Results

Summary This paper will share the progressive evaluation and selection of a thermal drying technology for application at the Athens-Clarke County Public Utilities Department (ACCPUD) North Oconee Water Reclamation Facility (NOWRF). The progressive evaluation and selection process was conducted in multiple phases and included: - Confirmation of Sizing Criteria - Evaluation of the 'World of Options' for Thermal Dryers - Screened Technology Assessment Site Visits - Technology Type Selection and Competitive Pre-Procurement Process - Detailed Design and Bidding This paper and presentation will share the progressive process utilized by ACCPUD for the selection of a dryer technology and a technology provider using a combination of cost and non-cost evaluation factors in a multi-criteria procurement process. Confirmation of Sizing Criteria The current plant is permitted for a 14-MGD capacity and uses an advanced activated sludge process for treatment coupled with high solids centrifuge dewatering to produce a cake for landfill disposal. Future plans are to expand the plant by adding primary treatment and anaerobic digestion. Dryer sizing was confirmed against current and future residuals production rate scenarios and a design evaporation of of 4,500 lb-water per hour was selected. Evaluation of the 'World of Options' for Thermal Dryers The first phase assessment included a preliminary screening of the following thermal dryer technologies for possible application of at NOWRF: - Belt Dryers, - Rotary Drum Dryers, - Indirect Paddle Dryers; and - Fluid Bed Dryers Based on the preliminary screening of technologies the belt dryers and indirect paddle dryer technologies were selected for additional screening assessment. Screened Technology Assessment Site Visits Following the preliminary screening site visits were arranged for plant operating and maintenance staff to visit operating installations of the belt and paddle dryer technologies. Site visits were conducted in Pennsylvania, North Carolina and Tennessee to view operating installations and have discussions with facility operators. Results of these site visits will be summarized in the paper and presentation. Technology Type Selection and Competitive Pre-Procurement Process Following the site visits and discussions with facility operators of belt and paddle dryers ACCPUD operations and maintenance staff selected the indirect paddle dryer technology as the most appropriate technology for application at the NOWRF. Based on the preliminary screening of technology suppliers a competitive procurement process was designed that would consider both cost and non-cost factors in the final selection of a technology vendor. The competitive procurement was conducted between the Komline-Sanderson Paddle Dryer and the Andritz-Gouda Paddle Dryer systems based on development of a detailed technical specification describing the system and the minimum required system elements coupled with a preliminary general arrangement drawing for location of the facility on the plant site and integration with the existing dewatering system. The competitive procurement scoring allocated 25% of the scoring points to cost factors and 75% of the scoring points to non-cost factors. Cost based scoring criteria considered the following: (1) equipment capital costs, (2) estimated building costs to house the equipment, and (3) system operating and maintenance costs based on power consumption and thermal energy efficiency of the dryer system. The non-cost factors were allocated to the following major criteria: (1) manufacturer experience; (2) operability and maintainability; (3) air permitting and air emissions rates; and (4) process safety. The paper and presentation will share the results of the cost and non-cost scoring for the selection of the technology supplier. Detailed Design and Bidding Following selection of the technology supplier detailed design activities were initiated for the project. Preliminary design activities included sending a large sample (~ 15 cubic feet) of dewatered cake to the selected technology supplier to test in their pilot plant to confirm heat transfer coefficients and the minimum ignition temperature (MIT) for the paddle dryer. The sludge-specific heat transfer coefficient was utilized to confirm adequacy of the proposed heat transfer surface area. The minimum ignition temperature was used to confirm the paddle dryer thermal oil operating temperature. Results of the pilot testing will be shared in the paper and presentation. Detailed design has progressed through the 'bid ready' stage and the project has been bid and will begin construction in late 2021 / early 2022.

