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Whole Farm Impact of Anaerobic Digestion and Biogas Use on a New York Dairy Farm

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Anaerobic digestion of manure for biogas production is one option for reducing the carbon footprint of milk production. This process reduces greenhouse gas emissions but increases the potential for nitrogen and phosphorus losses from the farm. A digester component was added to the Integrated Farm System Model to obtain a tool for comprehensive evaluation of the various effects of using this technology on dairy farms. A dairy farm in New York was simulated for 25 years of weather with and without the use of a digester. Farm records were used to verify simulated feed production and use, milk production, biogas production, and electric generation and use. Methane emission from the manure storage was reduced 71%, which reduced the whole-farm emission by 20%. Energy saved in water heating and purchased electricity reduced combustion and secondary carbon dioxide emissions by 9% and 11%, respectively. Over all farm sources and sinks, the digester reduced the net greenhouse gas emission and farm gate carbon footprint by 25 to 30% with a small increase in ammonia emission. Without financial assistance, there was no direct economic benefit to the producer, but benefits of reduced odor and a lower carbon footprint were obtained without much reduction in farm profit. Whole-farm simulation provides a useful tool for evaluating and comparing management options to reduce the environmental footprint of farm production systems.
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An ASABE Meeting Presentation
Paper Number: 1111194
Whole Farm Impact of Anaerobic Digestion and Biogas
Use on a New York Dairy Farm
C. Alan Rotz, Agricultural Engineer
USDA/ARS, 3702 Curtin Road, University Park, PA 16802
Sasha D. Hafner, Research Associate
10300 Baltimore Avenue, B-007, Room 213, BARC-West, Beltsville, Maryland 20705
Written for presentation at the
2011 ASABE Annual International Meeting
Sponsored by ASABE
Gault House
Louisville, Kentucky
August 7 – 10, 2011
Abstract. Anaerobic digestion of manure for biogas production is one option for reducing the carbon
footprint of milk production. This process reduces greenhouse gas emissions but increases the
potential for nitrogen and phosphorus losses from the farm. A digester component was added to the
Integrated Farm System Model to obtain a tool for comprehensive evaluation of the various effects of
using this technology on dairy farms. A dairy farm in New York was simulated for 25 years of weather
with and without the use of a digester. Farm records were used to verify simulated feed production
and use, milk production, biogas production, and electric generation and use. Methane emission
from the manure storage was reduced 71%, which reduced the whole-farm emission by 20%. Energy
saved in water heating and purchased electricity reduced combustion and secondary carbon dioxide
emissions by 9% and 11%, respectively. Over all farm sources and sinks, the digester reduced the
net greenhouse gas emission and farm gate carbon footprint by 25 to 30% with a small increase in
ammonia emission. Without financial assistance, there was no direct economic benefit to the
producer, but benefits of reduced odor and a lower carbon footprint were obtained without much
reduction in farm profit. Whole-farm simulation provides a useful tool for evaluating and comparing
management options to reduce the environmental footprint of farm production systems.
Keywords. Dairy farm, Simulation, Anaerobic digestion, Biogas.
USDA is an equal opportunity provider and employer
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Introduction
Anaerobic digestion of manure for biogas production is one of many options for reducing the
carbon footprint of milk production. This process removes a major portion of the volatile solids
(VS) from manure, reducing the potential for methane and carbon dioxide emission during
manure storage and following land application. The biogas produced can be used to generate
electricity and heat water, both of which reduce secondary greenhouse gas emissions by
displacing other sources of fuel and electricity.
Decomposition of manure in a digester has biological and chemical effects that may lead to
other changes in farm performance and environmental impact. Nitrogen and phosphorus forms
change, potentially affecting ammonia emissions, nitrate leaching losses, and phosphorus runoff
(Gooch et al., 2007). The effects of these changes in nutrient composition are dependent
though upon how the manure is managed following digestion. For example, total ammoniacal
nitrogen and dissolved phosphorus concentrations are generally greater than that found in fresh
or stored manure. If manure is applied on field surfaces without incorporation, this will lead to
greater ammonia emission to the atmosphere and greater phosphorus runoff in surface water. If
the digestate is injected below the surface, these changes may improve crop uptake without
added loss. These differences in nutrient availability can affect crop yields, feed production and
other interactions throughout the farm (Rotz et al., 2011b).
For a complete analysis of the benefits of anaerobic digestion, a comprehensive whole-farm
evaluation is needed that considers the flow of nutrients throughout the production system. This
type of evaluation is best done through process-level farm simulation using a tool such as the
Integrated Farm System Model (IFSM; Rotz et al, 2011a). This model has previously been used
to evaluate the effects of management on greenhouse gas emissions, nutrient losses, and farm
economics (Rotz et al., 2009; Rotz et al., 2010; Rotz et al., 2011b). However, previous versions
of the model did not include an anaerobic digester component.
