Tag: feedyard

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Measuring Nitrous Oxide and Methane Emissions from Feedyard Pen Surfaces; Experience with the NFT-NSS Chamber Technique

Why Study Nitrous Oxide and Methane at Cattle Feedyards?

Accurate estimation of greenhouse gas emissions, including nitrous oxide and methane, from open beef cattle feedlots is an increasing concern given the current and potential future reporting requirements for GHG emissions. Research measuring emission fluxes of GHGs from open beef cattle feedlots, however, has been very limited. Soil and environmental scientists have long used various chamber based techniques, particularly non-flow-through – non-steady-state (NFT-NSS) chambers for measuring soil fluxes. Adaptation of this technique to feedyards presents a series of challenges, including spatial variability, presence of animals, chamber base installation issues, gas sample collection and storage, concentration analysis range, and flux calculations.

What did we do? 

Following an extensive review of the literature on measuring emissions from cropping and pasture systems, it was decide to adopt non-flow-through – non-steady-state (NFT-NSS) chambers as the preferred measurement methodology. However, the use of these NFT-NSS chambers had to be adapted for use in conditions of beef cattle feedyards and open corral dairies.

What have we learned? 

Trials of various techniques for sealing the chamber to the manure surface including piling soil/manure around the chamber and various weighted skirts were trial, however no technique was as good at sealing the chamber as a metal ring driven 50-75 mm into the underlying substrate.

Chamber bases could potentially injure animal in the pen and/or animal could disturb the measurement installation, so measurements were only conducted in recently vacated pens.

Gas samples were drawn from a septa in the chamber cap using a 20 ml polyethylene syringe and immediately injected into a 12 ml evacuated exetainer vial for transport, storage and analysis. Trials of alternative vials led to sample loss and contamination issues.

Gas samples were analyzed using a gas chromatograph equipped with ECD, FID and TCD detectors for nitrous oxide, methane and carbon dioxide determination, respectively.

The metal rings or bases must be installed at least 24 and preferably 48 hours before measurements are commenced as the disturbance caused when installing the bases will result in a temporarily enhanced emission flux.

Ten, 20 cm dia chambers constructed from PVC pipe caps are deployed in a pen and yield a reasonable approximation of the average emission fluxes from the pen.

The range of gas concentrations measured in the chamber at the end of a 30 minute deployment was up to 2 orders of magnitude greater than that typically measured in cropping systems research. This required careful choice of calibration gas concentrations and calibration of the gas chromatograph. The response of the ECD detector used for determining N2O concentration may not be linear over the entire range experienced.

The rate of increase in concentration in the chamber is often curvilinear in form and a quadratic approach was adopted for determination of the flux rate.

Future Plans 

On-going studies are quantifying N2O and CH4 flux rates from pen surfaces in a cattle feedlots under varying seasonal conditions; further work is identifying contributing factors.

Authors

Kenneth D. Casey, Associate Professor at Texas A&M AgriLife Research, Amarillo TX kdcasey@ag.tamu.edu

Heidi M. Waldrip, Research Soil Scientist at USDA ARS CPRL, Bushland TX; Richard W. Todd, Research Soil Scientist at USDA ARS CPRL, Bushland TX; and N. Andy Cole, Research Soil Scientist at USDA ARS CPRL, Bushland TX;

Additional information 

For further information, contact Ken Casey, 806-677-5600

Acknowledgements

Research was partially funded from USDA NIFA Special Research Grants

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2015. Title of presentation. Waste to Worth: Spreading Science and Solutions. Seattle, WA. March 31-April 3, 2015. URL of this page. Accessed on: today’s date.

