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Assessing the Economic Aspects of Anaerobic Digester Adoption on U.S. Swine Operations
By
Brent A. Gloy October 19, 2011
Associate Professor Department of Agricultural Economics
Purdue University
Final Report for a Cooperative Agreement between the Economic Research Service, U.S. Department of Agriculture and Purdue University
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Assessing the Economic Aspects of Anaerobic Digester Adoption on U.S. Swine Operations Anaerobic digestion (AD) of livestock waste presents a promising technological response to the challenges of renewable energy production, greenhouse gas mitigation, and livestock waste management. While AD systems have been commercially available for many years, they have not been widely adopted on U.S. livestock operations. Among livestock species, AD systems have been more rapidly adopted by dairy operations. According to the U.S. EPA’s AgSTAR program website, http://www.epa.gov/agstar/projects/index.html, dairy operations account for 140 of the 171 active sites, whereas swine installations account for 23. This stark difference in adoption rates raises many questions about why the systems have been adopted so much more widely amongst dairy operations. While there are many possible explanations for the differences, a common perception is that the economics of adopting AD on dairy operations is more favorable than on swine operations. However, a 2007 NRCS study that examined the energy production costs on a variety of digester operations concluded that:
“The case study evaluation indicates that producing energy from swine facilities can be achieved at a lower cost than from dairy facilities.” Page 5
If accurate, such conclusions would cast doubt on whether economic considerations are truly the reason that few swine operations have chosen to adopt AD systems. This would cause one to question whether other factors are discouraging swine operations from adopting AD systems. While the NRCS study notes that the costs of generation for all types of AD systems are in excess of the cost of purchased electricity, it is perplexing why dairy operations, whose costs of generation would be even higher, have chosen to adopt AD at a more rapid pace. As a result, it is worthwhile to carefully re‐examine the costs of adopting AD systems on swine operations. The NRCS study also notes that the costs of electrical generation typically account for 36% of the capital costs and a large share of the annual operating and maintenance costs associated with AD systems. They suggest that farms should consider other possible benefits of digesters that might be obtained without electrical generation. These could include substitution for other fuels such as propane, odor reduction, or carbon credits. However, in all cases it is important for the farmer to accurately understand the costs of adopting an AD system in order to obtain these benefits. Presently there is little information available to make such an assessment. This again makes it important to carefully re‐asses the economics of AD adoption on swine operations. Given policy maker interest in encouraging farmers to use technologies such as AD, it is important to understand the economic parameters associated with AD so that one might be able to accurately predict how farmers would respond to changes in policy incentives for AD installation. For instance, in order to understand how farmers would respond to incentive
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payments for greenhouse gas emission reductions, one must have an accurate model to determine the costs of adopting AD systems on a wide range of farm types.
Objective and Approach
This study addresses these issues by carefully examining the technical and economic feasibility of installing anaerobic digestion systems on various types of swine operations. The primary objective of the work is to obtain the information and data necessary to begin to parameterize models to examine how potential climate change legislation would affect digester adoption on hog operations. The results of the work are based upon an analysis of the existing literature, published data on swine AD systems, and interviews with industry experts. The results of the study shed light on factors that should be considered when applying models to examine the adoption of swine AD systems including technical barriers and economic factors. The study provides estimates of the economic parameters that are required to estimate economic models that examine the adoption of AD systems on U.S. swine operations. The analysis reveals that many cost measures frequently reported in studies discussing the adoption of swine AD systems are inaccurate, misdirected, or based on too few observations to be reliable. The current study frames these issues and provides parameter estimates that can be used to more accurately estimate the adoption of swine AD systems. It also suggests that analysts should consider evaluating how benefits such as odor control would influence AD adoption on swine operations. The approach used seeks to answer the question of which types of farms could potentially adopt AD systems and then analyzes data to determine how to obtain the best parameter estimates for models which seek to examine the economics of adoption on these farms. The analysis makes use of data from 17 different swine AD systems. While not a complete sampling of swine AD systems, it represents a comprehensive collection of swine AD data. Collection of additional data is complicated due to non‐participation from operators. Many swine AD operations have been previously contacted and provided their information to other researchers. Often, information about a single operation was found in multiple reports. Additional phone‐based data collection from these operations was unlikely to result in meaningful data quality improvements. For operations that had not previously been reported, many were unwilling to participate, or were not able to be contacted. Instead, information was obtained from industry experts and detailed price quotes were obtained from an AD designer that has developed a large number of the existing U.S. swine AD systems. It is believed that the data represent the best available data that can be collected with existing resources.
AD Economic Background In order to accurately parameterize a swine AD model one must derive parameters associated with capital costs, operating costs, and energy production. For instance, studies by Gloy and
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Key and Sneeringer point out that capital costs, operating costs, and energy sales are the primary economic considerations in AD systems. Both studies then examined how the potential sale of carbon credits would influence AD adoption by dairy operations. In general, these basic factors also apply to the adoption of swine AD systems, but some important caveats apply. In the previous studies the estimation of capital costs was accomplished by building a relationship between dairy herd size and previous estimates of total capital costs. The findings presented in this report suggest that a more nuanced approach is necessary for swine AD systems. Specifically, a more refined measure of size is required to accurately estimate capital costs on swine AD systems. This is a result of the fact that several different types of swine production take place in the U.S. Rather than relying on capital cost estimates per pig, all hog operations should be converted to animal units or a standardized unit of manure production for comparison. Second, unlike dairy, there is a much greater tendency to use covered lagoon digesters in the swine industry. In the case of dairy, Gloy focused entirely on complete mix type digester systems, the type of AD system installed on the vast majority of dairy operations. Unlike Gloy, Key and Sneeringer estimated capital costs for swine digesters based upon whether the system was a lagoon or pit based digester system. In the case of swine, this is necessary for robust results. However, as they note in their analysis the data for the hog capital cost estimation was quite limited producing very little explanatory power with respect to capital costs. Third, many of the existing swine digesters do not contain an energy generation component. Rather, a driving benefit cited in many case studies is odor control. This suggests that one should consider estimating models that account for energy production separately or is flexible enough to make the adoption of an energy production unit optional. Finally, it would be desirable to derive a benefit curve that shows how adoption would vary depending on the value that swine operations place on odor control as well as with benefits associated from greenhouse gas emission reductions. The next section of the report identifies some of the key technical factors that will influence adoption, most notably the type of manure storage and handling system on the operation. These factors are important when identifying which types of swine operations would be potential candidates for an AD system. Then, a thorough presentation of the previous swine AD case studies is characterized and summarized. The analysis focuses on summarizing the case studies according to the categories of key variables that are necessary to model AD adoption on swine operations. The final section summarizes the findings of the research.
Identifying Potential Candidates for AD Systems
There are many different approaches that can be used to identify swine operations that are viable candidates for an AD system. One such screening system has been developed by the U.S. EPA’s AgSTAR program. The program’s initial screening form that can be used to help farmers assess the potential of installing an AD system. The screening form identifies some of the data
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that would be useful to evaluate the potential of AD systems. The key elements include the type of farm and numbers of animals on the farm, the type of confinement facility and manure collection/storage system, and the energy use on the farm. These broad categories are useful when evaluating the potential for the AD on swine operations. Manure Production The volume of manure to be processed in a digester plays a key role in determining the capital costs of the digester. Different types of swine animals (sows, finishers, nursery, etc.) generate manure in different volumes. Large animals generate more manure per animal. Because some swine animals are raised for finishing and some for breeding the American Society of Agricultural Engineers (ASAE) provides manure production estimates based upon the amount of manure produced per finished animal (Table 1). These estimates show that the typical feeder pig will be fed for approximately 156 days after weaning. Table 1. Manure Production per Finished Animal for Nursery and Grow/Finish Swine.
Finished Animal
Days in Stage
Total Solids (lbs)
Volatile Solids (lbs)
Manure (lbs)
Manure (ft3)
Moisture
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐Per Finished Animal‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ Nursery Pig 36 10 8.7 8.7 1.4 90% Grow/finish 120 120 99 1200 20 90%
Source: ASAE. “Manure Production and Characteristics.” American Society of Agricultural Engineers, St. Joseph, MI, March 2005, ASAE D384.2. The estimates of manure production for breeding livestock are based on manure production per animal per day (Table 2). This shows that lactating sows produce slightly more manure than gestating sows. In order to accurately characterize the manure volume on a swine operation one must consider the combinations of different types of animals present on a given farm. The common types of swine production systems in the U.S. are farrow‐to‐finish, farrow‐to‐wean, farrow and nursery, nursery, and grow‐finish operations. Table 2. Manure Production per Day per Animal for Sows and Boars.
