Analyses and decreasing patterns of veterinary antianxiety medications in soils

Journal of Hazardous Materials 275 (2014) 154–165

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Analyses and decreasing patterns of veterinary antianxiety medications in soils Jeong-Heui Choi a,b , Marc Lamshöft a , Sebastian Zühlke a , A.M. Abd El-Aty b,c , Md. Musfiqur Rahman b , Sung Woo Kim b , Jae-Han Shim b,∗∗ , Michael Spiteller a,∗ a

Institute of Environmental Research of the Faculty of Chemistry, Dortmund University of Technology, Otto-Hahn-Strasse 6, 44227 Dortmund, Germany Biotechnology Research Institute, College of Agriculture and Life Sciences, Chonnam National University, Yongbong-ro 77, Buk-gu, 500-757 Gwangju, Republic of Korea c Department of Pharmacology, Faculty of Veterinary Medicine, Cairo University, 12211 Giza, Egypt b

h i g h l i g h t s

g r a p h i c a l

a b s t r a c t

• The present study is the first record • • • •

for determination of antianxiety drugs in soils. Ultrasonic-assisted extraction and LC/MS/MS were used for extraction and analysis. Dissipations of the tested drugs were investigated using batch soil incubation experiments. Two kinetic models were calculated and validated according to SANCO guideline. Acepromazine was more adsorptive and degradable, while xylazine was more sustainable and mobile.

a r t i c l e

i n f o

Article history: Received 5 March 2014 Received in revised form 28 April 2014 Accepted 3 May 2014 Available online 12 May 2014 Keywords: Tranquilizers ␣-, ␤-blockers Orbitrap mass spectrometry Ultrasonic-assisted extraction Dissipation kinetics Adsorption–desorption isotherms

a b s t r a c t An ultrasonic-assisted extraction method was developed to detect 16 antianxiety medications in soil samples using liquid chromatography–high resolution mass spectrometry (LC–HRMS), Orbitrap mass spectrometer. The determination method resulted in satisfactory sensitivity, linearity, recovery, repeatability, and within-laboratory reproducibility. Acepromazine, azaperone, and xylazine were incubated in control, amended, and sterilized soils. The amendment with powdered blood meal affected the relatively fast dissipations of acepromazine, azaperone, and xylazine in the soils. Dissipation kinetics of acepromazine were consistent with bi-phasic kinetics (first-order multi compartment) and the other couples were fit to single first-order kinetics. A hydroxylated acepromazine was identified from soil samples using Orbitrap mass spectrometry. According to sorption batch experiments, the adsorption of acepromazine and azaperone was greatly high, whereas that of xylazine was relatively low. Xylazine was persistent in the incubated soils, and acepromazine demonstrated fast initial dissipation; hence, xylazine could have a potential harmful effect on the environment. To the best of our knowledge, this is the first report on the dissipation and adsorption–desorption patters of animal pharmaceutical tranquilizers and ␣, ␤-blockers. © 2014 Elsevier B.V. All rights reserved.

∗ Corresponding author. Tel.: +49 231 755 4080; fax: +49 231 755 4085. ∗∗ Corresponding author. Tel.: +82 62 530 2135; fax: +82 62 530 0219. E-mail addresses: [email protected], [email protected] (J.-H. Shim), [email protected] (M. Spiteller). http://dx.doi.org/10.1016/j.jhazmat.2014.05.005 0304-3894/© 2014 Elsevier B.V. All rights reserved.

J.-H. Choi et al. / Journal of Hazardous Materials 275 (2014) 154–165

1. Introduction Pets and livestock food-producing animals are given veterinary medications either to care for or prevent a disease or to fatten up. Psychological stability is also an important concern for healthy animals. Moreover, protecting animal safety and promoting animal welfare have been globally emphasized to produce safe and high-quality animal products from healthy livestock. Unfortunately, however, animal welfare is unattainable to petty stock farmers, and even developed counties continue to run concentrated animal feeding operations to make a huge profit and meet the high public demand. It should be given unrelenting efforts to conduct more advanced animal farming considering animal welfare. As of now, safe and correct use of veterinary medications in accordance with guidelines, and hygienic growing environment would be best to promise freedom against diseases and stress for animal welfare and safe animal products to consumers. The thing to consider at this point is that livestock wastewater and excretions are continuously formed while animals grow, although safe meat products are manufactured as a result of observance of safe use guidelines. Although inadmissible use of veterinary drugs is avoided actively, illegal discharge and incomplete purification of livestock wastewater and reuse of animal excretion are polluting aquatic and terrestrial environments. Active pharmaceutical ingredients can be introduced into soil through sludge land application, use of livestock wastes as fertilizers, and reclaimed water irrigation. Pollutants in soil may be accumulated in plants or migrate through soil intact or transformed and reach groundwater, finally resulting in pollution to the drinking water source [1]. The presence of significant amounts of residual pharmaceuticals and their potentially active metabolites in manure, sediment, sludge, and wastewater has been demonstrated by monitoring studies in the past few years [2–8]. Several tranquilizers and ␣, ␤-blockers have been employed to relief anxiety and stress of food-producing animals. Several hypnotic-sedatives are even injected into pigs to calm them during transportation to the slaughterhouse [9,10]. Therefore, slaughterhouse wastewater would be one of the main sources of pollution with veterinary drugs [11,12]. Likewise, on account of considerable risk of the residual veterinary medications in the environment, their environmental fate, including adsorption, desorption, transport, transformation, degradation, and biological accumulation has been comprehensively studied in water, sediment, and soil [13–20]. In particular, the mobility of contaminants in soil has been emphasized because it is directly linked to water resource quality. Vazquez-Roig et al. [7,21] were determined various type of pharmaceuticals in soils, sediments, and waters of the Spanish marshlands using pressurized liquid extraction (PLE) and liquid-chromatography tandem mass spectrometry (LC/MS/MS). They found that all pharmaceuticals (except one) were detected in waters, soils and sediments. Moreover, contamination by pharmaceuticals in that coastal wetland area affected ground, tap, and surface waters. Such contamination not only causes ecological problem to aquatic fauna but also constitutes potential risk to human health. Environmental fate is fundamentally predicted by laboratory batch experiments, including adsorption–desorption and incubation studies. However, there were no studies on the determination and dissipation of veterinary tranquilizers and ␣, ␤-blockers in soil. In order to extract various organic pollutants, including pesticides and veterinary drugs from soil, liquid–liquid extraction using organic solvents and diverse buffers has traditionally been employed as an exhaustive extraction method. Extractability, quickness, and performance were improved and automated by mechanical approach, such as pressurized liquid extraction (PLE) and microwave-/ultrasonic-assisted extraction (USE) [22–26]. Mechanical extraction methods are attractive because