The City of Des Moines, Iowa (the City) awarded a contract to CDM Smith for development of a comprehensive city-wide stormwater master plan (SMP). This session will communicate the value of applying a risk-based asset management framework to the City's SMP development. Municipalities will benefit from this discussion by learning about risk-based asset management principles for stormwater systems. This framework is adaptable, eases prioritization efforts, and enhances communication with stakeholders. The SMP was developed to provide a systematic, prioritized, and proactive framework for addressing the City's stormwater management challenges. To date, the SMP has consisted of two phases with the first focusing on a needs assessment and programmatic framework, and the second phase began implementation of the city-wide risk analysis and the more detailed application in the initially selected watersheds. The needs assessment and programmatic framework phase (Phase 1) was conducted by completion of a program audit, review of best practices, and identification of new practices to enhance the City's stormwater management program, including the initial development of a risk-based asset management framework. During the subsequent implementation phase (Phase 2), processes identified during the initial needs assessment were applied to characterize the existing stormwater system and provided insight for short- and long-term financial planning. Overall, the SMP informs future strategies by providing actionable recommendations and processes to manage assets more efficiently. Continued evaluation of level of service objectives, public engagement, and process refinement bring life to the SMP, allowing for future application and adaptation by the City. During Phase 1, a risk-based asset management framework was developed to prioritize stormwater asset inspections, maintenance, renewal, and capital projects. Under this structure, the Likelihood of Failure (LoF) and Consequence of Failure (CoF) are used to calculate the Risk associated with each asset. Each of these parameters ' LoF, CoF, and Risk ' range in value from 1 to 5, with 5 being the worst. LoF is based on the assessment of an asset's condition and performance, while CoF is based on an asset's significance to the stormwater system and the impact severity of failure. Condition may be evaluated through field investigations or estimated using a surrogate parameter easily obtained through analysis of asset properties, such as age and material. The preliminary LoF based on surrogate parameters may be used in conjunction with CoF to determine an initial Risk score and inform inspection priorities. This assessment allows itself to be conducted with limited field investigations to provide an initial estimate of system risk and needs. Initial estimates of system risk may then be used to identify priority catchments for detailed investigation and recommended capital improvement projects (CIPs). Specific processes for this purpose were developed as part of Phase 1. Phase 2 of the SMP applied the processes identified during Phase 1 to the City's stormwater system. A desktop analysis was performed to determine the LoF, CoF, and resulting Risk score of each asset. Surrogate parameters were used to determine LoF, because inspection data was not widely available. GIS-based algorithms were developed to calculate these LoF, CoF, and Risk scores for each asset. From this, three priority catchments were identified in the City. Upon review of priority catchments with City stakeholders, the project team deployed for field investigations to fill data gaps and determine a more accurate LoF condition score. Investigations included pole camera and CCTV of pipes and adjoining structures and visual inspections of stormwater basins. Parallel to field investigations, SWMM models were created for the priority catchments. Inspection-based LoF condition scores and LoF performance scores from the SWMM models were used to identify assets that should be included in a capital improvement project (CIP) due to the need for renewal, either by rehabilitation (lining) or replacement. Conveyance improvements and opportunities for additional storage were modeled to provide a preliminary CIP approach. Results of the desktop analysis used to inform priority catchment selection were also used to identify potential CIPs in non-priority areas. These projects were identified by focusing in areas with the highest LoF and Risk scores. Although these CIPs require additional design, the preliminary analyses results in short-term financial planning data. The necessity and reach of these identified CIP locations will be confirmed through final field investigation and detailed design. In additional to the risk-based asset management framework and identification of potential CIPs, other key outcomes of the SMP included: - Development of level of service (LOS) objectives - Development of a public outreach plan - Development of white papers regarding policy development to support the asset management framework - A summary of recommended operation and maintenance activities per asset type - Creation of Lucity-based asset management dashboards, improved asset inventory, inspection forms, and other tracking resources, as well as staff education on use of Lucity resources - Development of an Excel-based tool to estimate asset inspection and renewal needs based on surrogate parameters of age and material for use in long-term planning - A strategy for implementing SMP recommendations and processes, including identification of staffing needs - Short- and long-term financial planning recommendations Final deliverables of the Phase 2 Des Moines SMP are currently under review and will be finalized in early 2023. As the City implements SMP recommendations, the assessment methodology, data collection approach, and other processes may be refined to better support the City's system. Efforts should focus on ramping up proactive inspections to help shift asset management from reactive to proactive, further developing the asset inventory and understanding of the system's current condition. Moving forward, the developed risk-based asset management framework provides a clear path for asset evaluation and CIP prioritization, while providing flexibility for future iterations.