Breeding Animals
Total Solids (lbs)
Volatile Solids (lbs)
Manure (lbs)
Manure (ft3)
Moisture
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐Per Animal Per Day‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ Gestating Sow 1.1 0.99 11 0.18 90% Lactating Sow 2.5 2.3 25 0.41 90% Boar 0.84 0.75 8.4 0.13 90%
Source: ASAE. “Manure Production and Characteristics.” American Society of Agricultural Engineers, St. Joseph, MI, March 2005, ASAE D384.2. The predominance of various types of swine production systems has undergone a dramatic shift in recent years. Key and McBride report that farrow‐to‐finish operations, once the most popular style of production system, accounted for only 31% of swine farms in 2004. Farrow‐to‐finish systems are being replaced by those that focus specialized aspects of production such as
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breeding, gestation, and weaning. These operations are often referred to as farrow‐to‐wean, farrow and nursery, and nursery operations. In 2004 nearly 40% of U.S. swine operations are grow‐finish operations and that these operations account for nearly 77% of U.S. swine (Key and McBride). One of the challenges in understanding the volume of manure and capital costs associated with different systems is that operations do not typically report all of the different types of animals present on their farm. For instance, operations that include farrowing typically report size on the basis of sows. Likewise, as can be seen from Tables 1 and 2 the manure production from different types of animals can differ dramatically. This means that in order to compare capital costs across AD systems it is necessary to calculate size in terms of animal units. An animal unit is defined as 1,000 pounds of live weight animals. The most direct method for calculating the animal units on a farm operation is to multiply the exact number of each type of animal in the system by the typical weight of the animals and then divide by 1,000 pounds. The result is the number of animal units in the system. For instance, if the facility contains 500 lactating sows each weighing 420 pounds and 2,500 gestating sows weighing 440 pounds the total animal units in the system is calculated as:
AU = 1,310 = (420*500 + 440*2,500)/1000
Of course, if the system also includes a nursery one must also include any growing pigs as well as any boars in the system. This makes accurate calculation of the number of animal units in the system challenging because few operations or previous studies report this level of detail about the operation. For instance, many operations will simply report that they have a 4,000 sow farrow‐to‐wean operation. Chastain, Camberato, Albrecht and Adams address this problem by calculating animal units on the basis of typical weights associated with different types of swine production units. Their method relies on the standards used in South Carolina’s agricultural animal facility permitting process. In this framework the average weight of a typical farrow‐to‐finish swine operation production unit is assumed to be 1,417 pounds per sow (Table 3). This estimate includes the weight of the sows, off‐spring in various stages of production, and boar stock. The estimates are clearly approximations, but are a reasonable first‐step in being able to compare animal units across different types of swine production enterprises. One can observe from Table 3 that 1 sow in a farrow‐to‐feeder production system is about 36% (0.522/1.417) of the animal units associated with 1 sow in a farrow‐to‐finish operation.
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Table 3. Average Weight of Different Swine Production Systems.a
Farm Type Production Unit
Average Live Weight per
Production Unit (lbs)
Animal Units per
Production Unit
Manure Production per Animal Unit (lbs per day per 1,000 lbs of live weight)
Farrow‐to‐wean Sow 433 0.433 60
Nursery Pig 30 0.030 84
Farrow‐to‐feeder Sow 522 0.522 64
Farrow‐to‐finish Sow 1,417 1.417 77
Feeder to Finish Hog 135 0.135 84 a Source, Table 3.1, Chastain, J.P., J.J Camberato, J.E. Albrecht, and J. Adams, III. Swine Manure Production and Nutrient Content. Chapter 3 in the Confined Animal Manure Managers Program, Clemson University. Available at: http://www.clemson.edu/extension/livestock/livestock/camm/index.html It is still somewhat difficult to compare digestion system costs on the basis of animal units because the manure production for different types of animal units varies. This can be seen in the last column on Table 3 which shows that an animal unit in a feeder‐to‐finish system has a high rate of manure production relative to a farrow‐to‐wean system. This issue can be addressed by creating a standardized manure unit for each different production unit (Table 4). The base of the manure unit is arbitrary, so a standard manure production unit was chosen to be equal to 100 pounds of manure production per day. Table 4. Manure Units for Various Types of Swine Production Systems.
Farm Type Production Unit Manure Units per Production Unita
Farrow‐to‐wean Sow 0.2598
Nursery Pig 0.0252
Farrow‐to‐feeder Sow 0.3341
Farrow‐to‐finish Sow 1.0911
Feeder to Finish Hog 0.1134 a One manure unit represents 100 pounds of hog manure per day per production unit. The values in Table 3 were used to standardize the manure generation into manure units per production unit and are shown in table 4. The manure units are calculated by multiplying the animal units per production unit by the manure production per animal unit and dividing by 100. For instance, one sow unit in a farrow‐to‐finish operation generates 109 pounds of manure per day. This estimate includes the manure produced by the sow, her offspring, and other breeding animals in the system. This measure standardizes the amount of manure across the different type of livestock systems. For instance, the total manure production from 4.2 sow units in a farrow‐to‐wean system is roughly equivalent to the total manure production associated with 1 sow unit in a farrow‐to‐finish system.
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These measures of animal units and manure units for each type of swine production system can be used to estimate capital cost parameters for swine AD systems. This is particularly important when interpreting case study data. Use of these units should provide more accurate estimates of capital costs than one derived from simply estimating capital costs from the total number of swine animals in the herd or not accounting for differences across types of swine animals. Manure Storage and Handling The type of production taking place on the operation will influence the amount of manure that is available for digestion. Likewise, the type of manure storage and handling system is a critical determinant of the ability to incorporate an AD system. The AgSTAR screening form identifies the possible storages as anaerobic lagoon with secondary storage, combined storage and treatment lagoon, storage tank or pond, and deep pit. The primary types of manure handling systems in use today include flush systems with lagoon storage and deep‐pit systems with storage underneath the barn. It is also important to realize that significant changes have occurred in the geographic location of hog production. The heartland region contains 48.9% of feeder‐to‐finish farms and produced 45.2 percent of the output in 2004. The Southeast had 10.7% of these farms and accounted for 24.7% of the output. This is important because the manure handling systems used in these regions tends to differ (Key and McBride). The quad system is one of the most common systems currently used to finish swine in the upper Midwest (Heber). This system consists of a single building broken into 4 different rooms. Each room holds approximately 1,000 finishing pigs. The manure storage is a deep pit system in which manure falls through slatted floors into a pit which can typically hold 180 days of manure production. In some cases, two of these buildings will be built in proximity to each other and is often referred to as a double quad system. The pit systems, also frequently referred to as slurry based systems, tend to be most common in the north‐central region of the U.S. (Hatfield, Brumm, and Melvin). At the time of their study, slurry systems were used by 50 to 60 percent of swine producers and the most common form of the slurry system consists of a slatted floor over a pit sufficient for 120 to 180 days of storage (Hatfield, Brumm, and Melvin). The pit is often 8 to 12 feet deep. As the pit fills, manure is removed for application to cropland. Deep pit systems do not typically have other manure storage on‐site. Not all new swine operations use a deep pit system (Heber; Gooch). Liquid manure systems are also popular. One common version of the liquid manure system is known as a pull‐plug. In this system, a shallow pit is located underneath the barn to collect manure that falls through slats. This pit is then typically flushed with water to deposit the manure into a larger treatment lagoon. Usually some of the flush water is re‐circulated from the lagoon system. The frequency of the flushing will vary from operation to operation but often ranges between a week and a month (Heber). Some operations have multiple lagoons and some may utilize only one. The
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lagoon system serves as the manure storage for the operation. It is typically sized to handle in excess of a year’s worth of manure production and must be able to accommodate rainfall. The manure is often very diluted and irrigated onto cropland. These systems are most prevalent in the Southern regions of the U.S. In favorable climates and regulatory environments anaerobic lagoon storage systems are popular because irrigation equipment can be used to apply the wastes, reducing overall application costs for liquid as opposed to slurry type manures (Hatfield, Brumm, and Melvin). Lagoon systems are typically used by larger operations located in warm climates such as the Southeast, Southern Corn Belt, and Southwest Plains which account for 20 to 30 percent of hog production (Hatfield, Brumm, and Melvin). These estimates are consistent with Key and Sneeringer’s calculations which showed that in 2005, 25.5% of total hog production occurred in the Southern region and that 88% of these animals were raised under liquid manure based systems. The geographic location of swine operations is important for the adoption of digester systems because it is strongly correlated with the type of manure handling system used on swine farms. Pit systems tend to be used in the heartland and lagoon systems more common in the Southeast. This assertion is seen clearly in Table 2 of Key and Sneeringer which shows that 88 percent of the hogs in the South are produced on operations with lagoon manure handling systems. On the other hand nearly 70 percent of the hogs in the Midwest are produced on farms with pit based manure handling systems. The switch to pit based systems in the Midwest has occurred over time. For instance, Key, McBride, and Ribaudo document that in 2004 approximately 56% of hogs were raised on farms that used pit/tank storage systems and 39% that used lagoons, approximately the reverse of the situation in 1998 when 55% used lagoon systems. Other Potential Limitations Associated with Swine AD Systems In addition to the challenges identified above there are a number of other issues that can potentially limit the adoption of AD systems on swine operations. At this point these potential limitations might best be positioned as hypotheses in need additional investigation. First, low Carbon to Nitrogen ratios and high ammonia‐nitrogen concentrations are often an impediment to successful digestion of animal manures (Bernet and Beline; Creamer, Williams, Chen and Cheng). This is particularly true with regard to swine manure (Heber) and apparently a greater problem when one attempts digestion at higher temperatures (Hansen, Angelidaki, and Ahring). While the relationship between carbon and nitrogen in swine manure does not prohibit digestion, it must be managed to achieve high rates of production. In Europe, this is often accomplished by adding additional organic wastes to the digestion process (Bernet and Beline). While these factors are frequently discussed in the technical literature, additional work by a qualified biological engineer is needed to assess their relative importance in limiting swine AD adoption.
