Conference Papers

The City of Kalamazoo has, over several years, been implementing a programme of works to improve odor management performance. This programme has included upgrades to the design of the sewer network, the establishment of an Odor Task Force with representatives of the City, local industry, elected officials, regulators and community groups, and the implementation of continuous monitoring focused on odor impacts. To complement this programme, the City piloted the creation of a digital twin of the network to support the identification and mitigation strategies for odor (in addition to corrosion and safety risks associated with hydrogen sulfide and methane). This case study explores the application of the SeweX product at the Davis Creek catchment in the City of Kalamazoo. SeweX was undergoing transformation from a deterministic model usually applied through a consulting approach, to a commercial software product. This case study reviews the process of collaboration between vendor and the City and the progress towards implementation of its digital strategy. The project included: - Configuration of a sulfide and methane model. - Calibration of the model with wastewater quality and gas measurements. - Visualisation of high risk areas across the network. - Assessment of alternative operating scenarios including chemical dosing and ventilation. - Training. - Review by key project stakeholders for suitability as a tool for ongoing use. Assessment of value of the product for wider rollout. ...Critical Success Factors The critical success factors for this project were: - Model accuracy to a level of accuracy that could be used for decision making across the network. - Ease of use — Model setup should be possible by non-subject matter experts. Results should be accessible and understood by the key users of the information for making decisions regarding capital allocation. - Scaleability — The solution should be able to be used in other networks with similar levels of available information and be able to be integrated into current work practices. ...Lessons Learned Initial results showed good agreement between measured and modelled results for H2S gas at Davis Creek in both the range of concentrations and variation of concentration across the day. The key lessons learned included: - Engaging with a complex modelling product of this nature at its stage of maturity provided an opportunity to positively influence product design and rapid product improvement. Flexibility from both vendor and customer was needed. - Organisational champions are critical to both develop and deliver the strategy in a large and diverse organisation with many stakeholders in the management of odor, corrosion and safety. - As an organisation-wide, accessible model for sewer network corrosion, odor and safety was a very new concept, intensive internal stakeholder engagement was needed identify the best approaches for integrating the solution for the longer term. Adapting to feedback throughout the process, especially monitoring requirements, was important. Taking time to understand the needs of different functions and individuals within the business and how this initiative best supported those needs was a valuable exercise. ...Outcomes This case study shares the key results and outcomes from the analysis of potential improvements to odor, corrosion and safety managements at the two catchments, which considered changes to chemical dosing strategy, ventilation and/or hydraulic properties in the network. Progress towards organisational objectives of improved decision making related to odor, corrosion and safety management in sewer networks was also reviewed.

The Southwest Florida Water Management District (SWFWMD) began the watershed initiative program to provide comprehensive understanding of watersheds. The Withlacoochee Watershed Initiative delved into providing an understanding of the complexities of the Withlacoochee River and utilizing a modeling approach which uncovered many of the longstanding uncertainties surrounding the river. The Withlacoochee is a unique riverine system, winding 160 miles northward through eight Central Florida counties before eventually discharging into the Gulf of Mexico. The Withlacoochee River was called by its earliest inhabitants 'We-Thalko-Chee' or 'Little Big Water', characterizing the great fluctuations between drought and flood that are commonly exhibited by the river due to naturally changing hydrologic conditions. This complex system covering over 2000 square miles was one of the least understood in the region and yet because of its beauty, drew homeowners flocking to its banks. While alterations over the past 130 years have attempted to control this natural wonder to suit commercial navigation, industry, and private needs, the river continues to plot its own course. True to its name, homeowners on the Withlacoochee have experienced extreme drought followed by lasting floods, exemplified in Figure 1. In recent decades, public meetings and workshops involving stakeholders, special interest groups and residents identified several critical issues and ideas to either restore or further alter portions of the system. To comprehensively address those concerns, a first of its kind computer model of the entire Withlacoochee River and its surrounding watershed was developed. This included an unprecedented effort to map the entire bottom of the Withlacoochee River from the Green Swamp to the Gulf of Mexico and calibrating the model to the devastating 2004 Hurricane Season.

METHODOLOGY
To address the unique characteristics of the river and watershed, a comprehensive model was developed using the Interconnected Channel and Pond Routing software version 4 (ICPRv4) created by streamline technologies in Orlando, Florida. This computer model can simulate one-dimensional flow in channels as well as two-dimensional flow in wetlands and marsh areas, both of which are prevalent throughout the Withlacoochee River watershed. This flexibility was necessary to account for the river conditions which were alternatively a wide expansive marsh transitioning to a deeply channelized river section. High resolution LiDAR data supplemented with field work was used to characterize the hydraulic parameters in the watershed, exemplified in Figure 2. This detailed data combine with automated techniques for understanding and delineating the watershed boundaries served to guide the model development process. Additionally, the model was able to account for the volume and timing of contributing inflows from the surrounding watershed using dynamic rainfall inputs and varying initial water levels. This was a critical element since water levels and flow along the river are a direct result of spatially varied rainfall and the watershed's antecedent conditions. In the low condition, water is contained within the main channel and rainfall on the surrounding land will infiltrate prior to contributing flows to the river. In the high condition, water levels are higher and the surrounding land is inundated. Subsequently, when rainfall occurs, runoff immediately causes river levels to rise and flows to increase, since the watershed's soils are already saturated. Because the ICPRv4 model simulates hydrology and hydraulic conditions in parallel, these dynamic changes in soil moisture can be accurately simulated.

RESULTS
Calibration The river model was calibrated to over 20 USGS gauging stations over a three month period in 2004, which started in drought conditions until three hurricanes crisscrossed the watershed, sustaining flooding conditions for months. Despite the numerous calibration parameters available in ICPRv4, initial model results would not converge to the measured data. This prompted additional field work and ground truthing of model assumptions. During this process, it was learned that significant portions of the terrain, particularly in marsh area incorrectly depicted ground conditions. It was learned that the model was highly sensitive to storage and overland flow roughness within 2D zones. Correcting the terrain lead to a more accurate flow regime and ultimately a calibrated model. Resulting hydrograph depicting the rise in water level between modeled and measured data is seen in Figure 3. The model accurately depicted the more than two week lag time between headwater and discharge into the Gulf of Mexico. As seen in the graph, following each hurricane, water conditions sharply rise, yet do not fall quickly, rather remain high, setting an inundated condition subsequent storm events. In this watershed, the reality of highly variable initial conditions became a key feature in understanding flood levels throughout the watershed and inflow tributaries. Scenarios Working with SWFWMD staff and stakeholders throughout the watershed, both past and present concerns were documented, ultimately resulting in 19 scenarios as shown in Figure 4. These scenarios are designed to determine what effect historical or future changes might have on water levels and flows throughout the entire river and watershed. Results indicated how management strategies can optimize the balance between retaining water high for recreation, while being able to evacuate it prior to catastrophic events. Results indicated which river alterations would have had a positive impact on flooding conditions during the hurricane events, and which would not.