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they are easy to control, consume less solvent, and can avoid manual handling errors. Herein, an USE approach was introduced to extract 16 tranquilizers and ␣, ␤-blockers from soil, and liquid chromatography–high resolution mass spectrometry (LC–HRMS) using Orbitrap MS was employed for quantitative and confirmatory analyses. The dissipation behaviors and adsorption–desorption properties were evaluated for three representative analytes, such as acepromazine, azaperone, and xylazine in soil batch experiments. 2. Experimental 2.1. Chemicals and reagents Acepromazine maleate, carazolol, chlorpromazine hydrochloride, fluphenazine dimaleate, mesoridazine benzenesulfonate, perphenazine, prochlorperazine dimaleate, promazine hydrochloride, propionylpromazine hydrochloride, (±)-propranolol hydrochloride, thioridazine hydrochloride, trifluoperazine dihydrochloride, triflupromazine hydrochloride, xylazine, and acepromazine-d6 hydrochloride (internal standard, IS) were purchased from Sigma–Aldrich (Taufkirchen, Germany). Azaperone (98.5%) and metoprolol fumarate were supplied from Dr. Ehrenstorfer (Augsburg, Germany) and the US Pharmacopeial Convention (MD, USA), respectively. The purities of chlorpromazine and fluphenazine were 95 and ≥90%, and the others were ≥98%. Ammonium formate (AF), ammonium hydroxide (NH4 OH), sodium hydroxide (NaOH), magnesium sulfate, and sodium chloride were obtained from Sigma–Aldrich, formic acid (FA) and mercuric chloride (HgCl2 ) were obtained from Merck (Darmstadt, Germany). Acetonitrile (MeCN), methanol (MeOH), and n-hexane were purchased from JT Baker (Deventer, the Netherlands), and ethylacetate (EtOAc) was from AppliChem (Darmstadt, Germany). Primary secondary amine (PSA) was obtained from Agilent Technologies (CA, USA). All solvents and reagents used were of high-performance liquid chromatography or analytical grade. 2.2. Standard solutions Standard stock solutions of all analytes, including IS were prepared in MeOH at 100 ␮g/mL. A multi-compound intermediate standard solution was prepared by mixing 16 stock solutions, and then serially diluted with blank soil extracts to obtain calibration standards at the lowest calibrated level (LCL) ×1, ×4, ×10, ×20, ×100, ×200, and ×400 ␮g/kg. The blank soil was confirmed previously, and none of the tested analytes were in the extract. IS was added at a concentration of 25 ␮g/kg to all calibration standards. Every stock solution was stored at–26 ◦ C in a dark amber bottle, and all calibration standards were kept at 4 ◦ C. 2.3. LC–high resolution mass spectrometry An HPLC system was operated with an Agilent 1200 Series (CA, USA), and a high resolution mass spectrometric detection coupled to LC was carried out with a Finnigan LTQ Orbitrap mass spectrometer (Thermo Scientific, MA, USA). An internal lockmass calibration method of the high-accuracy MS was carried out using n-butyl benzenesulfonamide (m/z 214.0896, [M+H]+ ); m/z 231.1162, [M+NH4 ]+ ) to detect the high accurate masses of the tested analytes. The details of the LC and MS conditions were the same as mentioned before in our previous study [27]. Herein the experimental set-up was shown as a supplementary material (Table S1). Supplementary table related to this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jhazmat.2014.05.005.

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Table 1 Physicochemical properties of the tested soils. Properties

Barop

Scheyern

Soil classification (USDA)

Silt loam, Haplic Cambisol

Loam, Calcaric Regosol

11 73 16 6.7 2.88 55.0

40 45 15 5.3 1.36 31.5

Texture analysis (USDA) Sand (0.05–2.00 mm, %) Silt (0.002–0.05 mm, %) Clay (<0.002 mm, %) pH Corg (%) Maximum water holding capacity (%)

comparing the mean concentration measured from the repeatability test with the corresponding matrix-matched standard working solution (unextracted standard, including IS) prepared in a blank soil extract. The relative standard deviation was calculated for repeatability and within-laboratory reproducibility. 2.7. Soil incubation with acepromazine, azaperone, and xylazine

2.4. Soil Two surface layered (0–10 cm) soils (Barop and Scheyern) were collected from areas with vegetation in Dortmund and München, Germany. Both samples were analyzed by LC–HRMS to prove that they contain none of the tested analytes and were used as blank samples. The soils were air-dried, ground with a mortar, and sieved with a 2-mm sieve. Their general characteristics are presented in Table 1. 2.5. Sample preparation Fortified air-dried Barop soil (5 g) with 0.2 mL of multicompound standard solutions or incubated wet-soil (corresponding to air-dried 5 g) was placed in a 50-mL polypropylene conical centrifuge tube, and the fortified soil was left undisturbed for 30 min to remove organic solvent. Two mL of water (1 mL, incubated wet soil samples) was added, followed by 2 mL of 2 M aqueous NaOH and 10 mL of EtOAc. Then, USE was carried using an ultrasonic water bath (Bandelin Sonorex Longlife, 35 kHz, Berlin, Germany) for 15 min. Vigorous shaking was performed manually before and after USE, and the samples were centrifuged at 5000 rpm for 5 min. Five mL of the supernatant was taken, 0.2 mL of IS (62.5 ng/mL) was spiked, and the whole mixture was evaporated to dryness under an N2 gas steam at 50 ◦ C. The dried sample was dissolved with 1 mL of MeOH followed by vortex-mixing with 1% aqueous FA (pH 3.5 adjusted with NH4 OH) at the same ratio. The mixture was partitioned with 0.5 mL of n-hexane and then centrifuged at 5000 rpm for 5 min. The bottom layer was injected into the Orbitrap MS. 2.6. Method validation The developed method was validated against criteria, such as lowest calibrated level (LCL), the matrix effect (ME), linearity, recovery, repeatability, and within-laboratory reproducibility. To assess sensitivity the LCL which is the lowest concentration to enable quantitation of analytes was investigated instead of limits of detection and quantitation. The commonly occurring ME during ionization of analytes in MS was evaluated by comparing the peak area of the matrix-matched standard solutions (LCL ×1 and ×20 ␮g/kg) with those prepared in the mobile phase, in six replicates each. A matrix-matched standard calibration curve was constructed by plotting the ratio of the response of the analyte ion to the response of the IS ion against the concentrations in ranges from LCL × 1 to LCL × 400 ␮g/kg. The determination coefficients (R2 ) obtained from the matrix-matched calibration curves were used to determine linearity. Recovery, repeatability, and withinlaboratory reproducibility were tested with fortified samples at three different concentrations (LCL ×1, ×5, and ×20 ␮g/kg) in sextuplicate. Recovery and repeatability were carried out on the same day, while the within-laboratory reproducibility was tested for three consecutive days. Percent recovery was calculated by

