Upload
others
View
10
Download
0
Embed Size (px)
Citation preview
1
Massspectrometricstrategiesfortheinvestigationofbiomarkersof1
illicitdruguseinwastewater2
3
4 FélixHernández1*,SaraCastiglioni2,AdrianCovaci3,PimdeVoogt4,5,ErikEmke4,Barbara5 Kasprzyk-Hordern6, Christoph Ort7, Malcolm Reid8, Juan Vicente Sancho1, Kevin V.6 Thomas8,AlexanderL.N.vanNuijs3,EttoreZuccato2,LubertusBijlsma17 8
1ResearchInstituteforPesticidesandWater,UniversityJaumeI,Castellón9 2Department of Environmental Health Sciences, IRCCS - Istituto di Ricerche10
FarmacologicheMarioNegri,Milan,Italy.11 3ToxicologicalCenter,UniversityofAntwerp,Antwerp,Belgium12 4KWRWatercycleResearchInstitute,Nieuwegein,theNetherlands13 5IBED-UniversityofAmsterdam,Amsterdam,theNetherlands14 6DepartmentofChemistry,UniversityofBath,Bath,UnitedKingdom15 7Swiss Federal Institute of Aquatic Science and Technology (Eawag), Dübendorf,16
Switzerland17 8NorwegianInstituteforWaterResearch(NIVA),Oslo,Norway18 19 20 Runninghead:MSstrategiesforinvestigatingillicitdrugsinwastewater21 22 23 *Authorforcorrespondence:24 Prof.Dr.FélixHernández25 ResearchInstituteforPesticidesandWater,UniversityJaumeI26 Avda.SosBaynats/n27 E-12071Castellón,Spain28 e-mail:[email protected] tel:+3496438736630 31
brought to you by COREView metadata, citation and similar papers at core.ac.uk
provided by Repositori Institucional de la Universitat Jaume I
2
Tableofcontents32
33
1 Introduction
2 Targetandnon-targetapproaches
3 Samplingapproachesandsamplepreparation
3.1 Sampling
3.2 Monitoring
3.3 Collectionof(meta)information
3.4 StabilityofIDsbiomarkersinthesamplesunderstorageconditions
3.5 Sampletreatment
4 ApplicationsofLow-ResolutionMassSpectrometry
5 ApplicationsofHigh-ResolutionMassSpectrometry
5.1 Wide-scopescreening
5.2 Non-targetanalysis
5.3 Investigationofmetabolitesandtransformationproducts
6 Chiralanalysis
7 Relevantanalyticalparametersandqualitycontrol
8 Generalsummaryandperspectives
34
35
3
Listofacronymsandabbreviations36 37
CBH Cellobiohydrolase
EDDP 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine
EF EnantiomericFraction
EI ElectronIonization
EMCDDA EuropeanMonitoringCentreforDrugandDrugAddiction
ESI ElectroSprayIonization
GC-MS GasChromatographycoupledtoMassSpectrometry
HE HighcollisionEnergy
HRMS High-ResolutionMassSpectrometry
IDB IllicitDrugBiomarker
ILIS Isotope-LabelledInternalStandards
IP IdentificationPoint
LC-MS LiquidChromatographycoupledtoMassSpectrometry
LC-MS/MS Liquidchromatographycoupledtotandemmassspectrometry
LE LowcollisionEnergy
LOD LimitsofDetection
LOQ LimitsofQuantification
LRMS Low-ResolutionMassSpectrometry
MDA 3,4-methylenedioxyamphetamine
MDMA 3,4-methylenedioxymethamphetamine
NPS NewPsychoactiveSubstances
QC QualityControl
QqQ Triplequadrupoleanalyzer
QSRRs QuantitativeStructure-RetentionRelationships
SCORE SewageanalysisCORegroupEurope
SDL ScreeningDetectionLimit
SIM SelectedIonMonitoring
s/n signal-to-noise
SRM SelectedReactionMonitoring
TIC TotalIonChromatogram
TPs TransformationProducts
tR Retentiontime
4
38 39
UHPLC Ultra-HighPerformanceLiquidChromatography
WBE Wastewater-BasedEpidemiology
WWTP WasteWaterTreatmentPlant
5
Abstract40
Theanalysisofillicitdrugsinurbanwastewateristhebasisofwastewater-based41
epidemiology (WBE), and has received much scientific attention because the42
concentrationsmeasuredcanbeusedasanewnon-intrusivetooltoprovideevidence-43
basedandreal-timeestimatesofcommunity-widedrugconsumption.Moreover,WBE44
allows monitoring patterns and spatial and temporal trends of drug use. Although45
informationandexpertise fromotherdisciplines is required to refineandeffectively46
apply WBE, analytical chemistry is the fundamental driver in this field. The use of47
advancedanalyticaltechniques,commonlybasedoncombinedchromatography-mass48
spectrometry, is mandatory because the very low analyte concentration and the49
complexity of samples (raw wastewater) make quantification and identification/50
confirmationofillicitdrugbiomarkers(IDBs)troublesome.51
Wereviewthemost-recentliteratureavailable(mostlyfromthelastfiveyears)52
onthedeterminationofIDBsinwastewaterwithparticularemphasisonthedifferent53
analytical strategiesapplied.Thepredominanceof liquidchromatographycoupledto54
tandemmassspectrometrytoquantifytargetIDBsandtheessencetoproducereliable55
and comparable results is illustrated. Accordingly, the importance to perform inter-56
laboratoryexercisesandtheneedtoanalyzeappropriatequalitycontrolsineachsample57
sequence is highlighted. Other crucial steps in WBE, such as sample collection and58
samplepre-treatment,arebrieflyandcarefullydiscussed.Thearticlefurtherfocuseson59
thepotentialofhigh-resolutionmassspectrometry.Differentapproachesfortargetand60
non-target analysis are discussed, and the interest to perform experiments under61
laboratory-controlled conditions, as a complementary tool to investigate related62
compounds(e.g.,minormetabolitesand/ortransformationproductsinwastewater)is63
treated.Thearticleendsupwiththetrendsandfutureperspectivesinthisfieldfrom64
theauthors’pointofview.65
Keywords:Massspectrometry,Drugsofabuse,UrinaryMetabolites,Wastewater-based66
epidemiology67
68
6
1. Introduction69
Illicit drug use is a global problem with severe consequences, not only for70
people´shealthandwelfare,butalsoasaclearthreattothestabilityandsecurityof71
entire regions and economic and social development. Accordingly, there is a72
considerable financial cost related to illicit drug use, associated with drug use73
prevention,treatmentofaddicts,andonthefightagainstorganizedcrime(EMCDDA,74
2012; Nutt et al., 2007; UNODC, 2014). Policy makers need accurate and reliable75
informationontheuseofthesesubstancesinordertomakeevidence-baseddecisions76
andtoeffectivelyallocateresources.Theprevalenceofillicitdrugusehastraditionally77
been estimatedwith direct subjectivemethods, like general population surveys and78
interviews,andindirectmethodssuchasmonitordrug-relatedcriminality,seizures,and79
hospital records (EMCDDA,2015a).Despiteconsiderable improvementswithmodern80
communication facilities, and the use of complementary methods such as targeted81
studiesandstatisticalmodeling,thesesurveymethodsmainlyrelyonthewillingnessof82
userstoself-reportandtomonitoractions.However,thesocialtaboorelatedtoillicit83
drug use might provoke non-participation and false responses in such surveys that84
makes thesemethods vulnerable and potentially inaccurate. In addition, a common85
challengewithsuchmethodsisthattheyaretime-consuming,expensive,andcomplex86
(Banta-GreenandField,2011).Therefore,thedevelopmentofnewandcomplementary87
approaches is encouraged in order to obtain objective, low-cost, fast, reliable, and88
comparabledata.89
The chemical analysis of illicit drug residues in untreatedwastewater is as a90
valuabletooltocomplementexistingapproachestomonitorspatiotemporalpatterns91
andtrendsofillicitdruguseinlargecommunities(EMCDDA,2015b;Ortetal.,2014c;92
Thomasetal.,2012;Zuccatoetal.,2008).Thisapproachistermedwastewater-based93
epidemiology(WBE),andreliesontheprinciplethatillicitdrugsconsumedbyindividuals94
are excreted, either unchanged or as a mixture of metabolites, into urban sewer95
networks.Thequantitativemeasurementofthesespecificillicitdrugbiomarkers(IDBs)96
inwastewatersamplesreflectsthedrugscollectivelyexcretedbyusersandenablesdata97
tobegatheredondrugusebythecommunitywithinthegeographicalboundarydefined98
bythecatchmentareaofawastewatertreatmentplant(WWTP).Severalcrucialsteps99
7
are involved in this approach (Fig. 1.), which requires significant expertise from100
numerousresearchfields,andtherefore,strongmulti-disciplinarycollaboration(Ortet101
al.,2014a).102
103
104
105
Figure1.MainconsecutivestepsoftheWBEapproachanddatarequiredforeachstep106
(modifiedfrom(Castiglionietal.,2014)).107
108
TheWBEconceptwasinitiallyproposedbyDaughtonin2001(Daughton,2001)109
andfirstappliedin2005throughtheestimationofcocaineuseinItaly(Zuccatoetal.,110
2005). Since then,WBE has expanded to include other illicit drugs, such as heroin,111
cannabis,andamphetamine-likestimulants(Castiglionietal.,2014;EMCDDA,2015b;112
vanNuijsetal.,2011)andnewpsychoactivesubstances(NPS)(Kinyuaetal.,2015;Reid113
et al., 2014b; van Nuijs et al., 2014). Data have also been reported forWBE-based114
analysisofalcohol(Boogaertsetal.,2016;Mastroiannietal.,2014;Reidetal.,2011;115
Rodríguez-Álvarezetal.,2015,2014),tobacco(Castiglionietal.,2015;Rodriguez-Alvarez116
etal.,2014;B.J.Tscharkeetal.,2016),andcounterfeitmedicines(Venhuisetal.,2014).117
An important step in the progression of WBE was accomplished with the118
establishment of a European-wide network (Sewage analysis CORe group Europe –119
Wastewater-based epidemiology
Sample Collection
Sample AnalysisQuantitative determination of biomarkers
Loads of target biomarkers entering the WWTP (g/day)
Amount of substance consumed by the population served by the sewer network
Normalization to the defined population (mg/day/1000 inhabitants)
Amount of substance as doses/day/1000 inhabitants
Flow rate (m3/day)
Human metabolism Correction factors
Mean Dose
Population Estimates
1.
2.
3.
4.
6.
5.
8
SCORE), supportedby the EuropeanMonitoringCentre forDrug andDrugAddiction120
(EMCDDA) (EMCDDA, 2015b). This network has since 2010 standardized the WBE121
approach,coordinatedinternationalstudies(Ortetal.,2014c;Thomasetal.,2012),and122
conductedinter-laboratoryexercisesforqualitycontrolpurposes.Thelatterprovideda123
meanstoestimateandcriticallyassesstheuncertaintyrelatedtothewastewater-based124
estimates (Castiglioni et al., 2013).However, importantWBE researchhas alsobeen125
conductedinothercontinentssuchasAsia(Khanetal.,2014;Kimetal.,2015;Laietal.,126
2013b;Lietal.,2014),Australia(Irvineetal.,2011;Laietal.,2013a;Prichardetal.,2012;127
Tscharkeetal.,2016,2015),NorthAmerica(Banta-Greenetal.,2009;Burgardetal.,128
2013;SubediandKannan,2014),andCentralandSouthAmerica(Bijlsmaetal.,2016;129
Devault et al., 2014; Maldaner et al., 2012; Voloshenko-Rossin et al., 2015).130
Furthermore, a recently published review on neuropsychiatric pharmaceuticals and131
illicit drugs in wastewater treatment plants (Asimakopoulos and Kannan, 2016) is132
recommendedforreadersinterested.133
TheincreasinginterestofWBEisclearlyillustratedbythenumberofpapersand134
citations on the topic (>200 papers in years 2005-2015, >5000 citations; ISIWeb of135
Science),internationalconferencesandworkshopsorganizedonthistopic,andfunding136
received from the European Commission (“http://score-cost.eu/”; “http://sewprof-137
itn.eu/”).138
ChemicalanalysisofIDBsinwastewaterplaysanimportantkeyrolewithinthe139
WBE approach. Advanced analytical techniques and expertise is required to obtain140
accurateconcentrationdataonIDBsinwastewater,becausequantitativedataarethe141
basisofsubsequentback-calculationsofIDBmassloadsanddruguse.Concentrations142
ofIDBsinwastewatersamplesaregenerallyaroundafactor1000lowerthaninhuman143
biological fluids (ng/L versusng/mL),whichpointsout the challenge forquantitative144
analysis.Lowanalyteconcentrationsincombinationwiththecomplexityandunknown145
compositionofthewastewatermatrixmighthampernotonlythesensitiveandaccurate146
quantificationbutalsoasoundidentification.Chromatography-massspectrometryis147
the best-suited approach to obtain the sensitivity, selectivity, and identification148
requirementsinchemicalanalysisdirectedtowardsWBE.149
9
Gaschromatographycoupledtomassspectrometry(GC-MS)(González-Mariño150
etal.,2010;Marietal.,2009)ingeneralprovideshighlevelsofselectivityandsensitivity.151
However,derivatizationof thetargetcompounds isoftennecessary formost IDBs in152
order to make them compatible with GC. Consequently, sample treatment and153
measurement is generally laborious and time-consuming. Liquid chromatography154
coupled tomass spectrometry (LC-MS) is amore-versatile technique that allows the155
determinationofpolar,low-volatility,and/orthermolabilecompounds,whichmostIDBs156
are,withlesssampletreatmentandshorterchromatographicanalysistimes.Besides,157
thesamplematrix(i.e.,water)iscompletelycompatiblewiththistechnique.LC-tandem158
massspectrometry(LC-MS/MS),e.g.atriplequadrupole(QqQ)analyzer,isevenmore159
powerful,andhasbecomethetechniqueofchoiceforthequantitativedetermination160
of(known)IDBsinwastewatersamples(vanNuijsetal.,2011).161
Despite the predominance of LC-MS/MS in WBE studies, the use of high-162
resolution mass spectrometry (HRMS) has been recently explored and opens new163
perspectivesintheanalyticalfield.Itsstrongpotentialtoscreenandforidentification164
purposesoriginatesfromtheacquisitionofaccurate-massfull-spectrumdata.LC-HRMS165
is a powerful technique that allows the wide-scope screening of many illicit drugs,166
metabolitesandtransformationproducts,aswellastheinvestigationofNPS(Alechaga167
etal.,2015;Badeetal.,2015c;Baz-Lombaetal.,2016;Bijlsmaetal.,2013b;Hernández168
et al., 2014; Ibáñez et al., 2014; Reid et al., 2014a). There are several illustrative169
examples(aspresentedlaterinthismanuscript)inthemost-recentliteraturethatshow170
thatmodern analytical chemistry is essential in order to increase our knowledge on171
trendsinsubstanceuseinthegeneralpopulation.172
In this article, an exhaustive review of the existing literature is not the goal.173
Rather,theobjectiveistopresentanoverviewoftheapproachbyusingthemost-recent174
literatureavailable,withspecificemphasisonthedifferentanalyticalstrategiesapplied175
forWBE.Mostcitedpapershavebeenpublishedwithinthelastfiveyears,exceptfor176
somethathavealsobeenincludedbecauseoftheirrelevanceinthedevelopmentofthe177
WBEapproach.ThepredominanceofLC-MS/MStoquantifypriority,well-known,target178
IDBs and the essence to produce reliable and comparable results are illustrated.179
Accordingly, the importance to perform inter-laboratory exercises and the need to180
10
analyze appropriate quality controls in each sample sequence is highlighted. Other181
crucialstepsrelatedtoWBE,suchassamplecollectionandsamplepre-treatment,are182
discussed. The article further focuses on novel analytical approaches, such as183
enantiomericprofiling,thedifferentstrategiesfortargetandnon-targetanalysiswith184
LC-HRMS,andontheinteresttoperforminvivoorinvitrometabolismexperimentsand185
degradation laboratory experiments, as a useful tool to investigatemetabolites and186
transformationproductsinwastewater.Thearticleconcludeswiththetrendsandfuture187
perspectivesinthisdisciplinefromtheauthors’pointofview.188
189
2. Targetandnon-targetapproaches190
The terms target and non-target analyses are widely employed in analytical191
chemistry.Otherexpressions,suchasinvestigationofunknownsorsuspectscreening,192
arealsofrequentlyused,andillustratetheanalyticalchallengesincomplexfields,such193
as environmental analytical chemistry (Bletsou et al., 2015; Krauss et al., 2010;194
Schymanskietal.,2014b).Withthe implementationofLC-HRMS inseveralanalytical195
fields,thetermpost-targetanalysishasbeenalsoemployed,andillustratetheworking196
modeinwhichfull-spectrumaccurate-masstechniquesareapplied(Hernándezetal.,197
2005). Clarification of these terms is, however, necessary to fully understand the198
different strategies that can be applied to investigate the presence of IDBs in199
wastewatersamples.200
Target methodologies are commonly analyte-dependent; i.e., compound-201
specific information is required beforemeasurement. Based on this analyte-specific202
information,highly sensitiveand selectiveanalyticalmethods canbedeveloped,but203
othercompoundsthatmightbepresentinthesampleswillremainundetected.Target204
analysisistypicallyappliedinmethodsbasedonLCand/orGCcoupledtoMS(Selected205
IonMonitoring(SIM)mode)ortandemMS(SelectedReactionMonitoring(SRM)mode).206
Alimitedlistoftargetcompoundsisincludedinthescopeofthemethod,andonlythose207
previously selected ions/transitions are monitored. Reliable identification and208
quantification is commonly themain objective pursued in this type of analysis. This209
identificationisachievedthroughacquisitionofatleastthreeionsintheSIMmodeor210
twoMS/MStransitionsintheSRMmode,andevaluationofretentiontime(tR)andion-211
11
intensityratios(SANTE/11945,2015).Theuseofreferencestandardsiscompulsorywith212
this methodology in order to optimize the mass spectrometric measurement213
parametersandforquantitativemethodvalidation.214
ThismethodologycanalsobeappliedwithHRMSinstruments.However,thanks215
to the accurate-mass full-spectrum acquisition at good sensitivity, HRMS offers the216
possibilitytoinvestigatethepresenceofmanyothercompounds,notonlythoseinitially217
targeted.Databasesdevelopedin-housearecommonlyusedtofacilitatescreeningofa218
large number of compounds with HRMS. The information included in the database219
dependsontheavailabilityofareferencestandard.Whenavailable,theinformationis220
verycomplete(i.e.,tR,exactmassofthe(de)protonatedmoleculeand/oradducts,and221
themainfragmentions)tohighlyfacilitatetheanalyticalresearch.Whenthereference222
standardisnotavailable,onlylimitedinformationonthetargetanalytescanbeincluded223
inthedatabase(e.g.,molecularformulaandexactmass,theoreticalisotopedistribution,224
predictedtR).Informationreportedintheliteratureonproductionscanalsobetaken225
intoaccounttofacilitatecompoundidentification.Eveninthisworst-casesituation(i.e.,226
whennostandardisavailable),accurate-massfull-spectrumdatacanbeusedforthe227
tentative identification of the compounds in samples (Hernández et al., 2015a), a228
processwhere the interpretation and justification of the fragment ions observed is229
crucial.Inanycase,thefactthatasearchisdirectedtowardsalistofcompoundsimplies230
atargetapproach, independentof theavailabilityofreferencestandards.This target231
approachiscommonlyknownassuspectscreening(Hugetal.,2014;Kraussetal.,2010)232
whereasotherauthorsusethetermpost-target(Hernándezetal.,2005;Ibáñezetal.,233
2008).234
TargetanalysisbasedonHRMScommonlydetectsandidentifiesthecompounds235
(i.e., qualitative analysis) inwastewater, becauseHRMS really takes advantageof its236
excellent performance for this type of application (Hernández et al., 2014, 2011a).237
However,recentstudieshavealsobeendirectedtowardsthequantitativeanalysisof238
IDBsinwastewater(Bijlsmaetal.,2013b;Fedorovaetal.,2013;González-Mariñoetal.,239
2012;Heuettetal.,2015;vanderAaetal.,2013),andanotableincreaseinthenumber240
of quantitative applications of HRMS that pursue a complete analysis (i.e., sensitive241
detection,reliableidentification,accuratequantification)isexpectedinthenearfuture.242
12
Asignificantadvantageoffull-spectrumacquisitionsisthattheyalsoallowthe243
