Distribution of Anticancer Drugs in River Waters and Sediments of the Yodo River Basin, Japan

applied sciences

Article Distribution of Anticancer Drugs in River Waters and Sediments of the Yodo River Basin, Japan

Takashi Azuma

Osaka University of Pharmaceutical Sciences, Department of pharmacy, 4-20-1 Nasahara, Takatsuki, Osaka 569-1094, Japan; [email protected] or [email protected]; Tel.: +81-72-690-1055

Received: 31 August 2018; Accepted: 15 October 2018; Published: 24 October 2018

Featured Application: This work gives an overview of the present status of anticancer drugs in the environmental water of the Yodo River basin, a speciﬁc populated area in Japan. The results indicate importance of application of high-tech treatment(s) including advanced oxidation processes at sewage treatment plant for efﬁcient removal of the discharged drugs.

Abstract: This article reviews the pollution status of anticancer drugs present in the Yodo River basin located in the Kansai district of Japan, covering both the soluble and insoluble (adsorbed on the river sediments and suspended solids) levels. Procedures ranging from sampling in the field and instrumental analytical methods to the data processing for mass balance estimation of the target basin are also described. All anticancer drugs concerned with this article were detected in sewage and river waters, where the presence of bicalutamide (BLT) was identified at considerably high concentrations (maximum 254 ng/L in the main stream, 151 ng/L in tributaries, and 1032 ng/L in sewage treatment plant (STP) effluents). In addition, sorption distribution coefficient (logKd) values showed a tendency to become higher in the silty sediments at Suita Bridge than in the sandy sediments at Hirakata Bridge; these trends were supported by the results of the laboratory-scale sorption experiment. STPs were concluded to be the main sources of the anticancer drug load in the river, and a mass flux evaluation revealed that the effect of attenuation in the river environment was small. The effectiveness of ozonation in the sewage treatment process for removal of these anticancer drugs was further confirmed. The present article should be of value for facilitating the environmental risk assessment of a wide range of drugs in a broader geographical area.

Keywords: anticancer drugs; urban river basin in Japan; river water; river sediment; sorption distribution coefﬁcient (logKd); sewage treatment plants (STPs); ozonation

1. Introduction The emerging problem of the pollution of river environments by pharmaceuticals and personal care products (PPCPs) has received a large amount of attention [1–3]. Pharmaceuticals are designed to have specific physiological effects on target areas of the body. Concern is therefore rising about their toxic effects on ecosystems when discharged into environmental water, even when they are present at low concentrations. Furthermore, their impacts on human health via residues contaminating drinking water should be taken into consideration [4–7]. Generally, the concentrations of these compounds are low (roughly in the range from ng/L to µg/L) worldwide [7–9]. Even in this low concentration range, however, there have been reports of the endocrine-disrupting chemicals that have serious environmental impacts, such as the feminization of male fishes [10,11]. PPCPs include different groups of compounds typified by their chemical characteristics, structure, mechanism of action, mode of action, and their therapeutic use to treat specific diseases. Particularly,

Appl. Sci. 2018, 8, 2043; doi:10.3390/app8112043 www.mdpi.com/journal/applsci Appl. Sci. 2018, 8, 2043 2 of 17 anticancer drugs are emerging as an area of growing interest because of their promotion of a long lifespan via the suppression of human death through their use as a chemotherapy [12,13]. Human life is changing in response to recent developments in science and technology. In Japan, cancer has been the country’s top cause of death since 1981, accounting for 29% of all deaths in 2015. This was nearly double the rate of the second-highest cause of death, heart disease (15%) [14]. In addition, because of the aging of the Japanese population [14], the number of cancer patients who need treatment is likely to increase in future. Increasing numbers of new pharmaceuticals for chemotherapy [15], which, along with surgery and radiotherapy, is an important treatment for cancer, have been developed in recent years [16]. The use of anticancer agents in clinical situations is also increasing, whereas the rates of adoption of surgical therapy and chemotherapy in Japan have stayed about the same [17]. According to their mechanisms of action, anticancer drugs are mainly classified into alkylating agents, antimetabolites, hormone antagonists, cytotoxic antibiotics, antimitotics, cytotoxic quinolones, and topoisomerase inhibitors. Because all of these anticancer drugs have physiological activity and are highly cytostatic, there are many concerns about their cytostatic effects on aquatic ecosystems and on organisms living in the aquatic environments [12,18–20]. In fact, an anticancer drug, tamoxifen (TAM), inhibited the reproduction and growth of Daphnia at 120 ng/L [21] and showed a predicted no-effect concentration of 81 ng/L for fish, plankton, and algae [22]. In addition, anticancer drugs are present in the sediments in river environments. Therefore, serious pollution problems sometimes arise from contaminated river water because of the exposure of benthonic organisms and bioaccumulation in predators such as fish along the ecological chain through predation [23,24]. The sedimented substances affect not only river environments, but also marine environments, and humans are at risk when they eat fish polluted with them through bioaccumulation [25–27]. At present, the pollution aspect of anticancer drugs in Japan has been analyzed only in the very limited area surrounding the Yodo River since 2009 [13,28–31]. Their occurrence in the river water and sediments, including from hospital and sewage treatment effluents [13,28,32], their fate after discharge [31], and their attenuation properties [29,30], were reported in a separate fashion. The time has come to make an overview of the status of anticancer drugs in the environmental water of the Yodo River basin. The aim of this article is summarize the state of anticancer drugs in the regional river water and sediments in the subcatchment of the Yodo River basin in Japan, providing an invaluable fundamental basis for further spreading of the related studies into a wide range of PPCPs across a wide area to achieve the final goal for conducting effective environmental risk assessments of discharged PPCPs in the future.

2. Materials and Methods

2.1. Sampling of Environmental Waters and Sediments The question of primary importance is of how to select the sampling field to determine the distribution of pharmaceuticals in the environmental waters. For this purpose, considering the spreading out of the geographical region to core cities throughout Japan, the sampling areas in the Kansai district of Japan were selected; the locations were on the right bank of the middle-to-downstream region of the Yodo River [32] and on two other rivers, the Kanzaki and the Ai, and their tributaries. This area, known as the Kanzaki–Ai River basin, covers an important commercial and urban area of about 790 km2 in Osaka and Hyogo prefectures and is home to 2 million people [33,34]. To collect three different types of waters (river, tributary, and sewage treatment plant (STP)), 13 sampling sites consisting of six river sites (R1 to R6), four tributary sites (T1 to T4), and three STP sites (S1 to S3) (Figure1) were set in the Kanzaki–Ai River basin. The sampling site at the Suita Bridge (R5) was set as the farthest downstream boundary. One sample was basically taken per site, but two Appl. Sci. 2018, 8, 2043 3 of 17 effluents, S3(1) and S3(2), were sampled at S3, compiling 14 samples per each sampling time. Names of theAppl. sampling Sci. 2018, sites8, x FOR were PEER used REVIEW for identification (ID) of the samples. A conventional activated3 of 19 sludge (CAS)time. process Names followed of the sampling by chlorination sites were for used disinfection for identification was used (ID) in of all the STPs samples. except A S3 conventional where ozonation (8.6 mg/Lactivated ozone) sludge was (CAS) used processafter partial followed CAS. by The chlorination properties for of disinfection the STPs including was used treatment in all STPs process are shownexcept inS3 Tablewhere1 ozonation[ 35]. Annual (8.6 mg/L flow ozone) rates was and used BOD after (biological partial CAS. oxygen The properties demand, of th mg/L)e STPs at the samplingincluding sites in treatment the Kanzaki–Ai process are River shown basin in are Table listed 1 [35 in] Table. Annual2[ 30 flow,36 ]. rates Stainless-steel and BOD (biological pails were used to collectoxygen water demand, samples, mg/L) while at the a stainless-steel sampling sites in bottom the Kanzaki sampler–Ai was River used basin for are river listed sediment in Table samples 2 collected[30,36 at]. R5 Stainless (Suita-steel Bridge) pails and were R6 used (Hirakata to collect Bridge). water samples, All samples while were a stainless transferred-steel bottom in separate sampler was used for river sediment samples collected at R5 (Suita Bridge) and R6 (Hirakata glass bottles, transported to the laboratory within 2 h and kept at 4 ◦C under dark. Analysis of the Bridge). All samples were transferred in separate glass bottles, transported to the laboratory within concentration2 h and kept of theat 4 target°C under anticancer dark. Analysis drugs of in the each concentration sample was of the started target within anticancer 24 h drugs after in collection each by filtrationsample through was started a GF/B within glass 24 fiber h after filter collection (pore size, by filtration 1-µm) for through separation a GF/B of glass liquid fiber from filter the (pore suspended solidssize, [37 ].1-μm) for separation of liquid from the suspended solids [37]. The surveyingThe surveying anticancer anticancer drugsdrugs was was conducted conducted once once in the in four the seasons four seasonsin 2013 and in 2014; 2013 on and 4 2014; on 4 AprilApril (spring), (spring), 29 29 July July (summer), (summer), 18 18 December December (late (late autumn) autumn),, and and 4 February 4 February (winter). (winter). Sampling Sampling days weredays were selected selected on rain-lesson rain-less days days accompanied accompanied by by 22 mo morere ahead ahead fine fine days days (rainfall (rainfall ≤ 1 mm)≤ 1 [38 mm)]. [38].

