Skip to main content
ARS Home » Midwest Area » Ames, Iowa » National Laboratory for Agriculture and The Environment » Soil, Water & Air Resources Research » Research » Research Project #431574

Research Project: Reducing the Environmental Footprint from Agricultural Systems through Managing Resources and Nutrient Inputs

Location: Soil, Water & Air Resources Research

2017 Annual Report


Objectives
Objective 1: Characterize and improve accounting of N emissions as N2O and NH3 losses from cropping systems. Subobjective 1.1: Quantify the soil and environmental factors contributing to N2O production by nitrifying and denitrifying bacteria. Subobjective 1.2: Assess the effect of cover crops on N2O production in the field. Subobjective 1.3: Assess manure injection/incorporation methods for impact on residue/surface cover, soil disturbance, and N emissions. Objective 2: Enhance process-level characterization of agrochemical emissions, fate and transport across spatial scales from micro-environments to regions. Subobjective 2.1: Determine the effect tillage practices have on agrochemical volatilization losses from agricultural fields. Subobjective 2.2: Improve measurement and modeling approaches to describe agrochemical emissions and transport from agricultural operations. Subobjective 2.3: Determine the emission flux of NH3 and other gases from cattle feedlot surfaces using flux-gradient technique. Subobjective 2.4: Compare particulate plume data measured with LiDaR to conventional model (ex. AERMOD) predictions to assess model accuracy for both near facility and downwind transport. Subobjective 2.5: Develop an improved physics-based model on the dispersion of herbicide droplets from mechanical sprayers by incorporating ambient turbulence conditions, the turbulent kinetic energy generated by the motion of the sprayer, and atmospheric stability. Objective 3: Develop strategies to manage the effects of manure properties and air flow on NH3 emissions. Subobjective 3.1: Manipulate swine diet formulations to improve N utilization, and reduce N excretion and NH3 emission along with other gaseous emission into the environment. Subobjective 3.2: Evaluate and develop ventilation practices for reducing NH3 and other air quality emissions.


Approach
This project will focus on knowledge gaps that exist in the loss of N and agrochemicals from cropping and animal systems. Three approaches will be pursued for addressing knowledge gaps: 1) quantify soil and environmental factors contributing to N2O and NH3 emissions in animal production and field cropping systems; 2) determine soil properties that drive volatile loss and transport of agrochemicals and N compounds, and 3) determine effectiveness of N control strategies for reducing NH3 emissions. In cropping systems, there are large gaps in our understanding of the N budget in soil including both mechanisms and magnitude of losses through emissions. Laboratory studies on N2O emissions will use stable isotopes to quantify both the effect of temperature and kinetics of denitrification under varying NH3 concentrations. Field studies using chambers will be used to quantify N2O emission for a range of soil and nitrogen management strategies. Assessing the effect residue/surface cover and soil disturbance have on N loss from manure application in cropping systems will be conducted during late fall and early spring. Whole field emissions loss of N will be quantified using both an open path laser system coupled with inverse dispersion modeling for NH3 and eddy covariance with a quantum cascade laser system for N2O emissions. Quantifying the transport parameters controlling volatile losses of pesticides from cropping systems based on tillage practices will use eddy covariance micrometeorology techniques to determine turbulent flux from whole fields. The relaxed eddy accumulation technique will be used to provide more accurate eddy diffusivities for pesticide vapor transport to improve agrochemical volatilization flux estimates. In addition, LiDaR will be used to develop dispersion models for droplets from mechanical sprayers for physics-based models on the loss of agrochemicals from fields due to spray drift. Quantifying the transport parameters controlling volatile losses of N compounds and particulates from animal production systems will involve LiDaR- to measure plume dynamics and produce a remote-sensing approach to quantify emissions and compare these results to conventional modeling approaches. In animal production systems, NH3 is the dominant form of N emissions, but gaps exist in effective N control/mitigation strategies that reduce N emissions. Reducing NH3 emissions from animal production will focus on improving N utilization in animal diets by use of feed additives and improving grind size of feed particles. Ventilation practices will be evaluating and optimized for reducing NH3 emissions. Knowledge gained through this research will provide producers and regulatory agencies scientific data to improve sustainability of agricultural production facilities in U.S. farming systems.


