Occurrence, Fate and Removal of Synthetic Oral Contraceptives (Socs) in the Natural Environment: a Review

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Science of the Total Environment 409 (2011) 5149–5161

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Science of the Total Environment

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Review Occurrence, fate and removal of synthetic oral contraceptives (SOCs) in the natural environment: A review

Ze-hua Liu a,d,⁎, Jactone Arogo Ogejo a, Amy Pruden b, Katharine F. Knowlton c a Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24061, United States b Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA 24061, United States c Department of Dairy Science, Virginia Tech, Blacksburg, VA 24061, United States d Graduate School of Engineering, Osaka City University, Osaka 558-8585, Japan article info abstract

Article history: Synthetic oral contraceptives (SOCs) are a group of compounds with progestagenic and/or androgenic activities, Received 12 April 2011 with some also possessing estrogenic activities. Recent research has documented that some of these emerging Received in revised form 4 August 2011 contaminants have adverse effects on aquatic organisms at very low concentrations. To facilitate the evaluation Accepted 14 August 2011 of their latent risks, published works on their occurrence and fate in the environment are reviewed. Androgenic/ Available online 4 October 2011 progestagenic relative potencies or relative binding afﬁnity of these SOCs as well as their physicochemical properties and toxicity are summarized. Appropriate analytical methods are outlined for various environmental Keywords: ﬁ Synthetic oral contraceptives sample types, including methods of sample preparation and limit of detection/quanti cation (LOD/LOQ). Finally Micropollutants results on their occurrence and fate in wastewater treatment plants (WWTPs) and other environments are Toxicity critically examined. Wastewater © 2011 Elsevier B.V. All rights reserved. Occurrence and fate Removal

Contents

1. Introduction ...... 5149 0 2. Synthetic oral contraceptives ...... 5152 0 2.1. Bioactivity potencies of SOCs ...... 5152 0 2.2. Toxicity of SOCs to aquatic organisms ...... 5152 0 3. Synthetic oral contraceptives in the environment ...... 5152 0 3.1. Distribution of SOCs in the environment ...... 5152 0 3.2. Analytical methods for SOCs ...... 5155 0 3.2.1. GC-MS based methods ...... 5155 0 3.2.2. LC based methods ...... 5155 0 3.3. Occurrence and fate of SOCs in the natural environment ...... 5156 0 3.3.1. Estimated input concentrations of SOCs to WWTPs ...... 5156 0 3.3.2. Occurrence and fate of SOCs in WWTPs ...... 5157 0 3.3.3. Occurrence and fate of SOCs in other environment ...... 5157 0 3.3.4. Removal of SOCs by physical means and chemical oxidation ...... 5157 0 4. Summary ...... 5158 0 References ...... 5158 0

1. Introduction

In the last few decades, the occurrence and fate of micropollutants in water bodies including endocrine disrupting chemicals (EDCs), phar- ⁎ Corresponding author at: Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24061, United States. Tel.: +1 540 231/6815. maceuticals, personal care products and antibiotics have been exten- E-mail address: [email protected] (Z. Liu). sively studied due to their possible adverse effects to wildlife and

0048-9697/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.scitotenv.2011.08.047 5150 Z. Liu et al. / Science of the Total Environment 409 (2011) 5149–5161 humans (e.g., Kummerer, 2009; Liu et al., 2009a,b, 2010a; Le-Minh et al., countries; McClave et al., 2010; Population reports, 2010; Tsilidis et 2010). As the awareness is growing of the importance of these micro- al., 2010). In contrast, the usage rates of SOCs by Asian women are pollutants, particularly in the aquatic environment, synthetic oral con- low, especially for those living in India and China with the usage rate traceptives (SOCs) are deserving of greater attention (Besse and less than 6% (Population reports, 2010). More recently usage is increas- Garric, 2009). The estimated yearly usage of SOCs (about 1723 kg/year) ing in these countries because of both of cultural influences (Wiebe et is much greater than that of estrogens and androgens (about al., 2006) and government policies (e.g., Government of India; GOI, 706 kg/year) in the United Kingdom (UK, Runnalls et al., 2010), yet 2010). relatively little published research is available describing their As with other pharmaceuticals, broad usage of SOCs may lead to occurrence, fate, and removal in the natural environment. their widespread occurrence in the environment. Most currently-used SOCs consist of synthetic progestins or their mixtures with small SOCs possess a variety of hormonal activities: estrogenic, antiandro- amounts of synthetic estrogens (Besse and Garric, 2009; Duke, genic and androgenic. Thus their occurrence in aquatic environments 2009; Sitruk-Ware and Nath, 2010). They were first introduced and may result in latent risks to wildlife (Dao et al., 1996; Besse and Garric, used in the 1960s and continue to be popular as an effective method 2009). Several studies have reported the toxicity, occurrence, fate and for contraception (Dinger et al., 2007). In Europe and America, the removal of SOCs in the environment, but most research has focused usage rates of SOCs by premenopausal women are very high and SOCs only on a few SOCs. SOCs are often studied concurrently with other rank the first among all contraception methods (e.g., the latest estimat- micropollutants, making their effects difficult to elucidate. Thus, the ob- ed average usage rate of oral contraceptives (OCs) among women is jectives of this review are to: (1) highlight progestagenic/androgenic 32.8% in the United States, and as high as 58.4% in some European potencies of SOCs as measured by different in vitro assays;

Table 1 Physicochemical properties of twenty six chemicals used in SOCs and their in vitro bioactivitya.

Name of SOCs CAS Molecular WS Log RBA (AR) RBA (PR) RP (AR) RP (PR)

formula (mg/L) KOW

b c b c Chlormadione acetate (CMA) 302-22-7 C23H29ClO4 0.324 3.95 0.05 ; 0.18 0.67 ; 0.27 –– d e f g b c h h Cyproterone acetate (CPA) 427-51-0 C24H29ClO4 51.7 3.1 0.121 ; 4.8e−3 ; 0.067 ; 0.071 0.9 ; 0.08 0.01 0.075 i j Desogestrel (DES) 54024-22-5 C22H30O 0.27 5.65 – 1.25 ; 0.12 –– k k h h Dienogest (DIE) 65928-58-7 C20H25NO2 ––0.1 0.05 1.5e−3 0.012 k k Drospirenone (DRO) 67392-87-4 C24H30O3 ––0.65 0.35 –– b h h Dydrogesterone (DYD) 152-62-5 C21H28O2 3.66 3.45 – 0.75 7.7e−3 0.53 j h h Ethisterone (ETH) 434-03-7 C21H28O2 0.687 3.11 – 0.019 0.21 0.17 k l i c k m l i h h Etonogestrel (ETO) 54048-10-1 C22H28O2 – 3.16 0.2 ; 0.052 ; 0.16 ; 0.17 1.5 ; 1.87 ; 1.88 ; 1.25 0.18 3.25 b n l i b n l i Gestodene (GES) 60282-87-3 C21H26O2 8.12 3.26 0.85 ; 0.71 ; 0.062 ; 0.33 0.9 ; 8.64 ; 1.92 ; 1.25 –– o o Hydroxyprogesterone caproate 630-56-8 C27H40O4 ––– 0.26-0.3 – 0.91-1.7 (HPC) e k f n k n l p Levonorgestrel (LNG) 797-63-7 C21H28O2 2.05 3.48 0.166 ; 0.45 ; 0.105 ; 0.58 1.5 ; 3.23 ; 0.8 ; 0.94 –– j h h Lynestrenol (LYN) 52-76-6 C20H28O 0.768 4.75 – 0.017 0.051 0.041

Medroxyprogesterone (MEP) 520-85-4 C22H32O3 2.95 3.5 –––– b f n c m b n c h h Medroxyprogesterone acetate 71-58-9 C24H34O4 1.2 4.09 0.05 ; 0.197 ; 0.36 ; 0.29 0.918 ; 1.15 ; 2.98 ; 0.44 0.048 0.72 (MPA) b c b c h h Megestrol acetate (MGA) 595-33-5 C24H32O4 2.0 4.0 0.05 ; 0.20 0.65 ; 0.21 0.033 0.81

