lagoon liquor in Installation of the Bioactive Cover (July 2000)
this same time period. This suggests that at least some of
the reduction can be attributed to sequestering of the ammonia in the liquor. Finally, the data from 2/28/01 show a
continuing decrease in ammonia emissions while the methane has stabilized. It is unclear at this point whether we
are observing thermal or cover effects. We will be continuing this study for at least one more visit under warmer
conditions.
10
9
8
_ 7
£ 6
£ 5
CT>
'
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Table 4. Summary of Ammonia and Methane Emissions Along with Meteorological Data

Ammonia Flux
(g/min)
Methane Flux
(g/min)
Wind Speed
(tn/s)
Wind Direction
(degrees)
7/11/00
20
40
2,1
254
8/16/00
4.7
66
3.0
254
2/28/01
0.84
62
1.9
104
CONCLUSIONS
The combined OP-FTIR/CT method has demonstrated it can be used to determine emissions from actual area
sources. Though applied to a small source, the technique should he useful for larger sites by substituting the
appropriate optical source.
REFERENCES
Aneja, V, P., J, P. Chauhan, and J. T. Walker, 2000. Characterization of Atmospheric Ammonia Emissions from
Swine Waste Storage and Treatment Lagoons. J. Geophysical Research 105:11535-11545.
Childers, J. W., E. L. Thompson Jr., D. R, Harris, D. A. Kirchgessner. M. Clayton, D. F. Natschke, and W. I.
Phillips, 2001. Multi-Pollutant Concentration Measurements Around a Concentrated Swine Production Facility
Using Open-Path FTIR Spectrometry. Atmospheric Environment 35:1923-1936.
Drescher, A. C„ A. J. Gadgil, P. N. Price, and W. W. Nazaroff, 1996. Novel approach for tomographic
reconstruction of gas concentration distributions in air: Use of smooth basis functions and simulated annealing.
Atmospheric Environment 30(6):929-940.
Harper, L. A., and R. R. Sharpe, 1998. Ammonia Emissions from Swine Waste Lagoons in the Southeastern U.S.
Coastal Plains. Final Grant Report to Division of Air Quality, North Carolina Department of Environment and
Natural Resources, Raleigh, NC. USDA-ARS Agreement N. 58-6612-7M-022, December 1998.
Hashmonay, R. A., D. F. Natschke, K. Wagoner, D. B. Harris, E. L. .Thompson, and M. G. Yost, 2001. Field
Evaluation of a Method for Estimating Gaseous Fluxes from Area Sources Using Open-Path Fourier Transform
Infrared. Environmental Sci. and Tech. 35(11):2309-2313.
Hashmonay, R. A., and M. G. Yost, 1999a. Innovative Approach for Estimating Gaseous Fugitive Fluxes Using
Computed Tomography and Remote Optical Sensing Techniques. J. Air & Waste Mgt. Assoc. 49:966-972.
6
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Hashmonay, R. A., and M. G. Yost, 1999b. Localizing gaseous fugitive emission sources by combining real time
optical remote sensing and wind data. J. Air & Waste Mgt. Assoc. 49:1374-1379.
Hashmonay, R. A., M. G. Yost, D. B. Harris, and H. L. Thompson, Jr. 1998. Simulation Study for Gaseous Fluxes
from an Area Source Using Computed Tomography and Optical Remote Sensing. Proc. of SP1E Environmental
Monitoring and Remediation Technologies Conf.. Boston, MA, pp. 405-410.
Hashmonay, R. A., M. G. Yost, Y. Mamane, and Y. Benayahu, 1999a. Emission Rate Apportionment from
Fugitive Sources Using Open-Path FTIR and Mathematical Inversion. Atmospheric Environment 33(5):735-743.
Hashmonay, R. A., M. G. Yost, and C. F. Wu, 1999b. Computed tomography of air pollutants using radial
scanning path-integrated optical remote sensing. Atmospheric Environment 33(2):267-274.
Kirchgessner, D. A., S. D. Piccot, and A. Chadha. 1993. Estimation of methane emissions from a surface coal mine
using open-path FF1R spectroscopy and modeling techniques. Chemosphere 26(l-4):23.
Milton, M. J. T., R. H. Partridge, and B. A. Goody, 1995. Minimum emission rates detectable from landfill sites
using optical integrated-path techniques. In Proc. A&WMA International Specialty Conference on Optical Sensing
for Environmental and Process Monitoring, San Francisco, CA, VIP-55, p. 393.
Minnich, T. R., R. L. Scotto, M. R. Leo. B. C. Sanders, S. II. Perry, and T.H. Pritchett, 1992. A practical
methodology using open-path FTIR spectroscopy to generate gaseous fugitive-source emission factors at industrial
facilities. In Proc. Optical Remote Sensing. Application to Environmental and Industrial Safety Problems, Houston,
TX, SP-81, p. 513.