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In addition to biological process challenges, a number of other factors potentially limit adoption of swine AD systems. Several experts noted that electrical prices are a critical determinant of AD system adoption. For instance, a representative of RCM International indicated that they estimate that electrical prices in excess of $0.08 per kWh are required to make systems economical (McEliece). In addition, others noted that utility interconnection policies and net metering policies can vary from location to location (Costa). These policies are important determinants of the economics of swine AD. It is also possible that many swine facilities that could adopt AD systems tend to be located in areas with lower electrical prices and less favorable utility policies. This hypothesis could be explored more thoroughly with available data from the USDA‐ERS ARMS database. Additionally, this work could be complemented by existing work that uses ARMS to estimate the electrical and energy demands on existing swine operations. Finally, while it is potentially possible to convert deep pit manure handling systems for compatibility with AD systems more work is needed to understand the associated costs and how to best modify these systems. It is possible that many systems could be modified for relatively modest amounts ($20,000 to $30,000), but these modifications would like only allow one to draw manure from the deep pit and place it in the digester and additional manure storage would likely be required (McEliece). This would likely create a number of concerns as additional permits may be required and manure storages could be very costly. Additional engineering work is needed to better understand the economics of converting deep pit systems to digestion systems. Such work could be accomplished by hiring an engineer to provide estimates for storages based upon the waste facility specifications presented in the NRCS standards. Implications for Modeling AD Systems on Swine Operations The design of swine livestock housing and manure handling systems influences the likelihood that a swine operation can effectively install and AD system. There are essentially three broad categories of digester systems that are appropriate for swine systems. The NRCS categorizes these as complete mix digesters, ambient temperature (or covered lagoon digesters), and alternative design (fixed‐film, induced blanked, and other alternative designs) digesters (NRCS, 2009). In attempting to understand the economics of AD on Iowa swine operations, Garrison and Richard noted the challenges of applying AD systems to deep pit systems. The deep pit system is not conducive to anaerobic digestion because manure is not frequently removed from the building so substantial amounts of methane production takes place in these pits. Further, the system does not typically contain manure storage where digested manure could be stored. This presents a problem because there is no place to store digested manure other than placing it back into the deep pit system and mixing it with the freshly deposited manure. As a result, one would have to build and digester and manure storage for the digestate. This would significantly increase the cost of the system.
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Likewise these systems are not designed for constant pumping to a digester. They are typically agitated and pumped out once or twice a year. The longer that the manure stays in the deep pits, the greater the anaerobic activity in the pit itself, reducing the biogas that can be captured and reducing the odor reduction benefit that is associated with digestion. Hatfield, Brumm, and Melvin point out that because much of the U.S. hog production is located in the North‐Central U.S. heated digesters are required to maintain biological processes associated anaerobic digestion in the winter months. This means that complete mix digesters are most likely required in the Midwest. Pull‐plug systems are more adaptable to an AD system. The primary reason is that it is easy to intercept the manure stream before it reaches its primary storage container. The manure is removed from these systems frequently and can be diverted to a digester. Upon leaving the digester it would resume its normal path into the lagoon system. One challenge with these systems is to manage the level of dilution that occurs as the manure is flushed from underneath the barns. Pull‐plug systems utilize lagoon storage so it is also possible to cover the lagoon where most of the methane would be produced. Lagoon based digesters are more likely to be successful in the Southern regions because the warm climate provides enough heat for the biological activity to continue throughout the year. The NRCS study points out that energy production is only typically feasible on covered lagoon digesters south of the 40th parallel (NRCS, 2009). Some of the important swine production states that are included in this category include North Carolina, Missouri, Kansas, Arkansas, Georgia, Oklahoma, Kentucky, Texas, and Virginia. These states also tend to be more likely to utilize lagoon and pull‐plug manure systems than those in the upper Midwest. As a result of this discussion one can make the following conclusions about the technical feasibility of AD system adoption on swine operations.
Deep pit systems are not likely candidates for AD systems. This accounts for nearly 52% of the hog production in the U.S. (Key and Sneeringer).
If AD systems are modeled on farms with deep pit systems, the investigator should account for the fact that additional manure storage will likely be required. This would likely be challenging from a permitting perspective as well as create an exceedingly high capital cost barrier for AD adoption.
Pull‐plug and flush manure systems are likely candidates for AD system adoption. Approximately 35% of swine production takes place on farms with these types of manure handling systems (Key and Sneeringer).
Because lagoon based manure handling systems are present on considerable numbers of farms, new AD systems are likely to be viable in the Southern regions of the U.S. Approximately 22% of total hog production takes place in the South with lagoon based systems.
Some potential for AD exists in the Upper Midwest. Nearly 13% of total hog production in the U.S. occurs in the Midwest and uses lagoon based manure handling systems.
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Because of warmer climates in the Southern U.S. investigators should carefully consider the economics of installing covered lagoon digesters on these operations as well as complete mix systems.
According to NCRS, covered lagoon digesters with energy production are unlikely to be viable north of the 40th parallel. If modeling these types of digesters in that region, energy production should be omitted.