Our objective was to evaluate the whole-farm environmental and economic impacts of using an
anaerobic digester on a representative northeastern dairy farm. This required 1) development of
a component model for simulating anaerobic digestion, 2) evaluation of the model by comparing
simulated and actual performance for a New York dairy farm, and 3) using the model to
determine the whole-farm impacts of implementing an anaerobic digester for on-farm biogas
and electricity production and use.
Model Description
A component model was developed, evaluated, and used to simulate the performance of a
manure digester in a farming system. This new component was incorporated into the IFSM to
simulate daily biogas production and use as affected by manure production and handling and
other interactions throughout the farm.
Integrated Farm System Model
The IFSM is a research tool used to assess and compare the economic and environmental
sustainability of farming systems. Crop production, feed use, and the return of manure nutrients
back to the land are simulated for multiple years of weather on a crop, beef, or dairy farm (Rotz
et al., 2011a). Growth and development of crops are predicted daily based upon soil water and
nitrogen availability, ambient temperature, and solar radiation. Simulated tillage, planting,
harvest, storage, and feeding operations predict resource use, timeliness of operations, crop
losses, and nutritive changes in feeds. Feed allocation and animal response are related to the
nutrient contents of available feeds and the nutrient requirements of the animal groups making
3
up the herd. The quantity and nutrient content of the manure produced is a function of the feeds
consumed and the characteristics of the herd.
Nutrient flows through the farm predict potential nutrient accumulation in the soil and loss to the
environment (Rotz et al., 2011a). Ammonia volatilization is simulated in the barn, during manure
storage, following field application, and during grazing. Denitrification and leaching losses from
the soil are related to the rate of water movement and drainage from the soil profile as
influenced by soil properties, rainfall, and the amount and timing of manure and fertilizer
applications. Erosion is predicted using a version of the Modified Universal Soil Loss Equation
where sediment loss is a function of daily runoff, field area, soil erodibility, slope, and soil cover.
Edge-of-field runoff losses of sediment-bound and soluble phosphorus are influenced by
manure, tillage, and crop residue management along with daily soil and weather conditions.
Carbon dioxide fixation and carbon dioxide, methane, and nitrous oxide emissions are tracked
from crop, animal, and manure sinks and sources to predict the net greenhouse gas emission.
Carbon footprints (net greenhouse gas emission per unit of energy corrected milk produced) are
determined both with and without including biogenic sources and sinks of carbon dioxide.
Whole-farm mass balances of nitrogen, phosphorus, potassium, and carbon are determined as
the sum of all nutrient imports in feed, fertilizer, deposition, and legume fixation minus the
exports in milk, excess feed, animals, manure, and losses leaving the farm.
Simulated performance is used to determine production costs, incomes, and economic return
for each year of weather. A whole-farm budget includes fixed and variable production costs
(Rotz et al., 2011a). Annual fixed costs for equipment and structures are the product of their
initial cost and a capital recovery factor determined from an assigned economic life and real
interest rate. The resulting annual fixed costs are summed with predicted annual expenditures
for labor and resources to obtain a total production cost. This total cost is subtracted from the
total income received from the sale of milk, animals, and excess feed to determine a net return
to the herd and management.
By comparing simulation results, differences among production systems are determined
including annual resource use, production efficiency, environmental impact, production costs,
and farm net return. Because system performance is weather dependent, simulations are
conducted over a 25 yr sample of recent historical weather. The resulting distribution of
performance indicators describes possible performance outcomes as weather varies. No inter-
year dynamics are considered in these simulations, i.e. initial conditions such as soil nutrient
concentrations and feed inventories are reset each year. Therefore, simulation results indicate
the range of variation in economic and environmental performance that can occur given the
variation in weather at the farm location.
Anaerobic Digestion Component
A digester component model was developed to predict biogas production and use, electricity
production and use, changes in manure nitrogen and phosphorus, and the economics of owning
and operating a digester. Biogas is produced through the microbial degradation of VS in the
manure. The rate of volatile solids flow into the digester is determined from the manure dry
matter produced and loaded into the digester and the VS content of that dry matter:
 
 [1]
where
Q
VS
is the flow rate of VS into the digester (kg/d), is the VS concentration in the
influent (fraction), and
Q
m
is the loading rate of manure dry matter (kg/d).
The manure loading rate is the amount of manure excreted and collected from barns, which is
predicted in IFSM as a function of the number and type of animals fed and their diets (Rotz et
4
al., 2011a). The VS content of the manure is primarily a function of the animal types (heifers,
lactating cows, and non lactating cows on dairy farms) that produced the manure.