Medrogestone (MED) 977-79-7 C23H32O2 1.82 4.45 –––– f m p j h q h Mifepristone (MIF) 84371-65-3 C29H5NO2 – 5.4 0.028 0.354 ; 0.174 ; 0.347 1.5e−4 ; 1.99e−3 1.7e−3 k k Nomegestrol acetate (NGA) 58691-88-6 C21H28O3 ––0.42 1.25 –– r Norelgestromin (NOR) 53016-31-2 C21H29NO2 ––– – 0.18 – e k n g k n l p h h Norethisterone (NE) 68-22-4 C20H26O2 7.04 2.97 0.026 ; 0.15 ; 0.55 ; 0.055 0.75 ; 1.34 ; 0.22 ; 0.272 0.19 0.80

Norethisterone acetate (NEA) 51-98-9 C22H28O3 5.35 3.99 –––– e c m c h h Norethynodrel (NTL) 68-23-5 C20H26O2 8.95 3.51 2e−3 ; 0.03 0.012 ; 0.02 0.11 0.16 f s k m s h r h Norgestimate (NTE) 35189-28-7 C23H31NO3 0.0362 4.98 0.027 ; 0.013 0.15 ; 1.72 ; 0.94 1.8e−3 ; 0.25 0.35 g h h Norgestrel (NOG) 6533-00-2 C21H28O2 1.73 3.48 0.18 – 0.49 1.5 e b p j h h Promegestone (PRO) 34184-77-5 C22H30O2 – 4.04 2.3e−3 1 ; 0.758 ; 1.51 3.7e−3 2.16

Trimegestone (TRI) 74513-62-5 C22H30O3 ––0.024 5.88 –– a WS: water solubility; RBA: relative binding afﬁnity used in competitive binding assay; AR: androgen receptor; PR: progesterone receptor; RP: androgenic/progestagenic relative potency used in yeast or other in vitro assay; NB: not binding; –: not available; data for water solubility and Log KOW was adopted from SRC (http://www.syrres.com/what-we-do/ databaseforms.aspx?id=386). b Schindler et al., 2008; metribolone was used as the reference for AR, promegesterone was used as the reference for PR. c Bergink et al., 1983, Org 2058 and dihydrotestosterone were used as the reference compounds for progesterone and androgen receptor, respectively. d National Institute of Technology and Evaluation (NITE, 2010), testosterone was used as the reference for AR. e Fang et al., 2003, R1881 was used as the reference for AR. f Sonneveld et al., 2006, dihydrotestosterone was used as the reference. g Freyberger and Ahr, 2004, dihydrotesterone was used as the reference compound. h McRobb et al., 2008, testosterone was used as the reference for AR and Progesterone was used as the reference for PR. i Fuhrmann et al., 1995, R1881 and progesterone were used as reference compounds for the progesterone and androgen receptor, respectively. j Kelder et al., 2010, Org 2058 was used as the reference compound. k Burkman et al., 2011, metribolone was used as the reference for AR, promegesterone was used as the reference for PR. l Deckers et al., 2000, Org 2058 and DHT were used as reference compounds for the progesterone and androgen receptor, respectively. m Sonneveld et al. (2011), Org 2058 was used as the reference for PR. n Winneker et al., 2003. o Attardi et al., 2007, progesterone was used as the reference compound. p Schoonen et al., 1998, Org 2058 was used as the reference compound. q Sanseverino et al., 2009, dihydrotestosterone was used as the reference for AR. r Prifti et al., 2004, testosterone acetate was used as the reference. s Phillips et al., 1990, progesterone and dihydrotestosterone were used as reference compounds for the progesterone and androgen receptor, respectively. Z. Liu et al. / Science of the Total Environment 409 (2011) 5149–5161 5151

Fig. 1. Molecular structures of SOCs described in this review. 5152 Z. Liu et al. / Science of the Total Environment 409 (2011) 5149–5161

(2) summarize analytical methods currently available for measuring al., 1993; Greim et al., 1995; Brambilla and Martelli, 2002). Also CPA SOCs in environmental samples and (3) summarize occurrence and is reported to be hepatotoxic and genotoxic to humans (Miquel et fate of SOCs in the environment, including their removal by different al., 2007; Siddique and Afzal, 2008). Ostad et al. (1998) reported wastewater treatment methods. that both levonorgestrel and norethisterone possess cytotoxicity and teratogenicity to endometrial cells. 2. Synthetic oral contraceptives The androgenic/progestagenic or even estrogenic nature of these SOCs suggests they may also have latent risks to the aquatic living or- 2.1. Bioactivity potencies of SOCs ganisms (Sumpter and Johnson, 2005; Hernandez et al., 2009). In 2003, medroxyprogesterone (MEP) was detected at concentration of Great advances have been made to SOCs to reduce health risks asso- up to 15 ng/L in WWTP effluent samples along with other steroid hor- ciated with use by humans in the past 50 years since their introduction mones, and the effluents elicited pheromonal responses in fish that (Szarewski et al., 2010; Burkman et al., 2011). Lower dose estrogens are could alter their behavior and interfere with reproduction (Kolodziej common in new generations of contraceptive pills as a means to make et al., 2003). Pietsch et al. (2009) demonstrated that medroxyproges- SOCs safer to consumers by reducing the chances of their causing cancer terone acetate (MPA) is capable of influencing the innate immunity in and other side effects (Piper and Kennedy, 1987; Lewis et al., 1999; fish, as it significantly decreased nitric oxide formation by head and Cibula et al., 2010). However, the highly estrogenic ethinyloestradiol trunk kidney cells. Both levonorgestrel (LNG) and drospirenone (EE2) is still included in most of the current contraceptive pills (Lo, (DRO) were reported to inhibit reproduction in adult fathead minnows 2009; Runnalls et al., 2010). The occurrence, fate and degradation of (Pimephales promelas). The non-observed-effect concentration (NOEC) EE2 is well documented (e.g. Vaderetal.,2000;Clouzotetal.,2008; was as low as 0.8 ng/L for LNG, while the NOEC for DRO was 0.66 μg/L Liu et al., 2009a), so EE2 is not included in this review. (Zeilinger et al., 2009). Decreased fecundity has been demonstrated in The molecular structures, physicochemical properties, and in vitro Japanese medaka (Oryzias latipes) and fathead minnows' exposure to bioactivity potencies of 26 representative SOCs are shown in Table 1 norethindrone in the low ng/L range (Paulos et al., 2010). and Fig. 1 (Besse and Garric, 2009; Lo, 2009). Most SOCs are strong andro- Significant bioaccumulation is observed with these progestagenic genic compounds, comparable to or more potent than natural androgens chemicals. Contardo-Jara et al. (2011) reported that bioaccumulation excreted by humans (Liu et al., 2009b).Sideeffectssuchasmasculiniza- of LNG in Dreissena polymorpha was over 30–208 folds higher with tion of fish have been reported after their exposure to androgenic three different LNG concentrations. Astonishingly, LNG concentration substances at low concentrations, thus the influence of these compounds in the blood plasma of rainbow trout (Oncorhynchus mykiss) was on aquatic organisms deserves attention (Larsson et al., 2000; Jenkins et 12,500 times higher than that of the treated sewage effluent to al., 2001; Parks et al., 2001; Larsson and Forlin, 2002). Relative binding which those fish were exposed (Fick et al., 2010a). affinity (RBA) and relative potency (RP) information is not available for medrogestone, norethisterone acetate, and medroxyprogesterone. A few 3. Synthetic oral contraceptives in the environment SOCs (e.g. levonorgestrel, norethisterone, trimegesterone, etc.) are also estrogenic chemicals, and are not included in Table 1 (Zhang et al., 3.1. Distribution of SOCs in the environment 2000; Garcia-Becerra et al., 2002; Sonneveld et al., 2006). The distribution of SOCs in the environment is summarized in