Ai River

Taishou River Yamada River R1

S1 Yodo River Shojaku River

T1 S2 T2 STP effluent R2 T4 T3 Main stream R5 Tributary R4 R3 Flow Kanzaki River 0 1 km 3 km 0 200 km 400 km

FigureFigure 1. Locations 1. Locations of of sampling sampling sites in in the the Kanzaki Kanzaki–Ai–Ai River River basin basin (reproduced (reproduced from [ from30]). [30]). (Information(Information of the of the sampling sampling sites sites of of S1–S3 S1–S3 are shown shown in in Table Table 1, 1while, while those those of a ofcombined a combined group groupof of R1–R6R1 and–R6 T1–T4and T1– areT4 are shown shown in in Table Table2.). 2.).

TableTable 1. Information 1. Information of sewage of sewage treatment treatment plants plants (STPs) (STPs) located located in the in Kanzaki–Ai the Kanzaki– RiverAi River basin basin (Figure 1) (reproduced(Figure 1) from (reproduced the data from in [ 30the]). data in [30]).

Service ServiceService PopulationFlow RateFlow Rate (m3/day) Sample-ID Service Area (ha) 3 Treatment Process Sample-ID Area Population(Person) (m /day)Mean Treatment SD Process (ha) (person) Mean SD CAS + Chlorine disinfection S1 5459 494,974 256,110CAS 31,285+ Chlorine disinfection S1 5,459 494,974 256,110 31,285 A2O + Chlorine A2O + Chlorine disinfection S2 453 50,732 17,050 2,355 CAS + Chlorine disinfectionCAS + Chlorine S2 453 50,732 17,050 2355 disinfection CAS + Chlorine disinfection CAS + Chlorine S3(1) 3,550 415,364 128,497 11,876 Step AO + Chlorinedisinfection S3(1) 3550 415,364 128,497disinfection 11,876 Step AO + Chlorine S3(2) 2,152 18 CAS + Ozonationdisinfection Step AO + OzonationCAS + Ozonation S3(2)CAS: Conventional activated sludge; AO: Anaerobic/aerobic; 2152 A2O: Anaerobic/anoxic/aerobic. 18 Step AO + Ozonation CAS: Conventional activated sludge; AO: Anaerobic/aerobic; A2O: Anaerobic/anoxic/aerobic. Appl. Sci. 2018, 8, x FOR PEER REVIEW 4 of 19 Appl.Appl. Sci. Sci. 2018 2018, 8,, ,8 x,, xxFOR FORFOR PEER PEERPEER REVIEW REVIEWREVIEW 4 4of of 19 19 Appl. Sci. 2018, 8, 2043 4 of 17

