An evaluation of anaerobic co-digestion implementation on New York State dairy farms using an environmental and economic life-cycle framework

Abstract

Anaerobic digestion systems on dairy farms in New York State rely on gate-fee revenues from co-digestion to ensure economic viability. Yet, because gate fees are paid on a volumetric (or weight) basis, farmers have been compelled to accept large waste volumes. When these wastes are co-digested at rates exceeding the design capacity of the digester, potentially significant technical, environmental, and economic consequences may arise. To better understand these trade-offs, we performed a combined environmental life-cycle and economic assessment with uncertainty analysis. We used the Anaerobic Digestion Model #1 to simulate the co-digestion process for 10 potential co-substrates that were hypothetically mixed with dairy manure throughout a range of loading rates. These simulation results demonstrated the need to include a robust anaerobic digestion model to capture complex process dynamics and loading limits. Results also showed that while higher loading rates were more economically favorable, they caused considerable reductions in the degree of waste stabilization during the digestion process, which dramatically increased downstream methane emissions (e.g., >450%) on the farm compared to manure-only digestion. Regardless, most co-digestion scenarios led to a net reduction in total life-cycle emissions compared to manure only and not digesting the co-substrate due mainly to greater electric power production and synthetic fertilizer replacement. Economically, gate-fee revenue was the most important contributor to profitability, substantially outweighing the revenue from electric power production, while also compensating for the increased handling costs of the added waste volume. Ultimately, the model clearly demonstrated the important environmental and economic implications arising from current anaerobic digestion implementation practices and policy in New York State. In addition, the model highlighted key stages in the system life-cycle, which was used to instruct and recommend immediately actionable policy changes.