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Atmospheric Environment 44 (2010) 5084e5092

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Atmospheric Environment

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Emissions of volatile fatty acids from feed at dairy facilities

Phillip Alanis a, Shawn Ashkan b, Charles Krauter c, Sean Campbell a, Alam S. Hasson a,*

aDepartment of Chemistry, 2555 East San Ramon Avenue M/S SB70, California State University Fresno, Fresno, CA 93740, USAbCenter for Irrigation Technology, 4370 North Chestnut Avenue, California State University Fresno, Fresno, CA 93740, USAcDepartment of Plant Sciences, 2415 East San Ramon Avenue M/S AS72, California State University Fresno, Fresno, CA 93740, USA

a r t i c l e i n f o

Article history:Received 7 June 2010Received in revised form4 September 2010Accepted 7 September 2010

Keywords:CattleFlux measurementsOzone precursorsCaliforniaSilageVOC

* Corresponding author. Tel.: þ1 559 278 2420; faxE-mail address: ahasson@csufresno.edu (A.S. Hass

1352-2310/$ e see front matter � 2010 Elsevier Ltd.doi:10.1016/j.atmosenv.2010.09.017

a b s t r a c t

Recent studies suggest that dairy operations may be a major source of non-methane volatile organiccompounds in dairy-intensive regions such as Central California, with short chain carboxylic acids(volatile fatty acids or VFAs) as the major components. Emissions of four VFAs (acetic acid, propanoicacid, butanoic acid and hexanoic acid) were measured from two feed sources (silage and total mixedrations (TMR)) at six Central California Dairies over a fifteen-month period. Measurements were madeusing a combination of flux chambers, solid phase micro-extraction fibers coupled to gas chromatog-raphy mass spectrometry (SPME/GCeMS) and infra-red photoaccoustic detection (IR-PAD for acetic acidonly). The relationship between acetic acid emissions, source surface temperature and four samplecomposition factors (acetic acid content, ammonia-nitrogen content, water content and pH) was alsoinvestigated. As observed previously, acetic acid dominates the VFA emissions. Fluxes measured by IR-PAD were systematically lower than SPME/GCeMS measurements by a factor of two. High signals in fieldblanks prevented emissions from animal waste sources (flush lane, bedding, open lot) from beingquantified. Acetic acid emissions from feed sources are positively correlated with surface temperatureand acetic acid content. The measurements were used to derive a relationship between surfacetemperature, acetic acid content and the acetic acid flux. The equation derived from SPME/GCeMSmeasurements predicts estimated annual average acetic acid emissions of (0.7þ 1/�0.4) gm�2 h�1 fromsilage and (0.2þ 0.3/�0.1) gm�2 h�1 from TMR using annually averaged acetic acid content andmeteorological data. However, during the summer months, fluxes may be several times higher thanthese values.

� 2010 Elsevier Ltd. All rights reserved.

1. Introduction

Dairies are recognized to be significant sources of volatileorganic compounds (VOCs) in Central California (CARB, 2006). Inthis region, the large number of dairies (NASS, 2002; CDFA, 2006)and the region’s frequent violations of State and Federal ozonestandards (CARB, 2006) have prompted a re-examination of emis-sion fluxes from these facilities (Crow, 2005). However, the numberof dairy emissions studies performed is relatively small and thereare substantial analytical difficulties associated with quantifyingmany of the VOCs emitted. Further, large differences are expectedbetween different types of dairy operations, and emissions esti-mates based on the existing literature have been both difficult andcontroversial.

: þ1 559 278 4402.on).

All rights reserved.

One of the least-well characterized groups of VOCs presentwithin dairy emissions is volatile fatty acids (VFAs) (Martenssonet al., 1999; Sunesson et al., 2001; Rabaud et al., 2003; Hobbset al., 2004; Spinhirne et al., 2004; Shaw et al., 2007; Alanis et al.,2008; Ngwabie et al., 2008; Sun et al., 2008). These compoundsare present in both animal feed and waste sources in significantquantities, but gas-phase measurements are hampered by theiraffinity to adsorb to surfaces. Estimated fluxes of total VFAs varyfrom 0.3 to 11 kg cow�1 yr�1 (Alanis et al., 2008). VFAs are relativelyunreactive in the atmosphere, but if the fluxes of these compoundsare large, they could potentially impact regional ozone levels. VFAsare also constituents of particulate matter, and can affect particleformation, growth and cloud condensation properties (Keene andGalloway, 1986; Zhang et al., 2004). Additionally, thesecompounds contribute to the odor problems of dairy facilities(Rabaud et al., 2003).

Recently, our group reported the development of a techniqueusing a flux chamber and solid phase micro-extraction to measureVFAs (Alanis et al., 2008). The technique was used to measure VFA

P. Alanis et al. / Atmospheric Environment 44 (2010) 5084e5092 5085

fluxes from non-enteric sources at a small dairy located on thecampus of California State University Fresno. Total VFA emissionsfrom the sources tested (silage, total mixed rations, flush lane, openlot and lagoon) were 1.3� 0.3 g cow�1 h�1, with acetic acid as thedominant acid present. A comparison of the fluxes measured fromthe different sources tested suggests that animal feed may domi-nate VOC emissions from dairies in the region, accounting for over60% of the measured VFA emissions. VFA emissions from animalwaste were found to be substantially lower than from the feedsources.