2.2. Toxicity of SOCs to aquatic organisms Fig. 2. According to their distribution, Log Kow values are critical physicochemical parameters, which correlate inversely with SOCs' solubil-

Most SOCs are progestogens and have been classified by the Inter- ity (Briggs, 1981; Holthaus et al., 2002). Large Log Kow values (N4) national Agency for Research on Cancer (IARC) as possibly carcino- suggest large hydrophobic molecules that tend to associate with genic to humans. This classification is usually made on the basis of solid organic matter (high sorption potential), while smaller hydro- sufficient or limited evidence for carcinogenicity in experimental an- philic molecules are characterized by a low Log Kow (b2.5) and low imals and inadequate evidence for carcinogenicity in humans (IARC, sorption potential (Jason et al., 2003). By this measure, most SOCs 1999). Among these SOCs, cyproterone acetate (CPA) is the most ex- are hydrophobic substances (Table 1) and they are readily absorbed tensively studied and is found to generate DNA adducts in primary to solid materials. Thus their latent risks to the environment include cultures of rat hepatocytes and in the liver of intact rats (Topinka et both aquatic and non-aquatic (soil and sediment) environments.

Fig. 2. Distributions of SOCs in the environment. Modiﬁed from Besse and Garric, 2009. Z. Liu et al. / Science of the Total Environment 409 (2011) 5149–5161 5153

Table 2 Analytical methods of SOCs for environmental samplesa.

SOC Analytical method (IS) Matrix Sample preparation Recovery LOD (LOQ) Reference (ng/L or ng/g)

CMA UPLC-MS/MS (ESI) Tap, river, lake and wastewater SPE 85–100% 1.0 (–) Sun et al., 2009 UPLC-MS/MS (ESI) Aquatic products SPE 76–89% – (0.3–1.0) Xu et al., 2010 CPA LC-MS (ESI or APCI) Tap and river water Without concentration 93–97% – (0.02–1.7)b Matejicek and Kuban, 2007 LC-MS/MS (ESI) River and waste water SPE 60–87% 20–68 (–) Al-Odaini et al., 2010 UPLC-MS/MS (ESI) Tap, river, lake and wastewater SPE 84–92% 0.9 (–) Sun et al., 2009 UPLC-MS/MS (ESI) Soil and river sediment PLE plus SPE 35–70%c 2.1 (7.1) Perez-Carrera et al., 2010 UPLC-MS/MS (ESI) Aquatic products SPE 76–89% – (0.3–1.0) Xu et al., 2010 DES LC-MS (ESI or APCI) Tap and rive water Without concentration 98–99% – (1–1.8)b Matejicek and Kuban, 2007 DRO LC-MS/MS (ESI) Surface and ground water SPE 97% 0.29 (–) Vulliet et al., 2008 DYD UPLC-MS/MS (ESI) Aquatic products SPE 76–89% – (0.3–1.0) Xu et al., 2010 ETH UPLC-MS/MS (ESI) Aquatic products SPE 76–89% – (0.3–1.0) Xu et al., 2010 GES GC-MS (EI) Wastewater samples SPE 95% 10 (–) Robert et al., 2007 GC-MS (EI) Stream waters SPE 95% 1.28 (–) Velicu and Suri, 2009 LC-MS (ESI or APCI) Tap and river water Without concentration 93–97% – (0.01–0.05)b Matejicek and Kuban, 2007 HPLC-MS/MS (ESI) Soil and river sediment PLE plus SPE 25–50%c 0.5 (1.7) Perez-Carrera et al., 2010 HPC UPLC-MS/MS (ESI) Tap, river, lake and wastewater SPE 76–90% 1.8 (–) Sun et al., 2009 LNG GC-MS (EI) Effluent SPE ––(1) Kuch and Ballschmiter, 2000 GC-MS (EI) Wastewater samples SPE 81% 10 (–) Robert et al., 2007 GC-MS (EI) Stream waters SPE 81% 0.28 (–) Velicu and Suri, 2009 GC-MS (EI) Surface and wastewater SPE 77–98% 1–8(–) Labadie and Budzinski, 2005a ELISA (–)Influent and effluent SPE 95–124% 0.7 (–) Pu et al., 2008 ELISA (–) River and waste water ICCE 95–107% – (–) Qiao et al., 2009 LC (–) Drinking, ground, surface, waste water Online-SPE 91–101% 15 (–) Lopez de Alda and Barcelo, 2001b LC-MS (ESI) Tap, river and wastewater SPE 92–113% 2–50 (–) Lopez de Alda and Barcelo, 2000 LC-MS (ESI) Influent and effluent SPE – 2–20 (–) Sole et al., 2000 LC-MS (ESI) River sediment ULE plus SPE 68–79% 0.04–1(–) Lopez de Alda et al., 2002 LC-MS (ESI) River sediment PLE plus SPE 103% 0.5 (–) Petrovic et al., 2002a LC-MS (ESI) Influent, effluent and sludge LLE and/or SPE 80–113% 0.2d; 0.04e (–) Petrovic et al., 2002b LC-MS (ESI) River water and sediment SPEd or PLEe 89% 90d;2e (–) Cespedes et al., 2004 LC-MS (ESI or APCI) Tap and river water Without concentration 93–97% – (0.01–0.05)b Matejicek and Kuban, 2007 LC-MS/MS (ESI) Effluent SPE 65–98% 0.2 (–) Vulliet et al., 2007 LC-MS/MS (ESI) River, drinking and effluent Online-SPE 100% 1.8 (4.9) Kuster et al., 2008 LC-MS/MS (APPI) Influent and effluent Online-SPE 92–110% 2–10 (–) Viglino et al., 2008 LC-MS/MS (ESI) Surface and ground water SPE 97% 0.33 (–) Vulliet et al., 2008 LC-MS/MS (ESI) Effluent SPE 92% – (1) Fick et al., 2010a LC-MS/MS (ESI) River water SPE 101–102% 0.8–1.2 (–) Kuster et al., 2009 LC-MS/MS (ESI) River and waste water SPE 65–81% 22–66 (–) Al-Odaini et al., 2010 LC-MS/MS (ESI) Soil PLE plus SPE 55.8–96.7% 0.27 (–) Gineys et al., 2010 LC-MS/MS (ESI) Surface and drinking water SPE 81% – (0.7) Vulliet et al, 2011 UPLC-MS/MS (ESI) Tap, river, lake and wastewater SPE 64–96% 0.8 (–) Sun et al., 2009 UPLC-MS/MS (ESI) Aquatic products SPE 76–89% – (0.3–1.0) Xu et al., 2010 LDTD-MS/MS (APCI) Effluent SPE 76.7% 20 (–) Fayad et al., 2010 LDTD-MS/MS (APCI) Sediment, soil, and sludge ULE plus SPE 80–110%c 2.8–9(–) Viglino et al., 2011 MED GC-MS (EI) Wastewater samples SPE 72% 10 (–) Robert et al., 2007 GC-MS (EI) Stream waters SPE 72% 0.03 (–) Velicu and Suri, 2009 MEP GC-MS (EI) Wastewater SPE 21–59% – (8–95) Zheng et al., 2008 GC-MS/MS (EI) Wastewater SPE 74% 0.2 (0.4) Kolodziej et al., 2003 GC-MS/MS (EI) Surface and ground water SPE – 0.14 (0.4) Kolodziej et al., 2004 HPLC (–) Surface and wastewater SPE 89.7% 1.6 (–) Zarzycki et al., 2009 LC-MS/MS (APPI) Influent and effluent Online-SPE 92–110% 2–10 (–) Viglino et al., 2008 LC-MS/MS (ESI) Surface and drinking water SPE 105% – (1.6) Vulliet et al, 2011 UPLC-MS/MS (ESI) Tap, river, lake and waste water SPE 93–100% 1.0 (–) Sun et al., 2009 UPLC-MS/MS (ESI) Sediment and sludge LLE plus SPE 77–119% – (0.5–2) Yu et al., 2011 LC-MS/MS (ESI) Wastewater, surface water, sludge ULE or SPE 99.6–140% 0.04–0.38 (0.15–1.28) Liu et al., 2011 LDTD-MS/MS (APCI) Effluent SPE 83.3% 30 (–) Fayad et al., 2010 LDTD-MS/MS (APCI) Sediment, soil and sludge ULE plus SPE 65–110%c 0.9–12.8 (–) Viglino et al., 2011 MGA LC-MS/MS (ESI) River water SPE 75–100% 0.01–0.5 (–) Chang et al., 2009 UPLC-MS/MS (ESI) River and waste water SPE 82–90% 0.03–0.12 (–) Chang et al., 2008 UPLC-MS/MS (ESI) Tap, river, lake and wastewater SPE 79–90% 0.9 (–) Sun et al., 2009 UPLC-MS/MS (ESI) Aquatic products SPE 76–89% – (0.3–1.0) Xu et al., 2010 UPLC-MS/MS (ESI) River and wastewater SPE 78–100% 0.03–0.12 (–) Chang et al., 2011 MIF UPLC-MS/MS (ESI) Influent and effluent SPE 74–118% – (0.5) Liu et al., 2010b MPA LC-MS/MS (ESI) Surface and ground water SPE 96% 0.80 (–) Vulliet et al., 2008 LC-MS/MS (ESI) River water SPE 75–100% 0.01–0.5 (–) Chang et al., 2009 UPLC-MS/MS (ESI) River and waste water SPE 82–86% 0.01–0.16 (–) Chang et al., 2008 UPLC-MS/MS (ESI) River and wastewater SPE 78–100% 0.02–0.1 (–) Chang et al., 2011 NE GC-MS (–) River water SPE ––(–) Kolpin et al., 2002 GC-MS (EI) Surface and wastewater SPE 92–108% 1–8(–) Labadie and Budzinski, 2005a GC-MS (EI) Effluent SPE 80–118% 0.4–3(–) Labadie and Budzinski, 2005b GC-MS (EI) Wastewater samples SPE 40–120% 32–45 (–) Fernandez et al., 2007 GC-MS (EI) Wastewater samples SPE 100%c 32–45 (–) Ikonomou et al., 2008 GC-MS (EI) River water SPE N50% – (2.3) Jeffries et al., 2010 LC (–) Drinking, ground, surface, waste water Online-SPE 95–101% 15 (–) Lopez de Alda and Barcelo, 2001b