In water-stressed regions around the world, a dearth of resilient water utilities is jeopardizing access to basic needs such as piped drinking and irrigation water. The availability of this water is heavily tied to utility management of wastewater as a resource to reverse growing supply pressure on freshwater sources, something which the American Southwest has dealt with head-on with its established aquifer and reservoir infrastructure. However, wastewater treatment and reuse infrastructure has become even more challenging for utilities in the region due to the growing impact of climate change-proliferated droughts. While technologies like MBR (Membrane Bio Reactors) and MABR (Membrane Aerated Biofilm Reactors) are being readily implemented as creative reuse solutions for the region, innovation in utility planning will be just as valuable. Further, the need for innovative infrastructure strategy applies to A) densely populated cities with limited space to add centralized utility infrastructure, B) new towns or suburban regions where utilities need to be quickly built and C) irrigation infrastructure that needs to be built or improved (i.e., 2021 Lake Mead crisis). Given these challenging scenarios, Modular Decentralized Wastewater Treatment (DWT) is a compelling new solution gaining traction globally. These systems are crucial for the Southwestern US and beyond in the fight against 'Day Zero' (including Cape Town itself) due to their associated affordability and speed of implementation. When implemented correctly, Modular DWT can also deliver the following benefits: - Augmented biological load removal capacity (depending on the technology used) o Can extend to nutrient removal in order to reduce coastal 'dead zones' - Minimized piping infrastructure and land usage based on accurate fulfillment of treatment requirement - Can be easily deployed in regions with Combined Sewer Overflow (CSO) issues as a standby unit -Simplified sludge handling and disposal due to point source treatment - Impacts of system downtime can be reduced due to distributed approach and standardized IoT Integration (rather than relying on one custom, centralized system) Our paper will identify hotspots for the next 'Day Zero' scenarios and how what a modular DWT program there might look like.

Introduction: Surface waters are challenged by a variety of conditions that may influence the persistence of microbial and viral species of concern. Water monitoring and management practices rely on indicator organisms, and thus it is important to understand how common stressors affect the persistence of indicators and pathogens comparatively. Persistence has traditionally been assumed to follow first-order decay kinetics, but this assumption is potentially over-simplifying a process that is known to be more dynamic than the assumed linear profile. Previous reviews and analyses have identified two and three-parameter models that have been shown to more frequently provide a good fit to persistence data than the exponential model (Mitchell & Akram, 2017; Dean et al., 2020). To explore the applicability of these models for targets persisting in natural surface waters, a systematic literature review and meta-analysis were conducted to assess the availability of datasets for modeling, and to explore the relationship between the observed persistence and the documented experimental conditions. The implications of the first-order decay kinetics assumptions were evaluated by completing factor analyses that relied on only the exponential model to describe persistence, and factor analyses informed by the best fitting models from the tested suite. Methods: A systematic literature review was conducted to identify all available datasets pertaining to indicators and pathogens in natural surface waters that documented the following factors: water type, water temperature, sunlight presence, predation presence, and method of detection. The targets fell into five main groups including fecal indicator bacteria (FIB), bacteriophages, pathogenic bacteria, viruses, and protozoa. Over 650 datasets were identified, extracted or digitized for the meta-analysis. Five models, the exponential (Chick 1908; Watson, 1908), exponential damped (Whiting & Buchanan, 2001), Juneja and Marks 1 (Little, 1968), Juneja and Marks 2 (Juneja, Marks, & Mohr, 2003), and double exponential (Shull et al., 1963), were fit to the datasets. Bayesian Information Criteria (BIC) values were used to identify the best fitting model(s), and goodness of fit was determined with normalized root mean square errors (nRMSE). If more than one model provided a good fit to the dataset, model-averaged metrics were calculated using the BIC value as a weighting value (Dean et al., 2020; Haas et al., 2014). To evaluate the effect of considering alternative persistence models, T90 and T99 values were calculated for each dataset with the exponential model (EP-calculated) and using the models determined to provide the best fit by the BIC and nRMSE values (BF-calculated). The EP-calculated and BF-calculated T90 and T99 values were then used as dependent variables in an exploratory factor analysis using correlation coefficients, Kruskal-Wallis tests, and basic linear models. The performance and predictive power of the linear model method were evaluated by fitting the models to training and testing datasets to calculate RMSE values. Results: The exponential model provided a good fit to only 15% of the tested datasets and the distributions of EP-calculated T90s and T99s had a higher variance than those of the BF-calculated distributions. In particular, the exponential model calculated a higher range of T90 values for FIB, bacteriophages, bacteria, and viruses, as shown in Figure 1. The exponential model also predicted higher average T99s for all target groups, suggesting that the impact of model selection becomes more pronounced after the first log-reduction. The discrepancy between T99s was greatest for the protozoa targets as shown in Figure 2. The T90 and T99s predicted by the different persistence modeling methods were treated as dependent variables in a variety of factor analyses. When only the exponential model was used to calculate the dependent variables, sunlight had inflated importance as indicated by the correlation and Kruskal-Wallis coefficients. Interestingly, the linear model fit to EP-calculated decay metrics had more significant interactions than the model fit to the BF-calculated decay metrics. Significant interactions were observed between sunlight and water type, sunlight and method, temperature and predation, and water type and method. The BF-calculated linear model only identified a significant interaction between sunlight and method. However it is important to note that the linear models fit to both the EP-calculated and BF-calculated decay metrics had relatively poor performance with RMSE values greater than 14 days. The predictive power was better for the T90 linear models (~ 11 days) than the T99 (~14 days). Conclusions: Traditionally applied first-order decay kinetics only provided a good fit to 15% of the tested datasets and there was greater variance in the calculated T90 and T99 distributions when the exponential model was fit to the data. These results indicate that fitting two-parameter and three-parameter persistence models can potentially reduce the uncertainty associated with target decay. The differences between the EP-calculated and BF-calculated metrics were greater for the T99 data than the T90 data, suggesting that the importance of using more accurate persistence models increases as later time points are considered. This is especially important when considering the reliance on natural decay in a number of surface water uses and applications. Notably, the differences between the persistence models fit were more prominent for target groups like viruses and protozoa, which are pathogen groups of high concern in surface waters. The factor analyses conducted herein indicate that the reliance on the exponential model may be potentially overestimating the effect of sunlight on decay in natural surface waters. The linear models fit in the factor analysis, however, were found to have poor performance on the datasets as a whole. This suggests that there may be factor-decay relationships that are nonlinear in nature and that other methods may be more appropriate to explore the dynamic behaviors of indicators and pathogens in diverse water quality and environmental conditions. The results of this analysis have implications for the fields of water management and risk assessment, as narrowing the uncertainty associated with indicator and pathogen decay in surface waters is a critical component of human health-related decision making for surface waters.