Dairy cows are fed total mixed rations (TMR), which aremixtures containing primarily silage, along with a variety of food-stuffs designed to provide the appropriate nutritional content forthe animals. Silage consists of anaerobically fermented forage suchas corn and alfalfa. During the ensiling process, substantial quan-tities of organic acids are generated, which lowers the pH andprevents the feed from spoiling during storage. Lactic acid is themajor acid present, but the silage also contains substantial amountsof acetic acid and, to a lesser extent, larger VFAs (DOI, 2009). Dairycows consume about 50 kg of TMR each day, about half of which issilage. Since VFAsmay constitute asmuch as 1e2% of the total silagemass (moistureþ dry matter), the evaporation of only a smallfraction of the VFAs present would result in a large flux to theatmosphere. It is therefore not surprising that VFA emissions fromsilage may be substantial. The TMR formulations are proprietary,but Central California dairies tend to use similar mixtures withingredients that may include bakery waste, cottonseed, pulp (beetand orange), molasses, distillers grain and almond hulls. Sincethese feed items tend to have little or no VFA content, emissions ofVFAs are expected to be lower from TMR than from silage.

Bacterial degradation of animal waste can lead to VFA formation,and so emissions frommanure are also expected. The animal wastesources at the dairies vary from dried manure (used for beddingand to cover the open lots) to liquid manure in the lagoon. Diet isalso thought to have a substantial impact on the emissions fromanimal waste. These factors have been suggested to be the origin ofthe dramatically different VFA fluxes measured from animal wastein different studies (Mackie et al., 1998; Miller and Varel, 2001).

In addition to the VFA content itself, other aspects of thecomposition of the feed samples may have important roles indetermining VFA emissions from silage and TMR samples. Moisturecontent and pH may influence the equilibrium vapor pressures ofVFAs above feed samples. Additionally, silage contains a significantquantity of ammonia-nitrogen which may affect VFA levels eithervia its influence on pH or via chemical interactions. Very recently,Montes et al. (2010) investigated ethanol emissions from cornsilage using a wind tunnel system. The authors found that themeasured ethanol flux is strongly correlated with the temperature,wind speed and porosity of the silage sample. While the feedcomposition was analyzed by a commercial laboratory, Montes etal. do not report an analysis of the relationship between the ethanolflux and the silage composition. A number of other studies haveinvestigated the relationship between the air flow rate and VOCemissions from flux chambers and wind tunnels (Bianchi andVarney, 1997; Lee et al., 2004; Parker, 2008; Parker et al., 2009,2010). Fluxes are found to increase as the flow rate of sweep airincreases, and so the relationship between the emissions measuredand the ‘true’ flux depends in part on the relative magnitude of theair flow in the sampling device and the wind speed over thesample.

In recent years, infra-red photo-acoustic detectors (IR-PAD) haveincreased in popularity for the measurement of trace gas emissionsfrom dairies. In this technique, samples are isolated in a cell withinthe instrument. The sample is then exposed to monochromatic IRradiation. Gases within the cell that have non-zero absorption

cross-sections at the chosen wavelength absorb some of the radi-ation, resulting in a pressure pulse that can be detected witha microphone. Commercially available instruments can be config-ured to measure acetic acid. Since a measurement can be made ina few seconds using this technique, IR-PAD offers substantialimprovements in the time resolution of the VFA measurementsover the SPME/GCeMS approach previously used by our group.However, because multiple species may be present in an air samplethat absorb radiation at the probewavelength, there is the potentialfor signal interference from other trace gases present.

In this work, VFA fluxes were measured from feed (silage andTMR) and waste sources at six California dairies using the fluxchamber technique during 2007 and 2008. Fluxes were measuredusing both SPME/GCeMS and IR-PAD methods, allowing an inter-comparison of these techniques to be made. Feed samples from thetest sites were collected and sent for commercial analysis to enablethe composition of the feed to be compared to the emissionsmeasured. Collectively, these measurements provide new insightinto the origins and the relative importance of VFA emissions fromdairy facilities.

2. Materials and methods

2.1. Sampling and analysis

The sampling methods have been described in detail previously(Alanis et al., 2008). Samples were collected from a 60 L emissionisolation flux chamber (Odotech) with a 0.190 m2 footprint using70 mm Carbowax/Divinylbenzene SPME fibers (Supelco). The fluxchamber was placed over the emission source, and dry ultra-highpurity air was flushed into the chamber at a flow rate of 10.0 L/minfor 30 min to allow concentrations to reach steady state.

SPME samples were pumped from the flux chamber at a flowrate of 1.0 Lmin�1 through approximately 1 m of quarter-inchTeflon tubing into a 1 L pyrex sampling chamber fitted witha septum to allow for the introduction of the SPME fiber. Fiberswere exposed to the sample flows for 10 min. The fibers wererefrigerated during transport to the lab at Fresno State, and wereanalyzed on the same day as sample collection.

Identification and quantification of VFA fluxes was performed byGCeMS. Samples were thermally desorbed from the SPME fiberinto the 0.75 mm internal diameter inlet liner of the GC (HP 5890)at 200 �C. To ensure complete desorption of the analytes, the fiberswere left in the GC inlet for the duration of the run. A 30 m Sta-bilwax DA column (Restek) was used to separate the compoundspresent using helium as the carrier gas at a flow rate of 1 mLmin�1.The column was initially held at 50 �C for 4 min, and was thenramped at 12 �Cmin�1 to a final temperature of 200 �C. Thistemperature was held for 3 min resulting in a total run time of19.5 min. The mass spectrometer (HP 5973) was operated in elec-tron impact ionization mode (at 70 eV) and signals were collectedin the selective ion monitoring (SIM) mode usingm/z 59 andm/z 73for all of the acids.

