Conference Papers

Learning objective: Attendees will learn how workforce development is a continuous cycle of assessment, planning, application, measurement, and learning and be able to take actionable steps to enhance workforce development initiatives. Public water utilities face particular challenges to building and developing the talented and committed workforce needed to ensure successful operations. A convergence of challenges makes this especially difficult as we approach the middle of the 21st century. Increasing demands of environmental regulations and economic forces impacting the ability to deliver services cost-effectively are coupled with the loss of experienced professionals and fewer people entering public service. Add to this changing expectations of the employer-employee relationship and competing demands for funding, and the water utility sector is facing an unprecedented challenge. While most utility leaders recognize these workforce challenges, few are able to independently overcome the barriers to tackle the issue and make significant headway. The water utility sector can build a strategic, holistic, compelling vision for its workforce and thrive in today's work environment by adopting a practice of continuous improvement by implementing a Cycle of Successful Workforce Development. This cycle includes five stages: assessment, planning, application, measurement, and learning. In each stage, utility leadership can take tangible, actionable steps to enhance workforce development. This presentation will (1) explore the barriers to significant investment in workforce development in the water industry, (2) introduce the Cycle of Successful Workforce Development, and (3) share examples of several utilities where elements of this cycle were applied for enhancing workforce development. Industry guidance, former utility leadership experience and case studies will be used to walk attendees through the cycle. The cycle begins by performing a comprehensive organizational assessment that considers what skillsets and positions are needed and where gaps exist in the current workforce. Benchmarking, span of control, and matrix of authority reviews are integral parts of this 'on ramp' to the cycle. The results are then utilized for planning business process improvements and assembling the desired organizational structure. Recruiting and hiring are crucial to identifying and securing candidates, and will be guided by competency assessments and job descriptions improvements informed by strategies grounded in the realities of the current workforce supply/demand environment. Onboarding and training are crucial application steps to set up employees for success, whether they are new to the organization or established staffers assuming new and more challenging roles. Well-planned training programs will ensure all know the organization's goals and objectives and have the opportunity to succeed. Training should be coupled with business process improvements. Career ladders, succession planning and leadership training provide flexible pathways for professional growth, improve organizational continuity and resiliency, and help retain talented employees. Measurement of achievement against defined goals helps achieve success through both organizational and individual performance monitoring. Competitive salary, mentorship programs and incentive programs foster a culture of continuous improvement. Reassessment of the organization at budget preparation time each year will identify opportunities to adapt the plan to changing circumstances and external influences. Learning from regular review of both organizational and individual achievement against goals provides opportunity to refine processes and will help employees identify and achieve their career goals.

Microplastics is an important class of contaminants of emerging concerns. In scientific literature, microplastics typically refer to plastics particles, fibers, and fragments between 1 µm and 5 mm. Water Resource Reclamation Facilities (WRRFs) are conduits between the waste sources and the environment. WRRFs collect a large quantity of microplastics from various sources, including municipal waste, roadway run off, industrial discharge. Conventional wastewater treatment processes have been effective in separating microplastics driven by physical-chemical properties of microplastics, and consequently, microplastics accumulate in solids stream and biosolids (Blair et al., 2019; Bui et al., 2020). Treated biosolids have a range of disposal pathways, among which agricultural land application accounts for approximately 50% of annual total biosolids disposed. Land application of biosolids presents avenues for microplastics in biosolids to enter and accumulate in agricultural soil. The accumulation of microplastics in agricultural soils can lead to various adverse implications for soil quality by impacting soil structure, water dynamics, and soil biota. Microplastics that enter the terrestrial environment through biosolids can further mobilize to different environments, through storm runoff and aerosolization. Understanding microplastics' occurrence, fate, and transformation in biosolids treatment is crucial to mitigate the above-mentioned adverse effects of microplastics in biosolids and to promote the beneficial and sustainable use of biosolids. Information on microplastics cross the solids treatment steam is yet to be summarized or synthesized to assist stakeholders understand risks associated with microplastics on a high level. To this end, a comprehensive critical review was conducted to inform the state of knowledge of microplastics studies regarding sludge and biosolids and synthesizes data from those studies, to address the lack of understanding of microplastics in those unit processes. This study captures data and knowledge from 51 studies including peer-reviewed journals articles, reports, and conference proceedings. The proposed presentation will cover the abundance, fate and characteristics of microplastics in solids stream and biosolids, as well as methodologies for analyzing microplastics in sludge and biosolids samples. This study is part of a Water Research Foundation funded project (WRF 5221). Abundance and Fate of Microplastics in Solids Stream and Biosolids Wastewater sludge can be a sink of microplastics as a large portion of microplastics in wastewater can be separated during skimming and sedimentation. The abundance of microplastics in each type