L
Emission Factors in Published Literature

The following sections are excerpts from the committee’s interim report The Scientific Basis for Estimating Air Emissions from Animal Feeding Operations (NRC, 2002a). These sections have been copy edited since the publication of the interim report.

Ammonia

Several well-designed research studies have been published establishing some of the factors that contribute to variations in ammonia (NH3) emissions. For example, Groot Koerkamp et al. (1998) reported wide variations in emissions for different species (cattle, sows, and poultry) measured in different European countries, across facilities within a country, and between summer and fall. Amon et al. (1997) demonstrated that emissions increase as animals age. Differences due to the manure storage system have been demonstrated (Hoeksma et al. 1982). Climate, including temperature and moisture, also affects NH3 emissions (Hutchinson et al., 1982; Aneja et al., 2000). Zhu et al. (2000) reported diurnal variation in emission measurements. With so many sources of variation in NH3 emissions, it is unreasonable to apply a factor determined in one system, over a short period of time, to all animal feeding operations (AFOs) within a broad classification.

Although NH3 emissions have been reported under different conditions, there are few reliable data to estimate total NH3 emissions from all AFO components for all seasons of the year. Twenty-seven articles were used for NH3 emission factors by EPA (2001a); of these, only eleven with original measurements were from peer-reviewed sources. Additional data were taken from six progress reports from contract research. Two of these (Kroodsma et al., 1988; North Caro-



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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs L Emission Factors in Published Literature The following sections are excerpts from the committee’s interim report The Scientific Basis for Estimating Air Emissions from Animal Feeding Operations (NRC, 2002a). These sections have been copy edited since the publication of the interim report. Ammonia Several well-designed research studies have been published establishing some of the factors that contribute to variations in ammonia (NH3) emissions. For example, Groot Koerkamp et al. (1998) reported wide variations in emissions for different species (cattle, sows, and poultry) measured in different European countries, across facilities within a country, and between summer and fall. Amon et al. (1997) demonstrated that emissions increase as animals age. Differences due to the manure storage system have been demonstrated (Hoeksma et al. 1982). Climate, including temperature and moisture, also affects NH3 emissions (Hutchinson et al., 1982; Aneja et al., 2000). Zhu et al. (2000) reported diurnal variation in emission measurements. With so many sources of variation in NH3 emissions, it is unreasonable to apply a factor determined in one system, over a short period of time, to all animal feeding operations (AFOs) within a broad classification. Although NH3 emissions have been reported under different conditions, there are few reliable data to estimate total NH3 emissions from all AFO components for all seasons of the year. Twenty-seven articles were used for NH3 emission factors by EPA (2001a); of these, only eleven with original measurements were from peer-reviewed sources. Additional data were taken from six progress reports from contract research. Two of these (Kroodsma et al., 1988; North Caro-

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs lina Department of Environmental and Natural Resources, 1999) were identified as “preliminary,” and in one case (Kroodsma et al., 1988), the airflow measurement equipment was not calibrated. Emission factors for NH3 were also taken from nine review articles (EPA, 2001a); three of these modeled or interpreted previously reported information with the objective of determining emission factors (Battye et al., 1994; Grelinger, 1998; Grelinger and Page, 1999). Several of the reviews reported factors used in other countries, but not the original research used to develop them. Other reviews summarized data from primary sources that had already been considered. Thus, the review articles may not provide new information. Most measurements and estimates reported did not represent a full life cycle of animal production. As animals grow or change physiological state, their nutrient excretion patterns vary, altering the NH3 volatilization patterns (Amon et al., 1997). A single measurement over a short period of time will not capture the total emission for the entire life cycle of the animal. In addition, most measurements for manure storage represent only part of the storage period. The emissions from storage vary depending on length of storage, changing input from the animal system, and seasonal effects such as wind, precipitation (Hutchinson et al., 1982), and temperature (Andersson, 1998). Only one article reported measurements over an entire year (Aneja et al., 2000), although the measurements may not have been continuous. In this case, NH3 emissions were measured from an anaerobic lagoon using dynamic flow-through chambers during four seasons. Summer emissions were 13 times greater than those in winter, and the total for the year was 2.2 kg NH3-N (nitrogen) per animal (mean live weight = 68 kg) per year. Expressing NH3 emission factors on a per annum and per animal unit (AU) basis facilitates calculation of total air emissions and accounts for variation due to size of AFOs, but it does not account for some of the largest sources of variation in emissions. Clearly, there is a great deal of variation in reported measurements among AFOs represented by a single model. For example, only two references were provided for beef drylot NH3 emission factors, but the values reported were 4.4 and 18.8 kg N/yr per animal (see EPA, 2001a, Table 8-11). For swine operations with pit storage, mean values reported in eight studies ranged from 0.03 to 2.0 kg/yr per pig of less than 25-kg body weight (see EPA 2001a, Table 8-17). This higher rate represents 66 percent of the nitrogen estimated to be excreted by feeder pigs per year (see EPA, 2001a, Table 8-10). The actual variation among AFOs represented by a single model cannot be determined without data representing the entire population of AFOs to be modeled. This would require greater replication and geographic diversity. Much of the variation among studies within a single type of model farm can be attributed to different geographic locations or seasons and the different methods and time frames used to measure the emission factors. The approach in EPA (2001a) was to average all reported values in selected publications—both refereed and nonrefereed—giving equal weight to each ar-