A commercial six-gas IR-PAD instrument (INNOVA Model 1412)was used to measure gas-phase concentrations of both ammoniaand acetic acid. Samples were withdrawn from the chamber intothe analyzer through approximately 1 m of quarter-inch Teflontubing at a flow rate of 0.18 Lmin�1. Within the instrument,samples are isolated in a 3 mL cell, and exposed to filtered IRradiation from a heated nichrome wire source. The instrument isfitted with six filters, enabling the concentrations of six trace gases(acetic acid, ammonia, CO, CO2, N2O and water vapor) to besequentially measured. The instrument internally corrects forsignal interferences from the gases measured. Each set ofmeasurements takes 1 min to collect.

0 20 40 160 1800

2

4

6

8

10

12

14

16

18

20

Mea

sure

d [A

cetic

Aci

d] /

ppm

[Acetic Acid] / ppm

Fig. 1. Comparison of acetic acid fluxes and measured acetic acid fluxes using infra-redphotoaccoustic detection.

P. Alanis et al. / Atmospheric Environment 44 (2010) 5084e50925086

Calibration curves were generated for the acids using the fluxchamber. Pure liquid standards (95% purity or higher) were addedto separate 20 mL vials which were then weighed. The vials wereplaced into an aluminum heating block mounted within the fluxchamber. The chamber was continuously flushed with air at a flowrate of 10 Lmin�1, and samples were periodically collected on SPMEfibers or analyzed by IR-PAD as described above. The flux of eachstandard was determined by re-weighing the vials at time intervalsranging from 1 to 72 h. The flux for the standards was varied byadjusting the temperature of the heating block in the range1e50 �C. Each acid was calibrated individually. Previous work fromthis laboratory has shown that the presence of other VFAs does notaffect the signal response at the concentrations typically found inthese measurements (Alanis et al., 2008).

Feed samples were collected at each dairy at the same time asthe emissions measurements. Samples were sent to a commerciallaboratory for compositional analysis (Dairyland Inc.). Moisture andpH analyses were performed using conventional techniques.Organic acids were quantified by near infra-red (NIR) analysis. Feedsamples were dried and ground before the collection of a reflec-tance NIR spectrum. Spectral features were then fitted to anextensive set of standard spectra of feed samples of knowncomposition to determine the concentrations of VFAs and othercomponents.

2.2. Sampling locations

Samples were collected from six dairies located within the SanJoaquin Valley. The facilities selected represent a range ofgeographical locations, dairy size and operations.

The dairies were tested during 2007 and 2008 and ranged in sizefrom about 300 to almost 4000 cows. At each site, multiple sampleswere collected from two feed sources (silage and TMR) and fromthree waste sources (bedding, flush lane and open lot). Emissionsfrom the lagoons were not routinely monitored, but a number ofsamples were collected and analyzed during the summer collectionperiods. Separate sets of IR-PADmeasurements were collected fromeach site in three different time periods: Winter (FebruaryeApril),Summer (JuneeJuly) and Fall (SeptembereNovember). SPME/GCeMS samples were only collected and analyzed during thesummer. A total of 80 SPME/GCeMS and 350 IR-PADmeasurementswere made during this study.

3. Results

3.1. IR-PAD laboratory measurements of acetic acid

Results from the IR-PAD measurements carried out within thelaboratory are shown in Fig. 1. In the range 5e180 ppm acetic acid,the IR-PAD instrument signal is typically 10e30% of the concen-tration calculated using the measured mass of acetic acid evapo-rated from the vial in a given time interval and the flow rate of theflush gas. The low signal could result fromwall losses of acetic acidduring sampling. However, varying the length of the sampling linedid not systematically affect the measured acid concentration. Themeasurements were carried out shortly following a factory cali-bration, and so signal drift is not responsible for the discrepancybetween the expected and observed measurements.

3.2. Emissions

Average VFA emissions from the feed sources tested are shownin Figs. 2 and 3 and are summarized in Tables 1e3. As observed inour previous study, acetic acid is the dominant VFA present, withtrace emissions of other acids also observed. Emissions from silage

are higher than from TMR. Annual, seasonal and instrumentaldifferences in the measured flux are discussed below. Total VFAemissions from the waste sources tested (flush lanes, bedding andopen lot) are typically below the detection limits of the techniquesused, and are not reported here. However, acetic acid signals in theSPME fiber field blanks were high, resulting in relatively poor limitsof quantitation (0.05 gm�2 h�1). The limits of quantification for theother VFAs investigated by SPME/GCeMS are determined primarilyby the signal response, and are 5�10�3 gm�2 h�1 for propanoicacid, 1�10�3 gm�2 h�1 for butanoic acid, 5�10�4 gm�2 h�1 forpentanoic acid, 1�10�2 gm�2 h�1 for 3-methyl butanoic acid and2�10�4 gm�2 h�1 for hexanoic acid. Concentrations of pentanoicacid and 3-methyl butanoic acid were below the detection limit forall of the sources tested. Because of the large surface area of theopen lot and lagoon sources, a flux below the limit of quantitationcould still result in total VFA emissions that exceed those of the feedsources tested.

Ammonia emissions measured using the INNOVA from TMR andsilage are summarized in Tables 2 and 3. Measured fluxes rangefrom below the limit of detection up to 0.25 gm�2 h�1. The limit ofquantitation for the instrument is 4�10�4 gm�2 h�1. No system-atic differences are observed between the ammonia emissions fromsilage and from TMR, and the ammonia emissions are not corre-lated with any of the compositional factors investigated (aceticacid, ammonia, moisture and pH), or with temperature.

