Smart Water Engineering Group (SWING)

Drug and antibiotic biomarkers in sewage

The wastewater infrastructure, including water resource recovery facilities (WRRF), is responsible for the continuous release of drug and antibiotic biomarkers via sewage.

One of the results of this pollution is antibiotic resistance development in the environment with an increasingly negative effect on therapeutic effectiveness. 

SWING’s research focuses on engineering microbial communities to enhance the removal of antibiotics and resistant materials in biofilm-based water treatment processes. 

Additionally, our modelling framework (ASM-X) can help predict more accurately aqueous biomarker concentrations and chemical exposure in wastewater – essential e.g., forecasting antimicrobial resistance development in the environment, evaluating illicit drug abuse rates in urban areas, for advance environmental risk assessment of pharmaceuticals.

Climate change impact adaptation and mitigation

Extreme hydraulic shock events are expected to occur more often in the future due to climate change. 

Mitigation measures require sensors and models capable of describing and predicting urban water systems’ performance under changing flow conditions.

Increased uncertainties in the design, operation and control of city-scale water and wastewater systems require disruptive paradigm shifts to adopt; it is expected that these factors will shake up and dramatically transform regulatory frameworks and water quality engineering practices both in Norway and globally. 

SWING’s research focuses on developing advanced sensor monitoring, computational fluid dynamics and hybrid modelling tools to gauge existing capacities, and vulnerabilities (e.g., climate, digital), as well as the effective design and retrofitting of water process systems.

Water resource engineering

Resource transport and conversion through urban water systems are unsustainable: nutrients for agricultural fertilizer, and stabilized solids for soil improvement are ideas, often represented just by some small-scale demo studies. 

There is still much research time and effort as well as private and governmental capital invested in water resources, destroying technology worldwide.

Much like the success story of anaerobic digestion in water resource recovery facilities, more research and innovation are needed to upscale and implement new water technology in the future. 

SWING’s research focuses on developing new bioprocessing to separate and recover water resources for agricultural reuse.

Statistical optimization and machine learning. 

Quantifying uncertainties in urban water data is a crucial step in developing resilient systems.

Our group has broad expertise in Approximate Bayesian Computation enhanced with machine learning techniques, Markov Chain Monte Carlo optimization, sensor data and mathematical model structural analysis (practical identifiability), to name a few. 

We use these tools e.g., to create robust predictive tools, error analysis and propagation, multivariate regression analysis, global sensitivity, and uncertainty analysis. Our MSc students (Smart Water Process & Infrastructure Engineering 

• MaxBiogas (2022 – 2025)
• EU-H2020 In2Aquas (2023 – 2027)