The Use of USDA-NRCS Conservation Innovation Grants to Advance Air Quality Improvements

USDA-NRCS has nearly fifteen years of Conservation Innovation Grant project experience, and several of these projects have provided a means to learn more about various techniques for addressing air emissions from animal agriculture.  The overall goal of the Conservation Innovation Grant program is to provide an avenue for the on-farm demonstration of tools and technologies that have shown promise in a research setting and to further determine the parameters that may enable these promising tools and technologies to be implemented on-farm through USDA-NRCS conservation programs.

What Did We Do?

Several queries for both National Competition and State Competition projects in the USDA-NRCS Conservation Innovation Grant Project Search Tool (https://www.nrcs.usda.gov/wps/portal/nrcs/ciglanding/national/programs/financial/cig/cigsearch/) were conducted using the General Text Search feature for keywords such as “air”, “ammonia”, “animal”, “beef”, “carbon”, “dairy”, “digester”, “digestion”, “livestock”, “manure”, “poultry”, and “swine” in order to try and capture all of the animal air quality-related Conservation Innovation Grant projects.  This approach obviously identified many projects that might be related to one or more of the search words, but were not directly related to animal air quality. Further manual review of the identified projects was conducted to identify those that specifically had some association with animal air quality.

What Have We Learned?

Out of nearly 1,300 total Conservation Innovation Grant projects, just under 50 were identified as having a direct relevance to animal air quality in some way.  These projects represent a USDA-NRCS investment of just under $20 million. Because each project required at least a 50% match by the grantee, the USDA-NRCS Conservation Innovation Grant program has represented a total investment of approximately $40 million over the past 15 years in demonstrating tools and technologies for addressing air emissions from animal agriculture.

The technologies that have been attempted to be demonstrated in the animal air quality-related Conservation Innovation Grant projects have included various feed management strategies, approaches for reducing emissions from animal pens and housing, and an approach to mortality management.  However, the vast majority of animal air quality-related Conservation Innovation Grant projects have focused on air emissions from manure management – primarily looking at anaerobic digestion technologies – and land application of manure. Two projects also developed and enhanced an online tool for assessing livestock and poultry operations for opportunities to address various air emissions.

Future Plans

The 2018 Farm Bill re-authorized the Conservation Innovation Grant Program through 2023 at $25 million per year and allows for on-farm conservation innovation trials.  It is anticipated that additional air quality projects will be funded under the current Farm Bill authorization.

Authors

Greg Zwicke, Air Quality Engineer, USDA-NRCS National Air Quality and Atmospheric Change Technology Development Team

greg.zwicke@ftc.usda.gov

Additional Information

More information about the USDA-NRCS Conservation Innovation Grants program is available on the Conservation Innovation Grants website (https://www.nrcs.usda.gov/wps/portal/nrcs/main/national/programs/financial/cig/), including application information and materials, resources for grantees, success stories, and a project search tool.

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. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.

How Well Do We Understand Nitrous Oxide Emissions from Open-lot Cattle Systems?

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Purpose

Nitrous oxide (N2O) emissions from concentrated animal feeding operations, including cattle feedyards, have become an important research topic. However, there are limitations to current measurement techniques, uncertainty in the magnitude of feedyard N2O fluxes, and a lack of effective mitigation methods. There are uncertainties in the pathway of feedyard N2O production, the dynamics of nitrogen transformations in these manure-based systems, and how N2O emissions differ with changes in climate and feedyard management.

What Did We Do?

A literature review was conducted to assess the state-of-the-science of N2O production and emission from open-lot beef cattle feedyards and dairies. The objective was to assess N2O emission from cattle feedyards, including comparison of measured and modeled emission rates, discussion of measurement methods, and evaluation of mitigation options. In addition, laboratory, pilot-scale, and field-scale chamber studies were conducted to quantify and characterize N2O emissions from beef cattle manure. These studies led to new empirical model to predict feedyard N2O fluxes as a function of temperature and manure nitrate and water contents. Organic matter stability/availability was important in predicting manure-derived N2O emissions: inclusion of data for dissolved organic carbon content and Ultraviolet-visible (UV-vis) spectroscopic indices of molecular weight, complexity and degree humification improved model performance against measured data.

What Have We Learned?

