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Updated: Apr 15, 2026

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses
Published on: October 21, 2016
Emission factor estimation of ca. 160 emerging organic microcontaminants by inverse modeling in a Mediterranean river
Zoran Banjac1, Antoni Ginebreda1, Maja Kuzmanovic1
1Water and Soil Quality Research Group, Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, 08034 Barcelona, Spain.
Abstract:
Starting from measured river concentrations, emission factors of 158 organic compounds out of 199 analyzed belonging to different groups of priority and emerging contaminants [pesticides (25), pharmaceuticals and hormones (81), perfluoroalkyl substances (PFASs) (18), industrial compounds (12), drugs of abuse (8) and personal care products (14)] have been estimated by inverse modeling. The Llobregat river was taken as case study representative of Mediterranean rivers. Industrial compounds and pharmaceuticals are the dominant groups (range of 10(4) mg·1000 inhab(-1)·d(-1)). Personal care products, pesticides, PFASs and illegal drugs showed a load approximately one order of magnitude smaller. Considered on a single compound basis industrial compounds still dominate (range of ca. 10(3) mg·1000 inhab(-1)·d(-1)) over other classes. Generally, the results are within the range when compared to previously published estimations for other river basins. River attenuation expressed as the percentage fraction of microcontaminants eliminated was quantified. On average they were around 60-70% of the amount discharged for all classes, except for PFASs, that are poorly eliminated (ca. 20% on average). Uncertainties associated with the calculated emissions have been estimated by Monte-Carlo methods (15,000 runs) and typically show coefficients of variation of ca. 120%. Sensitivities associated with the various variables involved in the calculations (river discharge, river length, concentration, elimination constant, hydraulic travel time and river velocity) have been assessed as well. For the intervals chosen for the different variables, all show sensitivities exceeding unity (1.14 to 3.43), tending to amplify the variation of the emission. River velocity and basin length showed the highest sensitivity value. Even considering the limitations of the approach used, inverse modeling can provide a useful tool for management purposes facilitating the quantification of release rates of chemicals into the aquatic environment.

