Evidence map›Paper›PMID 40815330›Full record

ArticleEnvironmental science & technology2025

Spatially and Seasonally Resolved Predictions Reveal Widespread Ecotoxicological Risk from Pharmaceutical Mixtures in German (Saxon) Rivers.

Shixue Wu, Björn Helm, Geovanni Teran-Velasquez, Peter Krebs, Rohini Kumar

Abstract read
In one paragraph

Article in Environmental science & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Shixue WuDepartment of Computational Hydrosystems, Helmholtz Centre for Environmental Research─UFZ, 04318 Leipzig, Germany.ORCID 0000-0002-3470-0254
Björn HelmInstitute of Urban and Industrial Water Management, Technische Universität Dresden, 01069 Dresden, Germany.
Geovanni Teran-VelasquezInstitute of Urban and Industrial Water Management, Technische Universität Dresden, 01069 Dresden, Germany.
Peter KrebsInstitute of Urban and Industrial Water Management, Technische Universität Dresden, 01069 Dresden, Germany.
Rohini KumarDepartment of Computational Hydrosystems, Helmholtz Centre for Environmental Research─UFZ, 04318 Leipzig, Germany.ORCID 0000-0002-4396-2037

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pharmaceutical pollution is escalating due to the increasing prevalence of diseases driven by an aging population and socioeconomic and hydroclimatic changes, challenging the EU's goal of achieving a toxic-free environment. To comprehensively assess pharmaceutical pollution in rivers, we developed a spatially resolved model to predict pharmaceutical concentrations and associated ecological risks across 1 km river stretches in Saxony, Germany. We focused on five pharmaceuticals: two antiepileptics (carbamazepine, gabapentin), two antibiotics (ciprofloxacin, sulfamethoxazole), and one antidiabetic (metformin); and their toxicity to three aquatic species: algae, daphnia, and fish. Model evaluation demonstrated a good level of accuracy, with 95-100% of simulations aligning within 1 order of magnitude of observed values across spatial and temporal scales (2008-2014). Pharmaceutical-wise, low environmental concentrations led to a reduced performance of ciprofloxacin, whereas frequent observations of carbamazepine demonstrated its improved model skill. Further, ecological risk assessments for single toxicity indicated significant risks in over half of the Saxon rivers, with exposure frequencies reaching up to 80% for the analyzed pharmaceuticals. For mixture toxicity, the risk frequency increased to 99%, revealing widespread ecotoxicological risks. Our framework identifies transport trajectories and risk hotspots of pharmaceutical pollution, enabling spatiotemporal predictions under global change conditions to support proactive measures for a healthier planet.

Indexed as

RiversWater Pollutants, ChemicalAnimalsDaphniaEcotoxicologyEnvironmental MonitoringGermanyPharmaceutical PreparationsRisk AssessmentSeasonsPharmaceutical PreparationsWater Pollutants, Chemicalecotoxicological risk assessmentGerman riversmixture toxicitynode-link networkpharmaceutical pollutiontransport and fate modeling

Identifiers

PMID40815330
PMCPMC12392725

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.