investigationofanyothercompound,notonlythe listofselectedcontaminants, ina244
non-targetmethodology. In contrast to the (post-) target approach, a genuinenon-245
targetanalysisdoesnotuseanypreviousinformationonthecompoundstobesearched246
inthesamples.Someauthorsusethetermnon-targetscreeningwhentheysearchfor247
unknowns,whichinastrictsensestartswithoutanyinformationonthecompoundsto248
be investigated. The term unknown does not necessarily mean that the compound249
discovered in the analysis is a new or an unreported compound. Following the250
elucidationprocesses, theunknownmightturnouttobeaknowncompound,which251
alreadyhasbeenreportedintheliterature,butunexpectedornotspecificallysearched252
forinthesamples.Inagenuinenon-targetanalysis,thereisnoanalyteselectionapriori253
(neither before nor after MS acquisition). Under these circumstances, compound254
identificationattracelevelsinwastewaterisachallenge,andcommonlymorethanone255
elementalformulaandseveralplausiblestructuresareobtainedforagivenunknown256
detectedinasample(Ibáñezetal.,2008;Kraussetal.,2010;Schymanskietal.,2014a).257
Moreinformationonnon-targetanalysisappliedintheenvironmentalfieldcanbefound258
elsewhere (Chiaia-Hernandezetal., 2014;Hogenboometal., 2009;Hugetal., 2014;259
Schymanskietal.,2015,2014b;vanLeerdametal.,2014).260
Most IDBsareof (medium)highpolarity; therefore,LC-HRMScommonlyuses261
TOFandOrbitrapanalyzers.TheabsenceofstandardizedmassspectrallibrariesinLC-262
MS isanadditionaldifficulty innon-targetanalysis,opposite toGC-MSwithelectron263
ionization (EI), where the availability of commercial libraries (e.g., NIST) offers the264
possibilitytoidentifycompoundsbymatchingexperimentalandlibraryspectra.265
In order to have amore-realistic and complete overview on the presence of266
organiccontaminantsingeneral,andonIDBsinparticular,acombinationoftarget(both267
withorwithoutstandards(i.e.,suspectscreening)andnon-targetmethodologiesseems268
tobethemost-attractiveapproach(Hugetal.,2014).Furthermore,thecombinationof269
GC-HRMSandLC-HRMS(e.g.,usethesameQTOFinstrumentforbothconfigurations)270
movestowardsamore-comprehensivescreeningoforganiccontaminantsintheaquatic271
environmentindependentlyoftheirpolarityandvolatility(Hernándezetal.,2015b).272
273
13
3. Samplecollectionapproachesandsamplepreparation274
Measurementswithhigh-endinstrumentsandsophisticatedstatisticalanalysis275
cannot compensate or reveal deficiencies in sample collection. Depending on the276
desiredlevelofrepresentativenessandaccuracy,samplecollectionisasimportantas277
any subsequent steps. A sound understanding of the investigated environment is278
imperativeandmustbedocumentedindetail.FormostapplicationsinWBE,theend279
user relies on 24-hour composite influent (i.e., raw) wastewater samples collected280
routinely at the inlet of a WWTP. We briefly outline how such a sample is ideally281
collected (sampling) and how many samples are needed (monitoring) for specific282
applications.283
284
3.1. Sampling285
The number of consumers of a specific substance, pharmacokinetics, the286
populationconnected toaWWTP,and thehydraulicpropertiesof thesewersystem287
determinei)thenumberoftoiletflushesthatcontainthesubstanceofinterest,andii)288
over which period an individual toilet flush expands when it passes the sampling289
location.Thesetwofactorsdeterminethetemporalvariabilityonthescaleofminutes,290
whichinturndeterminestherequiredsamplingfrequencytocollectarepresentative291
sample(i.e.,howmanysamplesmustbecollectedandpooledoveracertainperiodfor292
analysis).Duetothepotentiallysmallnumberofrelevanttoiletflushes–atleastforone293
of multiple substances analyzed in the collected sample – it is recommended that294
sampling intervalsdonotexceed5-10minutesat the influentof largeWWTPs.Even295
shorter sampling intervalsof 1-5minutesarenecessary for composite samples from296
effluentsofindividualpremises.Attheeffluentofe.g.aprison,thetoiletflushesextend297
overshorterperiodsandtheabsolutenumberofsubstance-relatedflushesistypically298
muchsmallerthanattheinfluentofa(large)WWTP,bothleadingtoasubstancepattern299
that fluctuatesmuchmore at the scale of a fewminutes. This is also applicable to300
influentsofverysmallWWTPs,whereitmaybebeneficialtosamplefromtheeffluent301
ofaprimarytreatmenttank,whichattenuatestemporalfluctuationstosomeextent.302
However,pleasenote that the latteralso removessomeparticulatematterand that303
WWTP-internalrecirculationmayinfluencemassloadsthere.Shortersamplingintervals304
14
arealsorequiredforthecollectionofrepresentativesamplesthatextendoverperiods305
<24h,e.g.hourlycompositesamplestoreliablyassessdiurnalvariations.Pleasenote,306
grabsamplestodeterminediurnalvariationsarenotsuitablebecauseofpotentialhigh307
short-term variations. In addition, intra-day variations in wastewater flows require308
samples to be collected in a flow- or volume-weighted manner. More details and309
peculiaritiesforwastewatersamplinginsewers,anoverviewofrelevantliterature,and310
alistofrequirementsforaseriesoftypicalapplicationsisdescribedelsewhere(Coutu311
etal.,2016;DeKeyseretal.,2010;Ort,2014;Ortetal.,2010a,2010b).312
313
3.2. Monitoring314
Ideally,onewouldanalyze365dailycompositesamplesperyear.Duetolimited315
resources, this amount of samples is usually not feasible. Different316
(research/epidemiological) questions require different monitoring designs, and317
obviously more samples provide higher accuracy. Random day-to-day variability,318
systematic weekly cycles, and seasonal fluctuations influence baseline variation.319
Togetherwith thedesired level of sensitivity and significance, thebaseline variation320
determinestherequirednumberanddistributionofsamples.Todate,twomonitoring321
design studies have investigated different approaches that aim to answer different322
questions.Theyarebasedonafewavailablelong-termtimeseries;i.e.,datasetswith323
observationsovermorethan28consecutivedays.Inbrief,itwasfoundthatthebaseline324
variation of almost all investigated drug residues in five different catchments325
(populationsizesthatrangefromapprox.7000to1.3millionpeople)didnotexceed326
80%(ascoefficientofvariation),notaccountingforanytemporalcorrelation(EMCDDA,327
2016).Basedon thesedata,Ortetal. (Ortetal., 2014b)proposed that56 stratified328
random samples (10working days and 4weekend days per quarter) are suitable to329
estimateanannualmeanwithanaccuracyof10%.Humphriesetal.(Humphriesetal.,330
2016) evaluatedmore informedapproaches,which relyon knowledgeaboutweekly331
cycles.Inthepresenceofstrongweeklycycles(e.g.,cocaineorMDMA),itisefficientto332
distributemonitoringdayssystematicallybyconsideringpeak,mid,andthroughusage333
days. The identificationofweekly cycles requires an intensive,monitoringperiod. In334
return,theaccuracy,particularlyofintra-annualtrends,improvestheinformedroutine335
15
monitoring compared to an uninformed schemewith the same reduced number of336
samples. In thecontext toassesseffectsof interventions, thebaselinevariation, the337
magnitudeoftheeffecttobeshown,andtheconfidenceleveldeterminethenumber338
ofrequiredsamples.339
340
3.3. Collectionof(meta)information341
Anexampleofaquestionnairetocollect(meta)informationrelevanttoevaluate342
theappropriatenessofsamplingandtofacilitatetheinterpretationofresultsiscanbe343
found(Ortetal.,2014c).Thispaperencompassescatchmentproperties(e.g.,hydraulic344
residencetime,populationsize,andhowitwasestimated),aswellasdetailsonsample345
collectionandhandling.346
347
3.4. StabilityofIDsbiomarkersinthesamplesunderstorageconditions348
ItisoftennotpossibletoimmediatelyanalysesamplesforthepresenceofIDBs.349
Itis,therefore,necessarytostorewastewatersamplesuntilanalysisunderconditions350
that avoid transformationof theanalytes,becausebiotransformationduring storage351
wouldleadtofalseinterpretationsofWBEdata,evenifanalyticalmethodsareaccurate.352
For most IDBs, experiments have been performed to evaluate stability for353
different storage conditions, including various temperatures, pH values, and354
preservation agent additions, and for different time frames (reviewed in detail by355
(McCalletal.,2016).Storageofwastewatersamplesat-20°Censuresstabilityofmost356
IDBsforatleast3weeks.ForsomeIDBs(i.e.,theamphetamine-typestimulantsand11-357
nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH)),experimentshaverevealed358
thattheyareevenstableat-20°Cformorethan15weeks(McCalletal.,2016).Stability359
isensuredforonlyseveraldaysat4°C,whereasotherIDBs(e.g.,cocaine)arewithin360
severalhourstransformedatthistemperature(McCalletal.,2016).361
Acidification of the samples increases stability of the majority of IDBs, but362
significantly enhances biotransformation of THC-COOH. Because multi-analyte363
determinationsareoftenappliedinWBEstudies,itis,therefore,notadvisabletoacidify364
thesamplesbeforestorage.Theeffectoftheadditionofpreservationagentssuchas365
16
sodiummetabisulfite(Na2S2O5)hasalsobeenstudied,andrevealedhigherstabilityfor366
cocaineanditsmetabolitebenzoylecgonine(McCalletal.,2016).However,fortheother367
IDBs,moreexperimentsneedtobeperformedinordertoevaluatetheefficacytoadd368
preservationagentstowastewatersamplesforstoragepurposes.369
370
3.5. Sampletreatment371
Inordertoremovesolidparticlesfromthewastewatersamples,twostrategies372
canbefollowed:(i)afiltrationstepwithmembraneofglassfiberfilterswithporesizes373
as lowas0.1µm,or (ii)acentrifugationstep. Inaddition,becauseconcentrationsof374
mostIDBsinwastewaterareintheng/L-µg/Lrange,apreconcentrationstepisgenerally375
required prior to analysis in order to achieve the necessary quantification limits.376
However, some modern analytical instruments allow direct injection of filtered or377
centrifuged wastewater due to the high sensitivity provided (Berset et al., 2010;378
Biscegliaetal.,2010;Boixetal.,2015;Chiaiaetal.,2008;Laietal.,2011).379
A sample-preparation step is commonly needed not only to preconcentrate380
analytes,butalsotoremovematrixcomponentsthatmightinterferewiththeanalytical381
measurement(e.g.,ionizationsuppression/enhancementprocessesinLC–MS)ofIDBs.382
Byfar,themost-usedprocedurereportedintheliteratureisoff-linesolid-phase383
extraction (SPE)withsamplevolumesbetween50mLand1000mL (vanNuijsetal.,384
2011).PopularSPEsorbentsusedforareproducibleextractionofIDBsfromwastewater385
arebasedonapolymericbackbonewithreversed-phaseorcation-exchangeproperties.386
Some methods demonstrated that off-line SPE sample preparation could also be387
incorporatedinafullyautomatedon-lineSPEapplicationthatisdirectlylinkedtothe388
LC-MSanalysis(Fedorovaetal.,2013;Heuettetal.,2015;Postigoetal.,2008).389
Some alternativeways of sample preparation can be found in the literature.390
González-Mariñoetal. (González-Mariñoetal.,2009)appliedcommerciallyavailable391
molecular imprinted polymers (MIPs) to extract and concentrate amphetamine-type392
stimulantsfromwastewater,andreportedbetterperformanceoftheMIPsintermsof393
selectivity, sensitivity, accuracy, and precision compared to off-line SPE. The main394
drawbacks of this approach were no possibility for multi-class analysis, and higher395
17
analysistimeandcost.Theusefulnessofsolid-phasemicroextraction(SPME)forsample396
preparationtoanalyzeamphetamine-typestimulantsorTHC-COOHinwastewaterhas397
beendemonstrated(Racamondeetal.,2013,2012).SPMEishighlycompatiblewithGC-398
MS, and shows good performance; however, the main drawback was the limited399
applicabilitytodeterminatemulti-classcompounds,whichisdesiredforWBEpurposes.400
401
4. ApplicationsofLow-ResolutionMassSpectrometry402
Low-resolutionMSsystems,witheitheriontraporQqQanalyzers,arethemost403
widely applied for the quantitative determination of IDBs in wastewater. TheseMS404
systems typicallyoperate in theMS/MSmode,whereoneormoreproduct ionsare405
monitored by selecting appropriate precursor-to-product ion transitions (i.e., SRM).406
Evenwiththisapproach,therearesomeprobabilitiesthatothercompounds,notrelated407
to the analyte, can share the same transition. Therefore, at least two transitions is408
required to be monitored, and the presence of a compound is considered to be409
confirmed ifbothtransitionsproduceachromatographicpeakat thesameretention410
time, that corresponds to that of the injection of a reference standard. Identity411
confirmationisoftheutmostimportancebecauseitgivestherequiredconfidenceto412
the reported results and reduces the likelihood of reporting false positives. The413
confirmationofidentityisespeciallyrelevantwhenanalyzinghighlycontaminatedand414
complexmatricessuchasinfluentwastewatersamples.Forconfirmation,notonlythe415
acquisitionof several transitions is needed, but also the complianceof the ion ratio416
betweenreferencestandardsandsamples.Thisimportantaspectisdiscussedinmore417
detailinsection7“Relevantanalyticalparametersandqualitycontrol”.418
Although ion-trap analyzers have been used in this field (Bones et al., 2007;419
Gheorgheetal.,2008;MartínezBuenoetal.,2011;Postigoetal.,2008),LC-MS/MSwith420
QqQhasbecomethemost-populartechniqueduetoitsexcellentperformanceinterms421
ofrobustness,dynamicrange,sensitivity,andselectivity.Thesecharacteristics,together422
withthecompatibilityofLC-MS/MSwithaqueoussamplesandmostlypolaranalytes423
targeted inWBEstudies,allowone tonotably simplify sample treatment. LC-MS/MS424
withQqQcannowadaysbeconsideredastheworkhorseinanalyticallaboratoriesthat425
dealwithWBE.Thisfacthasalsobeenillustratedinmonitoringstudiesofillicitdrugsin426
18
wastewater,wherethemajorityoflaboratoriesappliedthistechnique(Castiglionietal.,427
2008;Ortetal.,2014c;Thomasetal.,2012).428
Someoftheearlystudies,usedonlyonetransitionforquantification(Bartelt-429
Hunt et al., 2009; Chiaia et al., 2008; Gheorghe et al., 2008;Metcalfe et al., 2010).430
However, it isnowadayswidelyaccepted thatconfirmationofanalyte identity inLC-431
MS/MS-based methodologies requires a minimum of two transitions (European432
Commission, 2002). Yet, the acquisition of more transitions per compound would433
obviouslygivemoreconfidence to theconfirmationprocess,and is feasiblewith the434
latestanalyticalinstrumentswithfasteracquisitiontimes(Bijlsmaetal.,2014a,2009;435
Boledaetal.,2007).ThelimitedfragmentationinESI,frequentlywithlow-abundance436
secondary and tertiary transitions, can limit the absolute number of useful MRM437
transitionsforidentificationinsomeparticularcases.Nevertheless,withtheexcellent438
sensitivity of the new instruments, the acquisition of, at least, two transitions is439
commonlynotaproblem.Typicallythemost-abundanttransition isselectedtofavor440
quantificationatlowconcentrations(quantifier,Q),andtheotheronesareacquiredfor441
confirmation (qualifier, q). At this point, it is also important to understand the442
fragmentationpatternoftheanalytesunderexperimentalconditionstoallowselection443
ofanalyte-specificfragmentsinordertominimizepotentialinterferencesofthematrix444
and/or background noise. Hence, it might occur that the most-sensitive transition445
presentsmorematrixinterferenceand/orbackgroundnoise,andmightthereforenot446
bethemostappropriateforquantification.Asanexample,THC-COOH,ametaboliteof447
the active ingredient found in cannabis, was measured in the positive electrospray448
ionization(ESI)mode.Inthismode,thetransitionm/z345>327isoccasionallyselected449
forquantification(Table1).However,thistransitioncorrespondstoanon-specificloss450
ofwater,whichmightbemorepronetointerferenceswhenanalyzingcomplexmatrices,451
suchaswastewater (Pozo, Sancho, Ibáñez,Hernández,&Niessen,2006). This fact is452
demonstratedinFigure2,wherethreedifferenttransitionswereacquiredtomeasure453
THC-COOH in influent wastewater. The transitions 345 > 327 and 345 > 299,454
correspondingtolossesofH2OandHCOOH,respectively,presentedhighernoisethan455
theless-abundant,butmore-selective,transition345>193.Thesematrixinterferences456
19
hasalsobeenobservedinthenegativemode;whenanon-specificlossofCO2(343>457
299)wasmeasured.458
459
460
461
Figure2.SelectivityofTHC-COOHtransitions.462
Table1showsthequantification(Q)andconfirmation(q)transitionsusedduring463
the monitoring campaign 2015 coordinated by SCORE to measure the most widely464
studiedIDBsininfluentwastewaterinWBEresearch.Ingeneral,theQtransitionis,in465
moststudies,thesamewithfewexceptions.However,moredifferencesareobserved466
inthequalifiertransitionusedforconfirmation.467
468
469
470
471
472
473
Time3.50 4.00 4.50 5.00 5.50
%
0
100
3.50 4.00 4.50 5.00 5.50%
0
100
3.50 4.00 4.50 5.00 5.50
%
0
100
DOA0057 5: MRM of 4 Channels ES+ 345 > 193.2
3.66e5Area
4.0216423
DOA0057 5: MRM of 4 Channels ES+ 345 > 299.3
1.86e6Area
DOA0057 5: MRM of 4 Channels ES+ 345 > 327.3
1.10e7Area
Time3.50 4.00 4.50 5.00 5.50
%
0
100
3.50 4.00 4.50 5.00 5.50
%
0
100
3.50 4.00 4.50 5.00 5.50
%
0
100
DOA0064 5: MRM of 4 Channels ES+ 345 > 193.2
3.74e5Area
4.0218042
DOA0064 5: MRM of 4 Channels ES+ 345 > 299.3
6.00e5Area
4.0226048
DOA0064 5: MRM of 4 Channels ES+ 345 > 327.3
1.10e6Area
4.0243030
O CH3
O
OH
H3C
H3C
O CH3
OH
H3C
H3C
-H2O
-H2O,-CO
H2C
HO CH3
OH -C9H12O2
Solvent Influentwastewater
4.0223494
4.0230205
4.021.80x103
4.022.60x103
4.024.30x103
4.021.64x103
4.022.35x103
4.023.02x103
20
Table1.SRMtransitionsmostoftenusedwithLC-QqQ-MSinstrumentstodetermine474 IDBsinwastewaterduringthemonitoringcampaign2015ofSCORE(“http://score-475 cost.eu/”).476
Compound Q-transition(#Labs/#totalLabs)a
q-transition(#Labs/#totalLabs)b
Amphetamine 136>91(12/17) 136>119(10/12)136>65(2/12)
136>119(5/17) 136>91(5/5) Methamphetamine 150>91(13/17) 150>119(11/13)
150>65(2/13) 150>119(4/17) 150>91(4/4) Methylenedioxymethamphetamine(MDMA) 194>163(15/17) 194>105(11/15)
194>135(3/15)194>77(1/15)
194>135(1/17) 194>105(1/1) 194>133(1/17) 194>105(1/1) Cocaine 304>182(15/16) 304>82(9/15)
304>150(2/15)304>105(2/15)304>77(2/15)
304>82(1/16) 304>182(1/1) Benzoylecgonine 290>168(17/17) 290>105(13/17)
290>77(3/17)290>82(1/17)
THC-COOH(+)mode
345>299(6/10) 345>245(4/6)345>327(1/6)345>193(1/6)
345>327(2/10) 345>299(1/2)345>193(1/2)
345>193(1/10) 345>299(1/1) 345>41(1/10) 345>327(1/1)THC-COOH(-)mode
343>299(3/5) 343>245(2/3)343>191(1/3)
343>245(2/5) 343>299(2/2)aNumberoflaboratoriesthatselectedtheSRMtransition(Q)forquantification/the477
totaloflaboratoriesthatusedLRMSanddeterminetheIBD.478 b Numberof laboratories that selected theSRM transition (q) for confirmation/ the479
