Table 6 NTS prioritisation approaches based on question to address and appropriate methods using chemical signature, biological activity and statistical tools

Contamination with regulated, highly used or emerging substances (suspects)

Screening with appropriate suspects lists (e.g., all registered pesticides; industrial compounds with high use; predicted TPs)

Selection or compilation of an appropriate suspect list (see Sect. “Candidate structure search and selection”) and screening of exact mass in samples and blank samples

196, 240, 242, 243

Contamination spots (often local)

High intensity in few samples from specific sites but not in samples from reference sites

Statistical analysis, e.g., density estimation, probability distribution, pairwise comparisons

244

Widespread contamination

High frequency of occurrence in samples from different sites

Statistical analysis, e.g., density estimation, probability distribution

236

Contamination with compounds that produce high seasonal or intraday fluctuation

Comparison of samples over time (e.g., industrial wastewater during different production processes)

Time series analysis using, e.g., (non)linear regression, (non)-parametric, uni-/multivariate statistical approaches

245,246,247

Similarly or differently contaminated sites/ contamination profiles

Comparison of the MS pattern of samples from different sites

Clustering (e.g., hierarchical), unsupervised PCA or supervised PLS, selection of masses in the loading plots

26, 35

Contamination with homologues of a substance class (e.g., PFAS, surfactants)

Characteristic mass (e.g., CF₂) and RT difference

Homologue series search, Kendrick mass defect and other mass defect plots

143, 235, 238, 237, 248,249,250

Substance classes with specific functional groups (aldehydes, conjugates)

Neutral loss, specific fragments in MS2 spectra from compound or derivative (e.g., –SO₃)

Fragment search in MS2 spectra

251,252,253

Anthropogenic compounds with specific isotope pattern

Isotope pattern (especially relevant for Cl = Br > S > Si)

Isotope search in MS1

38, 254

Compounds causing effect

Effect-directed selection of masses in samples or fractions of samples using effect data or bioassays;

Fractionation is often necessary to reduce candidate masses and chemical complexity

Comparison of masses in samples/fractions causing effect with those causing no effect using direct comparison or statistical methods

255, 256

Compounds potentially causing effects

Annotation of signals with in vivo or in vitro hazard characteristics

In silico prediction of toxicity based on chemical fingerprints produced from MS2 spectra by SIRIUS

257, 258

Persistent compounds

Comparison of samples before and after processes (e.g., water treatment) or along time scales (e.g., river stretch)

Statistical methods, such as clustering, PCA, PLS, fold change

259

Bioaccumulative compounds

Comparison of the MS pattern of samples along the trophic chain

Clustering (e.g., hierarchical), trend analysis

65

Formed TPs

Comparison of samples before and after processes (e.g., water treatment) or along time scales (e.g., along river stretch) for specific mass differences due to transformation reaction

Search for specific mass differences in mass lists of before and after samples or statistically (PCA, clustering, time series) separated groups (e.g., 15.9949 for addition of O)

241, 260,261,262

Formed disinfection by-products (DBPs)

Comparison of samples before and after water treatment, then isotopic pattern analysis (Cl, Br)

Isotope search in MS1 and MS2 for formed signals with specific isotope pattern

263

Isotope-supported detection of TPs, by-products

Lab experiments with isotopically labelled reagents, screening for isotope mass differences (e.g., reaction with ¹⁵NO₃⁻, screening for Δm = 0.9970)

Search for specific mass differences in mass lists of lab experiments with mixtures of isotopes (e.g., ¹⁴NO₃⁻ and ¹⁵NO₃⁻) or of two sample series with single isotopes

264, 265