Enabling wastewater treatment process automation: leveraging innovations in real-time sensing, data analysis, and online controls

Zhang, Wenjin; Tooker, Nicholas B.; Mueller, Amy

doi:10.1039/d0ew00394h

Cited by 35 publications

(39 citation statements)

References 102 publications

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“…For NH 4 -N removal, aerobic and anoxic biological nutrient removal (BNR) strategies have commonly been employed in centralized treatment plants. In these large-scale settings, BNR works very well because parameters such as dissolved oxygen (DO), pH, and oxidation/reduction potential (ORP) can be precisely monitored and controlled by operators, and where the costs of operation are generally non-prohibiting ( Moore, 2009 ; Zhang et al, 2020 ). Newer methods, such as partial nitritation/anammox, have also been implemented at full-scale treatment plants to treat high strength nitrogen wastewater.…”

Section: Introductionmentioning

confidence: 99%

“…However, performance is highly influenced by the varying influent solids concentration and maintaining precise DO levels in the system is critical ( Lackner et al, 2014 ; Vlaeminck et al, 2009 ). For small-scale NSSS, aerobic and anoxic BNR processes have limited application due to their high energy demand for operation, the requirement of high precision control, the availability of reliable small-scale sensors for system monitoring, and the intermittent nature of NSSS ( WSDH, 2005 ; Zhang et al, 2020 ). Furthermore, these BNR processes typically do not recover nitrogen for downstream reuse.…”

Section: Introductionmentioning

confidence: 99%

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Performance and onsite regeneration of natural zeolite for ammonium removal in a field-scale non-sewered sanitation system

Castro

Shyu

Xaba

et al. 2021

Science of The Total Environment

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Natural zeolite clinoptilolite was used as the primary ammonium removal method from the permeate of an anaerobic membrane bioreactor (AnMBR) treating high-strength blackwater generated from a community toilet facility. This zeolite-based nutrient capture system (NCS) was a sub-component of a non-sewered sanitation system (NSSS) called the NEWgenerator and was field tested for 1.5 years at an informal settlement in South Africa. The NCS was operated for three consecutive loading cycles, each lasting 291, 110, and 52 days, respectively. Both blackwater (from toilets) and blackwater with yellow water (from toilets and urinals) were treated during the field trial. Over the three cycles, the NCS was able to remove 80 ± 28%, 64 ± 23%, and 94 ± 11%, respectively, of the influent ammonium. The addition of yellow water caused the rapid exhaustion of zeolite and the observed decrease of ammonium removal during Cycle 2. After Cycles 1 and 2, onsite regeneration was performed to recover the sorption capacity of the spent zeolite. The regenerant was comprised of NaCl under alkaline conditions and was operated as a recycle-batch to reduce the generation of regenerant waste. Modifications to the second regeneration process, including an increase in regenerant contact time from 15 to 30 h, improved the zeolite regeneration efficiency from 76 ± 0.7% to 96 ± 1.0%. The mass of recoverable ammonium in the regenerant was 2.63 kg NH 4 -N and 3.15 kg NH 4 -N after Regeneration 1 and 2, respectively. However, the mass of ammonium in the regenerant accounted for only 52.8% and 54.4% of the estimated NH 4 -N originally sorbed onto the zeolite beds after Cycles 1 and 2, respectively. The use of zeolite clinoptilolite is a feasible method for ammonium removal by NSSS that observe variable nitrogen loading rates, but further research is still needed to recover the nitrogen from the regenerant waste.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance and onsite regeneration of natural zeolite for ammonium removal in a field-scale non-sewered sanitation system

Castro

Shyu

Xaba

et al. 2021

Science of The Total Environment

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“…Although EWQMS alone do not provide DR services, they can be customized to receive signals from the electric grid to advance their role as an energy management tool. However, sensor‐driven systems such as EWQMS can still benefit from advancements in sensor sensitivity and operational range to help decrease response times to changes in water quality (Allen et al, 2016; Cloete, Malekian, & Nair, 2016; Suciu, Vintea, Arseni, Butca, & Suciu, 2015; Umberg & Allgeier, 2013; W. Zhang, Tooker, & Mueller, 2020). Thus, services like EWQMS that offer an opportunity to exploit the flexibility of water and wastewater treatment systems while still maintaining water quality as a principal concern need additional research and development. Utilizing on‐site generation resources: An on‐site generation unit can decrease electricity purchased from the grid.…”

