A new analytical method to determine trace level concentrations of pharmaceuticals in influent wastewater: a tool to monitor human use patterns
Fontanals Torroja, Núria; Pocurull Aixala, Eva; Rodríguez Mozaz, Sara; Montes Goyanes, Rosa; González Mariño, Iria; Santana Vieira, Sergio; Miró Lladó, Manuel; Rico Artero, Andreu; Borrull Ballarín, Francesc; Quintana Álvarez, José Benito; Marcé Recasens
- Published
- 2023
- Publisher
- Elsevier
- Language
- en
Abstract
The occurrence of pharmaceuticals in influent wastewater samples (IWW) is a recurrent issue. The monitoring of their presence is not only valuable from an environmental point of view, but also as a tool to analyze patterns of human use by the so-called wastewater-based epidemiology. The development of an analytical method based on solid-phase extraction followed by liquid chromatography coupled to tandem mass spectrometry to monitor the occurrence of a group of seventeen pharmaceuticals including the most representative for various therapeutic families in IWW samples is described in this work. The samples were collected during a monitoring week in six wastewater treatment plants located in different cities and towns across Spain. The developed method provides acceptable figures of merit with apparent recoveries in IWW ranging from 42% to 139%, and low matrix effect (in general lower than ± 30%), and method quantification limits (MQL) between 1 ng/L and 24 ng/L for all compounds, except atenolol (58 ng/L). All the studied pharmaceuticals were found in all samples with concentrations ranging from < MQL to 10,393 ng/L, being the highest concentrations for tramadol. The population normalized daily loads revealed that the use of pharmaceuticals follows, in general, a similar pattern in all cities monitored.
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SUPPLEMENTARY INFORMATION A new analytical method to determine trace level concentrations of pharmaceuticals in influent wastewater: A tool to monitor human use patterns Núria Fontanals1*, Eva Pocurull1, Rosa Montes2, Iria González-Mariño3, Sergio Santana-Viera4, Manuel Miró5, Andreu Rico6,7, Sara Rodríguez-Mozaz8,9, Francesc Borrull1, José Benito Quintana2, Rosa Maria Marcé1 1Universitat Rovira i Virgili. Department of Analytical Chemistry and Organic Chemistry. Tarragona, Spain 2Department of Analytical Chemistry, Nutrition and Food Sciences. Institute of Research in Chemical and Biological Analysis (IAQBUS). Universidade de Santiago de Compostela. Santiago de Compostela, Spain 3Department of Analytical Chemistry, Nutrition and Bromatology, Faculty of Chemical Sciences, University of Salamanca, Salamanca, Spain 4Instituto de Estudios Ambientales y Recursos Naturales (i-UNAT), Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain 5FI-TRACE group, Department of Chemistry, University of the Balearic Islands. Palma de Mallorca, Spain 6IMDEA Water Institute, Science and Technology Campus of the University of Alcalá, Alcalá de Henares, Spain 7Cavanilles Institute of Biodiversity and Evolutionary Biology, University of Valencia, Paterna, Spain 8Catalan Institute for Water Research (ICRA-CERCA), Girona, Spain 9University of Girona (UdG), Girona, Spain *Corresponding author email: [email protected]
Figure S1. Structure of the studied compounds.
Table S1. Main characteristics of the wastewater treatment plants (WWTPs) included in this study. WWTP City Region Population Covering the city (%) Average flow (m3/day) Sampling date Sampling modea Madrid 1 Madrid Madrid Community 352188 30 75102 19-25/10/2022 T (450 mL/60 min) Madrid 2 Madrid Madrid Community 727176 30 63393 19-25/10/2022 T (100 mL/60 min) Tarragona Tarragona Catalonia 115567 100 24690 13-19/04/2021 T (400 mL/30 min) Reus Reus Catalonia 108953 100 17533 13-19/04/2021 Flow Palma de Mallorca Palma de Mallorca Balearic Islands 472319 100 (Palma city, excepting Palma Beach area) 65538 21-26/04/2021 T (100 mL/15 min) Las Palmas de Gran Canaria Las Palmas de Gran Canaria Canary Islands 477857 100 37009 14-19/04/2021 T (100 mL/30 min) a Sampling mode: T = Time proportional (volume sampled/frequency of sampling), Flow = Flow proportional
Figure S2. Extracted ion chromatogram of a standard solution using the optimized separation conditions. morphine atenolol codeine tramadol pentoxifylline omeprazole venlafaxine trazadone sulfamethoxazole quetiapine carbamazepine oxazepam methadone losartan diazepam bezafibrate diclofenac
Table S2. Validation parameters. Instrumental linear range (µg/L) R2 IQLs (µg/L) IDLs (µg/L) %R app a Precision intraday (%RSD, n=5) a Precision interday (%RSD,n=5) a MQLs (ng/L) MDLs (ng/L) Morphine 1-1000 0.9943 1 0.5 87 5.2 10.9 12 6 Atenolol 5-1000 0.9957 5 2 87 6.3 7.6 58 23 Codeine 1-250 0.9997 1 0.2 57 6.1 8.3 18 5 Tramadol 0.5-1000 0.9999 0.5 0.05 46 5.1 9.0 11 1 Pentoxifylline 1-1000 0.9930 1 0.1 122 4.3 10.5 8 0.8 Quetiapine 0.5-1000 0.9969 0.5 0.05 39 5.7 12.3 13 1 Omeprazole 1-500 0.9998 1 0.5 42 6.7 14.1 24 12 Sulfamethoxazole 1-1000 0.9994 1 0.5 62 4.6 11.0 16 8 Venlafaxine 0.1-500 0.9986 0.1 0.02 43 5.2 10.7 2 0.5 Trazodone 0.5-1000 0.9963 0.5 0.1 54 3.2 9.8 9 2 Losartan 0.8-1000 0.9997 0.8 0.2 101 5.8 6.4 8 2 Carbamazepine 0.5-1000 0.9918 0.5 0.1 97 5.8 12.1 5 1 Oxazepam 1-1000 0.9999 1 0.5 117 4.3 13.9 8 4 Diazepam 0.8-500 0.9993 0.8 0.2 68 5.5 9.2 12 3
Methadone 0.1-1000 0.9979 0.1 0.02 100 4.6 8.6 1 0.2 Bezafibrate 0.8-1000 0.9998 0.8 0.2 126 6.1 10.9 6 2 Diclofenac 2-1000 0.9998 2 0.5 139 5.8 12.3 14 4 a spiked at 1000 ng/L.