Experimental applications were carried out on 3 types of soils, such as control, amended, and sterilized soils. Sterilized soil was prepared by disinfection with HgCl2 , which are minutely described at the end of this paragraph. Powdered blood meal (biological fertilizer, 0.2 g) was added into 300 g of Barop and Scheyern soils for the amended and sterilized soils except for the control. Each stock solution of acepromazine, azaperone, and xylazine was fortified into the control, amended, and sterilized soils at 1 mg/kg dried soil and left on a table for 1 h to remove the organic solvent. The treated soils were homogenized by a tumbling mixer for 2 h. Subsequently, water was added up to 60% maximum water holding capacity of soils into the control and amended soils, and water containing 150 mg of HgCl2 (sterilizing agent, 500 mg/kg dried soil) was used for disinfection to prepare the sterilized soils. Water content in all soils was gravimetrically checked every two weeks. Blank samples without medications in the control, amended, and sterilized soils were also prepared. All soils were placed in a 1.5-L glass bottle and incubated in darkness at 24 ◦ C. Subsamples were collected from the incubation at 0 (2 h), 1, 3, 7, 14, 21, 30, 60, 90, and 120 d. 2.8. Adsorption–desorption studies Batch sorption experiments were performed according to the OECD Technical Guideline 106 [28]. Based on the incubation results in which the dissipation kinetics of acepromazine, azaperone, and xylazine were similar between Barop and Scheyern soils, only Barop soil was used for the sorption studies. Preliminary tests before the batch sorption experiment were conducted to estimate optimal soil/solution ratios as well as adsorption equilibration time. One or 2 g dried Barop soil was mixed with 0.01 M CaCl2 solution containing 0.1 mM HgCl2 as a bioinhibitor. The tested soil/solution ratios were 1:1, 1:5, and 1:25 for xylazine and 1:50, 1:100, and 1:200 for acepromazine and azaperone, respectively. Samples were equilibrated by shaking with an over-head shaker at 25 rpm overnight prior to adding standard solutions. Xylazine trials were carried out using a 15-mL polypropylene conical centrifuge tube and a concentration of 100 ␮g/L in a parallel method (n = 3), while acepromazine and azaperone were tested using a glass bottle with a PBT cap inserting a PTFE-faced silicon liner at 1000 ␮g/L using a serial method (n = 3). All soil solutions were covered with aluminum foil to protect the chemicals from light and were then shaken. Soil solution samples taken at 10 min, and at 1, 4, 8, 24, 48, and 72 h were centrifuged at 7000 rpm for 10 min, and the supernatant was analyzed by LC–Orbitrap MS. Soil solution samples of acepromazine and azaperone were transferred to a glass vial to avoid adsorptive loss followed by centrifugation. Individual control (drugs only) and blank (soil only) samples for every drug were also examined using the same steps as the fortified systems to check stability, possible adsorption of the analytes onto the vessels, and to assure interference and contamination of the soil, respectively. The adsorption isotherms of xylazine were determined using six different concentrations (50, 100, 200, 500, 1000, and 2000 ␮g/L), optimal soil/solution ratios, and a shaking period of 48 h in Barop soil, whereas acepromazine and azaperone adsorption isotherms were carried out at five concentrations (400, 600, 1000, 2000, and 3000 ␮g/L). The next steps proceeded as described above. The xylazine desorption study was carried out by replacing the supernatant of the adsorption study with a fresh 0.01 M CaCl2 solution to

J.-H. Choi et al. / Journal of Hazardous Materials 275 (2014) 154–165

keep the aqueous solution exactly at 5 mL. The polypropylene conical centrifuge tubes were shaken for 48 h followed by centrifugation at 7000 rpm for 10 min, and then the supernatants were analyzed. All measurements were performed in duplicate. 2.9. Data computation

C = C0 e−kt

(t/ˇ + 1)

ln 2 or ˇ(21/˛ − 1) = k ln 10 or ˇ(101/˛ − 1) k

The goodness of fit for the FOMC and SFO models was estimated by comparing with the chi-square (2 ) test and the tabulated 2 (2tab ). The 2tab was calculated with the CHIINV (˛,m) function in Microsoft Office Excel. The goodness of the fit model was expressed with a percent error (%), which was directly calculated from the following equation when the calculated value of 2 was equal to or smaller than the standard 2tab values at the 5% significance level and the given degrees of freedom (number of measurements minus number of model parameters): 2



mads s (ti ) × 100(%) m0

m0 = C0 · V0 where Ati is the adsorption percentage at time point ti (%), mads s (ti ) is the mass of the tested substance adsorbed on the soil at time ti (␮g), m0 is the mass of the tested substance fortified in the ads (t ) is the concentratest tube at the beginning of the test (␮g), Caq i tion of the tested substance in the aqueous solution taken at time ti (␮g/mL), and C0 and V0 are the initial concentration (␮g/mL) and volume (mL) of the aqueous solution at the beginning, respectively. In the results of the adsorption isotherm experiments, Csads (eq) ads (eq), and log-transformed C ads (eq) and was plotted vs. Caq s log Csads (eq) were also plotted. The graphs were fitted to a linear equation and Freundlich adsorption isotherms, respectively:

log Csads (eq) = log KFads +

˛

where C is the concentration (␮g/kg dry soil) of the tested substance present at time t (days), C0 is the initial concentration applied at time 0, k is the rate constant, ˛ is the shape parameter determined by coefficient of variation of rate constant values, and ˇ is the location parameter. The k value in the SFO kinetic and the ˛ and ˇ values in the FOMC kinetic were employed to calculate Deg T50 and T90 (DT50 and DT90 ) which are the times elapsed until 50 and 90% of the initial substance concentration has declined.