of sludge varies over multiple orders of magnitude (Fig. 1). The lack of consistent sampling across the entire solid treatment train poses challenges in developing an understanding of how different sludge treatment processes affect microplastics and quantifying the transformation of microplastics. Based on the intra-facility variation of microplastics in solids treatment stream, the level of microplastics does not significantly change from sludge generation, thickening to stabilization, but reduces after dewatering, showcasing potential accumulation of microplastics in sidestreams. Innovative biosolids treatment technologies, such as pyrolysis and hydrothermal liquefaction, provide opportunities to remove microplastics along with other persistent contaminants of emerging concerns. On average, 14,900 pieces of microplastics can be deposited into soil per dry kilogram of biosolids applied, revealing biosolids as a pathway for microplastics to enter the terrestrial environment. Furthermore, maximum sludge values are significantly higher than the average at 169,000,000 particles per kg. Sources in literature indicate microplastics increasing '280 items/kg and 430 items/kg' with sludge application (Yang et al., 2021). Soil concentrations are observed to range from single digits per kg to approximately 40,000 pieces per kilogram. The average concentration of microplastics in soil is approximately within 100 particles per kg to 1,000 particles per kg for a rough order of magnitude comparison. Approximately half of the microplastics found in sludge and biosolids are in the shape of fibers, which indicates laundry discharge is an important source of microplastics in wastewater and biosolids. Microplastics of Different Characteristics: Polymer Types and Morphology A total number of 31 types of polymers were reported in literature. Polyester, polypropylene, polystyrene, polyethylene, polyamide, polyethylene teraphatalate are the most frequently reported and abundant types of polymers. Polyester and polyamide are commonly used for making synthetic fabric (Sun et al., 2019). Thus, they often appear as microplastics fibers in wastewater and biosolids and their prevalence is in line with the abundance of fibers in various types of sludge. The polymer types abundant in biosolids align with the ones in wastewater reported in previous studies (Bui et al., 2020; El Hayany et al., 2022), showing that laundry discharge and storm runoff are major sources of microplastics in wastewater as well as biosolids. Source control to reduce microplastics load in raw sewage could be an effective measure for microplastics reduction in solids stream. Additionally, the similar abundance of polymer types in liquid and solids stream processes also reveals that the accumulation of microplastics in solids stream is not polymer type specific. Methodologies for Microplastics Quantification in Biosolids Sampling and analytical methods used in literature are summarized to inform future analysis of microplastics in sludge and biosolids. The sampling of low solids content samples, e.g. secondary sludge, digested sludge, can utilize automated sampling system and pumps, whereas high solids content samples are manually taken using containers or shovels. The sample processing procedure typically follows: density separation, chemical digestion, and vacuum filtration (Fig. 2). The quantification of microplastics in literature is count-based and relies on vibrational spectroscopy. Mass-based quantification should also be adopted for future studies due to the potential fragmentation of microplastics. Conclusion The literature review conducted by the Project Team showcases the state of knowledge on microplastics in solids treatment stream. It informs utilities of the abundance, fate of microplastics in different process units and in relation to facility characteristics and location, providing information that utilities can use to assess potential risks. It also provides insights into the origins of microplastics in biosolids, which help utilities identify potential entry points into the water treatment and wastewater systems. Currently there is no standard method for microplastics analysis in sludge and biosolids. The summary of reported methods in literature will provide the utilities valuable references and guidance on producing reliable, reproducible data.

Over the past five years, Federal and State level grant funding for resilience projects has significantly increased (BRIC, Infrastructure Investment and Jobs Act, etc.). Prioritizing where those investment dollars are best spent can be a challenge due to the high sensitivity of the benefit /cost models to the expected flooding depth. Typically, regional scale flood hazard analysis data is used to determine the feasibility of a project, with more detailed modeling to follow as a way to confirm benefit / cost information. However, the complexities of hydrologic and hydraulic processes often mean that accuracy is sacrificed when assessing regional scale flood risk assessments. If the ultimate benefit cost ratio determined from the detailed project specific model is drastically different than the initial regional model, it calls in to question whether the initial prioritization of projects was successful. In this presentation we will demonstrate how GIS and machine learning can be coupled with local site-specific modeling to produce detailed hazard information at a watershed-scale. This ultimately allows site specific information like stormwater capacity, detailed terrain information, infiltration data, and future conditions to increase confidence in regional feasibility level cost-benefit analyses. We will provide comparisons of the following data for several sites to examine how this new process can benefit resiliency planning: 1.FEMA flood hazard information 2.Regional scale hazard modeling 3.Detailed, project specific modeling 4.GIS & machine learning predictions (Flood Predictor) 5.Observed data Planning directors, as well as development and community infrastructure managers will learn how machine learning can be coupled with existing site specific hydraulic modeling efforts to rapidly scale detailed results to other areas throughout the watershed that are lacking good hazard information. Financial administrators can use this information to better invest in projects with greater confidence acknowledging this proactive and adaptive process has strengthened the success curve and ROI to the community.

