This manuscript summarizes the past 18 months of deploying a predictive operational dashboard leveraging machine learning (ML) to forecast inflow into Citizens Energy Group’s DigIndy Tunnel system. We will present our lessons learned in the deployment of the ML tool in the cloud, managing the ML tool, and the integration of meter data to evaluate the accuracy of the forecast. Citizens Energy Group is the combined water, wastewater, natural gas, steam, and chilled water utility in Indianapolis. Citizens is presently implementing a 20-year CSO consent decree with required completion in 2025. Consent decree compliance is primarily achieved through the DigIndy Tunnel system, a 28-mile long, 18-foot diameter tunnel network. Citizens is also implementing a pair of storage facilities in the Upper White River and Upper Pogues Run watersheds. Our ML tool consists of an artificial neural network fit to long-term datasets to predict inflows to the DigIndy Tunnel using the 72-hour NOAA radar rainfall forecast (Sutton et. al, 2022). The neural network and automated tools to obtain actual gauged rainfall and metered tunnel inflow are fully contained within Citizens’ Azure Synapse enterprise cloud environment, with data storage in Azure Data Lake. The forecasted rainfall and tunnel inflow and actual data is presented in an online Power BI dashboard hosted in Citizens’ enterprise architecture that is accessible to all engineering and operations staff.

The F. Wayne Hill Water Resources Center (FWHWRC) is Gwinnett County’s largest and most advanced wastewater treatment facility with a capacity of 60 MGD (maximum month). The FWHWRC utilizes enhanced biological phosphorus removal (EBPR) and chemical trim to meet a stringent effluent TP limit of 0.08 mg/L. This paper will discuss details of efforts undertaken to address impacts on full-scale plant operations, primarily resulting from changes in the collection system related to odor and corrosion control chemicals, that further influenced raw wastewater characteristics.

The City of Grand Rapids Water Resource Recovery Facility (WRRF) had only one option for biosolids management that relied on landfill disposal of un-stabilized wastewater residuals. A long-term strategy was developed that implemented an anaerobic digestion approach consistent with sustainability and environmental stewardship goals. A project was commissioned in 2018 to design and construct a Biodigestion with Combined Heat and Power Recovery facility with a Renewable Natural Gas (RNG) Conditioning system. The biogas from the process is refined with a renewable natural gas conditioning system and subsequently sold to the utility company. The combined heat and power system produces heat for the digestion process and provides electricity that is utilized within the plant to offset the power needs of the WRRF operation. The facilities have been constructed and operational for nearly 12 months and this is the first WRRF in Michigan to convert biogas to utility grade RNG.

In 2019 the author wrote a manuscript for the Water Environment Federation Residuals and Biosolids Conference titled, “RIN and California LCFS Credit Revenue from Electric Vehicle Fueling with Biogas Fueled Combined Heat and Power.” The manuscript included a comprehensive analysis of the EPA-directed Renewable Fuel Standard (RFS) program, with specific emphasis on the electricity Renewable Identification Number (eRIN) pathway, and the California Low Carbon Fuel Standard directed by the California Air Resources Board (CARB). Since the 2019 paper was authored, CARB finalized rulemaking for biogas to electric vehicle charging credits. In December 2022, EPA submitted proposed changes to the RFS to activate the eRIN pathway, increase Renewable Volume Obligations (RVOs) for 2023-2025, and streamline the accounting protocol for utilities co-processing multiple feedstocks (e.g., wastewater residuals that qualify for D3 RINs and food waste and fats oils and grease (FOG) that qualify for D5 RINs). In a recent update in June 2023, EPA delayed the activation of the eRIN pathway due “a wide variety of comments on all aspects of the proposed eRIN program.” The intent of this manuscript is two-fold: 1) in anticipation of finalization of EPA RFS rulemaking regarding these matters, to chronicle those changes and summarize them for entities to assist them in understanding how to leverage the credits, and 2) through the process of developing the manuscript, advocate for biogas generators to achieve maximum credit value through a streamlined process. The manuscript will document the proposed changes, the comment-period process, and EPAs anticipated finalization of the rules in 2023 for implementation in January 2024. The outcomes of the rulemaking as well as the RVO updates will have critical implications for biogas generators looking to realize RIN credits for both renewable natural gas (RNG) and combined heat and power (CHP) production. See Figure 1 illustrating the biogas to energy options for wastewater utilities.

The utility industry is faced with the challenge of providing reliable treatment, distribution, and collection of water/wastewater services to a large infrastructure of customers, while being good environmental stewards. Thousands of assets comprise the treatment, distribution, and collection system across multiple facilities. Standard equipment operation is critical to providing customers with high quality water/wastewater services that meet regulatory requirements. To ensure proper operation of critical equipment, a PM strategy is utilized at KUB. Multiple resources are utilized when executing preventive maintenance, such as labor, materials, and equipment, among others. Aligning resources in an optimized manner can be challenging. A common method for solving optimization problems such as scheduling is linear programming. This paper discusses the utilization of a linear program to define an optimized PM schedule for the water and wastewater treatment plants, and the sustainment of the gains through tracking KPIs.