DT90 =

Ati =

ads Csads (eq) = Kdads · Caq (eq)

C0

DT50

equilibrium time. A was calculated according to the following equations:

ads mads s (ti ) = m0 − Caq (ti ) · V0

2.9.1. Incubation study Dissipation kinetics were created according to SANCO/10058/ 2005 guideline, version 2.0 [29]. The dissipation kinetics of acepromazine, azaperone, and xylazine were calculated using single first-order (SFO) or bi-phasic kinetics, Gustafson and Holden model. The Gustafson and Holden model which was modified by the Forum for the Co-ordination of Pesticide Fate Models and Their Use (FOCUS) was used herein. The bi-phasic Gustafson and Holden model was denoted to a first-order multi compartment (FOMC) in the present study. The SFO and FOMC equations were as follows, respectively:

C=

157

(C − O)2 ¯ (error/100 × O)

 error = 100 ·

1 2tab

·

2

 (C − O)2 ¯2 O

where C is the calculated concentration, O is the observed concen¯ is the mean of all observed concentrations. tration, and O Confidence was assessed with an Excel paired two-sample ttest, which was also used to evaluate p-values between control, amended, and sterilized soils. Fitting the kinetic models and calculating DT50 , DT90 , and percent error values were carried out using an Excel spreadsheet provided at the FOCUS website (http://viso.ei.jrc.it/focus/). 2.9.2. Adsorption–desorption study The percentage adsorption (A) of each medication onto soil was plotted vs. time (t) to estimate optimal soil/solution ratio and

1 ads (eq) · log Caq n

where Csads (eq) is the concentration of the tested substance adsorbed onto the soil at adsorption equilibrium (␮g/g), Kdads and

KFads are the linear and Freundlich adsorption coefficients, and n is a regression constant. Kdads and KFads is the adsorption capacity of the tested substance to the soils. The batch desorption experimental results for xylazine were des (eq) and fitted by the plotted using log Csdes (eq) versus log Caq des (eq) are the conFreundlich desorption isotherm. Csdes (eq) and Caq centration of the tested substance adsorbed on the soil (␮g/g) and in the aqueous phase (␮g/mL), respectively at the desorption equilibrium. The adsorption coefficient (KOC ) normalized to soil organic carbon (%OC) was calculated using the adsorption coefficient (Kd ) using the following equation:

KOC = Kd ·

100 %OC

The hysteresis coefficient, H, was calculated for the adsorption–desorption isotherms according to the following formula [30]: H=

1/n of desorption 1/n of adsorption

where 1/n·desorption and 1/n·adsorption are the Freundlich constants obtained for the adsorption–desorption isotherms, respectively. The leaching potential of xylazine in soil was estimated by using the following empirical model of Gustafson [31], the groundwater ubiquity scores (GUS), as described by the following equation. GUS = log(DT50 ) × (4 − log KOC ) 3. Results and discussion 3.1. Optimization of sample preparation Stoob et al. [26] had chosen PLE as an exhaustive extraction method to determine five sulfonamide antibiotics (sulfadiazine, sulfadimethoxine, sulfamethazine, sulfamethoxazole, and sulfathiazole) in aged soil samples amended with manure. Chitescu et al. [24] resulted in better extraction efficiencies using PLE for the simultaneous determination of 42 compounds (pharmaceuticals,

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Fig. 1. Extraction efficiency (%) of the tested chemicals by pressurized liquid extraction (Ext 1) and ultrasonic-assisted extraction with varying extraction solvents: Ext 2 (EtOAc), Ext 3 (water–EtOAc), Ext 4 (water–2% NaOH–EtOAc), and Ext 5 (water–2% NaOH–MeCN).

azole biocides, and fungicides) in soil and plant samples, compared to those of the USE method. PLE was first tested for the analytes in soil in the present study because it was used to quantify the same analytes in powdered blood meal in our previous study [9]. However, as shown in Fig. 1, the results (Ext 1) of PLE were <70% except for carazolol (78%), metoprolol (93%), propranolol (94%), triflupromazine (82%), and xylazine (84%). The previous PLE conditions optimized to the blood meal might be not suitable for soil samples. Förster et al. [25] developed a microwave-assisted extraction method to analyze aged sulfadiazine and its two metabolites (N-acetylsulfadiazine and 4-hydroxysulfadiazine) residues in soils. The extraction efficiencies of the targeted compounds using microwave-assisted extraction were similar or higher than those obtained from PLE. In this respect, USE was introduced as an alternative extraction method in this study. The extraction solvent used in USE is a critical determinant of good recovery for the tested analytes. Four different extraction solvents were investigated as follows: EtOAc (10 mL, Ext 2), water–EtOAc (4–10 mL, Ext 3), water–2% NaOH–EtOAc (2–2–10 mL, Ext 4), and water–2% NaOH–MeCN (2–2–10 mL, Ext 5). Nothing was extracted with EtOAc (Ext 2), and adding water did not enhance extractability of EtOAc (Ext 3). Azaperone (log P 2.50), metoprolol (log P 1.79), xylazine (log P 2.37), and the other analytes had log P values > 3, which were predicted values from ACD/PhysChem Suites computer software (ACD/Labs, www.chemspider.com); hence, their water solubilities will be negligible. On the other hand, most analytes are weak basic compounds with dissociation constants (pKa) of 7.5–9.7 [32–35]. Therefore, the tested analytes would be partially ionized in neutral water. However, adding water will extend the surface area to contact soil matrices and the analytes rather than increasing water solubility of the analytes by ionization, finally leading to increased interactions, such as hydrogen bonding, polar interactions, interactions with metallic cations, van der Waals forces, and hydrophobic effects between soil constituents and the analytes. Adding NaOH solution dramatically increased all recoveries in Ext 4 (86–112%) and Ext 5 (68–106%). Aqueous NaOH solution suppressed ionization and increased hydrophobicity of the analytes, and could have masked potentially active sites in soil components, thereby enhancing solubility of the analytes in EtOAc and MeCN. The formation of an emulsion with the soil matrix, water, and EtOAc during hand shaking and USE also contributed to partitioning of the analytes into the organic phases from soil.