TableTable 2 2. .Information. InformationInformation of ofof flow flowflow rate raterate and andand biological biologicalbiological oxygen oxygenoxygen demand demanddemand (BOD) (BOD)(BOD) values valuesvalues at atat the thethe sampling samplingsampling sites sitessites ininin the thethe Kanzaki KanzakiKanzaki––AiAi River River basin basin (Figure (Figure 1) 1) (reproduced (reproduced(reproduced from fromfrom the thethe data datadata in inin [ 30[[30]).]]).). Table 2. Information of flow rate and biological oxygen demand (BOD) values at the sampling sites in 3 Flow Rate (m3/day)3 the Kanzaki–Ai River basin (Figure1) (reproduced from the dataFlowFlow in Rate Rate [30 (m]). (m(m/day)3/day)/day) BODBOD SampleSample-ID-ID BasinBasin ClassClass Sample-ID Basin Class (mg/L) MeanMean SDSD (mg/L)(mg/L)(mg/L) Flow Rate (m3/day) Sample-ID Basin BOD (mg/L) R1R1 AiAi ClassMainMain stream stream 7,3117,311 5,7105,710 1.21.2 Mean SD T1T1 TributaryTributary 27,41527,415 19,87219,872 1.61.6 R1T1 Ai MainTributary stream 731127,415 571019,872 1.6 1.2 T1T2T2 TributaryTributaryTributary 27,4155,7515,751 19,87211,99511,995 4.34.3 1.6 T2 Tributary 5751 11,995 4.3 R2R2 MainMain stream stream 546,352546,352 245,310245,310 1.51.5 R2R2 MainMain stream stream 546,352546,352 245,310245,310 1.5 1.5 R3R3 KanzakiKanzaki MainMain stream stream 1,180,8001,180,800 132,832132,832 N.A.N.A. R3R3R3 Kanzaki KanzakiKanzaki Main MainMain stream stream stream 1,180,8001,180,8001,180,800 132,832132,832132,832 N.A.N.A. R4R4R4 MainMainMain stream stream stream 1,379,4281,379,1,379,428428 88,64788,64788,647 1.01.0 1.0 T3 Tributary N.A. N.A. N.A. T3T3 TributaryTributary N.A.N.A. N.A.N.A. N.A.N.A. T4T3T3 TributaryTributaryTributary 198,627N.A.N.A. 78,298N.A.N.A. N.A.N.A. 3.2 R5T4T4 MainTributaryTributary stream 1,925,780198,627198,627 286,90378,29878,298 3.23.2 1.7 R6 Yodo Main stream 17,815,523 8,742,816 1.1 R5R5 MainMain stream stream 1,925,7801,925,780 286,903286,903 1.71.7 N.A.: not available. R6R6 YodoYodo MainMain stream stream 17,815,52317,815,523 8,742,8168,742,816 1.11.1 N.A.:N.A.: not not available available 2.2. Selection of Anticancer Drugs and Their Quantification 2.2.2.2. Selection Selection of of A Anticancernticancer Drugs Drugs and and Their Their Quantification Quantification With consideration of their highly frequent therapeutic use in Japan and high excretion rates in WithWith consi considerationderation of of their their highly highly frequent frequent therapeutic therapeutic use use in in Japan Japan and and high high excretion excretion rates rates in in unchanged form [39,40], this article focused on the following six anticancer drugs listed in Table3. unchangedunchanged form form [ 39[39,40,,40],] ,,this thisthis article articlearticle focused focusedfocused on onon the thethe following followingfollowing six sixsix anticancer anticanceranticancer drugs drugsdrugs listed listedlisted in inin Table TableTable 3. 3.3. BicalutamideBicalutamideBicalutamide (BLT) is an(BLT) (BLT) active is is an an antiandrogen active active antiandrogen antiandrogen medication medication medication used used used to to to treatto treat treattreat prostateprostate prostateprostate cancer. cancer. Capecitabine CapecitabineCapecitabine Capecitabine (CAP) is a chemotherapy(CAP)(CAP) is is a a chemotherapy chemotherapy medication medication medication used to used treat used to breast to treat treat cancer, breast breast cancer, cancer,gastric gastric gastric cancer, cancer, cancer, and colorectal and and colorectal colorectal cancer. Cyclophosphamidecancer.cancer. Cyclophosphamide Cyclophosphamide (CP) is a chemotherapy (CP) (CP) is is a a chemotherapy chemotherapy medication medication medication used to treatused used to ovarian to treat treat ovarian ovarian cancer, cancer, cancer, breast breast breast cancer, cancer, and small cell lung cancer. Doxifluridine (DFUR) is a chemotherapy medication used to and small cellcancer,cancer, lung and and cancer. small small Doxifluridine cell cell lun lungg cancer. cancer. (DFUR) Doxifluridine Doxifluridine is a chemotherapy (DFUR) (DFUR) is is a a chemotherapy chemotherapy medication medication medication used to treat used used gastric to to treattreat gastric gastric cancer, cancer, intestinal intestinal cancer, cancer, and and breast breast cancer. cancer. TAM TAM is is a a medication medication used used to to treat treat breast breast cancer, intestinaltreattreat gastric gastric cancer, cancer, cancer, and intestinal breastintestinal cancer. cancer, cancer, TAMand and breast breast is a medicationcancer. cancer. TAM TAM usedis is a amedication medication to treat breast used used to cancer.to treat treat breast breast Tegafur cancer.cancer. Tegafur Tegafur (TGF) (TGF) is is a a chemotherapeutic chemotherapeutic prodrug prodrug of of 5 5-fluorouracil-fluorouracil and and is is used used to to tr treateat various various (TGF) is a chemotherapeutic prodrug of 5-fluorouracil and is used to treat various types of cancer. typestypestypes of ofof cancer. cancer.cancer. Once OnceOnce these thesethese anticancer anticanceranticancer drugs drugsdrugs are areare discharged discharged in inin the thethe environment, environment,environment, their theirtheir distribution distributiondistribution Once thesewill anticancerwill be be affected affected drugs by by theirare their discharged individual individual physicochemical in physicochemical the environment, propert propert theiries;ies;ies; of of distribution these, these, surface surface will charge charge be affected due due to to by differences in pKa, pH, and hydrophobic properties estimable from logP were of importance to their individualdifferencesdifferences physicochemical in in p pKKa,aa ,, pH, pH, pH, and and and properties; hydrophobic hydrophobic hydrophobic of properti these, properti properti surfaceeses estimable estimable charge from from due log logP toP were differenceswere of of importance importance in pK a to, to pH, and hydrophobicestablishestablish properties their their solubility solubility estimable and and degree degree from of of log adsorption adsorptionP were ofonto onto importance organic organic matters matters to establish and and sedimented sedimented their solubility materials. materials. and The properties of the target anticancer drugs are summarized in Table 3. degree of adsorptionTheThe properties properties onto of of the the organic target targettarget anticancer mattersanticancer anddrugs drugs sedimented are are summarized summarized materials. in in Table Table 3. 3. The properties of the target anticancer drugs are summarized in Table3. TableTable 3. 3. Details Details of of the the t argettarget anticancer anticancer drugs drugs typified typified by by their their action action mechanisms mechanisms (reconstructed (reconstructed(reconstructed basedbased on on the the data data listed listed in in [ 41[[41]).]]).). Table 3. Details of the target anticancer drugs typified by their action mechanisms (reconstructed based CASCAS MolecularMolecular CAS Molecular Molecular on the data listed in [41]). MolecularMolecular Compound Registry Mass Structure pKa logP Action Mechanism CompoundCompound RegistryRegistry MassMass StructureStructure ppKKa aa logllogPP ActionAction Mechanism Mechanism FormulaFormula CAS RegistryNumber MolecularFormula Molecular(g/mol) Action Compound NumberNumber (g/mol)(g/mol)(g/mol) Structure pK logP Number Formula Mass (g/mol) a Mechanism Bicalutamide BicalutamideBicalutamide 90357-06-5 C18H14F4N2O4S 430.4 11.5 4.1 Antiandrogens Bicalutamide 9035790357-06-06-5- 5 CC1818HH1414FF4N4N2O2O4S4 S 430.4430.4 11.511.5 4.14.1 AntiandroAntiandrogensgens (BLT) 90357-06-590357-06C-185 H14CF184NH214OF44NS2O4S 430.4430.4 11.511.5 4.1 4.1 AntiandrogensAntiandrogens (BLT) (BLT)(BLT)(BLT) Tamoxifen TamoxifenTamoxifenTamoxifen 10540-29-1 C26H29NO 371.5 8.7 5.1 Antiestrogens 10540-29-11054010540-29-29- C1- 126 H29CC26NO26HH2929NONO 371.5371.5371.5 8.78.78.7 5.15.15.1 AntiestrogensAntiestrogensAntiestrogens (TAM)(TAM) 10540-29-1 C26H29NO 371.5 8.7 5.1 Antiestrogens (TAM)(TAM)(TAM) Cyclophosphamide Nitrogen mustard CyclophosphamideCyclophosphamide NitrogenNitrogenNitrogen mustard mustard Cyclophosphamide 50-18-0 C7H15Cl2N2O2P 261.1 2.8 0.2 50-18-05050-18--18-0-- C0 H CClC7H77H15N15Cl15ClO2N22N2PO22O2P22P 261.1261.1261.1 2.82.82.8 0.20.20.2 mustard (CP) (CP)(CP) 7 15 2 2 2 analoguesanalogues (CP) analoguesanalogues Capecitabine Pyrimidine CapecitabineCapecitabine PyrimidinePyrimidine Appl.Appl. Sci. Sci. 2018 2018, ,8 8, ,x x FOR FOR154361 PEER PEER-50 REVIEW REVIEW-9 C 15 H 22FN3O6 359.4 5.4 1.0 55 of of 19 19 Capecitabine 154361154361-50-50-9- 9 CC1515HH2222FNFN3O3O6 6 359.4359.4 5.45.4 1.01.0 Pyrimidine (CAP) 154361-50-9154361-50 C-159 H22CFN15H322OFN6 3O6 359.4359.4 5.45.4 1.0 1.0 analogues (CAP) (CAP)(CAP)(CAP) analoguesanaloguesanalogues DoxifluridineDoxifluridine PyrimidinePyrimidine Doxifluridine 3094-09-5 C9H11FN2O5 246.2 7.6 -0.7 Pyrimidine 3094-09-53094-09 C-59 H11FNC9H2O11FN5 2O5 246.2246.2 7.67.6 -0.7−0.7 (DFUR)(DFUR)(DFUR) analoguesanaloguesanalogues

TegafurTegafur PyrimidinePyrimidinePyrimidine Tegafur (TGF) 17902-23-71790217902--2323 C--787 H 9FNCC88H2HO99FNFN3 22OO3 3 200.2200.2200.2 7.67.67.6 --0.60.6− 0.6 (TGF)(TGF) analoguesanaloguesanalogues K P CAS: chemicalCAS:CAS: chemical chemical abstracts abstracts abstracts service; service; service; p a p :pKKaa: :logarithmiclogarithmic logarithmic acid acid acid dissociation dissociation dissociation constant; constant; constant; llogogPP: :octanol octanol log :--waterwater octanol-water partition partition partition coefﬁcients. coefficoefficientscients

