Background and aims Wastewater‐based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study were to: (i) assess spatial and temporal trends of population‐normalized mass loads of benzoylecgonine, amphetamine, methamphetamine and 3,4‐methylenedioxymethamphetamine (MDMA) in raw wastewater over 7 years (2011–17); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city; and (iii) compare these with existing prevalence and seizure data. Design Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017. Setting and Participants Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries. Measurements Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of Δ9‐tetrahydrocannabinol (11‐nor‐9‐carboxy‐Δ9‐tetrahydrocannabinol) were measured in wastewater using liquid chromatography–tandem mass spectrometry. Daily mass loads (mg/day) were normalized to catchment population (mg/1000 people/day) and converted to the number of combined doses consumed per day. Spatial differences were assessed world‐wide, and temporal trends were discerned at European level by comparing 2011–13 drug loads versus 2014–17 loads. Findings Benzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA and methamphetamine in East and North–Central Europe. In other continents, methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. During the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge. Conclusions The analysis of wastewater to quantify drug loads provides near real‐time drug use estimates that globally correspond to prevalence and seizure data.

Reports concerning the quantitative analysis of pharmaceuticals in marine ecosystems are somewhat limited. It is necessary to determine pharmaceutical fate and assess any potential risk of exposure to aquatic species and ultimately, seafood consumers. In the work presented herein, analytical methods were optimised and validated for the quantification of pharmaceutical residues in wastewater effluent, receiving marine waters and marine mussels (Mytilus spp.). Selected pharmaceuticals included two non-steroidal anti-inflammatory drugs (NSAIDs) (diclofenac and mefenamic acid), an antibiotic (trimethoprim), an antiepileptic (carbamazepine) and a lipid regulator (gemfibrozil). This paper also presents the results of an in situ study in which caged Mytilus spp. were deployed at three sites on the Irish coastline over a 1-year period. In water samples, pharmaceutical residues were determined using solid phase extraction (SPE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The extraction of pharmaceuticals from mussel tissues used an additional pressurised liquid extraction (PLE) step prior to SPE and LC-MS/MS. Limits of quantification between 15 and 225 ng·L(-1) were achieved in wastewater effluent, between 3 and 38 ng·L(-1) in marine surface water and between 4 and 29 ng·g(-1) dry weight in marine mussels. Method linearity was achieved for pharmaceuticals in each matrix with correlation coefficients of R(2)≥0.976. All five selected pharmaceuticals were quantified in wastewater effluent and marine surface waters. This work has demonstrated the susceptibility of the Mytilus spp. to pharmaceutical exposure following the detection of pharmaceutical residues in the tissues of this mussel species at measurable concentrations.

The development, characterisation and application of a new analytical method for multi-residue PPCP determination in the freshwater amphipod, Gammarus pulex are presented. Analysis was performed using pulverised liquid extraction (PuLE), solid phase extraction (SPE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Qualitative method performance offered excellent limits of detection at <20 ng g(-1) for 18 out of 29 compounds. For quantitative application, linearity and precision were considered acceptable for 10 compounds across the ng-μg g(-1) range (R2≥0.99; ≤20% relative standard deviation respectively). The method was applied to the analysis of G. pulex and river water sourced from six tributaries of the River Thames. Carbamazepine, diazepam, nimesulide, trimethoprim and warfarin were determined in G. pulex samples at low ng g(-1) (dry weight) concentrations across these sites. Temazepam and diclofenac were also detected, but were not quantifiable. Six pharmaceuticals were quantified in surface waters across the eight sites at concentrations ranging from 3 to 344 ng L(-1). The possibility for confirmatory detection and subsequent quantification of pharmaceutical residues in benthic organisms such as G. pulex will enable further understanding on the susceptibility and ecological effects of PPCPs in the aquatic environment.

For the first time, the performance of a generalised artificial neural network (ANN) approach for the prediction of 2492 chromatographic retention times (tR) is presented for a total of 1117 chemically diverse compounds present in a range of complex matrices and across 10 gradient reversed-phase liquid chromatography-(high resolution) mass spectrometry methods. Probabilistic, generalised regression, radial basis function as well as 2- and 3-layer multilayer perceptron-type neural networks were investigated to determine the most robust and accurate model for this purpose. Multi-layer perceptrons most frequently yielded the best correlations in 8 out of 10 methods. Averaged correlations of predicted versus measured tR across all methods were R(2)=0.918, 0.924 and 0.898 for the training, verification and test sets respectively. Predictions of blind test compounds (n=8-84 cases) resulted in an average absolute accuracy of 1.02±0.54min for all methods. Within this variation, absolute accuracy was observed to marginally improve for shorter runtimes, but was found to be relatively consistent with respect to analyte retention ranges (~5%). Finally, optimised and replicated network dependency on molecular descriptor data is presented and critically discussed across all methods. Overall, ANNs were considered especially suitable for suspects screening applications and could potentially be utilised in bracketed-type analyses in combination with high resolution mass spectrometry.