EtOAc was an effective solvent on the non-ionized or neutral analytes as the results of Ext 4; however, EtOAc did not dissolve the analytes spiked into the soil samples in Ext 1. These results were probably due to stronger interactions between the analytes and soil constituents than those with EtOAc. MeCN led to a single-phase solvent extraction of the soil matrix during USE in the Ext 5 experiment because of the miscibility of MeCN with water. Magnesium sulfate (4 g) and sodium chloride (0.5 g) were added to separate MeCN from water in the single-phase extract by referring to the original QuEChERS (quick, easy, cheap, effective, rugged, and safe) method [36]. Although the Ext 5 experiment generated good recoveries > 70% exclusive of perphenazine (68%), it was not attractive, compared to the Ext 4 method. Therefore, we employed an USE method and a water–2% NaOH–EtOAc combination extraction solvent to extract the 16 tranquilizers and ␣, ␤-blockers in soil. 3.2. High-accuracy mass spectrometry Orbitrap MS was used for the high-accuracy mass measurements of the analytes. The ion chromatogram (XIC) was reconstructed from the total ion chromatogram (TIC) based on an accurate mass and a 2-ppm mass tolerance window for identification and quantitation of the analytes. All of the detected experimental masses were matched with a protonated molecule ([M+H]+ ) with mass errors from −0.267 to 0.069 ppm. Accurate and experimental masses of the analytes are given in Table 2. 3.3. Method validation All of the method validation results are shown in Table 3. The LCL was assessed with matrix-matched standard solutions for the sensitivity of the developed method. A serial dilution with blank sample extracts was carried out to acquire the lowest quantitative concentration of the analytes. The LCL levels were 0.075–0.5 ␮g/kg. The peak area of the analytes in the mobile phase (A) was subtracted from those in blank sample extracts (B), which was divided by B and multiplied by 100 to calculate the percent ME. The MEs ranged from −17.3 to −3.4, which indicated ion suppression of all analytes in electrospray ionization Orbitrap MS. These ME values were not considerable unlike the preceding studies using blood meal, which was attributable to different co-extracted matrix

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159

Table 2 Accurate mass measurements of the protonated analytes ([M+H]+ ) in the LTQ–Orbitrap MS using a matrix-matched standard at LCL × 5 ␮g/kg. Protonated molecule ([M+H]+ )

Compound

Acepromazine Azaperone Carazolol Chlorpromazine Fluphenazine Mesoridazine Metoprolol Perphenazine Prochlorperazine Promazine Propionylpromazine Propranolol Thioridazine Trifluoperazine Triflupromazine Xylazine Acepromazine–d6 a

Mass error

Formula

RTa

Theoretical

Experimental

mDa

ppm

C19 H23 N2 OS C19 H23 FN3 O C18 H23 N2 O2 C17 H20 ClN2 S C22 H27 F3 N3 OS C21 H27 N2 OS2 C15 H26 NO3 C21 H27 ClN3 OS C20 H25 ClN3 S C17 H21 N2 S C20 H25 N2 OS C16 H22 NO2 C21 H27 N2 S2 C21 H25 F3 N3 S C18 H20 F3 N2 S C12 H17 N2 S C19 D6 H17 N2 OS

5.92 5.19 4.92 6.75 7.09 5.43 3.34 6.73 7.13 6.11 6.50 5.25 7.27 7.45 7.15 3.54 5.90

327.15256 328.18197 299.17540 319.10302 438.18214 387.15593 268.19072 404.15579 374.14522 285.14200 341.16821 260.16451 371.16102 408.17158 353.12938 221.11070 333.19022

327.15256 328.18193 299.17541 319.10297 438.18203 387.15588 268.19069 404.15573 374.14516 285.14201 341.16821 260.16452 371.16094 408.17154 353.12935 221.11069 333.19009

0.005 −0.035 0.009 −0.055 −0.117 −0.051 −0.047 −0.060 −0.058 0.015 0.001 0.018 −0.074 −0.043 −0.026 −0.002 −0.127

0.014 −0.106 0.031 −0.172 −0.267 −0.132 −0.177 −0.148 −0.156 0.052 0.002 0.069 −0.200 −0.105 −0.074 −0.009 −0.381

Retention time.

components of soil with those of blood meal. The developed method recorded good linearities (R2 ) of 0.9977 − 0.9999 in the quantitative ranges from LCL × 1 to LCL × 400 ␮g/kg. Recovery was evaluated with three different concentrations in sextuplicate. All recoveries were >70% although thioridazine was 66.2 and 58.9% at concentrations of LCL × 1 and × 5 ␮g/kg, respectively. Repeatability and within-laboratory reproducibility generated good levels of <15%, except for reproducibility (18.1%) of thioridazine at LCL × 5 ␮g/kg. The present study was more sensitive than those of previous studies, whereas recovery, repeatability, and within-laboratory reproducibility were similar to those of previous studies. The developed method for the determination of 16 tranquilizers and ␣, ␤-blockers in soil was reliable, based on the validation results, and further trials with aged soil samples will make the method more practical. 3.4. Dissipation of acepromazine, azaperone, and xylazine The residues of acepromazine, azaperone, and xylazine were monitored in the control, amended, and sterilized soils via the developed sample preparation and high resolution mass spectrometric detection methods during 120 d incubation. The extracts

that were out of the linear range were diluted five times with mobile phase, and quantitation errors were small due to the small MEs of the analytes and the use of internal calibration. As given in Fig. 2, all chemicals were more persistent in sterilized Barop and/or Scheyern soils, and were less persistent in the amended soils, compared to those in the control soils. The two-tailed p-values of acepromazine derived from a paired t-test comparing the control and amended Scheyern soils and of xylazine from the control and amended INFU soils were >0.05. Whereas a p < 0.05 was calculated for the other comparisons, indicating that the amendment was effective for dissipating of the medications with 95% confidence intervals. Microbial population decreases by sterilization and their growth by amendment of blood meal may be predominant factors determining the persistence of the chemicals in the soils [19,37]. All medications sharply decreased in the first 7 d of all incubation experiments even in the sterilized soils. Photolysis, vaporization, and volatilization affect fast initial dissipation of organic pollutants in the field. However, this was a laboratory batch experiment and the three chemicals have a low Henry’s law constant (8.91 × 10−15 –2.09 × 10−9 atm-m3 /mol) and vapor pressure (7.34 × 10−7 –1.79 × 10−5 mmHg, 25 ◦ C) predicted from EPISuite. The three chemicals may accumulate in soil rather than escape into the atmosphere. Adsorption of the medications