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs ticle. Emission factors reported in some studies represented a single 24-hour sample, while in others, means of several samples were used. Emission factors from review articles were averaged along with the others. Properly using available data to determine emission factors, if it could be done, would require considering the uniqueness and quality of the data in each study for the intended purpose and weighting it appropriately. The causes of the discrepancies among studies would also have to be investigated. Adding emissions from housing, manure storage, and field application, or using emission factors determined without considering the interactions of these subsystems, can easily provide faulty estimates of total emissions of NH3. If emissions from a subsystem are increased, those from other subsystems must be decreased. For example, most of the excreted nitrogen is emitted from housing, much of the most readily available nitrogen will not be transferred to manure storage. If emissions occur in storage, there will be less nitrogen for land application. The current approach ignores these mass balance considerations and simply adds the emissions using emission factors determined separately for each subsystem. Dividing the total manure nitrogen that leaves the farm by the total nitrogen excreted can identify some potential overestimation of emission factors. For example, using emission factors in Table 8-21 of EPA (2001a) for swine model farms, the total ammonia nitrogen emissions for 500 AUs in Model S2 can be estimated to be 1.12 × 104 kg/yr. (Three significant digits are carried for numerical accuracy from the original reference and may not be representative of the precision of the data.) The total nitrogen excreted by 500 AUs of growing hogs is 1.27 × 104 kg/yr (EPA, 2001a). Thus, one calculates that 90 percent of estimated manure nitrogen is volatilized to ammonia, leaving only 10 percent to be accumulated in sludge, applied to crops, and released as other forms of nitrogen (NO [nitric oxide], N2O [nitrous oxide], and molecular nitrogen [N2]). These emission factors suggest that almost all excreted nitrogen is lost as NH3, which seems unlikely. NITRIC OXIDE Although nitric oxide was not specifically mentioned in the request from the U.S. Environmental Protection Agency (EPA), the committee believes that it should be included in this report because of its close relationship to ammonia. An appreciable fraction of manure nitrogen is converted to NO by microbial action in soils and released into the atmosphere. NO participates in a number of processes important to human health and the environment. The rate of emission has been widely studied but is highly variable, and emissions estimates are uncertain. Attempts to quantify emissions of NOx from fertilized fields show great variability. Emissions can be estimated from the fraction of the applied fertilizer nitrogen emitted as NOx, but the flux varies strongly with land use and temperature.