Published annual per capita flux rates for beef cattle feedyards and open-lot dairies in arid climates were highly variable and ranged from 0.002 to 4.3 kg N2O animal-1 yr-1. On an area basis, published emission rates ranged from 0 to 41 mg N2O m-2 h-1. From these studies and the Intergovernmental Panel on Climate Change emission factors, calculated daily per capita N2O fluxes averaged 18 ± 10 g N2O animal-1 d-1 (range, 0.04–67 g N2O animal-1 d-1). Some of this variability is inherently derived from differences in manure management practices and animal diets among open-lot cattle systems. However, it was proposed that other major causes of variation were inconsistency in measurement techniques, and irregularity in N2O production due to environmental conditions.

For modeling studies, N2O emissions were measured during 15 chamber studies (10 chambers per study) on commercial Texas feedyards, where N2O emissions ranged from below detection to 101 mg N2O m-2 h-1. Numerous feedyard and manure data were collected and regression analyses were used to determine key variables involved in feedyard N2O losses. Based on these data, two models were developed: (1) a simple model that included temperature, manure water content, and manure nitrate concentration, and (2) a more complex model that included UV-vis spectral data that provided an estimate of organic matter stability. Overall, predictions with both models were not significantly different from measured emissions (P < 0.05) and were within 52 to 61% agreement with observations. Inclusion of data for organic matter characteristics improved model predictions of high (>30 mg m-2 h-1) N2O emissions, but tended to overestimate low emission rates (<20 mg N2O m-2 h-1). This work represents one of the first attempts to model feedyard N2O. Further refinement is needed to be useful for predicting spatial and temporal variations in feedyard N2O fluxes.

Future Plans

This work clearly identified that neither the magnitude nor the dynamics of N2O emissions from open-lot cattle systems were well understood. Five primary knowledge gaps/problem areas were identified, where current understanding is weak and further research is required. These include: (i) the need for accurate measurement of N2O emissions with appropriate and more standardized methods; (ii) improved understanding of the microbiology, chemistry, and physical structure of manure within feedyard pens that lead to N2O emissions; (iii) improved understanding of factors that influence feedyard N2O emissions, including manure H2O content, porosity, density, available nitrogen and carbon contents, environmental temperatures, and use of veterinary pharmaceuticals; (iv) development of cost-effective and practical mitigation strategies to decrease N2O emissions from pen surfaces, manure stockpiles, composting windrows, and retention ponds; and (v) improved process-based models that can accurately predict feedyard N2O emissions, evaluate mitigation strategies, and forecast future N2O emission trends.

Given the potential for future regulation of N2O emissions, feedyard managers, nutritionists, and researchers may play increasingly important roles in on-farm nitrogen management. Current management practices may need modification or refinement to balance production efficiency with environmental concerns. There is a need for data derived from both large-scale micrometerological measurement campaigns and small-scale chamber studies to assess the overall magnitude of feedyard N2O emissions and to determine key factors driving its production and emission. Refined empirical and process-based models based on manure physicochemical properties and weather could provide a dynamic approach to predict N2O losses from open-lot cattle systems.

Corresponding author (name, title, affiliation):

Heidi Waldrip, Research Chemist, USDA-ARS Conservation and Production Laboratory, Bushland, TX

Corresponding author email address

heidi.waldrip@ars.usda.gov

Other Authors

Rick Todd, Research Soil Scientist, USDA-ARS Conservation and Production Laboratory, Bushland, TX

David Parker, Agricultural Engineer, USDA-ARS Conservation and Production Research Laboratory, Bushland, TX

Al Rotz, Agricultural Engineer, USDA-ARS Pasture Systems and Watershed Management Research Unit, University Park, PA

Andy Cole, Animal Scientist, USDA-ARS Conservation and Production Research Laboratory (retired), Bushland, TX.

Ken Casey, Associate Professor, Texas A&M AgriLife Research, Amarillo, TX

Additional Information

“Nitrous Oxide Emissions from Open-Lot Cattle Feedyards: A Review”. Waldrip, H. M., Todd, R. W., Parker, D. B., Cole, N. A., Rotz, C. A., and Casey, K. D. 2016. J. Environ. Qual. 45:1797-1811. Open-access article available at:  https://dl.sciencesocieties.org/publications/jeq/pdfs/45/6/1797?search-r…

USDA-ARS Research on Feedyard Nitrogen Sustainability: http://www.beefresearch.org/CMDocs/BeefResearch/Sustainability_FactSheet…

Acknowledgements

This research was partially funded by the Beef Checkoff: http://www.beefboard.org/

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. 2017. Title of presentation. Waste to Worth: Spreading Science and Solutions. Cary, NC. April 18-21, 2017. URL of this page. Accessed on: today’s date.

