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Relating Degradation of Pharmaceutical Active Ingredients in a Stream Network to Degradation in Water‐Sediment Simulation Tests
Author(s) -
Honti Mark,
Bischoff Fabian,
Moser Andreas,
Stamm Christian,
Baranya Sándor,
Fenner Kathrin
Publication year - 2018
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2018wr023592
Subject(s) - persistence (discontinuity) , biotransformation , environmental science , streams , sediment , laboratory test , degradation (telecommunications) , settling , biodegradation , hydrology (agriculture) , environmental engineering , environmental chemistry , biochemical engineering , ecology , chemistry , geotechnical engineering , computer science , geology , biology , engineering , computer network , paleontology , biochemistry , telecommunications , enzyme
Abstract Many pharmaceuticals inevitably end up in surface waters, exerting unwanted biological activity in nontarget organisms. This effect is confined by the compound's environmental persistence. Regulatory laboratory simulation tests are used in persistence assessment and exposure modeling. While doubt has been expressed about the usefulness of laboratory‐derived persistence indicators under field conditions, these remain the only inputs for chemical fate models due to difficulties of measuring persistence in situ, especially at large scales. To improve understanding about relationships between laboratory experiments and the environmental fate in streams, we developed a mathematical model of biodegradation in stream networks and combined it with in‐stream monitoring data to (i) test if persistence could be evaluated from field data, (ii) check if persistence extracted from laboratory tests applied in the field, and (iii) locate hot spots of biodegradation in a large river basin. The model describes partitioning, and particle settling and resuspension, and is structurally compatible with those applied for evaluating laboratory simulation tests. Application to the Rhine river basin suggests that biotransformation rate constants extracted from laboratory tests underestimate those in the field, yet the percentage of biotransformation in the Rhine basin is less than in the laboratory tests due effective biotransformation being limited to small‐ and medium‐sized streams. In conclusion, our data show that biotransformation rates can accurately be predicted if (i) monitoring is performed across a wide range in stream order and (ii) precise estimates for consumption and removal rates at wastewater treatment plants are known.