CONCLUSION AND DISCUSSION
In the initial phases of the project, the public was skeptical of the overall process, accusing the water management district of mismanagement of the resource and being the cause of both extended drought conditions, as well as, the prolonged flooding conditions. Through a series of public meetings, transparency of the modeling approach, and ultimately demonstrating that the calibrated model would accurately predict conditions in the watershed, a trust was built with these concerned citizens. This trust extended to the results of the 19 model scenarios including those demonstrating existing water management procedures and simulations demonstrating proposed alterations to those procedures. The modeling effort and the project itself are a first of its kind floodplain mapping using a 2D model and providing an understanding of a complex river system. But what makes this project truly unique is its ability to transcend the algorithms and modeling complexities and connect with the public. This calibrated model and this project was able to heal the wound of an irate public skeptical of the water management district practices. These results now serve as the best available data in the region and the model approach for large watershed studies in the Water Management District.

Background: Wastewater surveillance is an important and emergent public health tool that relies on robust infrastructure to work well including accessible wastewater sampling points, detailed information on sewer system service areas, and trained personnel. Wastewater treatment plants are perhaps the most convenient wastewater sampling points, as they already sample wastewater as part of their environmental safety requirements. To evaluate the capability of treatment plants of different sizes and characteristics to participate in surveillance efforts, we developed and distributed a survey to New York State treatment plant supervisors in the summer and fall of 2021. The goal of the survey is to assess the knowledge, capability, and attitudes toward wastewater surveillance as a public health tool. Objectives: Our objectives are twofold. First, we want to determine what data treatment plants have about their service areas and in what form including physical maps, geospatial information systems (GIS) data, and address lists. Knowledge of the service area (sewershed) is essential for linking wastewater surveillance data back to upstream populations. The second objective is a broader questionnaire to identify the capability and limitations to conduct surveillance across treatment plants of different sizes and in different communities from urban to more rural settings. This second objective also included an evaluation of the knowledge and attitudes that treatment plant supervisors have regarding wastewater surveillance to inform what kind of education and outreach efforts public health departments may have to engage in. Methods: A population of treatment plants was identified using New York State Department of Environmental Conservation information on municipal treatment plant locations. Contact information was obtained from state and regional offices. Of the 638 treatment plants identified, contact information was available for 377 of them. The plants were contacted between July and September of 2021 by email and phone to complete a survey asking about what data they have on their treatment plant service area and what they know about wastewater surveillance. A total of 93 treatment plants participated in the survey representing a 25% response rate and accounting for nearly 15% of all the municipal plants in the state. Summaries of responses were calculated as well as statistical comparisons between plants of different sizes. Results: Data on service areas is not universal with 23% of respondents reporting no data on their service areas. Regarding knowledge of surveillance for public health, 84% of respondents know that wastewater samples can track COVID-19 but only 51% are aware that it can also be used to track opioids. In addition, 39% of respondents agree that wastewater surveillance could be beneficial with their community with most respondents (44%) indicating they are unsure or have no opinion. We find high capacity for treatment plants to collect 24-hour composite samples with 69% of all treatment plants reporting ability to take at least one sample per week. Of the responses, 90% of larger plants surveyed (> 2 mg/d of flow) indicate ability to take one sample per week or more with 55% of smaller plants (< 2mg/d of flow) indicating the same ability. For grab samples, the capability is similar with 67% of respondents indicating ability to take samples at least once per week. For larger plants, 81% of respondents indicate ability to take grab samples at least once per week while 58% of smaller plants indicate the same ability. Discussion: Results suggest diverse capabilities across sewer systems with differences between treatment plants by size. Knowledge about surveillance is also mixed with most supervisors knowing that COVID-19 can be tested in wastewater but having less knowledge about surveillance capabilities for other things like opioids. Findings provide guidance for outreach activities with results suggesting education and communication with treatment plant personnel would be beneficial to increase awareness of what surveillance can do to benefit public health. Results also provide important insight into treatment plant capabilities as they are connected to internal factors such as size, which may help public health departments understand the limitations and ability of future participation. Overall, we find that most treatment plants in New York State, regardless of size, report ability to conduct surveillance at least once per week suggesting that statewide scaleup of surveillance programs could occur with most treatment plants simply needing the knowledge and guidance on what to surveil. Next steps include evaluation for additional patterns across population levels and urban v. rural dynamics to better aid health departments in targeting resources for training, education, and equipment.

