(693b) Modeling Spatial and Temporal Emissions for Animal Farming Using Mechanistic Models

Animal farming is an important sector for economy of several states in USA, however, has high contribution to GHG emissions and waste production as manure. One challenge of tracking emissions from this sector is heterogeneous nature of this sector with varied practices across small scale, large scale and integrated livestock-crop farming. This poses a unique challenge for waste management and also design of waste recycling facilities related to animal farming sector. Hence, there is a need to standardize and automate approach of estimating emissions and waste generation in animal farming sector. We address this challenge using a mechanistic modeling approach for animal growth combined with scaling factors representing scale of operations for farm selected.

We demonstrated here that modeling the production technique of any live animal-based industry is often challenging as the mass transformation process from feed intake to biological body mass growth is very complex. The body mass of animals can vary based on several factors such as quantity and type of nutrient feed, water intake, age, gender, climate and living conditions, etc. To tackle this challenge, we develop a computational model in Python to model the hog farming industry and demonstrated application in Illinois, USA.

The model uses different biomass growth equations for different hog age groups. The nutrient and water intake data were obtained from the United States Department of Agriculture (USDA) databases. The environmental impacts of the hog farming in Illinois were also quantified by integrating environmental impact assessment equations. Formulas derived by The Livestock Environmental Assessment and Performance (LEAP) program of the United Nation’s Food and Agriculture Organization were used to calculate the methane emissions of the farm using dynamics of animal growth. The model assumes that the hog farm uses a deep pit manure management system and the pit system collects 100% of the manure, therefore 100% of manure produced is treated by the system. The percentage of volatile solids was assumed to be 75.7% based on literature search. Further, we identify the location of animal farms modeled to show spatial and temporal variation of emissions as geospatial data.