|Veltman, Karin - University Of Michigan|
|Jones, Curtis - University Of Wisconsin|
|Izaurralde, R. - University Of Wisconsin|
|Reddy, Ashwan - University Of Wisconsin|
|Gaillard, Richard - University Of Wisconsin|
|Duval, Benjamin - University Of Wisconsin|
|Cela, Sebastian - Cornell University - New York|
|Ketterings, Quirine - Cornell University - New York|
|Rotz, Clarence - Al|
|Salas, William - Applied Geosolutions, Llc|
|Jolliet, Olivier - University Of Michigan|
Submitted to: Agriculture, Ecosystems and Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/12/2016
Publication Date: 2/1/2017
Publication URL: http://handle.nal.usda.gov/10113/5618131
Citation: Veltman, K., Jones, C., Izaurralde, R., Reddy, A., Gaillard, R., Duval, B., Cela, S., Ketterings, Q.M., Rotz, C.A., Salas, W., Vadas, P.A., Jolliet, O. 2017. Comparison of process-based models to quantify nutrient flows and greenhouse gas emissions of milk production. Agriculture, Ecosystems and Environment. 237:31-44.
Interpretive Summary: Assessing the sustainability of nutrient use and losses on dairy farms is essential for future food security and environmental quality. Computer models can help evaluate all the production components of a dairy farm at the whole-farm level, but different models may give different information depending on how they are designed and how they work. We compared predictions of major nutrient (nitrogen, phosphorus) flows and greenhouse gas emissions for five different models for a New York dairy farm. Predicted whole-farm, global warming impacts were similar for the two whole-farm models. Model predictions were also comparable for most nutrient flows related to the animal, barn, and manure management. In contrast, predicted gas emissions and nutrient losses from fields varied across models. This indicates a need to improve our understanding and data for soil and crop nutrient flows in order to improve model use for assessing sustainability of dairy production systems.
Technical Abstract: Assessing and improving the sustainability of dairy production systems is essential to secure future food production. This requires a holistic approach that reveals trade-offs between emissions of the different greenhouse gases (GHG) and nutrient-based pollutants and ensures that interactions between farm components are taken into account. Process-based models are essential to support whole-farm mass balance accounting, however, variation between process-based model results may be large and there is a need to compare and better understand the strengths and limitations of various models. Here, we use a whole-farm mass-balance approach to compare five process-based models in terms of major nutrient (N, P) flows and greenhouse gas (GHG) emissions associated with milk production at the animal, farm and field-scale. Results show that predicted whole-farm, global warming impacts were very similar for the two whole farm models with a predicted global warming impact of approximately 1.1x107 kg CO2 equivalent per year for both models and a dominant contribution of enteric CH4 emissions. Model predictions are also highly comparable, i.e. within a factor of 1.5, for most nutrient flows related to the animal, barn and manure management system, including enteric CH4 emissions, and NH3 emissions from the barn. In contrast, predicted field emissions of N2O and NH3 to air, and N and P losses to the hydrosphere, are very variable across models. This indicates that there is a need to further our understanding of soil and crop nutrient flows and that measurement data on nutrient emissions are particularly needed for the field. In addition, there is a need to further understand how the anaerobic digester influences the manure composition and subsequent emissions of N2O and NH3 after application of the digestate to the field. Empirical data on manure composition before and after anaerobic digestion are essential for model evaluation. The whole-farm mass-balance approach is advocated as an essential tool to assess and improve the sustainability of dairy production systems. Our comparison of five process-based models provides insight into the range of expected emissions associated with milk production.