Providing animal protein to tomorrow’s nine billion people will be a challenge given the associated environmental pressures with animal production, particularly issues such as greenhouse gas (GHG) emissions, human health and water usage/quality. Globally, livestock production systems contribute 14.5% to the total human-induced emissions of greenhouse gases (FAO, 2013). Animal feed is a major component of these impacts with the composition of animal diets having important downstream effects (i.e. GHG emissions, animal productivity, animal health, product safety and quality and animal welfare) as well as upstream effects on water quality, GHG emissions, land use and energy consumption (Makkar, 2016). Despite these effects, feeding programs for swine largely only focus on cost minimization and productivity (Dubeau et al. 2011; Pomar et al. 2007). Finding ways to produce animal protein while reducing the environmental impacts is vital to maintaining the long-term economic viability and cultural significance of this industry.
Pork, and the meat industry in general, has downstream pressure from customers to decrease environmental impacts. Major food companies have initiated supply chain management programs to minimize their carbon footprint in response to consumer demands and societal concerns. Within pork production, feed grains and manure management are the two largest contributors to GHG emissions, water use and land use (Matlock et al., 2014; Thoma et al., 2011). However, there is high variability in agricultural production systems and the associated environmental impacts across these locations (Yang and Heijung 2016; Hellweg and Canals, 2014). There is further variability across space due to the large differences in manure management practices, climate conditions and fuel mixes employed in U.S. counties and processing facilities. While research has been done on characterizing the average environmental impacts across the U.S. (Thoma et al 2011; Macleod et al 2013), and for particular production systems on a specific farm (or on average) (Bandekar et al 2014), this substantial variability across the U.S. can significantly affect specific supply chain environmental impacts.
What did we do?
The US pork industry is not a homogenous group of producers (in location, size, or even feed inputs) and therefore providing one single LCA number for the entire industry is incomplete. To capture this variability we used the Food Systems Sustainable Supply-chain model (FoodS3) that uses county level environment impacts of corn production, rather than using a single national average estimate. We also added spatial difference in manure impacts by estimating the volatile solids excreted in manure by the three regional feeding programs using county specific manure management practices. Using these estimates, we calculated the water and land use impacts of corn feed inputs in regional pig feeding programs, as well as the GHG impacts from corn feed inputs and manure emissions. We ran these calculations for four feed programs including: 1) the use of corn distillers dried grains with solubles (DDGS) and 2) dehydrated retail level food waste, as approaches for recycling nutrients back into pig feed; as well as 3) the use of synthetic amino acids (AA) and 4) enzymes (i.e. phytase), as back-end diet supplementation strategies for minimizing the environmental impact of pork production.
What have we learned?
The inclusion of county level spatial environmental impact data and supply chain connections are significant to this work. Location matters, not just in regional diet mixes, but also in environmental impacts of sourcing ingredients and manure management. With the FoodS3 model is was possible to bring in modeled supply relationships in environmental impact analysis. Similarly, having food waste data nutrient analyses available to test a food waste diet added in a hypothetical “future technology” for pig food that has not been extensively studied.
We found that using the food waste feeding program resulted in the lowest corn input greenhouse gas emissions totals compared with all other feeding programs evaluated in this study. However, for all GHG emissions, the control feeding program had the lowest GHG emissions. While use of synthetic amino acids decreased excretion of volatile solids in manure, it resulted in the greatest greenhouse gas emissions. These emissions are the result of proportionally greater use corn in the synthetic amino acid diets than any other diet (more corn was required to ensure that the diet met the Nutrient Requirement for Swine (NRC, 2012) in our modeled diets). The impact of feeding program on greenhouse gas emissions also varied among geographic regions, where the Mid-West region had the least per pig emissions regardless of the type of diets used in the feeding program. This variation is primarily due to the spatially different emissions of feed ingredients estimated with our FoodS3 model. As expected, water and land use were least for the feeding program based on food waste, while using synthetic amino acids in diets resulted in the greatest water and land use per pig produced.
While this study was an important step in bringing spatial heterogeneity to understanding the environmental impacts of pig diets, further work should consider diets with combinations of our alternative ingredients. Most commercially available pig diets already include synthetic AA and inorganic phosphorus (P), and many include DDGS. Furthermore, the diets may have regional variations in more than just corn and soy (which we accounted for), but also in some of our alternative ingredients, such as DDGS and food waste. Future research is needed to compare the environmental impacts of these diets to one that includes food waste as well as examine different rates of inclusion for food waste.
Jennifer Schmitt1*, Pedro Urriola2, Jae Cheol Jang3; Gerald Shurson4
1 Program Director and Lead Scientist, NorthStar Initiative for Sustainable Enterprise, Institute on the Environment, UMN firstname.lastname@example.org
2 Research Assistant Professor, Department of Animal Science, UMN
3 Post-doctoral Associate Department of Animal Science, UMN
4 Professor-Swine Nutrition, Department of Animal Science, UMN
* Corresponding Author
Bandekar, P. et al., 2014. Life cycle analysis of swine management practices. San Francisco, Proceedings of the 9th International Conference on Life Cycle Assessment in the Agri-Food Sector.
Dubeau, F., Julien, P.-O., & Pomar, C. (2011). Formulating diets for growing pigs: economic and environmental considerations. Annals of Operations Research, 190(1), 239–269. https://doi.org/10.1007/s10479-009-0633-1
FAO. (2013). Food Wastage Footprint: Impacts on Natural Resources—Summary Report. Rome. Retrieved from http://www.fao.org/docrep/018/i3347e/i3347e.pdf
Hellweg, S. & Canals, L., 2014. Emerging approaches, challenges and opportunities in life cycle assessment. Science, 344(6188), pp. 1109-1113.
Macleod, M. et al., 2013. Greenhouse gas emissions from pig and chicken supply chains – a global life cycle assessment, Rome: Food and Agriculture Organization of the United Nations.
Matlock, M., Greg Thoma, B., Eric Boles Mansoor Leh, P., Sandefur Rusty Bautista, H., & Rick Ulrich, P. (2014). A Life Cycle Analysis of Water Use in U.S. Pork Production Comprehensive Report.
Pomar, C., Dubeau, F., Létourneau-Montminy, M.-P., Boucher, C., & Julien, P.-O. (2007). Reducing phosphorus concentration in pig diets by adding an environmental objective to the traditional feed formulation algorithm. Livestock Science, 111(1), 16–27. https://doi.org/10.1016/j.livsci.2006.11.011
Thoma, G., Nutter, D., Ulrich, R., Charles, M., Frank, J., & East, C. (2011). National Life Cycle Carbon Footprint Study for Production of US Swine, 1–75.
Yang, Y. & Heijungs, R., 2016. A general computation structure for regional life-cycle assessment. International Journal of Life Cycle Assessment, pp. 1-9.
Funding, in part, was provided by the National Pork Checkoff.
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