Like many entities across the nation, the neighboring Southwest Ohio Counties of Greene, Butler, Montgomery, and Warren (Counties) have faced increasing challenges with respect to solids management. These include: Stability. The Counties have generally relied on short-term contracts for solids management. Short-term contracts leave utilities vulnerable to unexpected price increases and, at a minimum, hinder projections for long-term financial planning. Most solids-processors and disposal outlets also prefer long-term contracts, and so short-term contracts can have higher costs. Resiliency. The biosolids sector is experiencing nearly unprecedented upheaval due to regulatory actions in some states and the issuance of the controversial EPA Office of Inspector General (OIG) report. A changing regulatory landscape, coupled with increasing public concerns regarding emerging contaminants and biosolids outlet availability, are driving the need for a biosolids program that can withstand these pressures. Cost-effectiveness. Costs remain a critical consideration for solids management. In addition to cost uncertainties associated with short-term contracts, the Counties are seeking approaches that maximize the value of each dollar spent via solids reduction and resource recovery. Moving to a regional approach for solids management can address these challenges and is the basis for the Southwest Ohio Regional Biosolids Collaborative Strategies Development project. The first phase of the project was conducted over most of 2020 whereby monthly virtual workshops were conducted with representatives from each of the Counties, along with representatives from the Ohio EPA to provide feedback and input into the development of project critical success factors, screening and identification of preferred solids stabilization technologies, identification and weighting of evaluation criteria, and development and evaluation of conceptual regional solids handling strategies. Feedstocks considered for processing at a regional facility included solids from each of the Counties wastewater treatment facilities, food scraps and yard waste from the Counties' municipal solid waste (MSW) programs that could potentially be recovered, and potential fats, oils, and grease (FOG) production from within the Counties. The facilities could potentially process other desirable feedstocks from commercial and industrial sources within the study area, but the focus for this first phase of the project was on organics generated by the Counties. A brief review of regulatory requirements and potential solids markets in the region was conducted to provide a framework for selecting those solids stabilization technologies considered to be the most suitable for the Counties to implement a regional solids handling approach. Four solids stabilization technologies were shortlisted in this first phase: composting, drying, thermal hydrolysis process (THP) with co-digestion, and high solids digestion. Three of these technologies were expanded into two strategies to facilitate potential phasing of implementation and a gradual introduction of feedstocks resulting in the following seven initial conceptual regional solids handling strategies. Refer to Table 1 for a summary of the anticipated solids and energy inputs and product outputs for each of these strategies.Strategy 1: Composting. Haul biosolids cake from regional treatment facilities and regional yard waste and food waste to a composting facility and produce a Class A compost. Strategy 2A: Drying. Haul biosolids cake from regional treatment facilities to a thermal drying facility and produce a Class A dried product. Strategy 2B: Drying and Composting. Haul biosolids cake from regional treatment facilities and regional yard waste and food waste to a dual drying and composting facility and produce a Class A dried product and compost. Strategy 3A: THP w/ Co-digestion. Haul biosolids cake from regional treatment facilities and regional FOG and food waste to an anaerobic digestion facility with THP pretreatment and produce a Class A cake. Strategy 3B: THP w/ Co-digestion and Composting. Haul biosolids cake from regional treatment facilities and regional FOG, food waste, and yard waste to a composting facility with THP and anaerobic digestion pretreatment and produce a Class A compost. Strategy 4A: High Solids Digestion. Haul biosolids cake from regional treatment facilities and regional FOG and food waste to an anaerobic digestion facility and produce a Class B cake. Strategy 4B: High Solids Digestion and Drying. Haul biosolids cake from regional treatment facilities and regional FOG and food waste to a drying facility with anaerobic digestion pretreatment and produce a Class A dried product. These conceptual strategies were evaluated using a quadruple bottom line framework consisting of four evaluation criteria categories: financial, social, environmental, and functional. Strategies which initially appear to offer the greatest benefits with manageable risks are planned to be further developed and evaluated as part of the next phase of the project. In addition to these strategies, other strategies may be evaluated in the next phase which consider the following key drivers: Long term regulatory compliance. With new data continuously being produced on emerging contaminants, namely polyfluorinated alkyl substances (PFAS), the Counties may be interested in evaluating thermal type solids stabilization technologies such as incineration, gasification, or pyrolysis, which may reduce these contaminants. Public private partnership. With the potential for biosolids from multiple wastewater treatment facilities and organics from multiple other sources directed to a regional facility, the Counties may be interested in partnering with a third party who could operate and maintain the facility and manage/market the reuse of the resulting solids product. Expanded regional participation. Given the notable capital cost anticipated to implement a regional solids handling facility, the Counties may be interested in seeking other participants who may benefit from directing their biosolids/organics to a regional facility and who could share in the upfront costs and risks. This manuscript provides an overview of the findings of this first phase conceptual level evaluation that has provided the Counties with foundational planning for the potential implementation of a regional solids handling approach which could serve the Counties and potentially other utilities in the Southwest Ohio region. It will also review some of the next steps that are anticipated to be included in the next phase of the project.

Stormwater ponds are designed to remove phosphorus (P) from stormwater via sedimentation of the particulate-P fraction per criteria established by the US EPA Nationwide Urban Runoff Program (NURP). They are ubiquitous features of the urban landscape in many states, and especially in northern tier of states. Ponds thermally stratify in the summer and experience sediment anoxia. Ponds typically go anoxic in the winter. Because sediment P is bound largely to ferric iron, reduction to ferrous iron releases P. Therefore, the dead pool P concentration of solubilized P determines pond performance, not sedimentation. A study of 72 stormwater ponds in the western suburbs of Minneapolis, Minnesota USA confirmed that a substantial fraction of particulate P solubilizes because of sediment anoxia induced by thermal stratification. Only 26% of ponds were mostly compliant to NURP performance criteria (median TP ‰¤150 µg/L), 21% partially compliant (median TP 150 to 280 µg/L), and 52% were uncompliant (median TP 290 to 2500 µg/L) (Figure 1). From a limnological perspective, poor compliance is not surprising. From a management perspective understanding performance of ponds across the landscape is problematic. Determination of NURP compliance by direct sampling is largely impractical because there are too many ponds. Therefore, we investigated a rapid assessment protocol (RAP) to predict non-compliance with NURP performance criteria using field observations on ponds that were sampled for phosphorus at least 48 hours after the last significant precipitation event to obtain dead pool TP concentrations. Weight of field parameters to predict dead pool TP was determined with a random forest algorithm. Four RAP score ranges were determined to have significant (Wilcoxon-Mann-Whitney, 0.04 < p < 0.0001) differences in median TP ranges. The most highly weighted parameter predicting dead pool TP values was presence of emergent macrophytes in ponds. The study demonstrated that many RAP parameters could be discarded in future assessments. It appears that other parameters (e.g., pond age) may prove useful in a RAP method. Improvement of stormwater pond performance is an active area of investigation demonstrating practical methods to reduce pond TP discharge or dead pool TP concentrations. A RAP methodology would allow municipalities to efficiently assess stormwater pond performance across urban landscape to prioritize application of methods to improve stormwater P performance.