ForFor quantitative quantitative analysis analysis of of CP CP and and TAM, TAM, gas gas chromatography chromatography (GC) (GC) combined combined with with mass mass spectrometryspectrometry (MS)(MS) waswas usedused initiallyinitially afterafter purificationpurification andand derivatizationderivatization [42[42––44]44].. RecentRecent inin--depthdepth quantificationquantification of of the thesese drugs drugs together together with with the the other other anticancer anticancer drugs drugs was was achieved achieved by by the the simultaneoussimultaneous combination combination of of procedures procedures known known as as solid solid--phasephase extraction extraction (SPE) (SPE) and and liquid liquid chromatographychromatography––massmass spectrometryspectrometry (LC(LC--MS/MS)MS/MS) [16,45[16,45––47]47],, withwith specialspecial carecare takentaken forfor differencesdifferences inin the the protocols protocols applied applied for for the the liquid liquid and and the the solid solid samples. samples. The The concentration concentration and and purification purification stepssteps ofof thethe anticanceranticancer drugsdrugs inin thethe liquidliquid samplessamples werewere performedperformed byby SPESPE [[1313,,3131]].. IInn thethe casecase ofof thethe riverriver sedimentssediments andand thethe suspendedsuspended solidssolids (solid(solid statestate samples),samples), solventsolvent extractionextraction ofof thethe adsorbedadsorbed materialsmaterials waswas achievedachieved byby sonicationsonication andand filtrationfiltration [[3131,,4848,,4949]] priorprior toto analysisanalysis.. TheThe finalfinal stepstep ofof measurementmeasurement waswas toto separateseparate andand quantifyquantify thethe targettarget pharmaceuticalspharmaceuticals byby thethe LCLC--MS/MSMS/MS systemsystem equippedequipped withwith anan appropriateappropriate PCPC forfor regulationregulation andand calculation.calculation. TheThe optimizedoptimized MS/MSMS/MS parameters parameters are are summarized summarized i inn Table Table 4. 4. TheThe cone cone voltages voltages for for detection detection of of the the hormone hormone antagonistsantagonists (BLT(BLT andand TAM)TAM) werewere somewhatsomewhat higherhigher thanthan the the otherother anticanceranticancer drugs, drugs, whilewhile lowerlower conecone voltagesvoltages werewere adequateadequate forfor thethe analysisanalysis ofof thethe antimetabolitesantimetabolites (CAP,(CAP, DFUR,DFUR, andand TGF),TGF), whichwhich havehave similsimilarar pyrimidinepyrimidine--analogousanalogous structures.structures. QuantificationQuantification ofof thethe anticanceranticancer drugsdrugs waswas donedone byby subtractingsubtracting thethe blankblank datadata fromfrom thethe datadata givengiven by by the the spiked spiked sample sample solutions solutions for for accounting accounting matrix matrix effects effects and and loss loss during during sample sample extractionextraction [[3030,,5050]].. Similarly,Similarly, recoveryrecovery ratesrates werewere calculatedcalculated fromfrom thethe deviationsdeviations betweenbetween thethe spikedspiked datadata andand thethe standardstandard datadata toto performperform calibration.calibration. RecoveryRecovery ratesrates variedvaried inin thethe rangerange ofof 6363––124%124% forfor riverriver water,water, 5252––116%116% forfor STPSTP effluent,effluent, 2323––11112%2% forfor riverriver sediment,sediment, andand 3333––122%122% forfor suspendedsuspended solids.solids. TheseThese valuesvalues werewere mostlymostly similarsimilar toto thethe valuesvalues previouslypreviously reportedreported forfor pharmaceuticalspharmaceuticals inin riverriver andand sewagesewage samplessamples [[4848,,5151]].. TheThe valesvales ofof limitlimit ofof detectiondetection (LOD)(LOD) andand limitlimit ofof quantificationquantification (LOQ),(LOQ), whichwhich areare importantimportant forfor estimatingestimating thethe sensitivitysensitivity ofof thethe methods,methods, werewere calculatedcalculated basedbased onon thethe concentrationsconcentrations atat signalsignal--toto--noisenoise ratiosratios ofof 33 andand 1010 [[5252,,5353]].. TheThe estimatedestimated LODLOD andand LOQLOQ valuesvalues forfor liquidliquid samplessamples werewere inin rangrangeses ofof 0.10.1––0.40.4 andand 0.30.3––1.41.4 ng/L,ng/L, respectively,respectively, butbut thethe correspondingcorresponding valuesvalues forfor solidsolid samplessamples appearedappeared inin largerlarger rangesranges ofof 2.42.4––1313 andand 8.28.2––4242 ng/kg,ng/kg, respectivelyrespectively..

TableTable 4 4. .LC LC--MS/MSMS/MS parameters parameters for for the the target target anticancer anticancer drugs drugs (re (reproducedproduced from from [ [3030]]).).

RetentionRetention PrecursorPrecursor ConeCone CollisionCollision ProductProduct Ion Ion IonizationIonization ComCompoundpound TimeTime IonIon VoltageVoltage EnergyEnergy ((m/zm/z)) ModeMode (min)(min) ((m/zm/z)) (V)(V) (eV)(eV)

BicalutamideBicalutamide (BLT) (BLT) 14.814.8 429.3429.3 255.2255.2 3030 1616 −−

TamoxifenTamoxifen (TAM) (TAM) 17.917.9 372.4372.4 72.372.3 4545 1515 ++

CyclophosphamideCyclophosphamide 10.210.2 261.2261.2 106.2,106.2,139.9139.9,181.,181.9,233.49,233.4 3535 1515 ++ (CP)(CP)

CapecitabineCapecitabine (CAP) (CAP) 12.412.4 360.4360.4 174.2,174.2,244.2244.2 2525 1616 ++

DoxifluridineDoxifluridine 2.02.0 247.2247.2 73.0,99.1,73.0,99.1,117.0117.0 1515 1212 ++ (DFUR)(DFUR)

TegafurTegafur (TGF) (TGF) 2.82.8 201.2201.2 71.071.0,131.1,131.1 1515 1818 ++ Appl. Sci. 2018, 8, 2043 5 of 17

For quantitative analysis of CP and TAM, gas chromatography (GC) combined with mass spectrometry (MS) was used initially after purification and derivatization [42–44]. Recent in-depth quantification of these drugs together with the other anticancer drugs was achieved by the simultaneous combination of procedures known as solid-phase extraction (SPE) and liquid chromatography–mass spectrometry (LC-MS/MS) [16,45–47], with special care taken for differences in the protocols applied for the liquid and the solid samples. The concentration and purification steps of the anticancer drugs in the liquid samples were performed by SPE [13,31]. In the case of the river sediments and the suspended solids (solid state samples), solvent extraction of the adsorbed materials was achieved by sonication and filtration [31,48,49] prior to analysis. The final step of measurement was to separate and quantify the target pharmaceuticals by the LC-MS/MS system equipped with an appropriate PC for regulation and calculation. The optimized MS/MS parameters are summarized in Table4. The cone voltages for detection of the hormone antagonists (BLT and TAM) were somewhat higher than the other anticancer drugs, while lower cone voltages were adequate for the analysis of the antimetabolites (CAP, DFUR, and TGF), which have similar pyrimidine-analogous structures.

Table 4. LC-MS/MS parameters for the target anticancer drugs (reproduced from [30]).

Retention Precursor Product Ion Cone Collision Ionization Compound Time (min) Ion (m/z) (m/z) Voltage (V) Energy (eV) Mode Bicalutamide 14.8 429.3 255.2 30 16 − (BLT) Tamoxifen (TAM) 17.9 372.4 72.3 45 15 + Cyclophosphamide 106.2, 139.9, 10.2 261.2 35 15 + (CP) 181.9, 233.4 Capecitabine 12.4 360.4 174.2, 244.2 25 16 + (CAP) Doxiﬂuridine 2.0 247.2 73.0, 99.1, 117.0 15 12 + (DFUR) Tegafur (TGF) 2.8 201.2 71.0, 131.1 15 18 + Product ions in italics were used for quantiﬁcation.

Quantification of the anticancer drugs was done by subtracting the blank data from the data given by the spiked sample solutions for accounting matrix effects and loss during sample extraction [30,50]. Similarly, recovery rates were calculated from the deviations between the spiked data and the standard data to perform calibration. Recovery rates varied in the range of 63–124% for river water, 52–116% for STP effluent, 23–112% for river sediment, and 33–122% for suspended solids. These values were mostly similar to the values previously reported for pharmaceuticals in river and sewage samples [48,51]. The vales of limit of detection (LOD) and limit of quantification (LOQ), which are important for estimating the sensitivity of the methods, were calculated based on the concentrations at signal-to-noise ratios of 3 and 10 [52,53]. The estimated LOD and LOQ values for liquid samples were in ranges of 0.1–0.4 and 0.3–1.4 ng/L, respectively, but the corresponding values for solid samples appeared in larger ranges of 2.4–13 and 8.2–42 ng/kg, respectively.