Table 3 The lowest calibrated level (LCL, ␮g/kg), matrix effect (ME, %), linearity (R2 ), trueness (recovery, %), repeatability (RSD, %) and within-laboratory reproducibility (RSD, %) of the ultrasonic-assisted extraction method. Compound

Acepromazine Azaperone Carazolol Chlorpromazine Fluphenazine Mesoridazine Metoprolol Perphenazine Prochlorperazine Promazine Propionylpromazine Propranolol Thioridazine Trifluoperazine Triflupromazine Xylazine

LCL (␮g/kg)

0.075 0.25 0.15 0.075 0.25 0.15 0.5 0.25 0.25 0.5 0.15 0.15 0.5 0.5 0.075 0.25

ME (%, n = 12)

−13.7 −5.1 −3.4 −17.3 −8.6 −7.8 −4.5 −9.7 −11.4 −12.0 −13.2 −4.2 −13.3 −12.5 −14.1 −6.1

Linearity (R2 )

0.9999 0.9993 0.9995 0.9999 0.9999 0.9977 0.9997 0.9999 0.9999 0.9999 0.9987 0.9996 0.9982 0.9997 0.9998 0.9997

Recovery (repeatability), %, n = 6

Within-laboratory reproducibility, %, n = 18

LCL × 1 (␮g/kg)

LCL × 5 (␮g/kg)

LCL × 20 (␮g/kg)

LCL × 1 (␮g/kg)

LCL × 5 (␮g/kg)

LCL × 20 (␮g/kg)

94.7 (6.7) 102.6 (3.1) 93.5 (7.6) 102.9 (8.2) 95.9 (10.1) 88.8 (5.8) 83.0 (7.3) 102.4 (11.1) 96.7 (7.6) 79.0 (13.4) 93.6 (4.4) 101.3 (4.1) 66.2 (12.3) 94.4 (6.2) 94.3 (9.8) 93.9 (2.0)

91.8 (9.1) 92.3 (6.1) 89.8 (6.1) 88.7 (4.2) 94.8 (6.7) 78.6 (4.4) 90.0 (5.0) 91.1 (6.1) 97.5 (3.7) 78.3 (2.4) 89.1 (8.4) 95.3 (2.9) 58.9 (3.4) 93.6 (4.2) 86.3 (5.0) 100.6 (1.8)

89.6 (4.4) 98.3 (2.5) 85.2 (6.3) 94.6 (6.0) 99.9 (3.7) 79.5 (3.3) 90.8 (1.5) 99.2 (7.1) 98.2 (2.2) 94.6 (2.7) 92.7 (3.2) 94.3 (2.0) 81.5 (9.5) 94.5 (3.1) 91.6 (5.4) 100.3 (0.9)

8.8 7.8 5.5 13.0 7.1 14.9 5.0 9.5 9.0 7.7 12.3 6.2 11.1 7.9 9.6 2.9

9.3 5.1 3.3 10.1 6.7 10.6 3.5 6.9 8.9 12.5 6.8 5.3 18.1 6.3 11.5 3.4

4.5 2.9 3.2 6.1 4.7 9.3 1.5 4.3 5.1 6.1 4.1 2.3 9.6 3.7 3.8 1.5

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Fig. 2. Dissipation kinetics of the chemicals in the control, amended, and sterilized soils: first-order multi compartment kinetics (acepromazine), single first-order kinetics (azaperone and xylazine).

to the soils was likely to result in a fast initial dissipation in the sterilized soils, instead of biological degradation. The three medications were not steadily decreased but increased after 7 or 14 d in the sterilized soils. Sterilization usually alters the chemical and physical properties of soil [38,39]. The changed properties of the soil following HgCl2 treatment might assist in release of the adsorbed chemicals into the soils, thereby increasing their residues. The increased residues found after the middle incubation time did not allow appropriate dissipation kinetics. The dissipation behavior of acepromazine, azaperone, and xylazine between the Barop and Scheyern soils was nearly the same in the control and amendment soils, indicating non-significant pvalues > 0.05. Statistically significant differences of azaperone and xylazine between in the control Barop and Scheyern soils were obtained (p < 0.05), but acepromazine was not significant (p > 0.05). Acepromazine in the control and amended soils decreased significantly in the first 30 d, but it stabilized during subsequent days. SFO kinetics has been usefully employed to plot residual concentration changes over time for dissipation or degradation of substances in soil. However, the FOMC kinetics fit the dissipation behaviors of acepromazine much better than the SFO kinetics, and the inputted parameters and outcomes are placed in Table 4. Fast initial dissipations of azaperone and xylazine were not obvious, and slow declines were observed after 7 d. SFO was applied to fit their dissipation behaviors. The inputs in and outcomes from SFO are described in Table 5. The C0 , ˛, k, and ˇ values were adjusted to better fit the SFO and FOMC kinetics to the experimental data. DT50 values

of acepromazine calculated by FOMC kinetics were 4.1–7.0 in the control and amended soils, and DT90 values were 45.3–472.8. In the amended soils, DT90 values of acepromazine shortened more compared to those in the controlled soils. Microbial biomass in soil decreases during incubation due to a lack of exogenous nutrition or energy supply [19,40]. However, an addition of blood meal as a source of nutrients and carbon may maintain microbial populations longer than that in the control soils; finally maintained microbial activities could decompose the chemicals more actively and for a longer period. Although most DT50 and DT90 values of azaperone

Table 4 First-order multi compartment kinetic properties for the dissipation of acepromazine in the soils. FOMC

Control

Amended

Barop

Scheyern

Barop

Scheyern

Parameters C0 (␮g/kg) ␣ ␤

800 0.40 1.50

900 0.70 2.40

700 0.50 1.50

800 0.90 3.80

Endpoints DT50 DT90

7.0 472.8

4.1 62.0

4.5 148.5

4.4 45.3

Assessments Error (%) t-Test

13.7 p > 0.05

10.3 p > 0.05

14.4 p > 0.05

14.3 p > 0.05

J.-H. Choi et al. / Journal of Hazardous Materials 275 (2014) 154–165

80 60 40

80

O N

CH3

40 S

20

Acepromazine 317 319 321 323 325 327 329 331 m/z

0

RT: 3.76 PA: 19959812

100

100

80

Relative Abundance

Relative Abundance

H+

CH3 N CH3

60

0

20

RT: 5.88 PA: 57047696

327.15275 C 19 H 23 O N 2 S = 327.15256 0.11804 ppm

100

Relative Abundance

Relative Abundance

100

161

60 40 20

343.14755 C19 H23 O2 N2 S = 343.14748 0.20399 ppm

CH3 N CH3

H+

O

80

N

60

HO

40

CH3

S

7-Hydroxyacepromazine

20 0 100

180

260

340 m/z

420

500

0 0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

Time (min) Fig. 3. Extracted ion chromatograms of acepromazine (RT 5.88) and a hydroxylated acepromazine (RT 3.76), and the accurate masses and the related elemental composition.

