Find in Library

Numerous technologies have been investigated for mitigating air pollutant emissions from swine barns. Among them, algal photobioreactors (PBRs) can remove and utilize air pollutants such as CO₂ and NH₃ from barn exhaust. However, a challenge to PBR operation is that it involves multiple system input parameters and output goals. A key question is then how to determine the appropriate CO₂ and NH₃ concentrations in this case. Conventional statistical methods are inadequate for handling this complex problem. Multi-criteria decision-making (MCDM) emerges as a practical methodology for comparison and can be utilized to rank different CO₂–NH₃ interactions based on their environmental and biological performance. By employing MCDM methods, producers can effectively control the ratio of CO₂ and NH₃ concentrations, enabling them to identify the optimal range of operating parameters for various housing types, ensuring efficient pollutant mitigation. In this study, a multi-criteria decision-making (MCDM) approach was employed to support operation management. Specifically, influent CO₂ and NH₃ concentrations were optimized for three scenarios (the best biological, environmental, and overall performance), using a combination of two MCDM techniques. This study is anticipated to facilitate the system analysis and optimization of algae-based phytoremediation processes.