This research aims to elucidate the impact and efficacy of thermal hydrolysis on anaerobic digestion for mitigating PFAS-laden sewage sludge, addressing a critical knowledge gap resulting from the absence of a definitive standard method to quantify PFAS in biosolids. It is widely recognized that biological treatments, including anaerobic digestion, are generally considered inefficient for the treatment of PFAS-laden sewage sludge. For the first time, our study reveals how thermal hydrolysis pretreatment induces a significant shift in the microbial community, fostering an environment conducive to the effective mitigation of PFAS contaminants. Consequently, this research provides valuable insights into the potential robustness of thermal hydrolysis pretreatment in managing the complexities of PFAS-contaminated sewage sludge, making a substantial contribution to the current scientific landscape. Furthermore, this paper presents both qualitative and quantitative assessments of conventional anaerobic digestion versus thermal hydrolysis pretreatment in terms of COD removal, biodegradability, and dewaterability. It correlates these findings with the changes in the microbial community resulting from both experimental conditions. The paper explores the examination of thermal hydrolysis as an intensification process aligned with the objectives of water resource recovery facilities (WRRF) to achieve sustainability within the circular economy framework. Accordingly, six semi-continuous bioreactors were operated over a sixty-day period with a hydraulic retention time of fifteen days under mesophilic conditions. Three bioreactors represented conventional anaerobic digestion (RAW TWAS bioreactors), while the remaining three represented thermally hydrolyzed anaerobic digestion (HTP TWAS bioreactors). The study demonstrates that pre-treating thickened waste-activated sludge (TWAS) at 170 °C for 30 minutes and a pressure of 3 bars prior to anaerobic digestion enhanced sludge solubilization, biodegradability, and viscosity. The soluble chemical oxygen demand (SCOD) concentration increased from 213 mg/L in conventional anaerobic digestion (Raw TWAS) to approximately 15,000 mg/L in the thermally hydrolyzed TWAS sample (HTP TWAS). The average reduction in volatile suspended solids (VSS) and total suspended solids (TSS) in the HTP TWAS was 51% and 43%, respectively. Thermal hydrolysis significantly influenced particle size distribution, shifting the mean diameter from 206 to 104 µm and drastically reduced TWAS viscosity from 510 cP to 18 cP after thermal treatment. The impact of thermal hydrolysis on pre-treated TWAS was evident in increased methane production and methane percentage in the biogas generated (Figure 1). HTP TWAS bioreactors exhibited a higher average methane production of 551 mL/day compared to 365 mL/day for untreated ones, with corresponding methane yields of 176 mL/g TCODadded versus 116 mL/g TCODadded (Figure 2). Additionally, HTP TWAS digesters demonstrated higher destruction of volatile solids than Raw TWAS. The integration of thermal hydrolysis and anaerobic digestion addressed the excess sludge elimination issue associated with the biological process alone, significantly improving the dewaterability of anaerobically digested sludge two-fold (Figure 3). Moreover, this study, for the first time, examined the microbial communities in conventional anaerobic digestion, thermal hydrolysis anaerobic digestion, and PFAS-laden sewage sludge under both conventional and thermal hydrolysis anaerobic digestion conditions (Figure 4). The impact of thermal hydrolysis on the microbial community reveals increased microbial diversity and richness during the anaerobic digestion process. Thermal hydrolysis exhibited a substantial influence on both microbial community composition and more pronounced effects on archaeal community distribution and methanogenesis pathways and co-occurrence patterns. The relative abundance of Firmicutes, Bacteroidetes, and Proteobacteria was higher in the thermally hydrolyzed digestate samples than in conventional anaerobic digestion digestate. Thermally hydrolyzed TWAS-fed bioreactors showed enrichment in Tissierellaceae and Porphyromonadaceae, positively correlating with high methane production. In contrast, the microbial community of Raw TWAS had a higher relative abundance of hydrolytic microorganisms (Chloroflexi) capable of carbohydrate hydrolysis. Thermal hydrolysis demonstrated the resilience of AD in overcoming potential ammonia and PFAS toxicity attributed to the adaptability of its microbial community to environmental changes.

