Pathways to Water Sector Decarbonization, Carbon Capture and Utilization

The global transition to net-zero emissions necessitates the integration of clean hydrogen as a key solution.To facilitate the required expansion of clean hydrogen production, sustainable water sources are required to support the electrolysis process. Utilizing nontraditional water sources such as water resource recovery facility (WRRF) effluents could potentially alleviate the water constraints and create cobenefits, but the realworld feasibility has not been explored in depth. Here, we investigated the geospatial interplay between WRRFs and H 2 users in a clean hydrogen economy. We developed an optimization framework for contiguous U.S. that would identify H 2 users-WRRF pairing through techno-economic constraint and multicriteria decision analysis, and we found that utilizing reclaimed water from WRRFs could save 66% (62−99%) of freshwater for clean hydrogen economy while accumulating $758 (275−1162) million annual national cost savings. The added benefits from H 2 users to WRRFs such as pure oxygen aeration would provide a compelling new opportunity for infrastructural symbiosis but warrant a future investigation on its technical and economic feasibilities.

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A Holistic Evaluation of Multivariate Statistical Process Monitoring in a Biological and Membrane Treatment System

Newhart

Klanderman

Hering

et al. 2023

ACS EST Water

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Unsupervised process monitoring for fault detection and data cleaning is underdeveloped for municipal wastewater treatment plants (WWTPs) due to the complexity and volume of data produced by sensors, equipment, and control systems. The goal of this work is to extensively test and tune an unsupervised process monitoring method that can promptly identify faults in a full-scale decentralized WWTP prior to significant system changes. Adaptive dynamic principal component analysis (AD-PCA) is a dimension reduction method modified to address autocorrelation and nonstationarity in multivariate processes and is evaluated in this work for its ability to continuously detect drift, shift, and spike faults. For spike faults, univariate drift faults, and multivariate shift faults, implementing AD-PCA on data that are subset by treatment processes and operating states with significant differences in covariates and whose model parameters use week-long training windows, moderate cumulative variance, and a high threshold for detection was found to detect faults prior to existing operational thresholds. To improve the consistency with which the AD-PCA method detects out-of-control conditions in real time, additional work is needed to remove outliers prior to model fitting and to detect multivariate drift faults in which the covariates change slowly.

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Pathways to Water Sector Decarbonization, Carbon Capture and Utilization

Cited by 5 publications

References 674 publications

The convergence of lactic acid microbiomes and metabolites in long-term electrofermentation

The convergence of lactic acid microbiomes and metabolites in long-term electrofermentation

Water Resource Recovery Facilities Empower the Electrolytic Hydrogen Economy

A Holistic Evaluation of Multivariate Statistical Process Monitoring in a Biological and Membrane Treatment System

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