Evaluation of a Model to Predict Enteric Methane Production from Feedlot Cattle


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Purpose

Continual refinement of methods estimating enteric methane production in beef finishing cattle provides a more accurate assessment of the environmental impact of the beef industry.  The USDA-OCE publication “Quantifying Greenhouse Gas Fluxes in Agriculture and Forestry: Methods for Entity-Scale Inventory” identified conservation practices and management strategies for reducing greenhouse gas emissions while improving agriculture production (Eve et al., 2014).  In Chapter 5 a new method to estimate effects of nutrition and management on enteric methane production of feedlot cattle is provided.  The system recommends using adjustment factors to correct the IPCC (2006) tier 2 Methane Conversion Factor (Ym) of 3.0% of gross energy intake to an adjusted Ym.  Adjustment factors are used for dietary grain and fat concentrations, grain type and processing method, and ionophore use.  These adjustment factors let beef producers more accurately determine the enteric methane production associated with their individual finishing operation.

What Did We Do?

To evaluate this new model, we developed a database consisting of 36 refereed publications, with 75 treatment means.  The focus of this database was to identify published research relating to high concentration beef finishing that provided methane as a percent of gross energy, or provided enough information for calculation.  Treatments containing greater than 20% forage were excluded, as they are not representative of a high concentration finishing diet.  Additionally, treatment diets utilizing a methane mitigation agent were excluded from the database. 

What Have We Learned?

This database encompassed 75 treatment means containing a wide range in weight, intake and protein of the diets.  Body weight, dry matter intake, and dietary crude protein concentrations for the database ranged from 150 to 723 kg, 4.78 to 12.9 kg, and 9.4 to 23%, respectively.  Predicted Ym had a significant but relatively low correlation (r = 0.31, P = 0.0077) to actual Ym.  However, when one experiment (4 treatments) with very high methane values (likely a result of manure CH4) was removed, the correlation improved (r = 0.62, P < 0.0001), resulting in the following relationship:  Predicted Ym = 2.23 + (0.41 * actual YM) (r2 = 0.39, RMSE = 0.58).  Predicted g of CHproduced daily were highly correlated to actual g of CH4/d (r2 = 0.63, RMSE = 22.61), and predicted CH4 produced, as a percentage of digestible energy intake, was highly correlated to actual CHper kcal of digestible energy intake, DEI (r2 = 0.46, RMSE = 0.61).  Under the conditions of this investigation, the new model moderately predicted enteric methane production from feedlot cattle fed high-concentrate diets.

Future Plans

The database will be expanded as refereed publications suitable to the selection criteria are identified.  Trials with greater forage inclusion will be evaluated to test the robustness of the model and evaluate the correlation to IPPC (2006) estimations. 

Corresponding author (name, title, affiliation) 

Tracy D. Jennings, Associate Research Scientist, Texas A&M AgriLife Research

Corresponding author email address  

Tracy.Jennings@ag.tamu.edu

Other Authors 

Kristen Johnson, Professor, Washington State University; Luis Tedeschi, Professor, Texas A&M University; Michael Galyean, Provost, Texas Tech University, Richard Todd, Soil Scientist, USDA-ARS; N. Andy Cole, Retired Animal Scientist, USDA-ARS

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. 2017. Title of presentation. Waste to Worth: Spreading Science and Solutions. Cary, NC. April 18-21, 2017. URL of this page. Accessed on: today’s date.

Use of zilpaterol hydrocholoride to reduce odors and gas production from the feedlot surface when beef cattle are fed diets with or without ethanol byproducts

Purpose

Many malodorous compounds emitted from the feedlot surface of beef finishing facilities result from protein degradation of feces and urine (Mackie et al., 1998; Miller and Varel, 2001, 2002). The inclusion of wet distillers grain with solubles (WDGS) in beef finishing diets has been shown to increase nitrogen excretion (Spiehs and Varel, 2009; Hales et al., 2012) which can increase odorous compounds in waste (Spiehs and Varel, 2009). Zilpaterol hydrochloride (ZH) is a supplement fed to cattle for a short period of time (21 days) near the end of the finishing phase to improve efficiency of lean gain. Improvements in feed efficiency and lean tissue accretion potentially decrease nitrogen excretion from cattle. Therefore, the use of ZH in feedlot diets, especially those containing WDGS, may reduce the concentration of odorous compounds on the feedlot surface. The objective of this study was to determine if the addition of ZH to beef f inishing diets containing 0 or 30% WDGS would decrease odor and gas production from the feedlot surface.

