Modelling multitudes of pharmaceuticals in the global river system at high spatial resolution

Treated and untreated domestic wastewaters that are discharged into surface waters often contain a variety of chemical substances, including residuals of pharmaceuticals that are not fully metabolized by the human body. These substances may be harmful to the health of aquatic ecosystems and to humans who rely on them as a source of water supply. Despite growing concerns and their frequent detection in wastewaters and surface waters, the concentrations of pharmaceuticals are not regularly monitored in water bodies. As an alternative to comprehensive monitoring campaigns that tend to be very resource intensive, contaminant fate models may be used to provide information to support the development of targeted local monitoring schemes in regions of highest exposure to pharmaceuticals in the environment as well as the prioritization of substances for further investigation.

In this work, a global contaminant fate model (called HydroFATE) was developed with the objective of estimating the concentration of contaminants of emerging concern (including pharmaceuticals) in the global river network at a high spatial resolution (500 m). The contaminant emission is calculated based on consumption per capita and population density. Then, the contaminant loads of treated or untreated wastewaters are reduced in the model either by centralized or decentralized wastewater treatment, by natural attenuation in soils and runoff, and/or by decay processes in rivers and lakes. HydroFATE’s structure is based on a vector routing structure, which besides its spatial precision being higher than in global pixel-based models, it is also fast to process. This key aspect allows for more complex analyses, including repeated execution of multiple substances and different scenarios in a short period of time, making HydroFATE a capable tool to inform on the prioritization of substances.

The model’s performance was validated by comparing predicted concentrations in river reaches worldwide against literature reports of measured concentrations of 22 broadly consumed antibiotics for which at least sparsely monitored data existed. The sensitivity of the model’s predictions was tested by altering key model parameters. This validation process showed that HydroFATE is generally able to predict aquatic concentrations measured worldwide to within one order of magnitude, which is judged to be sufficient for the intended purposes of the model.

Finally, HydroFATE was applied to estimate the concentrations of the 40 most widely used antibiotics in households worldwide and to compare these concentrations, both individually and cumulatively, to established no-effect thresholds of environmental exposure. It was estimated that a total of 8,500 tonnes of antibiotics per year are discharged into the river system. We found that 6.0 million km of rivers worldwide may have environmental exposure levels that exceed the no-effect concentration of antibiotic pollution during low streamflow conditions, with the largest extent of these rivers being in Southeast Asia, the most densely populated region in the world. The main contributors of exposure were found to be the widely and heavily used antibiotics amoxicillin, ceftriaxone, and cefixime.