In Indianapolis, Indiana a developed neighborhood was seeing localized flooding during smaller rain events. When the neighborhood was built in the 1960's, almost no storm water infrastructure was built as the neighborhood was established. HNTB Corporation was selected to help the Indianapolis Department of Public Works(DPW) solve the neighborhood's drainage issues. At the start of the project, the goal was to improve the neighborhood drainage, introduce green infrastructure where feasible and provide a lasting solution. This presentation will focus on how the project came together, starting with the planning phases of the project. The presentation will focus on the collaborative effort to develop multiple alternatives and work with stakeholder groups to develop a preliminary solutions. As the presentation continues, we will discuss how we transitioned from planning to design. As we shift to the design portion, we will continue to focus on the collaborative process developed to ensure that all stakeholders were happy with the final product. As we start the design portion of the project, we will talk about the community involvement, design issues encountered, and schedule that resulted in the final product. While working through the design, the DPW reinforced its desire to include green infrastructure where feasible. We will step through the design process of including permeable pavers, rain gardens and other aspects of green infrastructure into the project along with the calculations involved to ensure that Indianapolis Standards were met. We will also discuss the areas where green infrastructure was not feasible and talk about why those options were not feasible. In the last phase of the presentation, we will discuss issues that came up during construction of the project and how those issues were resolved during construction. We will focus again on how the team worked collaboratively to ensure a final product. We will talk about some of the challenges faced and highlight how the project was finished. We will walk through how the project team was able to accomplish the initial goals of the project and provide a long-lasting, sustainable solution to the neighborhood's flooding problems.

