Energy saving anammox technology-based nitrogen removal and bioenergy recovery from wastewater: Inhibition mechanisms, state-of-the-art control strategies, and prospects

The intensification of anaerobic ammonium oxidation (anammox) research immediately after its discovery in 1995 can largely be attributed to its low sludge production and aeration requirements, making it an economically energy efficient and eco-friendly technology with high potential for bioenergy recovery. However, anammox activity could be inhibited in waste streams containing highly variable compounds, such as free ammonia (FA), dissolved oxygen (DO), nitrite (NO2-), toxic and non-toxic organic matter (OM), salts, heavy metals, sulfide, and phosphate. Moreover, the long start-up period of anammox consortia is the main drawback of the process. Hence, careful control and mitigation of inhibiting factors is important for the successful use of this technology. This review provides a comprehensive understanding of the inhibition mechanism, threshold concentrations, and control strategies involved in ensuring the proper functioning of the anammox system. Knowledge and rule based state-of-the-art control strategies have been proposed, which will lead to successful operation and maintenance of anammox-based systems. These strategies will act as guidelines for the operators to address system irregularities at the earliest, thus preventing serious damage to the overall functioning of the system. Finally, key bottlenecks and innovative prospects that require attention, in order to achieve practicality and universal use of anammox-based technologies are highlighted.

Automated summary

The anammox technology is highly regarded for its low sludge production and energy efficiency, but faces challenges in dealing with inhibiting factors in waste streams. Detailed control and mitigation of these factors are crucial for successful implementation of the technology. Developing and implementing control strategies are key to addressing inhibiting factors and ensuring optimal performance.