The methane produced is a function of an assigned productivity and a conversion efficiency:
 [2]
where  is methane production rate (kg/d),  is the efficiency of VS conversion (fraction),
and  is methane productivity per unit of VS destroyed (kg CH4 / kg VS).
The methane productivity from VS is dependent on characteristics of the manure, and is not
expected to vary substantially. The methane productivity is set at 0.35 kg CH4 / kg VS, based on
predicted and measured values reported by Hill (1984) and measured values given by Converse
et al. (1977) and Moller et al. (2007). Over all studies, reported values range from 0.23 to 0.39
kg CH4/kg VS. The conversion efficiency is a user defined characteristic of the digester, and
may range from about 20% to 45% for dairy manure, with typical values close to 30%
(Converse, 1977; Hill, 1984; Moller et al., 2004).
A similar relationship is used to predict carbon dioxide production where the productivity is 0.9
kg CO2 / kg VS. In practice, carbon dioxide productivity also varies. Values calculated from the
data in Converse et al. (1977) range from 0.74 to 0.98 kg CO2 / kg VS. However, this parameter
has only a small effect on greenhouse gas emissions because all non methane carbon is
ultimately emitted as carbon dioxide from some part of the farm system.
The energy available in the biogas produced is a function of the energy content of methane:
 
. [3]
where  is the energy available in the biogas (kW-h/d),  is the lower heating value of
methane (50 MJ/kg CH4; Masters, 2004), is the biogas leakage rate (fraction), and 3.6
converts from MJ to KW-h. The leakage rate is assigned by the model user with a typical value
being 1% (EPA, 1999).
The total energy in the biogas produced can be used to heat water in a boiler, generate
electricity, or burned in a flare. The amount used to heat water is set by the model user as a
portion of the total available:
 
 [4]
where  is the biogas energy used in the boiler (kw-h/d) and  is the fraction of the total
biogas produced that is used to heat water.
All remaining biogas energy is available to generate electricity. Electricity production is a
function of the efficiency of electrical generation and the capacity of the generator. The amount
of electricity produced each day is limited by either the capacity of the generator and the time it
is operating or the amount of biogas available:
 min24,
  [5]
where  is the electricity produced (kW-h/d),  is the run-time efficiency or the portion of
time the engine-generator sets are running at their capacity,  is the electric generation
capacity (kW),  is the energy efficiency of the engine-generator set (fraction), and 24
converts kW to kW-h/d.
The portion of time the engine-generator sets are running, the generation capacity, and the
generation efficiency are all set by the model user to represent the characteristics of the system
5
modeled. The efficiency of the engine-generator varies with the type and age of the equipment
used, but is generally about 25%. The goal is to keep the engine-generator sets running most of
the time, but maintenance, repairs, and other shutdowns reduce this time. The generation
capacity is the designed output of the engine-generator set used.
Any remaining biogas that is not used for electric generation and water heating is burned in a
flare. The energy disposed through the flare (
P
flr
) is determined as:
 
   
[6]
Burning the methane converts the lost carbon to carbon dioxide, which reduces the global
warming potential of the emission (Rotz et al., 2010). Burning biogas in a flare represents a loss
of energy, and thus should be minimized.
A major benefit from anaerobic digestion of manure is a reduction in the VS content in the
effluent. The effluent is normally stored in a tank or earthen basin, the same as that used to
store raw manure without digestion. Because of the reduction in VS, the odor and methane
produced from this storage is less than that occurring from untreated manure.
The effluent dry matter leaving the digester is reduced to account for the VS converted to
methane and carbon dioxide:
  [7]
where
Q
ef
is the flow of digester effluent dry matter into long term storage (kg/d).
The VS leaving the digester are determined as the amount entering minus that decomposed in
the digester. Total VS can be separated into degradable and slow degrading or non degraded
fractions. The degradable VS in the effluent are determined as:
, 
,  [8]
where
Q
vs,d
is the flow of degradable VS (kg/d),
B
o
is the achievable emission of methane during
anaerobic digestion (kg/kg VS) and, is the potential methane productivity during long-
term storage of the manure (kg/kg VS). The achievable emission of methane and potential
methane productivity are assigned characteristics of the raw manure; typical values are 0.2 and
0.48 kg/kg, respectively (Sommer et al., 2004; Rotz et al., 2011a). The non degraded VS in the
effluent are determined as:
, 1
, [9]
where , is the flow of non degraded VS (kg/d). The remaining VS in the manure control the
methane emission rate of the stored effluent (Rotz et al., 2011a).
The digestion process also affects the nitrogen and phosphorus fractions in the manure. A
portion of the organic N in the raw manure is decomposed to TAN. Based upon data collected
by Gooch et al. (2007), the amount of TAN in effluent entering long term storage is modeled as
15% greater than that entering the digester. This increase in TAN potentially increases the
ammonia emissions from the storage and field applied effluent (Rotz et al., 2011a).