Regional flooding has been controlled within the Coachella Valley in Southern California since 1915, with existing facilities built or improved in the 1970s following severe floods. The Coachella Valley Water District provides stormwater protection for a 590 square mile area within the valley by using approximately 135 miles of channels along with a number of dikes and retention basins that can convey approximately 80,000 cubic feet per second of flow from the surrounding mountains into the Whitewater River. In 2017, the District partnered with Black & Veatch to launch an extensive asset inventory and support implementation of their asset management system. This presentation will show how the rapid growth of CVWD's asset management system has benefited their stormwater management program by: 1) Showing the importance of data structuring and establishing a data collection protocol for a successful asset management program. 2) Engaging stakeholders across their business to create an expansive and robust registry which supports current and future programs. 3) Providing data to justify capital improvements and preventative maintenance decisions; shifting away from reactive maintenance and developing defendable investment prioritization. The Project has completed a field-based inventory, baseline full-system condition assessment, development of risk-based prioritization criteria, and mapping business processes. The stormwater assets were collected over a 4-week field effort with zero injuries. To execute these efforts, Black & Veatch leveraged an off-the-shelf ESRI product tailored so the final asset inventory seamlessly integrated with the District's CMMS software. CVWD staff were involved in each step of the project, helping structure data hierarchies and dictionaries, collecting field data, and incorporating institutional knowledge into business process mapping and prioritization criteria development. Data management was key as the final inventory contained over 80,000 data points including sub-meter accuracy GPS coordinates, field documented asset specifications, over 1,500 photographs, opinions of replacement costs, and baseline likelihood of failure and consequence of failure criteria. Post collection, the District's forces now have verified asset locations and attributes that provide reliability to day to day efforts. Scalability was built into the implementation to support on-going and future development of the asset management system.

Stormwater systems are increasingly stressed due to the growing number of high precipitation events and the pressure on aging stormwater system capacity. Now, more than ever, efficient stormwater asset management is crucial to public safety and regulatory compliance. Unfortunately, the cost and effort of conducting field inspections and collecting accurate and comprehensive data is an ongoing challenge for municipalities. Radio frequency Identification (RFID) technology has been widely used in many industries for its unique ability to track items without needing direct visual confirmation. Passive RFID tags don't require power and can be affixed to nearly anything. Today, RFID is rapidly becoming the solution to bridging the gaps in field data collection workflows for stormwater management. This session will explore on-going deployments using RFID-enabled asset marking for stormwater assets in combination with mobile data collection and GIS-based asset management systems. Initial pilots indicate that RFID-enabled asset marking reduces the time, cost and errors in field data inspections. Several deployments will be reviewed, including how the approach performed when used with Esri's ArcGIS Online to manage water sampling stations; and when a range of assets are tagged, including catch basins, hydrants and manholes. The system consists of: RFID-enabled tags placed on assets RFID readers tied to mobile devices via Bluetooth Software apps (web or software) that run on the mobile device The workflow is as follows: 1. RFID tags are placed on the asset 2. The RFID tag is accessed through the reader and specific information is written to the RFID tag, including asset owner, date/time, lat/long 3. Then the tag data is connected to its specific asset record in ArcGIS through web apps or a widget on the mobile device which then launch inspection/maintenance forms for completion in the field. This data can be accessed and managed in the office or in the field, creating a direct link between physical assets and data. Additionally, accurate geolocation and asset performance data removes the guess-work from future location and maintenance. At the conclusion of this session, participants will be better able to: Understand the use of using RFID-enabled technology to enhance stormwater infrastructure asset locating maintenance, monitoring and management.

Decentralized stormwater reuse is emerging as a sustainable approach to mitigate urban runoff issues while promoting resource efficiency. This abstract highlights the benefits of such a decentralized system, exemplified by the Arbor House Affordable Housing complex project in the Bronx. The Arbor House project successfully deployed a real-time stormwater management solution to address the challenge of combined sewer overflow (CSO) in New York City. By capturing and storing rainwater in cisterns, the system optimizes water use for rooftop urban agriculture and minimizes untreated wastewater discharges into local waterways. Key advantages of decentralized stormwater reuse, as demonstrated by this project, include: Reducing CSO Impact: Decentralized systems like the one at Arbor House significantly reduce CSO discharges by retaining and reusing rainwater. This proactive approach aligns with sustainability goals and helps protect aquatic ecosystems. Maximizing Resource Efficiency: The captured rainwater serves as a valuable resource for irrigation, reducing reliance on potable water sources and conserving this precious resource for essential needs. Environmental Compliance: The project's monitoring and reporting capabilities ensure compliance with environmental regulations, facilitating transparency and accountability in stormwater management. Community Benefits: Decentralized stormwater reuse projects often have the added benefit of enhancing community well-being. In Arbor House, the reclaimed water supports urban agriculture, contributing to local food production and quality of life. Scalability and Adaptability: Decentralized systems are versatile and can be scaled to suit the needs of various developments, making them a flexible solution for urban areas facing runoff challenges. Decentralized stormwater reuse, as demonstrated by this project, offers a sustainable solution to urban runoff challenges. It reduces CSO impact, optimizes resource efficiency, ensures environmental compliance, enhances community well-being with urban agriculture, and provides scalability for diverse urban environments. This approach sets a sustainable precedent for global urban water management. The Arbor House Affordable Housing complex project goes beyond stormwater management; it actively addresses equity and inclusion by providing affordable housing, supporting urban agriculture, creating jobs, mitigating environmental challenges, engaging the community, and promoting sustainable practices. These efforts contribute to a more equitable and inclusive urban environment. The Arbor House project exemplifies the transformative potential of decentralized stormwater reuse, offering a sustainable blueprint for urban water management. As cities worldwide grapple with stormwater issues and water scarcity, this approach showcases the feasibility and benefits of implementing decentralized systems to achieve water resilience and environmental stewardship. Learning Objectives: 1. Explore the concept of decentralized stormwater reuse and its significance in addressing urban runoff challenges and promoting resource efficiency. 2. Examine the project as a real-world example of successful stormwater reuse, focusing on its key benefits and impact on sustainability. Recognize the role of decentralized stormwater reuse in enhancing community well-being, promoting urban agriculture, and creating opportunities for local residents. 3. Assess the versatility of decentralized systems and their potential applicability in various urban settings, emphasizing their flexibility and adaptability. 4. Consider the broader implications of decentralized stormwater reuse as a sustainable solution with global relevance for urban water management and environmental stewardship.

