Estimation of Ammonia Emissions from Estimation of Ammonia Emissions from Beef Cattle Feedyards Beef Cattle Feedyards

with Process-Based Models with Process-Based Models

Heidi Waldrip, Richard Todd, Andy Cole (USDA-ARS, Bushland, Texas)

C. Alan Rotz (USDA-ARS, University Park, PA)Changsheng Li (University of New Hampshire, Durham, NH)

William Salas (Applied GeoSolutions, LLC, Durham, NH)

Why do we need to estimate ammonia (NHWhy do we need to estimate ammonia (NH33))

emissions from feedyards?emissions from feedyards?

Beef cattle are responsible for ~15% of anthropogenic NH3

Emitted NH3 could impair air, soil, and water quality

Direct measurement on every feedyard is impractical and expensive

Inventory, assess impact, emissions reporting, develop reasonable regulatory policies, evaluate effects of changing managementpractices or climate

What are process-based models?What are process-based models?

Mechanistic models based on what we know about a system and how components interact •Track components of interest (nitrogen, carbon) through biogeochemical processes (e.g. hydrolysis, decomposition, mass transfer, nitrification, fermentation, etc.) based on classical principles of thermodynamics and reaction kinetics (may also contain some empirical elements)

•Rely on good input data to simulate processes under varying environmental and management conditions

•Can be expanded as knowledge base grows

Process-based models for Process-based models for livestock production systemslivestock production systems

Manure-DNDCManure-DNDCLi et al. 2012. Manure-DNDC: a biogeochemical process model for Li et al. 2012. Manure-DNDC: a biogeochemical process model for quantifying greenhouse gas and ammonia emissions from livestock manure quantifying greenhouse gas and ammonia emissions from livestock manure systems. systems. Nutr. Cycl. Agroecos. Nutr. Cycl. Agroecos. 93:163-200.93:163-200.

Integrated Farm Systems Model (IFSM)Integrated Farm Systems Model (IFSM)Rotz et al. 2012. Integrated Farms Systems Model: Reference Manual. Rotz et al. 2012. Integrated Farms Systems Model: Reference Manual. USDA Agricultural Research, University Park, PA Service.USDA Agricultural Research, University Park, PA Service.

Both models evaluated for dairy and swine, but not for large, Both models evaluated for dairy and swine, but not for large, open-lot beef feedyards.open-lot beef feedyards.

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ObjectivesObjectives

Evaluate IFSM and Manure-DNDC for predicting NH3 emissions from open-lot feedyards.

Model simulated emissions compared to two years of measurements taken at commercial feedyards in Deaf Smith County, Texas (Todd et al., 2011).

TX

OK

KSCO

NMThe Texas Panhandle is the #1 beef The Texas Panhandle is the #1 beef producing region in the U.S.producing region in the U.S.In 2007 there were 560,043 cattle on In 2007 there were 560,043 cattle on feed at any one time in Deaf Smith feed at any one time in Deaf Smith County.County.

1 dot = 10,000 cattle. 1 dot = 10,000 cattle. 2007 Census of Agriculture, USDA-NASS2007 Census of Agriculture, USDA-NASS

General Model InputGeneral Model Input1)Daily climate data: temperature, precipitation, wind speed, solar radiation, relative humidity

2) Animal characteristics 3) Average animal population: Feedyard A, 12,684 head Feedyard E, 19,620 head

4) Feed rate: 10.5 kg DM head-1 d-1 (Manure-DNDC)

5) Dietary crude protein (CP):varied monthly,determined by analyzing feedbunk samples.

