Evaluation of the integration of emerging sanitation technologies in centralized wastewater treatment systems

Jain, Nehal

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https://hdl.handle.net/2142/129781 Copy

Description

Title

Evaluation of the integration of emerging sanitation technologies in centralized wastewater treatment systems

Author(s)

Jain, Nehal

Issue Date

2025-05-08

Director of Research (if dissertation) or Advisor (if thesis)

Guest, Jeremy S

Department of Study

Civil & Environmental Eng

Discipline

Environ Engr in Civil Engr

Degree Granting Institution

University of Illinois Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Centralized wastewater treatment
• Urine diversion

Abstract

Centralized wastewater infrastructure in the U.S. faces critical challenges - aging systems, chronic underinvestment, operational overloading, and climate-induced vulnerabilities - that impair treatment efficacy and lead to regulatory non-compliance and environmental externalities. Integration of emerging non-sewered sanitation (NSS) technologies with traditional treatment facilities offer systemic improvements, enhance resilience and sustainability of wastewater management. Source separation of urine is one such NSS technology that reduces nutrient loads to centralized water resource recovery facilities (WRRFs), directly influencing the operational costs and energy demands. It is therefore essential to benchmark integrated urine diversion (UD) systems against conventional wastewater treatment processes. The primary aim of this study is to investigate how upstream urine diversion influences the key operational and environmental metrics – namely, costs and greenhouse gas (GHG) emissions – at centralized WRRFs. The modeled WRRF is a representative configuration targeting biological nutrient removal (BNR). Modified versions of Activated Sludge Model No. 2D and Anaerobic Digestion Model No. 1 (mASM2d and ADM1p, respectively), which include phosphorus (P) transformations, are used to model the biological processes. Plant-wide P dynamics were modeled using interfaces that transition between the two process models. QSDsan, an open-source, community-led, Python-based platform tailored to the quantitative sustainable design (QSD) of sanitation and resource recovery systems is used to model the WRRF configuration coupled with UD. Monte Carlo simulations were performed to evaluate two scenarios - conventional (without UD) and with full UD - under uncertainty. Results show that integrating UD leads to significant reductions in operational costs (~27%) and GHG emissions (~38%) at BNR facilities. The key drivers of operational costs and GHG emissions were identified by obtaining the Spearman’s rank correlation coefficients of these metrics with the continuously varying contextual parameters. Result of the sensitivity analysis revealed that operational costs were primarily influenced by the unit cost of electricity, which also remained the most significant driver of cost reductions following urine diversion. In parallel, the emission factor (EF) for N2O during secondary treatment was the key determinant of GHG emissions and continued to dominate the sensitivity of emission reductions post-diversion.

Graduation Semester

2025-05

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/129781

Copyright and License Information

Copyright 2025 Nehal Jain

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