SUMMARY Using smart technology to improve asset management has become an essential part of managing wastewater collection systems, especially for aging systems with little to no historical data. As an Investor-Owned Utility (IOU), New Jersey American Water has a mixture of wastewater systems with different topographies, sewer pipe ages, and other physical challenges. Performance data is critical to understanding both the (daily) operational and longer-term investment needs for the collection systems. New Jersey American Water started its first (pilot) deployment of sewer monitoring technology in Lakewood in June 2020, using SmartCover© satellite-based sensors. The pilot was successful in reducing the number of annual SSO events from 12 to zero, and the monitoring platform provided valuable data for estimating levels of inflow and infiltration (I&I). The sewer monitoring program was expanded over the following 2 years, and there are now over 160 units deployed across 7 wastewater systems. New Jersey American Water uses the SmartCover© monitoring platform to accelerate the evaluation of new acquisitions, including rapid identification of critical I&I targets. INTRODUCTION — A GROWING NETWORK OF WASTEWATER SYSTEMS New Jersey American Water is the largest water service provider in the state of New Jersey, serving approximately 2.8 million people in 190 communities. New Jersey American Water currently owns and/or operates 30 wastewater systems with 21 wastewater treatment plants, 85 lift stations, and over 500 miles of pipe. Over the last five years, New Jersey American Water has invested over $105 million into wastewater system assets, including wastewater mains, treatment plants and lift stations, to continue to provide reliable and environmentally sound service that complies with federal and state wastewater environmental regulations. THE CHALLENGE — IMPROVING WASTEWATER SYSTEM INTELLIGENCE In efforts to minimize health and environmental challenges, New Jersey American Water works to identify and eliminate potential weaknesses in each collection system: -Sanitary Sewer Overflows (SSOs) -Inflow (stormwater) that rapidly flows into sewer mains due to faulty drains, connections, and manhole covers -Infiltration (groundwater) that seeps into the sewer system due to aging pipelines -Aging pipelines that are blocked, cracked, or broken -Potential system power failures -Insufficient system capacity -Blockages caused by customer usage While New Jersey is the 5th smallest state, it contains 4 different physiographic regions that includes coastal plains, mountains, and regions of dense forests and small rivers. This creates a set of challenges that differ across the following 7 wastewater systems owned by New Jersey American Water: 1.Bound Brook: Total lack of historic records 2.Egg Harbor City: Older system, with flat topography with pump stations and tidal influences (high ground water table) 3.Haddonfield: Major I&I issues, suburb of an older major NJ City (Camden) 4.Lakewood: First site to deploy sewer monitoring, system suffers from high population and undersized pipes 5.Long Hill Township: Hilly terrain, no additional connections permitted (self-imposed sewer bans), and wet weather flows increase treatment needs from 1 to 4 MGD. 6.Ocean City: Older system, surrounded by water, and prone to flooding (tidal) 7.Somerville: A recent acquisition with known SSO issues and a wet weather facility being built downstream by the County THE SOLUTION: SMART SEWER MONITORING TECHNOLOGY New Jersey American Water's operations and engineering teams work collaboratively to develop comprehensive capital investment plans and preventive maintenance processes. The utility's Comprehensive Planning (CP) process is used for both new acquisitions and existing systems. The team was searching for a technology to enable targeted analysis on their sewer mains, providing real-time data and alarming to avert sanitary sewer overflows, backups, and subsequent cleanup. The technology also needed to provide valuable data for I&I analysis to make quicker, informed capital investment decisions. New Jersey American Water chose the SmartCover© platform for a pilot in its Lakewood NJ system in 2020. The monitoring units provide real-time, low-cost level/flow data, and provide real-time alarms to dispatch crews before overflows occur. This eliminates both the environmental and community impacts associated with SSOs. The technology also incorporates both National Oceanic and Atmospheric Administration (NOAA) weather (doppler radar) as well as United States Geological Survey (USGS) river/stream and ocean gauges. The platform enabled New Jersey American Water to understand the impact of extreme weather events across the entire Lakewood sewer shed, enabling more efficient use of capital by focusing on high-impact I&I areas as well as undersized pipe bottlenecks. THE PROOF: PINPOINTING HOTSPOTS LEADS TO IMMEDIATE ROI Large amounts of data are collected and analyzed daily, helping New Jersey American Water pinpoint problem areas in its 7 largest sewer systems. Critical repairs and targeted investigations, e.g., smoke/dye testing, are driven by SmartCover©. The sensors are now integrated with American Water's MapCall system, enabling operations team members an easy path to alarm management and work order management for field issues. In addition to preventing SSO events and identifying problematic areas in their sewer systems, the smart sewer technology has allowed the utility to better allocate resources for system maintenance, including: -Improved visibility allows site cleaning to be performed based on real-time trends -Personnel and equipment redirected to other projects delivers gains in productivity -Continuous monitoring between cleanings enables SSO protection and risk reduction -Less time in roadways results in crew safety -Fewer cleanings reduce pipe and structural wear to extend asset life The sewer technology has allowed New Jersey American Water to perform targeted analysis on their sewers, providing real-time data and alarming to avert sanitary sewer overflows, backups, and subsequent cleanup. Most important, the units are providing valuable data for I&I analysis to make quicker, informed capital investment decisions. It is a key tool in the utility's toolkit for collection system maintenance and replacements.

Environmental surveillance through wastewater monitoring has been implemented for a long time for poliovirus and antimicrobial resistance. Different principles for sampling and sample processing have been used in the past and sufficient comparative data have not been published to unequivocally prove that there is an advantage of any one principle over the others for detection of low-level poliovirus circulation in human populations. Most studies published to date on the use of environmental surveillance for SARS-CoV-2 have been from high-resource settings. However, approaches are needed that can be applied in lower-resource settings, where a greater proportion of the population is not connected to sewers and instead uses pit toilets or septic tanks. Possibilities include testing surface water contaminated by sewage. Several scientific teams around the world have begun to investigate the course of the virus in the population through epidemiology of sewage. The Netherlands, Australia and France were among the first to suggest that. According to these studies, the SARS-CoV-2 genome was detected in untreated wastewater at concentrations over 106 copies per liter, while in the corresponding study that carried out in France, in treated wastewater samples, the corresponding concentration of the viral genome was up to nearly 105 copies per liter (Wurtzer et al., 2020). However, more research is needed on the use of computational models to estimate the viral particles each person secretes at a time and how they are diluted in the drains to match the actual number of infected individuals. Here, we describe the implementation of the environmental surveillance for COVID-19 during the 2nd pandemic wave and seek to refine and streamline a protocol that could be applied in medium-sized urban settings during medium-sized outbreaks. 2. Materials & Methods 2.1. Sampling Network and Procedure The wastewater treatment plant was the reference sampling point for the whole city. Moreover, and in collaboration with the Water and Sanitation Department of Ioannina City (DEYAI), we identified sampling spots on the urban matrix that corresponded to specific well-defined urban regions of varying population density and covering the entire city. Finally, we also identified transmission and morbidity hotspots as follows: hospitals, nursing homes, hospices, and refugee camps. A surveillance map was constructed. For the WW treatment plant, WW was subsampled from 24-hour composites of total plant influent collected by WW treatment plant personnel. Subsamples consisted of 1lt drawn from daily 24-hour total plant intake composites using a WaterSam WS Porti 1, Portable Water Sampler. Samples were routinely collected once per week from April 2020 to November 2020 corresponding to the period before and during the COVID-19 city outbreak related to the second wave of the pandemic. For the sentinels, early-morning (7am-11am) grab 1-lt sampling was performed once weekly. We opted for early morning sampling since defecation in the general population is most frequent in the early morning (Heaton KW et al, 1992) and thus higher viral shedding was more probable. The samples were placed in an isothermal container with ice, transported to the laboratory into approximately 2 hours and stored at 4oC until further analysis. 2.2. Sample Pre-treatment & Viral Precipitation Before the treatment of the samples, the physicochemical parameters, mainly pH, conductivity, and UV254nm absorption were measured. The samples were pre-treated with the Skimmed Milk Flocculation method before isolating the viral genome to increase the chances of detecting SARS-CoV-2 RNA in wastewater (Calgua B. Et al. 2008). The Skimmed Milk Flocculation method is based on the absorption of the viruses to the flocks of skimmed milk. After sample analysis and pre-treatment, the viral RNA and DNA isolation kit (NucleoSpin Microbial DNA, Macherey-Nagel) was used according to the manufacturer's instructions. Following extraction of the viral genome, the extracted samples were measured in NanoDrop 2000 / 2000c Spectrophotometers (Thermo Scientific) to record their purity as well as the concentration of the viral nucleic acids. 2.3. RNA Extraction & RT-qPCR analysis The molecular detection of SARS-CoV-2 was performed using a commercially available RT-qPCR assay (Viasure SARS-CoV-2 Real Time PCR Detection Kit). The assay is based on the amplification of a conserved region of ORF1ab and N genes for SARS-CoV-2 using specific primers and a fluorescent-labeled probe the sequences of which have not been published by the company. A total of 5μl RNA extract was transferred into reaction tubes containing 15 μl PCR reagents. RT was performed at 450C for 15 min and amplification was performed for 1 cycle of 950C for 2 min and 45 cycles of 950C for 10 sec, 600C for 50 sec followed by a final cooling step at 40C. A CFX-96 instrument (Bio Rad Laboratories) was used for all amplification reactions. Both the efficiency of the RNA extraction and RT-qPCR were evaluated in all samples using the internal control (IC) RNA. 2.4. Recovery of SARS-CoV-2 from wastewater and limit of detection To determine the efficiency of recovering SARS-CoV-2 from wastewater using our precipitation and RNA purification methods, we first spiked synthetic RNA (Viasure SARS-CoV-2 Real Time PCR Detection Kit, CerTest Biotec) and added it in the resuspended precipitate at the final step of the extraction procedure. This approach was used to monitor successful handling of each sample in every step of the method. Assays showed recovery efficiencies of greater than 90% when input concentrations were log(6) and log(4) genome copies/ L. Efficiency declined rapidly when input was log(3) genome copies/ L and below. The limit of detection for SARS-CoV-2 virus extracted from wastewater samples was tested using serial dilutions of 105 to 10 copies / L of non-replicative recombinant virus particles with sequences from SARS-CoV-2 genome (Accuplex SARS-CoV-2 Verification panel, Seracare) into sterilized wastewater. Spiked wastewater samples were extracted and assayed using the protocols described above. Greater than 95% of qPCR reactions using the CDC N1 and N2 primers/ hydrolysis probes produced a positive detection when SARS-CoV-2 was diluted to as little as 100 copies/ mL (N = 20 for each dilution). The spiking experiment was performed in triplicates. 2.5. Statistical analysis All statistical analysis was performed using STATA 14.0. 3. Results 3.1. Sampling grid and sample characteristics The sampling grid consisted of 12 sampling spots. 151 wastewater samples were collected over a period of 8 months. Twelve sampling points were included. Six points were coming from 'hotspots' of interest such as nursing homes (n=3), tertiary hospital and 2 refugee camps. 3.2. Limit of detection In all cases, only the viral N gene could be detected by RT-qPCR and only in the concentration of 105 RNA copies/L (Figure 1). This concentration was therefore considered to be the limit of detection of our method and the criterion according to which our samples would be characterized as positive or negative for the detection of SARS-CoV-2 in wastewater. 3.3.RNA concentration and extraction Nanodrop spectrophotometer measurements showed that all samples had similar concentrations of nucleic acids (data not shown). Four samples (2,65%) showed inhibition of the internal control used in the RT-PCR reaction and were excluded from further analysis. Whenever, inhibition of the internal control was observed new samples from the same spot were collected. For all samples, the physico-chemical analysis for pH, conductivity, absorption at UV 254 nm and the results showed no statistically significant differences. 3.4. SARS-CoV-2 detection in wastewater samples Based on that, we were able to confirm the virus presence in 32 wastewater samples by detecting the Orf1ab genomic region and/or the N gene. Samples with low viral load showed N gene amplification only. 3.5. Wastewater SARS-CoV-2 detection and correlation with clinical cases Across the entire network, we detected the first positive sample in our system in week 21 of the surveillance and continued to detect positive samples up until week 34 of the surveillance following closely the outbreak course (Table 1) and without interruption for 13 weeks. A total of 32 wastewater samples were found positive in several spots of sampling ranging from 1 to 7 positive samples per week (median 2.5 positive samples per week). Of particular note, the peak of positive wastewater samples appeared by end-October, slightly preceding the apparent increase in new clinical cases. The number of human cases increased considerably by the beginning of November and remained high by late-November (Figure 2).