The COVID-19 pandemic has resulted in widespread illness, taken the lives of nearly five million people worldwide, and caused many other disruptions to daily life. The pandemic has also presented several challenges to disease surveillance and epidemiological risk mitigation. Addressing these challenges requires novel decision support methods to satisfy multiple and sometimes competing goals of risk reduction, securing private data, and preserving personal liberties. In this presentation, we will describe our contributions to the development of a SARS-CoV-2 wastewater surveillance monitoring program, subsequent data analyses to interpret results, and modeling to evaluate the predictability of this novel method that emerged during the pandemic. Weekly grab samples of wastewater were initiated in May 2020 for SARS-CoV-2 analysis at four locations. Three of these were on-campus building-level locations, with one off-campus catchment-level location. Preliminary results indicated elevated concentrations of SARS-CoV-2 co-occurring with new outbreaks in the community. As a result, sampling was continued through the Fall semester, expanding the program to monitor four specific residence halls at the building level. In January 2021, sampling was expanded to a total of six residence halls and one off-campus catchment-level location, sampling frequency was increased to twice weekly, and the temporal composition of these samples was modified with the installation of automatic composite samplers. The sampling protocol was again expanded in August 2021 to include a total of 18 composite samples at twice-weekly resolution. This included 15 on-campus locations yielding building-level samples and three off-campus catchment-level locations. Methods to model this type of data to establish public health implications are rapidly developing and have required ongoing research. Some preliminary approaches have been published to correlate wastewater concentrations with COVID-19 cases at the community level from samples taken at wastewater utility plants. These methods allow for a larger population (i.e. those contributing to wastewater) to be analyzed using a single test. Further, this style of testing captures results from communities without differentiating between symptomatic or asymptomatic cases. However, these methods have not been well-established at the building level where factors such as fluid mixing, transit time, sewer geometry, dilution with wastewater streams largely free of viral RNA (e.g. laundry), and more transient populations are assumed to negatively impact the interpretation of results. Additionally, fecal shedding rates SARS-CoV-2 variants are not well-established, potentially calling into question the application of preliminary models based on the original strain of the virus. To support decision-making on campus, we have created a data analysis plan using monitored wastewater concentrations and positive or presumptive cases identified through clinical sampling, screening-based saliva sampling, and contact tracing. Building-level data such as occupancy counts, the percentage of vaccinated residents, and building water use volume are being collected to better support modeling and interpretation of results. Wastewater samples are collected from manholes corresponding to building wastewater discharges, and analyzed for a variety of gene targets from known variants. We will present results of these analyses for data collected during the 2021 calendar year. Several analyses will be presented including (i) cross-correlation between wastewater signal and the number of known or presumptive cases contributing to samples; (ii) a Poisson regression to determine the predictability of the number of infections from wastewater concentrations; and (iii) variable selection to determine factors driving the relationship between case counts and wastewater signal which will best inform deterministic modeling. These results will provide a unique perspective into the challenges and benefits of conducting a wastewater surveillance program at the building-level, and will support future efforts to model case counts from building-level wastewater concentrations of the SARS-CoV-2 virus.

