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


Abstract and Figures

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
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
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]
is the flow rate of VS into the digester (kg/d), is the VS concentration in the
influent (fraction), and
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
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
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 (
) is determined as:
 
   
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]
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]
is the flow of degradable VS (kg/d),
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).
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
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.,
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
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
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.
digester With
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.
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
storage Enclosed
storage[b] Current
performance[c] Improved
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
[d] Runtime efficiency is increased to 85% and the efficiency of the micro-turbine generator sets is
increased to 25%.
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).
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.
Simulation analysis of a New York dairy farm showed that use of an anaerobic digestion
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 $9/cow.
Table 5. Simulated annual production costs and net return using different manure storages or
an anaerobic manure digestion system on a New York dairy farm[a].
Without digester With digester
storage Enclosed
storage[b] Current
performance[c] Improved
Production costs
Machinery ($) 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.
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Masters, G.M. 2004. Renewable and efficient electric power systems. Hoboken, NJ: Wiley.
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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.
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nitrous oxide emissions from manure management. Nutr. Cycl. Agroecosyst. 69(2):
... Methane emissions from stored liquid sludge is calculated with the CH 4 emission model as used in the Integrated Farm Systems Model (IFSM) for manure management in beef and dairy production systems (Chianese et al., 2009). This has been used previously to assess the impact of GHG reduction strategies in agriculture (Rotz and Hafner, 2011;Dutreuil et al., 2014). Equation 1 is used to calculate CH 4 emission from anaerobic stored livestock liquid manure and digestate from biogas plants if concentration volatile solids (VS) and air temperature is known (Baral et al., 2018): ...
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Worldwide dairy processing plants produce high volumes of dairy processing sludge (DPS), which can be converted into secondary derivatives such as struvite, biochar and ash (collectively termed STRUBIAS). All of these products have high fertilizer equivalent values (FEV), but future certification as phosphorus (P)-fertilizers in the European Union will mean they need to adhere to new technical regulations for fertilizing materials i.e., content limits pertaining to heavy metals (Cd, Cu, Hg, Ni, Pb, and Zn), synthetic organic compounds and pathogens. This systematic review presents the current state of knowledge about these bio-based fertilizers and identifies knowledge gaps. In addition, a review and calculation of greenhouse gas emissions from a range of concept dairy sludge management and production systems for STRUBIAS products [i.e., biochar from pyrolysis and hydrochar from hydrothermal carbonization (HTC)] is presented. Results from the initial review showed that DPS composition depends on product type and treatment processes at a given processing plant, which leads to varied nutrient, heavy metal and carbon contents. These products are all typically high in nutrients and carbon, but low in heavy metals. Further work needs to concentrate on examining their pathogenic microorganism and emerging contaminant contents, in addition to conducting an economic assessment of production and end-user costs related to chemical fertilizer equivalents. With respect to STRUBIAS products, contaminants not present in the raw DPS may need further treatment before being land applied in agriculture e.g., heated producing ashes, hydrochar, or biochar. An examination of these products from an environmental perspective shows that their water quality footprint could be minimized using application rates based on P incorporation of these products into nutrient management planning and application by incorporation into the soil. Results from the concept system showed that elimination of methane emissions was possible, along with a reduction in nitrous oxide. Less carbon (C) is transferred to agricultural fields where DPS is processed into biochar and hydrochar, but due to high recalcitrance, the C in this form is retained much longer in the soil, and therefore STRUBIAS products represent a more stable and long-term option to increase soil C stocks and sequestration.
... Losses include NH 3 volatilization, denitrification (N 2 O, NO, N 2 ) and leaching losses of N, erosion of sediment, and run-off of sediment-bound and dissolved P across farm boundaries. Carbon dioxide, CH 4 , and N 2 O (Chianese et al., 2009a(Chianese et al., , 2009b(Chianese et al., , 2009c, nutrient losses (Rotz et al., 2014), crop yields (Rotz et al., 2001 and2002) and feed production (Rotz and Hafner, 2011). ...