3.3. Effects of feed composition and temperature on VFA emissions

Emissions of VOCs from feed are controlled by the compositionof the source and environmental factors. Gas-phase measurementsof VFA fluxes are challenging, whereas similar measurementswithin feed samples are routinely performed. Thus if it is possibleto establish a relationship between feed composition and VFAemissions, an analysis of the feed sample can be used as a proxy forthe VFA flux measurement.

Results from the commercial analysis of feed samples collectedbetween July 2007 and July 2008 from all six dairies studied areconsidered here. Levels of acetic acid, ammonia-N, moisture/drymatter and pH within silage and TMR samples were evaluated. Infreshly exposed silage samples, levels of acetic acid are typically inthe range of 2.5e3.5% by mass. Silage samples that had been

A B C D E F0

1

2

3Em

issi

ons

/ g.m

-2.h

our-1

Dairy

Acetic Acid Propanoic Acid Butanoic Acid Hexanoic Acid

A B C D E F0

1

2

3

Not

Mea

sure

d

Dairy

Acetic Acid Propanoic Acid Butanoic Acid Hexanoic Acid

Not

Mea

sure

d

A B C D E F0

1

2

3

Emis

sion

s / g

.m-2

.hou

r-1

Dairy

Summer 08 Fall 07 Winter 07/08

SPME/GC-MS Summer 08SPME/GC-MS Summer 07

IR-PAD Acetic Acid

a b

c

Fig. 2. Comparison of VFA fluxes measured from silage at six dairies in Central California.

P. Alanis et al. / Atmospheric Environment 44 (2010) 5084e5092 5087

exposed to the atmosphere for an extended period prior tocollection may have acetic acid levels lower than 1%. Ammoniacontent in the silage samples, reported as a percentage of proteinspresent, is in the range 5e14%. The silage is typically 30e40% drymatter, and 60% water. The pH of the samples is mostly in the range3.8e4.2.

Acetic acid levels in TMR are significantly lower than in silagesamples (0.1e1%). Ammonia concentrations are in the range 2e17%.While this range of ammonia concentrations is similar to those insilage, the average levels in samples from the same dairy are oftensignificantly different from the corresponding average in the silagesamples. Drymatter is 50e60% of the TMR, and pH levels are higherthan in silage (4.6e6.7).

The relationship between acetic acid fluxes and the compositionand surface temperature was examined using both SPME/GCeMSand IR-PAD data. Since the number of IR-PAD measurements ismuch greater than the SPME measurements, initial work focusedon these data. A multivariate analysis was used to assess thepotential relationship between the flux and composition. Varioussubsets of the data were fitted to the multivariate linear regressionequation (E1)

Flux ¼ AþX5

i¼1

Bi$ci (E1)

where Flux (gm�2 h�1) is the acetic acid flux, A (gm�2 h�1) and Biare adjustable parameters, ci is the appropriate variable of interest(c1 is the acetic acid mass fraction of dry matter, c2 is the ammonia

mass fraction of dry matter, c3 is the mass fraction of water presentin the feed sample, c4 is the pH of the sample and c5 is the surfacetemperature of the sample during the flux measurement in K). Theunits of B1, B2, B3 and B4 are gm�2 h�1, and the units of B5 aregm�2 h�1. In each analysis, a least square fit to the data was per-formed by adjusting the Bi coefficients. A t-test is then performed totest the null hypothesis that the value of each of these parameters iszero. The flux is correlated with the compositional factor of interestif there is a >95% probability that the associated adjustableparameter is not zero (i.e., P< 0.05). Because the fractions of otherVFAs in the feed samples are typically below the detection limits,this analysis was not carried out for the other acids investigated inthis work.

An analysis was performed on the entire dataset, which consistsof approximately 160 separate flux measurements. Half of thesesamples were collected from silage and half from TMR samples. Thenumber of samples collected at each dairy is almost the same, as isthe number of samples from each dairy collected during Fall(SeptembereNovember 2007), Winter (FebruaryeApril 2008) andSummer (JuneeJuly 2008). The results of this analysis are shown inTable 4. The acetic acid fluxes are found to be positively correlatedwith both the acetic acid content of the sample and the tempera-ture (P< 1�10�4 for both parameters).

Since the compositional characteristics of silage and TMR aredifferent, data for these sources were also analyzed separately.Silage emissions are positively correlated with acetic acid contentand with temperature (P¼ 0.006 and 0.005, respectively). TMRemissions are positively correlated with acetic acid content

A B C D E F0.0

0.2

0.4

0.6

0.8

1.0

1.2Em

issi

ons

/ g.m

-2.h

our-1

Dairy

Acetic Acid Propanoic Acid Butanoic Acid Hexanoic Acid

B C D E F0.0

0.2

0.4

0.6

0.8

1.0

1.2

IR-PAD Acetic Acid

SPME/GC-MS Summer 08

Dairy

Acetic Acid Propanoic Acid Butanoic Acid Hexanoic Acid

SPME/GC-MS Summer 07

A B C D E F0.0

0.2

0.4

0.6

0.8

1.0

1.2

Not

Mea

sure

d

Not

Mea

sure

d

Not

Mea

sure

d

Emis

sion

s / g

.m-2.h

our-1

Dairy

Summer 08 Fall 07 Winter 07-08

a b

c

Fig. 3. Comparison of VFA fluxes measured from total mixed rations at six dairies in Central California.