(continued on next page) 5154 Z. Liu et al. / Science of the Total Environment 409 (2011) 5149–5161

Table 2 (continued) SOC Analytical method (IS) Matrix Sample preparation Recovery LOD (LOQ) Reference (ng/L or ng/g)

NE HPLC (–) Surface and wastewater SPE 96.7% 0.44 (–) Zarzycki et al., 2009 LC-MS (ESI) Influent and Effluent SPE – 2–20 (–) Sole et al., 2000 LC-MS (ESI) River sediment ULE plus SPE 66–67% 0.04–1(–) Lopez de Alda et al., 2002 LC-MS (ESI) River sediment PLE plus SPE 96% 0.5 (–) Petrovic et al., 2002a LC-MS (ESI) Influent, effluent and sludge LE and/or SPE 67–104% 0.2d; 0.4e (–) Petrovic et al., 2002b LC-MS (ESI) River water and sediment SPEd or PLEe 83 or 94% 200d;2e (–) Cespedes et al., 2004 LC-MS (ESI) Effluent SPE 69–100% 0.3 (–) Vulliet et al., 2007 LC-MS/MS (ESI) River, drinking and effluent Online-SPE 72% 3.9 (10.5) Kuster et al., 2008 LC-MS/MS (APPI) Influent and effluent Online-SPE 92–110% 2–10 (–) Viglino et al., 2008 LC-MS/MS (ESI) Surface and ground water SPE 96% 0.01 (–) Vulliet et al., 2008 LC-MS/MS (ESI) River water SPE 81–95% 2.4–3.6 (–) Kuster et al., 2009 LC-MS/MS (ESI) River and wastewater SPE 67–87% 9–162 (–) Al-Odaini et al., 2010 LC-MS/MS (ESI) Soil PLE plus SPE 65.3–92.3% 0.12 (–) Gineys et al., 2010 LC-MS/MS (ESI) Surface and drinking water SPE 84% – (0.02) Vulliet et al, 2011 UPLC-MS/MS (ESI) River and waste water SPE 78–82% 0.3–1.2 (–) Chang et al., 2008 UPLC-MS/MS (ESI) Surface and wastewater SPE 98–114% 1.4–2.3 (4.6–7.6) Batt et al., 2008 UPLC-MS/MS (ESI) Tap, river, lake and wastewater SPE 76–98% 2.8 (–) Sun et al., 2009 UPLC-MS/MS (ESI) River and wastewater SPE 78–100% 0.3–1.2 (–) Chang et al., 2011 LC-MS/MS (ESI) Wastewater, surface water, sludge ULE or SPE 53.8–111% 0.02–1.92 (0.21–6.39) Liu et al., 2011 LDTD-MS/MS (APCI) Effluent SPE 80% 25 (–) Fayad et al., 2010 LDTD-MS/MS (APCI) Sediment, soil and sludge ULE plus SPE 85–110%c 2–16.8 (–) Viglino et al., 2011 NEA GC-MS (EI) Effluent SPE ––(1) Kuch and Ballschmiter, 2000 UPLC-MS/MS (ESI) Tap, river, lake and wastewater SPE 85–102% 0.8 (–) Sun et al., 2009 UPLC-MS/MS (ESI) Aquatic products SPE 76–89% – (0.3–1.0) Xu et al., 2010 NOG GC-MS (EI) Wastewater samples SPE 81% 10 (–) Robert et al., 2007 GC-MS (EI) Wastewater samples LLE-SPE 40–120% 74–98 (–) Fernandez et al., 2007 GC-MS (EI) Wastewater samples LLE-SPE 105%c 74–98 (–) Ikonomou et al., 2008 GC-MS (EI) Stream waters SPE 81% 0.28 (–) Velicu and Suri, 2009 GC-MS (EI) River waters SPE N50% – (1.5) Jeffries et al., 2010 HPLC (–) Surface and wastewater LLE-SPE 95.6% 1.4 (–) Zarzycki et al., 2009 UPLC-MS/MS (ESI) River and wastewater SPE 78–83% 0.24–0.9 (–) Chang et al., 2008 UPLC-MS/MS (ESI) River and wastewater SPE 78–100% 0.08–0.3 (–) Chang et al., 2011 LC-MS/MS (ESI) Wastewater, surface water, sludge ULE or SPE 87.5–115% 0.03–0.9 (0.1–2.99) Liu et al., 2011 TRI GC-MS (EI) Wastewater samples SPE 120% 10 (–) Robert et al., 2007 GC-MS (EI) Stream waters SPE 120% 10 (–) Velicu and Suri, 2009

a IS: ion source; ESI: electrospray ionization; APCI: atmospheric pressure chemical ionization; EI: electron ionization; APPI: atmospheric pressure photoionization; LOD: limit of detection; LOQ: limit of quantification; SPE: solid phase extraction; PLE: pressurized liquid extraction; LLE: liquid liquid extraction; ULE: ultrasonic liquid extraction; ICCE: immunoaffinity chromatography column extraction; ELISA: enzyme-linked immunosorbent assay; GCCE: glass chromatography column extraction; LDTD: laser diode thermal desorption; –: not available. b Calculated as a 1000-concentration factor. c Estimated from the figure. d For river water sample. e For river sediment sample.

