With the abundance of data availability across treatment facilities, artificial intelligence is paving the way for unique optimization opportunities. The examples provided encompass the Agua Nueva Water Reclamation Facility (WRF), which concentrates on minimizing aeration energy expenses and enhancing nutrient management, as well as the Wilmington WWTF, emphasizing the optimization of disinfection chemicals. Several artificial intelligence (AI) and Bayesian modeling frameworks were developed with both sites using AI algorithms with mean absolute percentage errors < 10% for both forecasting of future conditions at a facility, as well as causal inferencing for predicting water quality. Post deployment, both sites are regularly achieving anywhere from 10-30% savings in energy or chemical usage. These case-study demonstrates significant progress in the successful implementation of AI at a treatment facility and the ability to aid in the empowerment of treatment plant operators while improving efficiencies in wastewater treatment.

Disposal of high-salinity concentrate generated from municipal facilities and industries (e.g., energy, semiconductor facilities) can have adverse environmental impacts. To address this issue, concentrate treatment seems to be a promising option to eliminate the wastewater discharge, while recovering extra water and valuable materials such as salts. This can be achieved through concentrate minimization and zero liquid discharge strategies. This paper presents six case studies that were implemented in the industrial and municipal sectors across the country to minimize concentrate, increase water recovery, and extract valuable resources.

Charlotte Water, located in Charlotte North Carolina, is the largest sewer utility in the Carolinas with approximately 4,500 miles of gravity sewer. Charlotte has been implementing a substantial and aggressive long-term sanitary sewer rehabilitation program to reduce sewer system overflows (SSOs), correct historic maintenance problems, and reduce infiltration and inflow (I/I) into aging sewers. Charlotte’s rehabilitation program has a current annual budget of about $26 million, including an annual budget of approximately $10 million for small diameter sewer rehabilitation and approximately $6 million for large diameter sewer rehabilitation. Charlotte has developed a specific, systematic rehabilitation program and approach to renew and restore the sewer system. Charlotte’s rehabilitation approach has been focused on expediting the identification and prioritization of sewers to be rehabilitated and minimizing the lengthy review, analysis, evaluation, and reporting that is often done when implementing sewer rehabilitation programs. This paper presents Charlotte’s streamlined design and construction process.

The City of Fort Lauderdale experienced a series of breaks along its aging sewer transmission main, spilling millions of gallons of sewage into the City's waterways. To solve the problem, the City decided to replace its main transmission line by constructing over 7 miles (11.26 km) of pressure forcemain to serve as a redundant line to convey 64 million gallons per day (mgd) (242,266 m3 /day) to its wastewater treatment plant. The new line was constructed mostly utilizing trenchless technologies to minimize disruptions through downtown Fort Lauderdale and minimize traffic impacts across major County and State roadways. The $65 million dollar project was fast-tracked; it was procured, designed, permitted, constructed and placed into operation in under 18-months. The entire project was built within highly developed urban corridors, downtown areas and business districts.

With the abundance of data availability across treatment facilities, artificial intelligence is paving the way for unique optimization opportunities. The examples provided encompass the Agua Nueva Water Reclamation Facility (WRF), which concentrates on minimizing aeration energy expenses and enhancing nutrient management, as well as the Wilmington WWTF, emphasizing the optimization of disinfection chemicals. Several artificial intelligence (AI) and Bayesian modeling frameworks were developed with both sites using AI algorithms with mean absolute percentage errors < 10% for both forecasting of future conditions at a facility, as well as causal inferencing for predicting water quality. Post deployment, both sites are regularly achieving anywhere from 10-30% savings in energy or chemical usage. These case-study demonstrates significant progress in the successful implementation of AI at a treatment facility and the ability to aid in the empowerment of treatment plant operators while improving efficiencies in wastewater treatment.

Sludge processing plays a key role in the energy balance (i.e., energy consumption; energy generation) of a sustainable water resource recovery facility. To this end, several advanced sludge conditioning technologies are increasingly being considered to improve this balance and to facilitate offsite management of the biosolids. This paper summarizes the evaluation of two of advanced sludge processing technologies, thermal and microbial hydrolysis processes, as part of ongoing efforts to further optimize the energy profile and overall sustainability of a large WRRF required to meet stringent effluent nutrient requirements.

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.