Piccot, S. D., S. S. Masemore, W. Lewis-Bevan, E. S. Ringler, and D. B. Harris, 1996. Field assessment of a new
method for estimating emission rates from volume sources using open-path FITR spectroscopy. J. Air & Waste
Mgt. Assoc. 46:159.
Piccot, S. D., S. S. Masemore, E. S. Ringler, S. Srinivasan, D. A. Kirchgessner, and W. F. Herget. 1994. Validation
of a method for estimating pollution emission rates from area sources using open-path FTIR spectroscopy and
dispersion modeling techniques. J. Air & Waste Mgt. Assoc. 44:271.
Price, P. N., 1999. Pollutant tomography using integrated concentration data from non-intersecting optical paths.
Atmospheric Environment 33(2):275-280.
Russwurm, G. M., and J. W. Childers, 1996. FT-IR Open-Path Monitoring Guidance Document, EPA/600/R-96/040
(NTIS PB96-170477). U.S. Environmental Protection Agency, Office of Research and Development, National
Exposure Research Laboratory, Research Triangle Park, NC.
Scotto, R.L., T. R. Minnich, and M. R. Leo, 1991. A method for estimating VOC emission rates from area sources
using remote optical sensing. In Proc. EPA/A WM A International Symposium on the Measurement of Toxic and
Related Air Pollution, Raleigh, NC, p. 698.
Simpson, O. A., and R. H. Kagan, 1990. Measurements of emissions at a chemical waste water site with an open
path remote Fourier transform interferometer. In Proc. EPA/A&WMA International Symposium on the
Measurement of Toxic and Related Air Pollution. Raleigh, NC, p. 937.
Whitcraft, W. K., and K. N. Wood, 1990. Use of remote sensing to measure wastewater treatment plant emissions.
In Proc. 83rd Annual Meeting & Exhibition of the A&WMA, Pittsburgh, PA, p. 65.
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TECHNICAL REPORT DATA
NRMRL-RTP-P-635 (Please read Instructions on the reverse before completing)
1. REPORT NO. 2.
EPA/600/A-01/097
3. RECIPIENT'S ACCESSION NO.
4, TITLE AND SUBTITLE
Seasonal Emissions of Ammonia and Methane from a Hog
Waste Lagoon with Bioactive Cover
5. REPORT DATE
6. PERFORMING ORGANIZATION CODE
7.authors D.Natschke,R.A.Hashmonay,and K.Wagoner (Arcadis);
and D.B.Harris,E.L.Thompson,Jr., and C.A.Vogel (EPA)
8. PERFORMING ORGANIZATION REPORT NO
9. PERFORMING ORGANIZATION NAME AND ADDRESS
ARCADIS Geraghty & Miller, Inc.
PO Box 13109
Research Triangle Park, North Carolina 27709
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68C-99-201
12 SPONSORING AGENCY NAME AND ADDRESS
U. S. EPA, Office of Research and Development
Air Pollution Prevention and Control Division
Research Triangle Park, North Carolina 27711
13 TYPE OF REPORT AND PERIOD COVERED
Published paper; 6/00-5/01
14. SPONSORING AGENCY CODE
EPA/600/13
is. supplementary notes APPCD project officer is D. Bruce Harris, Mail Drop 61, 919/541-7807.
For presentation at International Symposium, Addressing Animal Production and Environ-
mental Issues, Research Triangle Park, NC, 10/3-5/01.
16 abstractpaper discusses the use of plane-integrated (PI) open-path Fourier trans-
form infrared spectrometry (OP-FTIR) to measure the flux of ammonia and methane from a
hog waste lagoon before and after the installation of a bioactive cover. A computed
tomography algorithm using a smoothed basis function converts the measured PI concen-
trations into a plume profile. Simultaneously collected wind data are integrated across
the the plume to yield the emission flux. Seasonal data are reported, beginning with
summer data collected before and after the cover installation through the following
spring. Emission data from the naturally ventilated finishing barn feeding this lagoon
are also presented.
17. KEY WORDS AND DOCUMENT ANALYSIS
a DESCRIPTORS
b. IDENTIFIERS/OPEN ENDED TERMS
C- COSAT! Field/Group
Pollution Covering
Emission Biological Agents
Lagoons (Ponds) Hog Houses
Swine
Wastes
Anmonia
Methane
Bioactivity
Stationary Sources
Pollution Control
13B 11C
14G 15B
02C
02E,06C
07B
07C
18. DISTRIBUTION STATEMENT
19. SECURITY CLASS (This Report)
21. NO. OF PAGES
7
20. SECURITY CLASS (This Page)
22. PRICE
EPA Form 2220-1 (Rev. 4-77 ) PREVIOUS EDITION IS OBSOLETE	forms/admin/techrpt.frm 7/8/99 pad
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