Pharmaceutical emissions on the example of the Baltic Sea catchment: comparing measurements with multi-tier predictive models

Currently, there is uncertainty about emissions of pharmaceuticals into larger closed ecosystems that are at risk such as the Baltic Sea. There is an increasing need for selecting the right strategies on advanced wastewater treatment. This study analysed 35 pharmaceuticals and iodinated X-ray contrast media in effluents from 82 Wastewater Treatment Plants (WWTPs) across Denmark, Estonia, Finland, Germany, Latvia, Lithuania, Poland and Sweden. Measured concentrations from Finland and Denmark were compared to predicted effluent concentrations using different levels of refinement. The concentrations predicted by the Total Residue Approach, as proposed by the European Medicines Agency, correlated with R2 of 0.18 and 0.031 to measured ones for Denmark and Finland, respectively and the predicted data were significantly higher than the measured ones. These correlations improved substantially to R2 of 0.72 and 0.74 after adjusting for estimated human excretion rates and further to R2 = 0.91 and 0.78 with the inclusion of removal rates in WWTPs. Temporal analysis of compound variations in a closely monitored WWTP showed minimal fluctuation over days and weeks for most compounds but revealed weekly shifts in iodinated X-ray contrast media due to emergency-only operations at X-ray clinics during weekends and an abrupt seasonal change for gabapentin. The findings underscore the limitations of current predictive models and findings (...) demonstrate how these methodologies can be refined by incorporating human pharmaceutical excretion/metabolization as well as removal in wastewater treatment plants to more accurately forecast pharmaceutical levels in aquatic environments. [Display omitted] •35 pharmaceuticals were measured in 82 WWTPs across 8 countries.•Predicted concentrations were refined with human excretion and WWTP removal rates.•Measured concentrations were compared with predicted concentrations.•A scalable method for estimating predicted pharmaceutical emissions is proposed.