Aalto University researchers are developing a decision-making support tool to help the plant operators achieve almost the impossible: cleaning the wastewaters to attain exceptionally low levels of nutrients, while maintaining good energy balance and carbon neutrality.
The DIGICARBA research project is being conducted at Aalto University (Finland) by researchers in Water and Environmental Engineering between 2023 and 2025. The main goal of the project is to develop a digital twin of the wastewater treatment plant WWTP Viikinmäki in Helsinki,with a focus on greenhouse gas (GHG) emission mitigation to improve carbon balance and promote proactive process control and operation. A digital twin could be defined as a model of physical asset with a continuous automated connection to live data of the real entity.
The project is funded by Business Finland (via the Decarbonized Cities programme) and is supported by a main partner: Helsinki Region Environmental Services Authority HSY, which operates WWTP Viikinmäki. The work is done in collaboration with companies several companies: FCG Finnish Consulting Group Oy, Valmet Oyj, Brighthouse Intelligence Oy, Mittausguru Oy, and water utilities of Turku (Turun seudun puhdistamo Oy) and Hämeenlinna (Hämeenlinnan Seudun Vesi Oy). All stakeholders participate regularly in the ongoing project development, via discussions in the steering group meetings.
WWTP Viikinmäki possesses a significant advantage for this study, as it was constructed in underground bedrock with an exhaust air pipe equipped with gas compound measurement sensor and implanted liquid phase N2O emissions sensors. WWTP Viikinmäki is the largest treatment plant in Nordic countries, and receives a load of approximately 1.2 million population equivalent as per 2023. Its average flow is 280 000 m3/day, with peak flows up to 700 000 m3/day. Influent flow constitutes domestic wastewater (85%) and industrial wastewater (15%). WWTP employs biological wastewater treatment via nitrification/denitrification and post-denitrification via biofilters for nitrogen removal, alongside chemical phosphorus removal via ferrous sulphate. Processed excess sludge from biological treatment and raw primary sludge are both used for anaerobic digestion for biogas production. The generated biogas for heat and electricity production ensures approximately 90% sufficiency for the treatment plant’s electricity needs. As for the digested sludge, it is used for processing into soil products in composting fields. In addition, local energy company Helen Ltd operates a heat pump plant to produce heat and cooling from the treated wastewater.
The DIGICARBA project objective is to create a digital twin that combines a biomechanistic model with data-based information for the automated simulation of the actual wastewater treatment process. During the development, different machine learning techniques will be tested to provide influent wastewater quality predictions using the process data collected at the plant. These predictions would entirely rely on available data sources from WWTP Viikinmäki (HSY).
The digital twin will operate based on various data sources, including technical information, historical data, laboratory data, and process instrumentation data. Additionally, wastewater fractionation analysis will be performed to fine-tune the process model. The collected data will undergo pre-processing, systematisation, and utilisation in the development, calibration, and validation of the process model. At the end of the project, the developed digital twin should have automated data feeding to the process model, automated data pre-processing and automated model calibration. It should also provide useful information from simulations in the user interface.
GHG emissions from biological wastewater treatment modelling still requires comprehensive research to improve model accuracy. Nitrous oxide (N2O) is the most significant contributor to the carbon footprint of wastewater treatment plant Viikinmäki, and is therefore one of the primary variables for optimisation. Viikinmäki plant’s long-term monitoring of N2O for over 10 years will benefit digital twin development with a focus on carbon balance completed during the DIGICARBA project.
The parts of the treatment plant with the biggest energy consumption are the aeration systems for biological treatment steps, pumps, mixers and centrifuges. The aeration systems require the most energy, as the nitrogen removal process requires intensive air supply for ammonia conversion into nitrates. An advanced aeration control system is already used at the Viikinmäki WWTP: however, N2O emissions are caused by a complex mixture of pathways, and aeration affects N2O emissions. Also, optimisation of the carbon use between energy production and nutrient removal is a complicated challenge. Due to the extreme complexity of these tasks, the use of real-time predictions of different operational choices will be a valuable tool for plant operators, and this will allow them to make more informed decisions. The digital twin can also calculate energy consumption and energy production potential for different simulated operational scenarios. Therefore, the development of the digital twin will also focus on providing the operators with new information that supports proactive energy-efficient process operation. The project would result in the active use of the digital twin as a proactive process control tool, and therefore, the engagement of operating team and the early establishment of guidelines for cyber security is necessary.
The DIGICARBA project is progressing in various new directions, as the synthesis of different results are required for the successful development of a digital twin. One of the crucial steps was to encourage the operating and engineering teams of HSY to participate in the project, as they are the ones putting the digital twin into active use, and benefitting from its ability to predict the process behaviour. To that end, a workshop was organised in the autumn of 2023, during which operators and engineers of the plant cooperated with the research team at Aalto University, to define what improvements could to be implemented for the digital twin (Fig.1). One of the key outputs of the DIGICARBA project will be a doctoral thesis, but in the meantime, project updates will be provided on a regular basis via peer-reviewed articles and at conferences. More information on the DIGICARBA project is available on its website and LinkedIn page.
Author(s)
Ksenija Golovko, Doctoral Researcher, Aalto University
Henri Haimi, Professor of Practice at Aalto University
Anna Mikola, Assistant Professor at Aalto University