Just as some metabolites (e.g., hydroxyl metabolites of benzo[a]pyr- (CPA)) of the SOCs are reported to have estrogenic, androgenic or proges- ene and chrysene) of polycyclic aromatic hydrocarbons (PAHs) are togenic activities (Pasapera et al., 2002; Besse and Garric, 2009; Lemus et reported to be as or more estrogenic than their parent compounds (van al., 2009). However, no published information was found on the occur- Lipzig et al., 2005; Wessel et al., 2010), some metabolites (e.g., hydroxyl rence and fate of these metabolites of SOCs in the environment, a topic metabolites of chlormadinone acetate (CMA) and cyproterone acetate that would be of interest for future research.

Table 3 Derivatization conditions of SOCs.

Target SOCs Derivatization reagent Organic solution Derivatization QI IDI Ref for derivatization condition

NEA and LNG 100 μL mixture of MSTFA, TMSI, DTE (1000:4:2, v/ No other organic 60 °C for NEA: 412 NEA: 287 Kuch and Ballschmiter, m/m) solution 30 min LNG: 456 LNG: 301 2000

NE and LNG 30 μL mixture of MSTFA, mercaptoethanol, NH4I No other organic 65 °C for 30– NE: 442 NE: 287 Labadie and Budzinski, (507:3:2, v/m/m) solution 40 min 2005a LNG: 456 LNG: 316 Labadie and Budzinski, 2005b NE and NOG 50 μL BSTFA/TMCS (99:1, v/v) 50 μL anhydrous 90 °C for ––Fernandez et al. (2007) pyridine 180 min Ikonomou et al., 2008 MEP 50 μL heptaﬂuorobutyric anahydride No other organic 55 °C for 479 383 Kolodziej et al., 2003 solution 90 min Kolodziej et al., 2004 MEP 50 μL heptaﬂuorobutyric anahydride 200 μL acetonitrile 80 °C for 479 – Zheng et al., 2007 90 min GES, LNG, MED, TRI, 65 μL BSTFA/TMCS (99:1, v/v) 15 μL anhydrous 26 °C for GES: 353; LNG: GES: 73; LNG: Robert et al., 2007 NOG pyridine 15 min 355 73 MED: 412; TRI: MED: 397; TRI: Velicu and Suri, 2009 341 117 NOG: 355 NOG: 73

–: it is not provided. Z. Liu et al. / Science of the Total Environment 409 (2011) 5149–5161 5155

Table 4 trifluoroacetamide/trimethylchlorosilane (BSTFA/TMCS, 99:1, v/v), and Influent predicted environmental concentrations (PECs) of SOCs based on their con- then analyzed with GC-MS. Robert et al. (2007) broadened the scope sumption. Adapted from Besse and Garric, 2009. with five target SOCs (MED, TRI, NOG, LNG and GES), using BSTFA as SOC Consumption in Influent PECs Consumption in the derivatization reagent. In addition, there is also one analytical method France, 2004 (kg) (ng/L) United Kingdom, available for MEP in environmental samples with GC-MS/MS, in which a 2006 (kg) heptafluorobutyric anahydride was used as the derivatization reagent CMA 385.17 87.94 – (Kolodziej et al., 2003, 2004). Derivatization conditions are crucial for – CPA 821.56 187.57 the analytical methods of GC-MS or GC-MS/MS. Thus, the derivatization DES +ETO 28.88 6.86 13.87 DIE 5.73 1.31 – conditions of a few studies on SOCs are listed in Table 3 along with the DRO 149.38 34.10 153.19 quantification ion (QI) and identification ion (IDI) of these target SOCs. DYD 744.70 170.02 209.02 GES 22.04 5.03 – 3.2.2. LC based methods LNG +NTE 94.17 21.50 43.71 LC based methods of quantifying SOCs are generally more popular MED 87.73 20.03 – MEP 68.50 15.64 529.70 than those based on GC-MS. An effective LC-MS method for two SOCs NGA 312.10 71.26 – in environmental samples was first introduced in 2000 (Lopez de NOG 11.92 2.72 – Alda and Barcelo, 2000), and the method was further developed by – NOR 0.34 0.08 other researchers (Petrovic et al., 2002a,b; Cespedes et al., 2004). NE+NEA+LYN 100.99 31.80 440.16 PRO 13.41 3.06 – Since 2007, the LC-MS/MS has become the most popular method of MIF ––18.6 quantifying SOCs. Based on our summary in Table 2, analytical methods with LC-MS/MS are available for analyzing fifteen out of –: not available. a Adapted from Runnalls et al., 2010, estimated concentration in influent is not eighteen reported SOCs for environmental samples. However, there available. are still no analytical methods for eight (DIE, ETO, LYN, NGA, NOR, PRO, NTE, and NTL) of the twenty six selected SOCs in environmental samples. Development of LC-MS/MS methods able to analyze large a 3.2. Analytical methods for SOCs number of SOCs began 2009 with Sun et al. (2009) analyzing eight SOCs simultaneously in water samples, and Xu et al. (2010) analyzing Sensitive and accurate analytical methods are needed for the anal- seven SOCs simultaneously in aquatic products. ysis of micropollutants because they are present at μg/L or ng/L levels Three different ionization sources, i.e., electrospray ionization in the environment (Liu et al., 2009c). Studies on micropollutants (ESI), atmospheric pressure chemical ionization (APCI), and atmo- have not only enriched our insights on their occurrence and fate in spheric pressure photoionization (APPI) are now available for LC- the environment, but also enabled development of robust analytical MS/MS, which were all applied for monitoring of SOCs (Table 2). It methods (Fatta et al., 2007; Gabet et al., 2007; Gupta et al., 2011; is notable from Table 2 that the ESI mode is the most popular as it is Gorog, 2011). However, there are relatively few analytical methods also applicable to some other pharmaceuticals (Wong and MacLeod, for quantifying SOCs in environmental samples, and most are only ap- 2009). In Matejicek and Kuban (2007), four SOCs were simultaneously plicable to simultaneous analysis of one or a few SOCs (Lopez de Alda analyzed by LC-MS with both ESI and APCI modes, with the latter yield- and Barcelo, 2001a; Diaz-Cruz et al., 2003; Lopez de Alda et al., 2003; ing better performance. To our knowledge, this is the only study of SOCs Kuster et al., 2004). To strengthen these analytical methods, available available comparing different ionization sources. The results are not un- analytical methods of SOCs are summarized in Table 2. expected as the ESI mode is more susceptible to the matrix influence (Wong and MacLeod, 2009). However, in a recent comparative study 3.2.1. GC-MS based methods of five target pharmaceuticals analyzed by LC-MS/MS, the ESI mode GC-MS has been widely used for analysis of natural estrogens, an- showed the best performance (Garcia-Ac et al., 2011). This may be at- drogens and other EDCs in urine, meat and environmental samples tributable to the fact that other factors such as sample preparation, mo- (e.g., Fotsis, 1987; Seo et al., 2005; Liu et al., 2010c,d). To avoid ther- bile phase eluents as well as target analytes may also influence the mal decomposition and improve chromatographic separation and analysis performance of LC-MS/MS (Leinonen et al., 2002). For example, sensitivity of analysis, a derivatization procedure is necessary (Diaz- compared to APCI or ESI, APPI mode is considered to be more suitable Cruz et al., 2003). N-methyl-N-(trinethylsilyl)trifluoroacetamide for target chemicals with low polarity (Yamamoto et al., 2006). Detailed (MSTFA), N-(tert-butyldimethylsilyl)-N-methyl trifluoroacetamide information on improving the analysis performance of LC-MS/MS (MTBSTFA) and N,O-bis (trimethylsilyl) trifluoroacetamide (BSTFA) through sample preparation is summarized by Wong and MacLeod are the most commonly used derivatization reagents (Quintana et (2009). al., 2004). Among these, both BSTFA and MTBSTFA are derivatization Compared to other analytical methods, LC-MS/MS methods generally reagents for silylation; the silyl derivatives are formed by the dis- have the lowest LOD/LOQ, at around 1 ng/L or lower, although without placement of the active proton in ―OH, ―COOH, NH, ―NH2 and extensive sample preparation high LOD/LOQ of 10–50 ng/L is still ob- ―SH groups. In contrast, MSTFA can be used not only for silylation reserved (Viglino et al., 2008; Al-Odaini et al., 2010). Liquid chromatograph- action, but also for reactions with ketone groups (Hartmann and ic methods (LC-MS, LC-MS/MS) are superior to GC-MS or GC-MS/MS Steinhart, 1997; Shareef et al., 2006; Schummer et al., 2009; Fang et because direct analysis is possible without derivatization. However, in al., 2010a,b). As shown in Fig. 1, all SOCs described here have hydrox- some cases derivatization procedures can also greatly improve the analyt- yl or ketone groups. Therefore, when MSTFA is used as the derivatiza- ical performance of LC-MS/LC-MS/MS. In one LC-MS/MS analytical proto- tion reagent, analytical method with GC-MS or GC-MS/MS is col, the LOD was reported to be 20–170 times lower with dansyl chloride theoretically feasible for all of these SOCs. derivatization than that analyzed without derivatization (Yu et al., 2011). There have been some GC-MS analytical methods published for a Dansyl chloride enhances electrospray ionization (Anari et al., 2002), and few of SOCs in environmental samples. A GC-MS method with low has also been used in the analysis of natural estrogens in urine with LC- LOQ was first effectively developed in 2000 for LNG and NEA in waste- MS (Xu et al., 2005). water. In this method, a mixture solution of MSTFA, TMSI (trimethylsi- Methods using LC/HPLC for SOCs are also available, in which a lyliodide), and DTE (dithoerythritol) was used as the derivatization diode array detector was used (Lopez de Alda and Barcelo, 2000; reagent (Kuch and Ballschmiter, 2000). In Fernandez et al. (2007),NE Sole et al., 2000; Lopez de Alda and Barcelo, 2001b). However, the and NOG were derivatized with the mixture of N, O-bis (trimethylsilyl) corresponding LOD/LOQ was as high as 50 or 100 ng/L (Sole et al., 5156 Z. Liu et al. / Science of the Total Environment 409 (2011) 5149–5161