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs Vegetation cover greatly decreases NOx emissions (Civerolo and Dickerson, 1998); undisturbed areas such as grasslands tend to have low emission rates, while croplands can have high rates. The release rate increases rapidly with soil temperature—emissions at 30°C are roughly twice emissions at 20°C. The fraction of applied nitrogen lost as NO emissions depends on the form of fertilizer. For example, Slemr and Seiler (1984) showed a range from 0.1 percent for NaNO3 (sodium nitrate) to 5.4 percent for urea. Paul and Beauchamp (1993) measured 0.026 to 0.85 percent loss in the first six days from manure nitrogen. Estimated globally averaged fractional applied nitrogen loss as NO varies from 0.3 percent (Skiba et al., 1997) to 2.5 percent (Yienger and Levy, 1995). For the United States, where 5 Tg of manure nitrogen is produced annually, NOx emissions directly from manure applied to soil are roughly 1 percent, or 0.05 Tg/yr, of emissions from crops used as animal feed are neglected. Williams et al. (1992a) developed a simplified model of emissions based on fertilizer application and soil temperature. They estimated that soils accounted for a total of 0.3 Tg, or 6 percent of all U.S. NOx emissions for 1980. Natural variability of emissions dominates the uncertainty in the estimates. In order of increasing importance, errors in land use data are about 10-20 percent, and experimental uncertainty in direct NO flux measurements is estimated at about ±30 percent. The contribution of soil temperature to uncertainty in emissions estimates stems from uncertainty in inferring soil temperature from air temperature and from variability in soil moisture. Williams et al. (1992) show that their algorithm can reproduce the observations to within 50 percent. A review of existing literature indicates that agricultural practices (such as the fraction of manure applied as fertilizer, application rates used, and tillage) introduce variability in NO emissions of about a factor of two. Variability of biomes to which manure is applied (such as short grass versus tallgrass prairie) accounts for an additional factor of three (Williams et al., 1992a; Yienger and Levy, 1995; Davidson and Klingerlee, 1997). Future research may have to focus on determining the variability of emissions, measured as a fraction of the applied manure nitrogen, with agricultural practices, type of vegetative cover, and meteorological conditions. HYDROGEN SULFIDE Most of the studies on hydrogen sulfide (H2S) emissions from livestock facilities were conducted recently and included current animal housing and manure management practices. Several recent publications from Purdue University document H2S emissions from mechanically ventilated swine buildings (Ni et al., 2002a, 2002b, 2002c, 2002d). A pulsed fluorescence SO2 (sulfur dioxide) analyzer with an H2S converter was used to measure H2S concentrations in the air, and a high-frequency (16 or 24 sampling cycles each day) measurement protocol was used for continuous monitoring. In one of the studies reported, H2S emission

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs from two 1000-head finishing swine buildings with under-floor manure pits in Illinois was monitored continuously for a six-month period from March to September 1997. Mean H2S emission was determined to be 0.59 kg/d, or 6.3 g/d per 500-kg animal weight. Based on emission data analysis and field observation, researchers noticed that different gases had different gas release mechanisms. Release of H2S from the stored manure, similar to carbon dioxide and sulfur dioxide, was through both convective mass transfer and bubble release mechanisms. In comparison, the emission of NH3 was controlled mainly by convective mass transfer. Bubble release is an especially important mechanism controlling H2S emission from stirred manure. The differences in release mechanisms for different gases are caused mainly by differences in solubility and gas production rates in the manure. Some measurements from swine buildings were also conducted in Minnesota (Jacobson, 1999; Wood et al., 2001). Very few data are available on H2S emission from other types of livestock facilities such as dairy, cattle, and poultry. Using emission data from swine operations to estimate emission factors for other species such as dairy and poultry is not scientifically sound. Outside manure storage, such as storage in tanks or anaerobic lagoons, can be an important source of H2S emissions. Emission data for such sources are lacking in the literature. EPA (2001a) stated that H2S emissions from solid manure systems—such as beef and veal feedlots, manure stockpiles, and broiler and turkey buildings—were insignificant, based on the assumption that these systems are mostly aerobic. Such an assumption is not valid because it is not based on scientific information. Published data indicate that a significant amount of H2S is emitted from the composting of poultry manure when the forced aeration rate is low (Schmidt, 2000). It is very likely that H2S is emitted from other solid manure sources as well. H2S is produced biologically whenever there are sulfur compounds, anaerobic conditions, and sufficient moisture. Wet conditions occur in animal feedlots and uncovered solid manure piles during precipitation or in rainy seasons. Scientific studies should be conducted to provide emission data. NITROUS OXIDE Nitrous oxide is both a greenhouse gas and the main source of stratospheric NOx, the principal sink for stratospheric ozone; predominantly biological processes (nitrification and denitrification) produce N2O in soils; fertilization increases emissions. Although EPA (2001a) states that “emission factors for N2O were not found in the literature,” a large body of research exists on N2O emissions from livestock, manure, and soils. Time constraints prevent a thorough review of the literature, but this section condenses the main points of a few recent papers and attempts to summarize the state of the science. N2O emissions were reviewed for the Intergovernmental Panel on Climate Change (IPCC, 2001; see also Mosier et al., 1998) with the objective of balancing