Phosphorous solubility is also increased during the digestion process. The amount of soluble
phosphorus entering long term storage in the digester effluent is increased 13% compared to
that in untreated manure (Gooch et al., 2007). The increased solubility can affect phosphorus
runoff following field application (Rotz et al., 2011a).
6
Anaerobic digesters increase ownership and operating costs of the farm. Ownership cost is
determined by amortizing the initial investment over the life of the system (Rotz et al., 2011a).
The initial cost is set by the model user along with the economic life and the interest rate used
for amortization. The digester facility is typically depreciated over 20 years, while the associated
equipment for electric generation is depreciated over 10 years. Ownership costs for the
equipment also include annual costs of 0.5% and 6% of the initial investment for insurance and
repairs, respectively. Additional labor for managing the digester was set at 0.5 h per day. No
government assistance or other types of cost sharing were considered in this analysis.
Model Evaluation
Before simulating the effects of using the anaerobic digester, the model was evaluated to
determine how well it represented the performance of an aerobic digester used on an actual
farm in northern New York State. Farm performance was evaluated by comparing simulated
feed production and use to that reported for the farm. Digester performance was evaluated by
comparing predicted biogas and electricity production to that measured on the farm in 2009.
The farm is on 1,020 ha of shallow loam soil located near the city of Syracuse. Crops include
344 ha of alfalfa harvested as silage, 61 ha of grass hay, 485 ha of corn harvested as silage
and dry grain, 91 ha of wheat and 49 ha of soybeans. The wheat and soybeans are sold as
cash crops while all other feeds and straw bedding are used on the farm.
The Holstein dairy herd consists of 1,100 cows, 425 heifers over a year in age, and 500 younger
heifers. An annual milk production of 11,800 kg/cow is maintained with all animals housed in
free stall barns. Manure is scraped from the barn floors and moved into the anaerobic digester
on a daily basis. Effluent from the digester is moved through a liquid solid separator and the
solids are recycled as bedding material. The liquid is stored in an open lagoon for up to 4 mo
until it is applied to cropland. The effluent is broadcast on cropland and rapidly incorporated with
a tillage operation. About 12% of the manure solids are exported from the farm.
Feed production and use
Feed use on the farm was estimated from feed records. Typical diets fed to each animal group
and the number of animals in each
group were used to determine the
amount of each feed used. All
concentrate feeds other than corn and
canola meal were combined as other
concentrate feeds. To cross check
these estimates, the producer was
asked to provide typical amounts of
each feed bought and sold during a
year. This feed information was
combined to obtain the reported feeds
listed in Table 1.
The farm was simulated for 25 years of
historical Syracuse, New York weather
(1981-2005) with crop land areas and
yields set to represent the actual farm.
To meet energy and protein
requirements of the animals, their diets
were supplemented with canola meal
Table 1. Simulated average annual feed production
and use and milk production compared to that
reported as typical on the New York dairy farm.
Feed type Reported Simulated
Hay and haylage, t DM 3,700 3,690
Corn silage, t DM 3,200 3,650
Corn grain, t DM 1,500 1,940
Canola meal, t DM 360 410
Other concentrate, t DM 1,800 1,650
Minerals, t DM 50 66
Tallow, t DM 8 57
Total feed use, t DM 10,600 11,463
Milk production, kg/cow 11,800 11,750
7
and a feed mix with characteristics similar to that fed on the farm. The model was set to allow
milk production to be as high as could be maintained with the available feeds (Rotz et al.,
2011a).
Over the whole herd, total simulated feed use was 8% greater than that reported (Table 1). This
difference was primarily due to an over prediction of corn silage and grain production by the
model compared to that reported. Considering the possible error in determining the reported
values, the model adequately represented the feed production and use of the actual farm.
Simulated milk production was also very similar to that reported for the farm (Table 1).
Biogas production and use
An anaerobic digestion system was installed on the farm that became operational in 2008. The
plug-flow type digester is operated entirely on raw manure produced on the farm. About 110 m3
of manure are loaded each day with a retention time of about 20 days. Most of the biogas is
used to power up to six 30-kW micro-turbine generator sets. About 20% of the biogas is used in
a boiler to produce hot water and heat. Any remaining biogas is burned in a flare.
Biogas and electricity production were recorded on the farm from February 2009 through
January 2010. Total gas production and that used in the boiler, generators, and flare over the
year are reported in Table 2 along with the total electricity produced and used on the farm. Gas
units were converted assuming 6.0 kW-h of energy per m3 of biogas based on a 60% CH4
content.
