Identification and quantification of volatile organic compounds from a dairy

ARTICLE IN PRESS

Atmospheric Environment 40 (2006) 1480–1494 www.elsevier.com/locate/atmosenv

Identification and quantification of volatile organic compounds from a dairy Jenny Filipy, Brian Rumburg, George Mount, Hal Westberg, Brian Lamb Laboratory for Atmospheric Research, Department of Civil and Environmental Engineering, Washington State University, Pullman, WA 99164-2910, USA Received 13 February 2005; received in revised form 21 October 2005; accepted 21 October 2005

Abstract Volatile organic compounds (VOCs) that contribute to odor and air quality problems have been identified from the Washington State University Knott Dairy Farm using gas chromatography–mass spectroscopy (GC–MS). Eighty-two VOCs were identified at a lactating cow open stall and 73 were detected from a slurry wastewater lagoon. These compounds included alcohols, aldehydes, ketones, esters, ethers, aromatic hydrocarbons, halogenated hydrocarbons, terpenes, other hydrocarbons, amines, other nitrogen containing compounds, and sulfur-containing compounds. The concentration of VOCs directly associated with cattle waste increased with ambient air temperature, with the highest concentrations present during the summer months. Concentrations of most detected compounds were below published odor detection thresholds. Emission rates of ethanol (10267513 mg cow
1 s
1) and dimethyl sulfide (DMS) (13.8710.3 mg cow
1 s
1) were measured from the lactating stall area using an atmospheric tracer method and concentrations were plotted using data over a 2-year period. Emission rates of acetone (3.0370.85 ng cow
1 s
1), 2butanone (145735 ng cow
1 s
1), methyl isobutyl ketone (3.4671.11 ng cow
1 s
1), 2-methyl-3-pentanone (25.178.0 ng cow
1 s
1), DMS (2.1970.92 ng cow
1 s
1), and dimethyl disulfide (DMDS) (16.173.9 ng cow
1 s
1) were measured from the slurry waste lagoon using a laboratory emission chamber. r 2005 Elsevier Ltd. All rights reserved. Keywords: Cattle; Livestock; Manure; Odors; Emissions

1. Introduction Livestock operations in the United States are an escalating environmental concern. The industry’s movement toward increasing livestock number and density results in the concentrated release of odorous gases which has gained considerable attention from the public in recent years (NRC, Corresponding author. Tel.: +1 509 335 3790.

E-mail address: [email protected] (G. Mount). 1352-2310/$ - see front matter r 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2005.10.048

2003). Complaints from people living near livestock facilities have prompted regulatory agencies such as the US Environmental Protection Agency (EPA, 2003) and the US Department of Agriculture (USDA) to officially address public concerns. The US National Research Council (NRC) has reported that odorous compounds such as ammonia (NH3), volatile organic compounds (VOCs), and hydrogen sulfide (H2S) have an important effect on the quality of life of residents living near livestock facilities (NRC, 2003).

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Odorous compounds emitted from livestock waste are produced from the incomplete anaerobic fermentation of waste by bacteria (Mackie et al., 1998). The six major groups of odorous compounds include volatile fatty acids (VFA), NH3, volatile amines, phenols and indoles, as well as sulfurcontaining compounds (Mackie et al., 1998). Dairy cattle operations have multiple sources of odor emissions associated with the degradation of manure, e.g. housing, waste storage facilities, as well as during land application of animal waste (Mount et al., 2002; NRC, 2003). There are few studies quantifying the concentrations and emission rates of gaseous compounds emitted from livestock waste, and those studies primarily address swine operations (O’Neill and Phillips, 1992; Schiffman et al., 2001; Zahn et al., 1997). Olfactory methods have been used to quantify odor intensities of livestock facilities with the use of subjective human panelists (Jansen and Klarenbeek, 1986; Misselbrook et al., 1997; Powers et al., 1999; Sweeten et al., 1977; Zahn et al., 2001; Zhu et al., 2000). Little data have been collected to identify and quantify gaseous compounds emitted from open stall dairy operations (Miller and Varel, 2001; Rabaud et al., 2003; Sunesson et al., 2001) and no VOC emission rates have been quantified. Rabaud et al. (2003) identified 35 compounds in the air from a small industrial dairy located in northern California including acids, alcohols, aldehydes, esters, ketones, halogenates and amines. Highest concentrations were of 1-propanol, butylamine, acetic acid, DMSO, ethyl ether and methyl isobutyrate (386–748 mg m
3). Sunesson et al. (2001) identified 70 compounds in the air at eight dairy farms in northern Sweden including alcohols, aldehydes, carboxylic acids, esters, hydrocarbons and monoterpenes. The compounds with the highest concentrations were p-cresol, 2-butanone, ethyl acetate, a-pinene, and D3-carene (10–200 mg m
3). Miller and Varel (2001) identified 14 compounds in manure samples from a cattle feedlot located at the USDA research center in Nebraska. Liquid phase samples (20% slurry mixture) contained L-lactate, alcohols, VFA, phenols, indoles, aromatics, and benzoates with the highest liquid concentrations of ethanol (37 mM) and acetic acid (100 mM) after incubation. Concentrations and emissions will be highly dependent on feed, farming practices, and environmental conditions. The objectives of this paper are: (1) Identify gaseous compounds emitted from a slurry storage