2.3. Estimation of Sorption Distribution Coefﬁcient (LogKd) and Mass Balance

The sorption distribution coefficients (logKd) between the liquid samples and the solid samples were determined as log(Cs/Cw) in accordance with the previous reports [54,55], where Cs (ng/kg) is the concentration of pharmaceuticals in the solid samples and Cw (ng/L) is the concentration of pharmaceuticals in the liquid samples. Experimental sorption of the target anticancer drugs onto the river sediments was done separately by following the procedure as described previously [56–58] as well as OECD guideline No. 106 [59]. Sediment samples were suspended in ammonium acetate buffer (pH 7) containing a known amount of the anticancer drugs (0–200 µg/L), and the mixtures were shaken reciprocally for 24 h at 20 ◦C in the Appl. Sci. 2018, 8, 2043 6 of 17 dark to prevent photolysis [56,57]. After incubation, each solution was recovered by filtration through a GD/X glass fiber filter and the concentrations of the anticancer drugs were measured by LC-MS/MS. In the cases for the experimental sorption, the logKd values for the river sediment were determined from the slope of the linear regression lines produced by the initial and equilibrated concentrations in the dissolved phase and the dry weight of the adsorbent [24,60,61]. For estimation of the mass balance of the target anticancer drugs discharged into the Kanzaki–Ai River basin, the mass flux (g/day) of each anticancer drug at each site was calculated by multiplying the detected concentration by the mean river flow rate or the mean STP discharge rate in terms of m3/day. The flow rates at the sampling sites are listed in Tables1 and2. Total mass flux for each drug was calculated by numerical summation of the mass flux values from the upstream region to the farthest downstream boundary site at the Suita Bridge (R5). The mass balance of each drug was then estimated as a percentage of the mass flux for that drug at this boundary site.

3. Results and Discussion

3.1. Distribution of Anticancer Drugs in River Waters and STP Effluents Table5 summarized the detected concentrations of the target anticancer drugs. All anticancer drugs were present in both the river waters and the STP effluents [30]. The median concentrations of BLT, TAM, CP, CAP, DFUR, and TGF were 32 ng/L, N.D., 2 ng/L, 2 ng/L, N.D., and N.D., respectively, in the main stream samples, 30 ng/L, N.D., 3 ng/L, 1 ng/L, N.D., and N.D., respectively, in the tributaries, and 245 ng/L, N.D., 10 ng/L, 6 ng/L, N.D., and 23 ng/L, respectively, in the STP effluents (excluding the ozonation STP). The concentrations of BLT, CP, CAP, and TGF in the STP effluents were thus several times higher than those in the river waters. In the previous studies, CP and TAM were detected in the range of N.D. to several tens of ng/L in river water [12,45,62,63] and from N.D. to 100 ng/L in the STP effluent [12,19,47,63–65]. On the other hand, in the case of BLT, which is frequently used to treat prostate cancer [66], the maximum concentrations were about 2–10-fold higher than the concentrations of the other drugs: 254 ng/L in main stream samples, 151 ng/L in tributaries, and 1032 ng/L in STP effluents (excluding ozonation). Detection frequencies in the main stream and tributary samples were quite high (83–100%) for BLT and CAP, but low—in the range of 6–44%—for DFUR, TAM, and TGF. The corresponding values for CP were moderate (56–63%). In the cases of TAM and DFUR, their detected concentrations appreciably decreased in the STP effluents. This indicates easiness of degradation of these anticancer drugs by the usual treatment at STPs. Although concentration differences were detected among the seasons, the orders were about the same throughout the year. In addition, the quantities of water to be treated at these STPs and the river flow rates in the target basin were fairly stable throughout the year [36]. Consequently, the data shown in this article suggest that the target six anticancer drugs were being used all year round. The concentrations of the anticancer drugs detected in the STP effluents (BLT, CP, CAP, and TGF) tended to be several times higher than those in the river waters. Clarification of the levels and mass balances of all discharged anticancer drugs in the urban river environment, together with the optimization of clean-up treatments at STPs, will be helpful in maintaining the health of residents in the sampling area. In the effluent samples from the STP that used ozonation, the mean concentrations of all anticancer drugs ranged as low as from N.D. to several ng/L, which were roughly one-tenth to one-hundredth of the concentrations detected in the effluents from STPs with chlorination after biological treatment (Table5). This kind of observation was in accord with those of the previous studies [67–69], indicating the effectiveness of ozonation treatment for removing a wide range of pharmaceutical compounds, including anticancer drugs from water samples. Appl. Sci. 2018, 8, 2043 7 of 17

Table 5. Detection of the target anticancer drugs in river waters and STP effluents (n = 24 (main stream), n = 16 (tributary), n = 10 (STP effluent), n = 10 (STP effluent—ozonation)) (reproduced from [30]).

Sample Concentration (ng/L) Frequency Compound Type Mean (SD) Median Max Min (%) Bicalutamide Main stream 55 (71) 32 254 N.D. 83 (BLT) Tributary 46 (43) 30 151 N.D. 94 STP effluent 316 (303) 245 1032 49 100 STP effluent (ozonation) 13 (20) 5 41 N.D. 50 Tamoxifen Main stream 5 (16) N.D. 76 N.D. 33 (TAM) Tributary 8 (12) N.D. 33 N.D. 44 STP effluent 1 (3) N.D. 9 N.D. 10 STP effluent (ozonation) N.D. (0) N.D. N.D. N.D. 0 Main stream 3 (5) 2 16 N.D. 63 Cyclophosphamide Tributary 4 (6) 3 20 N.D. 56 (CP) STP effluent 11 (7) 10 20 N.D. 90 STP effluent (ozonation) 7 (10) 3 22 N.D. 50 Capecitabine STP effluent 3 (4) 2 20 N.D. 88 (CAP) Tributary 3 (4) 1 16 N.D. 100 STP effluent 6 (3) 6 11 2 100 STP effluent (ozonation) 2 (2) 2 4 N.D. 50 Doxifluridine Main stream 2 (8) N.D. 39 N.D. 8 (DFUR) Tributary 1 (3) N.D. 12 N.D. 6 STP effluent 1 (3) N.D. 8 N.D. 20 STP effluent (ozonation) N.D. (0) N.D. N.D. N.D. 0 Tegafur Main stream 5 (13) N.D. 56 N.D. 25 (TGF) Tributary 6 (12) N.D. 35 N.D. 25 STP effluent 20 (16) 23 49 N.D. 70 STP effluent (ozonation) 4 (8) N.D. 17 N.D. 25 N.D.: Not detected.

3.2. Allocation of Anticancer Drugs in the Sediment and Suspended Solid Samples The occurrences of anticancer drugs in the solid state samples (river sediments and suspended solids) at Suita Bridge (R5) and Hirakata Bridge (R6) are summarized in Figure2[ 31]. Three anticancer drugs (BLT, TAM, and CAP) were detected at appreciably higher concentrations in the suspended solids at 628, 13–658, and 231 µg/kg, respectively, with higher levels at the Hirakata Bridge than at the Suita Bridge. In the river sediments, however, only lower levels of the same two anticancer drugs (BLT and TAM) and DFUR were detected at 391, 42–250, and 392 ng/kg, respectively, with no clear difference between both of the sites. These profiles indicate an abundance of particles which have high affinity to the anticancer drugs in the river water. However, the concentration of the suspended solids at the Hirakata Bridge (2.6 mg) was about 30% of that of the Suita Bridge (9.0 mg). Based on these results, the pollution load of the anticancer drugs originating from the suspended solids was concluded to be not very large. Localization of DFUR and CAP in the different solid samples is attributable to the difference in the affinity of these drugs to the particles present in the samples. The sorption property of the present anticancer drugs on the river sediments was further characterized by a sorption experiment [31]. The measured logKd values varied in a range from −0.4 to 2.1 (Table6). The actual log Kd values of the individual anticancer drugs in the sediments at the Hirakata Bridge and the Suita Bridge were 0.4 and 1.4 (BLT), 2.1 and 1.6 (TAM), 0.8 and 0.6 (CP), −0.4 and 0.1 (CAP), 0.9 and 1.5 (DFUR), and 1.3 and 0.4 (TGF), respectively. The concentrations of the anticancer drugs at the Suita Bridge showed a tendency to become higher than those at the Hirakata Bridge. This result is attributable to differences in the particle types in the sediment: sandy sediment at the Hirakata Bridge (moisture content of 9% with 79% sand, 3% silt, and 0% clay) and silty sediment at the Suita Bridge (moisture content of 49%, but no available data for its composition). Similar observation has also been reported in previous studies dealt with different pharmaceuticals [60,67]. Appl. Sci. 2018, 8, x FOR PEER REVIEW 8 of 19

STP effluent 20 (16) 23 49 N.D. 70 STP effluent 4 (8) N.D. 17 N.D. 25 (ozonation) N.D.: Not detected