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Ammonia and Nitrous Oxide Model for Open Lot Cattle Production Systems

Purpose 

Air emissions, such as ammonia (NH3) and nitrous oxide (N2O), vary considerably among beef and dairy open lot operations as influenced by the climate and manure pack conditions. Because of the challenges with direct measurements, process-based modeling is a recommended approach for estimating air emissions from animal feeding operations. The Integrated Farm Systems Model (IFSM; USDA-ARS, 2014), a whole-farm simulation model for crop, dairy and beef operations, was previously expanded (version 4.0) to simulate NH3 emissions from open lots. The model performed well in representing emissions for two beef cattle feedyards in Texas (Waldrip et al., 2014) but performed poorly in predicting NH3 emissions measured at an open lot dairy in Idaho.

What did we do? 

The open lot nitrogen routine of IFSM was revised to better represent the effects of climate on lot and manure pack conditions. Processes affecting the formation and emission of NH3 and N2O from open lots were revised and better integrated. These processes included urea hydrolysis, surface infiltration, ammonium-ammonia association/dissociation, ammonium sorption, NH3 volatilization, nitrification, denitrification, and nitrate leaching (Figure 1). The soil water model in IFSM was also modified and used to represent an open lot. The accuracy of the revised model (version 4.1) was evaluated using measurements from two beef cattle feedyards in Texas (Todd et al., 2011; Waldrip et al., 2014) and an open lot dairy in Idaho (Leytem et al., 2011). Comparing the two regions, Idaho typically has much drier conditions in summer and wetter conditions in winter.

Lot model

Figure 1. The revised Integrated Farm Systems Model (IFSM)

What have we learned? 

The revised model predicted NH3 emissions for the Texas beef cattle feedyards similar to the previous version with model predictions having 59 to 81% agreement with measured daily emissions. Simulated NH3 emissions for the Idaho open lot dairy improved substantially with 56% agreement between predicted and measured daily NH3 emissions. For the Idaho open lot dairy, IFSM also predicted daily N2O emissions with 80% agreement to those measured. These results support that IFSM can predict NH3 and N2O emissions from open lots as influenced by climate and lot conditions. Therefore, IFSM provides a useful tool for estimating open lot emissions of NH3 and N2O along with other aspects of performance, environmental impact and economics of cattle feeding operations in different climate regions, and for evaluating management strategies to mitigate emissions.

Future Plans    

The revised IFSM is being used to study nitrogen losses and whole farm nutrient balances of open lot feed yards and dairies. The environmental benefits and economic costs of mitigation strategies will be evaluated to determine best management practices for these production systems.

Authors      

C. Alan Rotz, Agricultural Engineer, USDA-ARS al.rotz@ars.usda.gov

Henry F. Bonifacio, April B. Leytem, Heidi M. Waldrip, Richard W. Todd

Additional information 

Leytem, A.B., R.S. Dungan, D.L. Bjorneberg, and A.C. Koehn. 2011. Emissions of ammonia, methane, carbon dioxide, and nitrous oxide from dairy cattle housing and manure management systems. J. Environ. Qual. 40:1383-1394.

Todd, R.W., N.A. Cole, M.B. Rhoades, D.B. Parker, and K.D. Casey. 2011. Daily, monthly, seasonal and annual ammonia emissions from Southern High Plains cattle feedyards. J. Environ. Qual. 40:1-6.

USDA-ARS. 2014. Integrated Farm System Model. Pasture Systems and Watershed Mgt. Res. Unit, University Park, PA. Available at: http://www.ars.usda.gov/Main/docs.htm?docid=8519. Accessed 5 January, 2015.

Waldrip, H.M., C.A. Rotz, S.D. Hafner, R.W. Todd, and N.A. Cole. 2014. Process-based modeling of ammonia emissions from beef cattle feedyards with the Integrated Farm System Model. J. Environ. Qual. 43:1159-1168.

Acknowledgements      

This research was funded in part by the United Dairymen of Idaho. Cooperation of the dairy and beef producers is also acknowledged and appreciated.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2015. Title of presentation. Waste to Worth: Spreading Science and Solutions. Seattle, WA. March 31-April 3, 2015. URL of this page. Accessed on: today’s date.

