Using NTS for wide-scope target screening
While traditional target analysis often addressed only a limited number of contaminants, NTS now allows an “all-in-one” measurement and data can be directly used for target screening of hundreds to thousands of chemicals in monitoring studies [32, 33]. Examples are the screening for about 270 and 400 target chemicals in order to evaluate the impact of non-treated and treated wastewater effluents on the micropollutant burden in water in the River Danube [34, 35] and in small streams in Switzerland , respectively. In these studies, linking target screening with effect-based monitoring  was shown to help assess toxic risks, identify drivers of toxicity, quantify their contribution to mixture risks, and indicate the risk that is not explained by the limited selection of current target chemicals. In a study on wastewater treatment plant (WWTP) effluents, target screening helped to unravel seasonal dynamics in organic pollutant mixtures and related toxic risks .
Development and assessment of automated methods for small molecule identification
Software-based automated data processing methods play a critical role for the successful identification of compounds from NTS data. In general, NTS workflows start from detection of peaks by the peak picking software. To maximize the quality and number of detected peaks the performance of one of the widely used data processing software packages MZmine 2 was assessed for LC-HRMS data  and validated on both spiked and real surface water samples. This optimization workflow for MZmine 2 can be applied to data from other LC-HRMS instruments.
In compound identification, in silico MS/MS fragmentation prediction approaches are most widely applied to assign a compound structure to an unknown peak. The evaluation of the Critical Assessment of Small Molecule Identification (CASMI) 2016 contest  showed a substantial improvement in (semi-)automated fragmentation methods for small molecule identification. The inclusion of metadata information (e.g., commercial relevance of compounds) further improves the identification success for “real life” annotations of environmental contaminants .
In another study, a data set of 78 diverse known micropollutants analyzed by LC-HRMS was used to assess two different MS/MS fragmentation and two retention prediction approaches. To combine scores from these different candidate selection tools, consensus score values with optimal weights were calculated to show the contribution of each approach and whether the combination could improve candidate selection [40, 41].
Automated small molecule identification approaches require reporting standards that reflect the confidence of the identification based on NTS data. The “Level system” proposed in  has been used in SOLUTIONS and NORMAN efforts for communicating NTS results .
NTS in routine monitoring—the River Rhine case study
The international Rhine monitoring station has showcased the use of NTS with automated workflows in routine monitoring . This involves the automated screening for 320 target compounds for long-term trend analysis, suspect screening of 1500 compounds to identify peak events and emission patterns, and NTS to detect accidental spills of previously undetected compounds. Daily trend analysis revealed peak signal intensities triggering compound identification efforts. In 2014, ten major spill events of previously undetected compounds were recorded, representing a chemical load of more than 25 tons in the River Rhine.
Use of NTS to identify site-specific pollution
While the focus of chemical monitoring in Europe is on chemicals that are relevant on a European or basin scale, risks and impacts on water quality and ecosystems are quite often due to site-specific chemicals including many unexpected or unknown chemicals, which are typically overlooked or, in some cases, discovered via effect-based monitoring and identified by effect-directed analysis [24, 43]. Thus, an NTS-based approach has been developed and tested in case studies, which applies a rarity score based on detection frequency and ratios of maximum to median peak intensity on a set of sites of concern to identify water bodies with extensive occurrence of site-specific peaks . Focusing identification efforts on these peaks allowed for the establishment of major sources of pollution that should be addressed by targeted abatement .
Integration of NTS with multivariate statistics to prioritize unknown transformation products
During wastewater treatment, about 50% of parent micro-pollutants are (bio)transformed but not completely mineralized . As a result, transformation products (TPs) are of major concern in environmental monitoring. NTS and parent/TP similarity has been used to identify TPs formed in wastewater treatment . This approach combines principle component analysis (PCA) with difference analysis from known biotransformation pathways to prioritize NTS data and identify pairs of parent compounds and TPs. PCA and hierarchical clustering was also applied to prioritize TPs formed during ozonation of wastewater .
Exploring the potential of a global emerging contaminant early warning network
Alygizakis  introduced a pilot study for a global emerging contaminant early warning network, led by NORMAN, and supported by SOLUTIONS. Eight reference laboratories used archived NTS data from a range of samples for subsequent retrospective screening of a list of new and emerging contaminants contributed by members (https://comptox.epa.gov/dashboard/chemical_lists/normanews and https://zenodo.org/record/2623816). This revealed the widespread occurrence of drug transformation products (e.g., gabapentin-lactam, metoprolol acid, and 10-hydroxy carbamazepine), several surfactants (e.g., polyethylene glycols), as well as industrial chemicals such as 3-nitrobenzenesulfonate and bisphenol S.
This Policy Brief highlights the opportunities of HRMS screening for a holistic monitoring and assessment of chemical pollution with limited additional efforts, accentuates the benefit of recording, compilation and exchange of NTS data for retrospective analysis to understand trends of pollution, even for compounds which are not in the focus today, and highlights the need for establishing open science, international collaboration, and data exchange to maximize the benefit for environmental assessment and protection.