Introduction: The East San Gabriel Valley Watershed Management Group (ESGV Group), a client of Stantec, is comprised of the Cities of Claremont, La Verne, Pomona, and San Dimas (Group Members). The ESGV Group has performed water quality and storm parameter monitoring for five wet seasons. The collected data were analyzed to determine if simple relationships exist between descriptive storm parameters and the measured water quality. In other words, the group is interested in finding a linear relationship between storm parameters (e.g., storm duration, precipitation, intensity, etc.) and a specific water pollutant concentrations (e.g., E.coli). Traditionally, a multiple linear regression (MLR) is employed for this work, where all the available storm parameters are used as the predictors (i.e., regressors) and the water pollutant concentration serves as the output variable (i.e., response). This traditional approach can provide good performance when the number of predictors (i.e., available storm parameters) is small (e.g., 2-3). However, when the number of predictors becomes large (e.g., 5+), the traditional MLR may easily overfit and produce less optimal regression results. This is mainly because that MLR doesn't have any predictor selection process, so it tends to use all available predictors regardless of their usefulness. As a result, we propose a novel linear regression framework based on the Least Absolute Shrinkage and Selection Operator (LASSO), aimed at improving the performance on regression problems with large predictor numbers. We test our framework on three different types of water quality pollutants: E.coli, dissolved zinc, and total nitrogen. Each pollutant concentration is regressed against six available storm parameters: event precipitation, duration, peak intensity, average intensity, days since last storm, and days since last storm > 0.25 inches, under both traditional MLR method and the proposed LASSO regression. Although other storm parameters might be related to the water quality as well, those six storm parameters are the available data thus are selected as regressors in this study. The results show that for all three pollutants, the proposed LASSO regression outperforms the traditional MLR, using R squared (R2) as the evaluation metric. Methodology: Our proposed regression framework begins with pre-processing the collected data records, where outlier detection and influential data detection are conducted. Outliers are data values far from other data in the collected dataset, which have adverse impacts on regression. Figure 1 shows an example of how outliers can negatively influence the fit of the regression line. In our study, outliers are identified and filtered out by a pre-set z score. An influential data record is another type of 'outlier' that impacts the slope of the regression line. Influential data records are identified and filtered by a Cook's distance threshold. The processed dataset is obtained after removing both identified outliers and influential data records from the total available data. LASSO regression and the traditional MLR (for comparison) are then implemented on the processed data. LASSO regression is a variant of MLR, which encourages simple and sparse models (i.e., models with fewer storm parameters as predictors). It is usually preferred since it can automatically select useful predictors so that improve regression performance by avoiding overfitting. The difference between LASSO and MLR lies in the way of computing the estimated coefficient for each predictor, β ̂ , where LASSO adds an additional penalty term (l1 norm) on the coefficient in the minimization of residual. This penalty term shrinks the predictor coefficient values, so that an automatically predictor selection is achieved. The magnitude of this shrinkage is controlled by a hyperparameter α, known as LASSO parameter. The α value for each pollutant regression model is determined by fine tuning. The established regression models are evaluated on the processed dataset, based on cross-validation using R2 as the metric. R2 measures how much variation observed in the response is explained by the predictors in a regression model. The larger R2 is preferred for a model and the maximum is 1. Model Results: Three common pollutants are selected to compare the regression results of proposed LASSO with the traditional MLR approach: E.coli (contains 36 data points), dissolved zinc (contains 36 data points), and total nitrogen (contains 13 data points). Table 1 shows the R2 for both LASSO (red) and traditional MLR (blue). For all three selected pollutants, the R2 of the proposed LASSO regression outperforms the R2 of MLR. The total nitrogen provides the largest performance difference on two methods due to its limited amount of data. A small dataset usually favors the simple model, such as the LASSO model. To see how the LASSO regression model provides the simpler model than MLR for each pollutant, Table 2 presents the estimated regression coefficients for each predictor. For all pollutants, LASSO includes only a subset of predictors into the model with the positive predictor coefficients, while MLR uses all the available predictors. This demonstrates how LASSO can 'automatically' select the influential predictors and produce a simpler regression model. Figures 2, 3, and 4 show the regression results vs. actual data for all three pollutants. Consistent with the R2 comparisons, the LASSO regression results are in general slightly closer to the actual data than MLR, for all three test pollutants. Conclusions: This abstract presents a novel linear regression framework that has potential to be widely applied in stormwater management. Compared with the traditional MLR approach, the proposed LASSO regression encourages simpler and sparser models by automatically selecting the influential predictors. The regression relationship derived from LASSO outperforms the traditional MLR, as demonstrated in all three test cases of E.coli, dissolved zinc, and total nitrogen. More discussions on the framework will be provided in the following paper and the model will be further tested as more test data become available in the future.

ABBREVIATED ABSTRACT Utilities across the country face many similar issues aging infrastructure, tight budgets, legacy technology systems and processes, staff that are stretched thin, and customers, taxpayers, and ratepayers that demand innovation and accountability. These challenges are compounded by rising retirements among utility leadership and operations positions, and a shrinking pool of qualified applicants and talent to fill open positions. We often hear that the way to address this is to 'do succession planning' or 'focus on workforce development,' but many of our organizations lack concrete tools and action steps to achieve these objectives. During this session, participants will learn from two very different organizations that are actively working to address these workforce challenges, hear how they are using three key workforce development strategies to develop and retain their existing talent, and explore how participants can put these tactics to work in their own organizations. ABSTRACT Monroe Ohio is a small but growing city of 15,500 residents with agricultural roots and an emerging industrial base. In the last 20 years, the population of Monroe has more than doubled and the city has invested heavily in expanding utility infrastructure to meet growing demands. At the same time, Monroe's utility-focused staffing has stayed low and relatively steady, with a total of six dedicated utility staff positions in 2023 compared to five in 2000. Managing this rapid growth with limited staff is no small feat, but the dedicated team in Monroe has risen to the challenge in all aspects of their work. Situated strategically between Dayton and Cincinnati, Monroe's location offers unique advantages to its residents, but fosters intense competition for experienced utility professionals. Recognizing the importance of nurturing internal talent, Monroe has focused its efforts on internal succession planning and workforce development. Over the last several years, leadership has been relentless in identifying and cultivating promising young professionals, providing talented staff with opportunities to stretch their abilities, enhance their technical skills, and nurture their leadership potential. This concerted effort will ensure that the organization has a dynamic and capable leadership team ready to steer the utility forward into a thriving future. Two hours south on highway I-71, Louisville Water serves nearly one million people with a service area of over 1,000 square miles. Louisville Water's workforce is made up of more than 400 employees, many of whom stay with the company until retirement. Beginning with their 2019-2025 Strategic Business Plan, Louisville Water reinvented its approach to workforce development, starting with reframing the way it viewed its workforce. Just as its physical infrastructure requires ongoing investment and maintenance, Louisville Water believes that its people intrastructure deserves the same level of investment and attention. Starting with extensive new employee onboarding and new leader orientation programs, Louisville Water is reinventing the way it invests in and develops its staff to ensure their long-term success in the organization. Louisville Water is currently rolling out an all-employee development curriculum, 'Professional Unity,' that will develop organization-wide competency in areas like accountability, crucial conversations, personal performance, and generational alignment. Moving forward, the organization plans to continue to introduce new topics through this program, starting with skill-based leadership role training. This initiative aims to cultivate a cohesive and motivated workforce, drive higher employee satisfaction, increase productivity and improve business outcomes. While the scale of Monroe and Louisville Water's efforts are dramatically different, the concepts at their core, and many of the tools that they have employed are fundamentally the same. This session will explore three key strategies employed by both Monroe and Louisville Water that have been successful in transforming their talent into high performing leaders and managers. These include: Invest in Training and Developing Your Workforce Despite the Risk That People May Take Their New Skills Elsewhere Never Stop Succession Planning Start Building Your Bench Before You Need One Provide Opportunities for High-Potential Staff to Stretch and Grow Session attendees will be provided with a set of workforce development resources to put these strategies into action in their own organizations.