The Westport Regional Business League (WRBL) in conjunction with the City of Kansas City, Missouri (City) are finally addressing frequent and severe flooding within the Westport district of the Brush Creek CSO basin. This project is applying a multi-objective approach to design a more affordable and valuable solution. The overall objective was to significantly reduce flood depths at a more affordable cost within a combined sewer basin. The project team achieved this objective by first developing a detailed 2D stormwater model that accurately simulated historical flood depths and then used that model to inform the city and key stakeholders on the flood reduction benefit for a range of solutions. Overlaying the 2D model results over parcel and street information served as a clear communication tool to demonstrate the flood reduction benefit. Unlike typical stormwater designs the goal was not to eliminate flooding, but to reduce the flooding to a point that property was not damaged, and public roads could be passable. An example of the before and after model results graphics are provided as Figure 1. Westport's flooding problems have gone through numerous studies in the past. These efforts have ultimately resulted in solutions that were held to a traditional stormwater design standard that was not affordable or constructible within this highly developed and utilized area of the city. The City and WRBL are now interested in pursuing stormwater solutions that can improve their frequent flooding problems, outside of a traditional stormwater design standard. The project team approached this effort using available rainfall data for two recent rain events and targeted stormwater improvement solutions that would alleviate flooding for these historical events using a Infoworks ICM 2-Dimensional Model. This tool was developed to accurately reflect observed flooding conditions for the recent rain events to understand how much reduction in flood depth the proposed improvements could provide. While 'solving' flooding problems in Westport for all storm events is not a feasible goal, the project seeks to significantly improve the flooding conditions for the more frequent rainfall events. Reducing flood depths from over 4 feet to less than 6 inches can transform what has historically been expensive flood damage to buildings and vehicles to short-term ponding contained mostly within the street right-of-way. As part of the federal consent decree compliance for CSO control, the City implemented the Smart Sewer Program (SSP) and developed a systemwide hydrologic and hydraulic model of its sanitary and combined system. The SSP model was developed in Innovyze InfoWorks ICM Version 7.5 and is a one-dimensional (1D) model calibrated to simulate the underground combined sewer system and CSO volume. The Brush Creek basin model was used as the starting point to develop the Westport stormwater 2D flood model. The 2D model was invaluable during this project. Because 1D models are limited to showing flood depths only at modeled manholes and inlets, but cannot show how the overland flow travels above ground and the flood depths and extents. The 2D model also better simulates the duration those flood depths and extents are experienced. The 2D model provided a much better understanding of how floodwater traveled and accumulated in the problem sump areas causing flooding of cars and businesses. The model results were confirmed by personal accounts, photos, and videos of simulated historical flood events. The 2D flood model was developed using a digital elevation model (DEM) that was created from the City's latest LiDAR-derived DEM data and updated with the field topographic survey collected as part of the project. A 2D mesh zone, a series of contiguous triangles, was then created in the model. Rainfall data is then directly applied to the 2D mesh zone, and the model routes the simulated runoff to the closest inlet point or lowest depressed area based on the DEM. This more accurate approach for stormwater runoff in Westport, which has a very high amount of directly connected impervious area, proved to be critical in not only defining the flood depths but the significant surface routing through the area. Figure 2 provides an example of the surface routing in the model. The other benefit of using a highly detailed 2D surface mesh was that green infrastructure collection solutions were simulated as depressions in the 2D mesh representing proposed conditions. This approach better represented the stormwater benefit of green infrastructure intercepting surface runoff, storing stormwater runoff, and then metering the storage volume back to the pipe system. The 2D watershed model was then utilized to evaluate both green and gray stormwater improvement solutions. Gray stormwater improvement solutions included curb and grate inlets, collection piping to underground storage, and conveyance piping. Green stormwater improvement solutions included pervious pavements, bioretention, vegetated swales, and tree planters. A combination of green and gray stormwater improvement alternatives were evaluated with the 2D stormwater model for a range of rainfall events. Stormwater improvements were sized and located to align with the Westport District plan which included parking improvements, streetscape enhancements, increased pedestrian safety and connectivity while maintaining the historical significance of the area. Using this multiple objective integrated approach, the design team was able to develop a preferred improvement alternative that provided a flood reduction benefit, addressed the Westport District plan requirements, and was cost-effective. The preferred stormwater alternative is a system solution that collects, stores, and conveys stormwater at multiple locations. Two large underground storage units form the upstream and downstream control points while green infrastructure collection in the form of pervious pavements along with traditional curb inlets provide additional collection and storage. A large stormwater pipe system connects the upstream and downstream storage creating a complete system solution to maximize the stormwater function. At the very downstream point the captured stormwater must be metered back into the combined sewer system. The stormwater solutions were located in areas that also required park amenities, street improvements, and defined parking which maximized the overall restoration benefit. (See Figure 3 for graphic of proposed improvements). The preferred improvement solution is tens of millions of dollars less than previous solutions, which makes this project fundable by the city. The city plans to move this project forward to design and construction to finally solve this frequent and severe flooding in Westport. In addition, this integrated flood reduction project will have a significant impact on reducing the CSO volume discharged downstream to Brush Creek. During the design phase other project performance improvements will be evaluated including real-time controls of the storage volume, stormwater re-use opportunities, and integration of this project with another green infrastructure project downstream to increase the performance and maximize the benefit of both projects. Thinking bigger than just solving the flooding problems has resulted in a project that a broad range of stakeholders can support at a more affordable price.