What did we do?

Sixteen pens of cattle (25-28 cattle/pen) were used in a 2 x 2 factorial study. Factors included 0 or 30% WDGS inclusion and 0 or 84 mg/steer daily ZH for 21 d at the end of the finishing period. Each of the four following treatment combinations were fed to 4 pens of cattle: 1) finishing diet containing 0% WDGS and 0 mg ZH, 2) finishing diet containing 30% WDGS and 0 mg ZH, 3) finishing diet containing 0% WDGS and 84 mg/animal daily ZH and 4) finishing diet containing 30% WDGS and 84 mg/animal daily ZH. A minimum of 20 fresh fecal pads were collected from each feedlot pen on six occasions. Samples were mixed within pen and a sub-sample was placed in a small wind-tunnel. Duplicate samples for each pen were analyzed. Odorous volatile organic compounds were collected on sorbent tubes and analyzed for straight-chain fatty acids, branched-chain fatty acids, aromatic compounds, and sulfide compounds using a thermal desorption-gas chromatograph-mass spectrometry (Aglient Technologies, Inc, Santa Clara, CA). Ammonia (NH3) production was measured using a Model 17i Ammonia Analyzer (Thermo Scientific, Franklin, MA), and hydrogen sulfide (H2S) was measured using a Model 450i Hydrogen Sulfide Analyzer (Thermo Scientific, Franklin, MA).

What have we learned?

Inclusion of ZH in beef finishing diets was effective in lowering the concentration of total sulfides, total branched-chain fatty acids, and hydrogen sulfide from fresh cattle feces. Inclusion of 30% WDGS to beef feedlot diets increased the concentration of odorous aromatic compounds from feces. Ammonia concentration was not affected by the inclusion of either WDGS or ZH in the finishing diet. Producers may see a reduction in odorous emissions when ZH are fed to beef finishing cattle.

Table 1. Effect of ZH and WDGS inclusion in beef feedlot diets on concentration of odorous volatile organic compounds from cattle feces

Future Plans

Additional research is planned to evaluate the use of β-agonists, such as ZH, with moderate and aggressive implant strategies. These implants may further improve feed efficiency and lean gain, thereby potentially reducing excess nutrient excretion and odorous emissions. Evaluation odorous emissions from the feedlot surface when ZH are fed is also needed.

Authors

Mindy J. Spiehs, USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE mindy.spiehs@ars.usda.gov

Kristin E. Hales, USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE

Additional information

Mention of trade names or commercial products in their article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA. USDA is an equal opportunity provider and employer.

Literature cited

Hales, K. E., N. A. Cole, and J. C. MacDonald. 2012. Effects of corn processing method and dietary inclusion of wet distillers grains with solubles on energy metabolism, carbon-nitrogen balance, and methane emissions of cattle. J. Anim. Sci. 90:3174-3185.

Mackie, R. I., P. G. Stroot, and V. H. Varel. 1998. Biochemical identification and biological origin of key odor components in livestock waste. J. Anim. Sci. 76:1331-1342.\

Miller, D. N. and V. H. Varel. 2001. In vitro study of the biochemical origin and production limits of odorous compounds in cattle feedlots. J. Anim. Sci. 79:2949-2956.

Miller, D. N. and V. H. Varel. 2002. An in vitro study of manure composition on the biochemical origins, composition, and accumulation of odorous compounds in cattle feedlots . J. Anim. Sci. 80:2214-2222.

Spiehs, M. J. and V. H. Varel. 2009. Nutrient excretion and odorant production in manure from cattle fed corn wet distillers grains with solubles. J. Anim. Sci. 87:2977-2984.

Acknowledgements

The authors wish to thank Alan Kruger and Elaine Ven John for assistance with data collection.

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.

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.

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.

