Open Access
Sedorovich, Dawn
Graduate Program:
Agricultural and Biological Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
December 14, 2008
Committee Members:
  • Clarence Alan Rotz, Committee Chair
  • Thomas Lehman Richard, Committee Chair
  • Jason Philip Kaye, Committee Member
  • Paul Heinz Heinemann, Committee Member
  • simulation
  • agriculture
  • greenhouse gas
  • climate change
How does agriculture contribute to greenhouse gas emissions and what farm management scenarios decrease net emissions from agroecosystems? The reduction of greenhouse gas emissions is becoming more important world-wide. Although farmland can serve as a sink for carbon, agriculture is also an important source of emissions. As a sector, agriculture is reported to be the greatest contributor of nitrous oxide and the third greatest contributor of methane. As a result, various studies have attempted to answer the motivating questions. Despite the effort spent in answering these questions, most approaches have focused on one specific greenhouse gas, have used empirical relationships to quantify emissions, or have neglected important aspects an agricultural system. This research extended these approaches in order to answer the motivating questions by quantifying total net GHG emissions and developing a computer module to predict emissions using primarily mechanistic relationships. This module was incorporated into the Integrated Farm System Model (IFSM), which was then used to analyze reduction strategies in the context of a whole-farm system. First, typical ranges of greenhouse gas emissions were identified from sources (i.e., animal housing facilities, croplands, and manure storages) on dairy farms. The typical emission values were used to identify the major sources of greenhouse gases from dairy farms in order to guide the model development. A computer model was then created to predict greenhouse gas emissions from sources on a dairy farm. Process-based relationships were utilized for all of the major sources, and as many of the minor sources as was justified. The refined version of IFSM was evaluated for both prediction accuracy and sensitivity, and was determined to adequately predict whole-farm emissions of greenhouse gases. IFSM was then used to predict greenhouse gas emissions and net return from management scenarios in five categories: manure handling strategies, tillage systems, growth hormones, dietary forage concentration, and confined versus grazing production systems. The scenarios that emitted the least amount of greenhouse gases were: covered manure storages with surface application, no-till, using rBST growth hormone, high forage:grain ratio with additional forage produced on-farm, and winter confinement with summer pasture. Emissions of greenhouse gases need to be analyzed in the context of productivity (e.g., milk production) as well as profitability because farmers are unlikely to implement reduction practices that reduce their profit. Based on this analysis, the practices that resulted in the least greenhouse gas emissions were not always the most profitable, although a full economic analysis was out of the scope of this dissertation. All of these analyses were performed assuming no legislation regulating greenhouse gas emissions; future regulations restricting emissions would change the analysis by affecting the profitability of the scenarios. This research has identified management scenarios that result in environmental benefits and, in some cases, increased profitability. However, social factors and resistance to new practice will also influence whether the identified scenarios will actually be implemented. As a result, the identified scenarios must also be considered in the context of society and farm traditions.