Progress Report
Objective 1: Experiments were conducted to quantify the interactive relationship between nitrous oxide production, temperature, and soil water content. It was found that following precipitation events, nitrous oxide (N2O) emissions temporarily increased, then gradually decreased. The decrease in N2O emissions occurred despite increasing temperature, suggesting that temperature was not a major factor controlling emissions. However, the diurnal pattern of N2O emissions closely matched the diurnal temperature pattern. Temperature sensitivity coefficients (Q-10) decreased with decreasing soil water content. These results indicate a dual control of temperature and soil water content on N2O emissions. Additional experiments will be needed in order to distinguish between nitrifier and denitrifier N2O production. Nitrous oxide emissions were measured throughout the year, and the temporal variability analyzed. A “hot-moment” analysis was developed using Tukey’s outlier test to identify extreme N2O emissions events. There was no effect of cover crop on the frequency of extreme events, however, the frequency of extreme events under corn was approximately 3 fold higher than under soybeans an effect likely due to fertilizer application in corn years. Objective 2: Long-term monitoring of two common pre-emergent herbicides continued for the 17th year. In 2014, the volatilization monitoring program was directed to assess metolachlor and atrazine volatilization losses from a reduced tillage operation. The study is being conducted at the same location as in previous years but with the added surface component of corn residue to determine the impact on volatilization losses. A new measurement protocol (Relaxed Eddy Accumulation, REA) is being developed by ARS scientists in Ames, Iowa and Beltsville, Maryland. The protocol uses fewer assumptions than the flux-gradient approach and will improve the accuracy of pesticide volatilization loss estimates. A critical element in the development of the REA system is to determine the optimal flow necessary to capture detectable concentrations of metolachlor and atrazine. The FY 2017 volatilization study focused on identifying the lowest flow rates to capture metolachlor and atrazine vapor. Extraction and quantification of the pre-emergent herbicides will be completed by the end of the FY 2017. Data from this study will drive the specification in building the REA at the Ames ARS facility. Determine emission flux of ammonia (NH3) from cattle feedlot using gradient flux technique. Ammonia data collected over a two year period was coupled with corresponding micrometeorology data. Ammonia data collected with NH3 open-path tunable diode laser was reduced into 15 min averages to align with micrometeorology data, while NH3 concentrations collected with photoacoustic multigas analyzer were averaged with micrometeorology data in two hour intervals. Concentration gradients from the feedlot surface followed a power function relationship. Preliminary data analysis suggests that increasing pen surface scraping reduces overall ammonia emissions. Quantifying accurate particulate and gas emissions to the atmosphere is essential to addressing air quality issues from animal production facilities. Landscape and facility structures all impact transport processes across spatial scales from micro-environments to regional scales. Previous campaigns have produced a large number of two dimensional particulate plume images across different animal production facilities using a Light Detection and Ranging (Lidar) approach. Linking local meteorological data with Lidar measurements is enabling Ames, Iowa ARS scientist to better understand how meteorologically conditions impact transport processes of particulates downwind and offsite. Merging the two distinct large data sets (Lidar and meteorology) will enable a new remote sensing approach to estimate plume emissions. In FY 2017, ARS and university scientists have been identifying specific periods representing emissions from poultry, swine and beef cattle facilities and preparing data sets that will be evaluated in combined into a new physically based algorithm to predict particulate emissions. Pesticide spray drift detection and range dispersion. Spray drift plumes were visualized using Lidar technology to determine if spray drift model characterization were accurate. The two dimensional data from operations showed mechanical turbulence generated by spray rigs contribute to the upward lofting and off-target dispersion of spray droplets. Preliminary data strongly suggest that mechanical turbulence generated by spray rigs contribute to the upward lofting and off-target dispersion of spray droplets. Lidar technology along with high frequency turbulence measurements is providing improved spray drift modeling. Objective 3: Swine feeding trial was completed investigating the effect crude protein (CP) level and sources have on emissions from swine manure. Low CP swine diets supplemented with crystalline amino acids lowered manure pH and lowered odorous volatile organic compounds (VOC). Ammonia levels in the manure were reduced by 7.6% for each 1% reduction in CP. The protein source in the diet affected both the pH of the manure (associated with fiber content) and sulfide levels that was controlled by sulfur levels in the diet. Lower CP diets had reduced levels of both ammonia and VOCs being emitted from manure. Ammonia emissions were lowered by 9.4% for each 1% reduction in CP content. The source of the CP affected NH3, hydrogen sulfide, and VOC emissions. Lower CP diets reduced odor by 5% for each 1% reduction in CP.