totaloflaboratoriesthatselectedthesameQ-transition(seealsoa)480 481 Note: More-detailed information regarding the analytical procedures can be found482 elsewhere:(Andrés-Costaetal.,2014;Bersetetal.,2010;Bijlsmaetal.,2014a;Borova483 et al., 2014; Castiglioni et al., 2006; Castrignanò et al., 2016; Devault et al., 2014;484 Fedorovaet al., 2013;Kankaanpääet al., 2014;Karolaket al., 2010; Lai et al., 2011;485 Postigoetal.,2008;Sentaetal.,2013;Tscharkeetal.,2015;vanNuijsetal.,2009).Itis486 noteworthythatnotallanalyticalmethodologiesusedduringthemonitoringcampaign487 werepublished.488 489
21
TheQ-transitionsselectedforcocaineanditsmetabolitebenzoylecgonine(BE)490
areinpracticallyallcases304>182and290>168,respectively.Bothcorrespondtothe491
neutrallossofbenzoicacid,specificforcocaineanditsmetabolites(Bijlsmaetal.,2011;492
Castiglionietal.,2008).Inrelationtotheq-transition,somedifferenceswereobserved,493
but304>82and290>105weremostfrequentlyselected.TheQ-andq-transitionsfor494
amphetamineareinmostcases136>91and136>119,andformethamphetamine,495
150>91and150>119,respectively.Morevariationoccursintheselectionoftransitions496
forMDMA,althoughmostlaboratoriesuse194>163forquantification.497
THC-COOH has been measured in the negative- and positive-ESI modes.498
Obviously, different transitions/ions are selected in each case. The determination of499
THC-COOH is more problematic than other drugs investigated. The use of different500
ionizationmodes,thepoorersensitivityforthiscompound,andthematrixinterferences501
thataffectLC–MS/MSanalysismakeitsdeterminationmoretroublesome(Bijlsmaetal.,502
2014b;Ortetal.,2014c;Vazquez-Roigetal.,2013).Moreover,othernon-instrumental503
factors,suchaspossiblesorptiontosolids(Harmanetal.,2011),in-sewerandin-sample504
stability(McCalletal.,2016),mightalsoplayanimportantroleinthedifficultytoget505
satisfactoryresultsforthiscompound.Althoughsomedifficultiesmightberelatedtoits506
differentphysico-chemicalproperties(lowerpolarity)comparedwithotherillicitdrugs507
andmetabolites,anunambiguousexplanationhasnotyetbeenfound.Theproblems508
associatedtothedeterminationofTHC-COOHhavebeencorroboratedwiththeresults509
ofinter-laboratoryexercises,wheredataforthiscompound indicatethatrecoveriesof510
spikedamountsofTHC-COOHtowastewaterinvariablyarelow;thosedatasuggesta511
systematic underestimation of the true concentrations of THC-COOH in this type of512
matrix.513
The examples, shown above, illustrate that the selection of appropriate514
transitionsisnotabanalaspect,anditrequiresadetailedstudybefore,consideringnot515
only the abundance of the ions (used as common criterion), but also specificity and516
associatedissuessuchasbackgroundnoise.517
518
5. ApplicationsofHigh-ResolutionMassSpectrometry519
22
HRMS is a powerful technique with many different applications in the520
investigationofIDBsinwastewater,fromthescreeningoflargenumberofcompounds,521
the elucidation of unknowns, the identification of new metabolites and522
degradation/transformationproducts(TPs),toquantificationoftargetanalytesatlow523
concentrations.SeveralreviewshavebeenpublishedontheuseofHRMStodetermine524
of licit and illicit drugs in environmental analysis, and are recommended for those525
researchers interested in this field (Farré et al., 2012;Hernández et al., 2014, 2012;526
Kaufmann,2014;Petrovicetal.,2010;Vazquez-Roigetal.,2013;WongandMacLeod,527
2009).528
529
5.1. Wide-scopescreening530
HRMSallowstheefficientscreeningofalargevarietyofcompounds,including531
IDBs, in wastewater. Its potential comes from the acquisition of accurate-mass full-532
spectrumdata(Kaufmannetal.,2010).Thesedataallowonetoscreenofcompoundsin533
apost-targetwaywithouttheneedtopre-selecttheanalytesformethoddevelopment,534
as stated inprevious sections. Furthermore, thepresenceof compounds initiallynot535
considered,suchasnewsubstancesandmetabolites/TPs,canbealsoinvestigatedfrom536
dataacquiredinaretrospectivewaywithouttheneedforadditionalanalysis(Bijlsmaet537
al., 2013b; Hernández et al., 2011a). This ability is advantageous, because in some538
occasions,samplesmightalreadyhavebeendiscardedortheanalytesaredegraded,so539
additional sample injectionsmightnotbepossible. In thisway, thescreeningcanbe540
furtherwidenedbyreprocessingrawdatawithouttheneedtoperformnewanalysis.541
The most-used HRMS analyzers are undoubtedly TOF and Orbitrap. Both542
instrumentscanbeefficientlycoupledwithLC,althoughTOFMShastheadvantageof543
easy coupling with ultra-high performance liquid chromatography (UHPLC). On the544
contrary,restrictionsduetothelowerscanspeedcanlimittheapplicabilityofcoupling545
anOrbitrapwith UHPLC (Hernández et al., 2014). As a consequence of the intrinsic546
characteristics of these analyzers, the use of LC-HRMS enables screening for a large547
numberofIDBsatsatisfactorysensitivitywithinoneanalysis.Obviously,therestrictions548
derived from the chromatographic and ionization processes and from sample pre-549
treatmenthavetobetakenintoaccountinasearchforcontaminants.TOFanalyzers550
23
havebeenwidelyusedtoscreenlicitandillicitdrugs,andtheirpotentialhasbeenwell-551
documented (Hernández et al., 2014, 2011a).Mass resolution typically ranges from552
20,000uptorecently80,000FWHM,whereasmassaccuracy<2ppmandquantitative553
linearrangesstarttobecomeusual.FollowingtheinventionbyMakarov(Hardmanand554
Makarov,2003;Huetal.,2005;Makarovetal.,2006),theOrbitraphasgainedpopularity555
intheinvestigationofemergingcontaminants(deVoogtetal.,2011;Fedorovaetal.,556
2013). An Orbitrap possesses high mass resolution (>100,000 FWHM), high mass557
accuracy(<5ppm)andacceptabledynamicrange(5·103).Thenewestinstrumentscan558
reachupto450,000FWHMatm/z200andsub-ppmmassaccuracy.However,themain559
drawbackisitsscanningspeed,whichisinversetomassresolution.Thus,acompromise560
betweenachievableresolutionandadequatechromatographymustbefound(Kellmann561
etal.,2009;MakarovandScigelova,2010).562
Hybrid configurations increase the potential of these analyzers for screening563
purposes.Themost-commonareQ-TOFandLIT-Orbitrap,althoughotherpossibilities564
exist, such as IT-TOF and Q-Orbitrap. These hybrid instruments provide relevant565
structural information by obtaining accurate-mass product-ion spectra afterMS/MS566
experiments. InformationobtainedwithMS/MS is highly useful to confirmpotential567
positivesrevealedby,forexample,HRMSorQqQanalysis,andtoelucidatestructures568
ofunknownsorsuspectcompounds.However,thepre-selectionoftheprecursorionis569
required forMS/MS product-ion generation, and, therefore, a second injection is in570
principleneeded. Inorder toovercomethese limitations,product-ionspectracanbe571
collectedwithdata-dependentacquisition (DDA). In thismode, the first scanusually572
worksasthesurveyscan,wheredataareprocessed‘on-the-fly’tosearchforpotential573
compoundsofinterestbasedonpredefinedselectioncriteria;e.g.,intensitythreshold574
orasuspectinclusionlist.Iftheselectioncriteriaaremetortheincludedionisobserved,575
thenasecondMS/MSscan(data-dependent)isperformed.Themajoradvantageofthis576
approach is thecollectionof“clean”structural information in justone injection.The577
mainlimitationsaretheintensitythresholditself,aswellasthesizeoftheinclusionlist578
(numberof suspects searched);bothcannegativelyaffect theachievabledutycycle.579
Hence,adecreaseinthenumberofdatapoints(i.e.,thenumberofscans),affectsthe580
detectabilityofchromatographicpeaks.581
24
Advantageously,mostcurrentinstrumentsalsoallowtheacquisitionoffull-scan582
spectra at different collision energies in just one injection. As a function of the583
instrumentand/ormanufacturer,thisoperationmodefortheQTOFanalyzerisknown584
asMSE(Castro-Perezetal.,2002;Díazetal.,2011;Hernándezetal.,2011a;Plumbetal.,585
2006)inthecaseofWaters,broadbandcollision-induceddissociation(bbCID)(Dasenaki586
etal.,2015)inthecaseofBruker,orall-ionsMS/MS(Kinyuaetal.,2015)inthecaseof587
Agilent.LikewiseforQ-OrbitrapinstrumentsfromThermo,thistypeofacquisitionisalso588
possible,andknownasAllIonFragmentation(AIF)(Berendsenetal.,2015;Coscollàet589
al.,2014),orvariableData-IndependentAnalysis(vDIA)(ZomerandMol,2015).These590
approachesarepossiblethankstotheavailabilityofcollisiongasinsidethecollisioncell591
of the hybrid instruments. With the application of low energy in the collision cell,592
fragmentationisminimized,andtheinformationobtainedcorrespondsnormallytothe593
parent molecule ((de)protonated and/or adducts in some cases). At high collision594
energy,fragmentationofthemoleculeisfavored.Inaddition,thehigh-energyfunction595
providesnotonly fragmentationspectra similar toMS/MSexperiments,butalso the596
isotopicpatternofthefragments,anditconservesadductand/ordimerinformationas597
the quadrupole works as an ion guide. In this way, (de)protonated molecule and598
fragmentiondatacollectionarebothenabledinasingleacquisitionwithouttheneed599
toselecttheprecursorion;therefore,notaffectingnegativelythedutycycle.600
Oneofthemaindifficultiesinwide-scopescreeningistoensurethatthemethod601
candetectandidentifyallcompoundsincludedinthetargetlist.Referencestandards602
are obviously required for a final confirmation of the identity, but also needed to603
performmethodvalidation.Qualitativevalidationofthescreeningisakeyaspect,but604
alaboriousandtime-consumingtask.Theobjectiveistoensurethatthemethoddetects605
agivencompoundatanestablishedminimumconcentration;therefore,thescreening606
detectionlimit(SDL)isthemainparameterevaluated.Tothisaim,watersamplesspiked607
at different levels need to be tested to establish the SDL as the lowest analyte608
concentrationtestedthatcanbedetected(wihtthemostabundantion;i.e.,normally609
the(de)protonatedmolecule).Inabsenceofguidelinesintheenvironmentalfield,the610
approachusedinotherfields,suchaspesticideresidueanalysis(SANCO,2013)ordoping611
control analysis (Pozo, Van Eenoo, Deventer, & Delbeke, 2007) can be adopted. To612
25
accept the empirical value of SDL, it is necessary to have at least 95% of positive613
detections in the spiked samples tested. Another key parameter is the limit of614
identification; i.e., the lowest concentration tested for which the compound can be615
detected(onlyoneion)andidentified(atleasttwoaccurate-massions,withacceptable616
masserrors).Foridentification,otherparametershavetobealsoconsidered,suchas617
retentiontimeandion-ratios(seebelow).618
Qualitativevalidationisnormallyperformedwithselectedcompoundsfromthe619
target list that are taken as amodel, due to the extreme difficulties to validate the620
methodforthehugenumberofcompoundsthatmightbeincludedinthetargetlist.621
Once themethodology is validated, the screening is applied to sample analysis. The622
occurrence of false positives is drasticallyminimized if strict criteria are applied for623
identificationonthebasisoftheaccurate-massdata;however,onecannotignorethe624
possibilityoffalsenegativesforthosecompoundsthatwerenotpreviouslyvalidated.625
AlthoughthequalitativepotentialofHRMSisevident,quantitativeapplications626
havebeenmorelimiteduntilnow,mainlybecauseHRMSanalyzerstypicallyshowlower627
sensitivity and narrower dynamic range thanQqQ instruments that operate in SRM628
mode.Thus,mostresearchuntilnowhasbeenfocusedonidentificationandelucidation629
purposes. However, Orbitrap and the latest TOF instruments show improved630
performancetoprompttheirusealsoforquantificationofIDBsinwastewater(Bijlsma631
etal.,2013b;González-Mariñoetal.,2012).632
ThestrategyusedforHRMSscreeningstronglydependsontheavailabilityof633
reference standards, as described previously. Nevertheless, when dealing with634
thousandsofcompounds,itisalmostimpossibletohaveallreferencestandardsinthe635
laboratory.Oneof themainbenefitswithHRMS is that reference standardsarenot636
strictly required in a first step of the process, because a tentative identification of637
suspectcompoundscanbemadeonthebasisoftheobtainedinformation.Obviously,638
reference standards highly facilitate the analytical task in the screening, and are639
required forultimateandunambiguous confirmation (Fig. 3); however, theymaybe640
acquiredonlyinafinalstagewhensolidwell-foundedevidenceexistsonthepresence641
of the compound in the sample. In thisway, laboratoriesdonotneed toacquireall642
26
referencestandardsbeforeanalysis,withthesubsequentproblemsofavailability(e.g.,643
TPs),costs,andexpirydates(Ibáñezetal.,2014).644
645
646
Figure3.(Post)-targetscreeningstrategy.647
648
In the absence of reference standards, HRMS data might be sufficient for a649
tentativeidentification(Fig.3).Anexample,identificationof2-ethylidene-1,5-dimethyl-650
3,3-diphenylpyrrolidine(EDDP),ametaboliteofmethadone,inwastewaterbyLC-QTOF651
MS,isshowninFigure4.Bycombiningtheinformationobtainedinthelow-energy(LE)652
function on the protonated molecule and in the high-energy (HE) function on the653
fragment ions, tentative identification of this metabolite was feasible without any654
reference standard. The use of UHPLC also facilitated the assignment of the655
chromatographic peaks that corresponded to this compound (note that some ions656
presentintheHEspectradidnotcorrespondtoEDDP;markedasxinthefigure).657
(post)-Target screeningAnalysis after MS acquisition
Database of target compounds• LC-MS amenable• Reported data
Tentative identification(highly reliable, but laborious
and time-consuming
Standard available Standard unavailable
Information obtained from HRMS• Accurate mass (mass error)• Isotope pattern• Retention time• Fragment ions
Identification/Confirmation
Information in database(exact mass, fragment ions, retention time, isotope pattern)
Information obtained from HRMS• Accurate mass (mass error)• Isotope pattern• Retention time• Fragment ions
Information in database(exact mass, theoretical isotope pattern, predicted retention time)
Confirmation with reference standard (final stage)
27
658
Figure 4. Tentative identification of EDDP, a methadone metabolite. A) LE mass659
spectrum (bottom)HEmass spectrum (top).B)XICsof theprotonatedmoleculeand660
severalfragmentions(XindicatesthatthefragmentionisnotrelatedtoEDDP).661
662
Successful identification depends on the quality of the information provided663
(e.g.,morethanoneaccurate-massisrequired,lowmasserrorsgivemoreconfidence664
to the process) and on the knowledge ofmass spectrometry fragmentation rules to665
properlyjustifythefragmentionsobserved.Previousdatareportedintheliteratureon666
fragmentions(innominalandaccuratemass),whichcanalsobeavailableindatabases667
suchasMassBank (Horaietal.,2010; “http://www.massbank.jp/”), areuseful to the668
analyst. Another interesting tool is retention-timeprediction,whichhelps to discard669
potentialfalsepositivesandtofocustheelucidationprocessononlythosepeaksthat670
fit thepredictedtR.ThesetRpredictorsarebasedonquantitativestructure-retention671
relationships(QSRRs)thatvaryfromverysimple,whichincorporateasingledescriptor672
(Badeetal.,2015b;Kernetal.,2009),tomorecomplex,whichusealargenumberof673
descriptors(Badeetal.,2015a;BarronandMcEneff,2016;Gago-Ferreroetal.,2015;674
Milleretal.,2013;Munroetal.,2015);however,allofthesepredictorsarebasedona675
EDDPC20H24N+
-0.3 mDa
C18H19N+·0.0 mDa
C17H16N+
- 0.2 mDa
C13H16N+
- 0.1 mDa
- 0.3 NH2
NH2
NH
mDaC6H12N+
NH
278.1903 LE
249.1512
234.1277
186.1277
150.0918
108.0811
98.0964
XICHE
A B
X
X
XX
NH
28
singlecolumn,commonlyareversedphase(C18)column.Adirect-mappingtechnique676
(PredRet)abletopredictretentiontimesacrossdifferentchromatographicsystemshas677
also recently been developed (Stanstrup et al., 2015), but is limited to compounds678
havingtobewithinthePredRetdatabase.Althoughthisareaisrapidlyadvancing,the679
principal limitation is the use of a single column for most predictions, with further680
optimizationneededforatrulytransferablepredictiontechnique.681
One of the issues that still remains without broad consensus is the criteria682
appliedforconfidentidentityidentification/confirmation.Itisclearthatacombination683
ofparametersisrequiredforthisaim,includingretentiontimeandMSdata.Accurate-684
massmeasurements givemore confidence for a reliable identification than nominal685
massdata,andthisfactorisrecognizedinseveralguidelines,which,forexample,give686
moreidentificationpointstoHRMSionsthanLRMSions(EuropeanCommission,2002).687
In addition, the ion intensity ratio is commonly used as a key parameter in the688
identificationprocess. It iswidely accepted that at least twoaccurate-mass ions are689
requiredforaconfidentidentificationwithHRMS.However,twomainissuesneedtobe690
considered:1)what istheacceptablemasserror?2)what isthemaximumdeviation691
acceptableintheionratio?Moreover,anotherparameterhelpfulintheprocessisthe692
isotopicdistribution,especiallywhenabundantisotopeionssuchaschlorine,sulphur,693
orbrominearepresent.Severalsituationsmightoccurthatleadtodifferentdegreesof694
confidenceinidentification.Forexample,Schymanskietal.(Schymanskietal.,2014a)695
proposeupto5levelsofconfidenceinanon-targetanalysis.Theselevelsrangefrom696
only exact mass to unequivocal molecular formula, and then tentative candidate(s)697
followedbyprobablestructuretoafullyconfirmedstructurewithareferencestandard.698
Figure5summarizesthekeyparametersinthedetectionandidentificationofa699
compoundwithHRMS.As shown in this figure, different scenariosmight occur as a700
function on the information provided, and on the availability of reference standard701
(Badeetal.,2015c;Hernándezetal.,2015a;Nácher-Mestreetal.,2016).702
703
704
705
29
706
Figure 5. Detection and identification criteria in screening of illicit drugswithHRMS707
(modifiedfrom(Nácher-Mestreetal.,2016)).708
709
When a reference standard is available, compounds can be detected or710
identified. Detection is considered satisfactory when the most-abundant ion (Q),711
commonlythe (de)protonatedmolecule, is foundat theexpectedtR (±0.1min,)and712
masserror<5ppm(SANTE/11945,2015).Anotherlikelysituationfordetectionistofind713
tworepresentativeions(i.e.,themost-abundantion(Q)andafragment/adductions(q)714
attheexpectedtR),butwithmasserrorsbetween5-20ppm.Thelattersituationseems715
tooccurwhenthesignalintensityislow(favoredatlowanalyteconcentrations).Inthat716
case, an additional effort is recommended to investigate more accurate-mass ions717
and/orrepeatsampleinjection. Identificationisbasedonthepresenceofatleasttwo718
representativeions(Q,q)attheexpectedtRwithmasserrors<5ppm.Additionally,q/Q719
ratios should fit with those for reference standards within tolerance limits720
(SANTE/11945,2015).Identificationundertheseconditionsishighlyreliableandcanbe721
consideredastheidealsituation.722
Whenthereferencestandardisnotavailable, atentativeidentificationcanbe723
madewhenanexpected ionwithmasserror<5ppm isobserved, togetherwith its724
Screening with HRMS, key parametersRetention time (Rt)Accurate masses
Mass errorsIsotope pattern (Cl, Br…)
• Expected ion (Q), mass error < 5 ppm)
• Compatible isotope pattern (Cl, Br...)
