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.
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.
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.
Quantifying the long term environmental impacts of dairy and beef production is complex due to the many interactions among the physical and biological components of farms that affect the amount and type of emissions that occur. Emissions are influenced by climate and soil characteristics as well as internal management practices. Software models are needed to perform an integrated and comprehensive assessment of all important environmental and economic effects of farm management and mitigation strategies. Related: Manure value & economics
What Did We Do?
Figure 1. The Integrated Farm System Model simulates the performance, determines the economics, and predicts the air and water emissions of farm production systems.
Software tools were created that perform whole-farm analyses of the performance, economics and environmental impact of dairy and beef production systems. The Integrated Farm System Model (IFSM) is a comprehensive research tool that simulates production systems over many years of weather to quantify losses to the environment and the economics of production. From the simulated performance and losses, environmental footprints are determined for carbon, energy use, water use and reactive nitrogen loss. Crop, dairy and beef producing farms can be simulated under different management scenarios to evaluate and compare potential environmental and economic benefits. The Dairy Gas Emissions Model (DairyGEM) provides a simpler educational tool for studying management effects on greenhouse gas, ammonia and hydrogen sulfide emissions and the carbon, energy and water footprints of dairy production systems.
What Have We Learned?
Analyses with either the IFSM or DairyGEM tools illustrate the complexity of farming systems and the resultant effect of management choices. Although IFSM was primarily developed and used as a research tool, it is also used in classroom teaching and other education applications. DairyGEM provides an easier and more graphical tool that is best suited to educational use.
Future Plans
Figure 2. DairyGEM is an educational tool for evaluating management effects on air emissions and environmental footprints of dairy production systems.
Development of these software tools continues. Work is currently underway to add the simulation of VOC emissions to both models. Routines are also being implemented to better represent the performance and emissions of beef feed yards.
The IFSM and DairyGEM software tools are available through Internet download [https://www.ars.usda.gov/research/software/?modeCode=80-70-05-00] for use in individual, workshop and classroom education. Reference manuals and other detailed information on the models is also available at this website.
Acknowledgements
Many people have contributed to the development of these models and software tools. Although they can not all be listed here, they are acknowledged in each software program.
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.
Beef cattle are responsible for around 15% of the total anthropogenic ammonia (NH3) emitted in the U.S., and the cattle feeding industry is highly concentrated spatially, with the majority of commercial feedyards located in Texas, Iowa, Kansas,Colorado, and Nebraska (USEPA, 2005; USDA-NASS, 2009). Valid estimates of ammonia (NH3) emissions from beef cattle feedyards are needed to assess the impact of beef production on the environment, to comply with reporting requirements, and to develop reasonable regulatory policies. The processes involved in production and volatilization of NH3 from livestock housing are strongly influenced by environmental conditions and management practices (Fig. 1), which may not be captured by constant emission factors or mathematically-derived empirical models. Among different modeling approaches, process-based models, which track components of interest through biochemical and geochemical reactions as functions of specific conditions (e.g. temperature, wind speed, pH, precipitation, surface heating, animal diet), offer a better approach for predicting NH3 emissions from open-lot animal production systems than emission factors or empirical models. However, while process-based models have been developed to estimate NH3 emissions from dairy barns and other livestock facilities, little work has been conducted to assess their accuracy for large, commercial feedyards in the semi-arid Texas High Plains: the top beef producing region in the United States.
Figure 1. Processes and factors affecting feedyard ammonia emissions and modeled with IFSM and Manure-DNDC.
What Did We Do?
We evaluated two process-based models, the Integrated Farm Systems Model (IFSM) (Rotz et al., 2012) and the newly developed Manure-DNDC (DeNitrification DeComposition) model (Li et al., 2012), for predicting feedyard NH3 emissions in the Texas High Plains. To meet this objective, we compared model-simulated emissions to measured NH3 flux data collected from two commercial feedyards, Feedyard A and Feedyard E, in Deaf Smith County, Texas. Feedyard NH3 fluxes were measured from February 2007 to January 2009 using open-path lasers and an inverse dispersion model (Todd et al., 2011). The input data for the two models differed slightly; however, both required daily climate data (temperature, precipitation, wind speed, solar radiation), animal population (Feedyard A, 12,684 head; Feedyard E, 19,620 head), and concentration of crude protein (%CP) in cattle diets. Model performance was evaluated by the difference between predicted and observed emissions using both linear regression analysis and summary, univariate, and difference measures (Wilmott et al., 1982).
Figure 2 (above). Comparison of observed and IFSM predicted per capita NH3 emission rates (g head-1 d-1) at (a) Feedyard A, and (b) Feedyard E. Daily predictions were in good agreement (p < 0.001) with observations at both feedyards and responded appropriately to changes in ambient temperature and % CP in feedyard diets.
Figure 3 (below). Comparison of observed and Manure-DNDC predicted NH3 emission rates (kg ha-1 d-1) at (a) Feedyard A, and (b) Feedyard E. The units for Manure-DNDC (kg hectare-1 d-1) differ from IFSM (g head-1 d-1); however, daily Manure-DNDC predictions for 2008 agreed with observations (p < 0.001) in a manner similar to IFSM predictions.
What Have We Learned?