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lagoon and an open stall area housing lactating cows at the Washington State University (WSU) Knott Dairy Farm. (2) Report concentration ranges and seasonal variations. (3) Report emission rates for some compounds using an atmospheric tracer method or an emission chamber. (4) Complement NH3 research (Mount et al., 2002; Rumburg et al., 2004) by providing a better understanding of what compounds, in addition to NH3, are contributing to the overall odor produced from dairies. 2. Methods and materials 2.1. Location and dairy characteristics The WSU Knott Dairy farm is located approximately 8 km southwest of the WSU Pullman, WA campus. Fig. 1 shows the layout of the dairy. There are 414 Holstein dairy cows maintained at the dairy with 165 lactating cows which contribute to slurry lagoon waste and stall air emissions. The lactating cows are fed a controlled ration of corn (32%), barley (17.3%), peas (15%), wheat (19%), corn gluten meal (4.5%), soybean meal (4.5%), molasses (2.0%), sodium bicarbonate (2.0%), limestone (1.5%), TM salt premix (1.5%), magnesium oxide (0.4%), vitamin A and D premixes (0.05% each), and cellulose gum (0.05%). In addition to the controlled ration (35.65% of total feed), a bulk feed of alfalfa silage (25.62%), alfalfa hay (22.28%), wheat mill run (6.57%), whole cottonseeds (9.88%) is given to the cows in bins that are kept full most of the day. The total percentage of crude protein in the lactating cows diet is 19% of 25 kg day
1 cow
1 total dry feed. Milk production is approximately 41 kg cow
1 day
1. 2.2. Air sampling Air samples were collected from November 2001 to October 2003. Sample collection occurred every 7–14 days in the summer months and once a month from late fall to early spring. Air sampling locations were primarily downwind from the major animal waste sources of lagoon 2 inlet and one lactating cow open stall area as shown in Fig. 1. Background samples were collected upwind of the dairy and showed no upwind sources. VOC samples were collected on a two stage, Carbotrap B and Carbosieve S-III, adsorbent cartridge manufactured by Supelco (Bellefonte, PA) packed into a 6.4 mm diameter glass tube. This combination of adsorbents

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Weather Station 746

46.6950

748

46.6945

Pump House

Lagoon 2

*

Inlet

Lagoons 3 & 4 Lagoon 1

750

North Latitude

746

46.6940

+

46.6935

¤

¤

•• + • ••* • • ¤

+

Milking Parlor, Stalls & Barns

50 m

748

s

750

752 754

s

Solids Separator

s 752

s

754 756

46.6930

50 m

WSU Knott Dairy 758

117.2430

117.2420

117.2410

117.2400

West Longitude Fig. 1. Topographic map of the WSU Knott Dairy (elevation in m).+ represents 4 SF6 release points; represents 1 SF6 release point (15 total SF6 points); S represents syringe samplers;  represents the line inlets for the SF6 sampling system; n indicates where VOC air samples where collected for this study; - indicates wind direction during tracer experiments.

retained VOCs in the C2–C12 molecular weight range. Highly volatile compounds were collected cryogenically in 6.4 mm diameter U-shaped glass tubes. The lower portion of the U-shaped tube containing glass beads with Pyrex glass wool plugs was immersed in liquid oxygen (
83 1C) during sample collection. Evacuated canisters with digital pressure meters, manufactured by PSI-Tronix (Tulare, CA), were used to measure the volume of air passing through the two sampling devices. Sample volumes ranged from 600 to 3500 mL with sampling rates from 80 to 250 mL min
1 over a 15–30 min sampling time. Samples were stored at 4 1C until analyzed, typically within 1–2 days after sampling; 1 week was the maximum storage time. Duplicate samples showed up to 27% difference in concentration due to instrument variation and differences in cartridge adsorption and desorption. To measure compounds from the lagoon that might be present at ambient concentrations below the detection limit of the GC–MS, the headspace

above a bottle half full with slurry from lagoon 2 was sampled. This experiment was designed to concentrate compounds from the lagoon to a level above the detection limit of the GC–MS. These compounds were used only for identification purposes and no concentration or emission values were reported for this experiment. Wind speed, temperature, and solar radiation measurements were taken using a Campbell Scientific Weather Station located on the northeast side of lagoon 2 (Fig. 1). Wind speed was measured at a height of 3 m with a RM Young 05103 Wind Monitor, temperature was measured with a Campbell Scientific Model HMP35C Probe at a height of 2 m, and solar radiation measurements were made with a LI200S Pyranometer. All meteorological measurements were recorded as 5 min averages. A sonic anemometer giving wind speed and direction in 3 dimensions manufactured by Gill Instruments (Lymington, England) with 10 Hz response was used at the stall area for emission rate experiments.