• One or more fragment ions (q), - in agreement with data reported - compatible with the chemical structure
of the candidate (mass error < 5 ppm)
Tentative identification
Identification required withreference standard
Detection
Option 1
•One ion (Q)•Rt agreement •Mass error < 5 ppm
Option 2
• Two ions (Q and q)•Rt agreement •Mass error > 5 ppm
Identification
Standard available
• Two ions (Q and q)
•Rt agreement
•Q mass error < 5 ppm
• q mass error < 5 ppm
• Isotope pattern
Standard unavailable
30
characteristicisotopicpattern.Subsequently,thefragmentionsshouldbeevaluatedby725
comparingthedatawith,e.g.,datareportedintheliteratureorjustifiedbytheaccurate-726
mass fragments taking into account the structure of the molecule. However, for727
structureconfirmation,injectionofthereferencestandardiseventuallyrequired.728
729
5.2. Non-targetanalysis730
Full-spectrum accurate-mass acquisition provided with HRMS also opens the731
possibilitytoinvestigatenon-targetcompoundsinwater(Díazetal.,2012;Hernández732
etal.,2011b;Hugetal.,2014;Ibáñezetal.,2005;Kraussetal.,2010;Schymanskietal.,733
2015).Atrue“unbiased”non-targetscreening,withoutanyaprioriinformationonthe734
compoundstobedetected,isananalyticalchallenge.Thisprocessneedsexpertise,and735
iscomplexandtime-consuming.Themaindifficultiesassociatedwiththisprocesswhen736
applied to environmental orwastewater samples come from: (i) the complexity and737
unknowncompositionofthesamplethatisinvestigated,(ii)thepresenceofmanypeaks738
in the total ion chromatogramwith themost-abundant corresponding commonly to739
compoundsotherthantheanalytes,and,(iii)thelowanalyteconcentrations.Thus,the740
mainproblemistoprioritizethemost“relevant”chromatographicpeaksinthesample,741
becausethemajoritywillnotbeassociatedtodrugs,inordertofocusthesubsequent742
elucidation process on those compounds. From the HRMS information, a complex743
process has to be applied that establishes the empirical formula of the unknown744
compound,searcheschemicaldatabasesforpotentialcandidates,andfinallyassignsthe745
chemicalstructureofthediscoveredcompound.746
Ina truenon-targetanalysis, themaximumnumberof compounds fromvery747
different physico-chemical characteristics should be investigated. Therefore, a748
combination of GC-HRMS and LC-HRMS seems to be the most-appropriate way to749
achievethisaim.Duetothecomplementarityofthesetwotechniquesthisapproach750
canbe seenas themost-comprehensive toadvance towards thedesired “universal”751
screening(Hernándezetal.,2015b).Obviously,some“difficult”compoundswouldnot752
likely be included in a wide-scope screening. For example, very polar/ionic analytes753
wouldrequirespecificchromatographicseparation(e.g.,HILIC).Thus,acombinationof754
C18andHILICchromatographiccolumnswouldrenderawiderscopeforLC-amenable755
31
compounds.Itmustbetakenalsointoaccountthatuniversalityofthescreeningshould756
notreferonlytothetechniquesofmeasurementbutalsotothesampletreatment.From757
thispointofview,agenericextraction,orevenbetter,directanalysisofsamplesinto758
theMS system,would be the best option to avoid compound losses during sample759
manipulation.760
Because no pre-selection of analytes is made in non-target analysis, the761
compoundsdiscoveredinwatersamplesmightbelongtotheillicitdrugsgroup,butalso762
toanyotherfamilyoforganiccontaminantsortheirmetabolites.ThefactthatmostIDBs763
areofmediumtohighpolaritymakesLC-HRMSthemost-attractiveapproachfortheir764
potentialidentification.However,theabsenceofstandardizedmassspectrallibrariesin765
LC-MSisanadditionaldifficultyinnon-targetanalysis.Advancesinthecreationofmass766
spectra libraries for LC-MS/MSanalysiswill beofhelp in thenear future,but at the767
momenttheanalystdoesnotcountontheaidofstandardizedlibrariestofacilitatea768
non-targetanalysis.769
An intermediate situation between target and true non-target analysis is the770
applicationof“biased”non-targetapproaches,where,forexample,theformationof771
“unknown”metabolites/TPs from a given parent compound is investigated with “in772
vitro”or“invivo”experiments,degradationlaboratoryexperiments,orin-silicomodels773
(Reid et al., 2014a). Hence, the investigation is focused on chemically related774
compounds(e.g.,shareacommonfragment,moiety,ormassdefect)oroncompounds775
thathavespecificatomsintheirstructurethatgiveadistinctiveisotopicsignature(e.g.,776
Cl,Br,S).Here,thenumberofchemicallymeaningfulstructures,whichcanbeassigned777
toanunknownpeak, is limited to structures that showaclose relationshipwith the778
parentcompound(Kraussetal.,2010).Thisissuewillbrieflybetreatedinthefollowing779
section.780
781
5.3. Investigationofmetabolitesandtransformationproducts782
The investigationofmetabolitesandTPsof illicitdrugs inwater samples isa783
current topic of research (Bletsouet al., 2015).WBE is basedon the analysis of key784
biomarkersofdrugs.TheseIDBscanbetheparentcompoundand/orthemajorurinary785
32
metabolite(s).Forthemostknownandwidelyconsumeddrugs,informationonhuman786
metabolismisalreadyavailable,andhasallowedestablishmentofbenzoylecgonineas787
themainmetabolite and IDB of cocaine, THC-COOH asmainmetabolite and IDB of788
cannabis,orthatmethamphetamine,amphetamine,andMDMAaremainlyexcretedas789
unchanged compounds. However, this information is usually scarce for NPS and,790
therefore,themainbiomarkerofuseisgenerallynotwell-established.791
AlthoughWBEissolelybasedonthemeasurementofappropriatemetabolites792
thatresultfromhumanexcretion(commonlythemajorandmost-stableones),thereis793
alsoaconcernaboutthepresenceofmanyothermetabolitesandTPsofillicitandlicit794
drugs in the aquatic environment. Especially, possible long-term (chronic) effects on795
organismsandeffectsofcombinedexposuretomultiplecompoundsisofconcern(van796
derAaetal.,2013).Thedetectionandidentificationofthesecompoundsisachallenge797
forenvironmentalanalyticalchemists,anddifferentapproachescanbefollowedtothis798
aim.InthecaseofknownmetabolitesandTPs,alreadyreportedintheliterature,an799
inclusionlistoftargetanalytescanbemade.Fromananalyticalpointofview,theycan800
be treated similarly to their parent compound with the above-mentioned target801
methodologies. Furthermore, retrospective analysis is also feasible by reviewing the802
acquired MS data. For example, metabolites of drugs have been retrospectively803
investigatedinwastewatersamplespreviouslyanalyzedforparentcompoundsonly.In804
thisway,severalmetabolitesweretentativelyidentifiedwithouttheneedofadditional805
analysis, and illustrate the potential of HRMS in this field (Bijlsma et al., 2013b;806
Hernándezetal.,2011a).807
Regardingunknownmetabolites andTPs, theuseof common fragmentation808
pathways between the parent compound and metabolites/TPs might discover809
new/unexpected compounds. In this strategy, a common behavior in their810
fragmentation is assumed. Thepresenceof additional chromatographicpeaks at the811
accurate masses of the fragments might reveal the presence of analyte-related812
compounds. The accurate-mass spectra and appropriate study of the fragmentation813
mightfinallyallowthe(tentative)identificationofmetabolites/TPs(García-Reyesetal.,814
2007;Hernándezetal.,2011b;Thurmanetal.,2005).Thisapproachcanbeextended815
33
basednotonlyonthefragmentationpathwayoftheparentcompound,butalsoonthat816
ofmetabolites/TPsdetectedinsamples(Hernándezetal.,2009).817
A simpler approach is prediction of possible metabolites or TPs with818
computational(insilico)predictiontools(Kirchmairetal.,2015;Reidetal.,2014a).Many819
different methodologies to predict metabolites or sites of metabolism have been820
reportedrecently.Themetabolicfateofamoleculedependsonitschemicalreactivity821
towardsmetabolicprocessesthatcanoccur,aswellasonitsinteractions(affinityand822
binding orientation) with the biotransformation enzymes involved. The prediction823
systemshould,therefore,properlybeselectedafterconsiderationoftheorganismor824
the system where metabolites/TPs are formed. Commercially available and freely825
accessibleprogramshavebeenapplied in thisprediction step.Kirchmairetal,2015,826
reviewedtendifferentsoftwareforpredictingmetabolites,butonlytwoarewithout827
costsandanadditionaloneissolelyavailableforacademia(Kirchmairetal.,2015).This828
free-availabilityisprobablythemainreasonthattheUniversityofMinnesotaPathway829
PredictionSystem(UM-PPS:(“http://eawag-bbd.ethz.ch/”)isoneofthemost-common830
predictiontoolsinsuspectmetabolite/TPsscreening(Kernetal.,2009).831
Predictionofmetabolites/TPsisfollowedbyHRMSanalysis;theexactmassfor832
eachofthepredictedcompoundisextractedfromthechromatogramandcheckedbya833
comparisonwithcontrolsamples.TheplausibilityofthechromatographictR, isotopic834
pattern,andionizationefficiencyareusedasfurtherfilterstonarrowdownthenumber835
ofcandidatepeaks.Thestructuresofsuspectedcompoundsaretentativelyidentified836
basedontheobservedfragmentationpattern.837
AsuitablestrategytoinvestigatemetabolitesandTPsmakesuseof“invitro”or838
“invivo”metabolismexperiments,andoflaboratoryorfield-degradationexperiments839
undercontrolledconditions,whichcanidentifyknownandunknownmetabolitesorTPs840
ofselecteddrugs,respectively.Intherecentliterature,severalexamplescanbefound841
thatdealwiththeinvestigationofdrugmetaboliteswithinvitroorinvivoexperiments842
(Holmetal.,2015;Ibañezetal.,2016;Meyeretal.,2015;Pozoetal.,2014;Takayama843
etal.,2014).Theseexperimentsareveryusefulandallowthediscoveryofmetabolites,844
whichmight be expected and detected inwastewater, and are, therefore, potential845
targetIDBsinfutureWBE-basedstudies.Thediscoveryofmetabolitesisofparticular846
34
relevancefornewdrugs;i.e.,NPSwhosemetabolismisnotwellknown.Otherpapers847
study the degradation of illicit drugs, after spiked samples have been subjected to848
processes,suchashydrolysis,photodegradation,chlorination,biodegradation,orany849
otherprocessof interest(Bijlsmaetal.,2013a;Boixetal.,2014,2013;Postigoetal.,850
2011). In all cases, HRMS plays a key role in the tentative identification of the851
compoundsformed.Furthermore,theuseofspecializedsoftwareiscriticalforarapid852
andefficient comparisonbetween the full scandata set fromuntreatedand treated853
samples,becausemanualinspectionofTICchromatogramtolookforvisiblepeakscan854
easilyfailincomplexmatriceswithlowanalyteconcentrations.855
856
6. Chiralanalysis857
The determination of specificmetabolic excretion products of illicit drugs in858
wastewater is not always possible, andmakes difficult the differentiation between859
consumptionofdrugsanddirectdisposalofunuseddrugs. In such situations, chiral860
analysis can be applied because most illicit drugs are chiral, and are subject to861
stereoselectivehumanmetabolism (Emkeetal., 2014;EvansandKasprzyk-Hordern,862
2014).863
MDMA (3,4-methylenedioxymethamphetamine) and MDA (3,4-864
methylenedioxyamphetamine)profiling inwastewater isanexcellentexampleof the865
importanceofchiralenantioselectiveanalysistodistinguishbetweenconsumptionand866
directdisposalofunusedMDMAandMDA.Bothdrugshaveoneasymmetriccarbon867
centerandthereforetheycanexistintheformoftwoenantiomericpairs,whichdiffer868
bothquantitativelyandqualitativelyinpharmacologicalactivity:S(+)-enantiomersare869
more amphetamine-like stimulants and R(−)-enantiomers are more hallucinogenic870
(Kasprzyk-HordernandBaker,2012a).BothMDMAandMDAhavenomedicalusageand871
are synthesized and abused in racemic forms. Their human metabolism is872
stereoselective and leads to the enrichment of excreted drugs with their R(−)-873
enantiomers.However,ifthepresenceofMDAinurineisduetoMDMAabuseandnot874
directMDAuse,anenrichmentofMDAwithS(+)-enantiomertakesplace(Mooreetal.,875
1996).Itis,therefore,expectedthatafterconsumption,bothdrugswillbepresentin876
urineandwastewaterenrichedwithR(-)-enantiomers. Indeed,Kasprzyk-Hordernand877
35
Baker(Kasprzyk-HordernandBaker,2012a)reported,inafirststudyofthiskind,that878
MDMAwasenrichedwiththeR(-)-enantiomerduetopreferentialmetabolismofS(+)-879
MDMA in humans. Furthermore, the identified MDA was enriched with S(+)-880
enantiomer,tosuggestthatitspresencemightbeassociatedwithMDMAconsumption881
anditssubsequentmetabolismintoS(+)-MDAandnotintentionalMDAuse(ifthelatter882
weretrue,MDAinwastewaterwouldbeenrichedwithR(-)-enantiomer).883
Surprisingly,inseveralinstances,duringEurope-widemonitoringundertakenby884
theSCOREgroupin2011-13(Emkeetal.,2014;Ortetal.,2014c;Thomasetal.,2012),885
unexpectedlyhighloadsofMDMAwereobserved.Forexample,in2011,aberrantlyhigh886
massloadsofMDMAwereobservedinthewastewaterofUtrechtintheNetherlands.887
These loads highly deviated from the results observed in the previous monitoring888
campaign in 2010 (Bijlsma et al., 2012). Enantiomeric profiling as shown inFigure 6889
revealedthatMDMAwasracemic(enantiomericfraction(EF)=0.54),whichindicated890
its direct disposal in the sewage system and further explains high loads of MDMA891
quantifiedinUtrechtwastewaterduringthesamplingweekin2011(averageloadwas892
20-timeshigherthanin2010).Incontrast,thesamplesfrom2010(greenlineinFig.6)893
showedanaverageEFof 0.65 that corresponded toexcretionprofiles inurine after894
consumptionofMDMA(Emkeetal.,2014).Thisdirectdisposalcouldbetheresultofa895
police raid into an illegal production facility that took place two days before the896
monitoringstarted(Emkeetal.,2014).Thepoliceestimatedthat30kgofrawMDMAor897
tabletshadbeendisposedunderthepressureofthepoliceraid.898
Enantiomericprofilingofwastewaterrepresentsapowerfultoolthatallowto899
determineifmassloadsofstudieddrugsactuallyoriginatedfromconsumption,disposal900
ofunuseddrugs,orproductionwaste.901
902
903
36
904
Figure6.MDMA loadsduring two separateweeks sampled in2010and2011 in the905
sewage treatment plant of Utrecht, the Netherlands, and their corresponding906
enantiomericfractions(EF)(Emkeetal.,2014).907
908
Cellobiohydrolase (CBH) is the most widely used stationary phase for909
enantiomericprofilingofamphetamineswithchiralliquidchromatographycoupledwith910
tandemmassspectrometry.Thiscellulaseenzymeisimmobilizedonto5µmsilicabeads911
withanisoelectricpoint(pI)of3.9.Itcontainsmultiplechiralcentresandmechanisms912
forionic,hydrophobic,andhydrogenbonding.Ithasbeensuccessfullyappliedwithan913
isocraticmobilephaseofH2Owith10%2-propanoland1mMNH4OH,toamphetamine-914
likecompounds(Fig.6and7)(Bagnalletal.,2012;Emkeetal.,2014;Kasprzyk-Hordern915
andBaker,2012a,2012b).Thereareseveralfactorsthathavetobetakenintoaccount916
toachievesatisfactorychiralrecognitiononCBH.Theseareprimarilytemperature,pH917
andmobile-phasecomposition.Mobile-phasepHplaysakeyroleinchiralrecognition918
becauseitinfluencesionizationofbothanalytesandCBH.Duetotheisoelectricpointof919
3.9,CBHisnegativelychargedatpH>pI,soincreasingthemobilephasepHwillfacilitate920
ionicinteractionswithpositivelychargedanalyte(e.g.,amphetamineorMDMA).This921
interaction will facilitate longer retention times and higher enantioselectivity.922
Hydrophobicinteractionsandhydrogenbondingcanbeinfluencedwithmobilephases923
thatcontaindifferentnatureandpercentageoforganicmodifiersand ionicstrength.924
Lessthan20%oforganicmodifier isallowedtoavoiddenaturationofthisenzymatic925
chiralselector.Lowerpercentagesoforganicmodifiersleadtohigherretentioninthe926
37
case of amphetamine-like compounds. Isopropanol, methanol, or acetonitrile are927
usuallyusedasorganicmodifiers.Theyarecharacterizedbydifferentelutionstrengths;928
e.g.,methanol has a lower elution strength than isopropranol. Other factors, which929
should be considered are (Camacho-Muñoz et al., 2016): (i) correct sampling and930
sample-preparation protocols that do not introduce stereoselectivity (e.g.,microbial931
metabolicdegradationofanalytesmightleadtoincorrectestimationofenantiomeric932
fractions, or useof chargedeluting agents during SPE (e.g.,methanolmodifiedwith933
ammoniumhydroxide)mightleadtolossofchiralrecognitionintheCBHcolumn),and934
(ii)eliminationofmatrixeffects(viarobustsamplepreparationapproachesanduseof935
deuteratedor13C-labelledinternalstandards).936
EnantiomericprofilinghasbeenusedinWBEasacomplementarytoolalongside937
non-chiralmulti-residuemethods that use reversed phase (C18) stationarymaterials.938
Thisadditionalanalysisrequiredanadhocsamplepreparation,whichmeantahigher939
quantity of sample, and a more time-consuming and less-cost effective analysis. A940
recentlydevelopedmulti-residuemethodcombinedchiralrecognitioncapabilityofthe941
CBH-basedstationarymaterialswithmulti-residueseparationpotentialoftheC18-based942
materials.Themethodologyenableddetectionandquantificationofalltargeted(chiral943
andnon-chiral)humanbiomarkersinwastewateralongwithsatisfactoryenantiomeric944
separationsof18analytesandauniquesinglesample-preparationstep(Castrignanòet945
al.,2016).946
947
38
948
Figure7.Masschromatogramsshowchiraldrugs:amphetamine(AMPH),MDMA,MDA949
andmethamphetamine (METH) inwastewaterobtainedwithCBHcolumnandHPLC-950
QqQMS(modifiedfrom(Kasprzyk-HordernandBaker,2012b)). 951
952
7. Relevantanalyticalparametersandqualitycontrol953
Theuseofadvancedanalyticaltechniquesandtheexpertiseoftheanalystare954
essential to obtain accurate quantitative data for IDBs in wastewater samples. In955
addition,appropriatemeasuresforqualitycontrolarerequiredtoobtainreliabledata.956
1
2
S(+)-MDA
R(-)-MDA
R(-)-MDMA
S(+)-MDMA
S(+)-METH
R(-)-METH
R(-)-AMPH
S(+)-AMPH
39
Obviously,priortoitsapplication,theanalyticalmethodologyneedstobefully957
validatedforallanalytesintermsoflinearity,trueness/accuracy(evaluatedbymeans958
ofrecoveryexperiments)andprecision(asrepeatabilityRSD),selectivity/specificity,and959
limitsofdetection(LOD)andquantification(LOQ).Oneofthemaindrawbacksinthis960
fieldisthelackofguidelinesspecificallydirectedtowardsanalysisofIDBsinwastewater.961
In absence of such guidelines, recommendations in other fields, such as pesticide962
residue analysis (SANCO, 2013; SANTE/11945, 2015), residues in products of animal963
origin(EuropeanCommission,2002)bioanalyticalmethods(EMA,2012),orclearwater964
actprograms(EPA,2007)canbeusedasguidelines.965
Commonly,aminimumof5replicatesarerequiredtochecktheaccuracyand966
precisionatthetargetedLOQ,andatleastoneotherhigherlevel,forexample,10times967
the targeted LOQ. A quantitative analytical method should be demonstrated at the968
initialvalidation,butalsolaterwithsamplebatchestoperformqualitycontrols(QCs)969
thatprovideacceptablerecoveryateachspikinglevelandforeachanalyte.Acceptable970
mean recoveries for IDBs inwastewaterare typically in the range70–120%,withan971