Approaches to Characterizing and Measuring the Economics of AD Systems
Chvosta and Norwood describe several of the challenges associated with understanding the economics of AD systems. The costs of an AD system will vary considerably from farm to farm requiring that robust methods and data be used to accurately estimate cost models. The challenge is to accurately identify the relevant inputs at each farm. For instance how much excavation would be required, how much manure will be handled by the system. They argue that the average unit costs for materials and labor are not likely to vary considerably from farm to farm but that the amount of materials and labor are likely to vary. In their opinion, most of the costs will be driven by the volume of waste water that the system handles. As a result, most of the difficulty in constructing cost models lies in the developing sound representations of the engineering required at the site as opposed to the economics of the systems. In other words, identification of the appropriate engineering parameters is necessary. Consistent with this view, the NRCS suggests that using the volume of waste treated is a critical cost determinant because digesters should be built to the USDA‐NRCS standards for environmental performance (NRCS). These standards describe the design parameters that should be used in building a covered lagoon or anaerobic digester. For instance they describe the amount of slope, minimum depth, and other critical sizing features of a proposed system. From these parameters one could derive many of the critical cost elements of the system. Roos, Moser, and Martin (1999) reported the costs of covering lagoons on the basis of lagoon size and material used to cover the lagoon. Their report featured data from five different covered lagoon digesters. Their estimates suggest a very wide range ($0.37/ft2 to $5.81/ft2) of potential prices for lagoon covers. However, one should use caution in interpreting the data because a number of farms are listed multiple times and there is not enough detail in the paper to clearly understand how the cost estimates were derived and why several farms are listed multiple times. If accurate, Roos, Moser, and Martin’s finding that costs per square foot vary considerably contrasts with Chvosta and Norwood’s argument that average material costs are unlikely to vary considerably from farm to farm and that costs would be driven largely by the size of the lagoon to cover. It is likely that Chvosta and Norwood’s argument will hold in the long‐run as
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technologies become more standard and the materials used in the digesters are standardized, but the convergence to a standard technology may be yet to occur. The FarmWare model developed by the EPA’s AgSTAR program is a tool that can be used to understand the feasibility of adopting and AD system. The model calculates the potential biogas production of the digester as well as an estimate of capital costs. The model documentation does not explain how capital costs are estimated. A phone interview was conducted with a representative of the AgSTAR program to better understand the model and obtain the equations and data used to estimate the capital costs (Costa). The phone interview revealed that the capital cost estimates used in the FarmWare program were collected from USDA grant applications in the 1990’s. The specific program mentioned was the REAP (Rural Energy for America) program. However, it is unlikely that this is the program because it was not enacted until the 2000’s. In the case of swine, data from only 3 observations form the basis of the capital cost estimates. The size of the proposed digester system and inflation factors are used to estimate capital costs for any size digester from only these three observations. Unfortunately, the exact procedure is not available to the public. The result of some of these shortcomings can be seen by examining studies that attempted to use the AgSTAR model to understand the economics of swine AD systems. Garrison and Richard attempted to understand the economics of adopting AD systems on Iowa livestock operations. Their approach was to use the FarmWare model developed by the U.S. EPA’s AgSTAR program (1997) to estimate the economic parameters associated with livestock operations in Story county Iowa. They found that only AD installations on very large swine operations were likely to be economical. For instance, a farrow‐to‐finish system of over 20,000 head was required, which they note did not exist in Iowa. In the case of finishing operations, under some scenarios operations as small as 1,700 finishers could be economical with substantial subsidies. It is not clear why their results showed that smaller finishing operations could be profitable, but one should apply significant caution when using the FarmWare model. In addition to challenges in using the AgSTAR model to estimate capital costs, Chvosta and Norwood also note that FarmWare’s predictions of biogas production were often inaccurate and sometimes substantially (over 4 times) so. Ernst et al., use the McCabe farm digester as an example with which to examine the viability of digesters on Iowa swine operations. In order to convert the 1972 cost of the digester to their present time they use a compounding approach and a discount rate of 2.5%. They note that even under generous energy production assumptions the digester would not be economically viable on the basis of energy generation alone. Rather, using the digester for odor reduction is more appropriately viewed as a cost of doing business. The NRCS has recently released guidelines that can be used to better understand digester construction, costs, and revenues. They estimate that a 300 pound swine animal can
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theoretically produce 5.6 ft3 of biogas per animal per day. They estimate of the of operating and maintenance costs of the digester based on the total capital costs of the system. For the digester they suggest using an estimate of 1.75 to 2.25% of the total cost of the digester. In the case electrical generation they base their estimate on the basis of kWh produced. Here, they suggest that the cost of operating and maintaining and engine generator is between 1.25 and 1.5 cents per kWh. These guidelines were developed based on the analysis of several of the case study data from Kramer (2002), Lusk (1995; 1998), and Wright (2003). These previous efforts make it clear that in order to accurately measure the economic performance of AD systems it is necessary to collect data that accurately summarizes the key economic aspects of AD systems. Many previous efforts to accomplish this have suffered from a lack of consistently collected, interpreted, and reliable AD system data. Recently, efforts have been conducted to identify the necessary data and provide a framework for reliably reporting the data. Suggested Economic Data Collection Protocols The EPA AgSTAR program developed a protocol for reporting the performance of AD systems for livestock manure (Eastern Research Group, 2011). This protocol identifies and describes some of the data and information that should be collected in order to accurately characterize the experience livestock AD system operators. The protocol covers a number of areas, many of which are technical in nature. However, economic issues are covered in some depth and provide some useful advice in evaluating economic parameters of AD systems. Capital costs are a significant component of biogas systems. The protocol provides a number of useful suggestions with respect to measuring capital costs. The author argues that the information should include total as built costs, excluding the original site. In order to understand the cost estimate, the protocol should include an itemized list of costs as well as whether the system was constructed completely by a developer or with various amounts of farmer labor and supervision. Further, it is suggested that the AD system be treated as an entity separate from the farm operation. Only costs required by the biogas enterprise should be included. In order to standardize the capital costs they suggest using an internally derived cost of capital for the system based upon the equity and debt capital used in the system. This is particularly challenging because while borrowing costs are generally observable, the cost of equity capital will vary from farm to farm and is not observable. To avoid this difficulty the author argues that the most practical approach is to use the cost of debt capital in the calculation. It is noted that the system capital costs should be based on the turn‐key cost and not reduced by grants or subsidies including reduced interest rate loans. Equipment and structures should be valued based upon their useful lives. This requires one to estimate replacement costs for shorter‐lived components of the system. The author notes that the operating and maintenance costs of the system will evolve over time. In particular, maintenance costs should increase over time. Despite this, few farmers will have detailed
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records to document the operating and maintenance costs of the system. As an alternative, they suggest using 3% of capital costs as a proxy of operating costs. There is no justification given as to why 3% was chosen and one should likely be highly skeptical that this will produce a reasonable result. Biogas production will play a key role in determining the ultimate economic outcome of the system. The protocol seeks to accurately measure the amount of biogas that is produced by the system and the time period over which it is generated. The reporting should also carefully monitor and track the electrical production of the system. Electrical generation revenues should be calculated by comparing pre‐system electrical costs to post system costs. The difference is the savings associated with digester use with the caveat that adjustments need to be made if the installation of the digester results in an increased unit cost for electricity used by the system. The evaluation should be made over the course of an entire year, not just a few selected months. The author suggests that same approach for biogas used in boiler systems. With respect to methane emission reductions the protocol provides a detailed set of calculations that can be used to estimate the methane emission reductions of the system. While the protocol is a step in the right direction, there are clearly factors that need to be improved. In particular the costs associated with maintenance and operation of the system need to be carefully recorded and measured. The protocol is particularly sparse in this important area. The 3% of capital cost rule of thumb is unlikely to be accurate except by chance. More guidance must be given in order to identify the types of costs and insure that data is collected that ultimately leads to improved estimates of the operating and maintenance costs. Likewise, the cost of capital associated with the system will have a substantial impact on its economic desirability. While it is useful to record borrowing costs, one must be careful to report the actual cost of capital assumed in the calculation. This will allow researchers to determine the amounts of capital committed to the project and adjust the opportunity cost of capital. If the opportunity cost of capital is not reported, it will be impossible to infer the capital costs of the system and make it difficult to generalize across a wide variety of economic situations. While one can quickly find fault with aspects of the economic data that are to be collected by applying the protocol, it is clear that this data would represent a substantial quality improvement over the data that are currently available. Most of the economic data available on swine AD systems suffer from a number of serious deficiencies. For instance, the capital costs are frequently reported as a total, with no mention of the amount spent on the digester versus the electrical generation equipment. Based on the limited data for which itemized costs are available, the electrical generation equipment components can be quite substantial. In fact the NRCS suggests that these costs are typically 36% of the average capital costs in AD systems (2007).
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This is particularly important because nearly all of the currently operating swine digesters seem to be built with the primary goal of odor reduction. Odor reduction alone would not necessarily require that the electrical generation equipment be installed. The limited data available today do not clearly demonstrate the marginal revenues associated with electrical generation are sufficient to justify the additional capital, operating, and maintenance costs. These costs should be carefully investigated. It is quite possible that the optimal strategy for many operations would be to flare the methane and avoid the additional costs. However, data are not sufficient to justify this conclusion.
Estimating Parameters from Swine AD Data The previous discussion highlights some of the challenges in accurately predicting the parameters necessary to model the economics of swine AD adoption. A large number of case studies have been written about swine AD systems. These case studies often report information that can be used to estimate parameters for adoption models. The first step in this process is to carefully describe the AD systems. Table 1 lists some of the basic characteristics of the swine AD systems that have been studied. A total of 19 different farms and 12 different case study sources were identified. Two of the operations listed were obtained by contacting RCM Digesters and obtaining a price quote on hypothetical systems. The farm names are listed in the first column of Table 5 and the case study source is listed in the second column. A quick perusal of the table will show that characteristics of some farms have been described in several different reports. For instance, the Apex Pork digester was summarized in three different reports. Several of these reports appear to be based off of the same initial data but it is notable how different facts and characteristics emerge. For instance, the NRCS study does not describe the type of manure handling system and only reports the Apex operation as a swine farm. In other cases conflicting details emerge. For instance the Barham farm is listed by one source as being installed in 1996 and by others in 1997. However for these basic characteristics most sources tend to agree on the nature of the operation. This is less true when one considers other features of the digesters.