ARTICLE IN PRESS J. Filipy et al. / Atmospheric Environment 40 (2006) 1480–1494

2.3. Sample analysis After field collection, samples were analyzed in the laboratory using a 6890 Gas Chromatograph coupled to a 5973 Mass Spectrometer (GC–MS) (Agilent Inc., Palo Alto, CA). Adsorbent cartridges were placed in an aluminum block heater at 250 1C for 20 min for complete thermal desorption. The sample was transferred to the preconcentration loop using nitrogen gas. The cryogenic loop was immersed in a dewar filled with liquid oxygen. Samples that were directly collected in a cryogenic loop were not subjected to the pre-concentration step. To trap all of the compounds from the sample in a narrow band at the head of the GC column, the column oven was cooled to –50 1C before sample injection. The sample was injected into the column with helium carrier gas after exchange of the liquid oxygen dewar for one containing hot water at approximately 80 1C. Two GC capillary columns were employed: a DB-5MS, 30 m in length, 0.32 mm inner diameter, with a film thickness of 1 mm and a DB-1, 100 m in length, 0.32 mm inner diameter with a film thickness of 3 mm (Agilent, Inc., Palo Alto, CA). Temperature started at
50 1C and increased to 180 1C at 4 1C min
1 for the 30 m column and 6 1C min
1 for the 100 m column. No samples were duplicated on both columns. Compounds were identified using the National Institute of Standards and Technology (NIST) library of compound mass spectra for fragmentation patterns generated at 70 eV. Select compounds were quantified using individual standards. 2.4. Standards A TO-14 standard was used with an analytical accuracy of 710% (Supelco, Bellefonte, PA). Dimethyl sulfide (DMS) and dimethyl disulfide (DMDS) standards were made using permeation tubes and a Dynacalibrator (Model 220-P15, Metronics Associates, Inc., Palo Alto, CA). Air flow through the Dynacalibrator was maintained using a Tylan mass flow controller (Model FC-260) and a Tylan RO-32 control box, with a total accuracy of 713%. A terpene standard manufactured by Scott-Martin, Inc. (Riverside, CA) was also used with an approximate accuracy of 730%. A Japanese Indoor Air Standards Mix containing 52 compounds was purchased in liquid form from Supelco (Bellefonte, PA). The 52 compounds were dissolved in a solvent of 95 parts methanol, 5 parts

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water mix. A gaseous standard was prepared by adding 10 mL of liquid standard to a 45.5 L glass carboy pressurized with nitrogen gas and humidified with an injection of double deionized water to 30% according to procedures specified by Nelson (1992). Standards were collected on adsorbent cartridges and cold traps to simulate experimental techniques. For all of the quantified emission rates and most of the quantified compounds in Table 4 the adsorbent cartridge technique was used for consistency. Calibration curves were produced for each compound of interest by collecting at least three different volumes of the standard onto a collection device and then analyzing them on the GC–MS. Assumptions were made for some compound quantification using known standards of different molecules. The sample compound 2-methyl-3-pentanone was quantified using the standard 4-methyl2-pentanone since the compounds had the same molecular weight and similar structures. The DMS standard ran out before a calibration curve was made, so a point calibration of DMS was used. A concentration for DMS was also calculated with a DMDS standard curve and found to agree within 27%. Terpenes were also quantified with a onepoint calibration due to the loss of the standard over time. An average value of the remaining terpenes a-pinene, b-pinene and limonene in the standard was used for quantification of all terpenes. 2.5. Emissions from the lactating cow stall area A sulfur hexafluoride (SF6) tracer technique was used to determine emission rates from the northeast lactating cow stall area housing 95 cows. This technique has been successfully employed for measuring emissions from a variety of sources (e.g. Lamb et al., 1995; Kaharabata et al., 2000). The emission of a compound of interest was determined using a simple ratio of the known SF6 emission rate and concentration to the measured concentration of the compound of interest: Qi ¼

QSF6  C i , C SF6

(1)

where Qi and Ci are the emission rate (mg m
2 s) and concentration (mg m
3) of the compound of interest, respectively and QSF6 and C SF6 are the emission rate (mg m
2 s) and concentration (mg m
3) of the SF6 tracer, respectively. To simulate the area source of the stall, 15 SF6 point sources were placed around three feeders in

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J. Filipy et al. / Atmospheric Environment 40 (2006) 1480–1494

the open part of the stall area and inside the covered area of the stall as shown in Fig. 1. SF6 flow through each of the 15 emission points was measured before and after the tracer experiment using a Digital Flow Check, Model No. 4720 (Alltech Associates Inc., Deerfield, IL). All 15 SF6 sources were on and flowing during this tracer experiment. The SF6 concentration in air was measured downwind of the stall by a custom built multiple sampling and analysis system and four syringe samplers. The tracer system pumps air samples from seven polyethylene lines, 9.5 mm outer diameter, 100 m in length, to tedlar bags where the sample is stored briefly before it is sent to a continuous SF6 analyzer equipped with an electron capture detector (ECD) (Benner and Lamb, 1985). A blank followed by a standard were run after every seven samples with data averaged over 5 min. Syringe SF6 samplers collected 5 min average samples and were used to define the edges of the pollution plume. The syringes were analyzed for SF6 using a GCECD, Model 5880A (Hewlett-Packard, Palo Alto, CA). VOC analysis included one cold trap sample and two adsorbent cartridge samples that were collected at the sample line located downwind in the middle of the stall area (see Fig. 1). VOC samples were collected over 15 min periods corresponding with three syringe samples. Due to the elevation difference between the stalls and lagoon 2 (Fig. 1) and the curvature of the hill between the stall and the lagoon, background emissions from the lagoon were considered negligible. Smoke released upwind on the west edge of lagoon 2 showed that a west wind flows around the hill towards lagoons 3 and 4 and does not move towards the stall area. Background emissions from the milking parlor were considered negligible since for sanitation purposes the milking parlor cement floors are washed frequently. 2.6. Emissions from lagoon simulation Measurement of the emissions from lagoon 2 was unsuccessful due to extreme atmospheric dilution of the compounds. Thus, a headspace approach to quantify lagoon emissions similar to studies performed by Aneja et al. (2001) and Hobbs et al. (1999) was performed. The emission rate from a simulated lagoon surface within a glass carboy emission chamber was measured using a mass balance equation (Aneja