P. Alanis et al. / Atmospheric Environment 44 (2010) 5084e50925088

(P¼ 5�10�3) and temperature (P< 1�10�4), and are negativelycorrelated with ammonia content (P¼ 0.01) and water content(P¼ 2�10�3).

To investigate possible differences between dairies, the sameanalysis was carried out on silage and TMR samples collected fromindividual dairies. While some correlations were observed, therelatively small number of datapoints (10e15 for each dairy/source)means that the observed correlation is typically dependent on oneor two individual measurements. For this reason, we do not reportcorrelations for individual dairies in this work.

A similar analysis was performed with the SPME/GCeMS data.Because of the substantially smaller number of measurements, thefitting was carried out with the entire dataset only. As with the IR-PAD data, the acetic acid flux is correlated with both the acetic acidcontent of the feed (P¼ 0.002) and with the temperature (P¼ 0.05).

An equation incorporating the two key parameters for aceticacid flux (acetic acid content and temperature) was optimized toinvestigate the relationship between the acetic acid flux and thesetwo parameters. Since the measurement of acetic acid content andtemperature are both routine, this relationship could potentially beused to predict the acetic acid flux when direct measurement is notpossible. In simple mixtures, the vapor pressure of a component isexpected to be correlated with the mole fraction of that component(Raoult’s law and Henry’s law). While these equations are notexpected to hold for the complex environments of the acetic acidwithin the feed, a linear relationship between the mass fraction ofacetic acid present and the flux of acetic acid seems to be the mostreasonable functional form to use. However, for a pure substance,

the vapor pressure of a gas above a pure liquid varies exponentiallywith temperature, and so a linear relationship between thetemperature and the flux is not expected. Thus equation (E2)

Flux ¼ c1$½Acetic acid�$ec2$T (E2)

was used to model the acetic acid flux, where Flux is the acetic acidflux in gm�2 h�1, c1 and c2 are constants (with units of gm�2 h andK�1, respectively), [Acetic Acid] is the mass fraction of acetic acidpresent in the feed, and T is the temperature (in Kelvin). For eachsample analyzed, the acetic acid flux measured was plotted againstthe acetic acid flux predicted by equation (E2). A linear regressionwas then fitted to these data. Parameter c2 was first adjusted tomaximize r2 for the linear fit to the plot of Flux measured againstFlux predicted. Parameter c1 was then varied until the slope of thisequation was 1. The values of c1 and c2 obtained in this way are(8.4� 24)� 10�10 gm�min�1 and (0.08� 0.01) K�1, respectivelyfor the IR-PAD data and (1�0.15)� 10�4 m�2 �1 and (0.044�0.004) K�1, respectively for the SPME/GCeMS data. Comparisons ofthese fits to the measured fluxes are shown in Fig. 4. In each case,the parameters derived from the fit to the SPME data predictapproximately double the emissions of the IR-PAD-derived fit. Asystematic difference between the SPME/GCeMS and the IR-PADdata is that the former were only collected during Summer 2007and Summer 2008, whereas IR-PADmeasurements were also madeat other times of the year. Thus the differences in the emissionspredicted by equation (E2) using SPME/GCeMS and IR-PAD datamay reflect other factors that are correlated with acetic acidemissions, and which are not controlled for in this analysis. To

Table 1VFA Emissions measured from feed sources using SPME/GCeMS.

Source Period Dairy Emissionsa/g h�1m�2

Acetic acid Propanoic acid Butanoic acid Hexanoic acid

Total Mixed Rations Summer 2007 A 0.54� 0.06 (0.37e0.71) (2.8� 0.2)� 10�2

(2.1� 10�2e3.2� 10�2)(1.9� 0.2)� 10�3

(1.4� 10�3e2.5� 10�3)(1.2� 0.1)� 10�3

(1.1� 10�3e1.4� 10�3)B 0.63 2� 10�2 2� 10�2 5� 10�3

C n.m. n.m. n.m. n.m.D 0.30� 0.08 (0.22e0.37) (7.8� 0.9)� 10�3

(6.4� 10�3e8.2� 10�3)(4.7� 0.8)� 10�3

(4.0� 10�3e5.5� 10�3)(2.7� 0.5)� 10�3

(2.2� 10�3e3.2� 10�3)E 1.22� 0.06 (1.06e1.18) (1.1� 0.3)� 10�2

(0.8� 10�2e1.4� 10�2)(3� 2)� 10�3

(1� 10�3e5� 10�3)(2.4� 0.1)� 10�3

(2.4� 10�3e2.5� 10�3)F 0.54� 0.10 (0.31e0.85) (1.8� 0.3)� 10�2

(1.2� 10�2e2.6� 10�2)(9� 5)� 10�2

(1.4� 10�2e0.28)(1.5� 0.6)� 10�2

(5� 10�3e3� 10�2)

Summer 2008 A n.m. n.m. n.m. n.m.B 0.11 2� 10�3 1� 10�3 n.d.C n.m. n.m. n.m. n.m.D n.m. n.m. n.m. n.m.E 0.07 1.5� 10�2 6� 10�4 n.d.F 0.29 4� 10�3 n.d. n.d.

