Ex–ante LCA for circular resource management of liquid digestate, by predictive modeling of algae–bacterial processes

Abstract

The simplest method for treating liquid digestate, which involves directly spreading it over local agricultural land, is facing scrutiny due to the challenges of transporting large volumes and the environmental risks posed by nitrogen and phosphorus pollutants. Improvements in liquid digestate treatment are necessary to mitigate these threats and support a growing circular economy. This study evaluates an advanced digestate treatment method that decouples hydraulic retention time (HRT) and solid retention time (SRT) in high-rate algal/bacterial ponds (HRABPs). By combining life cycle assessment (LCA) with high-fidelity modeling for HRABPs, this study simulates productivity and removal efficiencies under realistic climatological conditions, providing life cycle inventories for numerous large-scale scenarios. To minimize environmental impacts while maximizing algal productivity and nitrogen intake in the algal biomass, 36 scenarios were simulated, considering different HRT, SRT, alkalinity addition, winter storage, and biomass post-treatment hypotheses. The results demonstrate that microalgae treatment makes sense for valorizing liquid digestate, proving to be less impactful than direct land application. However, the LCA results also highlight the complexity of the issue. Low HRT (HRT = 5 days < SRT = 10 days), including winter storage, requires the smallest production area, resulting in high productivity and low environmental impacts. Conversely, high HRT (HRT = 90 days > > SRT = 15 days) achieves the highest efficiency in nitrogen and phosphorus recycling but necessitates large production areas, leading to high environmental impacts. Mathematical modeling, coupled with LCA, can resolve these trade-offs and guide the optimization and scaling-up of climatology-dependent systems.