Predictions of daily NH3 emissions made by IFSM and Manure-DNDC were in good agreement (p < 0.001) with observations at both feedyards (Figs. 2 and 3, Table 1). IFSM predicted average NH3 fluxes of 151 and 75 g head-1 d-1 for Feedyards A and E, respectively (Table 1). Manure-DNDC output is on an area basis, and average modeled NH3 fluxes were 56 (Feedyard A) and 44 kg hectare-1 d-1 (Feedyard E). In addition, both models responded appropriately to changes in ambient temperature and %CP in feedyard diets, as shown by higher emissions in summer than winter, and the period of February to October 2008 at Feedyard A, when diets contained as much as 19% CP due to the inclusion of distillers grains (Figs. 2 and 3). The index of agreement (IA) indicates 71% to 81% agreement between model predictions and observed emissions (Table 1). Overall, both IFSM and Manure-DNDC predictions for Feedyard E had lower values for error and bias (MAE and MBE), while there was better agreement between observations and model predictions for NH3 emissions for Feedyard A.
Figure 4. Comparison of mean predicted and observed per capita NH3 emission rates from (a) Feedyard A and (b) Feedyard E in 2008. For most months, model predictions did not differ from observations, indicating that both models were useful for predicting average feedyard NH3 emissions.
Comparisons of modeled and observed mean daily per capita NH3 emissions for each month in 2008 are shown in Figure 4. For most months, model predictions did not differ significantly from observations, indicating that both models were useful for predicting average emissions. We also wanted to compare model predictions for annual per capita NH3 emissions to the emission factor of 13 kg head-1 y-1 that is currently used by the USEPA (USEPA, 2005). For 2008, IFSM and Manure-DNDC estimates of annual per capita emissions were 61 and 55 kg head-1 y-1 (Feedyard A) and 33 and 25 kg head-1 y-1 (Feedyard E), and model estimates for total feedyard emissions were within 3% to 24% of measured values (Table 2). In contrast, the current EPA emission factor underestimated total feedyard emissions by 61% to 79%: indicating that predictions by IFSM and Manure-DNDC can more accurately predict feedyard NH3 emissions than current constant emission factors.
Table 1. Regression and mean difference comparisons for observed and predicted daily feedyard NH3 emissions from Feb. 2007 to Jan. 2009, where there were 386 and 272 paired comparisons for Feedyard A and Feedyard E, respectively. Regression analysis indicated a highly significant (p < 0.001) relationship between observations and predictions made by both models. The index of agreement (IA) indicates 71% to 81% agreement between model predictions and observed emissions. Overall, both IFSM and Manure-DNDC model predictions for Feedyard E had lower values for error and bias (MAE and MBE), while there was better agreement between observations and model predictions for NH3 emissions for Feedyard A.
Table 2. Comparison of observed annual emissions at Feedyards A and E in 2008 with predictions by Manure-DNDC, IFSM, and the USEPA emission factor (EF) for beef cattle. For 2008, IFSM and Manure-DNDC estimates were within 3% to 24% accuracy. In contrast, the current EPA emission factor underestimated emissions by as much as 79%.
Future Plans
Future plans include using process-based models to predict nitrous oxide (N2O) emissions from feedyard pen surfaces. In addition, we will conduct laboratory and field-scale studies to better characterize the chemical and physical properties of feedyard manure in order to refine input parameters and improve model predictions of feedyard NH3 and N2O emissions.
Authors
Heidi M. Waldrip, Research Soil Scientist, USDA-ARS Conservation and Production Laboratory, Bushland, TX, heidi.waldrip@ars.usda.gov
C. Alan Rotz, Agricultural Engineer, USDA-ARS Pasture Systems and Watershed Management Research Unit, University Park, PA.
Changsheng Li, Research Professor, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH.
Richard W. Todd, Soil Scientist, USDA-ARS Conservation and Production Laboratory, Bushland, TX.
William Salas, President and Chief Scientist, Applied Geosolutions, LLC, Durham, NH.
N. Andy Cole, Research Leader and Animal Scientist, USDA-ARS Conservation and Production Laboratory, Bushland, TX.
Additional Information
Li, C., W. Salas, R. Zhang, C. Krauter, A. Rotz, and F. Mitloehner. 2012. Manure-DNDC: a biogeochemical process model for quantifying greenhouse gas and ammonia emissions from livestock manure systems. Nutr. Cycl. Agroecosyst. 93:163-200.
Rotz, C.A., M.S. Corson, D.S. Chianese, F. Montes, S.D. Hafner, R. Jarvis, and C.U. Coiner. 2012. Integrated Farm System Model: Reference Manual. University Park, PA: USDA Agricultural Research Service. Available at: http://www.ars.usda.gov/Main/docs.htm?docid=21345. Accessed 5 January 2013.
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. 40:1090-1095.
USEPA. 2005. National Emission Inventory – Ammonia Emissions from Animal Agricultural Operations: Revised Draft Report. 2005 Apr. 22. United States Environmental Protection Agency, Washington DC. Available at: http://www.epa.gov/ttnchie1/net/2002inventory.html. Accessed 02/27/2013.
Wilmott, C. J. 1982. Comments on the evaluation of model performance. Bull. Am. Meterol. Soc. 63:1309-1313.
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)”.
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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