CONTEXT To meet the nutritional and environmental needs of a growing population, dairy producers must increase milk production while minimizing the farm-gate environmental impact and adapting to the effects of climate change. OBJECTIVE Here we comprehensively assess the effects of climate change on the environmental performance and productivity of three typical US dairy farms, and evaluate the potential benefits of adaptation strategies and implementation of Beneficial Management Practices (BMPs) for mitigating these effects and the potential increases in environmental impact. METHODS Using the Integrated Farm System Model (IFSM), we predicted the productivity and environmental impact of these baseline farms under current emission scenarios and climate projections of 6 general circulation models (GCM), for high and low emission scenarios. We simulated farm-specific BMPs for current and future climate conditions for both unadapted and ‘adapted’ field cultivation plans, based on experiences from other climate locations. Finally, the IFSM predictions were compared to those of two other process-based models to test result robustness. RESULTS AND CONCLUSIONS We find that the environmental impact of the three northern US dairy farms (New York, Pennsylvania, and Wisconsin) generally increases by mid-century, if no mitigation measures are taken. Overall, feed production is maintained, as decreased corn grain yields are compensated by increased forage yields. Adoption of farm-specific Beneficial Management Practices can substantially reduce the GHG emissions and nutrient losses from dairy farms under current climate conditions and stabilize the environmental impact in future climate conditions, while maintaining farm productivity (milk and feed production). A comparison of three models corroborates the estimated reductions in methane and ammonia emissions associated with BMPs, as well as the relative trend in P-loss reduction. SIGNIFICANCE This study provides a holistic assessment of the impacts of climate change on dairy production systems focusing on both feed production and environmental impacts. It demonstrates the interest of BMPs to both reduce GHG emissions and contribute to more resilient farming systems in a changing climate.
... Existing models for estimating CH 4 emissions from liquid manure management all have significant limitations. A common approach is to link CH 4 production to OM loading using a first-order model (Section 2.2) and with conversion rate linked to temperature, typically through the Van't Hoff-Arrhenius equation mentioned in Section 3.5 (Khan et al., 1997;Mangino et al., 2001;Rotz & Hafner, 2011 ;Dutreuil et al., 2014). In addition to a site-specific calculation of temperature, which allows for a distinction between indoor and outdoor storage, some versions include the effect of OM degradability Sommer et al., 2004). ...
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National inventories of methane (CH4 ) emission from manure management are based on guidelines from the Intergovernmental Panel on Climate Change using country-specific emission factors. These calculations must be simple and, consequently, the effects of management practices and environmental conditions are only crudely represented in the calculations. The intention of this review is to develop a detailed understanding necessary for developing accurate models for calculating CH4 emission from liquid manure, with particular focus on the microbiological conversion of organic matter to CH4 . Themes discussed are: 1) The liquid manure environment; 2) Methane production processes from a modelling perspective; 3) Development and adaptation of methanogenic communities; 4) Mass and electron conservation; 5) Steps limiting CH4 production; 6) Inhibition of methanogens; 7) Temperature effects on CH4 production; and 8) Limits of existing estimation approaches. We conclude that a model must include calculation of microbial response to variations in manure temperature, substrate availability and age, and management system, because these variables substantially affect CH4 production. Methane production can be reduced by manipulating key variables through management procedures, and the effects may be accounted for by including a microbial component in the model. When developing new calculation procedures, it is important to include reasonably accurate algorithms of microbial adaptation. This review presents concepts for these calculations, and ideas to how these may be carried out. A need for better quantification of hydrolysis kinetics is identified, and the importance of short- and long-term microbial adaptation is highlighted. This article is protected by copyright. All rights reserved.
... Based on the fact that dairy production residues are a crucial part of the GHG emissions problem (FAO, 2010), effective treatment and management options to reduce the emissions of these residues would transform a problem into an opportunity by applying treatment and management options to reduce emissions Zucchella & Previtali, 2019;Treichel et al., 2020). To improve the production chain and use all available resources within the systems, the integration and application of new technologies such as manure treatment by means of anaerobic digestion (AD) for biogas production is a valid option for reducing the GHG footprint of farms (Rotz & Hafner, 2011). ...
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Methane emissions from livestock manure are primary contributors to GHG emissions from agriculture and options for their mitigation must be found. This paper presents the results of a study on methane emissions from stored liquid dairy cow manure during summer and winter storage periods. Manure from the summer and winter season was stored under controlled conditions in barrels at ambient temperature to simulate manure storage conditions. Methane emissions from the manure samples from the winter season were measured in two time periods: 0 to 69 and 0 to 139 days. For the summer storage period, the experiments covered four time periods: from 0 to 70, 0 to 138, 0 to 209, and 0 to 279 continuous days, with probing every 10 weeks. Additionally, at the end of all storage experiments, samples were placed into eudiometer batch digesters, and their methane emissions were measured at 20 °C for another 60 days to investigate the potential effect of the aging of the liquid manure on its methane emissions. The experiment showed that the methane emissions from manure stored in summer were considerably higher than those from manure stored in winter. CH4 production started after approximately one month, reaching values of 0.061 kg CH4 kg⁻¹ Volatile Solid (VS) and achieving high total emissions of 0.148 kg CH4 kg⁻¹ VS (40 weeks). In winter, the highest emissions level was 0.0011 kg CH4 kg⁻¹ VS (20 weeks). The outcomes of these experimental measurements can be used to suggest strategies for mitigating methane emissions from manure storage.
