Pork producers have made significant investments in life cycle assessments (LCAs) and the Pig Production Environmental Footprint Calculator (PPEC). This project built on pork’s previous data investments by harmonizing the life cycle inventory data for the stand-alone pork, corn, and soy LCAs to arrive at an integrated model that was utilized to determine the relationship between select best management practices, environmental outcomes, and farm-level economics.

The objective of this project was two-fold: 1) explore and quantify the potential of U.S. agricultural production systems to reduce impacts on water quality and greenhouse gas (GHG) emissions and increase carbon sequestration through implementation of best management practices. Toward that end, we evaluated aggregate row crop and livestock production data necessary to conduct LCA planning and scenario generation for two primary row crop systems (corn and soy) and one livestock production system (pork) and 2) determine the economic cost-benefit to producers of implementing best management practices that have a positive impact on environmental outcomes.

This research was undertaken in five phases:

  1. Literature Review: We prepared a literature-based review of the state of knowledge on production practice impacts on select environmental indicators (water quality, water quantity, greenhouse gas emissions, and carbon sequestration potential) within major row crops (corn, soybean, wheat, cotton, barley, and oats) and two major animal protein (pork and poultry) production systems.
  2. Harmonization of LCA Models for Pork, Corn, and Soy & Scenario Analysis: We compiled available life cycle inventory data from the Eco-Invent version 3.5 database and constructed a life cycle inventory database specific to pork, corn, and soy in the openLCA software platform. We then built a series of life cycle inventory models based on a harmonized suite of data from both the foreground (i.e., production systems) and background (i.e., all purchased inputs to pork, corn, and soy production) systems. Using this new data framework, we evaluated the environmental characteristics of each system through a series of nine crop production scenarios and five swine production scenarios. Cropping strategies included conventional, conservation, and no-till practices; buffer strips; crop rotation; and irrigation scenarios. Pork production strategies included gestation stalls vs. crates, use of ractopamine, improved animal health & welfare/use of antimicrobials in production, and feed conversion rate. The APEX model was used for simulating corn and soy production, and the PPEC was used to simulate gestating sows and farrow to finish operations. All crop systems were modeled from cradle-to-farm gate, using a functional unit of 1000 kg of 15% moisture corn, soy, or oats. The pork systems was modeled from cradle-to-harvesting facility loading dock, using a functional unit of 1000 kg live weight delivered to the harvest facility for swine.
  3. LCA Uncertainty and Sensitivity Analysis: We characterized the uncertainty of effectiveness of each best management practice with respect to the three environmental indicators of focus (water quality/quantity, GHG emissions, and carbon sequestration), using a statistical model involving Monte Carlo simulations and pairwise comparisons of each scenario against the baseline. We then conducted a sensitivity analysis to determine the contribution of each production practice, or variable, to the environmental indicators.
  4. Economic Assessment: We analyzed and assessed the farm-level financial impacts of the crop and swine production scenarios by assigning estimated costs and revenues to the LCA input and output data. By matching prices to inputs and outputs, we generated a more accurate assessment of the economic investment and return associated with practices that result in positive environmental outcomes and related tradeoffs that stand-alone environmental or economic models might not otherwise show.
  5. Data Platform Landscape: We evaluated a suite of existing calculators, standards, and certification programs available for measuring agricultural sustainability, as well as the input variables and format required by farmers to populate the models/programs.
  6. Evaluation of Ag Data & Precision Ag Technologies: We reviewed the current state and capacity of precision ag technology, including the various data streams and methods most commonly used throughout the ag industry.

The result of this effort is a first-of-its kind integrated life cycle inventory database and harmonized life cycle assessment for agricultural commodities that can be used to model the relationship between best management practices and environmental outcomes and to identify which practices have the greatest impact on environmental KPIs. Additionally, the paired pricing to LCA data inputs and outputs provides a framework for evaluating the tradeoffs between farm-level environmental performance and economic outcomes. Collectively, these databases, models, and scenarios provide a critical foundation for agricultural integration data and simplification of the variables that drive farm-level environmental and economic performance. Importantly, this body of work can be utilized to inform future sustainability research, narrow data gaps, and accelerate data integration across efforts for pork, corn, and soy. This work can also be leveraged to support goal-setting and provides a framework for modeling environmental and economic tradeoff scenarios as policy or supply chain conversations evolve.