Silage Summer 2007 A 0.76� 0.04 (0.69e0.81) (5.1� 0.8)� 10�2

(3.5� 10�2e6.2� 10�2)(3� 1)� 10�3

(2� 10�3e5� 10�3)(4.8� 0.7)� 10�3

(3.9� 10�3e6.3� 10�3)B 2.2 0.12 1� 10�3 6� 10�3

C n.m. n.m. n.m. n.m.D 1.6 7� 10�2 5� 10�3 1.5� 10�2

E 3.1 8� 10�2 9� 10�3 1.6� 10�2

F 1.1� 0.3 (0.5e1.5) (7� 3)� 10�2

(3� 10�3e0.10)(1.9� 0.4)� 10�3

(1.0� 10�3e2.6� 10�3)(3.8� 0.9)� 10�3

(2.0� 10�3e4.5� 10�3)

Summer 2008 A 0.55� 0.01 (0.54e0.56) 0.12� 0.04(9� 10�2e0.14)

n.d. n.d.

B 1.1� 0.2 (0.9e1.2) (6� 4)� 10�2

(3� 10�2e9� 10�2)n.d. n.d.

C 1.5� 0.2 (1.3e1.6) (6� 1)� 10�2

(5� 10�2e7� 10�2)(1.7� 0.2)� 10�2

(1.5� 10�2e1.8� 10�2)n.d.

D n.m. n.m. n.m. n.m.E 0.81� 0.01 (0.81e0.82) 0.16� 0.04 (0.13e0.18) n.d. n.d.F 0.25� 0.15 (0.14e0.35) (5� 4)� 10�3

(n.d.e7� 10�3)(6.5� 0.7)� 10�3

(6� 10�3e7� 10�3)n.d.

a Uncertainties are one standard deviation. Numbers in parentheses are the lowest and highest values measured from each source. n.m.¼ not measured; n.d.¼ not detected.

P. Alanis et al. / Atmospheric Environment 44 (2010) 5084e5092 5089

determine if differences in the datasets for the SPME/GCeMS andIR-PAD measurements are responsible for the differences in thevalues obtained for parameters c1 and c2, the IR-PAD data fromsummermeasurements were analyzed separately. The resultant fits

Table 2Acetic acid and ammonia emissions measured from TMR using IR-PAD.

Period Dairy Emissionsa/g h�1m�2

Acetic acid Ammonia

Fall A 0.18� 0.02 (0.10e0.23) 0.04� 0.01 (0.01e0.06)B 0.07� 0.02 (0.01e0.08) 0.06� 0.02 (0.02e0.09)C 0.09� 0.02 (0.04e0.17) 0.03� 0.01 (0.01e0.06)D 0.07� 0.02 (0.02e0.12) 0.03� 0.01 (0.01e0.06)E 0.07� 0.03 (0.02e0.15) 0.02� 0.01 (2� 10�3e0.07)F 0.05� 0.01 (0.01e0.08) 0.07� 0.02 (n.d.e0.07)

Winter A 0.07� 0.02 (0.02e0.13) 0.02� 0.01 (4� 10�3e0.04)B 0.06� 0.02 (0.02e0.13) 0.016� 0.007 (n.d.e0.04)C 0.08� 0.03 (0.02e0.15) 0.02� 0.01 (2� 10�3e0.06)D 0.07� 0.02 (0.02e0.12) 0.04� 0.01 (4� 10�3e0.08)E 0.08� 0.02 (0.03e0.16) 0.02� 0.01 (2� 10�3e0.05)F 0.09� 0.03 (0.02e0.16) 0.06� 0.03 (n.d.e0.16)

Summer A 0.14� 0.04 (0.04e0.39) 0.05�0.02 (0.01e0.11)B 0.12� 0.04 (0.02e0.25) 0.03� 0.01 (2� 10�3e0.07)C 0.14� 0.04 (0.04e0.22) 0.04� 0.01 (8� 10�3e0.08)D 0.37� 0.06 (0.24e0.46) 0.07� 0.01 (4� 10�3e0.1)E 0.18� 0.03 (0.06e0.25) 0.05� 0.02 (2� 10�3e0.1)F 0.15� 0.04 (0.02e0.23) 0.05� 0.02 (8� 10�3e0.1)

a Uncertainties are one standard deviation. Numbers in parentheses are thelowest and highest values measured from each source. n.d.¼ not detected.

are statistically indistinguishable from the fits to the entire dataset,demonstrating that systematic differences between the measure-ments obtained by SPME/GCeMS and the IR-PADmethods are mostlikely responsible for the observed disagreement.

Table 3Acetic acid and ammonia emissions measured from silage using IR-PAD.

Period Dairy Emissionsa/g h�1m�2

Acetic acid Ammonia

Fall A 0.42� 0.05 (0.29e0.51) 0.06� 0.02 (0.02e0.09)B 0.07� 0.05 (n.d.e0.16) 0.03� 0.02 (n.d.e0.09)C 0.13� 0.02 (0.10e0.18) 0.03� 0.01 (7� 10�3e0.06)D 0.30� 0.12 (n.d.e0.46) 0.14� 0.06 (n.d.e0.25)E 0.08� 0.01 (0.06e0.09) (4� 1)� 10�3 (2� 10�3-7� 10�3)F 0.12� 0.04 (0.03e0.23) 0.011� 0.004 (4� 10�3e0.02)

Winter A 0.19� 0.03 (0.13e0.24) 0.07� 0.01 (0.04e0.09)B 0.097� 0.008 (0.08e0.11) 0.012� 0.003 (7� 10�3e0.02)C 0.10� 0.01 (0.08e0.13) 0.03� 0.01 (0.01e0.05)D 0.14� 0.01 (0.13e0.15) 0.03� 0.01 (0.02e0.05)E 0.16� 0.04 (0.08e0.24) 0.07� 0.02 (0.02e0.11)F 0.21� 0.09 (0.08e0.20) 0.05� 0.04 (2� 10�3e0.14)