associated repeatability RSD ≤ 20%, (e.g., as established for pesticides in972
SANCO/12571/2013(SANCO,2013)).973
Aspreviouslydescribedinthisreview,LC-MSsystemsaremostwidelyappliedin974
WBE studies. Yet,matrix effects are one of themain problems associatedwith the975
correct determination of IDBswith these techniques.Matrix effects result from the976
competition between matrix co-eluting components and analytes in the ionization977
process(Trufellietal.,2011).Thiscompetitionaffectsquantificationoftheanalytesand978
must,therefore,beremoved,minimized,orcorrectedfor.Quantificationwithmatrix-979
matchedcalibrationissuitableandisfrequentlyusedinsomeresearchfields,wherea980
representative blank matrix can be easily obtained. However, the variability of the981
chemicalcompositionofwastewaterandthecommonpresenceofsomecompoundsin982
thesamplesusedas“blank”posesdifficultiestousethisapproachinWBE.Instead,the983
standardadditionsmethodmightbeused,butitwouldimplymanymoreinjectionsin984
theLC-MSsystem,apartfromtheneedtoadjusttheadditionsaccordinglytotheanalyte985
concentration in the sample for appropriate application of this methodology.986
Furthermore, the high level of some compounds makes it problematic to maintain987
40
linearityinthecalibrationcurve.Hence,theuseofisotope-labelledinternalstandards988
(ILIS)isthemostcommonwaytocorrectformatrixeffects,butalsoforpotentialerrors989
associatedwithsamplemanipulationandstorageiftheILISisaddedtothesamplejust990
aftersamplecollection(i.e.,assurrogate).Whenavailable,theuseofalabelledanalyte991
isrecommendedtoensureasatisfactorycorrectionofmatrixeffects.However,itshould992
be noted that, during method validation, there is an absolute need to thoroughly993
evaluateifthelabelledISaccuratelycorrectsformatrixeffects.994
Theestimationoflimitsofdetection(LODs)andlimitsofquantification(LOQs)995
isusuallyperformedbasedonasignal-to-noise(s/n)ratioof1:3and1:10,respectively.996
More-realisticLOQscanbeestimatedats/n10forthequantitationtransition,butalso997
at s/n 3 for the qualification transition to ensure not only the quantification of the998
compoundbut also its reliable identification (Bijlsma et al., 2014a). InOrbitrap data999
processing,noiseisfilteredout.Therefore,thecommons/napproachtoderiveLOQand1000
LODdoesnotapply.Instead,LOQsinOrbitrapMSaredeterminedbasedonthelowest1001
concentrationofanILISinpurewaterthatproducesanappreciablesignalthatmeets1002
theidentificationcriteria(Bijlsmaetal.,2013b;deVoogtetal.,2011).Thematrixeffect1003
iscalculatedfromtheratiooftheresponsesoftheILISinthematrixandinpurewater1004
and used to calculate the actual LOQ in that matrix. Some guidelines, like SANCO,1005
definedthemethodLOQas the lowestspiking levelof thevalidationthatmeets the1006
methodperformanceacceptability–thatdefinitionisastrictercriterionthatcanalso1007
be applied in WBE. Anyway, an estimation of LODs and LOQs in wastewater is1008
complicated, because notable variations in chemical composition between samples1009
occur.Representativematrix-matchedstandardscannotbeeasilyprepared,duetothe1010
presenceofanalytesinmostinfluentsamples,andbecauseofthevariationsinsample1011
composition from one sample to the other. This fact makes problematic a rational1012
comparison of these parameters among different published methodologies. An1013
estimation of LODs/LOQs from standards in solvent at least could make a fair1014
comparisonbetweeninstrumentalperformances,althoughnotanalyticalmethods.An1015
efficientandrealisticapproachtoestimatetheseparametersinahomogeneouswayis1016
frominter-laboratoryexerciseswhereallparticipantsanalyzethesamesampleswith1017
theirownanalyticalmethodology.1018
41
Confirmation of positives is an essential aspect in the analysis. To this aim,1019
guidelinessuchasthatfromtheEuropeanCommission(EuropeanCommission,2002)1020
canbeadopted,wheretheconfirmationofpositivefindingsisbasedonthecollection1021
ofidentificationpoints(IPs).ThenumberofIPsearneddependsonthemassanalyzer1022
used.Thus,forQqQlow-resolutioninstrumentsusedintandemMS,aminimumoftwo1023
transitionsshouldbemonitoredforasafepositivefinding,whereasinhigh-resolution1024
instrumentsatleasttwoionsmustbemonitored.Inaddition,theaccomplishmentof1025
theionratiobetweenrecordedtransitionsandaretentiontimewithinthemaximum1026
tolerancesallowedarerequired.1027
Notonlyquantification,butalsoconfirmationoftheidentitycouldbeaffected1028
bymatrixinterferences.Asstatedbefore,twotransitions(Q,q)arenormallyacquired1029
inLC-MS/MSanalysis.Oneofthemost-controversial issues istheaccomplishmentof1030
theionratiobetweenthesetransitions(q/Qratio)requiredforconfirmation.Ionratios1031
insamplesmightbeaffectedbymatrixcomponents;e.g.,whenatleastoneofthetwo1032
selectedSRMtransitionsissharedwiththematrix,whichmightleadtounexpectedion1033
ratioswithdeviationsthatexceedthemaximumallowed.Thissituationismoreprone1034
tohappenwhenthespecificityoftheneutrallossesinvolvedintheselectedtransitions1035
isnotevaluatedandcommonlosses,suchasthelossofH2OorCO2,areimplicated.Non-1036
specific transitions are a weakness not yet tackled with the current guidelines and1037
shouldbeconsideredinthisresearchfield(Delatouretal.,2007).Inthissituation,the1038
acquisitionofallavailabletransitionsisrecommendedtofacilitateconfirmationofthe1039
positivesbytestingtheadditionaltransitionsacquired.Incasesofnon-compliance,the1040
samplemightbereportedaspositive,butincludeacommentonthenon-complianceof1041
theratio,andreporttheactualq/Qratiodeviationobtained.Additionalworkwouldbe1042
necessarytotestifanyinterferingcompoundactuallyaffectedtheq/Qratio.1043
Duringarecentinter-laboratorystudyundertakenbytheSCOREgroup,oneof1044
thequestionsraisedrelatedtothesignificantvariationsinq/Qratiosreportedbythe1045
differentparticipants(Castiglionietal.,2013),evenwiththesameSRMtransitions.As1046
anexample,forcocaine,with304>182(Q)and304>82(q),ionratiosfromdifferent1047
laboratoriesrangedfrom0.12to0.38,andseemedtonotablydependontheinstrument1048
used and on the parameters optimized in each laboratory (e.g., cone and collision1049
42
voltages). In addition, some variations from batch to batch were also observed.1050
Nevertheless, these variations were not relevant to confirm identity, because it is1051
recommended that q/Q ratios are measured and evaluated for accomplishment by1052
everylaboratorywithineachsamplebatchwiththestandardsincludedinthesequence1053
ofsampleanalysis.1054
Apart fromthevalidationofthemethod ineach laboratorybefore itsroutine1055
use,theuseofinternalqualitycontrols(QCs)isofprimaryimportancetotrackpossible1056
dailymethodvariations.Intheory,aninternalQCisafinalcheckofthecorrectexecution1057
ofalltheprocessesthatareincludedintheanalyticalprotocol.Duetothedifficultiesto1058
obtainblankwastewatersamples,thosewiththelowestconcentrationsexpectedare1059
preferredtopreparespikedsamplesusedasinternalQCs.Thismeansthatsamplesfrom1060
locationswithlowdruguseand/orcollectedinthemid-week,wheretheconsumption1061
ofillicitdrugsisexpectedtobelowerthanintheweekends,wouldfitbettertoprepare1062
theQCs.DespitethisfactthatlowconcentrationsofIDBsareexpected,samplesselected1063
should be analyzed to accurately know the potential analyte concentration in these1064
“blank”samples,inordertobesubtractedfromtheQCprepared.Althoughthereisno1065
guidelineinthisfield,QCsindividualrecoveriesfrom60to140%mightbeacceptablein1066
wastewater analysis, as suggested in the SANCO guidelines (SANCO, 2013). Other1067
guidelinesrecommendanacceptablerangeof80-120%attheLOQlevel(EMA,2012).1068
WhenQCrecoveriesareoutofthisinterval,thesamplesequenceofanalysisshouldbe1069
repeated.Iftheproblempersists,thenappropriatemeasuresshouldbetakentoensure1070
theaccuracyofthemethod.1071
The implementation of quality assurance practices to analytical chemistry is1072
recognized as a prerequisite to produce data with known metrological qualities.1073
Regardlessofthetargetanalyteorsampletype,qualityassuranceandqualitycontrol1074
are the cornerstones to analytical data validation. In addition to daily internal1075
performanceverificationsviaQCmaterials,agoodqualityassuranceplanshouldinclude1076
regularexternalperformanceevaluationsforanindependentassessmentofanalytical1077
proficiency.Thegoalofinter-laboratorystudiesistodemonstratethatparticipationin1078
thisexercise leads to improvedqualityofanalytical results.Theresultsareofcrucial1079
interestforlaboratoriesbecausetheseprovideclearinformationoftheirmeasurement1080
43
capabilities.Ithastobepointedoutthatparticipationiseithervoluntaryorforcedby1081
external requirements (e.g., legal, accreditation, control bodies). Inter-laboratory1082
exercisesinvolvecomparisonofparticipants’resultsonasetofspikedwatersamples.1083
Careneeds tobetaken, toensureconcentrationsareequal inallaliquots,especially1084
whenparticulatemattershouldalsobeanalyzed.Thisalsoholdstruewhensubsampling1085
fromcompositesamples(CapelandLarson,1996).Theseparateresultsarecompared1086
withthemedianoftheentiregrouptodeterminetheaccuracyofthemethodused.By1087
usingasetoftwosamplesspikedatdifferentlevelswiththesamecompoundasocalled1088
Youdenpairiscreated.VisualizationoftheseresultsinaYoudenplotshowwithin-and1089
between-laboratory variability. Also individual constant errors become visible, and1090
randomerrorsandsystematicalerrorscanberecognized.1091
Several inter-laboratory studies have been organized by the SCORE group on1092
selectedIDBsregularlymonitoredinWBE.Intheperiod2011-2015fiveconsecutivesets1093
ofinterlaboratoryexerciseshavebeenorganized,initiallywithmethanolicsolutionsof1094
analytes that gradually moved to more-complicated matrices such as extracts and1095
genuinewastewatersamples.Thesewerethefirstinter-laboratoryexercisesorganized1096
todetermineIDBsinwastewater.Theresultsofthisstepwiseinter-laboratorytesting1097
and the improvements made during this five-year period can help to optimize the1098
analyticalproceduresofparticipatinglaboratoriesandaidinareliableinterpretationof1099
WBEdata.Tothisend,concentrationsofIDBsinwastewaterprovidedbylaboratories1100
thatdidn’tperformwellintheinterlaboratoryexerciseswerenottakenintoaccount;1101
however,togetherwithexpertsinthefield,solutionsfortheanalyticaldeviationsare1102
sought.1103
1104
8. Generalsummaryandperspectives1105
The investigation of IDBs in wastewater is a subject of current interest in1106
analyticalchemistry.Thecomplexityofthematrixunderinvestigation,thelowanalyte1107
concentrations commonly found, and the need to detect and quantify not only the1108
parentcompoundsbutalsothemainmetabolitesofdrugs,makethistaskananalytical1109
challenge. In addition, humanmetabolism is not alwayswell known, and the target1110
biomarkersmightbeunknown.Inthisfield,liquidchromatographycombinedwithlow-1111
44
andhigh-resolutionMSisanindispensabletool.Differentstrategiescanbeappliedto1112
investigateIDBsinwastewater(discussedinthisreview)fromquantificationoftarget1113
compoundstothedetectionand(tentative)identificationofunknownmetabolitesand1114
TPs.1115
QuantificationofIDBsinwastewaterisarequisiteinWBEinordertoestimate1116
druguseinpopulations.However,thepresenceofdrugresiduesinwastewateralsohas1117
other implications. For example, there is a possible environmental impact when1118
compounds are not completely removed byWWTPs. Indeed, low removal rates for1119
certain illicit drugs, such asMDMA, ketamine, andmethadone, have been observed1120
(Bijlsmaetal.,2012).Thuslowremovalratesimpliesthatdrugresiduescanbepresent1121
in effluent wastewater, and finally reach the aquatic environment. Therefore, the1122
determinationofillicitdrugsandmetabolitesineffluentwastewaterandsurfacewater1123
isalsoofinterest,aswellastheinvestigationofpotentialTPsthatcanbeformedinthe1124
environment.Here,concentration levelsaremuch lowerthan in influentwastewater1125
and,therefore,excellentsensitivityisrequiredfortheanalyticalmethods.1126
In this field,undercontinuousdevelopment,several trendsandneedscanbe1127
highlighted:1128
1) Thereisaneedtoincreasetheknowledgeofmetabolitesthatmightbepresent1129
in the aquatic environment. Especially forNPS, there is a lack ofmetabolism1130
studies,andtargetcompoundsarestillnotfullyidentified.Here,theuseofHRMS1131
is highly promising due to its potential to detect and identify drug-related1132
compounds to make use of different approaches, such as the “common1133
fragmentationpathway”,whichisveryusefultofindparent-chemicallyrelated1134
compounds.Advantageously,aretrospectiveanalysiscanbemadeatanytime1135
fromHRMS data to facilitate the search of compounds of interest (e.g., new1136
discoveredmetabolites)insamplespreviouslyanalyzed.Furthermore,fromthe1137
perspectiveofenvironmentalchemistry,itisofinteresttoextendthisresearch1138
toTPs,whichinmanyoccasionsarestillunknown.1139
2) Thedevelopmentofwide-scopescreeningwillsurelybeoneofthekeyfeatures1140
ofHRMSinthenextfewyears.Theuseof longlistsofselectedcompoundsis1141
essential to facilitate target screening with or without (suspect screening)1142
45
reference standards. Tomaintain the “universality” of this approach, generic1143
sample treatments would be required in order to avoid potential losses of1144
analytesduringsamplehandling.Someproblematiccompounds,mainlythose1145
presentinionicform,willalwaysrequirespecific/individualmethods,because1146
theycannotbeincludedinmulti-residue/multi-classmethodologies,duetotheir1147
specialphysico-chemicalcharacteristics.1148
3) Inlinewiththepreviouspoint,itisexpectedtowidenfuturescreeningtoinclude1149
NPS. However, it will not be easy to obtain satisfactory results in this case1150
because of twomain limitations: i) very low concentrations expected in the1151
samplesasaconsequenceofthelimiteduseofthesecompoundsincomparison1152
with “conventional” drugs, such as cocaine, cannabis, or amphetamines; ii)1153
continuousappearanceofnewNPSwithchangesinthechemicalstructurethat1154
complicatetheirdetectionandidentification.Relatedtothelastpoint,HRMSwill1155
beapowerfultooltoidentifyNPSandunknownmetabolites.1156
4) Thecombinationofnon-biasedandbiasednon-targetanalysiswithHRMSwill1157
beoneofthekeyresearchfields inthenearfuture.Hopefully, thiscombined1158
approach will allow one to discover new compounds of interest, such as1159
unknown or non-searched metabolites, TPs and/or new drugs. Their low1160
concentrations inmost caseswill be an extra difficulty to obtain satisfactory1161
results.1162
5) LC-MS/MS with triple quadrupolemass analyzers will still be the reference1163
techniquetoquantifyselectedIDBsintargetmethodologies,duetoitsexcellent1164
sensitivity and selectivity. However, new instruments with improved1165
performanceswillwidenthenumberofcompoundsincludedinthemethodup1166
to several hundreds. The incomparable sensitivity reached with this1167
instrumentationwillobtaindataonthepresenceofNPSinwastewaters,with1168
expectedconcentrationsatthepg/Llevel.1169
6) A common protocol of action should be used in WBE studies to produce1170
homogeneous and comparable data at different sites and provide the most1171
reliableestimatesofdruguse.Uncertaintyfactorsassociatedwiththedifferent1172
stepsinvolvedinWBE(sampling,chemicalanalysis,stabilityofdrugbiomarkers1173
insewage,back-calculationofdruguse,estimationofpopulationsize)haveto1174
46
beconsideredinordertoreduceand/orminimizetheuncertaintyoftheentire1175
procedure(Castiglionietal.,2013).Abestpracticeprotocolhasbeenrecently1176
proposedandadoptedbyEurope-widestudies.Threephasesoftheapproach1177
areincluded:samplingandsamplehandling,storagetreatmentduringsampling,1178
chemicalanalysis-quality control (EMCDDA,2016).Currently, themost-urgent1179
needs for future researchare:1) improve thequalityofchemicalanalysesby1180
followingspecificqualityrequirements;2)improvetheknowledgeonstabilityof1181
IDBs in-sewer; 3) plan additional pharmacokinetic studies to produce reliable1182
humanexcretionprofilesforIDBs;4)explorenovelpossibilitiestoestimatethe1183
populationsizeinacatchment.1184
7) TheimprovedcharacteristicsofHRMSinstruments,mainlysensitivityandlinear1185
dynamicrange,willmakethistechniqueattractiveforquantitativeanalysisas1186
well.Thesearch for thedesired“All-in-One”methodand instrumentwill still1187
continueinthecomingyears,becausecombinationofalldesiredfeaturesinjust1188
one method/instrument is an exciting issue: qualitative and quantitative1189
analysis, with possibilities for structural elucidation of unknowns. Future1190
developmentsofHRMSwillsurelyberelatedtoscan-speedimprovementsfor1191
Orbitrap,whichforexamplewillallowmoreefficientcombinationtoUHPLC,or1192
GC,whereasimprovementsinTOFMSanalyzerswillincreasethemass-resolving1193
power.Advanceswillincludedevelopmentoftribridanalyzersthatincorporate1194
newpossibilitiessuchasIonMobilitySpectrometry.Improvementsinaccurate-1195
mass full-acquisition data processing with more-powerful and user-friendly1196
softwarearealsoexpected. Inthenearfuture,wewillseeagrowthofHRMS1197
applications,notonly inWBE,butalso inother fields, suchasenvironmental1198
research,food-safety,toxicologyanddopingcontrolanalysis1199
8) It will be necessary to harmonize the criteria for reliable1200
identification/confirmation of compounds detected in samples. Relevant1201
parameters,asthenumberandspecificityofionsrequired,maximumion-ratio1202
deviationsallowed,masserrorsacceptedareneededtofacilitatecomparisonof1203
dataandtoavoidfalsepositivesornegativesduetotheuseofdissimilarcriteria1204
amongdifferentauthors.1205
47
9) The limitsofdetectionand/orquantificationofthemethods isarequisiteto1206
performrealisticcomparisonofdatainWBEstudies.Thenon-detectionmight1207
betranslatedtofiguresthatdependontheLOD;i.e.,themethodsensitivity.The1208
comparison of drug consumption among populations makes use in some1209
occasions of very low concentration data for less-consumed drugs; this1210
comparisonmightbedistortedwithunrealisticLOD/LOQdata.Thereisaneed1211
toharmonizecriteriafortheirestimationinWBE.1212
10) Further development of chiral analytical methods and wider application of1213
enantiomeric profiling ofwastewater are expected in the coming years. This1214
expectation is because enantiomeric profiling of illicit/abused drugs in1215
wastewater representsapowerful tool toallowone todifferentiatebetween1216
consumption and disposal of unused drugs or production waste in WBE.1217
Advancesareneededinthedesignofnew,more-robuststationarymaterialsto1218
separatemulti-residuemixturesofchiraldrugswithinashortermethodtime.1219