In accordance with the Municipal Separated Storm Sewer System (MS4) Permit issued to the District of Columbia by the United States Environmental Protection Agency (USEPA), the District Department of Transportation (DDOT) is required to retrofit areas in the city within the transportation public right of way (ROW). In this effort, the District Department of Energy and Environment (DOEE) and DDOT Infrastructure Project Management Division (IPMD) have identified four sub-watersheds located within the Anacostia watershed to be retrofitted with green infrastructure (GI) as part of the long-term stormwater management solution to improve the water quality and overall conditions of the affected tributaries. This presentation will summarize various aspects of one planning and design project implementing over 40 individual GI practices within these sub-watersheds. From planning and site selection through the detailed design process, focusing on innovative tools for site prioritization, neighborhood scale challenges surrounding community impact, and design lessons learned. Notable elements of the project are described below: Planning and Site Selection Process. An innovative GIS-based screening tool was developed using open source and utility GIS data together with system prioritization criteria to identify the optimal locations for GI systems across over 1000-acres in four sub-watersheds. The large analysis area necessitated the use of this type of tool to help rank and prioritize potential locations for GI implementation without having to manually analyze each location. Selection criteria included numerical rankings for street slopes, utility conflicts, parking impacts, street classifications, drainage areas, and tree coverage factors. This presentation will demonstrate how this challenge was overcome by using a GIS-based screening tool to screen, score and rank sites based on design and regulatory contributing factors. Figure 1 shows the scoring/ranking for GI in the subwatershed area. Outreach and Community Engagement. Public outreach efforts were initiated early in the project to share information related to the benefits of GI, potential project impacts to the community during construction and long-term, and to solicit their feedback to incorporate suggestions into the design process. Several innovative approaches were used to share this information and reach all the impacted residents during a time where in-person public meetings were not possible. Enhanced GI Design. GI designs included bioretention, permeable pavement parking lanes, permeable pavement green alleys, expanded green spaces, and other impervious area removal practices. Project implementation focused on a treatment train approach, combining multiple GI practices in series together with impervious area reductions to optimize overall benefit and performance. Several innovate approaches were implemented including incorporating multiple small-scale tree bump-outs in series along several streets with limited existing tree coverage. And providing expanded tree soil space to enhance performance and promote long-term tree health utilizing adjacent spaces under the sidewalks and adjacent areas. The use of project innovations such as a GIS-based screening tool to optimally site GI and a unique process that incorporates the use of soil volume under pavement areas for tree pit/bump-out installations provides an effective and cost-efficient way for communities to retrofit areas and maximize stormwater management options.

INTRODUCTION Arlington County (County) is implementing new biosolids management facilities at the Arlington County Water Pollution Control Plant (WPCP). The Arlington County WPCP Re-Gen Program (Program) is a comprehensive program that will include the engineering, design, construction, maintenance, startup, and operation necessary to add sustainable equipment and systems to effectively recover the County's renewable resources, produce a Class A biosolids product, and most efficiently utilize the biogas. The Program includes upgrades or replacement of nearly all existing solids handling processes. A thermal hydrolysis process (THP) followed by anaerobic digestion (AD) form the backbone of the new treatment train. The overall process flow diagram for the Facilities is shown in Figure 1. PURPOSE AND SCOPE OF STUDY The purpose of the biogas utilization evaluation is to review all feasible alternatives for the beneficial use of the biogas to assist in meeting the County's sustainability goals while also meeting the energy needs of the WPCP and then perform monetary, non-monetary, and sustainability evaluations to determine the recommended alternative for the County. It is not a stated goal of the Program to be 'cash positive' many additional factors impact the overall Program cost. The scope of the analysis included only biogas utilization portion of the Program, and not any other of the solids handling components. ALTERNATIVES DEVELOPMENT There are several options for the beneficial use of the biogas produced in AD, each with its own advantages and disadvantages including biogas conditioning requirements, capital cost, O&M requirements, financial benefits, sustainability impacts, and GHG emissions. From the potential biogas uses the following six major alternatives were developed: Alternative 1: Process and building heating Alternative 2A: CHP with Engines Alternative 2B: CHP with Turbine Alternative 3A: RNG to Pipeline Alternative 3B: RNG as CNG Alternative 4A: RNG and CHP with Engines Alternative 4B: RNG and CHP with Turbines For each of the alternatives, an energy balance was developed to help illustrate the sources and flows of energy purchased and produced. The resulting diagrams show the process and building heating requirements, electrical power requirements and production, equipment efficiencies, NG purchase, and biogas flaring for each alternative. These energy balances formed the basis for the financial, non-financial and sustainability analysis performed. FINANCIAL ANALYSIS A financial analysis focused on the financial costs over a 6-year period of construction and 25-year period of subsequent