Life Cycle Assessment Approach for Energy Usage in Animal Rendering Plants

The animal rendering industry plays a crucial role in transforming waste products from livestock production and meat processing facilities into valuable and economically beneficial products, promoting both resource efficiency and sustainability. This study uses a life cycle assessment (LCA) approach to evaluate energy usage and greenhouse gas emissions in animal rendering plants, focusing on electricity and natural gas as the main energy inputs for plant operation. This research examines three distinct rendering facilities, each processing different raw materials, to quantify the environmental impacts of rendering operations. Site visits, data collection, and real-time monitoring were used to capture energy use across key unit processes, such as cooking, milling, fat separation, odor control, and wastewater treatment. The findings indicate significant energy consumption in cooking and fat separation processes, primarily fueled by natural gas and electricity. The main cooking processes use almost all the natural gas at the rendering facilities. The allocation of electricity usage for unit operations varied among the three rendering plants studied. CO2 emissions from these processes contribute substantially to the carbon footprint, with Scope 1 and Scope 2 emissions quantified for each facility. Additionally, the study incorporates an upgraded carbon footprinting tool based on a previous model developed by Gooding (2012), allowing for the quantification of carbon emissions based on the raw material and production data for a rendering plant. Recommendations are provided for energy-saving opportunities, such as integrating renewable energy (e.g., biomass, solar) and implementing real-time data loggers to optimize operational efficiency. The study underscores the need for targeted strategies to reduce energy use and emissions in rendering plants, positioning these facilities for enhanced sustainability in the face of growing environmental regulations. This analysis serves as a foundational resource for future research and provides actionable insights for other rendering plants aiming to improve their environmental performance.