101.E+04 4 1.E+09 Sediment HiHirakataohashi rakata ohas hi SS SS (Hirakata Bridge) 101.E+03 3 SuiSuitaohashi taoh ashi SS SS Suspended solids HiHirakataohashi rakata ohas hi Sedi Sediment men t 1.E+09 (Hirakata Bridge) g/kg) 2

m 101.E+02 SuiHiSuitaohashi rakata taoh ashi ohas Sedi hiSediment SS men t

1.E+06 g/kg-dry) Sediment m Sui taoh ashi SS (Suita Bridge) 101.E+01 1 Hi rakata ohas hi Sedi men t Suspended solids Sui taoh ashi Sedi men t 1.E+06 (Suita Bridge) 101.E+00 0 1.E+03 1.E+03 Concentration(

Concentration ( Concentration

Concentration(ng/kg-dry) Concentration(ng/kg-dry) 101.E-01 -1

1.E+03

101.E-02 -2

Concentration(ng/kg-dry) Concentration(ng/kg-dry) 1.E+00

Tegafur

Daidzin

Tegafur

Daidzin

Glycitin

Tegafur

Genistin

Glycitin

Acridine

Caffeine

Puerarin

Genistin

Daidzein

Acridine

Caffeine

Puerarin

Daidzein

Acridone

Glycitein

Genistein

Acridone Glycitein

Tamoxifen

Genistein

Ibuprofen

Tamoxifen

Tamoxifen Crotamiton

Bicalutamide

Capecitabine

Famciclovir

Crotamiton Loxoprofen

Doxifluridine

Famciclovir

Loxoprofen

Bicalutamide

Capecitabine

Ethenzamide

Bicalutamide

Capecitabine

Doxifluridine

Ethenzamide

Doxifluridine

Theophylline

Indomethacin

Theophylline

Azithromycin

Indomethacin

Azithromycin

Carbamazepine

Clarithromycin

Carbamazepine

Clarithromycin Acetaminophen

1.E+00 Acetaminophen

Cyclophosphamide Cyclophosphamide

Cyclophosphamide

Daidzin

Tegafur

Daidzin

Glycitin

Tegafur

Genistin

Glycitin

Acridine

Caffeine

Puerarin

Genistin

Daidzein

Acridine

Caffeine

Puerarin

Daidzein

Acridone

Glycitein

trans-Loxoprofen Alcohol

Genistein

Acridone

Glycitein

2-Hydroxy Carbamazepine

3-Hydroxy Carbamazepine

trans-Loxoprofen Alcohol

Genistein

2-Hydroxy Carbamazepine

3-Hydroxy Carbamazepine Ibuprofen

Figure 2. Distribution of the target anticancerIbuprofen drugs in the river sediments and suspended solids

Tamoxifen

Tamoxifen Crotamiton

Figure 2. Famciclovir

Distribution of the target anticancer drugs inCrotamiton the river sediments and suspended solids

Loxoprofen

Famciclovir

Loxoprofen

Bicalutamide

Capecitabine

Carbamazepine 10,11-epoxide

Ethenzamide

Bicalutamide

Capecitabine

Carbamazepine 10,11-epoxide

Doxifluridine

Ethenzamide

Doxifluridine

Theophylline

Indomethacin

Theophylline

Azithromycin

Indomethacin

Azithromycin

Carbamazepine

Clarithromycin

Carbamazepine Clarithromycin

(abbreviation of each anticancer drugAcetaminophen is shown in Table 1) (reproduced from [31]).

(abbreviation of each anticancer drug isAcetaminophen shown in Table1) (reproduced from [31]).

Cyclophosphamide

trans-Loxoprofen Alcohol 2-Hydroxy Carbamazepine

The sorption property3-Hydroxy Carbamazepine of the present anticancer drugs on the river sediments was further

trans-Loxoprofen Alcohol 2-Hydroxy Carbamazepine

Table 6. Sorption distribution3-Hydroxy coefﬁcients Carbamazepine (logKd) of anticancer drugs for river sediments in sorption Carbamazepine 10,11-epoxide characterized by a sorption experimentCarbamazepine 10,11-epoxide [31]. The measured logKd values varied in a range from −0.4 experiments (reproduced from [31]). to 2.1 (Table 6). The actual logKd values of the individual anticancer drugs in the sediments at the Hirakata Bridge and the Suita Bridge were 0.4 and 1.4 (BLT), 2.1 and 1.6 (TAM), 0.8 and 0.6 (CP), Hirakata Bridge Suita Bridge −0.4 and 0.1 (CAP),Compound 0.9 and 1.5 (DFUR), and 1.3 and 0.4 (TGF), respectively. The concentrations of 2 2 the anticancer drugs at the Suita Bridgelog showedKd (L/kg) a tendencyr to log becomeKd (L/kg) higher thanr those at the Hirakata Bridge.Bicalutamide This result is (BLT) attributable to differences 0.4 in 0.98 the particle 1.4types in the 0.85sediment: sandy sediment at theTamoxifen Hirakata Bridge (TAM) (moisture content 2.1 of 9% with 0.99 79% sand, 1.6 3% silt, and 0.99 0% clay) and silty sediment at the Suita Bridge (moisture content of 49%, but no available data for its Cyclophosphamide (CP) 0.8 0.99 0.6 0.99 Capecitabine (CAP) −0.4 0.99 0.1 0.99 Doxiﬂuridine (DFUR) 0.9 0.99 1.5 0.97 Tegafur (TGF) 1.3 0.99 0.4 0.86

These observations suggest that the anticancer drugs present in the river water environment were mainly distributed in the liquid phase. The major reason of this biased view could be ascribed to the difference in their octanol–water partition coefﬁcients, logKOW (logP) values [68], which ranged from −0.7 to 5.1 (Table1). However, the overall results suggest that not only the log P values but also the electric charge and its density (associated with the functional groups in the anticancer drugs) participate as factors which determine the degree of adsorption onto the particles [37,69]. When the logKd values were estimated for the anticancer drugs in the solid state samples, positive values were detected only in the case of BLT; 4.3 for the suspended solids at the Hirakata Bridge, while 0.8 for the river sediments at the Suita Bridge. The value at the Suita Bridge was similar to that obtained by the laboratory experiment for the river sediments at this bridge, suggesting the possibility that the capacity for sorption onto the river sediments could be predicted by estimation. However, the logKd values for the other anticancer drugs whose concentrations were below LOD remained undetermined. This lack of logKd values or abundance of concentrations below LOD was the consequence of attenuation due to photodegradation by sunlight and biodegradation through water ﬂow over time [28,70]. The higher positive value for the suspended solids compared to the sediments was in association with the relatively low abundance of the suspended solids.

3.3. Source Distribution of Anticancer Drugs Based on the data compiled in this article, the major load source distribution of anticancer drugs in the Kanzaki–Ai River basin could be estimated. The amount of the individual anticancer drugs ﬂowing from the upstream region (S3, R6) to the farthest downstream sampling site (R5) was determined. Appl. Sci. 2018, 8, x FOR PEER REVIEW 10 of 19

the target anticancer drugs came from the upstream points surveyed in the main stream [73]. In the Appl. Sci. 2018, 8, 2043 9 of 17 present article, pollution loads might have come from areas beyond the sample collection points, because the Kanzaki River originates from a branch on the right bank of the Yodo River [74]. For this reason, advanced water-processing techniques should be introduced not only at STPs located in The contributionthe middle of and each downstream load source reaches, to as the well total as the mass upstream ﬂux reaches, was thento decrease calculated entire pollution as mass ﬂux (%) (Figure3)[loads30]. and improve the water quality of the Kanzaki–Ai River system.

Appl. Sci. 2018, 8, x FOR PEER REVIEW STP effluent Tributary STPSTPMain effluent effluent Streamstream TributaryTributary STPMainMain effluenteffluent Stream Stream Tributary 10 ofMain 19 Stream 100 100 100 the target anticancer drugs came from the upstream points surveyed in the main stream [73]. In the present article, pollution loads might have come from areas beyond the sample collection points, 80 because80 the Kanzaki 80River originates from80 a branch on the right bank of the Yodo River [74]. For this reason, advanced water-processing techniques should be introduced not only at STPs located in the60 middle and downstream60 reaches, as well60 as the upstream reaches, to decrease entire pollution loads and improve the water quality of the Kanzaki–Ai River system.