We would like to stress that both the volume and impact of this effort is immense. Importantly, this work was supported by leveraged investments, with generous support from the National Pork Board, the United Soybean Board, the Walton Family Foundation, and a resulting match from the Foundation for Food and Agriculture Research to launch the Agriculture Climate Partnership. In essence, we were able to amplify farmer dollars with a funding and research model that advances science and integrated data more rapidly. This model can be replicated for other commodities beyond pork, corn, and soy. The implications of this report will be far reaching to affect strategic ongoing efforts for research and data investments and ultimately further the critical research partnership between NPB, USB, and NCGA. Equally, the results of this project serve as a foundation to inform supply chain sustainability metrics efforts, database development, precision ag tools, and policy development. For questions about the results, please contact [email protected].

Key Findings

  1. Literature Review: The literature review provides us with a better understanding of the current state of knowledge as well as knowledge gaps for corn, soybean, and pork production systems. Importantly, we discovered new information demonstrating that introducing oats as a cover crop into the corn-soy rotation has the ability to achieve both positive environmental outcomes and economic returns, even in the absence of a strong market.
  2. LCA Harmonization for Pork, Corn, and Soy: Through the LCA harmonization, we discovered that common life cycle inventory databases lack key data that is directly representative of U.S. conditions. However, we developed a baseline database into which additional U.S.-specific information can be inserted in the future.
  3. Uncertainty and Sensitivity Analysis: The environmental impact did not change much across each of the nine cropping system scenarios. However, the inclusion of oats and clover in rotation with corn and soy proved most beneficial in terms of providing some reduction of environmental impact across our selected key performance indicators (GHG emissions, water quality/quantity, and carbon sequestration). The primary benefit of this rotation was substitution of synthetic nitrogen fertilizer by swine manure, further demonstrating the positive benefit of integrated crop and livestock systems.
  4. Economic Assessment: Conventional dryland no-till was the most profitable scenario over a six-year period, given time and fossil fuel savings, followed by conventional dryland minimum tillage, and conventional dryland standard tillage. The irrigated scenarios exhibited the highest average annual revenue per acre. Each of the oat scenarios generated a negative profit, largely due to the low selling point of oats per bushel. The corn/soy/oat rotation with conventional tillage drew the lowest profit of all scenarios tested. When accounting for subsidies, all scenarios increased in profitability, with buffer strips with conventional tillage showing the most dramatic increase in profit. Each of the four oats scenarios continued to demonstrate negative profit, even with subsidies. Generally speaking, profit was influenced primarily by four factors: machinery costs, specialty costs (buffer strips, irrigation infrastructure), crop revenues, and the oat rotation. Additionally, the high cash rents for our model country (Kossuth, IA) greatly impacted profitability. Conversely, each of the five hog scenarios was shown to be profitable.
  5. Ag Data & Precision Ag Technologies: There continues to be a lack of cohesive, interoperable data systems despite excessive funding of projects to get data to flow. More sincere public-private partnerships in the data space are needed to accelerate advancements in data integration and interoperability, particularly with respect to developing comprehensive public data sets that draw from data generated by precision ag technology.
  6. Economic and Environmental tradeoffs are real and thus demonstrate the need for models that integrate both types of results to inform more holistic conversations about the challenges and opportunities for farm-level sustainability. Adoption of practices with demonstrated environmental benefit can have serious economic implications for farmers and the industry. These tradeoffs need to be examined collectively to accurately assess sustainability impact.
  7. By the Numbers: Reviewed 181 peer-reviewed journals for environmental variables and 112 sources for economic variables; developed 14 alternative management scenarios (nine for corn and soy and five for swine) using the harmonized LCA; evaluated 10 sustainability calculators, 15 standards, 2 certification programs, and 24 national databases.