Title: Process-based modeling of ammonia emission from beef cattle feedyards with the integrated farm systems model Authors
Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 19, 2014
Publication Date: July 14, 2014
Citation: Waldrip, H., Rotz, C.A., Hafner, S.D., Todd, R.W., Cole, N.A. 2014. Process-based modeling of ammonia emission from beef cattle feedyards with the integrated farm systems model. Journal of Environmental Quality. 43:1159-1168. Interpretive Summary: Ammonia losses from the manure in beef cattle feedlots reduces the amount manure nitrogen could be used for crop fertilizer. Feedlot ammonia losses might also negatively affect the environment and human health. There are both mathematical and process-based models that can predict ammonia losses from dairies and other livestock production systems. However, these models have not been tested for predicting ammonia losses from large beef cattle feedlots. In this work, we improved a process-based model, the Integrated Farms Systems Model (IFSM), by adding components that simulate nitrogen dynamics in beef cattle manure. The model was tested by comparing IFSM-predicted daily ammonia emission rates to measured data that was collected from two commercial feedlots in Texas from 2007 to 2009. The model predictions agreed well with measured daily emission rates at both feedlots. The model also responded correctly to changes in air temperature and the amount of protein in cattle diets. The IFSM-predicted average daily ammonia emission rates for the two feedlots had 71% to 81% agreement with measured values. In addition, IFSM estimates of total yearly feedlot emissions were within 11% to 24% of measured values for the two feedlots. This agreement was much better than that of predictions that were made with the emission factor currently used by the United States Environmental Protection Agency (EPA). The EPA emission factor underestimated feedlot emissions by more than 79%. This work showed that IFSM can be used to determine average feedlot ammonia losses. The model could be a useful tool for assisting with ammonia emissions reporting. It could also provide good information about feedlot ammonia losses to lawmakers and assist in looking for ways to reduce feedlot ammonia losses.
Technical Abstract: Ammonia volatilization from manure in beef cattle feedyards results in loss of agronomically important nitrogen (N), and potentially leads to over-fertilization and acidification of aquatic and terrestrial ecosystems and formation of atmospheric fine particulate matter that can impact human health. Both empirical and process-based models have been developed to estimate ammonia emissions from various livestock production systems; however, little work has been conducted to assess their accuracy for large, open-lot feedyards. This work describes the extension of an existing process-based model, the Integrated Farm Systems Model (IFSM), to include simulation of N dynamics in this type of system. To evaluate the model, IFSM-simulated daily per capita ammonia emission rates were compared to emissions data collected from two commercial feedyards in the Texas High Plains from 2007 to 2009. Model predictions were in good agreement with observations from both feedyards and were sensitive to variations in air temperature and dietary crude protein (CP) concentration. Predicted mean daily ammonia emission rates for the two feedyards had 71% to 81% agreement with observed values. In addition, IFSM estimates of annual feedyard emissions were within 11% to 24% of observations for the two feedyards, whereas a constant emission factor currently in use by the USEPA underestimated feedyard emissions by as much as 79%. The results from this study indicate that IFSM can be used to quantify average feedyard ammonia emissions, assist with emissions reporting, provide accurate information for legislators and policy makers, investigate methods to mitigate ammonia loss, and help evaluate the effects of specific management practices on farm nutrient balances.