and xylazine were beyond the batch study period (120 d), their values in the amended soils were much shorter in the same manner. All kinetic fits were visually acceptable, and error values were <15%. The error level should not exceed 15% according to SANCO Guideline [29]. The two-tailed p values > 0.05 between the kinetic predictions and the experimental data at a 95% confidence level, showed a nonsignificant difference between the two datasets, suggesting that experimental data place within an error tolerance of the kinetic predictions. Therefore, the goodness of kit and confidence for agreement between the kinetic predictions and the experimental data were good for all of the kinetic models used.

Table 5 Single first-order kinetic properties for the dissipations of azaperone and xylazine in the soils. SFO

Control

Amended

Barop

Scheyern

Barop

Scheyern

Azaperone Parameters C0 (␮g/kg) k

850 0.003

890 0.003

800 0.006

750 0.004

Endpoints DT50 DT90

231.0 767.5

277.3 921.0

115.5 383.8

173.3 575.6

Assessments Error (%) t-Test

4.5 p > 0.05

4.4 p > 0.05

5.4 p > 0.05

7.0 p > 0.05

Xylazine Parameters C0 (␮g/kg) k

820 0.005

920 0.005

850 0.006

890 0.008

Endpoints DT50 DT90

138.6 460.5

138.6 460.5

115.5 383.8

92.4 307.0

Assessments Error (%) t-Test

8.6 p > 0.05

4.3 p > 0.05

5.2 p > 0.05

7.7 p > 0.05

Most derived endpoints, such as DT50 and/or DT90 of the chemicals exceeded the batch study period (120 d) due to the high persistence of azaperone and xylazine and the slower degradation of acepromazine in the middle and late part of the incubation. Regulatory endpoints of parent compounds and metabolites are used as triggers for higher-tier experiments [29]. However, endpoints should be used after much debate for higher-tier experiments regarding risk assessments on soil, organisms, and ground water, and more laboratory studies with different soil types and a longer duration and field dissipation studies need to be additionally conducted. All of the incubated soil samples were screened in full-scan mode (m/z 100–500) of Orbitrap MS to detect the metabolites of acepromazine, azaperone, and xylazine reported in our previously published article [27]. Nothing agreeing their accurate masses and elemental compositions was excavated from the TICs. However, the sharp peak was extracted at a retention time (RT) of 3.76 and m/z 343.14755, and its most probable elemental composition was C19 H23 O2 N2 S with a mass error of 0.20399 ppm, corresponding to a protonated molecule of hydroxylated acepromazine as shown in Fig. 3. 7-Hydroxyacepromazine and 4,7-dihydroxyacepromazine have been found from administered animal blood and urine in the literature [41,42]. Although the correct carbon position of the hydroxylation in the detected hydroxylated acepromazine was unclear, fragmentation of the hydroxylated acepromazine was elucidated in Fig. 4 in accordance with 7-hydroxyacepromazine. Consequently, the peak detected at RT 3.76 was predicted to be a hydroxylated acepromazine according to the elemental composition and possible fragmentation. Agricultural chemicals that enter soil are dissipated and mineralized by adsorption, chemical reactions, and microbial metabolism. All chemical and metabolic reactions with pesticides do not always succeed in complete detoxication, degradation, or mineralization. A parent pesticide molecule could be converted to a more toxic substance or a larger and more complex molecule [43]. Enzymatic reactions by living organisms in soil play a leading role in conjugation and oligomerization. Conjugation forms a linkage between cell constituents and activated metabolites of the parent compound, thereby creating glycoside, amino acid, and

162

J.-H. Choi et al. / Journal of Hazardous Materials 275 (2014) 154–165 FTMS + cESI Full ms3 [email protected] [email protected]

CH3 N CH3

CH

208.11216 C15 H14 N= 208.11208 0.41595 ppm

100 90 80

Relative Abundance

100

N

60

250.12265 C17H16 ON = 250.12264 0.02654 ppm

40 20 160

200

70

240 m/z

280

CH3

295.18085 C19 H23 ON2 = 295.18049 1.21037 ppm

222.09130 C15 H12 ON = 222.09134 -0.19556 ppm

80

0 120

Relative Abundance

O

N

312.12930 C18 H 20 ON2 S= 312.12909 0.69676 ppm H N

320

CH3 O

N

60

N HO

50 – H2O

40

·

CH2

S

256.07913 C15 H14 ONS= 256.07906 0.27632 ppm

CH3 N CH3

O N

30

238.06860 C15 H12 NS= 238.06850 0.44884 ppm

20

CH3 N CH3

O HO

S

N

270.05829 C15 H12 O2 NS= 270.05833 -0.13807 ppm

·

210

220

230

240

250

260

270

280 m/z

290

300

310

320

S

HO

330

H+

O N

CH3

326.14484 C19 H 22ON 2S = 326.14474 0.30927 ppm

10 0 200

CH3

S

340

CH3

S

343.14743 [M+H]+ C19 H 23 O 2N 2S= 343.14748 -0.13047 ppm

350

360

Fig. 4. MS2 and MS3 collision-induced dissociation fragmentations of 7-hydroxylacepromazine.

