4.5 Review

A critical review of the data pipeline: how wastewater system operation flows from data to intelligence

Journal

WATER SCIENCE AND TECHNOLOGY
Volume 82, Issue 12, Pages 2613-2634

Publisher

IWA PUBLISHING
DOI: 10.2166/wst.2020.393

Keywords

data treatment; digitalization; digital twin; metadata; wastewater modelling; water resource recovery facilities

Funding

  1. Natural Sciences and Engineering Research Council of Canada (NSERC) [RGPIN-2016-06522]
  2. Natural Sciences and Engineering Research Council of Canada (NSERC) through NSERC ES D PhD scholarship [PGSD3-519336-2018]

Ask authors/readers for more resources

Faced with an unprecedented amount of data coming from evermore ubiquitous sensors, the wastewater treatment community has been hard at work to develop new monitoring systems, models and controllers to bridge the gap between current practice and data-driven, smart water systems. For additional sensor data and models to have an appreciable impact, however, they must be relevant enough to be looked at by busy water professionals; be clear enough to be understood; be reliable enough to be believed and be convincing enough to be acted upon. Failure to attain any one of those aspects can be a fatal blow to the adoption of even the most promising new measurement technology. This review paper examines the state-of-the-art in the transformation of raw data into actionable insight, specifically for water resource recovery facility (WRRF) operation. Sources of difficulties found along the way are pinpointed, while also exploring possible paths towards improving the value of collected data for all stakeholders, i.e., all personnel that have a stake in the good and efficient operation of a WRRF.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Engineering, Environmental

Nitrification in a biofilm-enhanced highly loaded aerated lagoon

Bernard Patry, Paul Lessard, Peter A. Vanrolleghem

Summary: Nitrification in a highly loaded biofilm-enhanced aerated lagoon is mainly affected by operating temperature. Maximum nitrification is observed during the warmer months and occurs even at high organic loading rates (>5 g CBOD5/m(2) day). Compared with a simulated suspended growth system, the biofilm-enhanced lagoon shows a significantly extended nitrification period. The extension is observed at the end of the summertime maximum nitrification period. Low amounts of nitrate still produced during winter in the biofilm-enhanced aerated lagoon suggest year-long retention of autotrophic nitrifying biomass in the biofilm. Nitrification in the biofilm-enhanced aerated lagoon is negatively impacted by the presence of important quantities of accumulated solids that resuspend when their digestion starts as temperature increases.

WATER ENVIRONMENT RESEARCH (2021)

Review Water Resources

SARS-CoV-2 known and unknowns, implications for the water sector and wastewater-based epidemiology to support national responses worldwide: early review of global experiences with the COVID-19 pandemic

Kelly Hill, Arash Zamyadi, Dan Deere, Peter A. Vanrolleghem, Nicholas D. Crosbie

Summary: Wastewater surveillance of pathogens is a useful tool to assess the effectiveness of disease monitoring, providing a sensitive and rapid indicator of infection rate changes. Models can be used to back-calculate wastewater prevalence to population prevalence, as well as help design wastewater sampling strategies.

WATER QUALITY RESEARCH JOURNAL (2021)

Article Engineering, Chemical

Artificial neural networks and genetic algorithms: An efficient modelling and optimization methodology for active chlorine production using the electrolysis process

Majid Gholami Shirkoohi, Rajeshwar D. Tyagi, Peter A. Vanrolleghem, Patrick Drogui

Summary: This study evaluates the effectiveness of a modelling and optimization methodology based on artificial neural networks and genetic algorithms in predicting the behavior of an electrolysis process. Trained ANN models successfully predicted the active chlorine production and energy consumption, leading to insights on optimal operating conditions. Multi-objective optimization using genetic algorithms resulted in non-dominated optimal points for maximizing active chlorine production and minimizing energy consumption.

CANADIAN JOURNAL OF CHEMICAL ENGINEERING (2021)

Article Agricultural Engineering

Effects of ferric-phosphate forms on phosphorus release and the performance of anaerobic fermentation of waste activated sludge

Zhipeng Zhang, Qian Ping, Dan Gao, Peter A. Vanrolleghem, Yongmei Li

Summary: This study investigates the effects of different forms of Fe(III)Ps on phosphorus release and the performance of waste activated sludge (WAS) during anaerobic fermentation. The results show that Fe(III)Ps have diverse impacts on P release and the efficiency of anaerobic fermentation, with certain Fe(III)Ps even inhibiting the fermentation process.