et al., 2001):     d½C F ½C 0  JAL LAC ½C F ½C  ¼ þ þ
R,
dt V V V V (2)
3

where C is the concentration (mg m ) of the compound of interest, F is the flow rate (m3 s
1) of the nitrogen carrier gas into the carboy, C0 is the ambient air concentration (mg m
3) of C, V is the headspace volume (m3) within the carboy, J is the emission rate (mg m
2 s
1), AL is the simulated lagoon surface area (m2), AC is the surface area (m2) of the carboy above the liquid lagoon surface, L is the loss term to the carboy wall and is unique for C, and R is the chemical reaction rate inside the chamber. C0 was negligible since 499% pure nitrogen (N2) was used as a carrier gas. Given the small headspace inside the carboy chamber and a 2-day waiting period after filling the carboy before sample collection, wall loss equilibrium was believed to have been reached, and so the loss rate was assumed negligible. Eq. (2) simplifies to   dC JAL F ¼
½C. (3) dt V V Assuming the carboy chamber has reached steady state, the emission rate J can then be determined. The 20.5 L Pyrex glass carboy was filled with 2.0 L of sludge and 10.3 L of liquid slurry from lagoon 2 to simulate a miniature lagoon. The sludge to slurry ratio was determined from Neger (2002) and Rumburg et al. (2004). To mix the lagoon headspace a fan was added to the carboy. The fan displaces approximately 218 L min
1 with a velocity of 1.570.5 m s
1 measured 5 cm from the fan (measured by a mini anemometer, Kurz Instruments Inc., Carmel Valley, CA). Nitrogen gas flowed into the lid of the carboy at approximately 185 sccm. Air temperature was from 17.7 to 25.0 1C when samples were collected and the slurry temperature ranged from 23 to 28.5 1C in the laboratory. Previous measurements of lagoon 2 temperature and dairy air temperature showed a small difference 72 1C during daylight hours. Temperature of the simulated lagoon was somewhat high and demonstrates worst-case conditions of a warm summer day at the site. Samples were collected from the carboy with adsorbent cartridges and cold traps and the analyses were performed using the GC–MS as described earlier. Fig. 2 shows the lagoon emission chamber setup.

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Fig. 2. Lagoon carboy emission sampling setup.

3. Results and discussion

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Odor detection thresholds (ppbv) are from Devos et al. (1990). Of the 113 compounds identified, 94 were collected on adsorbent cartridges and 39 were collected on cold traps. The majority of compounds identified were detected downwind of the stall area (82) and at the lagoon inlet during low wind speeds (73). The lagoon inlet, located at the downwind edge of the lagoon, was the primary location used for sampling although studies have shown that emissions vary over the surface of the lagoon (DeSutter and Ham, 2005). Table 1 concentration results for lagoon samples are most likely a high estimate of the lagoon concentrations since conditions that allowed for collection of numerous VOCs occurred when the temperature was greater than 19 1C and average wind speed was between 0.9 and 6.1 m s
1. Some compounds were always present at background levels independent of weather conditions. In addition, compounds from diesel-fueled vehicles used at the dairy and terpenes from wood chip bedding in the stall areas were detected, but not upwind of the dairy. Fig. 3 shows cold trap versus adsorbent cartridge sample chromatograms from the open stall area. Differences between the two sampling techniques are especially noticeable in the retention time region of 30–42 min where cold trap samples are nearly devoid of peaks. Water condensed inside the glass tube after sample injection, so highly water-soluble compounds may have become trapped within the water droplets. Higher molecular weight compounds such as the ones missing from the cold trap sample chromatograms tend to have low volatilization rates. For these experiments the cold trap was only useful for very volatile compounds.

3.1. Identified compounds 3.2. Emissions from a stall and the lagoon chamber Table 1 lists all of the compounds identified using the GC–MS and the NIST library. NIST match factor values were also given for each compound identified. Concentration ranges in parts per billion by volume in air (ppbv) are listed for those compounds where standards were available. Temperature (1C) and wind speed (m s
1) ranges are observation conditions given for each compound detected, averaged over the sampling period. Sample locations include: background locations upwind of the dairy (B), headspace of lagoon 2 (HS), lagoon 2 (L), and the lactating cow open stall area (S). Sample collection devices include adsorbent cartridges (A) and U-shaped cold traps (C).

VOC emission rates of ethanol and DMS for the northeast lactating cow stall area are shown in Table 2. An average SF6 emission rate of 5.271.5 mg m
2 s
1 was measured. Emission per cow of ethanol and DMS was calculated by multiplying the area of the stall (1904 m2) by the initial emission value for each compound determined using Eq. (1) and then dividing by the number of cows in the stall (95). An additional factor of 5.78 was calculated into the emission value since the entire downwind plume was not measured. This factor was determined from the fraction of the SF6 concentration at position 6, were the VOC

Aromatic Hydrocarbons Benzene, C6H6 Toluene, C6H5CH3 Ethyl benzene, C8H10 m, p-Xylene, C8H10 Benzene, trimethyl, C9H12 Benzene, 1-methyl-3-(1methylethyl), C10H14 Benzene, 1-methyl-4-(1methylethyl), C10H15 Cyclopropane, 1,1-dimethyl-, C5H10

20.2–26.5

977

1.0–26.5 1.0–26.5 3.2–25.0 3.2–25.0 19.1–21.6 3.2–24.0

23.0–28.5 26.5 26.5

21.6–23.3 20.1 20.1–21.6 21.6 20.1–26.5 20.1–26.5 20.1–24.0 20.1–24.0 8.4–24.0 8.4–20.1 20.1–25.0 3.5–20.1

22.5 23.3–26.5 22.5 20.9 19.1–21.6 20.9–24.0

Temperature range (1C)

23.5

17 30 17 23 48

28

0.159

0.213–0.375 0.069–564 0.018–0.047 0.010–0.018 0.041–0.621

18

Error (%)