11) Awastewatervalidationguideline,basedontheexistingguidelines, isdesired1220
includingkeyaspectsrelatedtoqualitycontrolthatmustbecarefullyconsidered1221
inWBE. Internal and external quality controls are both needed for a reliable1222
analytical methodology. The organization of interlaboratory exercises are1223
imperative from twoperspectives: i) toproduce reliableWBEdata, and ii) to1224
improveanalyticalperformanceofparticipatinglaboratories.1225
12) The ultimate goal ofWBE is to provide results in real-time. This data can be1226
achieved with biosensors. Biosensors have already been applied in WBE to1227
screenPSA, prostate cancerbiomarker (Yanget al., 2015c),DNA (Yanget al.,1228
2015a),andcocaine(Yangetal.,2016).Thereare,however,severalissuesthat1229
need to be addressed;mainly the relatively low sensitivity of biosensors and1230
most probably low selectivity. Due to fast advancements in the field, wide1231
applicationofbiosensorsinWBEisenvisaged(Yangetal.,2015b).1232
13) ThepotentialofWBEwillbeexpandedtootheraspectsofpublichealth.Sewage1233
contains a hidden wealth of highly complex chemical information about1234
biologicalprocesses thatoccur in thehumanbody (Daughton,2011). Specific1235
biomarkerscouldserveasindicatorsofexposure,stress,vulnerabilitytodisease,1236
acquired disease, or health. Biomarkers include endogenous compounds1237
48
producedinresponsetostressorindicativeofhealth,adductsofendogenous1238
chemicals and xenobiotics, or metabolites of detoxification or intoxication1239
processes from xenobiotic exposure (Daughton, 2012). Theoretically, such1240
biomarkers could serve as collective measures of community-wide health or1241
disease,andcouldprovideameanstoconductepidemiologyinnear-realtime.1242
Ithas,therefore,thecapabilitytoserveasanearly-warningsysteminpandemics1243
(Ortetal.,2014a).Quantitativeanalysisof‘healthbiomarkers’insewagemight1244
allowone tomonitor changesover time; forexample, in response to specific1245
campaigns, identification of trends and, inter-community comparisons in1246
relationtotheirhealth,diet,lifestyle,andenvironment(ThomasandReid,2011).1247
14) Itisessentialtowidentheknowledgeonselectionofthemost-appropriateIDB1248
inWBEandtotakeintoaccountspecificrequirementsthataproperbiomarker1249
shouldfulfil inordertoensurethereliabilityoftheback-calculatedestimates.1250
Themain requirements for an IDB are: 1) excretion in consistent amounts in1251
urine; 2) detectable in urbanwastewater; 3) stable inwastewater; 4) human1252
excretion as unique source. These characteristics are essential to perform a1253
reliablequantitativeanalysisofthesubstanceunderinvestigationandshouldbe,1254
therefore,carefullyconsideredinfuturestudiestoselectnewIDBs.1255
1256
Acknowledgments1257
Financial support by the European Union's Program for research, technological1258
development,anddemonstrationSEWPROF(projectno.317205)andtheCOST-action1259
SCORE (Action no. ES 1307) are gratefully acknowledged. Dr. Felix Hernandez1260
acknowledges the Spanish Ministry of Economy and Competitiveness for financial1261
support inthefieldof illicitdrugresearch(RefCTQ2015-65603-P).Dr.Alexandervan1262
Nuijs acknowledges the Research Foundation Flanders (FWO) for his post-doctoral1263
fellowship. Dr. Lubertus Bijlsma acknowledges NPS-Euronet1264
(HOME/2014/JDRUG/AG/DRUG/7086),co-fundedbytheEuropeanUnion,forhispost-1265
doctoral fellowship. This publication reflects the views only of the authors, and the1266
EuropeanCommissioncannotbeheldresponsibleforanyusethatmightbemadeofthe1267
informationcontainedtherein. 1268
49
References1269
Alechaga, É., Moyano, E., Galceran, M.T., 2015. Wide-range screening of psychoactive 1270 substances by FIA–HRMS: identification strategies. Anal. Bioanal. Chem. 407, 1271 4567–4580. doi:10.1007/s00216-015-8649-7 1272
Andrés-Costa, M.J., Rubio-López, N., Morales Suárez-Varela, M., Pico, Y., 2014. 1273 Occurrence and removal of drugs of abuse in Wastewater Treatment Plants of 1274 Valencia (Spain). Environ. Pollut. 194, 152–162. 1275 doi:10.1016/j.envpol.2014.07.019 1276
Asimakopoulos, A., Kannan, K., 2016. Neuropsychiatric pharmaceuticals and illicit 1277 drugs in wastewater treatment plants: A review. Environ. Chem. 13, 541–576. 1278 doi:http://dx.doi.org/10.1071/EN15202 1279
Bade, R., Bijlsma, L., Miller, T.H., Barron, L.P., Sancho, J.V., Hernández, F., 2015a. 1280 Suspect screening of large numbers of emerging contaminants in environmental 1281 waters using artificial neural networks for chromatographic retention time 1282 prediction and high resolution mass spectrometry data analysis. Sci. Total Environ. 1283 538, 934–941. doi:10.1016/j.scitotenv.2015.08.078 1284
Bade, R., Bijlsma, L., Sancho, J. V, Hernández, F., 2015b. Critical evaluation of a 1285 simple retention time predictor based on LogKow as a complementary tool in the 1286 identification of emerging contaminants in water. Talanta 139, 143–149. 1287 doi:10.1016/j.talanta.2015.02.055 1288
Bade, R., Rousis, N.I., Bijlsma, L., Gracia-Lor, E., Castiglioni, S., Sancho, J. V., 1289 Hernandez, F., 2015c. Screening of pharmaceuticals and illicit drugs in wastewater 1290 and surface waters of Spain and Italy by high resolution mass spectrometry using 1291 UHPLC-QTOF MS and LC-LTQ-Orbitrap MS. Anal. Bioanal. Chem. 407, 8979–1292 8988. doi:10.1007/s00216-015-9063-x 1293
Bagnall, J.P., Evans, S.E., Wort, M.T., Lubben, A.T., Kasprzyk-Hordern, B., 2012. 1294 Using chiral liquid chromatography quadrupole time-of-flight mass spectrometry 1295 for the analysis of pharmaceuticals and illicit drugs in surface and wastewater at 1296 the enantiomeric level. J. Chromatogr. A 1249, 115–129. 1297 doi:10.1016/j.chroma.2012.06.012 1298
Banta-Green, C., Field, J., 2011. City-wide drug testing using municipal wastewater. 1299 Significance 8, 70–74. doi:10.1111/j.1740-9713.2011.00489.x 1300
Banta-Green, C.J., Field, J.A., Chiaia, A.C., Sudakin, D.L., Power, L., De Montigny, L., 1301 2009. The spatial epidemiology of cocaine, methamphetamine and 3,4-1302 methylenedioxymethamphetamine (MDMA) use: A demonstration using a 1303 population measure of community drug load derived from municipal wastewater. 1304 Addiction 104, 1874–1880. doi:10.1111/j.1360-0443.2009.02678.x 1305
Barron, L.P., McEneff, G.L., 2016. Gradient liquid chromatographic retention time 1306 prediction for suspect screening applications: A critical assessment of a generalised 1307 artificial neural network-based approach across 10 multi-residue reversed-phase 1308 analytical methods. Talanta 147, 261–270. doi:10.1016/j.talanta.2015.09.065 1309
Bartelt-Hunt, S.L., Snow, D.D., Damon, T., Shockley, J., Hoagland, K., 2009. The 1310 occurrence of illicit and therapeutic pharmaceuticals in wastewater effluent and 1311 surface waters in Nebraska. Environ. Pollut. 157, 786–791. 1312 doi:10.1016/j.envpol.2008.11.025 1313
Baz-Lomba, J.A., Reid, M.J., Thomas, K. V., 2016. Target and suspect screening of 1314 psychoactive substances in sewage-based samples by UHPLC-QTOF. Anal. Chim. 1315 Acta 914, 81–90. doi:10.1016/j.aca.2016.01.056 1316
Berendsen, B.J.A., Wegh, R.S., Meijer, T., Nielen, M.W.F., 2015. The Assessment of 1317 Selectivity in Different Quadrupole-Orbitrap Mass Spectrometry Acquisition 1318
50
Modes. J. Am. Soc. Mass Spectrom. 26, 337–346. doi:10.1007/s13361-014-1021-x 1319 Berset, J.-D., Brenneisen, R., Mathieu, C., 2010. Analysis of llicit and illicit drugs in 1320
waste, surface and lake water samples using large volume direct injection high 1321 performance liquid chromatography--electrospray tandem mass spectrometry 1322 (HPLC-MS/MS). Chemosphere 81, 859–866. 1323 doi:10.1016/j.chemosphere.2010.08.011 1324
Bijlsma, L., Beltrán, E., Boix, C., Sancho, J. V., Hernández, F., 2014a. Improvements in 1325 analytical methodology for the determination of frequently consumed illicit drugs 1326 in urban wastewater. Anal. Bioanal. Chem. 406, 4261–4272. doi:10.1007/s00216-1327 014-7818-4 1328
Bijlsma, L., Boix, C., Niessen, W.M.A., Ibáñez, M., Sancho, J. V., Hernández, F., 1329 2013a. Investigation of degradation products of cocaine and benzoylecgonine in 1330 the aquatic environment. Sci. Total Environ. 443, 200–208. 1331 doi:10.1016/j.scitotenv.2012.11.006 1332
Bijlsma, L., Botero-Coy, A.M., Rincón, R.J., Peñuela, G.A., Hernández, F., 2016. 1333 Estimation of illicit drug use in the main cities of Colombia by means of urban 1334 wastewater analysis. Sci. Total Environ. 565, 984–993. 1335 doi:10.1016/j.scitotenv.2016.05.078 1336
Bijlsma, L., Emke, E., Hernández, F., De Voogt, P., 2013b. Performance of the linear 1337 ion trap Orbitrap mass analyzer for qualitative and quantitative analysis of drugs of 1338 abuse and relevant metabolites in sewage water. Anal. Chim. Acta 768, 102–110. 1339 doi:10.1016/j.aca.2013.01.010 1340
Bijlsma, L., Emke, E., Hernández, F., De Voogt, P., 2012. Investigation of drugs of 1341 abuse and relevant metabolites in Dutch sewage water by liquid chromatography 1342 coupled to high resolution mass spectrometry. Chemosphere 89, 1399–1406. 1343 doi:10.1016/j.chemosphere.2012.05.110 1344
Bijlsma, L., Sancho, J. V., Hernández, F., Niessen, W.M.A., 2011. Fragmentation 1345 pathways of drugs of abuse and their metabolites based on QTOF MS/MS and MS 1346 E accurate-mass spectra. J. Mass Spectrom. 46, 865–875. doi:10.1002/jms.1963 1347
Bijlsma, L., Sancho, J. V., Pitarch, E., Ibáñez, M., Hernández, F., 2009. Simultaneous 1348 ultra-high-pressure liquid chromatography-tandem mass spectrometry 1349 determination of amphetamine and amphetamine-like stimulants, cocaine and its 1350 metabolites, and a cannabis metabolite in surface water and urban wastewater. J. 1351 Chromatogr. A 1216, 3078–3089. doi:10.1016/j.chroma.2009.01.067 1352
Bijlsma, L., Serrano, R., Ferrer, C., Tormos, I., Hernández, F., 2014b. Occurrence and 1353 behavior of illicit drugs and metabolites in sewage water from the Spanish 1354 Mediterranean coast (Valencia region). Sci. Total Environ. 487, 703–709. 1355 doi:10.1016/j.scitotenv.2013.11.131 1356
Bisceglia, K.J., Roberts, A.L., Schantz, M.M., Lippa, K.A., 2010. Quantification of 1357 drugs of abuse in municipal wastewater via SPE and direct injection liquid 1358 chromatography mass spectrometry. Anal. Bioanal. Chem. 398, 2701–2712. 1359 doi:10.1007/s00216-010-4191-9 1360
Bletsou, A.A., Jeon, J., Hollender, J., Archontaki, E., Thomaidis, N.S., 2015. Targeted 1361 and non-targeted liquid chromatography-mass spectrometric workflows for 1362 identification of transformation products of emerging pollutants in the aquatic 1363 environment. TrAC Trends Anal. Chem. 66, 32–44. doi:10.1016/j.trac.2014.11.009 1364
Boix, C., Ibáñez, M., Bijlsma, L., Sancho, J. V., Hernández, F., 2014. Investigation of 1365 cannabis biomarkers and transformation products in waters by liquid 1366 chromatography coupled to time of flight and triple quadrupole mass spectrometry. 1367 Chemosphere 99, 64–71. doi:10.1016/j.chemosphere.2013.10.007 1368
51
Boix, C., Ibáñez, M., Sancho, J. V., Niessen, W.M.A., Hernández, F., 2013. 1369 Investigating the presence of omeprazole in waters by liquid chromatography 1370 coupled to low and high resolution mass spectrometry: Degradation experiments. J. 1371 Mass Spectrom. 48, 1091–1100. doi:10.1002/jms.3260 1372
Boix, C., Ibáñez, M., Sancho, J. V, Rambla, J., Aranda, J.L., Ballester, S., Hernández, 1373 F., 2015. Fast determination of 40 drugs in water using large volume direct 1374 injection liquid chromatography-tandem mass spectrometry. Talanta 131, 719–727. 1375 doi:10.1016/j.talanta.2014.08.005 1376
Boleda, M.R., Galceran, M.T., Ventura, F., 2007. Trace determination of cannabinoids 1377 and opiates in wastewater and surface waters by ultra-performance liquid 1378 chromatography-tandem mass spectrometry. J. Chromatogr. A 1175, 38–48. 1379 doi:10.1016/j.chroma.2007.10.029 1380
Bones, J., Thomas, K. V, Paull, B., 2007. Using environmental analytical data to 1381 estimate levels of community consumption of illicit drugs and abused 1382 pharmaceuticals. J. Environ. Monit. 9, 701–707. doi:10.1039/b702799k 1383
Boogaerts, T., Covaci, A., Kinyua, J., Neels, H., van Nuijs, A.L.N., 2016. Spatial and 1384 temporal trends in alcohol consumption in Belgian cities: A wastewater-based 1385 approach. Drug Alcohol Depend. 160, 170–176. 1386 doi:10.1016/j.drugalcdep.2016.01.002 1387
Borova, V.L., Maragou, N.C., Gago-Ferrero, P., Pistos, C., Thomaidis, N.S., 2014. 1388 Highly sensitive determination of 68 psychoactive pharmaceuticals, illicit drugs, 1389 and related human metabolites in wastewater by liquid chromatography-tandem 1390 mass spectrometry. Anal. Bioanal. Chem. 406, 4273–4285. doi:10.1007/s00216-1391 014-7819-3 1392
Burgard, D.A., Fuller, R., Becker, B., Ferrell, R., Dinglasan-Panlilio, M., 2013. 1393 Potential trends in Attention Deficit Hyperactivity Disorder (ADHD) drug use on a 1394 college campus: Wastewater analysis of amphetamine and ritalinic acid. Sci. Total 1395 Environ. 450, 242–249. doi:10.1016/j.scitotenv.2013.02.020 1396
Camacho-Muñoz, D., Petrie, B., Castrignanò, E., Kasprzyk-Hordern, B., 2016. 1397 Enantiomeric Profiling of Chiral Pharmacologically Active Compounds in the 1398 Environment with the usage of chiral Liquid Chromatography Coupled with 1399 Tandem Mass Spectrometry. Curr. Anal. Chem. 12, 1–12. 1400 doi:10.2174/1573411012666151009195039 1401
Capel, P.D., Larson, S.J., 1996. Evaluation of selected information on splitting devices 1402 for water samples. U.S. Geol. Surv. Water-Resources Investig. Rep. 95–4141 1–1403 103. 1404
Castiglioni, S., Bijlsma, L., Covaci, A., Emke, E., Hernández, F., Reid, M., Ort, C., 1405 Thomas, K. V., Van Nuijs, A.L.N., De Voogt, P., Zuccato, E., 2013. Evaluation of 1406 uncertainties associated with the determination of community drug use through the 1407 measurement of sewage drug biomarkers. Environ. Sci. Technol. 47, 1452–1460. 1408 doi:10.1021/es302722f 1409
Castiglioni, S., Senta, I., Borsotti, A., Davoli, E., Zuccato, E., 2015. A novel approach 1410 for monitoring tobacco use in local communities by wastewater analysis. Tob. 1411 Control 24, 38–42. doi:10.1136/tobaccocontrol-2014-051553 1412
Castiglioni, S., Thomas, K. V., Kasprzyk-Hordern, B., Vandam, L., Griffiths, P., 2014. 1413 Testing wastewater to detect illicit drugs: State of the art, potential and research 1414 needs. Sci. Total Environ. 487, 613–620. doi:10.1016/j.scitotenv.2013.10.034 1415
Castiglioni, S., Zuccato, E., Chiabrando, C., Fanelli, R., Bagnati, R., 2008. Mass 1416 spectrometric analysis of illicit drugs in wastewater and surface water. Mass 1417 Spectrom. Rev. 27, 378–394. 1418
52
Castiglioni, S., Zuccato, E., Crisci, E., Chiabrando, C., Fanelli, R., Bagnati, R., 2006. 1419 Identification and measurement of illicit drugs and their metabolites in urban 1420 wastewater by liquid chromatography-tandem mass spectrometry. Anal. Chem. 78, 1421 8421–8429. doi:10.1021/ac061095b 1422
Castrignanò, E., Lubben, A., Kasprzyk-Hordern, B., 2016. Enantiomeric profiling of 1423 chiral drug biomarkers in wastewater with the usage of chiral liquid 1424 chromatography coupled with tandem mass spectrometry. J. Chromatogr. A 1438, 1425 84–99. doi:10.1016/j.chroma.2016.02.015 1426
Castro-Perez, J., Hoyes, J., Major, H., Preece, S., 2002. Advances in MS-based 1427 approaches for drug and metabolism studies. Chromatographia 55, S59–S63. 1428 doi:10.1007/BF02493354 1429
Chiaia, A.C., Banta-green, C., Field, J., 2008. Eliminating Solid Phase Extraction with 1430 Large-Volume Injection LC / MS / MS : Analysis of Illicit and Legal Drugs and 1431 Human Urine Indicators in US Wastewaters. Environ. Sci. Technol. I, 8841–8848. 1432 doi:10.1021/es802309v 1433
Chiaia-Hernandez, A.C., Schymanski, E.L., Kumar, P., Singer, H.P., Hollender, J., 1434 2014. Suspect and nontarget screening approaches to identify organic contaminant 1435 records in lake sediments. Anal. Bioanal. Chem. 406, 7323–7335. 1436 doi:10.1007/s00216-014-8166-0 1437
Coscollà, C., León, N., Pastor, A., Yusà, V., 2014. Combined target and post-run target 1438 strategy for a comprehensive analysis of pesticides in ambient air using liquid 1439 chromatography-Orbitrap high resolution mass spectrometry. J. Chromatogr. A 1440 1368, 132–142. doi:10.1016/j.chroma.2014.09.067 1441
Coutu, S., Pouchon, T., Queloz, P., Vernaz, N., 2016. Integrated stochastic modeling of 1442 pharmaceuticals in sewage networks. Stoch. Environ. Res. Risk Assess. 30, 1087–1443 1097. doi:10.1007/s00477-015-1118-1 1444
Dasenaki, M.E., Bletsou, A.A., Koulis, G.A., Thomaidis, N.S., 2015. Qualitative 1445 multiresidue screening method for 143 veterinary drugs and pharmaceuticals in 1446 milk and fish tissue using liquid chromatography quadrupole-time-of-flight mass 1447 spectrometry. J. Agric. Food Chem. 63, 4493–4508. doi:10.1021/acs.jafc.5b00962 1448
Daughton, C.G., 2012. Using biomarkers in sewage to monitor community-wide human 1449 health: isoprostanes as conceptual prototype. Sci. Total Environ. 424, 16–38. 1450 doi:10.1016/j.scitotenv.2012.02.038 1451
Daughton, C.G., 2011. Illicit drugs: contaminants in the environment and utility in 1452 forensic epidemiology. Rev. Environ. Contam. Toxicol. 210, 59–110. 1453 doi:10.1007/978-1-4419-7615-4_3 1454
Daughton, C.G., 2001. Pharmaceuticals and personal care products in the environment, 1455 scientific and regulatory issues., in: Daughton, C.G., Jones-Lepp, T.L. (Eds.), . 1456 American Chemical Society, Washington, pp. 348–364. 1457
De Keyser, W., Gevaert, V., Verdonck, F., De Baets, B., Benedetti, L., 2010. An 1458 emission time series generator for pollutant release modelling in urban areas. 1459 Environ. Model. Softw. 25, 554–561. doi:10.1016/j.envsoft.2009.09.009 1460
de Voogt, P., Emke, E., Helmus, R., Panteliadis, P., van Leerdam, J.A., 2011. 1461 Determination of illicit drugs in the water cycle by LC-Orbitrap MS, in: 1462 Castiglioni, S., Zuccato, E., Fanelli, R. (Eds.), Illicit Drugs in the Environment: 1463 Occurrence, Analysis, and Fate Using Mass Spectrometry. Wiley, New York, NY, 1464 pp. 85–114. 1465
Delatour, T., Mottier, P., Gremaud, E., 2007. Limits of suspicion, recognition and 1466 confirmation as concepts that account for the confirmation transitions at the 1467 detection limit for quantification by liquid chromatography–tandem mass 1468
53
spectrometry. J. Chromatogr. A 1169, 103–110. doi:10.1016/j.chroma.2007.08.065 1469 Devault, D.A., Néfau, T., Pascaline, H., Karolak, S., Levi, Y., 2014. First evaluation of 1470
