Environmental context Decades of research tried to understand the inherent complexity of biodegradation of contaminants. We describe calculus of biodegradation driven by bioavailability, redox, geometry and acclimation (adaptation) of microbiota. We tested predictions for thousands of contaminants across wastewater treatment plants, explaining up to 70% of the variance in observations. This competes with more intensive methods, and enables more efficient monitoring, experimentation and data interpretation. Rationale Release of harmful contaminants of emerging concern (CECs) in the environment prompts possible adverse toxicological effects. Increasing population, water use and process wastewater generation require more efficient removal of contaminants that allows for effluent discharge within environmental regulatory limits. Wastewater treatment plants (WWTPs) can remove hazardous contaminants, limiting unwanted release. Fine-tuning WWTP settings to fit the location, time, season, wastewater type, etc. may enhance removals to reduce CEC concentrations and toxic pressures. Methodology For this purpose, we need robust tools to calculate removal efficiencies. We studied influences of operational settings and CEC properties on their removal in WWTPs. For this purpose, we parameterised thermochemical properties of CECs: for their (1) speciation and acidification, (2) (re/im)mobilisation due to (de)sorption into solid/water, (3) redox-mediated biotransformation and (4) acclimation of biomass so to utilise metabolic pathways for biotransformation. By combining these parameters, we developed an energy-based framework for calculating biotransformation rates. Results We evaluated our calculus using removal efficiency (%) data for 373 measurements of 60 CECs in 14 different Dutch WWTPs and an additional 667 CECs in 49 WWTPs across the world. Our prediction precision, R2 ≈ 0.65 (P < 10−5), captures influences of wastewater characteristics (multiple measurements for each WWTP). It is higher than R2-values of modelling approaches currently available. Our model explains CEC removal with appreciative certainty. We identified outliers during evaluation. These outliers were attributed mostly to back-transformation and uncertainty in long-term background concentrations of contaminants, causing consequent acclimation of microbial consortia. Discussion Biodegradability and CEC-degrading biomass can be estimated from concentration and environmental residence time. Our framework and underlying parametrisations have a mechanistic basis, utilising simple WWTP operational information (CEC concentration, temperature, suspended solids concentration, oxygen demand, etc.). Thereby, our work has wide potential for implementation. Our approach can supplement current fate assessment for CECs for improved environmental risk assessments. We conclude by discussing the potential for removal enhancement.