... Some of the most comprehensive evaluations of crop yield across multiple years of weather were done by Rotz et al. (2001Rotz et al. ( , 2002. Predicted yield and feed production have also been evaluated for an actual, commercial farm in New York by Rotz and Hafner (2011). This commercial farm was originally used as the basis for setting up the New York farm in the current study. ...
Assessing and improving the sustainability of dairy production is essential to secure future food production. Implementation of Beneficial Management Practices (BMP) can mitigate GHG emissions and nutrient losses and reduce the environmental impact of dairy production, but comprehensive, whole-farm studies that evaluate the efficacy of multiple BMPs to reduce multiple environmental impacts and that include an assessment of productivity and farm profitability, are scarce. We used a process-based model (IFSM) to assess the efficacy of (10+) individual BMPs to reduce the carbon (C) footprint expressed per unit of milk produced of two model dairy farms, a 1500 cow farm and a 150 cow farm, with farming practices representative for the Great Lakes region. In addition to the C footprint, we assessed the effect of BMP implementation on the reactive nitrogen (N) footprint and total phosphorus (P) losses (per unit of milk produced), as well as milk production and farm profitability. We evaluated individual farm-component specific BMPs, that is, 5 dietary manipulations, 3 (150 cow farm) or 4 (1500 cow farm) manure interventions, and 6 field interventions, as well as an integrated whole-farm mitigation strategy based on the best performing individual BMPs. Our results show that reductions in the C footprint expressed per unit of milk are greatest with individual manure management interventions (4–20% reduction) followed by dietary manipulations (0–12% reduction) for both farm types. Field management BMPs had a modest effect on reducing this footprint (0–3% reduction), but showed substantial potential to reduce the reactive N footprint (0–19% reduction) and P losses (1–47% reduction). We found that the whole-farm mitigation strategy can substantially reduce the C footprint, reactive N footprint and total P loss of both farms with predicted reductions of approximately 41%, 41% and 46% respectively, while increasing milk production and the net return per cow by approximately 11% and 27%. To contextualize IFSM predictions for the whole-farm mitigation, we compared components of IFSM predictions to those of three other process-based models (CNCPS, Manure-DNDC and EPIC). While we did observe differences in model predictions for individual flows (particularly P erosion and P leaching losses), with exception of the total P loss, the models generally predicted similar overall mitigation potentials. Overall, our analysis shows that an integrated set of BMPs can be implemented to reduce GHG emissions and nutrient losses of dairy farms in the Great Lakes region without sacrificing productivity or profit to the farmer.
... The sub-model of the Integrated Farm Systems Model (IFSM) for CH 4 emissions from manure management in beef and dairy production systems (Chianese et al., 2008;USDA-ARS, 2009) shares several features with the model of Sommer et al. (2004). The IFSM has been used in several studies to assess the impact of GHG reduction strategies for dairy and beef farms (e.g., Rotz and Hafner, 2011;Dutreuil et al., 2014). The model performance in predicting CH 4 emissions during manure storage has not been extensively verified, but Chianese et al. (2009) did predict annual CH 4 emissions using 25 years of weather data and found that the results were in good agreement with an on-farm monitoring study (Husted, 1994), in which observed daily CH 4 emissions from a cattle slurry storage tank varied between 5 and 35 g CH 4 m −3 d −1 during a 12-month monitoring period. ...