14.3–58.0

Concentration range (ppbv)

940

938 949 895 939 910 908

976 880 883

859 851 903 929 892 857 855 873 936 932 953 933

Aldehydes 2-Propenal, C3H4O Propanal, 2-methyl, C4H8O Butanal, 2-methyl, C5H10O Butanal, 3-methyl, C5H10O Pentanal, C5H10O Hexanal, C6H12O Heptanal, C7H14O Octanal, C8H16O Nonanal, C9H18O Decanal, C10H20O Benzaldehyde, C7H6O Benzaldehyde, 4-methyl-, C8H8O

Amines Trimethylamine, C3H9N Tributylamine, C12H27N Ethanamine, 2-chloro-N, Ndiethyl, C6H14ClN

943 972 831 821 946 895

Match factora

Alcohols Methanol, CH4O Ethanol, C2H6O Propanol, C3H8O 2-Butanol, C4H10O Butanol, 2-methyl, C5H12O 1-Pentanol, C5H12O

Compound

Table 1 Compound Identifications

2.0

7.6

0.8–6.1 0.8–6.1 0.8–6.1 0.8–6.1 0.8–6.1 0.8–6.1

2.0 2.0

1.4–6.1 0.9 0.9–6.1 6.1 0.9–1.4 0.9–4.5 0.9–4.5 0.9–6.1 4.1–4.5 0.9–4.1 0.9–6.1 0.9–4.8

2.5 1.4–2 2.5 1.3 0.8–6.1 1.3–6.1

Wind speed range (ms
1)

S S S L, S S

S

HS, L

L

B, HS, B, HS, B, HS, B, HS, S HS, L,

HS L L

L, S S S S S S L, L, L, B, L,

S L S S S L, S

S

L, L, L, L,

Sample locationb

S S S S

A, C

A

A, C A, C A A A A

A C C

A A A A A, C A, C A A A A A A

A A, C A C A A, C

Sample collection devicec

3630 1550 2.88 490 154.9

2.40 5.25

2.24 6.03 13.8 4.79 1.35 2.24 0.891 41.7

174 40.7

141,000 28,800 832 490 115 468

Odor detection threshold (ppbv)d

1486 J. Filipy et al. / Atmospheric Environment 40 (2006) 1480–1494

ARTICLE IN PRESS

20.2

921 847

Other hydrocarbons 1-Propene, 2-methyl-, C4H8 Butane, C4H10

0.171–0.256

943

19

3.2–20.2 22.5

1.0–26.5

1.0–25.0 23.3

946

1.63–2.05 0.012

871 820

26.5

25 27 22 21

0.046–0.076 0.076 0.010–0.027 0.406–0.694 34 15

20 26 30 20

0.119–0.204 1.11 0.197–1.98 0.015–1.24

949 941 876 913 959 950 890 893 907 955

1.0–26.5 23.3 3.2–25.0 3.2–26.5 20.1–25.0 21.6–23.3 1.0–23.3 26.5 3.2–26.5 1.0–25.0

1.0–26.5

19.1–26.5 19.1–26.5 26.5 28.5

21.6–26.5 19.1–24.0 20.1 26.5 26.5 21.6–23.3

940

988

Fixed Gases Carbon dioxide, CO2

25 25

Halogenated Hydrocarbons Carbon tetrachloride, CCl4 Chloromethane, CH3Cl Methylene Chloride, CH2Cl2 Chloroform, CHCl3 Iodomethane, CH3I Iodoethane, C2H5I Trichloroethane, C2H3Cl3 Trichloroethylene, C2HCl3 Tetrachloroethylene, C2Cl4 Trichloromonofluoromethane, CCl3F Dichlorodifluoromethane, CCl2F2 Dichlorotetrafluoroethane, C2Cl2F4 Ethane, 1,1,2-trichloro-1,2,2trifluoro-, C2Cl3F3 Butane, 2-chloro-2-methyl-, C5H11Cl Bornyl chloride, C10H17Cl

921 907 971 917

0.102–0.681 0.126–0.468

26.5 8.4–24.0 8.4

873 909 916

984 958 856 969 950 901

26.5 21.6–23.3

921 861

Ethers Furan, 2-methyl-, C5H6O Furan, 2,4-dimethyl-, C6H8O 2, 3-Dihyrofuran, C4H6O Furan, tetrahydro, C4H8O

Esters Acetic Acid, methyl ester, C3H5O Acetic Acid, ethyl ester, C4H8O2 Acetic Acid, propyl ester,C5H10O2 Cyanic Acid, ethyl ester, C3H5NO Nitric Acid, ethyl ester, C2H5NO3 Benzoic Acid, methyl ester, C8H8O2

Cyclohexene, C6H10 Cyclohexene, 3,3,5-trimethyl-, C9H16 2H-Pyran, 3,4-dihydro, C5H8O Naphthalene, C10H8 Naphthalene, 2-mehtyl, C11H10