6) Diet composition (IFSM)

Feedyard A began feeding distillers grains

IFSM EvaluationIFSM Evaluation

Summer:Modeled: 214 + 43 g hd-1

Observed: 194 + 54 g hd-1

Winter:Modeled: 78 + 44 g hd-1

Observed: 78 + 43 g hd-1

Summer, 2008:Modeled: 88 + 21 g hd-1

Observed: 105 + 23 g hd-1

Winter, 2008:Modeled: 40 + 22 g hd-1

Observed: 60 + 23 g hd-1

Manure-DNDC EvaluationManure-DNDC Evaluation

Winter:Modeled: 42 + 20 kg ha-1

Observed: 29 + 16 kg ha-1

Summer:Modeled: 88 + 11 kg ha-1

Observed: 62 + 19 kg ha-1

Summer, 2008:Modeled: 64 + 8 kg ha-1

Observed: 54 + 12 kg ha-1

Winter, 2008:Modeled: 32 + 15 kg ha-1

Observed: 36 + 14 kg ha-1

Regression and measures of difference Regression and measures of difference between observed NHbetween observed NH33 flux and model flux and model

predictionspredictionsModel and feedyardModel and feedyard MAEMAE[a][a] MBEMBE IAIA RR22

IFSMIFSM ----g NH3 head-1 d-1-----

Feedyard A 45.8 5.99 0.810.81 0.455***0.455***

Feedyard E 25.3 -2.24 0.730.73 0.279***0.279***

Manure-DNDCManure-DNDC --kg NH3 hectare-1 d-1--

Feedyard A 16.7 7.43 0.780.78 0.426***0.426***

Feedyard E 12.9 0.47 0.710.71 0.242***0.242***

[a]MAE, mean absolute error; MBE, mean bias error; IA, index of agreement; R2, regression coefficient.Asterisks indicate significance at p < 0.05 (*), p < 0.01 (**), and p < 0.001 (***).

Comparison of Per Capita Emission RatesComparison of Per Capita Emission Rates

Annual Feedyard NHAnnual Feedyard NH33 Emissions Emissions

Per capita emissions rate (kg head-1 y-1)

Total feedyard emissions

(Mg feedyard-1 y-1) [1]

Difference (Mg y-1)

Feedyard AFeedyard A 61 774 ----

IFSM 55 698 -76 (10%)

Manure-DNDC 63 799 +25 (3%)

USEPA EF[2] 13 165 -609 (79%)

Feedyard EFeedyard E 33 639 ----

IFSM 25 484 -155 (24%)

Manure-DNDC 28 542 -97 (15%)

USEPA EF 13 252 -387 (61%)[1]Assumes one-time capacities of 12,684 and19,370 cattle for Feedyards A and E, respectively.[2]USEPA, 2005. National emission inventory – Ammonia emissions from animal agricultural operations: Revised draft report. 2005 Apr. 22.

Both IFSM and Manure-DNDC are better predictors of Both IFSM and Manure-DNDC are better predictors of annual feedyard NHannual feedyard NH33 emissions than emission factors. emissions than emission factors.

ConclusionsConclusions

Manure-DNDC and IFSM predictions were in 71% to 81% agreement with measured observations.

Both models were sensitive to changes in temperature and dietary CP concentration.

•Both models can be used to quantify average per capita NH3 emissions from feedyards and are more accurate than constant emission factors.

Potential room for improvement? Prediction of urine N excretion (Manure-DNDC); effects of precipitation, wind speed, and surface heating effects.

Questions?Questions?

This project was partially supported by USDA-NIFA funding to Texas A&M AgriLife Research for the federal special grant project TS2006-06009, "Air Quality: Reducing Emissions from Cattle Feedlots and Dairies (TX & KS)".

Feedyard A

Met tower

Laser path

Todd et al., 2011. J. Environ. Qual. 40:1090-1095

Ammonia Measurements

335-350 m

Model Input ContModel Input Cont..

7) No bedding7) No bedding

8) No housing8) No housing

9) Manure removal frequency: 365 days9) Manure removal frequency: 365 days

Our Assumptions: Our Assumptions:

No N losses due to leaching or runoffNo N losses due to leaching or runoff

Very little (if any) diffusion of NHVery little (if any) diffusion of NH33 through manure pack. through manure pack.

Urea hydrolysis: f (T, [urea]), (Muck, 1982):                 RUC, kg/m3 h-1 = Vmax CU / (Kmc + CU)         

CU = urea concentration, kg/m3

Vmax= maximum rate of urea conversion, kg N/m3,= 3.915 × 109 e6463/T      Kmc= Michaelis-Menten coefficient, kg N/m3 = 3.371 × 108 e(-5914/T)                     T = temperature, K

Ammonium dissociation: f (pH,Ka,T), (Stumm and Morgan, 1996; Montes et al., 2009):   

F = 1 / (1 + 10-pH /Ka ) Ka = 10(0.05 - 2788/T)          pH = surface pH of manure or urineKa is multiplied by 0.74 to account for ionic strength and sorption by OM.