 

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Particulate matter from open lot dairies and cattle feeding: recent developments

The research community is making good progress in understanding the mechanical, biochemical, and atmospheric processes that are responsible for airborne emissions of particulate matter (PM, or dust) from open-lot livestock production, especially dairies and cattle feedyards.  Recent studies in Texas, Kansas, Nebraska, Colorado, California, and Australia have expanded the available data on both emission rates and abatement measures. Although the uncertainties associated with our estimates of fugitive emissions are still unacceptably high, we have learned from our recent experience with ammonia that using a wide variety of credible measurement techniques, rather than focusing on one so-called “standard” technique, may be the better way to improve confidence in our estimates.  Whereas the most promising control measures for gaseous emissions continue to be dietary strategies  with management of corral-surface moisture a close second for particulate matter, corral-surface management and moisture management play comparable roles, depending on the mechanical strength of soils and the availability of water, respectively.  The cost per unit reduction of emitted mass attributable to these abatement measures varies as widely as the emissions estimates themselves, so we need to intensify our emphasis on process-based emissions research to (a) reduce the variances in our emissions estimates and (b) mitigate the contingency of prior, empirically based estimates.  As a general rule, although cattle feedyard emission factors may be thought a reasonable starting point for estimating emissions from open-lot dairies, such estimates should be viewed with suspicion.

Purpose          

Document the state of the art of particulate-matter (PM) emissions from open-lot livestock facilities, including emission fluxes and abatement measures.

What did we do?

We conducted (a) field research at commercial, open-lot livestock facilities in the southern High Plains and (b) an up-to-date review of the latest literature concerning primary particulate matter emission fluxes and the abatement measures appropriate to the source type. Field research included time-resolved concentration measurements upwind and downwind of the livestock facilities during the hottest, driest times of the year (in the case of dairy emissions) and throughout the year (in the case of beef feedyards); and a 5-month evaluation of stocking density manipulation using electric cross-fences that preserve optimum bunk space for beef cattle on feed. The literature review surveyed research findings from anywhere in the world that were published in refereed journals as recently as March 2015 concerning the same topics.

What have we learned?

Increasing the stocking density of fed beef cattle as compared to the industry-wide average during hot, dry weather suppresses dust emissions to a measurable and reasonably consistent degree. Concentrations of PM measured downwind of open-lot dairies vary throughout the day, though to a lesser degree and at lower overall concentrations than those measured downwind of nearby beef cattle feedyards, likely reflecting (a) the comparatively lower intensity of the dairy animal’s physical activity and (b) the greater diurnal uniformity of animal-activity patterns in dairies as compared to those in cattle feedyards. Stocking density manipulation does not appear likely to influence dairy dust emissions to the same degree as it influences feedyard dust emissions. Our confidence in emission-flux estimates from these open-lot systems suffers from a lack of methodological diversity; that confidence would be greatly bolstered by the deployment of measurement techniques that differ from the standard inverse-dispersion-modeling paradigm. The integrated horizontal flux (IHF) approach to emissions estimation, which we are now testing at a cattle feedyard in the Texas Panhandle, will provide some corroborating evidence that will allow us to narrow the range of PM flux estimates in the research literature, a range that now spans more than an order of magnitude when expressed on a per-animal-unit basis.

Future Plans

We will continue long-term, ground-level monitoring of time-resolved PM concentrations at a commercial cattle feedyard in the Texas Panhandle; continue our ongoing tests of the IHF flux-estimation technique; and evaluate eye-safe lidar as a path-averaging monitoring technology for the intermediate path lengths (50-300m) that will permit experimental discrimination of concentration data downwind of adjacent pen areas featuring different dust-abatement measures.