BIORESOURCE TECHNOLOGY (2021)

Article Pharmacology & Pharmacy

Two-dimensional moisture content and size measurement of pharmaceutical granules after fluid bed drying using near-infrared chemical imaging

Michael Ghijs, Brecht Vanbillemont, Niels Nicolai, Thomas De Beer, Ingmar Nopens

Summary: Drying is a critical step in pharmaceutical wet granulation, with granule moisture content and size determining tabletting performance. Current data collection methods struggle to measure individual granule properties, but a new method using NIR-CI is developed to simultaneously characterize moisture content and size. This method has potential to gain detailed experimental insights for building robust process models.

INTERNATIONAL JOURNAL OF PHARMACEUTICS (2021)

Editorial Material Engineering, Environmental

Carbonaceous vs. total biochemical oxygen demand as a basis for WRRF design and performance monitoring

James C. Young, Peter A. Vanrolleghem

Summary: The standard 5-day biochemical oxygen demand (BOD5) measurement is widely used in designing water resource recovery facilities, but the component of nitrogenous oxygen demand (NOD) should be taken into consideration to avoid oversizing. Carbonaceous BOD (CBOD5) is more accurate for sizing aerobic treatment processes based on the biodegradation of organic constituents in wastewater. Nitrogenous oxygen demand is important for nitrogen removal processes.

WATER ENVIRONMENT RESEARCH (2021)

Article Engineering, Environmental

An influent generator for WRRF design and operation based on a recurrent neural network with multi-objective optimization using a genetic algorithm

Feiyi Li, Peter A. Vanrolleghem

Summary: Modeling, automation, and control are widely used in the upgrading and optimization of Water Resource Recovery Facilities (WRRF). The current calibration of the influent generator (IG) models needs to consider the temporal variability of the dataset and optimize it using a multi-objective genetic algorithm. The developed model can generate a probability distribution time series that better represents reality, providing a better description for the design and operation of WRRF.

WATER SCIENCE AND TECHNOLOGY (2022)

Article Engineering, Chemical

Modelling and optimization of psychoactive pharmaceutical caffeine removal by electrochemical oxidation process: A comparative study between response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS)

Majid Gholami Shirkoohi, Rajeshwar D. Tyagi, Peter A. Vanrolleghem, Patrick Drogui

Summary: This study investigated the modelling and optimization of electrochemical oxidation (EO) process for the removal of psychoactive pharmaceutical caffeine in synthetic solution and real municipal wastewater effluent. The central composite design (CCD) based on response surface methodology (RSM) and adaptive neuro fuzzy inference system (ANFIS) were used to analyze the influence of independent variables on caffeine degradation. Both CCD and ANFIS models successfully predicted the electrochemical process behavior, with the ANFIS models performing slightly better. The degradation of caffeine by the EO process followed an oxidation pathway similar to other advanced oxidation processes. The optimal conditions determined using CCD were applied to real municipal wastewater effluent, demonstrating the effectiveness of the process. However, the EO process may increase the toxicity levels of the wastewater effluent, which can be reduced by extending the electrolysis time or using granular activated carbon.

SEPARATION AND PURIFICATION TECHNOLOGY (2022)

Article Engineering, Environmental

The transition of WRRF models to digital twin applications

Elena Torfs, Niels Nicolai, Saba Daneshgar, John B. Copp, Henri Haimi, David Ikumi, Bruce Johnson, Benedek B. Plosz, Spencer Snowling, Lloyd R. Townley, Borja Valverde-Perez, Peter A. Vanrolleghem, Luca Vezzaro, Ingmar Nopens

Summary: Digital Twins (DTs) are innovative and powerful technologies that utilize digitalization in the WRRF sector. However, the lack of consensus and understanding regarding the definition, perceived benefits, and technological needs of DTs hinders their widespread development and application in this field. This paper provides an overview of the state-of-the-art, challenges, good practices, development needs, and transformative capacity of DTs for WRRF applications.