Biomethanation is a power-to-gas technology that converts H2 and CO2 from biogas into renewable natural gas (i.e., CH4). In conventional biomethanation, H2 is produced via water electrolysis, while biogas is injected directly into the biomethanation reactor. Given that biogas contains about 65% CH4 and only about 35% CO2, the contained CH4 causes a dilution effect which limits the conversion efficiency of CO2. We propose a novel electrochemical reactor for simultaneous H2 production and CO2 capture. The captured CO2 is then routed to the downstream biomethanation reactor together with the H2, thus enabling for highly efficient biomethanation with reduced footprint.

Geosyntec was retained by a confidential client to perform an alternatives evaluation for the treatment of process wastewater at their rum distillery located in the Caribbean (the Site). The existing Anaerobic Filter (AF) reactors at the Site need replacement due to their high maintenance costs and frequent media replacement. Our client was looking for the most costeffective and technologically advanced replacement technology to manage their wastewater. After reviewing and discussing proposed solutions with our client and reaching out to several technology providers/vendors, as well as evaluating cost and non-cost criteria, the project team agreed upon the best technical solution and vendor for the facility. However, to confirm the design COD loading rate, process performance and stability, robustness after down time, and to optimize operating costs, the selected vendor performed laboratory testing on the Site wastewater with technical oversight from Geosyntec.

The City of Los Angeles, California saw an opportunity for improvement through redeveloping the land adjacent to the Los Angeles River (previously used for warehousing, vehicle repair, and fueling operations) to a Park to increase the total recreation center acreage to about ten acres and to implement environmentally positive water quality improvements systems to minimize harmful pollutants in the area. Some key construction items included inspection of underground vault units, subgrade preparation, and placement of geotextiles and liners as well as keeping the local community informed through constant communication. Redevelopment can create and/or add to community assets while also benefitting the environment, thus elevating the quality of life for surrounding members of the community.

The reliability of manufacturing equipment is critical for ensuring the productivity and energy efficiency of a manufacturing facility. An unexpected machine breakdown may lead to unexpected downtime, disruption of the process schedule, lower production efficiency, and higher operation and maintenance cost. The recent development in machine learning and artificial intelligence enables data-driven Predictive Maintenance (PdM) by means of perceiving the dynamics of manufacturing systems and abstracting them into learnable features to provide a better interpretation of machine failures or unplanned downtimes. Often, vibration is used as a proxy for an early indicator of impending failure. In this study, tri-axial acceleration data collected from biogas compressors are utilized. PdM-based strategies for machine condition monitoring and smart scheduling of equipment maintenance using an anomaly scoring model are discussed. This study exploresincorporating smart manufacturing concepts into Water Resource Recovery Facilities (WRRFs) by implementing non-intrusive sensors and edge computing.

Nowadays, earth's resources have been depleting faster than they can be replenished. With water resources as no exception, the shift toward sustainable wastewater treatment plants (WWTPs) has become a necessity rather than a choice. For this reason, there has been a restored interest in the two-stage A/B scheme. In this scheme, the A-stage process has a pivotal role to play in organics and nutrients diversion and achieving low energy expenditures in the B-stage. Despite its major advantages, SRT-based control has failed to maintain stable performance of the process due to the limited knowledge of the effect of other operational parameters. This study, for the first time, provides evidence that operational conditions (i.e., SRT, HRT, DO concentration) can be engineered to balance three objectives from the A-stage process including organics diversion, phosphorus removal, and facilitate nutrients removal in the B-stage.

Moving-bed biofilm reactors (MBBRs) can be used for anaerobic wastewater treatment. This work demonstrates the applicability of anaerobic MBBRs (AnMBBRs) for industrial wastewater treatment. The literature on wastewater treatment with AnMBBRs was reviewed. Laboratoryscale AnMBBRs (4L, AnoxK™5 or Z carriers) were evaluated for treating two industrial wastewaters: one oil-contaminated wastewater (36 gCOD/L) and a food-factory wastewater (882-3190mgCOD/L). AnMBBRs can treat various wastewaters with high removals, stability, and flexibility in operating conditions. AnMBBRs can treat both easily degradable (Foodbeverage: breweries, wineries, diaries) and more difficult-to-degrade wastewaters (Textile, pulp and paper, and oil and gas sectors). Both mesophilic (37°C) and thermophilic (50°C) AnMBBRs achieved COD reductions around 60% (HRT=30d) treating the oil-contaminated wastewater; however, mesophilic conditions ensured higher removals (67%COD) and methane yields at higher loads (1.1kgCOD/m3 d). The AnMBBRs achieved CODsoluble removals >86% treating the food-factory wastewater. Thinner biofilms (200μm-Z-200 carrier) led to lower removals (51- 60%CODsoluble) due to limited biomass inventory.

Due to its ability to decarbonize hard-to-electrify sectors, green hydrogen production projects are being built across the United States and several other countries. Although this technology constitutes a promising tool in the decarbonization portfolio, the high capital and operational expenses are the main obstacles in its wide-scale commercial implementation. By recovering the by-products from the electrolysis process, such as oxygen and waste heat, there is the potential to reduce the costs tied to green hydrogen production, while decarbonizing the operation of WRRFs. The City of Saint Cloud initiated a 2023 study to assess the potential to recover by-products from the hydrogen produced via electrolysis powered by renewable energy sources. Through this case study, this paper discusses the benefits of producing green hydrogen to aid in decarbonizing WRRFs and local industries; the practical considerations for capturing the waste by-products; and the challenges of cost-effectively integrating electrolyzers into existing WRRFs.