Demonstration of a Pilot Scale Leach-bed Multistage Digester for Treating Dry-lot Wastes

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Abstract

Dry-lot feedlot wastes have historically been a challenging feed-stock for digestion due to the dry recalcitrant nature of the waste, and the presence of settleable sand. Leach-bed dry digestion systems could theoretically circumnavigate these difficulties but poor hydraulic conductivities are noted in the literature. In addition to the poor hydraulic conductivities there are often serious problems with system stability and operation.  A leach-bed based design which addresses the hydraulic limitations of previous systems and utilizes a multiple process stages to enhance system stability is currently under development. By adding readily available inert shear stabilizers and biodegradable porosity improvers, hydraulic improvements have been demonstrated to be an order of magnitude higher than without the modifications.  By utilizing a multiple stage process the liquid leachategenerated from the leachate beds is treated through two stages, the buffering/storage tank and the high rate methanogenic reactor. The buffering tank is a tank for the leachate to reach chemical equilibrium and to store the leachate before it is precisely metered into the methanogenic tank.  Within the high rate methanogenic reactor compounds with the leachate are converted into methane which is removed and combusted. This system is demonstrated in a 48’ long refrigeration transport trailer which is essentially energy independent under continuously operation. This system will provide support for the validation of the technology with various wastes and will also serve as a research vessel for the continual optimization of this technology.

Front of the Pilot Unit

Is It Possible to Digest Dry or Solid Manure?

This new anaerobic digestion system has been designed from the ground up based on extension work carried out on Colorado dairy and beef facilities. Previous feasibility studies conducted on these sites indicated that conventional anaerobic digestion was not a recommended technology due to a variety of economic and technical parameters.

However, upon further review, it was found that these constraints were tied to specific technologies, not anaerobic digestion in general. Using an iterative design process, a digestion system was created which could effectively address these problems. In its most basic form, it will efficiently process difficult wastes like Colorado’s dry-lot manures as well as other more conventional waste streams.

What Did We Do?

Colorado State University has a pilot system located on the Foothills Campus. The purpose of this pilot unit is to gather data about the performance of the leachate bay reactor in an integrated system and to provide design criteria for scaling this concept. The system is currently in the inoculation stage. Using a consortium of animal manures and bedding waste generated onsite, the reactors are growing the bacteria needed before further testing can commence.

Intrinsic to the design is a three phased process that is tailored to the available substrates. Solid type wastes (Typically >20% total solids) are placed into the leachate bay reactor where liquid (leachate) is passed through, slowly striping away methane forming organic chemicals.

6kW Generator with Heat Exchanger for Heat Reactors with Waste Heat

Slurry wastes (Typically <20% total solids with high suspended solids) can pass into the second stage of the process- the leachate storage tank. This vessel acts as a pre digestion vessel, solids sedimentation basin, and storage tank for the pre-digestion products. Clarified leachate, rich with dissolved organic compounds, is then pumped into the final stage- the high rate reactor. In the high rate reactor process upset is mitigated by providing a very controlled flow rate of the acidic leachate into the reactor. This moderates the pH in the reactor, allowing the methane producing organisms to operate at maximum potential. Quickly degraded waste waters such as: milk processing water, run-off lagoon water, or nearby industrial wastes can be added directly to the high rate reactor.

What Have We Learned?

Solid wastes appropriate for the leachate bay reactor are dry-lot cattle manure, crop residues, equine and poultry manures, among many others. These types of wastes were the important drivers in the breakdown of technical and economic feasibility of conventional digestion systems. Due to the design of the leachate bay reactors though, many of these constraints were avoided and these wastes instead play a powerful role in this systems effectiveness by allowing digestion of often overlooked waste products. Related: Update on this project presented at the 2015 Waste to Worth conference in Seattle.

Manure Loading Dock with LBR

Future Plans

Extensive infrastructure has been built into this pilot unit to facilitate monitoring and logic control of this facility. Ongoing work will be to build out this sensing network. 

Important design parameters will be teased out of the collected data to guide the development of optimization models. With the use of these models, the system can be further modified. Potential technological enhancements include: nutrient recovery from leachate, various flushing procedures to reduce salt loading, and digestion of ligno-cellulotic by-products.

Authors

Sybil Sharvelle, Sybil.Sharvelle@colostate.edu

Lucas Loetscher, Graduate Reseach Assistant, Colorado State University

Sybil Sharvelle, Assistant Professor, Colorado State University

Acknowledgements

  • Colorado Agriculture Experiment Station
  • Colorado NRCS
  • Colorado Bioscience Discovery Grant
  • Colorado Governors Energy Office

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.

What are typical values for the higher heating value of manure scraped from cattle feedyard surfaces?

