A systematic decision-making framework for selecting nitrous oxide quantification methods in water utilities

Abstract

With the growing emphasis on reducing nitrous oxide (N<inf>2</inf>O) emissions in the wastewater treatment sector, an increasing number of water utilities are keen to quantify the actual N<inf>2</inf>O emissions from sewage treatment plants. Two main unit-based quantification methods are the liquid N<inf>2</inf>O sensor-based method and the gas flux hood-based method, both of which allow for real-time measurement at specific monitoring locations. Despite their widespread use, there is no clear, evidence-based framework to help utilities choose the most suitable method for their specific needs. This study addresses this gap by developing a systematic decision-making framework that considers the impact of key factors, including plant covering (fully covered or open surface), aeration type (diffused aeration or surface aerator), configurations (number of monitoring locations), monitoring duration, cost and technical difficulties etc. The framework incorporates a comprehensive multi-criteria evaluation to balance five essential criteria, including equipment cost, consumable cost, commissioning, maintenance and complexity in data analysis. Results indicate that the liquid-based method is more suitable for scenarios with fewer monitoring locations and shorter durations. In contrast, the gas-based method proves more advantageous in scenarios requiring high monitoring intensity. For intermediate-intensity scenarios, the likelihood of selecting gas-based method increases with monitoring intensity, with the decision being highly dependent on the weighting assigned to the factors. The findings also highlight the importance of determining the weights of criteria and scores based on specific operational needs, available resources, and technical capacity prior to multi-criteria evaluation process, which may vary the evaluation results accordingly. This framework provides utilities with a practical tool to optimize N<inf>2</inf>O monitoring strategies and support emission reduction.