Environmental Engineering Reference
In-Depth Information
Extraction Recoveries
(Ramirez et al.
2007
): All samples were analyzed by
LC-MS/MS, and individual analyte recoveries were calculated using the following
equation:
RECOVERY
= (
A
X1
/
A
IS1
) / (
A
X2
/
A
IS2
) ×
100%
where
A
X1
,
A
IS1
,
A
X2
, and
A
IS2
represent peak areas for the analyte (X) and inter-
nal standard (IS) in groups 1 and 2 samples, respectively.
Identification of Pharmaceuticals Using LC-MS/MS
(Ramirez et al.
2007
):
A LC-MS/MS total ion chromatogram resulting from analysis of clean
tissue (non-affected by contaminants) spiked with a mixture of stand-
ard pharmaceuticals is depicted in Fig.
3
. Peak identifications for pharma-
ceuticals in the chromatogram are as follows: (1) acetaminophen-
d
4
, (2)
acetaminophen, (3) atenolol, (4) cimetidine, (5) codeine, (6) 1,7-dimeth-
ylxanthine, (7) lincomycin, (8) trimethoprim, (9) thiabendazole, (10) caf-
feine, (11) sulfamethoxazole, (12) 7-aminolunitrazepam-
d
7
(
+
IS), (13)
metoprolol, (14) propranolol, (15) diphenhydramine-
d
3
, (16) diphenhydramine,
(17) diltiazem, (18) carbamazepine-
d
10
, (19) carbamazepine, (20) tylosin, (21)
fluoxetine,
d
6
, (22) fluoxetine, (23) norfluoxetine, (24) sertraline, (25) erythromy-
cin, (26) clofibric acid, (27) warfarin, (28) miconazole, (29) ibuprofen-
13
C
3
, (30)
ibuprofen, (31) meclofenamic acid (-IS), and (32) gemfibrozil. Three factors were
presumably considered in selecting the target analytes (Table
3
): First, number of
prescriptions dispensed in the United States during 2005 (RxList 2005). Second,
variability in structure, physicochemical properties, and therapeutic use. Third, rel-
ative frequency of occurrence in soils, sediments, and biosolids. The frequency of
detection of various PPCPs in analyzed sediment, soil, and biosolid samples (64-
100 %) is typically much higher than in water (5 %). This may be due to variation
in physicochemical properties favoring compound partitioning from water to solid
environmental matrixes. Compounds residing in sediment may then be taken up by
aquatic organisms via ingestion (Furlong et al.
2004
; Brooks et al.
2005
; Ramirez
et al.
2007
).
Optimized MS/MS transitions and collision energies employed for detection and
quantitation of each analyte are presented in Table
3
, along with the molecular struc-
ture and most common therapeutic use for each analyte. With the exception of eryth-
romycin, selected precursors represent the molecular ion [M
+
H]
+
or [M
−
H]
−
for
each analyte. The most abundant precursor for erythromycin was found to be the
[M
+
H
−
H
2
O]
+
ion at
m
/
z
716. Selected product ions generally represent the most
abundant fragment observed for each precursor at the noted collision energy. Once
suitable MS/MS transitions have been identified for each analyte, an aqueous mix-
ture of reference standards was employed to optimize chromatographic parameters.
A nonlinear gradient consisting of 0.1 % (v/v) formic acid and methanol resulted in
near baseline resolution of the majority of analytes in ~50 min (Fig.
3
). A 15-min