operations. Figure 2 presents the original conceptual construction cost (inclusive of contractor overhead and profit [O&P], mobilization and other preliminary costs, and contingency), and total present value of all capital and net operating costs through 2052, assuming a 3 percent discount rate. The financial analysis indicates that although Alternatives 3A and 3B (RNG alternatives) do not have the lowest capital cost, they do have the lowest total present-value cost due to the anticipated value of the RNG. In comparison, Alternatives 4A and 4B (RNG and CHP alternatives) would entail larger capital costs and comparable present-value costs when compared to Alternatives 2A and 2B (CHP alternatives). The initial present-value financial analysis supports eliminating Alternatives 4A and 4B for further consideration because of high capital costs, high overall complexity, and comparable present financial values to Alternatives 2A and 2B. NON-FINANCIAL ANALYSIS To account for non-monetary factors that impact stakeholders a comprehensive non-financial analysis was completed. This analysis included the development of evaluation criteria, shown in Table 1, and then the subsequent weighting of the criteria and scoring each alternative for those criteria. The results of the non-financial analysis are shown in Figure 3. Alternative 3A had the highest (most favorable) non-financial score at 68.2, followed by Alternative 1 at 67.5. Alternative 2B had the lowest non-financial score of 57.6. The main differentiators between the RNG alternatives (Alternatives 3A/3B) and CHP alternatives (Alternatives 2A/2B) were that the RNG alternatives had: -Lower localized emissions -Reduced noise -Increased flexibility and reduced flaring -Lower maintenance complexity -Adaptability to future opportunities SUSTAINABILTY CRITERIA The sustainability, or environmental impact, of the alternatives was identified by using the anticipated reductions of GHG emissions (namely CO2) for each alternative and using a social cost of GHG approach to monetize the reductions. The net GHG change presented is solely for the biogas utilization equipment, not the entire Program. Table 2 presents net change in GHG emissions for each of the sources of energy for 2037. Overall, Alternatives 2A, 3A, and 3B have greater emissions reductions than Alternatives 1 and 2B. COMPOSITE RESULTS To complete the analysis and understand the ultimate best use of biogas for the program the financial results, non-financial scoring and GHG emissions reduction, are combined into plots to illustrate the composite results for each alternative. Figure 4 presents the composite results of the base case scenario. Four additional scenarios were developed to reflect the variability of RIN prices, electrical prices and the social cost of carbon. For this base scenario, without considering the social cost of carbon, Alternative 3A had the highest non-financial score and the second lowest present financial value. SENSITIVITY ANALYSIS Finally, a computationally rigorous sensitivity analysis, using Monte Carlo simulation methods, was completed to assess the combined impact of changing several factors at once. Table 3 presents the limits and estimated value for variables that are included in the Monte Carlo model. Separate probability distributions are formed for each of these factors and the sources for these distributions include HDR assumptions and existing data. The results from the Monte Carlo simulation are presented as a probability distribution of possible outcomes, given the range of possible inputs of uncertain parameters. Figure 5 shows the distributions of possible present values of total financial and social outcomes for all five alternatives, in both probability density function (PDF) and cumulative density function (CDF). The CDF has a useful interpretation for decision making because it can clearly indicate the probability that a condition holds, such as if total present value of benefits exceeds costs. Figure 5 shows that Alternatives 1, 2A and 2B all have a very narrow range of potential financial values, showing that costs exceed benefits for the modeled parameters. Alternatives 3A and 3B have a wide range of potential financial values, which is a function of the uncertainty in the RNG market. However, even with the wide range, a majority of the model runs indicate a negative financial value (i.e., benefits exceed costs for the modeled parameters) for the 3A and 3B gas utilization scenarios. CONCLUSIONS AND RECOMMENDATIONS Based on the analyses presented, the Water Pollution Control Bureau (WPCB) recommends proceeding with Alternative 3 (RNG) as the selected biogas utilization approach. The basis for this recommendation is as follows: -The RNG alternatives have the lowest net present value for the baseline conditions using conservative capital and operating costs. -Alternative 3A (RNG into pipeline) scored the highest in the County's non-financial scoring. The County found that the RNG alternatives would be less complex and result in fewer localized impacts than the CHP alternatives. -A sensitivity analysis concluded that when considering multiple variables, including RIN volatility and changes to electrical rates, Alternative 3A had a very high likelihood of being more financially advantageous than Alternative 2A. -The County has the ability to retain GHG credits if the biogas is used within Arlington County for transportation purposes. Should the biogas be used outside of Arlington County, the revenue from the RINs could be used to purchase an equivalent amount of GHG credits on the open market. -Benefits of on-site CHP are limited because the CHP size would not be sufficient to power the entire WPCP and the existing WPCP has adequate stand-by power. The County's current preference is for Alternative 3A (RNG into pipeline) over Alternative 3B (RNG as CNG) due to this option's diverse opportunities for end use customers, rather than relying on a specific direct customer. However, the final decision to inject RNG into the NG utility pipeline or use CNG will be made in the future as more discussions with the stakeholders are conducted.