Authors    

Brent Auvermann, Professor, Texas A&M AgriLife Extension Service b-auvermann@tamu.edu

K. Jack Bush and Kevin R. Heflin, Research Associates, Texas A&M AgriLife Research

Additional information              

6500 Amarillo Blvd. West, Amarillo, TX 79106-1796, (806)670-8081 (cell)

Acknowledgements      

USDA-NIFA Contract Nos. 2010-34466-20739 and 2009-55112-05235; Texas A&M AgriLife Research; JBS Five Rivers Cattle Feeding; Texas Air Research Center; Texas Cattle Feeders Association

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2015. Title of presentation. Waste to Worth: Spreading Science and Solutions. Seattle, WA. March 31-April 3, 2015. URL of this page. Accessed on: today’s date.

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Ammonia Emissions and Emission Factors: A Summary of Investigations at Beef Cattle Feedyards on the Southern High Plains

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Why Study Ammonia Emitted from Feedlots?

Ammonia volatilization is a major component of the nitrogen balance of a feedyard, and the effects of ammonia loss range from the economic (loss of manure fertilizer value) to the environmental (air quality degradation, overfertilization of ecosystems). Although not yet regulated, ammonia emissions from cattle are required to be reported under the Emergency Planning and Community Right to Know Act. Emission factors are used to estimate ammonia emissions for purposes of reporting and national inventories, but current emission factors are based on limited data. Our objective was to definitively quantify ammonia emissions and emission factors from commercial feedyards on the southern High Plains of Texas.

A typical feedyard on the High Plains of Texas. In the foreground, cattle in corrals with a stocking density of about 150 sq. ft./animal. In the background on the left, the runoff water retention pond, and center, a mound of stockpiled manure.

What Did We Do?

Ammonia emissions were quantified at three commercial feedyards in the Texas Panhandle from 2002 to 2008 using micrometeorological methods. Seasonal, intensive measurement campaigns were conducted from 2002 to 2005 at one feedyard, and ammonia emissions were near-continously monitored from 2007-2008 at two more feedyards. Meteorological and cattle management data were also collected.

What Have We Learned?

Ammonia emissions followed a distinct annual pattern. Emissions during summer were about twice those during winter, while spring and autumn emissions were intermediate. Annualized ammonia emissions ranged from 0.20 to 0.37 lb NH3/animal/day, and averaged 0.26 lb NH3/animal/day over all studies. Ammonia loss as a fraction of nitrogen fed to cattle averaged 41% during winter and 69% during summer; on an annual basis, 54% of fed nitrogen was lost as ammonia. Greatest emissions were observed when crude protein in cattle rations exceeded the nutrient requirements of beef cattle. Mean monthly ammonia emissions were strongly correlated with mean monthly temperature, and the relationship can be used to predict ammonia emissions from southern High Plains feedyards. Cattle feeders that meet recommended crude protein in rations can expect to lose half of fed N as ammonia. We recommend an annual emission factor of 88 lb/head for beef cattle feedyards based on one-time capacity, or 39 lb/head fed, based on a 150-d feeding period.

The annual pattern of ammonia emission rates (ER) followed seasonal temperatures, but also was sensitive to dietary crude protein (CP). Adding distillers grains to rations from March, 2008 to October, 2008 increased crude protein at Feedyard A to as high as 19%. Ammonia emissions greatly increased compared with the previous year and compared with Feedyard E.

Future Plans

Next steps involve using the extensive database from this research to adapt and refine process-based models of ammonia emissions. These models, based on the actual physical and chemical processes that control ammonia loss, will be more generally applicable than emission factors to a wider range of feedyards.

On an annual basis, ammonia emission averaged 0.26 lb per animal per day across the three feedyards and six years of study. Increased ammonia emission at Feedyard A in 2008 was due to high dietary crude protein when distillers grains were added to rations. Using these data and other estimates of ammonia loss from retention ponds and stockpiles, we recommend, for beef cattle fed a diet that meets protein requirements, an annual emission factor of 88 lb/head based on one-time capacity, or 39 lb/head fed, based on a 150-d feeding period.