Simulated total biogas produc-
tion was very similar to that
measured using a VS
conversion efficiency of 33%
(Table 2). Due to operational
problems with the micro-
turbines, the average use of the
generators was only about 54%
of their capacity. To match the
reported electricity generation on
the farm, the generator set
conversion efficiency was set at
19%. Considering that a typical
efficiency for these generator
sets is 25 to 30%, this efficiency
was low. With this assumption
though, simulated gas and
electric production and use were
very similar to that recorded on
this farm during the given year
(Table 2).
Whole-Farm Evaluation
The New York dairy farm was simulated over 25 years of Syracuse weather to compare four
manure management strategies. The first two represented the farm without the use of an
anaerobic digester and the last two included the digester. The first scenario represented a
typical dairy farm where manure is stored in an open tank or lagoon. Manure solids were
removed prior to storage and primarily used for bedding material. To export the equivalent
Table 2. Simulated average annual gas and electric
production compared to that measured on the New York
dairy farm in 2009.[a]
Reported Simulated
Total biogas produced, MW-h[b] 7,007 7,100
Biogas used to heat water, MW-h 1,400 1,420
Biogas burned in flair, MW-h 1,851 1,946
Biogas used by generators, MW-h 3,757 3,735
Electricity produced, MW-h 501 511
[a]Simulation assumed 33% volatile solids conversion
efficiency, 150 kW generator capacity, 54% runtime efficiency,
and 19% efficiency for the turbine-generator sets.
[b]Gas units converted assuming 6 kW-h of energy per m3 of
biogas.
8
amount of solids as obtained from the current farm, only 7% of the undigested solids were
exported. The second strategy was similar except that a sealed cover was placed over the
storage and a flare was used to combust any methane produced within the storage.
For the next two strategies, a manure digester was defined to represent that used on the actual
farm. For the third strategy, the operating characteristics of the system were as defined above
for the current system. Because of the apparent low efficiency of the current system, a fourth
strategy was simulated with an improved efficiency. The runtime efficiency was increased to
85%, i.e., the micro-turbine generator sets were assumed to operate at their capacity 85% of the
time. The conversion efficiency of the generator sets was increased to 25% with unused biogas
being used to heat water. These efficiencies were more representative of values reported for
farm scale systems. These changes in efficiency reduced the amount of biogas burned in the
flare and increased the amount of electricity produced.
Farm Performance
The use of the digester had little effect in the general performance of the farm in terms of feed
and milk production and the resource requirements beyond those directly required for
maintaining the digester.
The only minor effect was
that caused by nitrogen
availability. The increased
volatility of nitrogen
increased loss during
storage and following field
application. Because the
manure liquid on this farm
was normally incorporated
into the soil with a tillage
operation within a few
hours of application, this
loss was minimal. The
small loss though caused a
slight reduction in corn and
straw yields, which lead to
a minor increase in
purchased grain for
supplementing feed rations
(Table 3).
Environmental Impacts
As expected, the primary environmental benefit of covering the manure storage or using a
manure digester system was the reduction of greenhouse gas emissions and the resulting
carbon footprint (Table 4). A sealed cover on the manure storage virtually eliminated methane
emissions from the storage. With a majority of the solids removed from the stored manure by
solid-liquid separation, surface crusting and the resulting potential for nitrous oxide production
did not occur. Thus, covering the storage had no effect on nitrous oxide emissions from this
source. Covering the manure storage reduced VS decomposition during storage, resulting in a
slight increase in carbon dioxide production in the soil following field application. Together these
changes reduced the carbon footprint by about 0.15 kg CO2e/kg ECM. Using the standard
approach of not including biogenic carbon dioxide, this is an 18% reduction. Considering all
biogenic sources and sinks of carbon dioxide, this is a 28% reduction in the carbon footprint.
Table 3. Simulated annual feed production and use for a New
York dairy farm[a] with and without an anaerobic digester.
Without
digester With
digester
Hay and silage production (t DM) 3,686 3,686
Corn silage production (t DM) 3,650 3,650
Corn grain production (t DM) 2,066 2,063
Wheat production (t DM) 303 303
Soybean production (t DM) 124 124
Straw production (t DM) 529 528
Wheat sold (t DM) 303 303
Soybean sold (t DM) 124 124
Grain purchased (t DM) 422 425
Protein/mineral feed purchased (t DM) 1,770 1,770
Total feed use (t DM) 11,594 11,594
[a] Herd of 1,100 cows plus 925 replacement heifers on 1,020 ha of
cropland (344 ha alfalfa, 485 ha corn, 91 ha wheat, 49 ha soybean,
and 61 ha grass) producing 11,800 kg of milk (3.5% fat) per cow.