Accomplishments
1. Winter cover crops impact on nitrogen (N) emissions from cropping systems. Reactive N species are lost from poorly managed agricultural ecosystems. A long term study assessing the effect cover crops have on N loss through emissions was conducted at an ARS facility in Ames, Iowa. Winter cover crops were shown to reduce available soil mineral N during active growth, but potentially increased N loss through nitrous oxide (N2O) emissions when plants were killed by providing substrate for denitrifying bacteria. In this study direct soil emissions of N2O were measured over a 10 year period in a corn/soybean rotation with and without a winter rye cover crop, with no significant effect of the rye cover crop on N2O emissions, however, emissions were different between corn and soybeans. The rye cover crop did reduce indirect N2O emissions due to reductions in soil nitrate leaching. N2O emissions over 10 years tended to be lower in the rye cover crop treatment, thus the increased benefits of cover crops are not offset by greater N2O emissions. Large year-to-year variations in precipitation appeared to be a major determinant of annual N2O losses with larger emissions occurring after intense rainfall events. Increasing frequency of intense rainfall events due to climate change could result in larger soil N2O emissions in the future.

2. Tillage effects on agrochemical volatilization losses. Herbicides still dominate in terms of pounds of pesticide active ingredient applied annually. Researchers from Beltsville, Maryland and Ames, Iowa are conducting a long-term volatilization study (16 years) to quantify metolachlor and atrazine losses to the atmosphere under a wide range of local meteorological conditions and under conventional and reduced tillage practices. Results from the multi-year volatilization study for a low volatility pre-emergent herbicide showed that five days after application, cumulative herbicide volatilization ranged from 5% to 63% of that applied for metolachlor and from 2 to 11% of that applied for atrazine. For both atrazine and metolachlor, volatilization losses to the atmosphere were substantial and strongly related to soil surface water content and local meteorological conditions. Volatilization were orders of magnitude greater than surface runoff losses. This length of study is necessary to understand the differences among years and to provide a greater insight into the relationships between herbicide runoff and volatilization. Data results from this unique long-term research will influence the United States Department of Agriculture and United States Environmental Protection Agency policy with regard to herbicide behavior and the information on volatilization will be used to develop or improve pesticide transport models.

3. Comparison of particulate plume data using a laser to conventional model predictions. Quantifying particulate emissions from livestock operation remains a challenging issue due to the complex and diverse array of production facilities. Scientists from ARS in Ames, Iowa and University of Iowa conducted a series of two dimensional plume measurements at poultry, swine and cattle facilities that produced numerous two dimensional plume dispersion images. These images integrated turbulence and meteorological data to produce emission concentrations that were compared to conventional model emission concentrations. Integrating the laser measurements with meteorological data provided higher resolution estimates of particulate emissions which can be used evaluate new management strategies to reduce particulate emissions. Specific two dimensional images for a range of meteorological conditions have been identified for further analysis using turbulence data to correlate with plume transport features. Integrating two dimensional imagery of plume dispersion with local meteorological data will improve particulate emission estimations at the animal facility scale.