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs the global atmospheric N2O budget and predicting future concentrations. Although substantial uncertainties exist regarding the source strength for N2O, agricultural activities and animal production are the primary anthropogenic sources. According to the IPCC (2001), these biological sources can be broken down into direct soil emissions, manure management systems, and indirect emissions. These three sources are about equally strong, each contributing about 2.1 Tg N/yr to the atmospheric N2O burden. Total anthropogenic sources are estimated to be 8.1 Tg N/yr, and natural sources about 9.9 Tg N/yr, for a total of 18 Tg N/yr (Prather et al., 2001). Soils The Intergovernmental Panel on Climate Change estimated soil N2O emissions as a fraction of applied nitrogen. IPCC assumed that 1.25 percent of all fertilizer nitrogen is released from soils as N2O, with a range of 0.25 to 2.25 percent. Estimating direct soil N2O emissions is subject to the same uncertainties as NO emissions. The fraction of applied nitrogen emitted as N2O varies with land use, chemical composition of the fertilizer, soil moisture, temperature, and organic content of the soil. Of the global value of 2.1 Tg N/yr emitted directly from soils, Mosier et al. (1998), using the IPCC1 method, estimates that manure fertilizer contributes 0.63 Tg/yr. Using the Intergovernmental Panel on Climate Change method, 5 Tg/yr of manure nitrogen in the United States would yield 0.06 Tg N/yr as N2O. Li et al. (1996) employed a model that accounts for soil properties and farming practices and concluded that the Intergovernmental Panel on Climate Change method underestimates emissions. They put annual N2O emissions from all crop- and pastureland (including emissions from manure and biosolids applied as fertilizer) in the United States in the range of 0.9 to 1.1 Tg N/ yr, although this number includes what Mosier et al. (1998) refers to as “indirect” sources. Nitrification is primarily responsible for NO production, but both nitrification and denitrification lead to N2O release from soils, and both aerobic and anaerobic soils emit N2O. The following studies show some of the variability in estimates of the efficiency of conversion of manure nitrogen to N2O emission. Paul and Beauchamp (1993) measured 0.025 to 0.85 percent of manure nitrogen applied to soil in the lab lost as N2O, but Wagner-Riddle et al. (1997) found 3.8 to 4.9 percent from a fallow field. Petersen (1999) observed 0.14 to 0.64 percent emission from a barley field. Lessard et al. (1996) measured 1 percent emission of manure nitrogen applied to corn in Canada. Yamulki et al. (1998) measured emissions from grassland in England and found 0.53 percent of fecal nitrogen and 1.0 percent of urine nitrogen lost as N2O over the first 100 days. Whalen et al. (2000) applied swine lagoon effluent to a spray field in North Carolina and observed 1.4 percent emission of applied nitrogen as N2O. Flessa et al. (1995) ap-

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs plied a mixture of urea and NH4NO3 (ammonium nitrate) to a sunflower field in southern Germany and measured an N2O emission of >1.8 percent of the nitrogen applied. Long-term manure application (possibly linked to increased organic content of soils) appears to increase N2O production. Rochette et al. (2000) determined that after 19 years of manure application, 1.65 percent of applied nitrogen was converted to N2O. Chang et al. (1998) followed the same soil for 21 years of manure application and found 2-4 percent of manure nitrogen converted to N2O. Flessa et al. (1996) determined a total emission of N2O from cattle droppings on a pasture equivalent to 3.2 percent of the nitrogen excreted. Clayton et al. (1994) showed that grassland used for cattle grazing could convert a larger portion of fertilizer NH4NO3 nitrogen to N2O (5.1 percent versus 1.7 percent for ungrazed grassland). Williams et al. (1999) applied cow urine to pasture soil in the lab and observed a 7 percent partition of the nitrogen to N2O. Manure Management Several recent studies indicate that N2O emissions from manure can be large (Jarvis and Pain, 1994; Bouwman, 1996; Mosier et al., 1996; IPCC, 2001). For example, Jungbluth et al. (2001) measured 1.6 g N2O/d per 500 kg of livestock emitted directly from dairy cattle; Amon et al. (2001) measured 0.62 g N2O/d per 500 kg of livestock. Groenestein and VanFaassen (1996) found 4.8 to 7.2 g N/d per pig as N2O. The Intergovernmental Panel on Climate Change (2001) estimates N2O emissions from animal production (including grazing animals) as approximately 2.1 Tg N/yr. These estimates are based on an assumed average fraction of manure nitrogen converted to N2O and are subject to variability due to temperature, moisture content, and other environmental factors in a manner similar to soil emissions. Berges and Crutzen (1996) estimated the rate of N2O emissions by measuring the ratio of N2O to NH3. They determined that 40 Tg N/yr of cattle and swine manure in housing and storage systems generates 0.2-2.5 Tg N/yr as N2O; they did not account for additional emissions outside the housing and storage systems. Indirect Emissions Formation of N2O results indirectly from the release of NH3 to the atmosphere and its subsequent deposition as NH3-NH4+ or nitrate, or from their leaching and runoff (IPCC, 2001). Human waste in sewage systems is another indirect path to atmospheric N2O. On a global scale, leaching and runoff give an estimated 1.4 Tg N/yr; atmospheric deposition, 0.36 Tg N/yr; and human sewage, about 0.2 Tg N/yr—for a total of about 2 Tg N/yr. Dentener and Crutzen (1994) pointed out that atmospheric reactions involving NH3 and NO2 (nitrogen dioxide) could lead to production of N2O; however the strength of this source is unknown.