Water utilities across the nation are facing the challenge of doing much more with fewer resources. Face it, our industry attempts to recover mostly fixed costs from a mostly variable revenue source, and it is becoming increasingly difficult to do so, especially when you factor in affordability concerns. This is why it is so important for utilities to examine their other sources of revenue. System development charges (SDCs), or impact fees, are a common source of non-rate revenues for funding system expansions and/or improvements required to serve new users. An SDC is a one-time charge assessed to new development to pay for the capacity in the system required to serve them. They can also be assessed to existing customers requiring an increase in capacity. AWWA's M1 Manual, Principles of Water Rates, Fees, and Charges, 7th Edition (M1), provides a high-level discussion of SDCs in Chapter VII.2. To address the increasing interest in an expanded discussion of SDCs, AWWA plans to develop a new manual focused on SDCs and with sufficient detail to be truly helpful to a utility without experience implementing or updating SDCs. SDC BASICS Specifically designed to recover an equitable share of the cost of system infrastructure from growth, SDCs provide a source of capital funding along with user rates, debt financing, and up-front reimbursements from developers. SDCs assign the capacity cost of growth to those causing the growth rather than existing ratepayers. In addition, SDCs can recover a portion of the cost of improvements to the existing system if there is existing capacity available to serve new customers. Infrastructure commonly financed with SDCs include water rights, source of supply, treatment plant facilities, pumping, and transmission lines, sometimes collectively referred to as 'backbone' facilities. Water distribution mains are typically constructed by developers and therefore not usually included. A rational nexus must exist between the SDC amount and the costs associated with serving new users, whether or not the system needs to be expanded to serve them. According to the M1 manual, there are three basic methods for calculating SDCs: (1) the buy-in method, (2) the incremental cost method, and (3) the combined approach. Depending on the utility's goals, objectives, legal constraints, and financial circumstances, one method may be more appropriate than another. KEY TOPICS TO EXPAND ON The SDC chapter in M1 addresses several key topics, including the basic approaches to calculating SDCs and methods of fairly administering SDCs to customers with varying capacity requirements, at a very high level. A manual devoted entirely to SDCs will be able to expand on these topics, as well as many others, to give readers the additional detail they need to develop fair and equitable SDCs to enhance their revenue stream. The SDC manual will include additional examples to help readers understand the calculations for all components of the SDC. The new manual will explore eligible costs related to growth or capacity-related improvements to include as part of the capital improvements plan. Such topics as raw water supply capacity costs, regional transmission costs, interest or financing costs of eligible improvements, and debt service costs related to growth/capacity infrastructure for purchased water treatment services will be explored in greater detail. One key topic that the SDC manual will expand upon is the methods of assessing SDCs to different types of customers, particularly the advantages and disadvantages of each method to help a utility determine which method is appropriate for their service area. With development trends evolving to include accessory dwelling units, mixed-use (e.g. apartments above ground-level retail shops), single-resident occupancy units, and green/low-impact development, there is growing interest in standards for assigning equivalent units to these types of properties to ensure that they pay their fair share of system costs. Another key topic to be expanded upon in the new SDC manual will be defining system capacity. Because system capacity is not available in the same proportions throughout the various functional components of the water system (source of supply, treatment, pumping, storage, etc.) care must be taken to calculate the SDC component cost by functional cost component. This allows the utility to recognize variations in system capacity, system value, and customer capacity needs by functional area. The fundamental formula for calculating an SDC is: (System Value/System Capacity) X New customer capacity demands = SDC Summing the SDC functional component costs yields the water system SDC. The new SDC manual will examine some of the ways a utility can accomplish this task. NEW TOPICS TO INCLUDE The new SDC manual will include the following topics: (1) a summary of legislation by state, which varies widely; (2) guidance for SDCs regarding potential challenges and/or litigation; (3) administrative procedures and accounting requirements for SDCs; (4) land use assumption plans; (5) utilization of potential demand (capacity-based) versus estimated/actual demand (usage-based); and (6) incorporating major changes such as SDC process changes and definitions of Equivalent Residential Units (ERUs). In addition, the new SDC manual will contain more step-by-step examples for the reader. OVERVIEW OF PRESENTATION The presentation will provide a summary of SDC basics, including uses and methodologies for calculating them, as well as explaining the drivers behind development of the new manual. The presentation will provide examples of expanded and new topics and introduce the proposed timeline for developing and publishing of the SDC manual.

