Quantifying the log reduction of pathogenic microorganisms by constructed wetlands: A review

Over the last 30 years, constructed wetlands (CWs) have been used as an alternative, cost-efficient way of treating wastewater, mainly in combination with conventional wastewater technologies. When CWs are attached at the end of conventional wastewater treatment plants, they adequately remove pollutants and thus provide a polishing step. However, recent studies have shown that when CWs are used as a main wastewater treatment method for agricultural reuse of effluents, they perform poorly on meeting the accepted limit of microbial contamination. Moreover, CWs are increasingly used within the scope of circular economy and water reuse applications. Therefore, there is a need for a comprehensive exploration of the performance of CWs on pathogen removal. This paper explores relevant case studies regarding pathogen removal from constructed wetlands in order to create a comprehensive dataset that provides a complete overview of CWs performance under various conditions. After performing a systematic literature review, a total of 48 case studies qualified for both qualitative and quantitative analyses. From the dataset, the general performance, optimal conditions, and knowledge gaps were identified. The review confirmed what was already known, that constructed wetlands (as a standalone treatment) cannot meet the accepted limits of pathogen removal. However, they can be a credible choice for wastewater polishing when they are combined with conventional wastewater treatment systems. Regarding the most common indicators that were recorded, the removal of Escherichia coli ranged between 0.01-5.6 log, the removal of total and fecal coliforms was 0.2-5.32 and 0.07-6.08 log respectively while the removal of fecal streptococci was 0.2-5.2 log. The great variability on pathogen removal indicates that the complexity of CWs makes it difficult to draw robust conclusions regarding their removal efficiency. Moreover, the inadequate reporting of extractable data and CW conditions (except hydraulic characteristics) in the reviewed papers, made it difficult to validate any relationship between CW performance and external parameters. However, the spatial distribution of case studies in the climatic zones around the world indicated a potential statistical correlation between temperature and removal of pathogens. Finally, the dataset can be used as a benchmark of CWs performance as a barrier against the spreading of pathogens in the environment. The knowledge gaps identified in this review can provide direction for further research. A potential meta-analysis of the dataset using statistical analysis can pave the way for a better understanding of the design and operational parameters of CWs in order to fine-tune and quantify the factors that influence the performance of these systems.