Community Structure and Function During Periods of High Performance and System Upset in a Full-Scale Mixed Microalgal Wastewater Resource Recovery Facility

Abstract

Microalgae have the potential to exceed current nutrient recovery limits from wastewater, enabling water resource recovery facilities (WRRFs) to achieve increasingly stringent effluent permits. The use of photobioreactors (PBRs) and the separation of hydraulic retention and solids residence time (HRT/SRT) further enables increased biomass in a reduced physical footprint while allowing operational parameters (e.g., SRT) to select for desired functional communities. However, as algal technology transitions to full-scale, there is a need to understand the effect of operational and environmental parameters on complex microbial dynamics among mixotrophic microalgae, bacterial groups, and pests (i.e., grazers and pathogens) and to implement robust process controls for stable long-term performance. Here, we examine the first full-scale, intensive WRRF utilizing mixed microalgal for tertiary treatment in the US (EcoRecover, Clearas Water Recovery Inc.) during a nine-month monitoring campaign. We investigated the temporal variations in microbial community structure (18S and 16S rRNA genes), which revealed that stable system performance of the EcoRecover system was marked by a low-diversity microalgal community (DINVSIMPSON = 2.01) dominated by Scenedesmus sp. (MRA = 55%-80%) that achieved strict nutrient removal (effluent TP < 0.04 mg.L-1) and steady biomass production (TSSmonthly avg. = 400-700 mg.L-1). Operational variables including pH, alkalinity, and influent ammonium (NH4+), correlated positively (p < 0.05, method = Spearman) with algal community during stable performance. Further, the use of these parameters as operational controls along with N/P loading and SRT allowed for system recovery following upset events. Importantly, the presence or absence of bacterial nitrification did not directly impact algal system performance and overall nutrient recovery, but partial nitrification (potentially resulting from NO2- accumulation) inhibited algal growth and should be considered during long-term operation. The microalgal communities were also adversely affected by zooplankton grazers (ciliates, rotifers) and fungal parasites (Aphelidium), particularly during periods of upset when algal cultures were experiencing culture turnover or stress conditions (e.g., nitrogen limitation, elevated temperature). Overall, the active management of system operation in order to maintain healthy algal cultures and high biomass productivity can result in significant periods (>4 months) of stable system performance that achieve robust nutrient recovery, even in winter months in northern latitudes (WI, USA).

Introducing ARTiMiS: A low-cost flow imaging microscope for phytoplankton monitoring in engineered and natural environments

“…To test ARTiMiS’ potential to monitor more complex microalgal communities, we used ARTiMiS to image samples from the EcoRecover wastewater nutrient recovery system, a full-scale microalgae-based nutrient removal process in the Village of Roberts, Wisconsin, USA 23 . Through a combination of direct observation and referencing of 18S rRNA gene sequencing 33 , the dominant taxonomic groups present in the EcoRecover microalgal community were identified and libraries comprising representative images of each group were annotated. Three clades of Chlorophyta were found to dominate the system at different times of the year: multiple members of the Scenedesmaceae family, one or several species of Chlorella , and two or more species of Monoraphidium .…”

Intensive Microalgal Cultivation and Tertiary Phosphorus Recovery from Wastewaters via the EcoRecover Process

“…Additionally, when compared to a variable performance period (February 15, 2023 to April 28, 2023) immediately following the focus period, eukaryotic communities in these two periods showed significantly different clusters ( p < 0.01, AMOVA) as illustrated by ellipses encompassing 95% of cluster assigned data points (Figure S10). Full, longer-term sequencing results and more in-depth community structure analyses are the focus of a separate study …”

“…Periods of process upset or variable performance were often characterized by variable or basic pH, loss of DO diel rhythm (e.g., as seen in November 2022, Figure S11), and at times included insufficient alkalinity and solid composition changes. Additional details of process upsets are provided in Section S6 of the SI, and two specific examples are discussed in detail by Alam and colleagues for a separate study period (November 2021 through August 2022) …”

“…Full, longer-term sequencing results and more in-depth community structure analyses are the focus of a separate study. 60 …”

“…Periods of process upset or variable performance were defined as periods of prolonged or intermittent exceedance of the 0.04 mg-P·L –1 effluent target, respectively. Although not the focus of this study, the system was susceptible to process upsets driven by upstream changes to the wastewater treatment process (e.g., reduction in SBR settling time that resulted in TSS concentrations >100 mg-TSS·L –1 entering the EcoRecover process), high influent concentrations of a disinfectant (quaternary ammonium), and biological drivers (including grazers 60 ). Periods of process upset or variable performance were often characterized by variable or basic pH, loss of DO diel rhythm (e.g., as seen in November 2022, Figure S11 ), and at times included insufficient alkalinity and solid composition changes.…”