Defining the opportunity space for a novel modular system for distributed treatment of food and beverage industry wastewaters

Wastewater treatment is estimated to account for 1-3% of a nation's total electric energy consumption, with the energy needed for aeration and biosolids disposal being significant contributing factors. Anaerobic pretreatment of high strength food and beverage industry wastewater presents a unique opportunity for resource recovery and has the potential to achieve energy positive wastewater treatment. The Modular Encapsulated Two-stage Anaerobic Biological (METAB) system is an emerging technology for distributed treatment of high strength food and beverage industry wastewaters and the production of hydrogen (H2) and methane (CH4). The METAB system also lowers COD loads to centralized wastewater resource recovery facilities (WRRFs), directly reducing their operational costs and energy demand. A critical barrier in industry adoption of METAB systems lies in the identification of optimal contexts for deployment. The primary aim of the study is to evaluate the financial viability and environmental impacts of METAB systems in different deployment contexts. To this end, a series of contextual parameters – including the configuration of existing centralized WRRF, the high-strength wastewater composition, and local utility costs – were intentionally varied to represent the range of potential deployment scenarios for the METAB system. The modelled WRRFs are representative of plant layouts typically seen in North America, and are designed for varying degree of treatment (e.g., BOD removal, nitrification, and biological nutrient removal). Activated Sludge Model No. 2D (ASM2d) and a modified version of Anaerobic Digestion Model No 1 (mADM1), which includes Phosphorous (P) transformations, are used to model biological process. ASM2d, mADM1, and mADM1-ASM2d interfaces have been employed to allow plant wide P simulations. QSDsan, an open-source, community-led platform specializing in quantitative sustainable design (QSD) of sanitation and resource recovery system has been used to model the coupled METAB-WRRF systems under consideration. The uncertainty of each contextual parameter was characterized and incorporated into the Monte Carlo simulations of the modelled WRRFs. For each WRRF configuration, the savings in operational costs and reduction in GHG emissions after METAB deployment were quantified over a range of industrial COD loadings. We find that METAB deployment presents greater economic and environmental incentives for pretreatment of industrial wastewaters with higher COD loading at WRRFs aiming for less energy intensive treatment, such as BOD removal or nitrification. In WRRFs designed for biological nutrient removal (BNR), we find that METAB deployment leads to net increase in operational costs, while net emissions are reduced only after crossing a threshold for industrial organic loading. The main drivers of operational cost savings and GHG emission reduction were identified by obtaining spearman correlation rank coefficients against the continuously varying contextual parameters. Operational cost savings were found to be most sensitive to unit cost of sludge disposal, unit cost of electricity, blower efficiency, and unit cost of external carbon addition (if required), but their relative importance varies across configurations. For reduction in GHG emissions, emission factors (EFs) of CH4 and N2O during treatment, EF of electricity, and EF of acetic acid are the critical contextual parameters.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Environ Engr in Civil Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2024

Author dc:creator

• Rai, Saumitra

Contributors dc:contributor

• Guest, Jeremy S

• Keyword One: Anaerobic Pretreatment
• Keyword Two: Industrial Wastewater Treatment
• Keyword Three: Quantitative Sustainable Design (qsd)
• Keyword Four: Plant Wide P Modelling
• Keyword Five: Deployment Scenario Analysis

Statement dc:rights

• Copyright 2024 Saumitra Rai

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/125832

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F125832