3.5 2.5

1.4–2.0

0.8–6.1

1.4–4.5 1.4

0.8–6.1 1.4 1.4–6.1 0.8–3.5 0.9–6.1 1.4–6.1 0.8–6.1 2.0 2.0–3.5 0.8–6.1

0.8–6.1

0.8–2.0 0.8–2.0 2.0

1.4–6.1 0.8–6.1 0.9 1.4–2.0 1.4–2.0 1.4–6.1

1.4 0.9–6.1 4.1

2.0 1.4–6.1

HS, L, S S S L, S S S HS, L, S

HS, L, S

HS, L S

HS

L, S

B, HS, L, S

B, L L

B, L L B, L, L, B, L, L, B,

B, HS, L, S

HS, L, S L, S L HS

S S S L, S L, S L, S

S B, L, S L

L, S L, S

A A

A

C

A

A A

A A A A, C A A A A, C A A

A, C

A, C A, C C A

A, C A,C A C C A

C A A

C A

12,300 204,000

1320 22,400 4900 6170 16,200

18,600 10,200 28,800 11,700

6170 2630 575

14.8

21,900

J. Filipy et al. / Atmospheric Environment 40 (2006) 1480–1494

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965 912 978 992 985 970

3.27

823 970 896

Other nitrogen compounds 1H-Pyrrole, 1-methyl, C5H7N 1H-Pyrrole, 1-ethyl, C6H9N 2-Propenenitrile, C3H3N Methyl nitrate, CH3NO3 Nitromethane, CH3NO2 Acetonitrile, dichloro, C2HCl2N

0.114–1.25

785 947 32

32

28 24

22

0.014–2.10

0.132–0.680 1.14–26.2

26

Error (%)

0.105–3.97

Concentration range (ppbv)

976 947 934 927 956 832

868

940 933 923 852 896 896 926 950 920 879 821 904 902 910 943 925

Butane, 2-methyl, C5H12 2-Butene, C4H8 1,3-Butadiene Pentane, C5H12 1-Pentene, C5H10 Pentane, 2-methyl, C6H14 2-Pentene, 4-methyl, C6H12 Hexane, C6H14 Hexane, 3-methyl, C7H16 1-Hexene,C6H12 Heptane, C7H16 1-Heptene, C7H14 Octane,C8H18 1-Octene, C8H16 Nonane, C9H20 Decane, C10H22

Ketones Acetone, C3H6O 2-Butanone, C4H8O 2-Pentanone, C5H10O 3-Pentanone, C5H10O Cyclohexanone, C6H10O Cyclopentanone, 2-methyl-, C6H10O Methyl isobutal ketone, C6H12O 3-Penten-2-one, 4-methyl-, or 3Hexen-2-one, C6H10O 3-Pentanone, 2-methyl-, C6H12O 2-Heptanone, 6-methyl-, C8H16O 5-Hepten-2-one, 6-methyl-, C8H14O 3-Octanone, C8H16O

Match factora

Compound

Table 1 (continued )

20.1–26.5 26.5 26.5 26.5 26.5 26.5

20.2–23.3

28.5 28.5 20.1

20.2–28.5 26.5

19.1–28.5 19.1–28.5 19.1–23.3 28.5 8.4 23.3

22.5 25.0 25.0 19.1–20.2 19.1 19.1–20.1 20.2 3.2–23.3 19.1–21.6 19.1–25.0 3.2–28.5 25.0–26.5 21.6–28.5 20.1–21.6 19.1–23.3 20.1

Temperature range (1C)

0.9–2.0 2.0 2.0 2.0 2.0 2.0

1.4

0.9

4.5 1.4

4.1 1.4

0.8–4.5 0.8–6.1 0.8–1.4

0.8–3.5 0.8–6.1 0.8–3.3 2.0–3.5 2.0–3.3 6.1 0.9–6.1 0.8–1.4 0.9

2.5 4.5 4.5 0.8–0.9 0.8 0.8–0.9

Wind speed range (ms
1)

L, S L, S L L, S L L

HS, L

HS HS S

HS, S S

HS, L, S HS, L, S HS, L, S HS L L

S S S HS, S HS, S HS, S HS HS, L, S HS, S HS, S HS, L L, S HS, S S HS, S, L S

Sample locationb

A, C C C C C C

A

A A A

A, C C

A, C A, C A A A A

A A A A A A A A A A A, C C A A A A

Sample collection devicec

16,600

60

380

537

14,500 7760 1550 316 708

5750 62 1260 741

9770

21,900

31,600

5130

Odor detection threshold (ppbv)d

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955 915 932 942 892 851 943

Terpenes alpha-pinene, C10H16 Camphene, C10H16 beta-pinene, C10H16 3-Carene, C10H16 D-limonene, C10H16 Alpha-phellandrene, C10H16 Tricyclene, C10H16 30 30 30 30 30

24

0.184–2.27

0.665–5.722 0.165–0.255 0.077–1.223 0.426–3.234 0.185–0.189

42

0.064–0.927

3.2–25.0 3.2–28.5 3.2–25 3.2–25.0 3.2–25.0 21.6 19.1–21.6

23.3 3.2–28.5 3.2–25.0 23.3 23.3 19.1 19.1–23.3 20.1–25.0 23.3 26.5

0.8–6.1 0.8–4.5 0.8–3.5 0.8–6.1 0.8–6.1 6.1 0.8–6.1

1.4 0.8–6.1 0.8–3.5 1.4 1.4 0.8 0.8–1.4 0.9–1.4 1.4 2.0

HS, HS, HS, HS, HS, S HS, S

L, L, L, L, L,

L, S HS, L, HS, L, L HS, L HS, S HS, L, HS, L, L L

S S S S S

S S

S S

A A A A A A A

A A, C A, C A A A A A, C A C

437

692

12.3 1.66

2.24 95.5 331

b

Match factor values are for the unknown spectrum and the NIST library: 900 or greater is an excellent match; 800–900 is a good match; 700–800 is a fair match. Sample locations: B ¼ background; HS ¼ lagoon headspace; L ¼ lagoon; S ¼ stall c Sample collection device: A ¼ adsorbent cartridge; C ¼ cold trap d Odor threshold values are from Devos et al. (1990).