4. Lower ammonia and odor emissions through diet formulation. Livestock production is the main source of ammonia (NH3) in the environment and limiting nitrogen into the system will reduce the emissions of NH3. Lowering the crude protein (CP) content of animal diets has the potential to lower NH3 emissions. A swine feeding trial in Ames, Iowa was conducted to test this hypothesis with amino acid supplements replacing CP levels. Data from this study showed that NH3 and odor emissions were both reduced by 9.6% and 5% for each percent reduction of CP in the diet. The source of protein in the diet also impacted emissions of both ammonia and odor. Animal diet reformulations with crystalline amino acids have the potential to lower emissions thereby reducing the environmental footprint of swine facilities.


Review Publications
Van Weelden, M., Andersen, D., Kerr, B.J., Trabue, S.L., Rosentrater, K., Pepple, L., dos Santos, T. 2016. Impact of dietary carbohydrate and protein source and content on swine manure foaming properties. Biological Engineering (ASABE). 59(4):923-932. doi: 10.13031/trans.59.11470.
Nichols, V.A., Miguez, F.E., Sauer, T.J., Dietzel, R.N. 2016. Maize and prairie root contributions to soil CO2 emissions in the field. Crop Science. 56:1-11. doi: 10.2135/cropsci2016.01.0048.
Xiao, X., Sauer, T.J., Singer, J.W., Horton, R., Ren, T., Heitman, J.L. 2016. Partitioning evaporation and transpiration in a maize field using heat pulse sensors for evaporation measurement. Transactions of the ASABE. 59(2):591-599. doi: 10.13031/trans.59.11059.
Hatfield, J.L., Prueger, J.H. 2016. Variable atmospheric, canopy, and soil effects on energy and carbon fluxes over crops. In: Hatfield, J.L., Fleisher, D.H. editors. Advances in Agricultural Systems Modeling. Vol. 7. Madison, WI: ASA, CSSA, and SSSA. p. 195-216.
Willis, W., Elchinger, W., Prueger, J.H., Hapeman, C.J., Li, H., Buser, M., Hatfield, J.L., Wanjura, J.D., Holt, G.A., Torrents, A., Plenner, S., Clarida, W., Brown, S.D. 2017. Particulate capture efficiency of a vegetative environmental buffer surrounding an animal feeding operation. Agriculture, Ecosystems and Environment. 240:101-108.
Panzacchi, P., Gioacchini, P., Sauer, T.J., Tonon, G. 2016. New dual in-growth core isotopic technique to assess the root litter carbon input to the soil. Geoderma. 278:32-39. doi: 10.1016/j.geoderma.2016.05.010.
Parkin, T.B., Kaspar, T.C., Jaynes, D.B., Moorman, T.B. 2016. Rye cover crop effects on direct and indirect nitrous oxide emissions. Soil Science Society of America Journal. 80(6):1551-1559. doi: 10.2136/sssaj2016.04.0120.
Boote, K.J., Porter, C., Jones, J.W., Thorburn, P.J., Kersebaum, K.C., Hoogenboom, G., White, J.W., Hatfield, J.L. 2016. Sentinel site data for model improvement – Definition and characterization. In: J. L. Hatfield, D. Fleisher, editors. Improving Modeling Tools to Assess Climate Change Effects on Crop Response. Advances in Agricultural Systems Modeling. Volume 7. Madison, WI: American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc. p. 125-158. doi: 10.2134/advagricsystmodel7.2014.0019.
Prueger, J.H., Alfieri, J.G., Gish, T.J., Kustas, W.P., Hatfield, J.L., Daughtry, C.S., McKee, L.G. 2017. Multi-year measurements of field-scale metolachlor volatilization. Water, Air, and Soil Pollution. 228:84. doi: 10.1007/s11270-017-3258-z.
Anderson, R.G., Alfieri, J.G., Tirado-Corbala, R., Gartung, J.L., McKee, L.G., Prueger, J.H., Wang, D., Ayars, J.E., Kustas, W.P. 2016. Assessing FAO-56 dual crop coefficients using eddy covariance flux partitioning. Agricultural Water Management. 179:92-102. doi: 10.1016/j.agwat.2016.07.027.