Authors

Richard W. Todd, Research Soil Scientist, USDA-ARS Conservation and Production Research Laboratory, Bushland, Texas, richard.todd@ars.usda.gov

Richard W. Todd, Research Soil Scientist; N. Andy Cole, Research Leader and Research Animal Scientist (Nutrition); and Heidi M. Waldrip, Research Soil Scientist: USDA-ARS Conservation and Production Research Laboratory, Bushland, Texas.

Additional Information

Cole, N.A., R.N. Clark, R.W. Todd, C.R. Richardson, A. Gueye, L.W. Greene, and K. McBride. 2005. Influence of dietary crude protein concentration and source on potential ammonia emissions from beef cattle manure.  J. Anim. Sci. 83:722 731.

Cole, N.A., A.M. Mason, R.W. Todd, M. Rhoades, and D.B. Parker. 2009. Chemical composition of pen surface layers of beef cattle feedayrds. Prof. Anim. Sci. 25:541-552.

Flesch, T.K., J.D. Wilson, L.A. Harper, R.W. Todd, and N.A. Cole. 2007. Determining ammonia emissions from a cattle feedlot with an inverse dispersion technique. Agric. For. Meteorol. 144:139-155.

Hristov, A. N., M. Hanigan, A. Cole, R. Todd, T. A. McAllister, P. M. Ndegwa, A. Rotz. 2011. Ammonia emissions from dairy farms and beef feedlots: A review. Can. J. Anim. Sci. 91:1-35.

Preece, S.L., N.A. Cole, R.W. Todd, and B.W. Auvermann. 2012. Ammonia emissions from cattle-feeding operation. Texas A&M AgriLife Extension Bulletin E-632 12/12.

Rhoades, M.B., D.B. Parker, N.A. Cole, R.W. Todd, E.A. Caraway, B.W. Auvermann, D.R. Topliff, and G.L. Schuster. 2010. Continuous ammonia emission measurements from a commercial beef feedyard in Texas. Trans. ASABE 53:1823-1831.

Sakirkin, S.L., N.A. Cole, R.W. Todd, and B.W. Auvermann. 2011. Ammonia emissions from cattle-feeding operations. Part 1: issues and emissions. Texas Agricultural Experiment Station Bulletin, Air Quality Education in Animal Agriculture, Issues: Ammonia, December, 2011. p. 1-11.

Sakirkin, S., R.W. Todd, N.A. Cole, and B.W. Avermann. 2011. Ammonia emissions from cattle-feeding operations. Part 2: abatement. Texas Agricultural Experiment Station Bulletin, Air Quality Education in Animal Agriculture, Issues: Abatement, December, 2011. p. 1-11.

Todd, R.W., N.A. Cole, and R.N. Clark. 2006. Reducing crude protein in beef cattle diet reduces ammonia emissions from artificial feedyard surfaces. J. Environ. Qual. 35:404-411.

Todd, R.W., N.A. Cole, M.B. Rhoades, D.B. Parker, and K.D. Casey. 2011. Daily, monthly, seasonal and annual ammonia emissions from southern High Plains cattle feedyards. J. Environ. Qual. 40:1-6.

Todd, R.W., N.A. Cole, H.M. Waldrip, and R.M. Aiken. 2013. Arrhenius equation for modeling feedyard ammonia emissions using temperature and diet crude protein. J. Environ. Qual. 2013. (accepted for publication).

Acknowledgements

Research was supported by CSREES Grant #TS2006-06009 under the direction of Dr. John Sweeten, Resident Director, Texas A&M University AgriLife Research and Extension Center, Amarillo, TX. Larry Fulton, Research Technician, USDA-ARS-CPRL, provided invaluable technical and logistical support and expertise.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2013. Title of presentation. Waste to Worth: Spreading Science and Solutions. Denver, CO. April 1-5, 2013. URL of this page. Accessed on: today’s date.

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Photometric measurement of ground-level fugitive dust emissions from open-lot animal feeding operations.

