Investigation of process changes and microbial community dynamics to improve Ammonia removal in rotating biological contactors treating domestic and industrial wastewater

Process changes, including installation of a flow splitter to equalize flow into two rotating biological contactors (RBCs) and an influent water pH adjustment, were implemented at a full-scale WWTF to improve ammonia removal. 16S rRNA amplicon sequencing and novel statistical methods were used to provide unique insight into the structure of microbial communities within the RBCs and their impact on ammonia removal before and after the process changes. RBC A met effluent ammonia targets throughout the study, while ammonia removal in RBC B improved after the process changes were initiated. The flow splitter was installed shortly before pH adjustments were made, and multiple linear regression analysis was used to isolate each process change to determine if the individual or the combined impact of these changes contributed to variations in ammonia removal. The flow splitter was primarily responsible for the improved ammonia removal, likely due to a decrease in flow into RBC B. The microbial communities were distinct between RBC A and RBC B, and while shifts in the microbial community occurred after flow equalization, these changes were minor and likely not the primary cause of increased ammonia removal. When treatment objectives are not met, utilities must respond quickly and often implement multiple process changes within a short time. Once treatment is optimized, it can be difficult to determine which process was primarily responsible for achieving effluent targets. This study highlights the role of advanced molecular tools and statistical techniques in identifying optimization strategies critical for improved treatment performance. • Multiple process changes for rotating biological contactors implemented concurrently • MLR found flow equalization was primarily responsible for improved ammonia removal • Introduction of novel statistical methods for microbial community analysis