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs Summary The uncertainty in emissions of N2O from AFOs is similar to that for NO—roughly a factor of three. While no-till agriculture decreases emissions of most greenhouse gases (Civerolo and Dickerson, 1998; Robertson et al., 2000), it appears to increase N2O. The means for decreasing emissions do exist. Smith et al. (1997) suggested that substantial reductions in N2O could be achieved through matching fertilizer type to environmental conditions and by using controlled-release fertilizers and nitrification inhibitors. Timing and placement of fertilizer and controlling soil conditions could also help decrease N2O production. The vast body of work on emissions of N2O from agricultural activities cannot be thoroughly reviewed in the short time frame of this study. METHANE Four original research articles, an agency report, one doctoral thesis, and one review article are cited in EPA (2001a) in estimating emission factors for methane (CH4). Much research was overlooked since a number of papers and reports describing CH4 emission rates can be found in the literature. Fleesa et al. (1995) reported CH4 fluxes of 348 to 395 g per hectare (ha) per year in fields fertilized with manure. A value of 1 kg/m2 per year CH4 (carbon equivalents) has been reported for an uncovered dairy yard (Ellis et al., 2001). Amon et al. (2001) concluded that methane emissions were higher for anaerobically treated dairy manure than for composted manure. EPA (2001a) estimates the CH4 production potential of manure as the maximum quantity of CH4 that can be produced per kilogram of volatile solids in the manure. However, a considerable amount of CH4 is lost during eructation (belching), which this estimate does not take into account. In estimating the CH4 emission factor for the model farm, EPA (2001a) did not take several factors into consideration, such as the difficulty associated with measuring emissions without having a negative impact on animals. New methods have been designed to measure CH4 emissions under pasture conditions with minimal disturbance of the animals (Leuning et al., 1999). There are some limitations to this technique; it does not work well with low wind speeds or rapid changes in wind direction, and requires high-precision gas sensors. Methane production increases while cattle are ruminating (digesting) feedstuffs—both grass and high-energy rations. In one study, lactating beef cattle grazing on grass pasture were observed to have 9.5 percent of the gross energy intake converted to CH4 (McCaughey et al., 1999). During periods when the cattle are fed a high-grain diet, approximately 3 percent of gross intake energy is converted to CH4 (Johnson et al., 2000). Methods for estimating CH4 emissions from other sources—such as rice paddies, wetlands, and tundra in Alaska—have been well studied. However, the mod-

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs els used to extrapolate emissions over these large areas may not apply to AFOs because of the different variables that must be taken into account. This is a knowledge gap that has to be addressed. PARTICULATE MATTER A limited number of studies have reported emission factors for particulate matter (PM) for various confinement systems. One of the most recent reports includes the results of an extensive study that examined PM emissions from various confinement house types, for swine, poultry, and dairy in several countries in Northern Europe (Takai et al., 1998), and a few studies report cattle or dairy drylot emissions in the United States (Parnell et al., 1994; Grelinger, 1998; Hinz and Linke, 1998; USDA, 2000b). Some of this work was cited by EPA (2001a). Two PM10 emission factors for cattle were reported for drylot feed yards by Grelinger (1998) and USDA (2000b). Another emission factor for poultry broiler house emissions was also included (Grub et al., 1965). According to the EPA (1995b) AP-42 document, emission factor data are considered to be of good quality when the test methodology is sound, the sources tested are representative, a reasonable number of facilities are tested, and the results are presented in enough detail to permit validation. Whenever possible, it is desirable to obtain data directly from an original report or article, rather than from a compilation or literature summary. Only a very limited number of published papers have been used to estimate PM emission factors for AFOs. Some of the papers utilized do not appear to be of the highest quality or relevance to modern operations. Takai et al. (1998) and Grub et al. (1965) appeared in the peer-reviewed literature, but other work cited was not. Takai et al. (1998) represents one of the most extensive studies conducted on livestock houses to date; it made 231 field measurements of dust concentrations and dust emissions from livestock buildings across Northern Europe. Factors included in their study design were country (England, the Netherlands, Denmark, and Germany); housing (six cattle housing types, five swine housing types, and three poultry housing types); season (summer and winter); and diurnal period (day and night). Each field measurement was for a 12-hour period, and each house was sampled for a 24-hour period, or two 12-hour samples per house. Where possible, measurements were repeated at the same house for both seasons (Wathes et al., 1998). One reference (Grelinger, 1998) appeared in a specialty conference proceedings (non-peer reviewed), and it is not clear how the emission rates were derived. The U.S. Department of Agriculture (USDA, 2000b) summarizes results from other cattle studies. The Grub et al. (1965) study was more than 35 years old and reported emission factors for a poultry confinement configuration (chambers 2.4 m by 3.0 m by 22.1 m high, ventilated at a constant airflow rate) that is not used in current operations.