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Abstract

Fugitive dust from confined livestock operations is a primary air quality issue associated with impaired visibility, nuisance odor, and other quality-of-life factors.  Particulate matter has conventionally been measured using costly scientific instruments such as transmissometers, nephelometers, or tapered-element, oscillating microbalances (TEOMs).  The use of digital imaging and automated data-acquisition systems has become a standard practice in some locations to track visibility conditions on roadways; however, the concept of using photometry to measure fugitive dust concentrations near confined livestock operations is relatively new.  We have developed a photometric method to estimate path-averaged particulate matter (PM10) concentrations using digital SLR cameras and high-contrast visibility targets.  Digital imaging, followed by automated image processing and interpretation, would be a plausible, cost-effective alternative for operators of confined livestock facilities to monitor on-site dust concentrations.  We report on the development and ongoing evaluation of such a method for use by cattle feeders and open-lot dairy producers.

Purpose

To develop a low-cost practical alternative for measurement of path-averaged particulate matter (PM10) concentrations downwind of open-lot animal feeding operations.

What Did We Do?

Working downwind of a cattle feedyard under a variety of dust conditions, we photographed an array of high contrast visibility targets with dSLR cameras and compared contrast data extracted from the photographs with path-averaged particulate matter (PM10) concentration data collected from several TEOMs codeployed alonside the visibility targets.

What Have We Learned?

We have developed a photometric method to estimate path-averaged particulate matter (PM10) concentrations using digital SLR cameras and high-contrast visibility targets.  Using contrast data from digital images we expect to predict PM10 concentrations within 20% of TEOM values under the dustiest conditions.  Digital imaging, followed by automated image processing and interpretation, may be a plausible, cost-effective alternative for operators of open-lot livestock facilities to monitor on-site dust concentrations and evaluate the abatement measures and management practices they put in place.

Future Plans

We intend to improve the prediction accuracy of the photometric method and automate it such that it can be easily adapted for use as a cost-effective alternative for measuring path-averaged particulate matter (PM10) concentrations at cattle feedyards and open-lot dairies.

Authors

Brent Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research.  b-auvermann@tamu.edu

Sharon Preece, Senior Research Associate, Texas A&M AgriLife Research; Brent W. Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research; Taek M. Kwon, Professor of Electrical and Computer Engineering, University of Minnesota-Duluth; Gary W. Marek, Postdoctoral Research Associate, Texas A&M AgriLife Research; Kevin Heflin, Extension Associate, Texas A&M AgriLife Research; K. Jack Bush, Research Associate, Texas A&M AgriLife Research.

Additional Information

Please contact Brent W. Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research, 6500 Amarillo Boulevard West, Amarillo TX, 79106, Phone: 806-677-5600, Email: b-auvermann@tamu.edu.

Acknowledgements

This research was underwritten by grants from the USDA National Institute on Food and Agriculture (contract nos. 2010-34466-20739 and 2009-55112-05235).

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2013. Title of presentation. Waste to Worth: Spreading Science and Solutions. Denver, CO. April 1-5, 2013. URL of this page. Accessed on: today’s date.

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Developing a Modeling Framework to Characterize Manure Flows in Texas

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Abstract

In recent years, sharply rising costs of inorganic fertilizers have contributed to an increased demand for manure and compost in crop production acreage, transforming cattle manure from a valueless waste to a viable alternative to commercial fertilizer. If additional demand for manure as a bio-fuel were to arise manure could take on two distinct values, a fertilizer value and a fuel value. This potential “dual” value of manure begs several questions. What would the fertilizer and fuel markets of manure look like? Is there enough manure supply for the markets to operate independently? If not, which market would prevail? In essence, how, if at all, would manure’s potential value as a bio-fuel distort the traditional Panhandle manure market? A modeling framework was developed to assess the potential impacts of a manure-fired ethanol plant on the existing Texas Panhandle manure fertilizer market.  Two manure-allocation runs were performed using a spreadsheet model. Run #1 allocated all available manure from dairies and feedlots to cropland as manure fertilizer; run #2 first allocated fuel manure to the ethanol plant and then allocated the remaining manure to cropland. Both model runs assumed a time horizon of one year and no antecedent nutrients in cropland soils. Other constraints included only irrigated acreages received manure and no supplemental fertilizer was used. The model revealed a 6.4% increase in cost per acre of fertilizing with manure for fields whose nutrient requirements were fully satisfied in both runs. The increase in cost per acre was likely due to an increase in hauling distances attributed to fewer CAFOs available for fertilizer manure. The model is not presented as a dynamic, systems model, but rather a static model with the potential to be incorporated into a more dynamic systems-based modeling environment. Suggestions for further model development and expansion including GAMS integration are presented.

