Conference Agenda

Wastewater treatment is estimated to account for 1-3% of a nation's total electric energy consumption, but anaerobic treatment of high strength wastewaters has the potential to be energy positive. A Modular Encapsulated Two-stage Anaerobic Biological (METAB) system has been proposed for distributed treatment of high strength food/beverage industry wastewaters and the production of hydrogen (H₂) and methane (CH₄). The METAB system also lowers COD loads to centralized wastewater treatment plants (WWTPs), directly reducing their operational costs and energy demand. A critical barrier in industry adoption of METAB systems lies in the identification of optimal contexts for deployment. The primary aim of the study is to evaluate the financial viability and environmental impacts of METAB systems in different deployment contexts. A series of contextual parameters – including the configuration of existing centralized WWTP, the high-strength wastewater composition, and local utility costs – were intentionally varied to represent the range of potential deployment scenarios for the METAB system. A benchmark centralized WWTP has been coded in QSDsan, and a broader portfolio of representative WWTP configurations (and sludge management strategies) are being coded to evaluate the implications of centralized wastewater management with and without up-stream treatment of the high-strength wastewater by the METAB system. Life cycle assessment (LCA) and techno-economic analysis (TEA) are being employed to characterize system sustainability indicators such as effluent quality, the levelized cost of wastewater management, and global warming potential (GWP).

Surveilling wastewater for hazards introduces information management as a supplementary objective when preserving, protecting, and providing our water resources. For example, treating waste as a source of information for pathogens, not for treatment optimization but for source identification, has increased our understanding of the community dynamics of SARS-CoV-2. However, public health surveillance places primary value on the information, whereas other social challenges surrounding the management of opportunistic pathogens (e.g., Legionella), control of antimicrobial resistance, and regulation of synthetic organisms (synbio) stand to benefit from the destruction of information. Therefore, waste and water policy actors develop unified monitoring and treatment strategies to prevent the escape of or invasion by these organisms. By being involved in the design and approval process for synbio organisms, policy actors can anticipate and prepare for risks emanating from biotechnology. With the need to predict the hazard of synbio organisms establishing in unanticipated environments, this talk will focus on presenting the capabilities of the new EcoGenoRisk framework. EcoGenoRisk utilizes the genome of the synbio organism to identify species susceptible to displacement and microbial communities at risk of invasion. A case study predicts where within the wastewater conveyance and treatment train a genetically modified Escherichia coli is likely to colonize, highlighting critical areas to monitor and manage within the collection system. Overall, our current surveillance approach supports public health monitoring but may be even more critical to adapt this framework to manage the ongoing revolution within the biotechnology industry, potentially preventing self-replicating bio-contaminants of emerging concern.

Wastewater collection infrastructure represents vast networks within our cities, and yet incidents such as accidental or malicious discharges of hazardous chemicals are typically only detected at the influent point of the treatment facility, or worse, only after the biological treatment process has been impacted. Having sensors distributed throughout the network would allow operators to respond proactively, but commercially available instruments capable of characterizing wastewaters to enable this are too costly for municipalities to install (and maintain) tens to hundreds throughout the network. In contrast, by reframing the problem to detecting anomalies against a statistical understanding of wastewater characteristics allows us to identify a reduced set of the most critical measurements, with the potential to vastly reduce the cost.

This work leverages data collected using a commercial absorbance spectrometer installed at the Upper Blackstone Clean Water facility (Worcester, MA) from August 2019 to December 2021 (total 111,354 measurements) and a database of 150 pollutant types (spectral shape and effect limit). From these, a large synthetic and balanced dataset of unpolluted, no-risk-polluted (concentration below effect limit), and dangerously polluted samples was created. Multiple machine learning approaches were considered to (1) classify samples into risk/no-risk (2) evaluate model hyperparameters and (3) evaluate value of each wavelength in achieving good classification accuracy. This presentation will discuss how this methodology can be used from real-world applications to data/modeling to sensor design and its implications in how these adaptive models might be applied in other fields.

Water resource recovery facilities are faced with stringent limitations for effluent phosphorus limits. Enhanced biological phosphorus removal (EBPR) is a process that helps meet the discharge limits and relies on polyphosphate accumulating organisms (PAO). Sidestream EBPR (S2EBPR) diverts a portion of Return Activated Sludge (RAS) flow to a longer Hydraulic Retention Time sidestream reactor that selects for PAO without relying on influent readily-biodegradable COD.

To meet most recent limits, the Wisconsin Rapids Wastewater Treatment Plant opted for a nutrient control process and resource recovery approach. During the testing period, a full-scale pilot test was carried out with a RAS fermenter. Key operational changes were performed to target a concentration at the P limit included the establishment of the RAS fermentation tank, increase of RAS diversion flow, halting of P-control chemical dosing and the addition of cranberry syrup waste as additional carbon source. Batch fermentation rate tests were completed and provided an indication of the amount of soluble biodegradable COD produced per mass of volatile solids in the fermenter. A model was developed to capture orthophosphate trends and predict microbial population shifts due to operational changes. The simulations showed that these changes impacted the enrichment of PAO. Cranberry syrup waste was successfully implemented and enhanced performance (90% TP removal). Additionally, the model indicated an average RAS apparent hydrolysis rate in range with the experimental findings. Overall, this study shows that joint strategies, including RAS diversion and carbon addition (cranberry syrup waste) can be effective to achieve optimal control of P effluent.

Wastewater-based epidemiology (WBE) has become a critical tool for assessing community level incidence of disease, such as COVID-19, around the world. While much of the progress on WBE has been focused on implementation in large population centers, rural communities present key challenges for the implementation of WBE, including high rates of onsite sewage treatment, limited wastewater treatment plant (WWTP) staff to support sample collection, and lack of availability of automated sampling equipment at WWTPs. Additionally, little consideration has been given to the impact of wet weather flows in combined sewer systems on the accuracy of WBE for predicting community disease. This presentation will address the following research objectives: (1) Evaluate sample collection methodology during dry vs. wet weather conditions in combined sewer systems and quantify the impact of stormwater dilution on accuracy of WBE metrics; (2) Assess sample collection locations to optimize population coverage in terms of geographic, socioeconomic, environmental justice, and healthcare access factors; and (3) Identify limitations and challenges for WBE associated with rurality and aging infrastructure in West Virginia. Results will describe hourly sampling at two WWTPs served by combined sewers during wet and dry weather conditions to assess changes in water quality and flow relative to SARS-CoV-2 markers and human fecal markers. Additionally, data will be presented summarizing the representativeness of WBE coverage in the state of West Virginia, comparing populations served by WBE vs. not served in terms of COVID-19 vulnerability, and a variety of other social and epidemiologic risk factors.