a

989 957 986 811 924 890 801 914 718 750

Sulfides Carbonyl sulfide, COS Dimethyl sulfide, C2H6S Carbon disulfide, CS2 Thiophene, C4H4S Thiophene, 3-methyl-, C5H6S Thiophene, 2,3-dimethyl-, C6H8S Thiophene, 3 or 2-ethyl-, C6H8S Dimethyl disulfide, C2H6S2 Dimethyl trisulfide, C2H6S3 Ethylenethiourea, C3H6N2S J. Filipy et al. / Atmospheric Environment 40 (2006) 1480–1494

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Fig. 3. (a) GC–MS analysis of an adsorbent cartridge sample (2984 mL) and (b) cold trap sample (1952 mL) taken downwind of a lactating stall area.

samples were collected, to the total concentration of SF6 measured over the entire plume. This factor is probably underestimated due to the edges of the plume not being measured for SF6 (see Fig. 4) and is included in our error analysis (see Table 5). The SF6 tracer experiment assumes the SF6 plume concentration downwind of the source will be Gaussian in shape (Davidson et al., 1995). Fig. 4 shows the actual SF6 tracer concentration distribution for the sample locations shown in Fig. 1. The non-Gaussian shape is caused by the large hay barn located just upwind of sample positions 3 and 4, and the wind direction not being parallel to the barns and stall areas. The nonparallel wind direction does induce vertical turbulence into the stalls, since the wind must travel over and around the milking parlor to reach the stall area. Wind speed measured from the Gill sonic anemometer, placed at the center

of stall area near sampling position 6, was 2.471.2 m s
1 and the average temperature was 24.670.2 1C. Miller and Varel (2001) found ethanol in fresh (o24 h) and aged cow manure (424 h) to be at least 95% of the total alcohol emissions with initial concentrations for fresh and aged manure of about 1 and 7 mM, respectively in a 20% slurry mixture. Assuming a manure density of 990 kg m
3 and 65 kg manure cow
1 day
1 produced (ASAE, 2003), 752 kg average cow weight at the WSU Knott dairy, calculated emission rates of ethanol for fresh and aged manure for the WSU Knott dairy using the concentrations found by Miller and Varel (2001) are 175 and 1223 mg cow
1 s
1, respectively. Our measured value of 1026 mg cow
1 s
1 fits within the upper end of this range. An additional source of ethanol at the WSU Knott dairy could be the hay

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Table 2 SF6 tracer experiment and lagoon carboy experiment Compound

Stall emissions Ethanol, C2H6O Dimethyl sulfide, C2H6S Lagoon emissions Acetone, C3H6O 2-Butanone, C4H8O Methyl isobutyl ketone, C6H12O 2-Methyl-3-pentanone, C6H12O Dimethyl sulfide, C2H6S Dimethyl disulfide, C2H6S2 a

Odor thresholda (ppbv)

Concentrationb (ppbv)

Concentrationb (mg m
3)

Emission/cowb (mg cow
1 s
1)

Temperatureb (1C)

Wind speedb (m s
1)

28,800 2.24

16.773.3 0.16670.076

31.476.3 0.42170.192

10267513 13.8710.3

24.670.2 24.670.2

2.471.2 2.471.2

14,500 7760 537

0.6870.19 26.276.3 0.4570.14 3.2771.05 0.4670.19 2.2770.54

1.6170.45 77.2718.5 1.8470.59 13.474.3 1.1770.49 8.7372.10

0.00370.001 0.14570.035 0.00370.001 0.02570.008 0.00270.001 0.01670.004

28.570.2 28.570.2 28.570.2 28.570.2 28.570.2 23.070.2

2.24 12.3

Devos et al. (1990). 7Values were calculated using the total error percentage for the given compound and collection technique.

SF6 Concentration (pptv)

b

5000 4500 4000 3500 3000 2500 2000 1500 1000 500 0

3:00-3:15 3:15-3:30 3:30-3:45

0

1

2 3 4 5 6 8 9 10 11 7 Sampler Postion Across Stall Area SW to NE

12

Fig. 4. SF6 concentrations versus tracer sampler position averaged over 15 min intervals during sample collection. VOC samples were collected at position 6. Error: 730%.

silage within the barn adjacent to the open stall area as well as the hay silage within the cow feeders since fermentation of hay silage could produce ethanol as a byproduct. DMS has been identified in dairy cattle waste (Sunesson et al., 2001). Sulfur compounds are apart of the essential amino acids methionine, cysteine, homocysteine, and taurine (NRC, 2001) that come from the proteins that livestock are fed. Sulfur content in livestock feed is directly proportional to the amount of protein in a diet (NRC, 2001). Sulfur content requirement for dairy cattle in the United States is typically 0.20 percent of the dry matter fed to the cattle (NRC, 2001). Reduced sulfur compounds are likely to be a large contributor to odor problems at a dairy due to their low human odor detection thresholds. Additionally, DMS can be oxidized to methanesulphonic acid and eventually sulfuric acid, which can contribute to the formation

of cloud condensation nuclei (CCN) and aerosols when combined with NH3 (Hobbs and Mottram, 2000). In addition to ethanol and DMS from the stall area, Table 2 shows the results of the emission chamber experiment conducted inside the glass carboy filled with lagoon slurry. Eq. (3) gives an emission rate per area of the lagoon; an emission per cow was determined by multiplication of the emission rate by the surface area of lagoon 2 (5881 m2) and division by the 165 lactating cows contributing waste to the lagoon. These numbers are an underestimate of the total dairy emissions since they do not account for lagoons 3 and 4. However, these lagoons should emit less VOCs due to the fact that they do not have daily manure additions but are only pumped to when lagoon 2 is full. The emission values for the compounds coming from the lagoon are low in comparison to ethanol measured at the stall area since the lagoon slurry is diluted waste from the stall area. The combination of DMS and DMDS with other potentially odorous compounds could produce an odor that is greater than any individual odor threshold (Schiffman et al., 2001). The four ketones measured could also be contributing to odor, but to a smaller degree than that of the sulfur containing compounds. The ketones have potential to react with the hydroxyl radical to form aldehydes and peroxyacetyl nitrate (PAN) precursors if sufficient NO2 is present. Acetone can undergo photooxidation to form formaldehyde, carbon dioxide and PAN (Seinfeld and Pandis, 1998). All of the compounds measured