The higher heating value of manure scraped from cattle feedyard surfaces depends primarily on its ash and moisture content. If the manure’s ash and water were completely removed with only the combustible fraction remaining as a residue, that (primarily organic) residue would have a higher heating value (HHV) of about 8,500 BTU per pound, as determined experimentally by Annamalai et al. (1987) and Rodriguez et al. (1998). That figure of 8,500 BTU/lb is known as a “dry, ash-free” (DAF) fuel value. To estimate the HHV of actual feedyard manure (i.e., in its “as-received” or “as-is” state), which always has some ash and some moisture in it, you can multiply the 8,500 BTU/lb figure by (1 – ash) and (1 – moisture). In this case, “ash” is the manure’s ash content expressed as a fraction (dry basis), and “moisture” is the manure’s moisture content as a fraction (wet basis). For example, a manure sample having 40% ash (dry basis) and 20% moisture (wet basis) would have an HHV of approximately: HHV(ash = 40%, moisture = 20%) = 8,500 BTU/lb x (1 – 0.40) x (1 – 0.20) = 8,500 x 0.6 x 0.8 = 4,080 BTU/lb Cattle manure (as excreted) has about 75% moisture and 15% ash, which translates to an HHV around 1,750 BTU/lb. On the feedyard surface, it generally dries out and may reach moisture contents as low as 15 to 20%. Depending on whether the corral surfaces are paved or native soil, the ash content may increase dramatically. HHV values between 2,000 and 5,000 BTU/lb are common, but they are highly variable because of moisture and ash dynamics of these outdoor facilities. Fuel value of manure generated in full confinement?under roof, on concrete?can be more tightly controlled.

Other cited literature:

Annamalai, K., J. M. Sweeten and S.C. Ramalingam. 1987. Estimation of gross heating values of biomass fuels. Transactions of the ASAE 30(4):1205-1208. Rodriguez, P.G., K. Annamalai, and J.M. Sweeten. 1988. The effect of drying on the heating value of biomass fuels. Transactions of the ASAE 41(4):1083-1087

 

Solid Manure Sampling Procedures

Developing a nutrient management plan depends on testing manure for nutrient content. Your manure test results are only as good as your sample. This page outlines recommended ways to sample solid manure from open feedlots.

Sample During Loading

The recommended sampling for solid manure is to sample while loading the spreader. Sampling the manure pack in a barn directly has been shown to result in very variable results and is not recommended. Take at least 5 samples during the process of loading several spreader loads and save them in a bucket. When all of the samples are collected, thoroughly mix the samples and take a subsample from this to fill the lab manure test container.

Sample Manure During Spreading

Spread a tarp or sheet of plastic in the field and spread manure over this with the manure spreader. Do this in several locations and with several loads of manure. Collect the manure from the tarp or plastic sheet in a bucket. Mix the manure collected from different locations and spreaders, and take a subsample from this to fill the lab manure test container. This procedure is usually only practical for more solid manures.

Photo courtesy USDA NRCS

Sampling Daily Haul Manure

Place a 5 gallon bucket under the barn cleaner 4 or 5 times while loading the spreader. When all of the samples are collected, thoroughly mix the samples and take a subsample from this to fill the lab manure test container. Repeat this several times throughout the year to determine variability over time.

Sampling Manure in a Poultry House

Collect 8-10 samples from throughout the house to the depth of the litter to be removed. Samples near feeders and waterers can be very different. Collect samples from these areas proportional to the space they occupy in the house. When all of the samples are collected, thoroughly mix the samples and take a subsample from this to fill the lab manure test container. A sample taken while loading the spreader or during spreading is likely to be a more representative sample.

Sampling Stockpiled Litter

Take 10 samples from different locations around the pile at least 18 inches below the surface. When all of the samples are collected, thoroughly mix the samples and take a subsample from this to fill the lab manure test container. Large diameter auger bit and portable drill or soil sampler can be used to access manure deep within pile.

Taking a sample from a manure stockpile Taking representative sample from all subsamples mixed together in a bucket

Sampling stockpiled manure. Picture Source: Manure Testing for Nutrient Content

Sampling Manure from an Open Lot

These videos were produced by the Iowa Learning Farms project.

Sampling Stockpiled and Composted Manure

Related Web Pages

Overview of Manure Testing

Page Authors: Douglas Beegle, Penn State University and John Peters, University of Wisconsin