Background SARS-CoV-2, the virus responsible for COVID-19, is shed in the feces of both symptomatic and asymptomatic individuals and often before the onset of symptoms. Wastewater testing for COVID-19 virus can, therefore, provide population-level information about the circulation of the virus that is not captured by clinical testing. Wastewater testing is a proactive approach to detecting the presence and prevalence of infection and developing public health strategies to mitigate spread of the virus. Missouri's Coronavirus Sewershed Surveillance Project (CSSP) is a collaborative effort to monitor community sewersheds and congregate living facilities for genetic indicators of SARS-CoV-2 in wastewater. At the start of the project in June 2020, CSSP was collecting weekly samples from 12 community wastewater treatment facilities. In subsequent months, community interest in participation in the project grew. Currently, CSSP is collecting samples from 94 community facilities and 36 state congregate facilities, representing over 70% of the state's residents. Methods In CSSP, untreated wastewater (influent) samples are collected weekly or biweekly from select sewersheds and congregate living facilities for detection and analysis of trends of 'true' prevalence of the virus. Twenty-four-hour composite samples of raw influent sewage are collected using auto-sampling devices and shipped on ice to a lab at the University of Missouri-Columbia. The wastewater samples are then filtered, concentrated using polyethylene glycol (PEG) precipitation, and RNA is extracted. Following extraction, SARS-CoV-2 levels are quantitated by qPCR using N1 and N2 primers/probes (CDC). Standard curves are included in every PCR plate so that cycle threshold (Ct) values can be converted to Copy numbers/L from wastewater. In order to account for volumetric dilution that occurs within wastewater systems (e.g. rain fall), RNA concentration (copies/L) are multiplied by facility-specific flow rates (MGD) on the day of sample collection, yielding an estimate of total copies. Samples with high and sufficient viral load are screened for variant mutations using a novel computation workflow based on amplicon sequencing of the SARS-CoV-2 spike N-terminal domain (NTD) and receptor-binding domain (RBD), allowing for detection of variants of concern (VOC) and other lineages within sewersheds. Results Using Spearman's correlation analysis, CSSP found that wastewater concentrations most strongly correlate with positive case counts 4-6 days in the future (Figure 1). In analysis of community sewershed data, the team has found that a ≥45% increase in the exponential weighted moving average (EWMA) of viral genetic fragments in wastewater is proceeded by an increase in clinical cases in the following week approximately 65% of the time. Bland-Altman plots have revealed that wastewater is indeed a reliable proxy marker of current or future clinical cases. Application of Findings CSSP publishes the community sewershed data, including viral load trends and variant mutation detections, in a storymap (https://storymaps.arcgis.com/stories/f7f5492486114da6b5d6fdc07f81aacf) posted on the Missouri Department of Health and Senior Services (MDHSS) website (Figure 3). In addition, CSSP notifies MDHSS staff, local public health agencies (LPHAs), and other stakeholders of significant increases or elevations in viral load and the presence of variant mutations in sewersheds (Figure 4). In April 2021, CSSP began using the wastewater testing results to help identify communities in need of COVID-19 testing. CSSP extends offers for MDHSS to host a free community testing event where sewershed viral load trends are significantly increasing. LPHAs have helped raise awareness of wastewater testing results and interest in testing among their community members by advertising the events, holding meetings, issuing press releases, and conducting interviews. These outreach efforts have been particularly beneficial in rural areas of the state, where vaccination rates are low, COVID-19 testing options are sometimes limited, and, in May and June 2021, mutations of the more transmissible Delta variant were first being detected in the wastewater samples. Conclusions Sewershed surveillance can be utilized to identify potentially high risk communities and assist in data-driven public health efforts/decisions. In the future, sewershed surveillance may be used to better understand the spread of other communicable diseases and possibly even opioid use.

Executive summary: In this study, the impact of thermal hydrolysis pretreatment (THP) on the mono- and co-digestion of thickened waste activated sludge (TWAS) and food waste (FW) was carried out at temperatures of 150, 170, 190, and 210 C and volumetric ratios of 90:10, 70:30, and 50:50 in batch anaerobic tests. THP enhanced solubilization, reduced volatile suspended solids (VSS) and the particle size of TWAS as the temperature increased showing optimal improvements at 170 C. THP showed no significant impact on FW with only marginal improvements at 150 C. Increasing the temperature beyond 170 C for TWAS and 150 C for FW deteriorated anaerobic biodegradability forming refractory compounds. Co-digestion improved methane yields and kinetics as the contribution of FW increased. Co-digestion of thermally pretreated TWAS with FW improved the methane yields by 27% and kinetics by 29% at 170 C with no synergism. Co-digestion of thermally pretreated FW with TWAS improved methane yields by 15% and kinetics by 25% at 150 C, with improvements up to 21% in synergy. THP of the mixed feedstocks improved methane yields by 53% and kinetics by 92% at 170 C, with improvements becoming less pronounced with the increase in the volume of FW and temperature. Keywords: Co-digestion, thermal hydrolysis pretreatment, methane yields, Gompertz, kinetics, synergy 1. Introduction Background: Currently, the treatment of excess sludge produced from activated sludge treatment plants may account for more than 50% of the total operational cost .Anaerobic digestion (AD) of wastewater sludges results in reduction of sludge volumes, destruction of pathogenic organisms, stabilization of sludges, and production of valuable biogas. However, the application of anaerobic digestion to biological solids is associated with limitations in the hydrolysis stage. Despite the increasing interest in food waste prevention and recovery, very little food waste (FW) is recovered, mostly ending up in landfills. Reported advantages of THP are improved anaerobic degradation kinetics; increased biodegradability, volatile solids destruction, and methane production; solubilization of the macromolecular components of sludges (i.e., carbohydrates, proteins, and lipids); improved dewaterability; and higher digester organic loading rates. Considering that sewage sludge anaerobic digesters operate at relatively low organic loading rates ranging from 1.6 to 4.8 kg VSS/m d, with an unused capacity of almost 30%, and to alleviate operational upsets that arise from the mono-digestion of MSW and WAS, co-digestion becomes one of the most attractive solutions. Co-digestion promises a myriad of benefits such as process stability by supplemental alkalinity, trace elements, nutrients, enzymes; balanced C/N ratios; dilution of toxic compounds; diversion of food wastes from landfills; and the diversion of fat, oil, and grease from the wastewater collection infrastructure. Objectives: In this study, the impact of thermal hydrolysis on characteristic changes, anaerobic biodegradability, and kinetics of WAS and FW was evaluated at 150, 170, 190 and 210 C. Mixing ratios of 90:10, 70:30, and 50:50 (v/v) were adopted to identify the optimal pretreatment temperatures and mixing ratios for the thermally pretreated substrates with respect to anaerobic biodegradability and kinetics. The study also investigated the characteristic changes at elevated temperatures and their impact on subsequent anaerobic digestion and co-digestion, as well as the possible synergism through thermal hydrolysis and co-digestion. 2. Methodology Thickened waste activated sludge (TWAS) was collected from the rotary drum thickeners at Greenway Wastewater Treatment Centre (London, Canada). Anaerobically digested sludge was collected from a mesophilic anaerobic digester at the Water Pollution Control Plant (Stratford, Canada) fed primary sludge, and used as an inoculum for all biochemical methane potential (BMP) tests in this experiment. FW was collected from StormFisher (London, Canada). The design of each phase comprised pretreatment at 4 different temperatures (i.e., 150, 170, 190, and 210 C) and 3 mixing ratios for FW to TWAS (i.e., 10, 30, and 50%) on a volumetric basis. The volumes of both the substrate and the inoculum were calculated based on an inoculum to substrate ratio (ISR) of 2 g VSS/ g COD as recommended for most applications. All BMPs were carried out in duplicates at 37 ± 1 C by incubating the bottles in a water bath set at the designated temperature. 3. Results and Discussion TSS and VSS of the TWAS concentrations decreased as the THP temperature increased, resulting in solubilization efficiencies of 31%, 45%, 61%, and 62% at 150, 170, 190, and 210 C respectively. sCOD concentrations of the FW remained almost equal at all temperatures. The viscosity of the raw TWAS decreased sharply with the increase in temperature from 259 to 2 cP at 210 C. The mean particle size of the raw TWAS decreased from 167 µm to 106, 96, 57, and 42 µm at 150, 170, 190, and 210 C, respectively. The viscosity of the raw FW decreased with the increase in temperature from 670 cP to 270, 240, 220, and 45 cP at temperatures of 150, 170, 190, and 210 C respectively. The particle size distribution of the raw FW and pretreated FW at 150 C were bimodal, forming two peaks at 20 µm and 275 µm, and at 91 µm and 240 µm respectively. Samples pretreated at 170 C constituted a single peak at 91 µm, while samples pretreated at 190 C and 210 C peaked at 79 µm. Interestingly, the mean particle size of the FW increased with pretreatment from 106 µm to 111, 153, 109, and 114 µm at 150, 170, 190, and 210 C, respectively which is hypothesized to be due to the formation of chemical bonds catalyzed by temperature. Phase I The largest improvement in methane yields was in the 90:10 mixture at 170 C with a methane yield of 312 mL/g COD, 27% higher than the raw mixture. The highest methane yields from thermally pretreated TWAS were 234 and 250 mL/g COD at 150 C and 170 C respectively. Increasing the temperature to 190 C and 210 C detrimentally impacted methane yields. THP increased methane production rates of the raw TWAS from 147 mL/d to 199, 191 and 205 mL/d at 150, 170, and 190 C, respectively, while pretreatment at 210 C decreased it to 136 mL/d. Phase II The highest methane yield from thermally pretreated FW was 276 mL/g COD at 150 C. Increasing the temperature beyond 150 C decreased methane yields below that of raw FW. The 50:50 mixture produced the highest yield of 309 mL/g COD, 15% higher than the raw mixture. The increase in temperature to 170 C improved the methane yield by only 4%. THP had a more significant impact on the synergistic outcome of this phase with improvements ranging from 7% to 21%. At 150 C, a 17% synergistic increase in methane yields was observed for all mixtures. Despite the formation of refractory compounds at the higher temperatures (< 170 C), the dilution of these toxins with co-digestion compared to mono-digestion might have influenced improvements in both methane yields and kinetics. Phase III Methane yields improved in the 90:10 mixtures at all temperatures, with a maximum yield of 286 mL/g COD at 170 C, 52% higher than the raw mixture. However, increased solubilization was not reflected in increased biodegradability at the higher temperatures. The most pronounced improvement was in the 90:10 mixture where thermal hydrolysis at 170 C increased the methane production rate by 91% from 140 to 268 mL/d, beyond which kinetics deteriorated. 4. Conclusions THP showed a more significant impact on the characteristics and anaerobic biodegradability of TWAS than FW. The increase in the degree of solubilization, particle size, and VSS reduction with the intensification of the pretreatment temperature did not result in improved anaerobic biodegradability. The impact of thermal hydrolysis on co-digestion was inversely proportional to the biodegradability of the mixture showing the largest improvement of 53% in the methane yield and 92% in kinetics in the 90:10 mixtures relative to the raw mixture. Refractory compounds produced from thermally hydrolyzing FW seemed to be less inhibitory compared to those produced from TWAS and could be diluted with co-digestion, hence, synergistic improvements up to 21% in methane yields and 27% in kinetics were observed. The synergistic increase in methane yields observed with the co-digestion of thermally pretreated FW with TWAS decreased with the increase in the volumetric contribution of FW and pretreatment temperature, showing the largest improvements in the 90:10 mixtures owing to the larger biomass availability from the higher TWAS contribution.