Summer A 0.38� 0.04 (0.29e0.41) 0.04� 0.01 (0.01e0.06)B 0.21� 0.11 (0.07e0.49) 0.010� 0.004 (2� 10�3e0.016)C 0.21� 0.09 (0.09e0.43) 0.05� 0.03 (2� 10�3e0.13)D 0.54� 0.02 (0.52e0.56) 0.12� 0.01 (0.12e0.13)E 0.96� 0.14 (0.62e1.2) 0.10� 0.02 (0.07e0.17)F 0.49� 0.14 (0.28e0.75) 0.04� 0.02 (4� 10�3e0.08)

a Uncertainties are one standard deviation. Numbers in parentheses are thelowest and highest values measured from each source. n.d.¼ not detected.

Table 4Correlation of feed source characteristics and sample temperature with acetic acidemissions measured using IR-PAD.

Emissions source Factor r-Value

Silage Acetic acid content 0.49a

Ammonia-N content 0.29Moisture 0.09pH 0.61Sample temperature 0.44a

TMR Acetic acid content 0.33a

Ammonia-N content �0.58a

Moisture �0.20a

pH �0.23b

Sample temperature 0.46

All feed sources(silage and TMR)

Acetic acid content 0.56b

Ammonia-N content 0.04Moisture 0.68pH �0.35Sample temperature 0.46b

a P< 0.01.b P< 0.001.

P. Alanis et al. / Atmospheric Environment 44 (2010) 5084e50925090

4. Discussion

The correlations between acetic acid emissions from the feedand the parameters investigated are shown in Table 4. The datacollectively show that acetic acid emissions from animal feed arecorrelated with two of the five factors investigated: acetic acid

0.0 0.2 0.4 0.6 0.8 1.0 1.20.0

0.5

1.0

1.5

Slope = 2.4r = 0.64

Flux

Mea

sure

d (IR

-PAD

) / g

.m-2.h

r-1

Flux Predicted (IR-PAD) / g.m-2.hr-1

Slope = 1r = 0.64

0.0 0.2 0.4 0.6 0.8 1.0 1.20

1

2

3

Flux Predicted (SPME) / g.m-2.hr-1

0 1 2 30

1

2

3

Slope = 1r = 0.78

Flux

Mea

sure

d (S

PME)

/ g.

m-2

.hr-1

Flux Predicted (IR-PAD) / g.m-2.hr-1

Slope = 0.59r = 0.69

0 1 2 3 40

1

2

3

4

Flux Predicted (SPME) / g.m -2.hr-1

Fig. 4. Comparison of acetic acid fluxes predicted using equation (E2) and measuredacetic acid fluxes from feed sources using IR-PAD and SPME/GCeMS data.

content and temperature. Clearly, as the content of a componentwithin the sample increases, the partial vapor pressure of thatcomponent is expected to increase as well. Likewise, as thetemperature increases, the vapor pressure also increases, leading toa higher flux.

TMR emissions are also negatively correlated with watercontent and ammonia content. Since acetic acid is highly soluble inwater, a reduction in moisture level is expected to increase thepartial vapor pressure and thus the flux of acetic acid. The origin ofthe relationship between acetic acid flux and ammonia content isless clear. Ammonia is a product of the degradation of proteinsduring ensiling, but it is sometimes added to the forage at thebeginning of the ensiling process. In general, ammonia content insilage is expected to be positively correlated with acetic acidcontent, water content and pH. In the silage samples studied here,ammonia is correlated with acetic acid content and pH, but notwater content, whereas the TMR samples are positively correlatedwith pH only.

The most obvious way that the presence of ammonia may alterthe vapor pressure of acetic acid is by increasing the pH of thesamples. Since ammonia is a strong base, its presence is expected tohelp to regulate the acidity of the feed. Acetic acid is in equilibriumwith acetate anions:

CH3CO2H¼ CH3CO2�þHþ

Thus as the pH increases and the concentration of Hþ falls, theequilibrium moves to the right, reducing the levels of acetic acidand thus its vapor pressure. The pKa for acetic acid is 4.75. In silage,where the pH is typically below 4, acetic acid is mostly present asthe conjugate acid. However, in TMR where the pH is in the range4.6e6.7, the fraction of the conjugate acid is expected to be 0.68 atthe lowest pH observed and 0.01 at the highest pH observed. Thiswill have a corresponding impact on the flux of the acid. Howeverthe acetic acid flux is not correlated with pH (P¼ 0.1), suggestingthat this is not the controlling factor. Alternatively, the presence ofions in an aqueous solution typically reduces the solubility of gasesthrough a salting-out effect. Since the pKa of ammonium ions is9.24, almost all of the ammonia in the TMR samples will be presentas NH4

þ. Thus as the concentration of ammonia-N increases, theionic strength of the sample will increase, and an associatedincrease in the vapor pressure of acetic acid is expected.

The comparison between predicted and measured acetic acidfluxes using both IR-PAD and SPME/GCeMS is shown in Fig. 4. The r2

values for the best fit lines are significantly lower than 1, and so themodel clearly does not capture all of the observed variation in themeasured emissions. The calibration data indicate that whencombined with the flux chamber, the IR-PAD instrument measuresfluxes of acetic acid that are systematically lower than the true flux.Consistent with this observation, the predicted acetic acid flux fromthefit to the IR-PADmeasurements is about a factorof two lower thanthepredictedacetic acidfluxusing thefit to theSPME/GCeMSdata. Ingeneral, gas-phase acetic acid concentrations are difficult tomeasurebecause the acid readily adsorbs to surfaces leading to systematicallylow measured concentrations. Since this tends to bias the measure-ments low, in general it is expected that the higher of the measuredconcentrations will be closer to the true value. Our measurementstherefore suggest that the SPME/GCeMS measurements and modelfits are more reliable than those made using IR-PAD.