9
Covering the manure storage also greatly reduced the ammonia emission from the storage, but
this caused a slight increase following field application. All totaled, there was an 8% reduction in
the whole-farm emission of ammonia. With less volatile loss of nitrogen, nitrate leaching and
denitrification losses were increased about 5%. Because manure was incorporated into the soil
soon after field application, the change in phosphorus solubility had no effect on runoff loss.
Table 4. Simulated annual environmental impacts using different manure storages or an
anaerobic manure digestion system on a New York dairy farm[a].
Without digester With digester
Open
storage Enclosed
storage[b] Current
performance[c] Improved
performance[d]
Nutrient Loss
Nitrogen lost by volatilization (kg/ha) 55.5 51.2 57.5 57.5
Nitrogen lost by leaching (kg/ha) 22.8 23.8 22.1 22.1
Nitrogen lost by denitrification (kg/ha) 14.5 15.3 13.7 13.7
Phosphorus loss by runoff (kg/ha) 0.4 0.4 0.4 0.4
Erosion sediment loss (kg/ha) 767 767 767 767
Ammonia Emission
Barn (kg/cow) 26 26 26 26
Manure storage (kg/cow) 8 1 8 8
Field (kg/cow) 29 31 31 31
Total (kg/cow) 63 58 65 65
Methane Emission
Barn (kg/cow) 201 201 201 201
Manure storage and digester (kg/cow) 81 1 23 23
Total (kg/cow) 282 202 224 224
Nitrous Oxide Emission
Barn and manure storage (kg/cow) 0.2 0.2 0.2 0.2
Field (kg/cow) 1.8 1.9 1.8 1.8
Total (kg/cow) 2.0 2.1 2.0 2.0
Net GHG (CO2e)
Housing and animal (kg/cow) 5,092 5,092 5,092 5,092
Manure storage and digester (kg/cow) 2,021 15 560 560
Feed production (kg/cow) 495 506 482 482
Net biogenic CO2 (kg/cow) -4,207 -4,006 -4,054 -4,054
Fuel combustion (kg/cow) 607 607 555 555
Secondary emissions (kg/cow) 2,895 2,894 2,582 2,406
Not allocated to milk (kg/cow) -1,376 -1,128 -1,148 -1,126
Net emission allocated to milk (kg/cow) 5,527 3,980 4,069 3,914
Carbon footprint (kg CO2e/kg milk)
Including all CO2 sources and sinks 0.47 0.34 0.35 0.33
Including only CO2 from fuel combustion 0.83 0.68 0.69 0.68
[a] 1,100 cows plus 925 replacement heifers on 1,020 ha of cropland (344 ha alfalfa, 485 ha corn, 91 ha
wheat, 49 ha soybean, and 61 ha grass) annually producing 11,800 kg of milk (3.5% fat) per cow.
[b] An enclosed manure storage is used with a flare to burn the methane produced.
[c] Simulated biogas and electricity production similar to that measured on the actual farm during the past
year.
[d] Runtime efficiency is increased to 85% and the efficiency of the micro-turbine generator sets is
increased to 25%.
10
Use of the digester provided less benefit in reducing methane emissions compared to an
enclosed storage. Biogas leakage was assumed to be 1% for both the enclosed storage and the
digester. Because much more methane was produced in the digester, a 1% loss was a greater
emission than occurred from the enclosed storage. Compared to the open storage alone, there
was a 72% reduction in methane emission from the digester and storage combined. Use of the
digester had no effect on the potential for nitrous oxide emissions. The carbon dioxide released
through the combustion of methane was partially offset by a reduction in carbon dioxide
emission from soil respiration to provide a reduction in the net biogenic emission. Together,
these changes reduced the carbon footprint by 26% with biogenic carbon dioxide included.
Excluding biogenic carbon dioxide, the footprint was reduced by 17%. The increase in
ammoniacal nitrogen concentration in the manure following digestion created a 3% increase in
ammonia emission from the farm.
Improving the efficiency of the micro-turbine generator sets had no effect on primary sources
and sinks of greenhouse gas from the farm. The amount of electricity produced and used on the
farm was increased, which further reduced purchased electricity. With less electricity purchased,
secondary emissions were reduced. This reduction though, had a relatively small effect on the
whole-farm carbon footprint, and nitrogen and phosphorus losses were not affected (Table 4).
Economics
To obtain a whole-farm economic comparison of the four manure handling systems, a number
of economic parameters and prices were assumed; only those important in this comparison are
presented. All prices were set to reflect long term relative values, not necessarily current values.
The initial cost of the manure storage used on the farm was set at $297,000. To obtain an
annual cost, all structures were amortized over 20 years using a real interest rate of 6%/yr (Rotz
et al., 2011a). No additional annual costs for repairs, maintenance and insurance were included.