Table 5 Occurrence and fate of SOC in WWTP.

SOCs Country WWTP type (n) Analytical method Sample collection Inﬂuent Efﬂuent Removal References (ng/L) (ng/L) (%)

CMA China AS (1) UPLC-MS/MS N.M N.D N.D – Sun et al., 2009 CPA China AS (1) UPLC-MS/MS N.M N.D N.D – Sun et al., 2009 Malaysia EA-AS (1) LC-MS/MS Grab – b20 – Al-Odaini et al., 2010 GES US AS (1); TF (1); SBR (1) GC-MS Grab N.D N.D – Robert et al., 2007 China AS (1) UPLC-MS/MS N.M N.D N.D – Sun et al., 2009 HPC China AS (1) UPLC-MS/MS N.M N.D N.D – Sun et al., 2009 LNG Germany AS (1) GC-MS 6-h continuous – N.D-1 – Kuch and Ballschmiter, 2000 Spain AS (4) LC-MS 24-h composite N.D N.D – Sole et al., 2000 Spain AS (4) LC-MS 24-h composite b0.2–16.1 b0.2–4.0 −1100 to 93.2 Petrovic et al., 2002b France AS (3) GC-MS N.M – b2.5–7.2 – Labadie and Budzinski, 2005a France AS (1) GC-MS N.M – b2–5 – Labadie and Budzinski, 2005b US AS (1); TF (1); SBR (1) GC-MS Grab N.D N.D – Robert et al., 2007 France AS (2) LC-MS N.M – 0.9–17.9 – Vulliet et al., 2007 Spain AS (3) LC-MS/MS N.M – N.D – Kuster et al., 2008 China – (1) HPLC N.M 5.6 1.1 80.4 Pu et al., 2008 China – (1) ELISA N.M 6.5 1.3 80 Pu et al., 2008 Canada PPCTP (1) LC-MS/MS N.M 150–170 30 81.3 Viglino et al., 2008 Brazil – (1) LC-MS/MS N.M – N.D – Kuster et al., 2009 China AS (1) UPLC-MS/MS N.M N.D N.D – Sun et al., 2009 China – (1) HPLC N.M 74.3 8.1 89.1 Qiao et al., 2009 Sweden AS (3) LC-MS/MS N.M – N.D-1 – Fick et al., 2010a Malaysia EA-AS (1) LC-MS/MS Grab – b66 – Al-Odaini et al., 2010 MED US AS (1); TF (1); SBR (1) GC-MS Grab N.D N.D – Robert et al., 2007 MEP US PT (5); AS (5); OD/FP (2) GC-MS/MS Grab – N.D-14.7 – Kolodziej et al., 2003 Canada PPCTP (1) LC-MS/MS N.M N.D-5 N.D 100 Viglino et al., 2008 China AS (1) UPLC-MS/MS N.M N.D N.D – Sun et al., 2009 MGA Japan AS (2) UPLC-MS/MS Grab N.D N.D-0.35 – Chang et al., 2008 China AS (1) UPLC-MS/MS N.M N.D N.D – Sun et al., 2009 China AS (7) UPLC-MS/MS 24-h composite 1.9–9.3 N.D-0.7 79.5–100 Chang et al., 2011 MPA Japan AS (2) UPLC-MS/MS Grab 0.21–2.42 0.03–0.42 82.6–85.7 Chang et al., 2008 China AS (7) UPLC-MS/MS 24-h composite 18–58 N.D-1.1 96–100 Chang et al., 2011 MIF China – (1) UPLC-MS/MS 24-h composite 0.4–1.62 0.7–0.75 −75 to 53.7 Liu et al., 2010b China – (21) UPLC-MS/MS 24-h composite – 0.4–195 – Liu et al., 2010b NE Spain AS (4) LC-MS 24-h composite N.D N.D – Sole et al., 2000 Spain AS (4) LC-MS 24-h composite b0.2–8.9 b0.2–17.4 −2550 to 81.8 Petrovic et al., 2002b France AS (3) GC-MS N.M – b1.1–6.5 – Labadie and Budzinski, 2005a France AS (1) GC-MS N.M – b1–5 – Labadie and Budzinski, 2005b France AS (2) LC-MS N.M – 5.2–41 – Vulliet et al., 2007 Canada AS (3); TF/SC (1); AL (1) GC-MS Grab 0–224 0–159 78–100 Fernandez et al., 2007 Spain AS (3) LC-MS/MS N.M – N.D – Kuster et al., 2008 Canada PPCTP (1) LC-MS/MS N.M 70–205 53 61.5 Viglino et al., 2008 Japan AS (2) UPLC-MS/MS Grab N.D N.D – Chang et al., 2008 US – (7) UPLC-MS/MS N.M – N.D – Batt et al., 2008 Brazil – (1) LC-MS/MS N.M – N.D – Kuster et al., 2009 China AS (1) UPLC-MS/MS N.M N.D N.D – Sun et al., 2009 Malaysia EA-AS (1) LC-MS/MS Grab – 188 – Al-Odaini et al., 2010 China AS (7) UPLC-MS/MS 24-h composite 4.6–12 N.D 100 Chang et al., 2011 NEA Germany AS (1) GC-MS 6-h continuous – N.D – Kuch and Ballschmiter, 2000 China AS (1) UPLC-MS/MS N.M N.D N.D – Sun et al., 2009 NOG US AS (1); TF (1); SBR (1) GC-MS Grab N.D N.D – Robert et al., 2007 Canada AS (3); TF/SC (1); AL (1) GC-MS Grab 0–48 0–126 −93 to 0 Fernandez et al., 2007 Japan AS (2) UPLC-MS/MS Grab N.D N.D – Chang et al., 2008 China AS (2) LC-MS/MS MS 59 9.2 84.4 Liu et al., 2011 TRI US AS (1); TF (1); SBR (1) GC-MS Grab N.D N.D – Robert et al., 2007

AS: activated sludge process; EA-AS: extended aeration activated sludge process; TF: trickling ﬁlter; SBR: sequencing batch reactor; PPCTP: primary physico-chemical treatment plant; TF/SC: trickling ﬁlter/solid contact; AL: aerated lagoon; PT: primary treatment; OD/FP: oxidation ditch/facultative pond; N.M: not mentioned; N.D: not detected; –: not available; MS: mixed samples, for which three grabbed samples were mixed.