The use of Green Infrastructure (GI) and its addition to stormwater regulatory requirements became widespread with the publication of the USEPA National Pollutant Discharge Elimination System requirements in 2000 (EPA, 2000). In most areas of the United States, this this was addressed with the addition of a volume management criteria to address water quality, recharge, and streambank geomorphology, while maintaining past peak flow requirements. For example, in Pennsylvania, the pre-construction water volume cannot be increased, and water quality cannot be degraded for new development for all storms up to the 2-year/24-hour event (PADEP, 2006). The peak flow restrictions for the 2-, 10-, 50- and 100-year storm remain as well (Pennsylvania Code, 2022). Most applicants have used NRCS techniques based upon the design storm approach (NRCS, 2007). While GI was embraced and brought to the design of stormwater systems, the design storm approach was not rethought. This too often results in the need for a hybrid of two separate stormwater systems - one for small, frequent storms (targeting water quality and geomorphologic concerns) and one for large, infrequent events (such as 50, 100 year storms). The use of continuous simulation was proposed by the USEPA as far back as the 1970's for water quality design (USEPA, 1979). Continuous simulation was proposed as superior to the design storm approach even for peak flow. A major challenge of the mission to use continuous simulation at that time was the lack of available rainfall and climate data with fine intervals. Design storms were intended for designs of structures whose failure would cause catastrophic consequences. The stormwater best management practice design guide from the USEPA expressed concern as to the accumulation effect of peak flows and to the extended peak flow erosion a streambanks (Clar et al., 2004). Pennsylvania and other states combine these two regulations requiring both the pre-construction volume and peak rate to be met. Unfortunately, the design storm approach for long storm events (such as 24-hour durations) artificially concentrate most rainfall volume over a small time interval which occurs at the center of the storm. The statistics used to develop design storm distributions do not separate the high-intensity, small volume thunderstorm from that of the low-intensity, long duration frontal system. Thus, the statistics that create the high-intensity center peak are more consistent with the intensity of short duration thunderstorm than that of a 24-hour rainfall event. An example, a recorded 24-hour storm event is compared the design storm of the same rainfall volume and duration (Figure 1). The graph shows a distinct difference between the design storm and the recorded rainfall event in terms of peak intensities.Vegetated GI design, that utilize infiltration and evapotranspiration, is strongly influenced by the short-duration, high-intensity peaks and as such temporary storage is needed. The additional storage is rarely used but required by the design storm approach. This prejudices the selection of GI towards lesser green solutions (such as underground detention basins), which require more space and typically more maintenance. It is hypothesized that a site tailored to the soil, vegetation, and local rainfall patterns would be more resilient, more appropriate, and more feasible especially in urban areas (Traver and Ebrahimian, 2017). Villanova University was approached by the Commonwealth of Pennsylvania to develop an update to the Stormwater management Manual, which enabled the researchers to implement what has been learned worldwide since the previous manual was published in 2006. Besides the introduction of climate change adaptations, the researchers are proposing parallel paths (continuous simulation or design storm approach) for meeting the 2-year/24-hour volume and water quality requirement as well as for peak flow (using continuous simulation/storm of record approach or design storm approach). Results from model studies used to validate these approaches will be presented. References Environmental Protection Agency (EPA). 2000. 'Proposed Reissuance of National Pollutant Discharge Elimination System (NPDES) Storm Water Multi-Sector General Permit for Industrial Activities.' Federal Register. Accessed January 17, 2023. National Resource Conservation Service (NRCS). (2007). Chapter 7 Hydrologic Soil Groups. Pennsylvania Department of Environmental Protection (PADEP). (2006). Pennsylvania Stormwater Best Management Practices Manual. Pennsylvania Code. 2022. '25 Pa. Code § 102.8. PCSM requirements.' Accessed January 17, 2023. http://www.pacodeandbulletin.gov/Display/pacode?file=/secure/pacode/data/025/chapter102/s102.8.html&d=reduce. United States Environmental Protection Agency (USEPA). 1979. '1978 Needs Survey: Continuous Stormwater Pollution Simulation System - Users Manual.' Office of Water Programs Operations. Clar, M., B. J. Barfield, and T. O'Connor. 2004. Stormwater Best Management Practices Design Guide Volume 1 - General Considerations. U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-04/121. Traver, R. G., and Ebrahimian, A. (2017). 'Dynamic design of green stormwater infrastructure.' Frontiers of Environmental Science & Engineering, 11(4), 15. United States Environmental Protection Agency (USEPA). (2016). Summary of State Post Construction Stormwater Standards. Washington State Department of Ecology. (2012). Stormwater Management Manual for Western Washington (Publication Number 12-10-030).