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Table 5. Characteristics of Various U.S. Swine Digester Systems, Multiple Sources and Various Dates.
Farm Source State Date Installed
Type of Digester
Manure Handling System
Type of Farm
Apex Pork A IL 1998 Covered lagoon Pull‐plug Finisher
Apex Pork I IL 1998 Covered lagoon Pull‐plug Finisher
Apex Pork K IL 1998 Covered lagoon
Barham A NC 1996 Covered lagoon Pull‐plug Farrow‐to‐wean
Barham E NC 1997 Covered lagoon Flush Farrow‐to‐wean
Barham K NC 1997 Covered lagoon Farrow‐to‐wean
Bell Farms A IA 1997 Complete mix Pull‐plug Farrow‐to‐wean
Bell Farms I IA 1998 Complete mix Pull‐plug Farrow‐to‐wean
Bell Farms (Swine USA)
B IA 1999 Pull‐plug Farrow‐to‐wean
Carroll Food E NC 1992 Covered lagoon Flush Farrow‐to‐finish
Carroll Food K NC 1992 Covered lagoon Farrow‐to‐finish
Colorado Pork A CO 1997 Complete mix Pull‐plug Farrow‐to‐wean
Colorado Pork H CO 1999 Complete mix Pull‐plug Farrow‐to‐wean
Crawford I IA 1999 Other Pull‐plug Finisher
DJ Acres A PA 1986 Complete mix Scrape Farrow‐to‐finish
Feasibility Study
C MI Hypothetic Complete mix Centralized Various
Gypsy Hill A PA 1983 Complete mix Scrape Finisher
Lou Palmer K AR 1992 Covered lagoon Farrow‐to‐feed
Lou Palmer L AR 1992 Covered lagoon Farrow‐to‐feed
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Table 5. Continued.
Martin A VA 1993 Covered lagoon Flush Farrow‐to‐feed
Martin E VA 1993 Covered lagoon Flush Farrow‐to‐wean
Martin K VA 1993 Covered lagoon Farrow‐to‐feed
McCabe E IA 1972 Covered tank Flush Farrow‐to‐finish
McCabe K IA 1972 Covered lagoon
Pine Hurst F PA 2003 Complete mix Deep pit Finisher
Rocky Knoll E PA 1985 Complete mix Farrow‐to‐finish
Rocky Knoll K PA 1985 Complete mix Farrow‐to‐finish
Royal Farms E CA 1982 Covered lagoon Flush Farrow‐to‐finish
Unnamed G NC Covered lagoon Pull‐plug Farrow‐to‐wean
Valley Pork K PA 1986 Complete mix Farrow‐to‐finish
Valley Pork L PA 1986 Complete mix Farrow‐to‐finish
Vendor Quote 1 D IN Hypothetic 2011
Complete mix Pull‐plug Farrow‐to‐wean
Vendor Quote 2 D IN Hypothetic 2011
Complete mix Pull‐plug Finisher
Sources: A. Moser, M.A. “A Dozen Successful Swine Waste Digesters.” RCM Digesters, Inc. Available at http://www.rcmdigesters.com/images/PDF/ADozenSuccessfulSwineWasteDigesters.pdf B. Lorimor, J. “Swine USA Anaerobic Digester.” Tour Handout October 2000, Department of Agricultural and Biosystems Engineering. http://www.rcmdigesters.com/publications/swusa.html C, Frazier, Barnes, and Associates. “Feasibility Study, West Michigan Regional Liquid Manure Processing Center.” Final Report, West Michigan Livestock Producer Group, April 25, 2006. D. Quote received from RCM International, LLC, AD system vendor, August 3, 2011. E. Lusk, P. “Methane Recovery from Animal Manures the Current Opportunities Casebook.” Final Report, National Renewable Energy Laboratory, Golden, CO. September 1998. F. Topper, D., P. Topper, and R. Meinen. “Pine Hurst Acres Case Study.” Department of Agricultural and Biological Engineering, Penn State University, January 10, 2008. G. Martin, J.H. Jr. “A Comparison of Three Swine Waste Stabilization Systems.” Eastern Research Group, Inc. March 20, 2002.
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H. Martin, J.H. Jr. “An Assessment of the Performance of the Colorado Pork, LLC. Anaerobic Digestion and Biogas Utilization System.” Eastern Research Group, Inc. March 18, 2003. I. Kramer, J. “Agricultural Biogas Casebook.” Resource Strategies, Inc., Report for Great Lakes Regional Biomass Energy Program, September 2002. J. Kramer, J. “Agricultural Biogas Casebook, 2004 Update.” Resource Strategies, Inc., September 2004. K. Natural Resources Conservation Service. “An Analysis of Energy Production Costs from Anaerobic Digestion System on U.S. Livestock Production Facilities.” U.S. Department of Agriculture, NRCS, Technical Note No. 1, October 2007. L. Lusk, P. “Methane Recovery from Animal Manures the Current Opportunities Casebook.” National Renewable Energy Laboratory, Washington, D.C. December 1994. NREL/TP‐424‐7577. Size and Other Characteristics of the Operations For the most part, there are only minor differences across sources on the characteristics listed in Table 5. However, some important differences begin to emerge when one considers the herd size and biogas production associated with the various digesters (Table 6). In some situations the total number of animals at various stages of production is reported. In others, one total number is reported. In other situations the number of animals differs by case study. For example, Apex Pork is listed as having 8,000 finishers by two sources and 8,300 by another. The Barham farm is listed as having 4,000 sows by one source, 4,000 sows and 4,800 growers by another, and finally as having 8,800 animals in a third. Similarly, DJ Acres is reported as a farrow‐to‐finish system with 17,000 head. It is unlikely that this represents 17,000 sows, but rather the total number of pigs in the entire system at any given time. Another important characteristic of the AD systems is whether they are used to generate electricity. Ideally, one would obtain information on the electrical production and costs associated with the electrical generate equipment as well as the biogas production. The electrical generation data is even more difficult to interpret than the biogas data and is not listed in Table 6. Instead, the table simply lists whether electrical generation equipment is installed on the farm operation.
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Table 6. Size, Biogas Production, and Electrical Generation Reported for Various U.S. Swine Digester Systems, Multiple Sources, Various Dates.
Farm Source Number of Animals
Biogas Produced Biogas Reporting Period
Electrical Generation
Apex Pork A 8,000 finishers
36,000 ft3/day 1 summer month None
Apex Pork I 8,300 finishers
36,000 ft3/day Not clear
Apex Pork K 8,300 finishers
33,200 ft3/day
Barham A 4,000 sows 22,300 ft3/day 18 months 120 kW
Barham E 4,000 sows and 4,800 growers
50,000 ft3/day summer and 36,000 ft3/day winter
Appears to be summer and winter averages
120 kW
Barham K 8,800 44,000 ft3/day
Bell Farms A 5,000 sows 2.268 million ft3 6 months 80 kW
Bell Farms I 5,000 sows 30,000 ft3/day 80 kW
Bell Farms (Swine USA)
B 5,000 sows 950,000 ft3/month
80 kW
Carroll Food E 1,000 sows and 10,500 finishers
35,000 ft3/day 110 kW
Carroll Food K 11,500 34,500 ft3/day
Colorado Pork
A 5,000 sows 1.7 million ft3/day 5 months 80 kW
Colorado Pork
H 5,000 sows 27,370 ft3/day Flared gas not measured
80 kW
Crawford I 2,800 finisher
42,500 ft3/day Not clear
DJ Acres2 A 17,000 total
Feasibility Study
C 100,000 gal/day
6.335 million ft3/year
Hypothetical
Gypsy Hill A 4,000 finishers
Lou Palmer K 3,500 3,500 ft3/day
Lou Palmer L 300 sows 3,200 ft3/day summer and 1,400 ft3 winter
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Table 6. Continued.