Ammonia gas-liquid equilibrium: f (T), (Montes et al., 2009) H = (T/0.2138) × 10(1825/T -6.123)                                        

H = Henry’s Law constant for ammonia, dimensionless

                         Overall mass transfer coefficient: f(wind, T, resistance), (Montes et al., 2009),

K = 1 / ( H / Kg + 1/Kl + Rm)        Kg = mass transfer coefficient through gaseous layer, m/s

Kg = 0.001 + 0.0462 U ( SC-0.67)       U = air friction velocity near surface, m/s= 0.02Va

1.5                                                 Va= air velocity SC= Schmidt number (Perry et al., 1997), dimensionlessKl= 1.417 × 10-12T4   Rm = resistance to mass transfer, s/m, Rm = Rs + Rc Rs = resistance to mass transfer through the manure, s/mRc = resistance to mass transfer through a storage cover, s/m             Emission rate: f(overall mass transfer rate, and the difference in ammonia concentration between the manure and surrounding atmosphere (Datta, 2002):

J = 3600 K ( Cm – H ( Ca) )J = ammonia flux, kg/m2-sCm = concentration of ammonia in manure, kg/m3

Ca = concentration of ammonia in ambient air, kg/m3

The ammonia concentration in the manure is calculated from the bulk TAN concentration and F from Eq. 11.6.Cm  = F × CTAN                             CTAN = concentration of TAN in the manure solution, kg/m3                                           

UREASE (% of urea hydrolyzed per day) is a linear function of dissolved organic carbon content (DOC, kg C ha-1), water filled pore space (WFPS), environmental temperature (T, oC) and a rate coefficient (k1, 0.9 ha kg-1 oC-1) according to: UREASE = k1 x DOC x WFPS x T

 The specific rate of urea hydrolysis (dUrea, daily hydrolyzed urea) is a function of urea concentration ([Urea], kg N ha-1) and urease activity (UREASE) according to: dUrea = [Urea] x UREASE

Dissociation constants (Glasstone, 1946; Sutton, 1990; Sutton et al., 1993)

Ka = (1.416 + 0.01357 x T) x 10-5

 

Kw = 10(0.08946 + 0.03605 * T) x 10-15

A two-film model with Henry’s law and mass transfer coefficients predicts NH3 emission from the manure liquid surface into the air (De Visscher et al., 2002).

F1 = K1 x ([NH3]bl –[NH3]il) 

where F1 is the diffusion rate in the liquid phase (kg N m-2 h-1), K1 is the NH3 mass transfer coefficient in the liquid boundary layer (dimensionless), [NH3]bl is the NH3 concentration in the bulk liquid phase (kg N m-3), and [NH3]il is the NH3 concentration in the interface liquid phase (kg N m-3).

Subsequently, the transfer of NH3 from the interface liquid phase to the bulk air is calculated by: 

Fg = Kg x ([NH3]ig – [NH3]ag) 

where Fg is the NH3 transfer rate from the interface liquid to the bulk air (kg N m-2 h-1), Kg is the NH3 mass transfer coefficient in the air boundary layer (L/T), [NH]ig is the NH3 concentration in the interface gas phase (kg N m-3), and [NH3]ag is the NH3 concentration in the air (kg N m-3).

The equilibrium between NH3 in the interface liquid and NH3 in the interface gas phase is calculated as: 

[NH3]ig = Kh x [NH3]il

 where [NH3]ig is the NH3 concentration in the interface gas phase (kg N m-3), [NH3]il is the NH3 concentration in the interface liquid phase (kg N m-3), and Kh is Henry’s coefficient (dimensionless). The NH3 concentration in the interface gas phase ([NH3]ig) is subject to wind speed. In Manure-DNDC [NH3]ig is simply set to linearly decrease as wind speed increases.