Mass fluxMass (%)

Mass flux (%) Mass flux (%) 40 40 Mass flux (%) 40

STP effluent Tributary STPSTPMain effluent effluent Streamstream TributaryTributary STPMainMain effluenteffluent Stream Stream Tributary Main Stream 100 100 100 20 20 20 20

80 80 800 80 0 0 0

60 60 60 Tegafur

Tegafur

Tegafur Tegafur

Tamoxifen

Bicalutamide

Capecitabine

Doxifluridine

Tamoxifen

Capecitabine

Bicalutamide

Levofloxacin

Doxifluridine

Azithromycin

Doxifluridine

Azithromycin

Ciprofloxacin

Carbamazepine

Clarythromycin

Clarythromycin Clarythromycin

Mass fluxMass (%)

Mass flux (%) Mass flux (%) 40 Mass flux (%)

40 40 40 Cyclophosphamide

Cyclophosphamide

Cyclophosphamide Cyclophosphamide Figure 3. SourceFigure 3. distribution Source distribution of anticancer of anticancer drugs drugs in in the the Kanzaki–Ai Kanzaki–Ai River River basin basin (abbreviation (abbreviation of of each 20 anticancer20 each drug anticancer is shown drug20 in is Tableshown1 in) (reproducedTable 1)20 (reproduced from from [30]). [30]).

59, 0 For all0 anticancer drugs0 except TAM, the0 contribution of STP efﬂuents5* as pollutant loading sources was large, amounting about 50–92% of the total load, while the contribution of tributaries was as low as

Ai River Tegafur

Tegafur Tegafur 356 Tegafur in the level of 0.3–2.0%. A typical exampleTamoxifen of these mass ﬂow transitions by using the case of BLT as a

Bicalutamide

Capecitabine

Doxifluridine

Tamoxifen

Capecitabine

Bicalutamide

Levofloxacin

Doxifluridine

Azithromycin

Doxifluridine

Azithromycin

Ciprofloxacin

Carbamazepine Carbamazepine

representative anticancer drug is shown in Figure4[ 30]. Consequently, STP efﬂuent was strengthenedCarbamazepine

Clarythromycin

Clarythromycin Clarythromycin

Taishou River Cyclophosphamide 2

Cyclophosphamide

Cyclophosphamide Cyclophosphamide to be a major contributor to theYamada pollution River of river waters by the target anticancer compounds in the Figure 3. Source distribution of anticancer drugs in the Kanzaki–Ai River basin (abbreviation of surveyed area. each anticancer drug is shown in Table 1) (reproduced56 from [30]). Yodo River Shojaku River 0.2 1 9 59, 5* STP effluent (n=3) N.A. 25 Ai River Main356 stream (n=4) 54 Tributary (n=4) 62 Taishou River 2 Yamada River Kanzaki River (* Ozonation) 0 1 km 3 km 56 0.2 1 Yodo River Figure 4. TransitionShojaku of massRiver flows (g/day) from upstream to downstream regions in the Kanzaki–Ai River basin for bicalutamide (BLT).9 N.A.: not available (reproduced from [30]). STP effluent (n=3) 3.4. Mass Balance of Anticancer Drugs N.A. 25 Main stream (n=4) The mass balance for each target anticancer drug in the Kanzaki–Ai River basin could further 54 Tributary (n=4) be estimated by calculation62 of percent contribution of total efflux load in the influent load through

Kanzaki River (* Ozonation) 0 1 km 3 km Figure 4.FigureTransition 4. Transition of mass of mass ﬂows flows (g/day) (g/day) fromfrom upstream upstream to downstream to downstream regions regionsin the Kanzaki in the–Ai Kanzaki–Ai River basinRiver for basin bicalutamide for bicalutamide (BLT). (BLT). N.A.: N.A.: not not available (reproduced (reproduced from from[30]). [30]).

3.4. Mass Balance of Anticancer Drugs These results also showed that the contribution of STP effluents to the total load of TAM was low (19%; Figure3The). In mass the balance case of for this each anticancer target anticancer drug, drug the contributionsin the Kanzaki–Ai of River the main basin streamcould further and tributaries be estimated by calculation of percent contribution of total efflux load in the influent load through were higher than the other anticancer drugs. Recently, a screening assessment of TAM has been published [71], along with a review of its ecotoxicological effects [21,22,72]. However, because of a lack of enough information about the fate of this drug after its discharge into environmental waters, more extended investigations are needed to explain the findings mentioned above. In addition, the bulk of the contributions remained as unassigned in the total mass flux of the target anticancer drugs came Appl. Sci. 2018, 8, 2043 10 of 17 from the upstream points surveyed in the main stream [73]. In the present article, pollution loads might have come from areas beyond the sample collection points, because the Kanzaki River originates from a branch on the right bank of the Yodo River [74]. For this reason, advanced water-processing techniques should be introduced not only at STPs located in the middle and downstream reaches, as well asAppl. the Sci. upstream 2018, 8, x FOR reaches, PEER REVIEW to decrease entire pollution loads and improve the water11 qualityof 19 of the Kanzaki–Ai River system. the farthest downstream boundary site (R5). In the present article, the total efflux load for each anticancer drug was obtained by summation of the mass fluxes from two data sets from Kanzaki 3.4. Mass Balance of Anticancer Drugs River (R3 and T4) and Ai River (R1, S1, T1, T2, and S2). The influx load was estimated as the load Thepassing mass balance through forthe eachboundary target site anticancer (R5). The resulting drug in mass the balance Kanzaki–Ai data are River shown basin in Figure could 5 [ further30]. be estimated byThe calculation load of CP of was percent reduced contribution by 70% as it of was total flowed efflux downstream load in the indicating influent occurrence load through of the attenuation, but the attenuation rates for the other anticancer drugs were smaller, roughly in the farthest downstreamrange of 15–50%. boundary BLT has site a high (R5). recalcitrant In the present property article, and detected the total at effluxhigh concentrations load for each in anticancer the drug wasriver obtained waters by[75 summation,76]. Therefore, of some the massof the fluxesanticancer from drugs two are data attenuated sets from while Kanzaki being flowed River to (R3 and T4) and Aithe River lower (R1, reaches, S1, T1, but T2, the rateand of S2). the The attenuation influx load is slow was and estimated such anticancer as the drugs load passing become the through the boundarymatter site of environmental (R5). The resulting pollution. mass balance data are shown in Figure5[30].

100

Mass balance (%)

N.A. 0

Tegafur

Tamoxifen

Capecitabine

Bicalutamide

Doxifluridine

Cyclophosphamide Figure 5.FigureMass 5.balances Mass balances of anticancer of anticancer drugs drugs in the the Kanzaki Kanzaki–Ai–Ai Rive Riverr basin. basin. N.A.: not N.A.: available. not available.The The abbreviationabbreviation of eachof each anticancer anticancer drug is is shown shown in inTable Table 1 (reproduced1 (reproduced from from[30]). [30]).

The loadToday, of CP STPs was play reduced an important by 70% role asfor itmaintaining was flowed the quality downstream of river water indicating environment. occurrence In of Japan, the contributions of pharmaceutical components, including endocrine-disrupting chemicals attenuation, but the attenuation rates for the other anticancer drugs were smaller, roughly in the (EDCs) such as estrogen, to the pollutant loads in the river waters range from 50% to nearly 100% range of[ 15–50%.73,77], because BLT of has thea high high coverage recalcitrant of sewerage property systems and bydetected STPs (more at than high 90% concentrations of urban areas) in the river waters[35]. [75 As, 76 a ]. result, Therefore, STPs become some of indispensabl the anticancere facilities drugs responsible are attenuated for reducing while being the levels flowed of to the lower reaches,pharmaceuticals but the rate included of the in attenuationsewage effluent is slow[16]. The and conventional such anticancer activated drugs sludge become (CAS) process, the matter of environmentalwhich is pollution. often used as the convenient physicochemical and biological treatment at STPs, covers 35% of biological water treatment in Japan [35]. However, its insufficient ability to eliminate anticancer Today, STPs play an important role for maintaining the quality of river water environment. drugs at STPs, as described above, necessitates the introduction of additional post-treatment In Japan,technologies. the contributions Importance of pharmaceutical of such an advanced components, water treatment including systems endocrine-disrupting at STPs is becoming widely chemicals (EDCs) suchrecognized as estrogen, [78–80] to, because the pollutant of high loads power in for the removing river waters not only range PPCPs from but 50% also to other nearly chemicals 100% [ 73,77], because ofsuch the as high EDCs coverage [81], persistent of sewerage organic pollutants systems (POPs) by STPs [82] (more, bacterial than pathogens, 90% of urbanand viruses areas) [83 []35. ]. As a result, STPs become indispensable facilities responsible for reducing the levels of pharmaceuticals 3.5. Advanced Technologies for Removal of Anticancer Drugs included in sewage effluent [16]. The conventional activated sludge (CAS) process, which is often used as the convenientAdvanced oxidation physicochemical treatment and[84], biological membrane treatment treatment [ at85] STPs,, and covers hybrid 35%treatment of biological of water treatmentadsorption in with Japan ozonation [35]. However, and/or UV its [86 insufficient] are representative ability totreatments, eliminate which anticancer can be effectively drugs at STPs, used to solve the water pollution problems and ensure the safety of the water environment. as described above, necessitates the introduction of additional post-treatment technologies. Importance Examples of these treatments applied to CP, one of the target anticancer drugs discussed in this of such anarticle, advanced are listed waterin Tabletreatment 7. systems at STPs is becoming widely recognized [78–80], because of high power for removing not only PPCPs but also other chemicals such as EDCs [81], persistent organic pollutants (POPs) [82], bacterial pathogens, and viruses [83]. Appl. Sci. 2018, 8, 2043 11 of 17