Martin A 600 sows Not clear None
Martin4 E 600 sows 12,000 ft3/day Appears to be annual average
25 kW
Martin Farms
K 3,000 12,000 ft3/day
McCabe E 150 sows and 1,000 finishers
None
McCabe K 1,150
Pine Hurst F 4,400 finishers 47 kW
Rocky Knoll E 1,000 sows and 12,000 finishers
40 to 50,000 ft3/day
Not clear, also includes co‐digestion
200 kW
Rocky Knoll K 13,000 65,000 ft3/day
Royal Farms E 1,650 sows and 14,850 finishers
70,000 ft3/day Not clear 100 kW
Unnamed G 4,240 sows 21,349 ft3/ day Based on one year of data
Valley Pork K 14,600 73,000 ft3/day
Valley Pork L 1,650 sows 50,000 to 75,000 ft3/day
Guess 110 kW
Vendor Quote 1
D 5,000 sows 43,000 ft3/day Hypothetical 100 kW
Vendor Quote 2
D 8,000 finishers 48,000 ft3/day Hypothetical 100 kW
Sources: Same as listed for Table 5. If not clarified, the discrepancies in Table 6 will almost certainly result in inaccurate estimation of capital costs. The first step in making use of the data was to determine the most accurate characterization of the animal population possible. Next, the size of the operation was converted into animal units and manure production units based upon the production practice on the farm and using the conversion parameters listed in Tables 3 and 4. This process required that judgment be applied to the data listed in Table 6. For instance, when an operation such as DJ Acres was listed as a farrow‐to‐finish operation with 17,000 animals it was assumed that this characterized the entire population of animals because a 17,000 sow farrow‐to‐finish operation did not seem plausible. In order to determine the appropriate number of animal units, the 17,000 animals in the system had to be converted to the appropriate number of sows. Then, the values in Tables 4 could be used to calculate animal units and manure units.
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In the case of DJ acres, the number of sows was determined on the basis that there are roughly 9 pigs in a farrow‐to‐finish system for each sow. For instance, Foster, Hurt and Hale assume 9.4 pigs per sow in their analysis of a 1,200 sow operation. This same conversion was applied to the Rocky Knoll and Valley Pork operations. The animal unit and manure unit conversions were applied to each operation on the basis of the productive unit shown in Table 7 which lists each separate farm, its production practice, the number of production units, the number of animal units and the number of manure units on the system. The value of converting to animal or manure units can readily be observed in Table 7. For instance, in terms of animal or manure units Apex Pork is smaller than Barham, whereas in terms of total animals it is more than twice as large. This conversion should allow for a more accurate estimation of capital costs for the digester systems. Table 7. Measures of the Animal Units and Size of Digesters Reported in the Case Studies.
Farm Production Practice
Production Unit
Number of Production Units
Animal Units
Manure Units
Apex Pork Feeder to finish Hog 8,300 1,121 941
Barham Farrow‐to‐wean Sow 4,000 1,732 1,039
Bell Farms Farrow‐to‐wean Sow 5,000 2,165 1,299
Carroll Foods Farrow‐to‐finish Sow 1,000 1,417 1,091
Colorado Pork Farrow‐to‐wean Sow 5,000 2,165 1,299
Crawford Feeder to finish Hog 2,800 378 318
DJ Acres Farrow‐to‐finish Sow 1,700 2,409 1,855
Gypsy Hill Feeder to finish Hog 4,000 540 454
Lou Palmer Farrow‐to‐feed Sow 300 157 100
Martin Farrow‐to‐feed Sow 3,000 1,566 1,002
McCabe Farrow‐to‐finish Sow 150 213 164
Pine Hurst Feeder to finish Hog 4,400 594 499
Rocky Knoll Farrow‐to‐finish Sow 1,300 1,842 1,418
Royal Farms Farrow‐to‐finish Sow 1,650 2,338 1,800
Valley Pork Farrow‐to‐finish Sow 1,650 2,338 1,800
Vendor quote 1 Farrow‐to‐wean Sow 5,000 2,165 1,299
Vendor quote 2 Feeder to finish Hog 8,000 1,080 907
Biogas Production Accurately determining biogas production is particularly important when one considers AD systems that generate electricity. It would also likely be important if one were to be compensated or awarded emission reduction credits on the basis of methane destruction. Several discrepancies exist in the biogas production data. Here, the differences can be quite large. Biogas production is often reported in various formats and periods of time. Often, the
22
reporting does not contain the amount of methane in the biogas. Table 6 summarizes the biogas production from the various digesters. In many cases these reports covered odd reporting periods or made no mention of reporting periods. This is particularly problematic when dealing with covered lagoon digesters whose biogas production will likely peak in the summer drop in the winter months. The reporting often does not indicate whether the biogas is metered or whether the reporting was an educated guess. In many cases, one should assume the latter. The differences can be quite large for each farm. For instance, the reported average values for the Barham farm ranged from 22,300 to 44,000 ft3 per day. Several assumptions were used to standardize the biogas production estimates across the various studies. First, when the reports offered different values for biogas production, the lower value was included. An exception for this was made when a higher value was reported as a result of metering or a longer observation time period. In other words, what appeared to be the highest quality data was included, and if the quality of the data appeared to be equal, the lower value was chosen. All of the biogas production values were converted to ft3 of biogas production per day and are also reported on the basis of ft3 per AU‐day and are reported in Table 8. In four cases biogas production data were not reported in the case studies. One can observe the wide range in the amount of biogas produced per animal unit per day. On balance, the data in Table 8 show a great amount of variation in the amount of biogas produced by the digesters. Some digesters, notably Crawford reports an unrealistically high value. It appears that this digester never fully operated and is not currently operating. In some cases covered lagoon digesters produced more biogas than complete mix digesters. While this is conceivable in some locations, many of these systems would be expected to produce very low amounts of biogas in winter months.
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Table 8. Biogas Production for Various Swine Digesters.
Farm Digester Type Biogas ft3/day Biogas (ft3/AU‐day)
Apex Pork Covered lagoon 33,200 29.6
Barham Covered lagoon 22,300 12.9
Bell Farms Complete mix 12,600 5.8
Carroll Foods Covered lagoon 34,500 24.3
Colorado Pork Complete mix 11,333 5.2
Crawford Other 42,500 112.4
DJ Acres Complete mix
Gypsy Hill Complete mix
Lou Palmer Covered lagoon 2,300 14.7
Martin Covered lagoon 12,000 7.7
McCabe Covered tank
Pine Hurst Complete mix
Rocky Knoll Complete mix 45,000 24.4
Royal Farms Covered lagoon 70,000 29.9
Valley Pork Complete mix 62,500 26.7
Vendor quote 1 Complete mix 43,000 19.9
Vendor quote 2 Complete mix 48,000 44.4
Table 9 displays the averages and standard deviation for biogas production from the AD systems. The measures are calculated for all digesters, complete mix digesters, and covered lagoon digesters. The calculations exclude the Crawford digester which was not categorized as a complete mix digester, but “other” type. Table 9. Average and Standard Deviation of Biogas Production Measures for Swine AD Systemsa.
Digester Type Biogas ft3/day Biogas (ft3/AU‐day)
Average All Digesters 33,061 20
St. Dev. All Digesters 21,520 12
Average Complete Mix 37,072 21
St. Dev. Complete Mix 20,617 15
Average Covered Lagoon 24,900 17
St. Dev. Covered Lagoon 24,149 11 a Production for Crawford farm digester is not included in any of the measures. Electrical Production and Operating Costs Several of the digester systems are used to generate electricity. Often very little information is available on the amount of electricity production that is actually achieved by the digester
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systems. Frequently, the amount of electricity production does not correspond across case studies of the same farm. It appears that nearly all of the case studies report estimates of production, rather than a value that is measured over time. For that reason, one should be very cautious in evaluating the electrical production levels shown in Table 10. Table 10 also shows the annual reported operating and maintenance costs that are reported for various farm AD systems. These data are also of limited quality. In most every case, it appears that the estimates are educated guesses as to the operating and maintenance costs. Further, the estimates span many years and it is not clear what years the operating and maintenance costs reflect. The NRCS study recognizes this challenge and inflates all operating and maintenance costs to 2006 dollars, but it is not clear what data the study used to inflate. The costs frequently appear to be quite low and likely do not reflect the actual maintenance of an engine generator for electrical generation. One should be quite cautious in using the operating and maintenance costs data in Table 10.
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Table 10. Electrical Generation and Operating and Maintenance Costs as Reported in Various Case Studies.