2000). Therefore, in most situations, they are not feasible for envi- 3.3. Occurrence and fate of SOCs in the natural environment ronmental samples. The newest analytical technology applied to SOCs and other micropollutants is laser diode thermal desorption 3.3.1. Estimated input concentrations of SOCs to WWTPs (LDTD)-atmospheric pressure chemical ionization (APCI) tandem Detection of micropollutants (at ng/L level or below) in influent spectrometry, in which a heat gradient volatilizes the analytes of and effluent of WWTPs is time-consuming, difficult and expensive, interest, and the volatilized analytes are then ionized in the APCI so approaches to estimate their input to WWTPs and possible concen- region upon entering the triple quadrupole system for detection. tration in effluent would be beneficial. Input of natural estrogens, an- By eliminating the LC step, the analysis time is shortened to only drogens and phytoestrogens has previously been estimated (Johnson 15 s, which is far faster than LC-MS/MS (Fayad et al., 2010; Viglino et al., 2000; Johnson and Williams, 2004; Liu et al., 2009b, 2010a), and et al., 2011). In addition, a method called enzyme-linked immuno- a recent study in France has predicted input of as many as 19 SOCs to sorbent assay (ELISA) was also applied for analysis of SOCs, but the WWTP based on their consumption (Besse and Garric, 2009). Pre- available method can only quantify LNG (Pu et al., 2008; Qiao et al., dicted concentrations in influent ranged from 0.08 to 188 ng/L 2009). (Table 4). Some predicted environmental concentrations (PECs) of Z. Liu et al. / Science of the Total Environment 409 (2011) 5149–5161 5157

SOCs in influent are far higher than predicted critical environmental that the three SOCs studied were easily biodegraded, and their bio- concentrations (CECs), indicating that a pharmacological effect degradation kinetics fit a pseudo first-order model well, in which would be expected in fish. CECs reflect expected bioconcentration their half-life times of biodegradation were 1.5, 1.7 and 3.0 h, respec- from water to a steady state fish blood plasma concentration equal tively. The results agree with observations at full-scale (Table 5). to the human therapeutic blood plasma level (concentration However, concentrations of the target SOCs in sludge were not mon- ratio=1; Fick et al., 2010b). For example, the influent PEC of MEP is itored, thus possible saturation of the sludge's sorption capacity was 15.64 ng/L, which is more than six-fold higher than its CEC of not considered. 2.1 ng/L. However, these PECs may still underestimate true effects of the SOCs because possible synergistic effects among various com- 3.3.3. Occurrence and fate of SOCs in other environment pounds are not considered. As removal of SOCs likely occurs within As with natural estrogens and androgens, the wide distribution of WWTPs, a more helpful comparison would be between effluent SOCs in the environment is attributed to effluent discharge from PECs and CECs. However, lack of information on removal of these WWTPs with increasing urbanization and regulation of wastewater SOCs by WWTP makes the prediction difficult, thus effluent PECs of treatment. From the limited data in Table 5, it is obvious that SOCs SOCs are not yet available. Nevertheless such prediction is a valuable in wastewater do enter receiving water bodies due to their incom- starting point. For accurate prediction, data on annual consumption of plete removal by WWTP; this may in fact be one of the main routes SOCs is critical. Unfortunately, there is very limited information, for of their dissemination in the environment. which only one other reference on annual consumption of SOCs in The occurrence of SOCs in surface water, groundwater, sediment, UK is available. Comparing the consumption data between France etc. is summarized in Table 6. While some SOCs are never detected, and UK, it appears that the consumption volume of each specific at least one SOC was found to exist in almost all environments. SOC varies greatly. For example, the annual consumption of DYD in Their wide distribution may have adverse effects on fish or other France is about 745 kg, and the corresponding value in the UK is aqueous wildlife. For example, the NOEC for LNG was reported to be about 209 kg, for which the former is over three times higher than as low as 0.8 ng/L (Zeilinger et al., 2009), and the concentration of the latter. However, the annual consumption of MEP in France is LNG in a Malaysia river was as high as 38 ng/L (Al-Odaini et al., only about 69 kg, but in UK the corresponding value is about 530 kg. 2010). This compound was even reported to exist in drinking water To facilitate comparison, their annual consumption data of SOCs is in- with the maximal concentration of 10 ng/L (Vulliet et al., 2011). Addi- cluded in Table 4. tional information on both the occurrence and latent risks of these SOCs is urgently needed. 3.3.2. Occurrence and fate of SOCs in WWTPs Unlike other industrial micropollutants such as bispenol A and 3.3.4. Removal of SOCs by physical means and chemical oxidation nonylphenol (Staple et al., 1998; Soares et al., 2008; Huang et al., in Removal of SOCs by existing WWTPs is not sufficient to prevent press), the predominant source of SOCs is the urine and feces excret- their wide distribution in the environment. Optimization of WWTP ed by premenopausal women. Therefore, if these compounds can be operational parameters provides a fundamental approach to increase completely biodegraded by WWTPs, their occurrence in the environ- the removal of SOCs. Apart from biological treatment, both physical ment (surface water, sediment, ground water, soil, etc.) can be elim- means and chemical oxidation have also been applied to micropollu- inated. Despite 10 years of research and progress in developing tants including natural estrogens/androgens, industrial chemicals, analytical methods, only a few studies report monitoring results on and pharmaceuticals (Snyder et al., 2007; Klavarioti et al., 2009; Liu the occurrence and fate of SOCs in WWTPs. et al., 2009a). Based on very limited data, removal efficiencies of MGA and MPA In the only currently published study evaluating physical removal by the conventional activated sludge process were 79.5 to 100%, and of SOCs, removal of NE and LNG by nano-filtration from two different 82.6 to 100% (Table 5), respectively (Chang et al., 2008, 2011). Log waters was studied by Dudziak and Bodzek (2009). The influence of

KOW values above 4 for these compounds suggest strong hydrophobic polymer type, molecular weight cut-off and desalting degree of the characteristics (Table 1), so sorption to sludge is likely a key mecha- membranes were examined in two waters, in which nanofiltration nism of their removal. Viglino et al. (2008) reported that MEP was was conducted under the following conditions: transmembrane pres- easily removed by physico-chemical processes. This was supported sure of 2.0 MPa, flow velocity of liquid over membrane surface in by the observations of Yu et al. (2011), in which concentrations of cross-flow of 0.85 m/s, stirring rate in dead-end flow of 250 rpm, MEP ranged from 5.7 to 53.5 ng/g in sewage sludge. and the temperature was 20 °C. Results indicated that cellulose ace- Reported removal efficiencies of LNG and NE varied greatly, from tate membrane showed higher relative removal efficiencies than the as high as 100% to as low as −2550% (Table 5). Based on Jason et al. polyamide membrane with average removal efficiencies of 74.1%