Located about 20-min south of Detroit, the South Huron Valley Utility Authority (SHVUA) operates a 24 mgd Wastewater Treatment Plant (WWTP) that treats an average of 10 mgd. The SHVUA WWTP treats wastewater from 7 communities: Brownstown Township, Woodhaven, Gibraltar, Van Buren Township, Huron Township, and South Rockwood which is comprised of approximately 90,000 residents. Due to the rural nature around Michigan, many facilities land apply biosolids. Prior to 2020, SHUVA would combine gravity thickened primary sludge and WAS and then lime stabilize to create a liquid-lime product which would be Class B land applied during the summer and stored during the winter. Since 2014, the facility struggled to store all the material over the winter, especially if the fall or spring was particularly wet thereby limiting the ability to liquid land apply. Historically, the facility would have to 'store' solids in the primary clarifiers and bioreactors which put the facility at risk of permit compliance. In fall 2018, Jacobs was selected to contract operate the SHVUA WWTP. Part of the first step of taking over was to 'un-constipate' the plant using mobile dewatering which cost nearly half a million dollars to dispose at the landfill. At WEFTEC 2018, knowing that biosolids hauling was a systemic issue during the winter, Jacobs conducted an informal technology review. Among those technologies reviewed, Lystek appeared to be viable option by being capable of increasing the available detention time from 180 days at 6-7% total solids (%TS) to approximately 326 days of storage due to a higher concentration (14-16%TS). In addition, the process also created a Class A product, although this was not a major driver given that there was generally sufficient land available for Class B land application. In spring 2019, Hubble, Roth & Clark (HRC), SHUVA's resident engineer, evaluated multiple biosolids technologies to address the off-season woes as part of a 20-yr capital improvement plan. The evaluated alternatives included: -Installing additional winter storage -Ship excess biosolids to a regional facility for process -Install a new sludge stabilization system consisting of Thermal hydrolysis and anaerobic digestion and a combined heat and power system. -Installing a permanent dewatering facility to dewater excess solids and dispose to the landfill -Continue emergency mobile dewatering and landfill disposal The results of the HRC evaluation proposed installing a permanent dewatering facility. However, in Fall 2019, Jacobs augmented that evaluation by including the Lystek process alongside the prior evaluated alternatives. The Lystek process was found to be the most cost effective on a unit cost per dry ton basis and could utilize an existing building (see Table 1). In addition, it would maximize the beneficial reuse of biosolids. The new Lystek facility, Michigan's first, was constructed using a design-build contract and is operational today, producing a Class A product. This presentation will provide the background how SHVUA, Jacobs, and HRC worked together to address the on-going plant issues and develop a cost effective, environmentally friendly solution that was constructed and operates successfully today.

Background: Bioinformatic analysis of whole genome sequencing data has played a central role in surveillance throughout the SARS-CoV-2 pandemic by allowing scientists to identify novel variants and to track the proportions of variants across time and geographic location. Because SARS-CoV-2 is shed in fecal material that ends up in wastewater, whole genome sequencing of SARS-CoV-2 from wastewater samples can be an effective method for the surveillance of the virus. Methods: Here, we describe Colorado's wastewater whole genome sequencing and surveillance strategy for SARS-CoV-2. We have been collecting twice weekly samples from March of 2021 to present from 20 wastewater utility sites. After extraction of RNA from wastewater, we perform tiled PCR-amplicon whole genome sequencing for SARS-CoV-2. We also present the bioinformatics workflow that we developed for analyzing whole genome sequencing data from wastewater samples, which determines the variants likely present in a sample based on sets of mutations associated with variants of concern or interest. Variant-associated mutations are determined using the Spike mutations present in known variants of concern (VOC) or variants of interest (VOI) as defined in the outbreak.info database (https://outbreak.info/situation-reports) and are updated regularly. Briefly, this workflow performs quality control and filtering of raw reads, aligns reads to the reference genome, calls single nucleotide polymorphisms (SNPs) using FreeBayes and filters SNPs based on quality. We then use custom scripts to identify the presence and frequency of mutations associated with known VOCs and VOIs and to generate summary files for further analysis and visualization. We have made this workflow a publicly available resource for use on Google Cloud's Terra platform. Results: Using this surveillance and analysis strategy we have been able to determine which SARS-CoV-2 variants are likely present in wastewater samples based on the constellations of VOC/VOI-associated mutations that are present. For example, we observed the rapid transition from Alpha to Delta as the dominant variant circulating in Colorado (Fig. 1A). Furthermore, we can see the emergence of VOCs in CO prior to their emergence in clinical samples sequenced by either the state public health department or a commercial laboratory and reported to the state public health department. As shown in Fig. 1B, in most of the counties for which we have sampling, we identified the mutations associated with the Delta variant in wastewater prior to it being identified in clinical samples. These results also show geographic differences in which variants are present, when they are first detected in wastewater, and when they are first detected in clinical samples. Conclusions: These results demonstrate that SARS-CoV-2 wastewater sequencing can be used to monitor SARS-CoV-2 trends over geographic location and over time. Our ability to detect VOC/VOI-associated mutations prior to the detection of the viral lineages with which they are associated in clinical samples suggests that wastewater whole genome sequencing can be used as an early warning signal. More broadly, these results can inform public health strategies and can be applied to other pathogens of current or future public health concern.