Farm Source Electricity Produced (kWh/year)
Reported Electricity Value ($/year)
Operating and Maintenance Costs
Barham A $18,000
Barham E 325,000 to 355,000 $35,000
Bell Farms A $36,000
Bell Farms I 400,040 $35,000 to $46,000 2 hours per day
Bell Farms (Swine USA)
B 507,480 $33,480
Carroll Food E 550,000 to 600,000 $45,000 to $50,000 $8,000 to $10,000 per year
Carroll Food K $15,182 / year (2006 $’s)
Colorado Pork A $34,800
Colorado Pork H 342,414 $22,907 $5,459/year
Crawford I N/A N/A 1.5 hours per day
Lou Palmer K N/A N/A $791 / year (2006 $’s)
Lou Palmer L N/A N/A $500/year
Martin E 150,000 to 175,000 $10,625 $2,500/year
Martin K $3,782/year (2006 $’s)
McCabe E N/A N/A $2,500/year
McCabe K N/A N/A $11,241/year (2006 $’s)
Pine Hurst F $1,200/year
Rocky Knoll E 1.1 to 1.2 million 60,000 to $65,000 $8,000/year
Rocky Knoll K $15,032/year (2006 $’s)
Royal Farms E 700,000 to 750,000 $43,000 to $44,000 $8,000/year
Unnamed G $17,140 to $23,805
Valley Pork K N/A N/A $9,176/year (2006 $’s)
Valley Pork L N/A N/A $5,000/year
Sources: Same as listed for Table 5. Digester Volume As described earlier, the amount of waste handled in the digester is an important determinant of the capital costs of the system. Some of the case studies list the volume and top surface area of the digester system. The top surface area of the system should be an important driver of the costs of covered lagoon systems and volume should be important in determining the costs of complete mix systems. Both top surface area and volume are shown in Table 10. Blank entries indicate that the data were not reported. The values in Table 11 were used to determine a single measure for each farm which is shown in Table 12.
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Table 11. Digester Size and Capital Costs, Multiple Sources, Various Years.
Farm Source Top Surface Area (ft2) Volume (ft3) Total Capital Costsa
Apex Pork A 19,200 316,800 174,000
Apex Pork I 19,200 106,944 152,300
Apex Pork K 202,789 a
Barham A 289,500
Barham E 69,696 1,394,000 264,474
Barham K 357,831 a
Bell Farms A 525,000
Bell Farms I 6,300 93,576 576,000
Bell Farms (Swine USA) B 6,300 100,800 500,000
Carroll’s Food E 70,225 935,400 191,500
Carroll’s Food K 302,809 a
Colorado Pork A 374,000
Colorado Pork H 5,200 66,840 368,000
Crawford I 22,057 290,000
DJ Acres A 250,000
Feasibility Study C 12,478,363
Gypsy Hill A 289,500
Lou Palmer K 25,300 a
Lou Palmer L 4,400 35,200 16,000
Martin A 120,000
Martin E 14,400 389,000 95,200
Martin K 128,795 a
McCabe E nr 7,400 20,000
McCabe K 89,932 a
Pine Hurst F 19,075 256,620
Rocky Knoll E 4,004 46,800 325,000
Rocky Knoll K 610,685 a
Royal Farms E 42,025 1,050,000 220,000
Unnamed G 912,500
Valley Pork K 458,820 a
Valley Pork L 5,625 67,500 250,000
Vendor Quote 1 D 1,145,574
Vendor Quote 2 D 1,080,856 a Initial capital costs adjusted and reported in 2006 dollars. Sources: Same as listed for Table 5.
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Table 12. Measures of the Size of the Digesters Reported in Case Studies
Farm Digester Type Volume ft3 Surface Area ft2 Electrical Generation (kW)
Apex Pork Covered lagoon 316,800 19,200 None
Barham Covered lagoon 1,394,000 69,696 120
Bell Farms Complete mix 93,576 6,300 80
Carroll Foods Covered lagoon 935,400 70,225 110
Colorado Pork Complete mix 66,840 5,200 80
Crawford Other 22,057 None
DJ Acres Complete mix None
Gypsy Hill Complete mix None
Lou Palmer Covered lagoon 35,200 4,400 None
Martin Covered lagoon 389,000 14,400 25
McCabe Covered tank 7,400 None
Pine Hurst Complete mix 19,075 47
Rocky Knoll Complete mix 46,800 4,004 200
Royal Farms Covered lagoon 1,050,000 42,025 100
Valley Pork Complete mix 67,500 5,625 None
Vendor quote 1 Complete mix 100
Vendor quote 2 Complete mix 100
Capital Costs Many of the different systems were built at different times. This complicates the analysis because input prices, construction materials, construction techniques, and technologies of digesters have evolved over time. There are numerous methods and approaches that could be used to adjust the capital costs to account for these changes. The NRCS (2007) study inflated capital costs to 2006 values using the ENR Construction Index1. These values are marked with a footnote in the last column of Table 11. Unfortunately, the exact details that were used to inflate the values are not presented, making it difficult to interpret the values. Almost all approaches to adjusting the capital costs have some drawbacks, but it was felt that the wide range of elapsed time made adjustment necessary. The approach used in this study was to inflate the costs using the GDP deflator. Table 13 shows the date the digester was installed and the capital cost as reported, the 2006 cost as reported in the NRCS study, the GDP price index, and the capital costs adjusted using the chain‐type GDP price index2. Several important points should be made about the values in Table 13. As seen in Table 11, the capital cost estimates associated with the same digester can
1 The ENR construction cost index is calculated by the Engineering News‐Record. It is available by subscription on‐line at http://enr.construction.com/economics/. 2 Bureau of Economic Analysis. Price Indexes for Gross Domestic Product, Table 1.1.4. Downloaded August 17, 2011.
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vary from report to report. In some cases, the difference can be substantial. The approach used to construct Table 13 was to include the largest reported capital cost estimate. Similarly some studies report different dates for the installation of the digester. The values in Table 13 show the earliest possible date. Table 13. Date of Installation and Capital Costs Estimates for Swine AD Systems.
Farm Date Installed
Reported Capital Cost
NRCS 2006 Cost Estimate
GDP Price Index (2006 = 100)
Capital Cost Estimate 2006 USD
Capital Cost Estimate 2011 USD
Apex Pork 1998 174,000 202,789 0.8290 209,900 226,559
Barham 1996 289,500 357,831 0.8055 359,419 387,944
Bell Farms 1997 576,000 Not reported 0.8197 702,666 758,434
Carroll Foods 1992 191,500 302,809 0.7420 258,086 278,569
Colorado Pork
1997 374,000 Not reported 0.8197 456,245 492,455
Crawford 1999 290,000 Not reported 0.8412 344,757 372,119
DJ Acres 1986 250,000 Not reported 0.6108 409,300 441,785
Gypsy Hill 1983 289,500 Not reported 0.5590 517,929 559,035
Lou Palmer 1992 16,000 25,300 0.7420 21,563 23,275
Martin 1993 120,000 128,795 0.7583 158,242 170,801
McCabe 1972 20,000 89,932 0.2583 77,418 83,562
Pine Hurst 2003 256,620 Not reported 0.9118 281,436 303,772
Rocky Knoll 1985 325,000 610,685 0.5975 543,916 587,085
Royal Farms 1982 220,000 Not reported 0.5377 409,125 441,595
Valley Pork 1986 250,000 458,820 0.6108 409,300 441,785
V. Quote 1 2011 1,145,574 N/A 1.0794 1,061,340 1,145,574
V. Quote 2 2011 1,080,856 N/A 1.0794 1,001,381 1,080,856
The values in Table 13 clearly show the importance of adjusting the capital costs for different installation dates. In many cases, the cost of the digester would have increased substantially if priced in today’s dollars. The process of using the GDP deflator to adjust the values to 2006 gives similar results as the process used by the NRCS although differences exist. The last column of Table 13 shows the estimated capital costs for each system in 2011 dollars. There are many different ways in which to summarize the capital cost data. One common method is to report the values per animal unit. Table 14 shows the average capital costs on the basis of several different measures of system size. When comparing the cost per unit of volume or top surface area it is important to distinguish between covered lagoon and complete mix digesters. On the basis of cost per animal unit the average cost for all of the digesters shown is $400 per animal unit and the standard deviation was 313. The standard deviation was a slightly
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smaller percentage of the mean for the average cost per manure unit, but otherwise the two measures seem to produce similar results. Table 14. Average Capital Costs for Various Measures of Digester Size, 2011 Total Capital Costs.