(2003), Log KOW values near 3.5 are most favorable for microbial bio- (NE) and 87.1% (LNG) for the former, and 60.3% (NE) and 70.8% degradation. If microbial degradation is the main removal mechanism (LNG) for the latter. The authors concluded that these differences of SOCs, WWTP operating conditions might be very important for were attributed to different degrees of desalting, while molecular their removal. Variable operating conditions at different WWTPs weight cut-off had no effect on removal of these compounds. Com- could be the inherent reason for the widely variable removal of the pared to pure membrane separation, processes that incorporate bio- two SOCs observed across the different WWTPs worldwide; these in- logical degradation with membrane filtration, e.g., membrane fluences are worthy of further research. bioreactor (MBR) technologies, represent a promising future direc- While studies based on full-scale WWTPs yield useful information tion of wastewater treatment (Basile et al., 2011). MBR technologies about the fate of SOCs, lab-scale studies provide a basic understand- have shown effective removal of natural and synthetic estrogens as ing of the fundamental mechanisms for the removal of the micropol- well as pharmaceuticals (e.g., Urase et al., 2005; Hu et al., 2007; Gusseme lutants. In lab-scale studies, wastewater constitutes and et al., 2009; Clouzot et al., 2010). However, review of the literature environmental factors such as dissolved oxygen (DO), hydraulic re- revealed no such studies on removal of SOCs, which would be of interest tention time (HRT) and sludge retention time (SRT), have been varied for future research. in order to determine the effect on EDCs (Liu et al., 2009a). However, Regarding chemical oxidation, Fu et al. (2007) studied ultrasound- very few lab-scale studies have been reported evaluating biological induced destruction of LNG and GES in aqueous solutions in a batch re- removal of SOCs. The removal of NOG, MPA and MGA by biodegrada- actor using a 1.1 W/mL sonication unit, and in a continuous flow reactor tion at lab-scale was studied by Chang et al. (2011). HgCl2 was used to using a 2.1 W/mL sonication unit. Degradation followed pseudo first- inhibit the biological activity of the sludge. These authors reported order kinetics, and low solution pH was favorable for degradation, 5158 Z. Liu et al. / Science of the Total Environment 409 (2011) 5149–5161

Table 6 Occurrence of SOCs in the various environments.

Surface water (ng/L) Tap Ground Sediment (ng/g) water water River Lake Dam River Soil Sludge (ng/L) (ng/L)

CMA N.D [1] N.D [1] – N.D [1] –– –– N.D [1] CPA N.D [2] N.D [1] N.D [2] N.D [1] – b7.1 [3] N.D – b68 [3] N.D [2] [3] DES N.D [2] – N.D[2] N.D [2] –– –– DRO – N.D [5] N.D [5] N.D [5] ––– GES N.D [1] N.D [1] N.D [2] N.D [1] –– –– N.D [2] N.D [2] N.D [6] HPC N.D [1] N.D [1] – N.D [1] –– –– N.D [1] N.D [2] LNG 38 [4] N.D [1] N.D [2] N.D [1] 7.4– N.D-2.18 24– 33–53 11.0 [5] [7] 52 [8] [8] N.D [6] 5.3 [5] 7.0 [5] N.D [2] N.D-19 N.D-4.7 N.D- N.D- N.D- [8] [9] 8.0 [9] 5.3 [9] 10 [9] Fig. 3. Destruction of micropollutants in clean water under sonolysis; power density

7.5 [10] 2.1 W/mL, pH 7.0, individual initial concentration (C0 =10 μg/L). b3.8– Adapted from Fu et al., 2007. 5.9 [12] MED N.D [6] –––– – –– fi MEP N.D [1] N.D [1] N.D [5] N.D [1] N.D [5] N.D-29 13– 22–31 ef ciency of the reactor was higher at lower power density. Degrada- [8] 28 [8] [8] tion characteristics of MEP, NE and LNG by ozone oxidation were stud- b0.4–1 N.D [5] 1.83– 5.7– ied by Broseus et al. (2009).Inthatstudy,second-orderrateconstants [16] 2.07 [17] 53.5 determined in lab-scale experiments at pH 8.10 were 558± N.D [1] [17] −1 −1 −1 −1 MGA N.D [13] N.D [1] – N.D [1] –– –– 9M S for MEP, 2215±76 M S for NE, and 1427± −1 −1 N.D-25 62 M S for LNG. As these constants are far lower than those of ste- [15] roidal estrogens (estrone, 17β-estradiol, estriol and ethinyl estradiol), it MPA N.D [13] –––– – –– suggested that the target SOCs reacted far slower with ozone, similar to N.D-34 trends in response to sonolysis in the report of Fu et al. (2007). [15] N.D [1] b46 [4] 4. Summary N.D [6] N.D [1] – – – NE N.D-2.9 2.7 [5] 2.8 [5] N.D [1] 4.2 5.6 N.D-1.08 91 105 Synthetic oral contraceptives are important emerging environ- [9] [5] [7] 93 [8] 106 [8] N.D-872 N.D- N.D- N.D-90 mental micropollutants about which little is known. The chemicals [11] 2.8 [9] 6.8 [9] [8] contained in synthetic oral contraceptive pills are not only strongly b1.3– progestagenic, but also have strong androgenic potencies. Areas in 2.5 [12] need of further study include development of sensitive and accurate N.D-1 analytical methods, removal performance in WWTPs, mechanisms [14]a N.D-16 of biological SOC removal, other efficient removal strategies for [15] SOCs, and toxicity studies based on environmentally relevant NEA N.D [1] N.D [1] – N.D [1] –– –– concentrations. N.D [6] LC-MS/MS is the most popular and predominant methods for anal- N.D [13] NOG N.D- –––– – –– ysis of SOCs. However, development of GC-MS based methods is still 8 [14]a needed and important because GC-MS is more widely available. N.D-6.2 Based on their molecular structures, all 26 SOCs discussed here can [15] theoretically be analyzed with GC-MS but should be demonstrated 3.7 [18] along with further efforts to decrease their LOD/LOQ. Also, methods TRI N.D [6] –––– – –– allowing simultaneous analysis of many SOCs are needed. To decrease – : not available; N.D: not detected; [1] Sun et al., 2009; [2] Matejicek and Kuban, 2007; their wide occurrence in the environment, efficient removal of SOCs [3] Perez-Carrera et al., 2010; [4] Al-Odaini et al., 2010; [5] Vulliet et al., 2008; [6] Velicu and Suri, 2009; [7] Lopez de Alda et al., 2002; [8] Viglino et al., 2011; [9] by WWTPs is crucial. Studies on removal of SOCs attributed to sludge Vulliet et al., 2011; [10] Qiao et al., 2009; [11] Kolpin et al., 2002; [12] Labadie and adsorption are needed as are studies on removal of SOCs by physical Budzinski, 2005a; [13] Chang et al., 2008; [14] Jeffries et al., 2010; [15] Chang et al., means and chemical oxidation. 2011; [16] Kolodziej et al., 2004; [17] Yu et al., 2011; [18] Liu et al., 2011. Although there have been a few studies on the toxicity of a small a Estimated from the figure. number of SOCs on fish, the toxicity of most SOCs to aquatic organisms remains unknown. while high temperature inhibited their degradation. Compared to other micropollutants studied (17α-estradiol, equilin, estrone, 17β-estradiol, References and ethinyl estradiol), LNG and GES were the least degradable com- Al-Odaini NA, Zakaria MP, Yaziz MI, Surif S. Multi-residue analytical method for human pounds by sonication (Fig. 3). Effects of power density, power intensity fl fi pharmaceuticals and synthetic hormones in river water and sewage ef uents by and reactor con guration on ultrasound assisted degradation of NOG solid-phase extraction and liquid chromatography-tandem mass spectrometry. J were studied by Suri et al. (2007). Destruction removal of NOG was Chromatogr A 2010;1217:6791–806. 67–95% under different power intensity systems within 40–60 min of Anari MR, Bakhtiar R, Zhu B, Huskey S, Franklin RB, Evans DC. Derivatization of ethiny- fi lestradiol with dansyl chloride to enhance electrospray ionization: application in contact time, and its rst order rate constant was calculated. Degrada- trace analysis of ethinylestradiol in rhesus monkey plasma. Anal Chem 2002;74: tion rate increased with increase in power intensity, while energy 4136–44. Z. Liu et al. / Science of the Total Environment 409 (2011) 5149–5161 5159

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