TY - JOUR
T1 - Sustainable circularity and intelligent data-driven operations and control of the wastewater treatment plant
AU - Matheri, Anthony Njuguna
AU - Mohamed, Belaid
AU - Ntuli, Freeman
AU - Nabadda, Esther
AU - Ngila, Jane Catherine
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/6
Y1 - 2022/6
N2 - Rapid urbanization, population increase, emerging contaminants and increasing water scarcity have put a major constraint on the wastewater treatment system. Scarcity of water is steering current way of water recycle, and the drive focus towards resource recovery. Zero waste pathway in circular bioeconomy can bring transformation of wastewater commercialization by adding value with resource recovery. The complex biological reactions, unforeseen microbial behaviours, lack of reliable on-line instrumentation, complex modelling, lack of visualize techniques, low-quality industrial measurements and highly time-varying intensive data-driven operations call for the intelligence techniques and operations. The study is a review of sustainable circularity and intelligent data-driven operations and control of the wastewater treatment plant. Water surveillance and monitoring, circular economy and sustainability, automation pyramid, digital transformation, artificial intelligence, data pipeline, digital twin, data mining, and data-driven visualization, cyber-physical systems and water-energy-health management were reviewed. The deployment of the digital systems has evidently proven to bridges the gap between the data-driven soft sensor, operation and control systems in WWTP. Accurate prediction of the WWTP variables can support process design and control, reduce operation cost, improve system reliability, predictive maintenance and troubleshooting, increase water quality, increase stakeholder's engagement and endorse optimization of the plant performance. This procures the best compliance with international standards and diversification. The inclusion of life cycle environmental or cost management technologies in optimization models is an interesting pathway towards sustainable water treatment in-line with sustainable development goals, circular bioeconomy and industry 4.0.
AB - Rapid urbanization, population increase, emerging contaminants and increasing water scarcity have put a major constraint on the wastewater treatment system. Scarcity of water is steering current way of water recycle, and the drive focus towards resource recovery. Zero waste pathway in circular bioeconomy can bring transformation of wastewater commercialization by adding value with resource recovery. The complex biological reactions, unforeseen microbial behaviours, lack of reliable on-line instrumentation, complex modelling, lack of visualize techniques, low-quality industrial measurements and highly time-varying intensive data-driven operations call for the intelligence techniques and operations. The study is a review of sustainable circularity and intelligent data-driven operations and control of the wastewater treatment plant. Water surveillance and monitoring, circular economy and sustainability, automation pyramid, digital transformation, artificial intelligence, data pipeline, digital twin, data mining, and data-driven visualization, cyber-physical systems and water-energy-health management were reviewed. The deployment of the digital systems has evidently proven to bridges the gap between the data-driven soft sensor, operation and control systems in WWTP. Accurate prediction of the WWTP variables can support process design and control, reduce operation cost, improve system reliability, predictive maintenance and troubleshooting, increase water quality, increase stakeholder's engagement and endorse optimization of the plant performance. This procures the best compliance with international standards and diversification. The inclusion of life cycle environmental or cost management technologies in optimization models is an interesting pathway towards sustainable water treatment in-line with sustainable development goals, circular bioeconomy and industry 4.0.
KW - Circular bioeconomy
KW - Data pipeline
KW - Digital twin
KW - Process design
KW - Sensor
KW - Wastewater treatment
UR - http://www.scopus.com/inward/record.url?scp=85129970204&partnerID=8YFLogxK
U2 - 10.1016/j.pce.2022.103152
DO - 10.1016/j.pce.2022.103152
M3 - Article
AN - SCOPUS:85129970204
SN - 1474-7065
VL - 126
JO - Physics and Chemistry of the Earth
JF - Physics and Chemistry of the Earth
M1 - 103152
ER -