The management of PFAS has been a topic of discussion among the water/wastewater industry for the last few years, which has led to the development of the EPA's interim guidance for PFAS management. Our current understanding of both the extent of PFAS contamination nationwide in drinking water supplies and the concentrations that produce adverse health effects in the human body are in their early stages. What is certain is that PFAS will become an issue of growing concern over the next several years, if not decades, with the advancement of contamination site and health testing. Recently drafted EPA interim guidance and its key focus areas. The current on-going USEPA's PFAS Action Plan intend to develop MCLs for PFOA and PFOS in drinking water and to take steps to classify PFAS as hazardous substances. These actions have the potential to affect wastewater utilities in two keyways: (1) By requiring higher levels of treatment to protect downstream public water supplies and/or expanded source water protection measures; and (2) By limiting disposal options for PFAS contaminated waste or biosolids. States are also developing their own standards for PFAS in surface waters. The standards could be drivers for new permit limits and/or additional monitoring requirements for WWTPs. In turn, these requirements could result in costly investments in new treatment technologies to achieve a higher level of PFAS removal. Following States have already developed MCLs ahead of EPAs action plan: -New York established MCLs for PFOA and PFOS of 10 ppt individually -New Jersey adopted MCLs for drinking water for PFOS (13 ppt), PFOA (14 ppt), PFNA (13 ppt), and groundwater quality standards for PFNA (13 ppt), PFOA (14 ppt), and PFOS (13 ppt) -Michigan adopted groundwater cleanup standards for PFNA (6 ppt), PFOA (8 ppt), and PFOS (16 ppt), and MCLs in drinking water for PFNA (6ppt), PFOA (8ppt), PFOS (16ppt), PFHxS (51ppt), GenX (370ppt), PFBS (420ppt), and PFHxA (400,000ppt) -New Hampshire adopted drinking water MCLs for PFOA (12 ppt), PFOS (15 ppt), PFHxS (18 ppt), and PFNA (11ppt) -Vermont adopted a drinking water MCL for PFHxS, PFHpA, PFNA, PFOS, and PFOA of 4ppt individually and 20 ppt combined. -Massachusetts adopted drinking water MCLs for PFOS (3.3 ppt), PFOA (3.3 ppt), PFNA (3.3 ppt), PFHpA (3.3 ppt), PFDA (3.3 ppt) and not to exceed 20 ppt combined. During this presentation the following topic areas will be also covered: 1.Removal mechanisms of the PFAS treatment technologies focused on destruction, concentrating, and sequestration 2.'Off-the-shelf' and innovative treatment technologies 3.PFAS minimization as a primary management strategy and the fate and transport of PFAS when these substances are used Although most municipal wastewater utilities have not yet had to deal with PFAS issues, a proactive approach, starting with an initial PFAS risk evaluation is recommended. This initial risk evaluation is intended to provide municipal decision-makers with some idea of where their PFAS risks lie, as well as give them recommendations for next steps to inform proactive planning for PFAS response.

Wastewater analysis for SARS-CoV-2 RNA has been underway in various locations across the world since early 2020 and is a rapidly expanding area of research. There is a limited understanding of the behaviour of viruses within the sewer network. However, it is likely that the virus is subject to a range of biotic and abiotic factors which may influence its persistence and transit time within the network . Understanding this behaviour is key in developing sampling strategies which underpin an effective Wastewater Based Epidemiology (WBE) health surveillance system. Developing this understanding requires answers to a number of core questions, namely:

•Does the virus follow conservative flow regimes?
•Does the virus degrade in the sewer environment?
• How long does the virus persist in the network?
•What are the impacts of re-entrainment after weather events?

A better knowledge of these factors would allow better interpretation sample results in the context of the environmental conditions, which will also create the foundation for being able to triangulate and track the sources of viral outbreaks.

In the UK over 90% of the water and wastewater networks are representing in hydraulic models. These models have been built over the past 10 – 15 years and have been subject to millions of pounds of investment to ensure they are fit for purpose and accurate. These models have the potential to be a key tool in an effective WBE program if used in the right way. To date, development has primarily been focused on flooding, which is the core driver in the UK, and less so on the representation of water quality parameters.

Method

Through this study we worked to assess how well these models could be used to represented viral transport in sewer network, as well as identify any potential limitations.