For the enclosed manure storage modeled in the second strategy, the initial cost was increased
to $505,000 with all other assumptions remaining the same.
For the last two strategies, the initial cost of the digester was set at $800,000 plus $500,000
invested in the equipment for handing the biogas and generating electricity. The digester was
depreciated over 20 yr and the equipment was depreciated over 10 yr using a real interest rate
of 6%/yr. An annual repair and maintenance cost was included at a rate of 6% of the initial
equipment cost. The equipment was also insured at an annual rate of 0.5% of the initial cost.
With these assumptions, all strategies reduced farm profitability compared to the net return
using a conventional open manure storage (Table 5). Use of a covered manure storage
increased the annual facilities cost with a relatively minor reduction in feed costs. On farms with
a greater need for the nitrogen saved through reduced ammonia emissions, a greater reduction
in feed cost would be obtained. With the use of alfalfa, the crop nitrogen needs were efficiently
met on this farm. Even if the reduction in nitrogen loss reduced purchased fertilizer, the
additional economic benefit would still not likely justify the additional investment in the structure.
However, both an enclosed manure storage and an anaerobic digester system have the non-
economic benefits of odor control and reduced greenhouse gas emissions.
Use of the anaerobic digestion system increased the annual facility cost by 40%, which was
partially offset by the reduction in energy costs. For the system using current performance,
annual energy costs were reduced by $92/cow, which left a reduction in annual profit of $54/cow
(Table 5). With the efficiency improved, the annual savings in energy cost increased to
$138/cow. With this cost savings, profitability approached that of the base farm with an open
storage, but the annual net return was reduced by $9/cow.
11
Conclusions
Simulation analysis of a New York dairy farm showed that use of an anaerobic digestion
system:
Had little effect on feed production and use on this farm where nutrients were recycled and
used efficiently.
Reduced the carbon footprint of the dairy production system by 17 to 26% dependent
primarily upon the method used to calculate the footprint and secondarily on the efficiency
of biogas use.
Reduced annual farm profit by $54/cow, but with an improvement in the efficiency of
converting biogas to electricity, farm profit was reduced by only $9/cow.
Table 5. Simulated annual production costs and net return using different manure storages or
an anaerobic manure digestion system on a New York dairy farm[a].
Without digester With digester
Open
storage Enclosed
storage[b] Current
performance[c] Improved
performance[d]
Production costs
Machinery ($) 258,655 258,842 258,794 258,799
Energy ($) 330,702 330,737 229,072 179,214
Labor ($) 386,962 386,973 388,952 388,952
Seed, fertilizer, and pesticide ($) 479,080 479,080 479,080 479,080
Net purchased feed[e] ($) 690,214 689,437 691,946 691,946
Facilities[f] ($) 405,193 423,323 564,025 564,025
Land charge ($) 252,000 252,000 252,000 252,000
Livestock expenses ($) 315,300 315,300 315,300 315,300
Milk hauling and marketing ($) 299,245 299,245 299,255 299,255
Property tax ($) 16,683 16,683 16,683 16,683
Other unaccounted overhead ($) 200,000 200,000 200,000 200,000
Total ($/cow) 3,304 3,320 3,359 3,314
Income ($/cow) 4,171 4,171 4,171 4,171
Net return ($/cow) 867 851 812 857
[a] 1,100 cows plus 925 replacement heifers on 1,020 ha of cropland (344 ha alfalfa, 485 ha corn, 91 ha
wheat, 49 ha soybean, and 61 ha grass) annually producing 11,800 kg of milk (3.5% fat) per cow.
[b] An enclosed manure storage is used with a flare to burn the methane produced.
[c] Simulated biogas and electricity production similar to that measured on the actual farm during the
past year.
[d] Runtime efficiency is increased to 85% and the efficiency of the micro-turbine generator sets is
increased to 25%.
[e] Total purchased feed cost minus the income from feed sold.
[f] Includes all ownership and operating costs of farm structures and associated equipment including the
anaerobic digester. The initial investment in the digester and associated equipment was $1.3 million
and annual repair and maintenance costs are about $30,000.