illicit and licit drug consumption based on wastewater analysis in Fort de France 1471 urban area (Martinique, Caribbean), a transit area for drug smuggling. Sci. Total 1472 Environ. 490, 970–978. doi:10.1016/j.scitotenv.2014.05.090 1473
Díaz, R., Ibáñez, M., Sancho, J. V., Hernández, F., 2012. Target and non-target 1474 screening strategies for organic contaminants, residues and illicit substances in 1475 food, environmental and human biological samples by UHPLC-QTOF-MS. Anal. 1476 Methods 4, 196–209. doi:10.1039/c1ay05385j 1477
Díaz, R., Ibáñez, M., Sancho, J. V., Hernández, F., 2011. Building an empirical mass 1478 spectra library for screening of organic pollutants by ultra-high-pressure liquid 1479 chromatography/hybrid quadrupole time-of-flight mass spectrometry. Rapid 1480 Commun. Mass Spectrom. 25, 355–369. doi:10.1002/rcm.4860 1481
EMA, 2012. Guideline on bioanalytical method validation, European Medicines 1482 Agency, Committee for Medicinal Products for Human Use. 1483 doi:EMEA/CHMP/EWP/192217/2009 1484
EMCDDA, 2016. Assessing illicit drugs in wastwater, in: Castiglioni, S., Vandam, L., 1485 Griffiths, P. (Eds.), Assessing Illicit Drugs in Wastewater: Advances in 1486 Wastewater-Based Drug Epidemiology, EMCDDA Insights 22. Publications 1487 Office of the European Union, Luxembourg, pp. 1–82. doi:10.2810/017397 1488
EMCDDA, 2015a. The EMCDDA’s five key epidemiological indicators [WWW 1489 Document]. URL http://www.emcdda.europa.eu/themes/key-indicators (accessed 1490 5.20.11). 1491
EMCDDA, 2015b. Wastewater analysis and drugs : a European multi-city study. 1492 EMCDDA, 2012. EMCDDA publishes 2012 report on the state of the drugs problem in 1493
Europe., Annual report. doi:10.2810/64775 1494 Emke, E., Evans, S., Kasprzyk-Hordern, B., de Voogt, P., 2014. Enantiomer profiling of 1495
high loads of amphetamine and MDMA in communal sewage: a Dutch 1496 perspective. Sci. Total Environ. 487, 666–672. doi:10.1016/j.scitotenv.2013.11.043 1497
EPA, 2007. Method 1694 : Pharmaceuticals and Personal Care Products in Water , Soil , 1498 Sediment , and Biosolids by HPLC / MS / MS, Environmental Protection Agency: 1499 Method 1694. 1500
European Commission, E., 2002. Decision 2002/657/EC, implementing Council 1501 Directive 96/23/EC concerning the performance of analytical methods and the 1502 interpretation of results. 1503
Evans, S.E., Kasprzyk-Hordern, B., 2014. Applications of chiral chromatography 1504 coupled with mass spectrometry in the analysis of chiral pharmaceuticals in the 1505 environment. Trends Environ. Anal. Chem. 1, e34–e51. 1506 doi:10.1016/j.teac.2013.11.005 1507
Farré, M., Kantiani, L., Petrovic, M., Pérez, S., Barceló, D., 2012. Achievements and 1508 future trends in the analysis of emerging organic contaminants in environmental 1509 samples by mass spectrometry and bioanalytical techniques. J. Chromatogr. A 1510 1259, 86–99. doi:10.1016/j.chroma.2012.07.024 1511
Fedorova, G., Randak, T., Lindberg, R.H., Grabic, R., 2013. Comparison of the 1512 quantitative performance of a Q-Exactive high-resolution mass spectrometer with 1513 that of a triple quadrupole tandem mass spectrometer for the analysis of illicit 1514 drugs in wastewater. Rapid Commun. Mass Spectrom. 27, 1751–1762. 1515 doi:10.1002/rcm.6628 1516
Gago-Ferrero, P., Schymanski, E.L., Bletsou, A.A., Aalizadeh, R., Hollender, J., 1517 Thomaidis, N.S., 2015. Extended Suspect and Non-Target Strategies to 1518
54
Characterize Emerging Polar Organic Contaminants in Raw Wastewater with LC-1519 HRMS/MS. Environ. Sci. Technol. 49, 12333–12341. doi:10.1021/acs.est.5b03454 1520
García-Reyes, J.F., Molina-Díaz, A., Fernández-Alba, A.R., 2007. Identification of 1521 pesticide transformation products in food by liquid chromatography/time-of-flight 1522 mass spectrometry via “fragmentation- degradation” relationships. Anal. Chem. 1523 79, 307–321. doi:10.1021/ac061402d 1524
Gheorghe, A., van Nuijs, A., Pecceu, B., Bervoets, L., Jorens, P.G., Blust, R., Neels, H., 1525 Covaci, A., 2008. Analysis of cocaine and its principal metabolites in waste and 1526 surface water using solid-phase extraction and liquid chromatography-ion trap 1527 tandem mass spectrometry. Anal. Bioanal. Chem. 391, 1309–1319. 1528 doi:10.1007/s00216-007-1754-5 1529
González-Mariño, I., Quintana, J.B., Rodríguez, I., Cela, R., 2010. Determination of 1530 drugs of abuse in water by solid-phase extraction, derivatisation and gas 1531 chromatography-ion trap-tandem mass spectrometry. J. Chromatogr. A 1217, 1532 1748–1760. doi:10.1016/j.chroma.2010.01.046 1533
González-Mariño, I., Quintana, J.B., Rodríguez, I., Gonzáez-Díez, M., Cela, R., 2012. 1534 Screening and selective quantification of illicit drugs in wastewater by mixed-1535 mode solid-phase extraction and quadrupole-time-of-flight liquid chromatography-1536 mass spectrometry. Anal. Chem. 84, 1708–1717. doi:10.1021/ac202989e 1537
González-Mariño, I., Quintana, J.B., Rodríguez, I., Rodil, R., González-Peñas, J., Cela, 1538 R., 2009. Comparison of molecularly imprinted, mixed-mode and hydrophilic 1539 balance sorbents performance in the solid-phase extraction of amphetamine drugs 1540 from wastewater samples for liquid chromatography-tandem mass spectrometry 1541 determination. J. Chromatogr. A 1216, 8435–8441. 1542 doi:10.1016/j.chroma.2009.09.069 1543
Hardman, M., Makarov, A., 2003. Interfacing the orbitrap mass analyzer to an 1544 electrospray ion source. Anal. Chem. 75, 1699–1705. doi:10.1021/ac0258047 1545
Harman, C., Reid, M., Thomas, K. V., 2011. In situ calibration of a passive sampling 1546 device for selected illicit drugs and their metabolites in wastewater, and subsequent 1547 year-long assessment of community drug usage. Environ. Sci. Technol. 45, 5676–1548 5682. doi:10.1021/es201124j 1549
Hernández, F., Bijlsma, L., Sancho, J. V., Díaz, R., Ibáñez, M., 2011a. Rapid wide-1550 scope screening of drugs of abuse, prescription drugs with potential for abuse and 1551 their metabolites in influent and effluent urban wastewater by ultrahigh pressure 1552 liquid chromatography-quadrupole-time-of-flight-mass spectrometry. Anal. Chim. 1553 Acta 684, 96–106. doi:10.1016/j.aca.2010.10.043 1554
Hernández, F., Grimalt, S., Pozo, Ó.J., Sancho, J. V., 2009. Use of ultra-high-pressure 1555 liquid chromatography-quadrupole time-of-flight MS to discover the presence of 1556 pesticide metabolites in food samples. J. Sep. Sci. 32, 2245–2261. 1557 doi:10.1002/jssc.200900093 1558
Hernández, F., Ibáñez, M., Bade, R., Bijlsma, L., Sancho, J.V., 2014. Investigation of 1559 pharmaceuticals and illicit drugs in waters by liquid chromatography-high-1560 resolution mass spectrometry. TrAC Trends Anal. Chem. 63, 140–157. 1561 doi:10.1016/j.trac.2014.08.003 1562
Hernández, F., Ibañez, M., Botero-Coy, A.M., Bade, R., Bustos-Lopez, M.C., Rincon, 1563 J., Moncayo, A., Bijlsma, L., 2015a. LC-QTOF MS screening of more than 1,000 1564 licit and illicit drugs and their metabolites in wastewater and surface waters from 1565 the area of Bogotá, Colombia. Anal. Bioanal. Chem. 407, 6405–6416. 1566 doi:10.1007/s00216-015-8796-x 1567
Hernández, F., Ibáñez, M., Portolés, T., Cervera, M.I., Sancho, J. V, López, F.J., 2015b. 1568
55
Advancing towards universal screening for organic pollutants in waters. J. Hazard. 1569 Mater. 282, 86–95. doi:10.1016/j.jhazmat.2014.08.006 1570
Hernández, F., Pozo, Ó.J., Sancho, J. V., López, F.J., Marín, J.M., Ibáñez, M., 2005. 1571 Strategies for quantification and confirmation of multi-class polar pesticides and 1572 transformation products in water by LC-MS2 using triple quadrupole and hybrid 1573 quadrupole time-of-flight analyzers. TrAC - Trends Anal. Chem. 24, 596–612. 1574 doi:10.1016/j.trac.2005.04.007 1575
Hernández, F., Sancho, J.V., Ibáñez, M., Portolés, T., 2011b. Time-of-Flight and 1576 Quadrupole Time-of-Flight Mass Spectrometry for Identifying Unknown 1577 Contaminants and Degradation Products in the Environment. Encycl. Anal. Chem. 1578 doi:10.1002/9780470027318.a9233 1579
Hernández, F., Sancho, J. V., Ibáñez, M., Abad, E., Portolés, T., Mattioli, L., 2012. 1580 Current use of high-resolution mass spectrometry in the environmental sciences. 1581 Anal. Bioanal. Chem. 403, 1251–1264. doi:10.1007/s00216-012-5844-7 1582
Heuett, N. V, Ramirez, C.E., Fernandez, A., Gardinali, P.R., 2015. Analysis of drugs of 1583 abuse by online SPE-LC high resolution mass spectrometry: communal assessment 1584 of consumption. Sci. Total Environ. 511, 319–330. 1585 doi:10.1016/j.scitotenv.2014.12.043 1586
Hogenboom, A.C., van Leerdam, J.A., de Voogt, P., 2009. Accurate mass screening and 1587 identification of emerging contaminants in environmental samples by liquid 1588 chromatography-hybrid linear ion trap Orbitrap mass spectrometry. J. Chromatogr. 1589 A 1216, 510–519. doi:10.1016/j.chroma.2008.08.053 1590
Holm, N.B., Pedersen, A.J., Dalsgaard, P.W., Linnet, K., 2015. Metabolites of 5F-AKB-1591 48, a synthetic cannabinoid receptor agonist, identified in human urine and liver 1592 microsomal preparations using liquid chromatography high-resolution mass 1593 spectrometry. Drug Test. Anal. 7, 199–206. doi:10.1002/dta.1663 1594
Horai, H., Arita, M., Kanaya, S., Nihei, Y., Ikeda, T., Suwa, K., Ojima, Y., Tanaka, K., 1595 Tanaka, S., Aoshima, K., Oda, Y., Kakazu, Y., Kusano, M., Tohge, T., Matsuda, 1596 F., Sawada, Y., Hirai, M.Y., Nakanishi, H., Ikeda, K., Akimoto, N., Maoka, T., 1597 Takahashi, H., Ara, T., Sakurai, N., Suzuki, H., Shibata, D., Neumann, S., Iida, T., 1598 Tanaka, K., Funatsu, K., Matsuura, F., Soga, T., Taguchi, R., Saito, K., Nishioka, 1599 T., 2010. MassBank: A public repository for sharing mass spectral data for life 1600 sciences. J. Mass Spectrom. 45, 703–714. doi:10.1002/jms.1777 1601
http://eawag-bbd.ethz.ch/ (accessed 2.12.16). 1602 http://score-cost.eu/ (accessed 2.12.16). 1603 http://sewprof-itn.eu/ (accessed 2.12.16). 1604 http://www.massbank.jp/ (accessed 2.12.16). 1605 Hu, Q., Noll, R.J., Li, H., Makarov, A., Hardman, M., Cooks, R.G., 2005. The Orbitrap: 1606
A new mass spectrometer. J. Mass Spectrom. 40, 430–443. doi:10.1002/jms.856 1607 Hug, C., Ulrich, N., Schulze, T., Brack, W., Krauss, M., 2014. Identification of novel 1608
micropollutants in wastewater by a combination of suspect and nontarget 1609 screening. Environ. Pollut. 184, 25–32. doi:10.1016/j.envpol.2013.07.048 1610
Humphries, M.A., Bruno, R., Lai, F.Y., Thai, P.K., Holland, B.R., O’Brien, J.W., Ort, 1611 C., Mueller, J.F., 2016. Evaluation of monitoring schemes for wastewater-based 1612 epidemiology to identify drug use trends using cocaine, methamphetamine, 1613 MDMA and methadone. Environ. Sci. Technol. doi:10.1021/acs.est.5b06126 1614
Ibañez, M., Pozo, A.J., Sancho, J. V., Orengo, T., Haro, G., Hernandez, F., 2016. 1615 Analytical strategy to investigate 3,4-methylenedioxypyrovalerone (MDPV) 1616 metabolites in consumers’ urine by high-resolution mass spectrometry. Anal. 1617 Bioanal. Chem. 408, 151–164. doi:10.1007/s00216-015-9088-1 1618
56
Ibáñez, M., Sancho, J. V., Bijlsma, L., Van Nuijs, A.L.N., Covaci, A., Hernández, F., 1619 2014. Comprehensive analytical strategies based on high-resolution time-of-flight 1620 mass spectrometry to identify new psychoactive substances. TrAC - Trends Anal. 1621 Chem. 57, 107–117. doi:10.1016/j.trac.2014.02.009 1622
Ibáñez, M., Sancho, J. V., Hernández, F., McMillan, D., Rao, R., 2008. Rapid non-1623 target screening of organic pollutants in water by ultraperformance liquid 1624 chromatography coupled to time-of-light mass spectrometry. TrAC - Trends Anal. 1625 Chem. 27, 481–489. doi:10.1016/j.trac.2008.03.007 1626
Ibáñez, M., Sancho, J. V., Pozo, Ó.J., Niessen, W.M.A., Hernández, F., 2005. Use of 1627 quadrupole time-of-flight mass spectrometry in the elucidation of unknown 1628 compounds present in environmental water. Rapid Commun. Mass Spectrom. 19, 1629 169–178. doi:10.1002/rcm.1764 1630
Irvine, R.J., Kostakis, C., Felgate, P.D., Jaehne, E.J., Chen, C., White, J.M., 2011. 1631 Population drug use in Australia: a wastewater analysis. Forensic Sci. Int. 210, 69–1632 73. doi:10.1016/j.forsciint.2011.01.037 1633
Kankaanpää, A., Ariniemi, K., Heinonen, M., Kuoppasalmi, K., Gunnar, T., 2014. Use 1634 of illicit stimulant drugs in Finland: A wastewater study in ten major cities. Sci. 1635 Total Environ. 487, 696–702. doi:10.1016/j.scitotenv.2013.11.095 1636
Karolak, S., Nefau, T., Bailly, E., Solgadi, A., Levi, Y., 2010. Estimation of illicit drugs 1637 consumption by wastewater analysis in Paris area (France). Forensic Sci. Int. 200, 1638 153–160. doi:10.1016/j.forsciint.2010.04.007 1639
Kasprzyk-Hordern, B., Baker, D.R., 2012a. Estimation of community-wide drugs use 1640 via stereoselective profiling of sewage. Sci. Total Environ. 423, 142–150. 1641 doi:10.1016/j.scitotenv.2012.02.019 1642
Kasprzyk-Hordern, B., Baker, D.R., 2012b. Enantiomeric profiling of chiral drugs in 1643 wastewater and receiving waters. Environ. Sci. Technol. 46, 1681–1691. 1644 doi:10.1021/es203113y 1645
Kaufmann, A., 2014. Combining UHPLC and high-resolution MS: A viable approach 1646 for the analysis of complex samples? TrAC Trends Anal. Chem. 63, 113–128. 1647 doi:10.1016/j.trac.2014.06.025 1648
Kaufmann, A., Butcher, P., Maden, K., Walker, S., Widmer, M., 2010. Comprehensive 1649 comparison of liquid chromatography selectivity as provided by two types of liquid 1650 chromatography detectors (high resolution mass spectrometry and tandem mass 1651 spectrometry): “where is the crossover point?”. Anal. Chim. Acta 673, 60–72. 1652 doi:10.1016/j.aca.2010.05.020 1653
Kellmann, M., Muenster, H., Zomer, P., Mol, H., 2009. Full Scan MS in 1654 Comprehensive Qualitative and Quantitative Residue Analysis in Food and Feed 1655 Matrices: How Much Resolving Power is Required? J. Am. Soc. Mass Spectrom. 1656 20, 1464–1476. doi:10.1016/j.jasms.2009.05.010 1657
Kern, S., Fenner, K., Singer, H.P., Schwarzenbach, R.P., Hollender, J., 2009. 1658 Identification of transformation products of organic contaminants in natural waters 1659 by computer-aided prediction and high-resolution mass spectrometry. Environ. Sci. 1660 Technol. 43, 7039–7046. doi:10.1021/es901979h 1661
Khan, U., van Nuijs, A.L.N., Li, J., Maho, W., Du, P., Li, K., Hou, L., Zhang, J., Meng, 1662 X., Li, X., Covaci, A., 2014. Application of a sewage-based approach to assess the 1663 use of ten illicit drugs in four Chinese megacities. Sci. Total Environ. 487, 710–1664 721. doi:10.1016/j.scitotenv.2014.01.043 1665
Kim, K.Y., Lai, F.Y., Kim, H.-Y., Thai, P.K., Mueller, J.F., Oh, J.-E., 2015. The first 1666 application of wastewater-based drug epidemiology in five South Korean cities. 1667 Sci. Total Environ. 524–525, 440–446. doi:10.1016/j.scitotenv.2015.04.065 1668
57
Kinyua, J., Covaci, A., Maho, W., McCall, A.-K., Neels, H., van Nuijs, A.L.N., 2015. 1669 Sewage-based epidemiology in monitoring the use of new psychoactive 1670 substances: Validation and application of an analytical method using LC-MS/MS. 1671 Drug Test. Anal. 7, 812–818. doi:10.1002/dta.1777 1672
Kirchmair, J., Göller, A.H., Lang, D., Kunze, J., Testa, B., Wilson, I.D., Glen, R.C., 1673 Schneider, G., 2015. Predicting drug metabolism: experiment and/or computation? 1674 Nat. Rev. Drug Discov. 14, 387–404. doi:10.1038/nrd4581 1675
Krauss, M., Singer, H., Hollender, J., 2010. LC-high resolution MS in environmental 1676 analysis: From target screening to the identification of unknowns. Anal. Bioanal. 1677 Chem. 397, 943–951. doi:10.1007/s00216-010-3608-9 1678
Lai, F.Y., Bruno, R., Hall, W., Gartner, C., Ort, C., Kirkbride, P., Prichard, J., Thai, 1679 P.K., Carter, S., Mueller, J.F., 2013a. Profiles of illicit drug use during annual key 1680 holiday and control periods in Australia: Wastewater analysis in an urban, a semi-1681 rural and a vacation area. Addiction 108, 556–565. doi:10.1111/add.12006 1682
Lai, F.Y., Bruno, R., Leung, H.W., Thai, P.K., Ort, C., Carter, S., Thompson, K., Lam, 1683 P.K.S., Mueller, J.F., 2013b. Estimating daily and diurnal variations of illicit drug 1684 use in Hong Kong: A pilot study of using wastewater analysis in an Asian 1685 metropolitan city. Forensic Sci. Int. 233, 126–132. 1686 doi:10.1016/j.forsciint.2013.09.003 1687
Lai, F.Y., Ort, C., Gartner, C., Carter, S., Prichard, J., Kirkbride, P., Bruno, R., Hall, 1688 W., Eaglesham, G., Mueller, J.F., 2011. Refining the estimation of illicit drug 1689 consumptions from wastewater analysis: co-analysis of prescription 1690 pharmaceuticals and uncertainty assessment. Water Res. 45, 4437–4448. 1691 doi:10.1016/j.watres.2011.05.042 1692
Li, J., Hou, L., Du, P., Yang, J., Li, K., Xu, Z., Wang, C., Zhang, H., Li, X., 2014. 1693 Estimation of amphetamine and methamphetamine uses in Beijing through 1694 sewage-based analysis. Sci. Total Environ. 490, 724–32. 1695 doi:10.1016/j.scitotenv.2014.05.042 1696
Makarov, A., Denisov, E., Kholomeev, A., Balschun, W., Lange, O., Strupat, K., 1697 Horning, S., 2006. Performance Evaluation of a Hybrid Linear Ion Trap / Orbitrap 1698 Mass Spectrometer. Anal. Chem. 78, 2113–2120. 1699
Makarov, A., Scigelova, M., 2010. Coupling liquid chromatography to Orbitrap mass 1700 spectrometry. J. Chromatogr. A 1217, 3938–3945. 1701 doi:10.1016/j.chroma.2010.02.022 1702
Maldaner, A.O., Schmidt, L.L., Locatelli, M.A.F., Jardim, W.F., Sodré, F.F., Almeida, 1703 F. V., Pereira, C.E.B., Silva, C.M., 2012. Estimating cocaine consumption in the 1704 brazilian federal district (FD) by sewage analysis. J. Braz. Chem. Soc. 23, 861–1705 867. doi:10.1590/S0103-50532012000500011 1706
Mari, F., Politi, L., Biggeri, A., Accetta, G., Trignano, C., Di Padua, M., Bertol, E., 1707 2009. Cocaine and heroin in waste water plants: A 1-year study in the city of 1708 Florence, Italy. Forensic Sci. Int. 189, 88–92. doi:10.1016/j.forsciint.2009.04.018 1709
Martínez Bueno, M.J., Uclés, S., Hernando, M.D., Fernández-Alba, A.R., 2011. 1710 Development of a solvent-free method for the simultaneous 1711 identification/quantification of drugs of abuse and their metabolites in 1712 environmental water by LC-MS/MS. Talanta 85, 157–166. 1713 doi:10.1016/j.talanta.2011.03.051 1714
Mastroianni, N., Lopez de Alda, M., Barcelo, D., 2014. Analysis of ethyl sulfate in raw 1715 wastewater for estimation of alcohol consumption and its correlation with drugs of 1716 abuse in the city of Barcelona. J. Chromatogr. A 1360, 93–99. 1717 doi:10.1016/j.chroma.2014.07.051 1718
