2025/04/18 by John Nightingale, Stefan Trapp, Andrea-Lorena Garduño-Jiménez +1 · 1 voice
Environmental Science · Medicine · #Antibiotics Pharmacokinetics and Efficacy #Pharmaceutical and Antibiotic Environmental Impacts #Wastewater Treatment and Reuse
paper · doi:10.1016/j.jhazmat.2025.138297
openalex publication_date 2025/04/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23
The reuse of treated wastewater for irrigation can inadvertently introduce a suite of emerging contaminants such as pharmaceuticals into agri-ecosystems. However, current monitoring efforts to characterise exposure usually focus on a limited range of analytes. A modelling framework was developed that employs a sequence of pre-developed models to predict accumulative potential in a model crop, Zea mays (corn), using chemical structure and excretion rate as the only model inputs. Z. mays was selected as the model crop as it is a major food source, stands as one of the highest cultivated crops globally, and is characterised as having a medium uptake potential. The framework was used to predict uptake in Z. mays in three regions characteristic of high wastewater reuse (Australia, the US and the Middle East). Despite regional and plant specific differences, 72.7 % of the calculated concentrations were within a factor of ten of those reported in the literature. Topiramate, furosemide, and gemfibrozil were observed to accumulate to the greatest extent in Z. mays , predicted concentrations ranged between 50.27 and 418.01 ng/g (dw) for the top 10. Acids predominantly accumulated in leaves and fruit whereas a higher proportion of bases were predicted to accumulate in the roots. To the best of our knowledge 56.7 % of the 30 highest-ranked pharmaceuticals have not been previously documented in existing literature or monitoring campaigns. This presented framework demonstrates a method to assess risk posed by pharmaceutical compounds with limited experimental data. • Pharmaceutical uptake can be predicted from a chemical structure and excretion data. • The framework provides a rapid approach to screen large chemical datasets. • 56.7 % of the top 30 pharmaceuticals have not been previously reported in literature. • Consumption of contaminated produce was deemed to be a negligible human health risk. • Consumption of multiple crops and co-contaminants increased the hazard index > 1.