WATER SCIENCE AND TECHNOLOGY (2022)

Article Engineering, Environmental

Mainstream short-cut N removal modelling: current status and perspectives

Gamze Kirim, Kester McCullough, Thiago Bressani Ribeiro, Carlos Domingo-Felez, Haoran Duan, Ahmed Al-Omari, Haydee De Clippeleir, Jose Jimenez, Stephanie Klaus, Mojolaoluwa Ladipo-Obasa, Javad Mehrani, Pusker Regmi, Elena Torfs, Eveline I. P. Volcke, Peter A. Vanrolleghem

Summary: This article provides an overview of the current state-of-the-art in modelling short-cut nitrogen removal processes in mainstream wastewater treatment, identifying future research directions and challenges. The importance of mathematical models in considering N2O emissions and the need for new, advanced approaches are emphasized.

WATER SCIENCE AND TECHNOLOGY (2022)

Article Engineering, Environmental

An essential tool for WRRF modelling: a realistic and complete influent generator for flow rate and water quality based on data-driven methods

Feiyi Li, Peter A. Vanrolleghem

Summary: A new data-driven influent generator (IG) model is proposed in this study, which only uses routine data and weather information without the need for additional data collection. The model can generate reliable flowrate and quality data at different time scales and resolutions.

WATER SCIENCE AND TECHNOLOGY (2022)

Review Engineering, Environmental

Artificial intelligence techniques in electrochemical processes for water and wastewater treatment: a review

Majid Gholami Shirkoohi, Rajeshwar Dayal Tyagi, Peter A. Vanrolleghem, Patrick Drogui

Summary: This paper reviews the application of artificial intelligence techniques in water and wastewater treatment processes, specifically focusing on electrochemical processes. The study highlights the importance of reliability and robustness of the AI models developed using techniques such as artificial neural networks and support vector machines.

JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE AND ENGINEERING (2022)

Article Environmental Sciences

Influence of MBBR carrier geometrical properties and biofilm thickness restraint on biofilm properties, effluent particle size distribution, settling velocity distribution, and settling behaviour

Raheleh Arabgol, Peter A. Vanrolleghem, Robert Delatolla

Summary: This study evaluates the influence of carrier geometric properties and biofilm thickness levels on the characteristics and settleability of solids in the moving bed biofilm reactor (MBBR) system. The ViCAs method is used to assess particle settling velocities in the MBBR effluent, combined with microscopy imaging to relate particle size distribution to settling velocity. The results show that the commonly used AnoxK TM K5 carrier demonstrates different biofilm characteristics and settling behavior compared to the newly designed thickness-restraint carriers (AnoxK TM Z-carriers). Furthermore, statistical analysis confirms that different carrier types and biofilm thickness levels have significant effects on biofilm characteristics and particle settling properties in the MBBR system.

JOURNAL OF ENVIRONMENTAL SCIENCES (2022)

Article Engineering, Environmental

Machine learning for modeling N2O emissions from wastewater treatment plants: Aligning model performance, complexity, and interpretability

Mostafa Khalil, Ahmed Alsayed, Yang Liu, Peter A. Vanrolleghem

Summary: This study develops a comprehensive approach for using machine learning to perform online process modeling of N2O emissions, providing operators with the insights needed for informed corrective actions. By employing feature selection and parametric multivariate outlier removal methods, the complexity and data collection cost of modeling are reduced without significant effect on accuracy. The highest performing models are kNN, AdaBoost, and DNN.

WATER RESEARCH (2023)

Article Engineering, Environmental

Including snowmelt in influent generation for cold climate WRRFs: comparison of data-driven and phenomenological approaches

Feiyi Li, Peter A. Vanrolleghem

Summary: A data-driven methodology is proposed in this study to create an influent generator (IG) model that accurately describes the influent flow and water temperature dynamics under the impact of snowmelt in cold climate conditions. The performance of the model is evaluated and compared with a phenomenological model, showing that the proposed model has better accuracy.

ENVIRONMENTAL SCIENCE-WATER RESEARCH & TECHNOLOGY (2022)

No Data Available