3.5. Advanced Technologies for Removal of Anticancer Drugs Advanced oxidation treatment [84], membrane treatment [85], and hybrid treatment of adsorption with ozonation and/or UV [86] are representative treatments, which can be effectively used to solve the water pollution problems and ensure the safety of the water environment. Examples of these treatments applied to CP, one of the target anticancer drugs discussed in this article, are listed in Table7.

Table 7. Removal efﬁciency of cyclophosphamide (CP) from wastewater [86–93].

Initial Temperature Category Technology Treatment Source Concentration % Removal Reference (◦C) (pH) Supplemented wastewater 5 µg/L 60% Seira et al., MBR 25~32 ◦C COD 1750 (pH 7~8) (153 days) 2016 [87] mg/L Membrane separtion Wang et al., NF 20 ◦C ~60% 2009 [88] 1.513 µg/L 20 ◦C 92.0~96.9% Wang et al., RO MBR-effluent 1.382 µg/L 20 ◦C 92.5~96.7% 2009 [88] Physico-chemical MBR-permeate 8 mg/L 41% Kovalova et PAC 0.185 µg/L 27~28 ◦C 23 mg/L 73% al., 2013 [89] 43 mg/L 73% Adsorption Effluent Kovalova et AC 2 µg/L 27~28 ◦C 28% 22 mg/L al., 2013 [86] Surface water de Ridder et AC Wastewater 2 µg/L 12 ◦C <95% al., 2009 [89] 84~444 (mg/L) MBR-effluent 0.64 (g/g DOC) 33% Kovalova et O 0.185 µg/L 27~28 ◦C 3 0.89 47% al., 2013 [86] 1.08 57% 100% (pH11) Hospital 20 mg/L Lin et al., O (3g/L) 20 ◦C 69.8% (pH9) 3 wastewater (pH 3.5~11) 2015 [90] 61.2% (pH5.6) Artificial wastewater Cesenˇ et al., O3 (10 mg/L) 10 µg /L - 42% (120 min) (36 mg O3/g 2015 [91] DOC) Wastewater O (1 mg/mg effluent 5 µg/L Li et al., 3 - ca. 70% DOC) (10.0 mg/L (pH 7.2) 2016 [92] DOC) O Ferre-Aracil Chemical Oxidation 3 Hospital (43.9 g/m−3) (pH 8.1~8.2) 20 ◦C 97% et al., 2016 wastewater (55.3 g/m−3) 99% [93]

O3/UV (10 mg/L, O ; Artiﬁcial Cesenˇ et al., 3 10 µg/L - 59% (120 min) 44 mJ/cm2, wastewater 2015 [91] UV254)

O3/UV/H2O2 (10 mg/L, O ; 99% (120 min) 3 Artificial Cesenˇ et al., 2.5~5 g/L, H O ; 10 µg/L - 21% (UV only, 2 2 wastewater 2015 [91] 44 mJ/cm2, 120 min) UV254) O /H O 3 2 2 Artificial 30~40% Cesenˇ et al., (10 mg/L, O ; 10 µg/L - 3 wastewater (120 min) 2015 [91] (2.5~5 g/L, H2O2) O /H O Ferre-Aracil 3 2 2 Hospital 1.187 µg/L [O ]sat:[H O ] 20 ◦C 100% (20 min) et al., 2016 3 2 2 wastewater (pH 8.1~8.6) = 1:0.5~1:3 [93] NF: nanofiltration; RO: reverse osmosis; MBR: membrane bioreactor; PAC: powdered activated carbon; AC: activated carbon, DOC: dissolved organic carbon. Appl. Sci. 2018, 8, 2043 12 of 17

Ozonation is one of the techniques known as advanced oxidation processes (AOPs), which use HO· generated from ozone (O3). HO· is the second strongest oxidant, after fluorine. Combined techniques with UV (O3/UV), H2O2 (O3/H2O2), and both (O3/UV/H2O2) were also developed and applied to remove CP. UV and H2O2 are known to increase the rate of HO· formation [89]. Application of these treatments to remove the anticancer drugs has an outstanding benefit of higher degradability with lower toxicity of the reaction byproducts, but is accompanied by the shortcomings of the undesirable consumption of the oxidizing agents by the associated scavengers in the samples and the possible formation of less biodegradable byproducts and/or conversion into still more highly toxic byproducts. Additional treatments are sometimes still needed to achieve complete mineralization. These processes are thought to be cost-effective and their practical utilization has already started at some model STPs, as described in this article. Removal of the target compounds by adsorption is the simplest, most cost-effective, and versatile way. Various kinds of materials are usable as adsorbents, such as activated carbon, mesoporous silica, zeolite, biochar, carbon nanotubes, clays, graphene oxide, chitosan, biomass wastes, and functionalized resin [90]. In addition, two types of operation systems, batch-wise and continuous, are also available practically. By using the affinity of the special adsorbent for a specific drug, selective removal of recalcitrant drugs could be achieved. This article is concentrated to a specific area in Japan where the population is high. Evidently, there are similar areas in many other countries with a high population and a rather limited flow of streams, where concentrations of anticancer drugs may thus be more or less similar to those presented in this article. Finally, the present article should have value for conducting future ecotoxicity assessments of anticancer drugs and the risks they pose to human health via drinking water.

4. Conclusions The present article contributed summative clarification of the distribution of six anticancer drugs (BLT, TAM, CP, CAP, DFUR, and TGF) in the river waters and sediments of the Yodo River basin in Japan, including effluents from sewage treatment plants (STPs). In the year-round survey, all anticancer drugs were detected at medium concentrations in the range of N.D.–32 ng/L in the river water and N.D.–245 ng/L in the STP effluents, with the highest levels for BLT (254 ng/L in river water and 1032 ng/L in the STP effluents). STPs were the primary sources of anticancer drugs in the river water, and the attenuation effect of the river environment was small. Ozonation was effective in removing these drugs. BLT, DFUR, and TAM were also detected in the river sediments at maximum concentrations of 391, 392, and 250 ng/kg, respectively. In addition, the sorption distribution coefficient (logKd) in river sediments appeared to be higher in the silty sediments at Suita Bridge than in the sandy sediments at Hirakata Bridge, in accord with the results of the laboratory-scale sorption experiment. The present article provides fundamental data as an initiative for conducting risk assessments of environmental pharmaceuticals in a wider geographic area.

Author Contributions: This manuscript was entirely conceptualized, developed, and performed by T.A. Funding: This research was funded by the River Foundation (25-1263-024, 26-1263-017), the Kurita Water and Environment Foundation (14E007), and the Ministry of Education, Culture, Sports, Science, and Technology of Japan (16K16218) for funding in the form of research grants and scholarships. Acknowledgments: We thank the staff of the STPs for sampling the water. Conﬂicts of Interest: The authors declare no conﬂict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Appl. Sci. 2018, 8, 2043 13 of 17

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