Throughout the United States, over 1,500 wastewater treatment plants (WWTP) are equipped with anaerobic digestion to stabilize sewage sludge into biosolids. In those facilities, the byproduct of digestion is biogas, a methane rich gas that has the potential to be used as a renewable energy source. Only a fraction of the WWTPs however utilize their biogas for renewable energy, outside of being used in boilers for process heating. If biogas is upgraded to biomethane, the gas is equivalent in quality to natural gas, only from a renewable source, then it is termed Renewable Natural Gas (RNG). Due to the environmental benefit of RNG, through GHG emission reductions and offsetting of fossil fuel natural gas, the value of RNG exceeds its energy value. With this in mind, Bartlett &amp; West teamed up with the Oakland WWTP in Topeka, KS to develop a project for upgrading their biogas to RNG. The project was funded in 2018 and fully commissioned in 2022. This presentation will outline the process details along with design considerations and performance of the design. The treatment train consists of bulk desulfurization, biogas drying and boosting, activated carbon system, compressor and 3 stage membrane carbon dioxide removal. Construction, balance of plant requirements, and the injection station interface are important factors to consider and design around. The presentation will also focus on the economics, not only on a monetary but also the environmental benefit. The capital and operating expenses are apart of the overall proforma. And the final section will cover the lessons learned throughout the 4 year journey to completion.

Introduction The Coronavirus Disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome virus 2 (SARS-CoV-2), has exposed modern society's vulnerability to infectious diseases. Reliance on clinical testing of symptomatic individuals has proven challenging due to the inability to identify asymptomatic cases and time lags between disease onset and clinical reporting to public health agencies. Wastewater surveillance is a disease-tracking tool that supports early response, such as public health decision making and vaccination efforts. Public health agencies have partnered with local officials, wastewater utilities, research institutions, and consultants to implement practical wastewater surveillance programs. CDM Smith has focused on building these partnerships to facilitate SARS-CoV-2 wastewater testing programs around the globe. Our work aims to support the use of wastewater data to inform specific public health interventions. This presentation highlights wastewater surveillance case studies at facility, neighborhood, and city scales to illustrate best practices for developing wastewater surveillance programs. Wastewater Surveillance Program Development A successful wastewater surveillance program requires collaboration between community leaders, wastewater utilities, epidemiologists, public health officials, engineers, doctors, and other scientists. Our approach to building programs relies on early engagement of these stakeholders. The team defines program objectives, devises a cost-efficient approach to wastewater sampling and analysis, develops communication plans, establishes data presentation techniques, and informs on potential public health interventions. The collaborative approach improves consensus building. Program execution focuses on gathering and presenting reliable wastewater data in a timely and effective manner. Wastewater Surveillance Case Studies CDM Smith has helped develop wastewater surveillance programs at the facility-, neighborhood-, and city-scales in the United States and Middle East with varying goals and objectives. The United States Department of Veterans Affairs developed a program to monitor eight conjugate living centers (CLCs) throughout the U.S (CA, NC, PA(2), TN, TX, WA (2)). The goal of the program was to provide an early warning system to prevent outbreaks in CLCs. From January to June 2021, CDM Smith assisted in grab sample coordination, collection, and delivery to the VA analytical laboratories in Temple Texas. The VA project showed that initial planning of sampling and shipping logistics was critical to rapid turnaround of wastewater surveillance data. The VA labs indicated the SARS-CoV-2 wastewater data was used to target testing resources and mitigate outbreaks in CLCs. In collaboration with CDM Smith, the Massachusetts Department of Health implemented facility and neighborhood programs with the objectives of identifying COVID-19 cases sooner than clinical testing and confirming absence of disease. 24-hour composite wastewater samples were collected three days per week and analyzed for SARS-CoV-2 and other sewage markers. Results are communicated via email to state and city officials, and COVID-19 case data are evaluated for correlation with wastewater virus concentrations. Local-level surveillance provided public health officials an early-warning of an outbreak in a community in eastern Massachusetts. Public health measures included mask distribution, deployment of mobile testing units, and education campaigns. A city-scale surveillance program was established in April 2020 in Detroit, Michigan, and is still ongoing. The program objective is to develop a model to predict spatial and temporal variation in COVID-19 cases based on wastewater concentrations, demographic data, and sewer conditions. Grab samples are collected weekly at 12 locations, including at the wastewater treatment plant, and analyzed for SARS-CoV-2 and other sewage markers. Results are discussed weekly with public health officials, and data are analyzed using principal components analysis. Collaborating with the United States Agency for International Development (USAID), CDM Smith helped develop city-scale surveillance programs in Amman, Jordan and Cairo, Egypt. These program building projects focused on analyzing existing research infrastructure to support sampling campaigns and analytical testing, implementing wastewater monitoring and action plans, training seminars, and data visualization dashboards. Insights from U.S. case studies were used to establish recommendations that allow international partners to manage their wastewater surveillance programs. Conclusions and Recommendations Wastewater surveillance is an effective tool to measure aggregated community-level biomarker data. The approach is being used effectively at many scales during the COVID-19 pandemic. CDM Smith's wastewater surveillance work revealed several important findings including: A successful program starts with collaboration between public health agencies, local officials, research agencies, and their partners. SARS-Cov-2 wastewater concentrations are strongly correlated with COVID-19 cases. Normalizing viral concentration data to other wastewater data is helpful to mitigate competing influences in the sewer system. Wastewater surveillance data was used to inform specific public health actions such as awareness campaigns. Development of wastewater surveillance programs can provide a proactive tool to respond to disease outbreaks, understand drug use, and measure other indicators of community health and wellbeing. Future applications of the approach include early identification and understanding of disease outbreaks, understanding antibiotic resistance, and addressing health disparities Widespread development of programs could provide public health officials a proactive tool to respond to disease outbreaks. The Centers for Disease Control and Prevention (CDC) established the National Wastewater Surveillance System (NWSS) to improve acceptance of the approach. Wastewater surveillance is being funded through a combination of federal, state, and local support.