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in this experiment were also measured near the lagoon inlet, but at lower concentrations due to dilution by wind, except for DMS. 3.3. Seasonal trends of DMS and ethanol A plot of seasonal concentrations of DMS and ethanol from the stall area is shown in Fig. 5. Temperature is shown in the size gradation of the sample points. Both ethanol and DMS have the

highest concentrations in the summer months, however ethanol appears to be affected more than DMS by temperature changes and is not detected in the winter months. Ethanol coming from the cattle waste is temperature dependent due to fermentation processes. DMS, however, is known to come from the exhalation of the cows (Hobbs and Mottram, 2000) and not just the cow waste, so it exhibits noticeably less temperature dependence than ethanol.

2.5

31-35 26-30 21-25

Ethanol

16-20

80

11-15 6-10

60

0-5 Temperature (˚C)

1.5

40 1.0

Ethanol Concentration (ppbv)

DMS Concentration (ppbv)

2.0

DMS

20

0.5

0

0.0 0

50

100

150

200

250

300

350

Day of Year Fig. 5. Concentration of DMS and ethanol for a 2-year data set. DMS error 745.5%; ethanol error 713.5%.

Table 3 Quantifiable errors of measurement techniques Quantifiable errors

TO14 standard (%)

Japanese indoor air standard (%)

DMDS (1) & DMS (2) permeation tube standards (%)

Stall emissions for ethanol (1) & DMS (2) (%)

Evacuated canister volume Pressure gauge reading Standard manufacturer spec. Dilution of standard Instrument variation Compound standard deviation Tracer experiment uncertainty Lamb et al. (1995)

72 70.5 710 72 73–36

72 70.5 70.5–3.5 72 72–8.5

72 70.5 73 713 74(1)–27(2)

72 70.5 73(1,2) 72(1)–13(2) 76(1)–27(2)

Total error range

717.5+50.50

730 77–16.50

722.5(1)–45.5(2)

744.5(1)–75.5(2)

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3.4. Additional compounds of interest Although not quantified, some compounds were detected often and are believed to come directly from cattle waste: trimethylamine, C3H9N, methyl acetate, C3H5O2, ethyl acetate, C4H8O2, 2-methyl furan, C5H6O, 2-pentanone, C5H10O, carbon disulfide, CS2, 2-ethyl-thiophene, C6H8S. For most of these compounds no standard was available for quantification of our measurements, except for ethyl acetate, which was not detected at the stalls during the tracer experiment. 3.5. Error analysis Table 3 lists errors in standards as specified by the manufacturer, the equipment used to collect a standard onto an absorbent cartridge or cold trap collection device and the instrument error that is quantified for each compound of interest within a standard mixture. Unquantifiable errors during sample preparation for GC–MS analysis came from incomplete adsorption and desorption on and off the adsorbent cartridge and incomplete transfer of sample from the cold trap due to condensation on the glass tube walls. When the instrument was programmed to scan masses from 30 to 250, CO2 at mass 44 often altered instrument minimum detection limit by raising the background on the chromatogram. 3.6. Limitations of our measurements Sampling results were dependent on the meteorological conditions of wind speed, wind direction and temperature, especially in the stall areas. Due to the layout of buildings at the dairy and the topography of the surrounding area, measurements for the tracer experiment were only attempted when the wind field conditions were ideal with wind speeds of 4.5–9 m s
1 coming from a westerly direction. This produces winds (2.4–5 m s
1) in the stall area sufficient for application of the tracer technique. Additional limitations were that no VFA acids were detected during the course of this project due to the type of columns used in the GC–MS. 4. Conclusions A total of 113 compounds were identified at the dairy. The highest concentrations of volatile organic compounds directly associated with cattle waste

1493

were measured during the summer months. Concentrations were mostly below odor detection thresholds found in the literature. However, the combination of many low concentration odorous compounds within a given air sample could contribute to a detectable odor (Schiffman et al., 2001). Also contributing to the total odor intensities were many compounds that were visible chromatogram peaks, but were not clearly identifiable using the NIST library. Emission rates from the stall tracer experiment and the emission chamber experiment give new estimates for ethanol, DMS, DMDS, acetone, 2-butanone, methyl isobutyl ketone, and 2-methyl3-pentanone production from dairy operations similar to the Knott Dairy. A seasonal plot was produced for DMS and ethanol. More research is needed to further quantify concentrations and emissions of identified compounds due the fact that dairies differ in many respects, such as cow density and number, waste handling practices, feed, housing, and climate. Acknowlegdements Many thanks to David Yonge, Lee Bamsberger, and Gene Allwine for their helpful guidance and technical support. The authors would like to thank John Swain, dairy manager, and everyone at the Knott Dairy Farm for their cooperation throughout the course of this project. We would also like to thank Washington State Department of Ecology their support on this project.

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