sulfur conjugates and alkylated, acylated, and methylated compounds. Oligomerization is involved in a condensation reaction of several units of the parent compound or in secondary conjugation of the parent compound with cellular components [44]. Accordingly, all incubated samples were additionally detected in the scan ranges of m/z 500–1000 and m/z 1000–2000 by Orbitrap MS to identify the conjugated and oligomerized analytes. However, no distinguishable peaks from the blank samples were not detected in the incubated samples and in the retrospective data processing of the basic data detected in the scan range of m/z 100–500. 3.5. Soil sorption studies for acepromazine, azaperone, and xylazine The soil/solution ratio based on the percentage of chemicals adsorbed to soil was selected at >20% and preferably >50%. The optimal ratios of acepromazine, azaperone, and xylazine were 1:100, 1:200, and 1:2.5 in Barop soil, respectively; hence, the ratios were much different between the chemicals as shown in Fig. 5. According to the control experimental results, acepromazine, azaperone, and xylazine provided 105 ± 3.4, 101 ± 3.3, and 97 ± 2.4% recovery, respectively. Therefore, the adsorption of acepromazine and azaperone onto the glasses and caps inserting a PTFE-faced silicon liner, and of xylazine onto the polypropylene apparatuses was assumed to be negligible. After shaking acepromazine and azaperone in each glass bottle using a serial method during the batch soil experiment, additional centrifugation of the soil solution samples in a polypropylene microcentrifuge tube was responsible for approximately 7% and 10% losses, respectively. Also, adsorptive losses of acepromazine and azaperone were a maximum of 45% and 35% if a polypropylene tubes and caps are used for shaking. Therefore, adsorption batch experiments of acepromazine and

azaperone should be carried out using glass apparatuses to minimize adsorptive losses. The chromatograms resulting from the blank samples demonstrated no interferences and uncontaminated soils for detecting the drugs (data not shown). The adsorption equilibrium time to reach a plateau was 48 h for the three chemicals in Barop soil. Desorption equilibrium time of xylazine given in Fig. 5D was set to 48 h, which resulted from the desorption study using a soil/solution ratio of 1:2.5. Estimated adsorption and/or desoprtion isotherms parameters of acepromazine, azaperone, and xylazine in Barop soil are placed in Table 6 and Fig. 6. The percentage adsorbed was in the order of azaperone (97.77%) > acepromazine (93.76%) > xylazine (81.37%). Other adsorption parameters, such as Kdads , KFads , and KOC showed the same order for the chemicals. The adsorption of acepromazine and azaperone was much stronger than that of xylazine, and azaperone had the largest adsorption parameters. Adsorption of chemicals heavily depends on their molecular structure and physicochemical properties. A difference in adsorption sites of the soil with respect to the chemicals may be involved. 1/n values of acepromazine and xylazine were <1, indicating minor competition between the chemical molecules and water molecules for soil adsorption sites. Therefore, the chemicals molecules were able to interact with the soil strongly, suggesting that the adsorption tendency decreased with increasing equilibrium concentration. This was caused by heterogeneous media adsorption where high energy sites of the soil are occupied first, followed by adsorption at lower energy sites. The adsorption isotherm of azaperone were S-type (1/n > 1), suggesting more competition between azaperone and water molecules for adsorption sites at low azaperone concentrations and the adsorption tendency increased with increasing equilibrium concentration. Performing desorption isotherm experiments for acepromazine and azaperone were impossible due to limitations of centrifuging

J.-H. Choi et al. / Journal of Hazardous Materials 275 (2014) 154–165

163

Fig. 5. Percentage and equilibrium time of adsorption in different soil/solution ratios of acepromazine (A), azaperone (B), and xylazine (C), and the percentage and equilibrium time of desorption of xylazine (D) in the soil/solution, 1:2.5.

100 or 200 mL soil solution samples in a glass container. However, their adsorptions to Barop soil were very strong; particularly, their KOC values were extremely high. Although adsorption–desorption hysteresis of acepromazine and azaperone could not be calculated, significant amounts were tightly bound to the soil particles and were not readily desorbed. Additionally, their leaching potential in the soil would be insignificant. Using the DT50 of acepromazine

in the dissipation kinetic study with Barop soil noted in Table 4, the GUS value was −0.61, suggesting a low leaching characteristic and placing it in the low leaching potential category of GUS < 1.8. Xylazine recorded relatively low Kdads and KFads values. However,

the higher KFdes and positive H values meant that the amount of desorbed xylazine was smaller than the total amount of adsorbed xylazine, indicating strong binding of xylazine to the soil as well.

Fig. 6. Linear (A) and Freundlich (B) adsorption isotherms for acepromazine and azaperone, and linear (C) and Freundlich (D) adsorption/desorption isotherms for xylazine.

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J.-H. Choi et al. / Journal of Hazardous Materials 275 (2014) 154–165

Table 6 Estimated adsorption and/or desorption isotherms parameters of acepromazine, azaperone, and xylazine in Barop soil. Compound

Xylazine Acepromazine Azaperone a b

Aa

81.37 93.76 97.77

Linear adsorption

Kd

r2

10.92 1501.60 8774.10

0.994 0.990 0.991

Freundlich adsorption KOC b

KF

379.03 52,138.89 304,656.25

9.01 1244.52 11,923.40

Freundlich desorption

1/n

r2

0.80 0.92 1.09

0.998 0.991 0.979

KF

1/n

r2

12.55 – –

0.89 – –

0.999 – –

A percentage adsorption. KOC normalized to organic carbon content.

Even if the DT50 (138.6 d) of xylazine in Barop soil was greater than the dissipation batch time period (120 d), the derived GUS value (3.04) revealed a high leaching potential due to GUS range >2.8 which is considered high leaching potential. 4. Conclusions Antianxiety medications were examined for the first time in soil. The determination method using ultrasonic-assisted extraction and Orbitrap mass spectrometry resulted in excellent validation outcomes on the tranquilizers and ␣, ␤-blockers in soil samples. Furthermore, the simplicity and high sample throughput made the method more attractive. Acepromazine displayed initial profound decrease and subsequent lag phase in residues during incubation with control and amended Barop and Scheyern soils. The acepromazine dissipation pattern fit a first-order multi compartment model. In contrast, azaperone and xylazine declined slowly and steadily, and their behaviors followed single first-order kinetics. A FOCUS spreadsheet was very useful to calculate the dissipation patterns of acepromazine, azaperone, and xylazine. A hydroxylated acepromazine was identified from the incubated soil samples. Adsorption of acepromazine was stronger than that of xylazine, but its dissipation or degradation was much faster than that of xylazine. It might be attributable to different soil-active sites and reaction velocity building non-extractable bound residues, different microbial communities for degrading acepromazine and xylazine, or acepromazine was more susceptible to microbial activity. Xylazine showed low dissipation or degradation and high leaching potential in soil, indicating its significant mobility into subsurface drainage water and groundwater, and transport along; hence, xylazine should be included in environmental fate and risk assessments of ground and drinking water.

[6]

[7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]

Acknowledgements

[18]

We are grateful to the National Research Foundation of Korea (357–2011–1–F00004) for their financial support. Additionally, great appreciation is given to the Ministry of Innovation, Science, Research and Technology of the State of North Rhine-Westphalia for financial support.

[19]

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