Multi-Criteria Decision Analysis for Optimizing CO2 and NH3 Removal by Scenedesmus dimorphus Photobioreactors

Abstract

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.