4.1. Emissions estimates

Equation (E2) was used to estimate annual acetic acid emissionsfrom silage and TMR, using annually averaged values for acetic acid

P. Alanis et al. / Atmospheric Environment 44 (2010) 5084e5092 5091

content and temperature. In the feed samples tested, the averageacetic acid content was 1.9% of dry mass for silage and 0.55% of drymass for TMR. The acetic acid content is substantially lower thanthe average content for corn and alfalfa silage reported nationwide(2.3% (DOI, 2009)). This is because many of the samples tested hadbeen exposed to the atmosphere for a considerable amount of time,and so evaporative loss reduces the VFA content of these samples.Since the exposed face of the silage pile at a dairy is a mixture offreshly exposed and aged material, the measured average aceticacid level is used here rather than the average value in fresh silage.The average annual temperature for 2008 in Fresno was 18 �C.Substituting these values for temperature and acetic acid contentalong with the SPME/GCeMS model fits reported here into equa-tion (E2) gives average emissions of (0.7þ1/�0.4) gm�2 h�1 and(0.2þ 0.3/�0.1) gm�2 h�1 for silage and TMR, respectively. Thesenumbers are considerably lower than the 1.8 gm�2 h�1 and1.0 gm�2 h�1 for silage and TMR, respectively, reported in ourprevious work (Alanis et al., 2008). In that study, samples werecollected from Dairy C during Spring only. An examination of thedata indicates that the SMPE/GCeMSmeasured emissions from thisfacility are high compared to the other dairies sampled. The averagetemperature during the Spring 2007 measurements was alsoslightly higher (20 �C) than the value used in the estimates here.The large uncertainties primarily result from the propagation of theuncertainty in c2. In these experiments, the source was exposed toa flow of sweep air within the flux chamber. Previous studiesdemonstrate that the flux measured using chambers and windtunnels increases with air flow (Bianchi and Varney,1997; Lee et al.,2004; Parker, 2008; Parker et al., 2010). The relationship betweenthe emissions measured and the actual emissions therefore dependon the relative airspeed within the chamber and the wind speed atthe dairy facility. The air flow used in this work results in a turnoverof 0.17 flush volumes per minute. Wind speed was not systemati-cally monitored during these measurements, but wind speedsmeasured previously at these facilities are typically low, and areoften below 1.5 m s�1 (Krauter et al., 2005). The averagewind speedmeasured in Fresno during 2008 is consistent with these observa-tions. The annual average was 2.4 m/s, with monthly averages inthe range 1.3e3.4 m/s. Higher wind speeds were observed duringthe summer months. The wind speed over silage and TMR sourcesis complicated by the topography of the silage pile and the freestallstructure, respectively. As a result of these complications and sincethe wind speed within the chamber was not directly measured, nocorrections were made for air flow. Because of the relationshipbetween flux and air flow, and the relatively low flow of sweep airused compared to wind speeds in Central California, the reportedemissions should be treated as a lower limit.

The emissions reported above are annual averages. Since ozoneis primarily a problem in Central California during the summer andduring the day, when temperatures are much higher than 18 �C,much larger emissions are expected during this period. Forexample, during July 2008, the average daytime maximumtemperature in Fresno was 38 �C. Under these conditions, thepredicted fluxes increase to (1.7þ 3/�1) gm�2 h�1 and (0.5þ1/�0.3) gm�2 h�1 for silage and TMR, respectively. Since the silagepile face may be exposed to direct sunlight, surface temperatures ashigh as 48 �C were observed, and therefore even higher acetic acidfluxes may be expected. Solar radiation is therefore likely toinfluence emissions, and is a parameter that should be monitoredin future work.

5. Conclusions

The measurements reported here confirm that dairy feed isa significant emissions source of VFAs. Temperature and acetic acid

content are the two major factors (of the five investigated) influ-encing emissions of this VFA from TMR and silage. A comparison ofIR-PAD and SPME/GCeMSmeasurements indicates that the IR-PADapproach may underestimate the acetic acid flux by about a factorof two. Taking the estimated average source areas of emissions/cowused by Alanis et al. (2008) of 0.17 m2 cow�1 and 0.45 m2 cow�1 forsilage and TMR, respectively, and assuming that the average fluxto be 0.7 gm�2 h�1 and 0.2 gm�2 h�1 (as described above) givesa total source strength of acetic acid from feed sources of1.7 kg cow�1 yr�1, significantly lower than the estimate from ourprevious work (Alanis et al., 2008) (6.4 kg cow�1 yr�1).

While the results reported here are more comprehensive thanour original estimates, some uncertainties remain. The equationused to predict the acetic acid flux does not capture all of thevariation in the measured emissions, such as variation due to solarradiation and wind speed. Emissions from waste sources werebelow the detection limits of the methods used, but may still besignificant. Additional work is therefore still needed to accuratelyquantify VFA fluxes from dairy facilities.

Acknowledgements

This work was supported by the Agricultural Research Initiative(Project Number 06-2-010) and by a National Oceanic and Atmo-spheric Administration award under cooperative agreement #NA06OAR4810187.

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