Farm Per Animal Unit
Per Manure Unit
Per ft3 of Digester Volume
Per ft2 of Top Surface Area
Per kW
Apex Pork 202 241 0.72 11.80 N/A
Barham 224 373 0.28 5.57 3,233
Bell Farms 350 584 8.11 120.39 9,480
Carroll Foods 197 255 0.30 3.97 2,532
Colorado Pork
227 379 7.37 94.70 6,156
Crawford 984 1172 16.87 N/A N/A
DJ Acres 183 238 N/A N/A N/A
Gypsy Hill 1035 1232 N/A N/A N/A
Lou Palmer 149 232 0.66 5.29 N/A
Martin 109 170 0.44 11.86 6,832
McCabe 393 511 11.29 N/A N/A
Pine Hurst 511 609 15.93 N/A 6,463
Rocky Knoll 319 414 12.54 146.62 2,935
Royal Farms 189 245 0.42 10.51 4,416
Valley Pork 189 245 6.54 78.54 N/A
Vendor quote 1
529 882 N/A N/A 11,456
Vendor quote 2
1001 1191 N/A N/A 10,809
Average 400 528 6 49 6431
St. Deviation 313 368 6 55 3260
Examination of the results in Table 14 indicates that the costs per animal unit for complete mix and covered lagoon digesters can be quite different. For example, Apex Pork has 1,121 animal units and covered lagoon digester. Vendor quote 2 is for a complete mix system on a farm with 1,080 animal units. The cost per animal unit was roughly 5 times for the complete mix digester. Additionally, the Apex digester did not include energy generation while the vendor quote did. These factors will likely have a dramatic impact on AD costs. The impact of the digester style can be more accurately described by calculating the averages for the different types of digesters. The average capital costs for complete mix and covered lagoon digesters are shown in Table 15. Here, one can see that the average cost per animal unit for complete mix digesters was $520 and for covered lagoon digesters the average was $178.
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Table 15. Various Measures of Capital Costs for Complete Mix and Covered Lagoon Digesters, 2011 Total Capital Costs.
Farm Per Animal Unit
Per Manure Unit
Per ft3 of Digester Volume
Per ft2 of Top
Surface Area
Per kW
Complete Mix Digesters
Bell Farms 350 584 8.11 120.39 9,480 Colorado Pork 227 379 7.37 94.70 6,156 Crawford 984 1172 16.87 N/A N/A DJ Acres 183 238 N/A N/A N/A Gypsy Hill 1035 1232 N/A N/A N/A McCabe 393 511 11.29 N/A N/A Pine Hurst 511 609 15.93 N/A 6,463 Rocky Knoll 319 414 12.54 146.62 2,935 Valley Pork 189 245 6.54 78.54 N/A Vendor quote 1 529 882 N/A N/A 11,456 Vendor quote 2 1001 1191 N/A N/A 10,809
Average 520 678 11.24 110.06 7,883 St. Deviation 333 379 4.13 29.85 3,267
Covered Lagoon Digesters
Apex Pork 202 241 0.72 11.80 N/A Barham 224 373 0.28 5.57 3,233 Carroll Foods 197 255 0.30 3.97 2,532 Lou Palmer 149 232 0.66 5.29 N/A Martin 109 170 0.44 11.86 6,832 Royal Farms 189 245 0.42 10.51 4,416
Average 178 253 0.47 8.17 4,253 St. Deviation 42 66 0.18 3.60 1,887
The cost data for the various digesters is graphically in Figure 1, which shows the total capital costs on the vertical axis and animal units on the horizontal. Complete mix digesters are shown as red squares and covered lagoon digesters as blue X’s. The graph also shows a regression line for each type of digester. It is clear that the costs of the covered lagoon digesters per animal unit are much lower than those for the complete mix digesters. A similar analysis was done on the basis of manure production units, and the results are very similar. This makes it clear that one must consider different estimates for covered lagoon and complete mix digesters.
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Figure 1. Capital Costs by Animal Units for Compelte Mix and Covered Lagoon Swine Digesters. The capital cost data were also anlyzed using regression analysis. Two different regression models were estimated. In the first model the total capital cost is estimated as a function of the natural log of animal units on the farm, an indicator variable for whether the operation produced electricity, and an indicator variable for whether the digester was a complete mix digester (Table 16). The t‐statistics for the estimated parameters are all greater than one, but most are not signficant at the 10% level. The model explains roughly half of the variation in the capital costs of digester systems. The results show that complete mix digesters are on average much more expensive (roughly $300,000) than covered lagoon digesters with costs and that the presence of energy generation equipment tends to increase the capital costs by nearly $200,000.
Covered Lagoon = 131981ln(x) ‐ 666918R² = 0.7235
Complete Mix = 191949ln(x) ‐ 775022R² = 0.2745
‐
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
‐ 500 1,000 1,500 2,000 2,500 3,000
Cap
ital Costs 2011
USD
Animal Units
Digester Capital Costs by Animal Units, 2011 USDCovered Lagoon Digesters Complete Mix Digesters Log. (Covered Lagoon Digesters) Log. (Complete Mix Digesters)
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Table 16. Regression Results for Capital Costs (2011, USD) of Swine AD Systems.
Parameter Estimate t‐statistic Probability
Intercept ‐631,709 ‐1.26 0.23 Ln(Animal Units) 108,131 1.42 0.18 Energy Production (1=yes, 0=no) 197,027 1.48 0.16 Complete Mix Digester (1 = yes, 0 = no) 336,408 2.9 0.01 F‐Statistic 5.52 0.01 R‐Square 0.56 Adjusted R‐Square 0.46 N= 17
The second regression estimated capital costs as a function of animal units, animal units squared, an indicator variable for whether the operation produced electricity, and an indicator variable for whether the digester was a complete mix digester (Table 17). The results for this formulation are similar to the results of the first regression. Again the style of digester is the most clearly signficant variable determining the cost of AD systems on swine operations. Table 17. Regression Results for Capital Costs (2011, USD) of Swine AD Systems.
Parameter Estimate t‐statistic Probability
Intercept 193,114 ‐0.85 0.41 Animal Units 504 1.13 0.28 Animal Units Squared ‐0.15 ‐0.94 0.37 Energy Production (1=yes, 0=no) 154,125 1.00 0.34 Complete Mix Digester (1 = yes, 0 = no) 369,050 2.98 0.01 F‐Statistic 4.00 0.03 R‐Square 0.57 Adjusted R‐Square 0.43 N= 17
The results from the regression analysis provide capital cost parameter estimates that can be useful when estimating the adoption of swine AD systems. They allow the analyst to estimate adoption of covered lagoon or complete mix digesters as appropriate. They also allow one to incorporate the decision to include electrical generation in the adoption decision.
Summary Swine AD systems have been viewed as having the potential to help hog producers deal with a number of issues such as odor control, neighbor relations, energy production, and provide beneficial environmental solutions such as greenhouse gas emission reductions. In order to better understand what factors might influence adoption of AD by swine producers it is necessary to more fully understand the econmic factors associated with adoption. The anlysis in this study indentifies several important features of the swine AD adoption process and provides
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estimates of parameters that can be used in economic adoption models. These parameters will allow researchers to more fully understand how changing incentives and policies would influence AD adoption on swine operations. The manure handling system present on the farm operation plays a key role in technical viability of AD systems on swine operations. AD systems can be implemented in both liquid manure and slurry based systems. However, most slurry based systems use deep‐pit manure storage beneath the swine operation. These systems are particularly prevalent in the upper Midwest. Unfortunately, it is quite difficult to incorporate an AD system on an operation with deep‐pit manure storage. AD would be much easier to incorporate into a liquid manure systems with lagoon storage. Often these systems utilize a pull‐plug manure handling system. The focus of swine AD adoption should be placed on farms with these types of manure handling systems. In order to develop cost functions from existing swine AD system data it was necessary to charactierize the size of the farms by animal units rather than number of pigs. It was also necessary to adjust capital costs to account for the wide range of time that had elasped between the installation of the various systems. These changes allowed for a more accurate estimation of the capital costs associated with the systems. Both complete mix and covered lagoon digesters have been used on swine operations. Complete mix digesters are more easily heated and are most appropriate in Northern regions of the U.S., while covered lagoon digesters are easier to implement in warmer climates. Investigations of swine AD should allow for the possibility that a farm would install either type of digester system and take into consideration the farm’s location. The analysis should account for the cost differences associated with different digester designs. Analysis of the capital costs of the various digester sytems indicates that other things equal, complete mix systems can be expected to cost over 300 thousand dollars more than covered lagoon digesters. Some existing swine digesters do not contain energy production modules. The analysis of swine AD should allow for the possiblity that the digester be constructed without an energy production unit. The analysis indicates that other things equal, the energy prodcution unit could be expected to result in total capital cost increase of 150 to 200 thousand dollars. The analysis suggests that the greatest potential for adoption of swine AD systems is on farms that currently use lagoon type manure storages. These farms account for a substantial amount of U.S. hog production and are most heavily concentrated in the Southern U.S. When analyzing the potential for adoption one should consider quanitifying the magnitude of benefits for factors such as odor control that would be required for adoption of AD systems.
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