Greenhouse gas emissions during storage of manure and digestates: Key role of methane for prediction and mitigation Khagendra R. Baral1, Guillaume Jégo2, Barbara Amon3, Roland Bol4, Martin H. Chantigny2, Jørgen E. Olesen1 and Søren O. Petersen1* 1Department of Agroecology, Aarhus University, Tjele, Denmark; 2Quebec Research & Development Centre, Agriculture and Agri-Food Canada, Québec, Canada; 3Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Potsdam, Germany 4Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, Jülich, Germany *Corresponding author. E-mail: Abstract Treatment of liquid manure and other wastes by anaerobic digestion (AD) adds to renewable energy targets, and it is thus a favorable strategy for greenhouse gas (GHG) mitigation. Both untreated manure and digestates are typically stored for a period in order to recycle nutrients for crop production, and emissions of methane (CH4), nitrous oxide (N2O) and ammonia (NH3) during storage contribute to the overall GHG balance. We determined emissions of all three gases during summer and autumn storage of digestates and untreated manure in pilot-scale experiments. Using these and other data, GHG balances were calculated for treatment, post-treatment storage, and field application. The GHG mitigation potential of AD was demonstrated, but CH4 emissions during storage dominated the overall GHG balance irrespective of treatment; hence for GHG inventories and mitigation efforts, the correct estimation of this source is critical. Current inventory guidelines from the Intergovernmental Panel on Climate Change (IPCC) estimate CH4 emissions from manure management based on a simple classification of livestock production systems, volatile solids (VS) excreted, and annual average temperature, and the effects of treatment and management at farm level are therefore not accounted for in any detail. Two empirical models were evaluated, which instead calculate VS degradation and storage temperature with daily time steps; both models were based on concepts presented by Sommer et al. [2004; Nutr. Cycl. Agroecosys. 69: 143-154]. Parameters for the Arrhenius temperature relationship of CH4 production, i.e., apparent activation energy, E_a, and pre-exponential factor, A, could be selected, for which cumulative CH4 emissions calculated with the two models approached observed emissions. However, the magnitude of emissions during a warm period were not well reproduced, and the parameters identified for the two models differed. Sensitivity analyses showed that deviations from observations could not be explained by errors in manure storage temperature. The results thus suggest that CH4 emissions cannot be predicted from VS and temperature alone, i.e., that the methanogenic potential changes during storage. Determination of parameters for estimation of CH4 emissions from manure management is discussed with reference to recent literature.
... The farm was simulated over 25 years of recent historical weather for Syracuse, New York (1981to 2005. Further details related to this farm can be found in Rotz and Hafner (2011). ...
Conference Paper
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Farms both produce greenhouse gas emissions that drive human-induced climate change and are impacted by that climate change. Process-level modeling at the farm scale provides a method for evaluating strategies for both mitigating emissions and adapting to climate change. The Integrated Farm System Model (IFSM) simulates representative crop, beef or dairy farms over many years of weather to predict performance, economics and environmental impacts including various gas emissions and a farm-gate life cycle assessment of carbon, energy, water and reactive nitrogen footprints of the feed, meat or milk produced (Rotz et al., 2014). IFSM provides a useful tool for evaluating farm emissions and mitigation strategies and the effects of climate variability on the sustainability of production systems under a changing climate.
In recent years, many livestock farms have transitioned from total confinement housing to a pasture-based system in an effort to reduce labor and production costs and improve profitability. There is a growing interest in biogas recovery among livestock producers to reduce energy costs and manure odors but the economic benefits of anaerobic digestion (AD) on small farms is not well known. A comprehensive analysis was conducted using the Integrated Farm System Model (IFSM), to describe, evaluate and compare the farm performance and economic impacts of representative dairy farms in Michigan transitioning from conventional confinement to seasonal- and pasture-based systems, and evaluate the potential for integration of an AD in the confinement and seasonal pasture systems. The results in farm performance present higher milk production per kilogram of feed in the confinement systems, followed by the seasonal pasture and the annual pasture systems. In the economic analysis, the annual pasture-based system had the greatest net return to management and unpaid factors followed by the seasonal pasture and confinement systems. The addition of an AD on a 100-cow, total confinement dairy decreased the net return to management and unpaid factors by 20%. When anaerobic digestion was added to the seasonal pasture with an increased land base for cash crop production and an imported manure volume equivalent to a 500-cow dairy, the net return to management and unpaid factors increased 269% compared to the seasonal pasture dairy alone.