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs The sizes of ambient particulate matter varied from study to study, ranging from “respirable” and “inhalable” to total suspended particulates (TSPs). Takai et al. (1998) sampled inhalable dust using European Institute of Occupational Medicine dust samplers. The respirable fraction was measured using cyclone dust samplers with a 50 percent cut diameter of 5 μm. Grub et al. (1965) measured dust rather than PM10; it is not clear whether the emission factors quoted represented dust or PM10 estimated from the dust. Grelinger (1998) measured TSP and obtained PM10 by multiplying by 0.25. USDA (2000b) reported that TSP was measured rather than PM10, according to the AFO project data summary sheets in EPA (2001a). The representativeness of emission factors in the literature is also questionable. For example, the emission factors reported by Takai et al. (1998) were based on data collected for very brief periods, one to two days at each barn. Relevant work was overlooked in the estimation of cattle feedlot PM emissions (e.g., Parnell et al., 1994), or it is not clear from EPA (2001a) whether that work was included in the USDA (2000b) publication cited. Auvermann et al. (2001) extensively reviewed the PM emission factors suggested for AFOs (for both feedlots and feed mills) in AP-42 (EPA, 1995b). They pointed out that the PM10 emission factor for cattle feedlots specified in AP-42 was five times as high as the more recent values determined by Parnell et al. (1994). EPA (2001a) did not discuss the AP-42 emission factors. When more than one study was found that examined PM emissions, the results were not consistent among studies. The two poultry house emission factors differed by an order of magnitude and were simply averaged to characterize PM emissions from poultry houses, even though the Grub et al. (1965) study was of questionable relevance to today’s production systems. The two drylot cattle yard PM emission factors differed by a factor of five and were averaged to characterize the PM emissions from drylots. Relevant work was overlooked by EPA (2001a) for the estimation of cattle feed yard PM emissions. Recent work by Holmen et al. (2001) using lidar (light detection and ranging) was not included. The Parnell et al. (1994) study was not cited, but it is not clear whether that work was included in USDA (2000b), which was cited. Potential PM emissions from land spraying with treatment lagoon effluent are assumed to be negligible and thus were not considered further by EPA (2001a). For PM, unlike most other air pollutants, emission factors developed for use in emission inventories and for dispersion modeling can, ideally, be reconciled using receptor modeling techniques. Receptor modeling makes use of the fact that atmospheric PM is composed of many different chemical species and elements. The sources contributing to ambient PM in an airshed also have specific and unique chemical compositions. If there are several sources and if there is no chemical interaction between them that would cause an increase or decrease, then the total PM mass measured at a “receptor” location will be the sum of the contributions from the individual sources. By analyzing the PM for various chemical