To do this we worked in two catchments, each with different properties to deploy an enveloped viral marker at known places into the sewer network and then tracking its appearance at various locations. This work was complemented with the conservative flow fluorescent dye tracer, rhodamine-WT. We followed these tracers through the use of an autosamplers in the network over 17 days. Using these results, we then calibrated a hydraulic model (with contaminant transport processes) to understand the key parameters which influence transport (degradation rate, flow rate, rainfall, pipe material and roughness).

The models use the Innovyze Infoworks ICM modelling platform. In all cities the models were 'cut down' to represent only the major network with inflow files at junctions, as in Figure 1. This was done to increase the speed of the models.

In order to ensure accuracy these cut down models are checked against the full model to make sure there are no differences. The conditions on the sampling days were then re-created by adding any rainfall and inputting the markers at the upstream manhole, representing it as coliform.

Results

The different catchments each highlighted different challenges and opportunities. In the first there was a pumping station in between the input location and the sampling point. This meant that initially the model under predicted the travel time by over 4 hours. To counter this the impact of the pump was derived by including its operational controls. After this was done the time of travel matched that of the experiments closely, as seen in Figure 2. In our simulations we ran a number of scenarios with different T90 decay times. In Figure 2 it can be seen that a T90 of 10 – 12 hours most accurately matches the experiments. This influences the design of a sampling strategy or interpretation of the result to incorporate this decay of the virus.

In the second catchment there was a single straight run of pipe, with no significant hydraulic structures. However, we were unable to recreate the travel time accurately, as shown in Figure 3.

The models use a standard Dry Weather Flow day based upon when they were originally verified. We compared velocity measurements taken on the day of the experiments to the validation day and there was a large differential. This may be explained by changing water usage during Covid altering the flow patterns in the sewer, as was suggested by the flow monitor at the outlet point, as shown in Figure 4.

Conclusion

The key conclusion from the work is that it is possible to represent an enveloped virus in the sewer network through the use of hydraulic models. Both in terms of travel time and decay rate. However, using the models 'off the shelf' can lead to large inaccuracies as the models may not be validated/ developed with the intention for use in water quality modelling or water usage has changed during Covid with home working to the point at which the models are no longer representative. In these conditions having flow measurements recorded at the same time as sample extraction can lead to more certainty around the outputs/ results and allow for the models to be adapted to match reality.

If the models are fully validated it is possible to use the water quality modules to represent the virus transport with a T90 decay rate of 10-14 hours. This means that sampler coverage needs to ensure that areas outside of this distance from a sampler need to be covered by additional in-network samplers to represent SARS-CoV-2 prevalence. Or include scaling factors to incorporate the likely decay of the virus.
The transport of the virus is conservative (via advection), as a result if the key parameter of interest is travel time this can be calculated based on only knowledge of the network configuration and the flow rates. However, the models are still required to explore the relationship with decay rates.

Future work

The opportunity to represent other health markers and chemicals is being explored as well as whether these models can be run in real time and integrate real time sample data to track the sources of infection in communities.

The City of Minneapolis established a Green Infrastructure (GI) Program in response to calls from the community to incorporate GI throughout the city. The community asked for practices that improve the environment and mitigate the impacts of climate change, largely in response to transportation project outreach. The resulting program supports a shift in design to integrate stormwater management and greening into transportation projects. The inevitable resistance to change 'how we've always built roads' without clearly defined requirements, guidelines, training, and funding came from expected and unexpected places. This resistance uses a variety of justifications, including questioning the motives and function of GI, imbalanced performance and aesthetic expectations, project deadlines, funding, a gap in the maintenance program, among others. This resistance uses a variety of tactics, including procrastination, the promise of the next project, budget constraints, feasibility challenges, among others. The resistance can be sophisticated or novel making it harder to recognize as a 'no', but it is often repeated, until a response can be crafted. Yet, the city has successfully installed hundreds of GI facilities in the three years since the program began, garnering major community support, and providing community, air and water quality benefits throughout the city. In this presentation, we will introduce the first in a series of challenges the program has had to endure and transcend: incorporating sustainable landscaping. Sustainable Landscaping is a term borrowed to help define the difference between GI practices such as native plantings that do not directly treat stormwater (SL) from green stormwater infrastructure (GSI) that captures and treats stormwater. We will walk through the motivations and goals around sustainable landscaping, introduce the forms of resistance we faced, and then present the various techniques we used to overcome individual and programmatic resistance to successfully implement sustainable landscaping in projects throughout the city.