Section: Dr Research Efforts and Applications In The Water And Wastewater Sectorsmentioning

confidence: 99%

Leveraging thewater‐energynexus to derive benefits for the electric grid throughdemand‐sidemanagement in the water supply and wastewater sectors

et al. 2021

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Leveraging the potential flexibility of large electrical loads has become an attractive option for maintaining grid reliability, especially in electric grids with high penetrations of variable renewable energy. The water sector is a particularly attractive option for demand‐side flexibility due to its vast water storage infrastructure, large interruptible pumping loads, and energy generation opportunities. Shifting the timing of water supply and wastewater utility operations can reduce peak load and temporally align energy‐consuming activities with periods of cheap electricity prices and/or high renewable energy generation. This paper presents a general overview of demand‐side management strategies in water and wastewater systems, focusing primarily on demand‐response measures. We find that while there is consensus in the literature about the potential for water systems to provide flexible demand‐side management services, there is a need for developing comprehensive water‐energy models to examine the value of load management as a source of revenue for water utilities and as a source of flexibility for the electric grid. More experimental studies and simulation efforts are also needed to address the technical complexities and water quality concerns associated with interrupting water and wastewater utility operations. This article is categorized under: Engineering Water > Sustainable Engineering of Water Engineering Water > Planning Water

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“…Fulfilling this initiative heavily relies on trustable water sensors to monitor multiplex physicochemical and biochemical reactions occurring in water and wastewater streams, a spatiotemporal data processing capability to promptly process numerous types of data collected at varying time frames, and a hyperspectral data application to interpret and apply sensor data into diverse water systems. 12 − 14 …”

Section: Introductionmentioning

confidence: 99%

Forward-Looking Roadmaps for Long-Term Continuous Water Quality Monitoring: Bottlenecks, Innovations, and Prospects in a Critical Review

Huang

Wang

Xiang

et al. 2022

Environ. Sci. Technol.

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Long-term continuous monitoring (LTCM) of water quality can bring far-reaching influences on water ecosystems by providing spatiotemporal data sets of diverse parameters and enabling operation of water and wastewater treatment processes in an energy-saving and cost-effective manner. However, current water monitoring technologies are deficient for long-term accuracy in data collection and processing capability. Inadequate LTCM data impedes water quality assessment and hinders the stakeholders and decision makers from foreseeing emerging problems and executing efficient control methodologies. To tackle this challenge, this review provides a forward-looking roadmap highlighting vital innovations toward LTCM, and elaborates on the impacts of LTCM through a three-hierarchy perspective: data, parameters, and systems. First, we demonstrate the critical needs and challenges of LTCM in natural resource water, drinking water, and wastewater systems, and differentiate LTCM from existing short-term and discrete monitoring techniques. We then elucidate three steps to achieve LTCM in water systems, consisting of data acquisition (water sensors), data processing (machine learning algorithms), and data application (with modeling and process control as two examples). Finally, we explore future opportunities of LTCM in four key domains, water, energy, sensing, and data, and underscore strategies to transfer scientific discoveries to general end-users.

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Enabling wastewater treatment process automation: leveraging innovations in real-time sensing, data analysis, and online controls

Abstract: The primary mandate of wastewater treatment facilities is the limitation of pollutant discharges, however both tightening of permit limits and unique challenges associated with improving sustainability (i.e., resource recovery) demand innovation.

Cited by 35 publications

References 102 publications

Performance and onsite regeneration of natural zeolite for ammonium removal in a field-scale non-sewered sanitation system

Performance and onsite regeneration of natural zeolite for ammonium removal in a field-scale non-sewered sanitation system

Leveraging thewater‐energynexus to derive benefits for the electric grid throughdemand‐sidemanagement in the water supply and wastewater sectors

Forward-Looking Roadmaps for Long-Term Continuous Water Quality Monitoring: Bottlenecks, Innovations, and Prospects in a Critical Review

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