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs species and elements, it should then be possible to back-calculate the contributions from various sources in the airshed. A variety of techniques are available for doing this; some (e.g., the chemical mass balance model; Watson et al., 1997) rely on the availability of predetermined source chemical composition libraries and are based on regression to determine the amounts contributed by various sources. Other receptor models are based on multivariate techniques and do not require source “fingerprints” determined a priori, but do require large numbers of receptor samples so that statistical methods can be applied. Target transformation factor analysis (Pace, 1985) and positive matrix factorization (Ramadan et al., 2000) are two examples of multivariate techniques that do not require explicit source composition data. Source apportionment may be especially useful for understanding the contributions from AFOs to the ambient PM in an airshed. Both receptor and dispersion modeling are associated with a significant level of uncertainty. The best approach is to use a combination of methods and attempt to reconcile their results. VOLATILE ORGANIC COMPOUNDS Emissions of volatile organic compounds (VOCs) from stationary and biogenic sources are significant, but limited data are available in most regions of the world. This situation makes it difficult to determine the impact of VOCs on a global basis. However, the United States (EPA, 1995a) and Europe have accumulated extensive data on the quantities and sources of their VOCs emitted to the atmosphere. The three references in EPA (2001a) on VOC emission factors—Alexander, 1977; Brock and Madigan, 1988; and Tate, 1995—came from microbiology textbooks. Thus, the basis for determining VOC emission factors was rather weak. Despite the paucity of data, attempts are being made to shed light on the estimation of emission factors for VOCs. For example, some for pesticides have been determined by the Environmental Monitoring Branch of the Department of Pesticide Regulation in Sacramento, California (California Environmental Protection Agency, 1998, 1999, 2000). The applicability of these efforts to VOC emissions from AFOs is unknown at this time. Ongoing studies to determine emission rates of VOCs were not included in EPA (2001a). Scientists from Ames, Iowa, have developed techniques to collect and measure VOCs emitted from lagoons and earthen storage systems (Zahn et al., 1997). They found that 27 VOCs were prevalent in most samples and could be classified as phenols, indoles, alkanes, amines, fatty acids, and sulfur-containing compounds. Emission rates for many of these were determined at several sites, and the data have been transferred to EPA and state air quality specialists. According to EPA (2001a), estimation of VOC emissions from confinement facilities, manure storage facilities, and manure application sites is difficult because of the lack of a reasonable method for estimating CH4 production. CH4

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs does not provide an appropriate basis for predicting VOC volatilization potential in livestock management systems. Gas-transfer velocities for CH4 and VOCs differ by several hundredfold (MacIntyre et al., 1995). In addition, surface exchange rates for some VOCs are influenced by solution-phase chemical factors that include ionization (pH), hydrogen bonding, and surface slicks (MacIntyre et al., 1995). Physical factors such as temperature, irradiance, and wind are also major factors in the emission rates of sparingly soluble VOCs from liquid or semisolid surfaces (MacIntyre et al., 1995; Zahn et al., 1997). The differences in wind and temperature exposures between outdoor and indoor manure management systems can account for between 51 and 93 percent of the observed differences in VOC emissions (MacIntyre et al., 1995). This analysis suggests that exposure factors can account for differences observed in VOC flux rates, VOC air concentrations, and odor intensities. Therefore, the equation used to model the emission factor for VOCs in EPA (2001a) cannot be extrapolated for the majority of livestock operations. Receptor modeling techniques can provide information on air quality impacts due to VOC emissions from AFOs. For example, Watson et al. (2001) reviewed the application of chemical mass balance techniques for VOC source apportionment. Multivariate methods have also been applied to source apportionment of ambient VOCs (Henry et al., 1995). Receptor modeling techniques to apportion VOCs from AFOs may be limited because many of the expected compounds may be formed in the atmosphere, react there, or have similar emission profiles from many sources. To understand the contribution of AFO VOCs to ozone formation and gain insight into effective control strategies, measurements of individual compounds are essential. This is a difficult task because of the large number of compounds involved. The most widely used analytical technique involves separation by gas chromatography (GC) followed by detection using a flame-ionization detector (FID) or mass spectrometer (MS). The latter is useful for identification of nonmethane hydrocarbons using cryofocusing. VOC detectors that can be used for real-time measurements of typical ambient air are commercially available. New portable devices that use surface acoustic wave technology have been developed for field measurements of VOCs. Their sensitivity is not adequate to measure the low levels that may be harmful to humans. Research to support the development of more sensitive devices is needed. There is a lack of information on the acute and chronic toxicological effects of VOCs from agricultural operations on children and individuals with compromised health. Recent epidemiological studies (without environmental measurements of VOCs) have shown higher incidences of psychological dysfunction and health-related problems in individuals living near large-scale swine production facilities (Schiffman et al., 1995; Thu et al., 1997). Further studies are needed to better understand the risks associated with human exposure to VOCs from AFOs.