Why Model Manure Transport and Use?

To demonstrate the potential for systems modeling to characterize manure flows in response to fertilizer prices,  biofuel demand, and other externalities in the Texas Panhandle

Conceptual model diagram.

What Did We Do?

We develeloped a spreadsheet based modeling framework to evaluate how both manure use and transport might be affected by regional changes in fertilizer prices, crop composition, and biofuel demand.  Specifically, we evaluated how traditional fertilizer valued manure flows might be affected by potential biofuel based flows stemming from a proposed manure-fired ethanol plant.  Two model simulations representing manure flows with and without biofuel manure demand from the proposed plant were performed.

Explicit model boundary shown with TNRIS satellite imagery used to locate and identify center pivot irrigated fields.

What Have We Learned?

Although the cattle industry in Texas Panhandle generates a substantial volume of manure, almost all of it is land applied as fertilizer.  However, the introduction of manure-fired facilities such as the proposed ethanol plant would undoubtedly change the dynamics of the existing manure market by introducing at least additional demand, if not a second value-based market.  Assuming only transportation costs of acquiring manure for biofuel, our model simulations suggested a 6.4% increase in cost per acre for lands whose manure requirements were fully satisfied in both simulations.  Assuming that manure for biofuel received an allocation preference for proximity to the plant, we propose that costs associated with having to transport manure over longer distances significantly contributes the the increased cost per acre for fertilized lands.

In terms of what we learned about systems modeling, we have experienced (although anticipated) that translating broad, systems based conceptual modeling ideas into an explicit, user friendly, and robust modeling interface can be extremely challenging. Although systems-based modeling efforts occur largely at a macro level, they often require extensive supplemental datasets.  We have experienced difficulty in identifying software packages that are equipped to adequately handle both aspects of systems modeling.

Future Plans

We plan to continue to develop and expand the current modeling framework by incorporating  a GIS-based water availability aquifer component, expanding the current crop-composition database, and providing logic algorithms for producer-based management decisions using GAMS (General Algebraic Modeling System) optimization modeling.

Manure allocation map for model run #1 (232 LMU cells allocated).

Authors

Brent Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research, b-auvermann@tamu.edu

Gary Marek, Postdoctoral Research Associate, Texas A&M AgriLife Research; Brent W. Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research; Kevin Heflin, Extension Associate, Texas A&M AgriLife Extension

Additional Information

Please contact Gary Marek, Postdoctoral Research Associate, Texas A&M AgriLife Research, 6500 Amarillo Boulevard West, Amarillo TX, 79106, Phone: 806-677-5600, Email: gwmarek@ag.tamu.edu or  Brent W. Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research, 6500 Amarillo Boulevard West, Amarillo TX, 79106, Phone: 806-677-5600, Email: b-auvermann@tamu.edu.

Acknowledgements

Special thanks to Dr. Raghavan Srinivasan and David Shoemate of the Texas A&M University Department of Ecosystem Science and Management Spacial Sciences Laboratory for their help in GIS processing scripts.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2013. Title of presentation. Waste to Worth: Spreading Science and Solutions. Denver, CO. April 1-5, 2013. URL of this page. Accessed on: today’s date.

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