12
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Greenhouse gas (GHG) emissions and their potential effect on the environment has become an important national and international issue. Dairy production, along with all other types of animal agriculture, is a recognized source of GHG emissions, but little information exists on the net emissions from dairy farms. Component models for predicting all important sources and sinks of CH(4), N(2)O, and CO(2) from primary and secondary sources in dairy production were integrated in a software tool called the Dairy Greenhouse Gas model, or DairyGHG. This tool calculates the carbon footprint of a dairy production system as the net exchange of all GHG in CO(2) equivalent units per unit of energy-corrected milk produced. Primary emission sources include enteric fermentation, manure, cropland used in feed production, and the combustion of fuel in machinery used to produce feed and handle manure. Secondary emissions are those occurring during the production of resources used on the farm, which can include fuel, electricity, machinery, fertilizer, pesticides, plastic, and purchased replacement animals. A long-term C balance is assumed for the production system, which does not account for potential depletion or sequestration of soil carbon. An evaluation of dairy farms of various sizes and production strategies gave carbon footprints of 0.37 to 0.69kg of CO(2) equivalent units/kg of energy-corrected milk, depending upon milk production level and the feeding and manure handling strategies used. In a comparison with previous studies, DairyGHG predicted C footprints similar to those reported when similar assumptions were made for feeding strategy, milk production, allocation method between milk and animal coproducts, and sources of CO(2) and secondary emissions. DairyGHG provides a relatively simple tool for evaluating management effects on net GHG emissions and the overall carbon footprint of dairy production systems.
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Anaerobic degradation studies for maximum CH//4 production were conducted at 35 degree C and 60 degree C on three types of dairy cattle manure at three different detention times. Digester size was . 72 m**3 with a loading rate of 6. 5 per cent VS. Gas yields ranged from 1. 53 to 1. 68 m**3 gas/m**3 reactor for mesophilic digester and 1. 04 to 2. 34 m**3 gas/m**3 reactor for thermophilic digester.
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In this chapter we present an overview of the development of today’s electric power industry, including the regulatory and historical evolution of the industry as well as the technical side of power generation. Included is enough thermodynamics to understand basic heat engines and how that all relates to modern steam-cycle, gas-turbine, combined-cycle, and cogeneration power plants. A first-cut at evaluating the most cost-effective combination of these various types of power plants in an electric utility system is also presented.
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Methane production using animal waste is becoming economically feasible for intermediate to large scale animal production operations. No general economic assessment can be made, however, since each individual application of the technology must be evaluated as construction methods, labor costs and alternative energy values vary from one production facility to another. The methane yield from a fermentation plant, however, will be relatively constant from site to site, given the same waste type and operating conditions. The expected methane yield from a fermentation plant is needed to evaluate the site-specific economics and for on-site energy use planning and development. The methane productivity of the four major animal waste types has been studied by computer simulation using a validated dynamic mathematical model of the methane fermentation process. Methane productivity is reported on two bases: (a) yield per unit total solids loaded (cubic m CH4/Mg TS) and (b) yield per unit animal live weight (cubic m CH4/Mg LW-day). Results indicate that there are large differences between the waste types and that poultry waste produces the highest yield for animal LW while dairy waste is the least productive on a LW and TS basis. (Refs. 21).
Article
Biogenic emissions of methane (CH4) and nitrous oxide (N2O) from animal manure are stimulated by the degradation of volatile solids (VS) which serves as an energy source and a sink for atmospheric oxygen. Algorithms are presented which link carbon and nitrogen turnover in a dynamic prediction of CH4 and N2O emissions during handling and use of liquid manure (slurry). A sub-model for CH4 emissions during storage relates CH4 emissions to VS, temperature and storage time, and estimates the reduction in VS. A second sub-model estimates N2O emissions from field-applied slurry as a function of VS, slurry N and soil water potential, but emissions are estimated using emission factors. The model indicated that daily flushing of slurry from cattle houses would reduce total annual CH4 + N2O emissions by 35% (CO2 eq.), and that cooling of pig slurry in-house would reduce total annual CH4 + N2O emissions by 21% (CO2 eq.). Anaerobic digestion of slurry and organic waste produces CH4 at the expense of VS. Accordingly, the model predicted a 90% reduction of CH4 emissions from outside stores with digested slurry, and a >50% reduction of N2O emissions after spring application of digested as opposed to untreated slurry. The sensitivity of the model towards storage temperature and soil water potential was examined. This study indicates that simple algorithms to account for ambient climatic conditions may significantly improve the prediction of CH4 and N2O emissions from animal manure.
Integrated Farm System Model: Reference Manual
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Grazing can reduce the environmental impact of dairy production systems. Online. Forage and Grazinglands doi:10 Algorithms for calculating methane and nitrous oxide emissions from manure management
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Rotz, C.A., K.J. Soder, R.H. Skinner, C.J. Dell, P.J. Kleinman, J.P. Schmidt, and R.B. Bryant. 2009. Grazing can reduce the environmental impact of dairy production systems. Online. Forage and Grazinglands doi:10.1094/FG-2009-0916-01-RS. Available at: http://www.plantmanagementnetwork.org/sub/fg/research/2009/impact/. Accessed June 14, 2011. Sommer, S. G., S. O. Petersen, and H. B. Moller. 2004. Algorithms for calculating methane and nitrous oxide emissions from manure management. Nutr. Cycl. Agroecosyst. 69(2): 143‐154.