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs ODOR In a recent review, Sweeten et al. (2001) define odor as the human olfactory response to many discrete odorous gases. Regarding the constituents of animal odors, Eaton (1996) listed 170 unique compounds in swine manure odor, while Schiffman et al. (2001) identified 331. Hutchinson et al. (1982) and Peters and Blackwood (1977) identified animal waste as a source of NH3 and amines. Sulfides, volatile fatty acids, alcohols, aldehydes, mercaptans, esters, and carbonyls were identified as constituents of animal waste by the National Research Council (NRC, 1979), and by Miner (1975), Barth et al. (1984), and the American Society of Agricultural Engineers (1999). Peters and Blackwood (1977) list 31 odorants from beef cattle feedlots. Zahn et al. (2001) found that nine VOCs correlated with swine odor. The sources of odors include animal buildings, feedlots, manure handling, manure storage and treatment facilities, and land applications. Sweeten et al. (2001) also outline various scientific and engineering issues related to odors, including odor sampling and measurement methods. Odors are characterized by intensity or strength, frequency, duration, offensiveness, and character or quality. Odor concentration is used for odor emission measurement. Several methods are available for measuring odor concentrations including sensory methods, measurement of concentrations of specific odorous gases (directly or indirectly), and electronic noses. Human sensory methods are the most commonly used. They involve collecting and presenting odor samples (diluted or undiluted) to panelists under controlled conditions using scentometers (Huey et al., 1960; Miner and Stroh, 1976: Sweeten et al. 1977, 1983, 1991; Barnebey-Cheny, 1987), dynamic olfactometers, and absorption media (Miner and Licht, 1981;Williams and Schiffman, 1996; Schiffman and Williams, 1999). Among sensory methods the Dynamic Triangle Forced-Choice Olfactometer (Watts et al., 1991; Ogink et al., 1997; Hobbs et al., 1999) appears to be the instrument of choice. Currently, there is an effort among researchers from several universities, including Iowa State University, the University of Minnesota, Purdue University, and Texas A & M University, to standardize the measurement protocol for odor measurement using the olfactometer. Some odor emission data are available in the literature, particularly for swine operations (e.g., Powers et al., 1999). However, there are discrepancies among the units used in different studies. Standard measurement protocols and consistent units for odor emission rates and factors have to be developed. As shown in a recent review (Sweeten et al., 2001), the data (see Table L-1) on odor or odorant emission rates, flux rates, and emission factors are lacking for most livestock species (and for different ages and housing) and are needed for the development of science-based abatement technologies. Further research in well-equipped laboratories is needed as a precursor to rational attempts to develop emission factors for odor and odorants.

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Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs TABLE L-1 Odor Emission Rates from Animal Housing as Reported in the Literature Animal Type Location Odor Emission Flux Rate (OU/s-m2)a Reference Nursery pigs (deep pit) Indiana 1.8a Lim et al., 2001 Nursery pigsb Netherlands 6.7 Ogink et al., 1997; Verdoes and Ogink, 1997 Nursery pigs Minnesota 7.3-47.7 Zhu et al., 1999 Finishing pigs Minnesota 3.4-11.9 Zhu et al., 1999 Finishing pigsc Netherlands 19.2 Ogink et al., 1997; Verdoes and Ogink, 1997 Finishing pigsd Netherlands 13.7 Ogink et al., 1997; Verdoes and Ogink, 1997 Finishing pigs (daily flush)e Indiana 2.1 Heber et al., 2001 Finishing pigs (pull-plug)e Indiana 3.5 Heber et al., 2001 Finishing pigs (deep pit) Illinois 5.0 Heber et al., 1998 Farrowing sows Minnesota 3.2-7.9 Zhu et al., 1999 Farrowing sows Netherlands 47.7 Ogink et al., 1997; Verdoes and Ogink, 1997 Gestating sows Minnesota 4.8-21.3 Zhu et al., 1999 Gestating sows Netherlands 14.8 Ogink et al., 1997; Verdoes and Ogink, 1997 Broilers Australia 3.1-9.6 Jiang and Sands, 1998 Broilers Minnesota 0.1-0.3 Zhu et al., 1999 Dairy cattle Minnesota 0.3-1.8 Zhu et al., 1999 NOTE: Rates have been converted to units of OU/s-m2 for comparison purposes, where OU = odor unit. aNet odor emission rate (inlet concentration was subtracted from outlet concentration). bNumber of animals calculated from average animal space allowance. cPigs were fed acid salts. dMultiphase feeding. eOdor units normalized to European odor units based on n-butanol. SOURCE: Adapted from Sweeten et al. (2001).