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Solid-liquid separation of manure is a method to produce nutrient and dry matter rich fractions with higher volumetric methane potential than that of the original liquid manure. Centrifugation and chemical precipitation and flocculation are efficient options for such separation. Centrifugation efficiency depends on factors such as manure type, G-force, and dewatering volume, while chemical precipitation and flocculation depend on the amount and type of chemicals and polymers used. We assess all these factors in this study. The methane yields of the solids from centrifugation and precipitation were assessed by batch digestion. Dewatering volume and G-force had great influence on separation efficiency and on the chemical composition of the solids. Centrifugation transferred increasing amounts of nutrients and dry matter to the solid fraction as gravitational force increased to approximately 2200G. However, increasing gravitational force beyond 2047G did not significantly improve separation efficiency. The quantity of solids and separation efficiency of dry matter and nutrients varied for different manure types. Separation efficiencies for total N and dry matter greatly depended on the manure's dry matter content, while separation efficiency for total P was little affected by the same factors. Because different manure types were used for the tests with precipitation and flocculation, it was impossible to determine the effect of changing the chemicals. However, the separation efficiencies achieved for N and P were higher than those achieved with centrifuged manure of the same dry matter content. The methane yield from the solids separated by chemical precipitation and flocculation were significantly higher than the yield from centrifuged solids. The yields from the solids produced by centrifugation of pig manure were 161 to 186 L CH4/kg VS compared to 253 L CH4/kg VS from centrifuged dairy cow manure, while the yields from the solids produced by coagulation and flocculation were 392 to 404 L CH4/kg VS.
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Alternative methods for applying livestock manure to no-till soils involve environmental and economic trade-offs. A process-level farm simulation model (Integrated Farm System Model) was used to evaluate methods for applying liquid dairy (Bos taurus L.) and swine (Sus scrofa L.) manure, including no application, broadcast spreading with and without incorporation by tillage, band application with soil aeration, and shallow disk injection. The model predicted ammonia emissions, nitrate leaching, and phosphorus (P) runoff losses similar to those measured over 4 yr of field trials. Each application method was simulated over 25 yr of weather on three Pennsylvania farms. On a swine and cow-calf beef operation under grass production, shallow disk injection increased profit by $340 yr(-1) while reducing ammonia nitrogen and soluble P losses by 48 and 70%, respectively. On a corn (Zea mays L.)-and-grass-based grazing dairy farm, shallow disk injection reduced ammonia loss by 21% and soluble P loss by 76% with little impact on farm profit. Incorporation by tillage and band application with aeration provided less environmental benefit with a net decrease in farm profit. On a large corn-and-alfalfa (Medicago sativa L.)-based dairy farm where manure nutrients were available in excess of crop needs, incorporation methods were not economically beneficial, but they provided environmental benefits with relatively low annual net costs ($13 to $18 cow). In all farming systems, shallow disk injection provided the greatest environmental benefit at the least cost or greatest profit for the producer. With these results, producers are better informed when selecting manure application equipment.
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Incorporating managed rotational grazing into a dairy farm can result in an array of environmental consequences. A comprehensive assessment of the environmental impacts of four management scenarios was conducted by simulating a 250-acre dairy farm typical of Pennsylvania with: (i) a confinement fed herd producing 22,000 lbs of milk per cow per year; (ii) a confinement fed herd producing 18,500 lbs; (iii) a confinement fed herd with summer grazing producing 18,500 lbs; and (iv) a seasonal herd maintained outdoors producing 13,000 lbs. Converting 75 acres of cropland to perennial grassland reduced erosion 24% and sediment-bound and soluble P runoff by 23 and 11%, respectively. Conversion to all perennial grassland reduced erosion 87% with sediment-bound and soluble P losses reduced 80 and 23%. Ammonia volatilization was reduced about 30% through grazing, but nitrate leaching loss increased up to 65%. Grazing systems reduced the net greenhouse gas emission by 8 to 14% and the C footprint by 9 to 20%. Including C sequestration further reduced the C footprint of an all grassland farm up to 80% during the transition from cropland. The environmental benefits of grass-based dairy production should be used to encourage greater adoption of managed rotational grazing in regions where this technology is well adapted.
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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.
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.
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.
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).
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
  • C A Rotz
  • M S Corson
  • D S Chianese
  • F Montes
  • S Hafner
  • R Jarvis
  • C U Coiner
Rotz, C.A., M.S. Corson, D.S. Chianese, F. Montes, S. Hafner, R. Jarvis, and C.U. Coiner. 2011a. Integrated Farm System Model: Reference Manual. Available at (verified 11 March 2011). USDA Agricultural Research Service, University Park, PA.
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
  • C A Rotz
  • K J Soder
  • R H Skinner
  • C J Dell
  • P J Kleinman
  • J P Schmidt
  • R B Bryant
  • S G Sommer
  • S O Petersen
  • H B Moller
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: 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.