58
McCall, A.-K., Bade, R., Kinyua, J., Lai, F.Y., Thai, P.K., Covaci, A., Bijlsma, L., van 1719 Nuijs, A.L.N., Ort, C., 2016. Critical review on the stability of illicit drugs in 1720 sewers and wastewater samples. Water Res. 88, 933–947. 1721 doi:10.1016/j.watres.2015.10.040 1722
Metcalfe, C., Tindale, K., Li, H., Rodayan, A., Yargeau, V., 2010. Illicit drugs in 1723 Canadian municipal wastewater and estimates of community drug use. Environ. 1724 Pollut. 158, 3179–3185. doi:10.1016/j.envpol.2010.07.002 1725
Meyer, M.R., Holderbaum, A., Kavanagh, P., Maurer, H.H., 2015. Low resolution and 1726 high resolution MS for studies on the metabolism and toxicological detection of 1727 the new psychoactive substance methoxypiperamide (MeOP). J. Mass Spectrom. 1728 50, 1163–1174. doi:10.1002/jms.3635 1729
Miller, T.H., Musenga, A., Cowan, D. a, Barron, L.P., 2013. Prediction of 1730 Chromatographic Retention Time in High-Resolution Anti-Doping Screening Data 1731 Using Arti fi cial Neural Networks. Anal. Chem. 85, 10330–10337. 1732
Moore, K.A., Mozayani, A., Fierro, M.F., Poklis, A., 1996. Distribution of 3,4-1733 methylenedioxymethamphetamine (MDMA) and 3,4-methylenedioxyamphetamine 1734 (MDA) stereoisomers in a fatal poisoning. Forensic Sci. Int. 83, 111–119. 1735 doi:10.1016/S0379-0738(96)02025-7 1736
Munro, K., Miller, T.H., Martins, C.P.B., Edge, A.M., Cowan, D.A., Barron, L.P., 2015. 1737 Artificial neural network modelling of pharmaceutical residue retention times in 1738 wastewater extracts using gradient liquid chromatography-high resolution mass 1739 spectrometry data. J. Chromatogr. A 1396, 34–44. 1740 doi:10.1016/j.chroma.2015.03.063 1741
Nácher-Mestre, J., Ibáñez, M., Serrano, R., Boix, C., Bijlsma, L., Lunestad, B.T., 1742 Hannisdal, R., Alm, M., Hernández, F., Berntssen, M.H.G., 2016. Investigation of 1743 pharmaceuticals in processed animal by-products by liquid chromatography 1744 coupled to high-resolution mass spectrometry. Chemosphere 154, 231–239. 1745 doi:10.1016/j.chemosphere.2016.03.091 1746
Nutt, D., King, L.A., Saulsbury, W., Blakemore, C., 2007. Development of a rational 1747 scale to assess the harm of drugs of potential misuse. Lancet (London, England) 1748 369, 1047–1053. doi:10.1016/S0140-6736(07)60464-4 1749
Ort, C., 2014. Quality assurance/quality control in wastewater sampling, in: Zhang, C., 1750 Mueller, J.F., Mortimer, M. (Eds.), Quality Assurance & Quality Control of 1751 Environmental Field Samples. Future Science, London, UK. 1752
Ort, C., Banta-Green, C., Bijlsma, L., Castiglioni, S., Emke, E., Gartner, C., Kasprzyk-1753 Hordern, B., Reid, M.J., Rieckermann, J., van Nuijs, A.L.N., 2014a. Sewage-based 1754 Epidemiology Requires a Truly Transdisciplinary Approach. GAIA 23, 266–268. 1755
Ort, C., Eppler, J.M., Scheidegger, A., Rieckermann, J., Kinzig, M., Sörgel, F., 2014b. 1756 Challenges of surveying wastewater drug loads of small populations and 1757 generalizable aspects on optimizing monitoring design. Addiction 109, 472–481. 1758 doi:10.1111/add.12405 1759
Ort, C., Lawrence, M.G., Reungoat, J., Mueller, J.F., 2010a. Sampling for PPCPs in 1760 Wastewater Systems: Comparison of Different Sampling Modes and Optimization 1761 Strategies. Environ. Sci. Technol. 44, 6289–6296. doi:10.1021/es100778d 1762
Ort, C., Lawrence, M.G., Rieckermann, J., Joss, A., 2010b. Sampling for 1763 pharmaceuticals and personal care products (PPCPs) and illicit drugs in wastewater 1764 systems: Are your conclusions valid? A critical review. Environ. Sci. Technol. 44, 1765 6024–6035. doi:10.1021/es100779n 1766
Ort, C., van Nuijs, A.L.N., Berset, J.D., Bijlsma, L., Castiglioni, S., Covaci, A., de 1767 Voogt, P., Emke, E., Fatta-Kassinos, D., Griffiths, P., Hernández, F., González-1768
59
Mariño, I., Grabic, R., Kasprzyk-Hordern, B., Mastroianni, N., Meierjohann, A., 1769 Nefau, T., Östman, M., Pico, Y., Racamonde, I., Reid, M., Slobodnik, J., Terzic, 1770 S., Thomaidis, N., Thomas, K. V., 2014c. Spatial differences and temporal changes 1771 in illicit drug use in Europe quantified by wastewater analysis. Addiction 109, 1772 1338–1352. doi:10.1111/add.12570 1773
Petrovic, M., Farré, M., de Alda, M.L., Perez, S., Postigo, C., Köck, M., Radjenovic, J., 1774 Gros, M., Barcelo, D., 2010. Recent trends in the liquid chromatography-mass 1775 spectrometry analysis of organic contaminants in environmental samples. J. 1776 Chromatogr. A 1217, 4004–4017. doi:10.1016/j.chroma.2010.02.059 1777
Plumb, R.S., Johnson, K.A., Rainville, P., Smith, B.W., Wilson, I.D., Castro-Perez, 1778 J.M., Nicholson, J.K., 2006. UPLC/MS E ; a new approach for generating 1779 molecular fragment information for biomarker structure elucidation. Rapid 1780 Commun. mass Spectrom. 20, 1989–1994. doi:10.1002/rcm 1781
Postigo, C., Lopez De Alda, M.J., Barceló, D., 2008. Fully automated determination in 1782 the low nanogram per liter level of different classes of drugs of abuse in sewage 1783 water by on-line solid-phase extraction-liquid chromatography-electrospray-1784 tandem mass spectrometry. Anal. Chem. 80, 3123–3134. doi:10.1021/ac702060j 1785
Postigo, C., Sirtori, C., Oller, I., Malato, S., Maldonado, M.I., López de Alda, M., 1786 Barceló, D., 2011. Solar transformation and photocatalytic treatment of cocaine in 1787 water: Kinetics, characterization of major intermediate products and toxicity 1788 evaluation. Appl. Catal. B Environ. 104, 37–48. doi:10.1016/j.apcatb.2011.02.030 1789
Pozo, O.J., Ibanez, M., Sancho, J. V., Lahoz-Beneytez, J., Farre, M., Papaseit, E., de la 1790 Torre, R., Hernandez, F., 2014. Mass Spectrometric Evaluation of Mephedrone In 1791 Vivo Human Metabolism: Identification of Phase I and Phase II Metabolites, 1792 Including a Novel Succinyl Conjugate. Drug Metab. Dispos. 43, 248–257. 1793 doi:10.1124/dmd.114.061416 1794
Pozo, O.J., Sancho, J. V., Ibáñez, M., Hernández, F., Niessen, W.M.A., 2006. 1795 Confirmation of organic micropollutants detected in environmental samples by 1796 liquid chromatography tandem mass spectrometry: Achievements and pitfalls. 1797 TrAC Trends Anal. Chem. 25, 1030–1042. doi:10.1016/j.trac.2006.06.012 1798
Pozo, O.J., Van Eenoo, P., Deventer, K., Delbeke, F.T., 2007. Development and 1799 validation of a qualitative screening method for the detection of exogenous 1800 anabolic steroids in urine by liquid chromatography-tandem mass spectrometry. 1801 Anal. Bioanal. Chem. 389, 1209–1224. doi:10.1007/s00216-007-1530-6 1802
Prichard, J., Lai, F.Y., Kirkbride, P., Bruno, R., Ort, C., Carter, S., Hall, W., Gartner, 1803 C., Thai, P.K., Mueller, J.F., 2012. Measuring drug use patterns in Queensland 1804 through wastewater analysis. Trends Issues Crime Crim. Justice 1–8. 1805
Racamonde, I., Rodil, R., Quintana, J.B., Cela, R., 2013. In-sample derivatization-solid-1806 phase microextraction of amphetamines and ecstasy related stimulants from water 1807 and urine. Anal. Chim. Acta 770, 75–84. doi:10.1016/j.aca.2013.02.001 1808
Racamonde, I., Villaverde-de-Sáa, E., Rodil, R., Quintana, J.B., Cela, R., 2012. 1809 Determination of Δ9-tetrahydrocannabinol and 11-nor-9-carboxy-Δ9-1810 tetrahydrocannabinol in water samples by solid-phase microextraction with on-1811 fiber derivatization and gas chromatography-mass spectrometry. J. Chromatogr. A 1812 1245, 167–174. doi:10.1016/j.chroma.2012.05.017 1813
Reid, M.J., Baz-Lomba, J.A., Ryu, Y., Thomas, K. V., 2014a. Using biomarkers in 1814 wastewater to monitor community drug use: a conceptual approach for dealing 1815 with new psychoactive substances. Sci. Total Environ. 487, 651–658. 1816 doi:10.1016/j.scitotenv.2013.12.057 1817
Reid, M.J., Derry, L., Thomas, K. V., 2014b. Analysis of new classes of recreational 1818
60
drugs in sewage: Synthetic cannabinoids and amphetamine-like substances. Drug 1819 Test. Anal. 6, 72–79. doi:10.1002/dta.1461 1820
Reid, M.J., Langford, K.H., Mørland, J., Thomas, K. V., 2011. Analysis and 1821 interpretation of specific ethanol metabolites, ethyl sulfate, and ethyl glucuronide 1822 in sewage effluent for the quantitative measurement of regional alcohol 1823 consumption. Alcohol. Clin. Exp. Res. 35, 1593–1599. doi:10.1111/j.1530-1824 0277.2011.01505.x 1825
Rodríguez-Álvarez, T., Racamonde, I., González-Mariño, I., Borsotti, A., Rodil, R., 1826 Rodríguez, I., Zuccato, E., Quintana, J.B., Castiglioni, S., 2015. Alcohol and 1827 cocaine co-consumption in two European cities assessed by wastewater analysis. 1828 Sci. Total Environ. 536, 91–98. doi:10.1016/j.scitotenv.2015.07.016 1829
Rodríguez-Álvarez, T., Rodil, R., Cela, R., Quintana, J.B., 2014. Ion-pair reversed-1830 phase liquid chromatography-quadrupole-time-of-flight and triple-quadrupole-1831 mass spectrometry determination of ethyl sulfate in wastewater for alcohol 1832 consumption tracing. J. Chromatogr. A 1328, 35–42. 1833 doi:10.1016/j.chroma.2013.12.076 1834
Rodriguez-Alvarez, T., Rodil, R., Rico, M., Cela, R., Quintana, J.B., 2014. Assessment 1835 of Local Tobacco Consumption by Liquid Chromatography − Tandem Mass 1836 Spectrometry Sewage Analysis of Nicotine and Its Metabolites, Cotinine and trans-1837 3 ′ -Hydroxycotinine, after Enzymatic Deconjugation. Anal. Chemsitry 86, 10274–1838 10281. 1839
SANCO, 2013. Guidance document on analytical quality control and validation 1840 procedures for pesticide residues analysis in food and feed. 1841
SANTE/11945, 2015. Guidance document on analytical quality control and method 1842 validation procedures for pesticide residues analysis in food and feed. 1843
Schymanski, E.L., Jeon, J., Gulde, R., Fenner, K., Ru, M., Singer, H.P., Hollender, J., 1844 2014a. Identifying Small Molecules via High Resolution Mass Spectrometry: 1845 Communicating Confidence. Environ. Sci. Technol. 48, 2097–2098. 1846 doi:10.1021/es5002105 | 1847
Schymanski, E.L., Singer, H.P., Longrée, P., Loos, M., Ruff, M., Stravs, M.A., Ripollés 1848 Vidal, C., Hollender, J., 2014b. Strategies to characterize polar organic 1849 contamination in wastewater: Exploring the capability of high resolution mass 1850 spectrometry. Environ. Sci. Technol. 48, 1811–1818. doi:10.1021/es4044374 1851
Schymanski, E.L., Singer, H.P., Slobodnik, J., Ipolyi, I.M., Oswald, P., Krauss, M., 1852 Schulze, T., Haglund, P., Letzel, T., Grosse, S., Thomaidis, N.S., Bletsou, A., 1853 Zwiener, C., Ibáñez, M., Portolés, T., de Boer, R., Reid, M.J., Onghena, M., 1854 Kunkel, U., Schulz, W., Guillon, A., Noyon, N., Leroy, G., Bados, P., Bogialli, S., 1855 Stipaničev, D., Rostkowski, P., Hollender, J., 2015. Non-target screening with 1856 high-resolution mass spectrometry: critical review using a collaborative trial on 1857 water analysis. Anal. Bioanal. Chem. 407, 6237–6255. doi:10.1007/s00216-015-1858 8681-7 1859
Senta, I., Krizman, I., Ahel, M., Terzic, S., 2013. Integrated procedure for multiresidue 1860 analysis of dissolved and particulate drugs in municipal wastewater by liquid 1861 chromatography-tandem mass spectrometry. Anal. Bioanal. Chem. 405, 3255–1862 3268. doi:10.1007/s00216-013-6720-9 1863
Stanstrup, J., Neumann, S., Vrhovšek, U., 2015. PredRet: Prediction of Retention Time 1864 by Direct Mapping between Multiple Chromatographic Systems. Anal. Chem. 87, 1865 9421–9428. doi:10.1021/acs.analchem.5b02287 1866
Subedi, B., Kannan, K., 2014. Mass loading and removal of select illicit drugs in two 1867 wastewater treatment plants in New York State and estimation of illicit drug usage 1868
61
in communities through wastewater analysis. Environ. Sci. Technol. 48, 6661–1869 6670. doi:10.1021/es501709a 1870
Takayama, T., Suzuki, M., Todoroki, K., Inoue, K., Min, J.Z., Kikura-Hanajiri, R., 1871 Goda, Y., Toyo’oka, T., 2014. UPLC/ESI-MS/MS-based determination of 1872 metabolism of several new illicit drugs, ADB-FUBINACA, AB-FUBINACA, AB-1873 PINACA, QUPIC, 5F-QUPIC and α-PVT, by human liver microsome. Biomed. 1874 Chromatogr. 28, 831–838. doi:10.1002/bmc.3155 1875
Thomas, K. V., Bijlsma, L., Castiglioni, S., Covaci, A., Emke, E., Grabic, R., 1876 Hernández, F., Karolak, S., Kasprzyk-Hordern, B., Lindberg, R.H., Lopez de Alda, 1877 M., Meierjohann, A., Ort, C., Pico, Y., Quintana, J.B., Reid, M., Rieckermann, J., 1878 Terzic, S., van Nuijs, A.L.N., de Voogt, P., 2012. Comparing illicit drug use in 19 1879 European cities through sewage analysis. Sci. Total Environ. 432, 432–439. 1880 doi:10.1016/j.scitotenv.2012.06.069 1881
Thomas, K. V., Reid, M.J., 2011. What Else Can the Analysis of Sewage for Urinary 1882 Biomarkers Reveal About Communities? Environ. Sci. Technol. 45, 7611–7612. 1883 doi:10.1021/es202522d 1884
Thurman, E.M., Ferrer, I., Zweigenbaum, J.A., García-Reyes, J.F., Woodman, M., 1885 Fernández-Alba, A.R., 2005. Discovering metabolites of post-harvest fungicides in 1886 citrus with liquid chromatography/time-of-flight mass spectrometry and ion trap 1887 tandem mass spectrometry. J. Chromatogr. A 1082, 71–80. 1888 doi:10.1016/j.chroma.2005.03.042 1889
Trufelli, H., Palma, P., Famiglini, G., Cappiello, A., 2011. An overview of matrix 1890 effects in liqiud chromatography-mass spectrometry. Mass Spectrom. Rev. 30, 1891 491–509. doi:DOI 10.1002/mas.20298 1892
Tscharke, B., Chen, C., Gerber, J.P., White, J.M., 2015. Trends in stimulant use in 1893 Australia: A comparison of wastewater analysis and population surveys. Sci. Total 1894 Environ. 536, 331–337. doi:10.1016/j.scitotenv.2015.07.078 1895
Tscharke, B.J., White, J.M., Gerber, J.P., 2016. Estimates of tobacco use by wastewater 1896 analysis of anabasine and anatabine. Drug Test. Anal. 8, 702–707. 1897 doi:10.1002/dta.1842 1898
Tscharke, Chen, C., Gerber, J.P., White, J.M., 2016. Temporal trends in drug use in 1899 Adelaide, South Australia by wastewater analysis. Sci. Total Environ. 565, 384–1900 391. doi:10.1016/j.scitotenv.2016.04.183 1901
UNODC, 2014. World Drug Report 2014, Trends in Organized Crime. 1902 doi:10.1007/s12117-997-1166-0 1903
van der Aa, M., Bijlsma, L., Emke, E., Dijkman, E., van Nuijs, A.L.N., van de Ven, B., 1904 Hernández, F., Versteegh, A., de Voogt, P., 2013. Risk assessment for drugs of 1905 abuse in the Dutch watercycle. Water Res. 47, 1848–1857. 1906 doi:10.1016/j.watres.2013.01.013 1907
van Leerdam, J.A., Vervoort, J., Stroomberg, G., de Voogt, P., 2014. Identification of 1908 unknown microcontaminants in dutch river water by liquid chromatography-high 1909 resolution mass spectrometry and nuclear magnetic resonance spectroscopy. 1910 Environ. Sci. Technol. 48, 12791–12799. doi:10.1021/es502765e 1911
van Nuijs, A.L.N., Castiglioni, S., Tarcomnicu, I., Postigo, C., de Alda, M.L., Neels, H., 1912 Zuccato, E., Barcelo, D., Covaci, A., 2011. Illicit drug consumption estimations 1913 derived from wastewater analysis: A critical review. Sci. Total Environ. 409, 1914 3564–3577. doi:10.1016/j.scitotenv.2010.05.030 1915
van Nuijs, A.L.N., Gheorghe, A., Jorens, P.G., Maudens, K., Neels, H., Covaci, A., 1916 2014. Optimization, validation, and the application of liquid chromatography-1917 tandem mass spectrometry for the analysis of new drugs of abuse in wastewater. 1918
62
Drug Test. Anal. 6, 861–867. doi:10.1002/dta.1460 1919 van Nuijs, A.L.N., Tarcomnicu, I., Bervoets, L., Blust, R., Jorens, P.G., Neels, H., 1920
Covaci, A., 2009. Analysis of drugs of abuse in wastewater by hydrophilic 1921 interaction liquid chromatography-tandem mass spectrometry. Anal. Bioanal. 1922 Chem. 395, 819–828. doi:10.1007/s00216-009-3017-0 1923
Vazquez-Roig, P., Blasco, C., Picó, Y., 2013. Advances in the analysis of legal and 1924 illegal drugs in the aquatic environment. TrAC - Trends Anal. Chem. 50, 65–77. 1925 doi:10.1016/j.trac.2013.04.008 1926
Venhuis, B.J., de Voogt, P., Emke, E., Causanilles, A., Keizers, P.H.J., 2014. Success of 1927 rogue online pharmacies: sewage study of sildenafil in the Netherlands. BMJ 349, 1928 g4317. doi:10.1136/bmj.g4317 1929
Voloshenko-Rossin, A., Gasser, G., Cohen, K., Gun, J., Cumbal-Flores, L., Parra-1930 Morales, W., Sarabia, F., Ojeda, F., Lev, O., 2015. Emerging pollutants in the 1931 Esmeraldas watershed in Ecuador: discharge and attenuation of emerging organic 1932 pollutants along the San Pedro–Guayllabamba–Esmeraldas rivers. Environ. Sci. 1933 Process. Impacts 17, 41–53. doi:10.1039/C4EM00394B 1934
Wong, C.S., MacLeod, S.L., 2009. JEM spotlight: recent advances in analysis of 1935 pharmaceuticals in the aquatic environment. J. Environ. Monit. 11, 923–936. 1936 doi:10.1039/b904065j 1937
Yang, Z., Anglès d’Auriac, M., Goggins, S., Kasprzyk-Hordern, B., Thomas, K. V, 1938 Frost, C.G., Estrela, P., 2015a. A novel DNA biosensor using a ferrocenyl 1939 intercalator applied to the potential detection of human population biomarkers in 1940 wastewater. Environ. Sci. Technol. 49, 5609–5617. doi:10.1021/acs.est.5b00637 1941
Yang, Z., Castrignanò, E., Estrela, P., Frost, C.G., Kasprzyk-Hordern, B., 2016. 1942 Community Sewage Sensors towards Evaluation of Drug Use Trends: Detection of 1943 Cocaine in Wastewater with DNA-Directed Immobilization Aptamer Sensors. Sci. 1944 Rep. 6, 1–10. doi:10.1038/srep21024 1945
Yang, Z., Kasprzyk-Hordern, B., Frost, C.G., Estrela, P., Thomas, K. V, 2015b. 1946 Community sewage sensors for monitoring public health. Environ. Sci. Technol. 1947 49, 5845–5846. doi:10.1021/acs.est.5b01434 1948
Yang, Z., Kasprzyk-Hordern, B., Goggins, S., Frost, C.G., Estrela, P., 2015c. A novel 1949 immobilization strategy for electrochemical detection of cancer biomarkers: DNA-1950 directed immobilization of aptamer sensors for sensitive detection of prostate 1951 specific antigens. Analyst 140, 2628–2633. doi:10.1039/c4an02277g 1952
Zomer, P., Mol, J.G.J., 2015. Simultaneous quantitative determination, identification 1953 and qualitative screening of pesticides in fruits and vegetables using LC-Q-1954 OrbitrapTM-MS. Food Addit. Contam. Part A Chem. Anal. Control. Expo. Risk 1955 Assess. 32, 1628–1636. doi:10.1080/19440049.2015.1085652 1956
Zuccato, E., Chiabrando, C., Castiglioni, S., Bagnati, R., Fanelli, R., 2008. Estimating 1957 community drug abuse by wastewater analysis. Environ. Health Perspect. 116, 1958 1027–1032. doi:10.1289/ehp.11022 1959
Zuccato, E., Chiabrando, C., Castiglioni, S., Calamari, D., Bagnati, R., Schiarea, S., 1960 Fanelli, R., 2005. Cocaine in surface waters: a new evidence-based tool to monitor 1961 community drug abuse. Environ. Heal. A Glob. Access Sci. Source 4, 1–7. 1962 doi:10.1186 1963
1964