Analytical method for the samples from Australia
Ethyl sulfate in the wastewater samples was measured through direct injection into the liquid
chromatograph coupled with tandem mass spectrometry (LC-MS/MS). The 1 mL filtered sample was
spiked with 10 ng of the corresponding mass-labelled standard, ethyl sulfate-D5, before instrumental
analysis. Chromatography for measuring this analyte was performed on a Synergi Polar-RP (100 × 2
mm, 2.5 µm, Phenomenex) analytical column with a Shimadzu Nexera Ultra-High Performance LC
system. The column temperature was at 45 °C. The mobile phases used were (A) Milli-Q water in 0.1 %
formic acid and (B) 95 % acetonitrile in 0.1 % formic acid, and run at the flow of 0.3 mL/min in the
gradient as: 0 min, 100 % A; 1.9 min, 100 % A; 2.4 min, 40 % A; 5.4 min, 40 % A; 5.5 min, 100 % A for
a 3-min column equilibration. The analyte was identified and quantified using a QTRAP® 6500 MS
system (Applied Biosystems SCIEX, Thornhill, Ontario, Canada) at a negative electrospray ionisation
mode. Both the native and mass-labelled standard of ethyl sulfate was infused into the MS system
for optimising the related MS parameters and selecting two most abundant product ions as the
quantifier and confirmer for measuring this analyte in the samples with the multiple reaction
monitoring mode.
The calibration curve was linear over the range of 0.5 – 50 ng/mL with correlation coefficient (R2) of
0.9999. The intra- and inter- day precisions (as %RSD) were 5.5 and 3.7 %, respectively while the
accuracy was 106 %. Limit of quantification based on a signal-to-ratio of 10 (S/N10) was 1 ng/mL.
Analytical method for the samples from Lugano
The analysis of EtS was performed by direct injection of wastewater into the mass spectrometer
system. 1 mL of influent wastewater was centrifuged at 8000 rpm for 5 min to separate particulate
matter. Then, an aliquot of 190 µL was mixed with the internal standard ethyl sulfate-D5 (spiked
amount 10 ng). After mixing, the extract was transferred into a glass vial for instrumental analysis.
An Agilent 1200 series LC system with an Atlantis T3 2.1 mm × 150 mm, 3 µm column (Waters) was
used for chromatographic separation. The column temperature was maintained at room
temperature. The flow rate was 0.18 mL/min and the injection volume was set to 4 μL. Mobile phase
consisted on milli-Q water 0.1 % acetic acid (eluent A) and acetonitrile (eluent B). The percentage of
eluent A changed as follows: 0 min, 98 % eluent A; 10 min, 80 % eluent A; 11 min, 100 % eluent B; 1115 min, 100 % eluent B for column washing; 16 min, 98 % eluent A for column equilibration which
was maintained for 8 min. The mass-spectrometry (MS) system was an API 5500 triple quadrupole
equipped with a Turbo Ion Spray source (Applied Biosystems - Sciex, Thornhill, Ontario, Canada) and
a 1200 Series pumps system (Agilent Technologies, Santa Clara, CA, USA) were used. Specific MS
parameters such as source parameters and collision energy were optimised y direct infusion of
standards. Quantitative analyses were performed in multiple reaction monitoring (MRM) mode, and
the two most abundant fragmentation products (selected as quantifier and qualifier) were recorded.
The calibration curve was established in the range of 0 – 500 ng/mL with correlation coefficient (R2)
of 0.9995. Accuracy and precision were determined by analysing wastewater samples spiked at 30
and 50 ng/mL. Satisfactory accuracy and precision values were obtained, which ranged 96.2 – 101.1 %
and 5.9 – 11.1 %, respectively. Limit of quantification based on S/N10 was 0.2 ng/mL.
Table S1. Concentration of ethyl sulfate (ng/mL) and sewage flow (m3/day) in participating cities during the sampling period.
City
Population served by
WWTP
sampling period
Canberra
338888
Toowoomba
125000
Montreal
1958257
Granby
55255
Lugano
103561
Dortmund
371788
Dülmen
34495
Dresden
593050
Concentration Day 1
11-17 Mar
2014
11.5
11-17 Mar
2014
13.0
11-17 Mar
2014
7.4
11-17 Mar
2014
14.3
18-24 Mar
2014
3.3
11-17 Mar
2014
19.6
11-17 Mar
2014
10.3
11-17 Mar
2014
25.1
Concentration Day 2
9.9
15.4
5.6
16.5
3.4
21.7
17.1
31.2
Concentration Day 3
12.1
11.2
5.4
16.0
3.0
19.7
14.9
20.3
Concentration Day 4
13.5
18.0
6.7
19.0
2.9
25.0
22.5
29.0
Concentration Day 5
19.2
24.4
7.8
20.0
1.5
25.7
38.1
70.7
Concentration Day 6
24.0
14.7
10.3
13.9
1.2
37.2
38.0
20.9
Concentration Day 7
15.2
15.4
9.0
10.6
1.6
22.9
19.4
20.4
Sewage volume Day 1
86000
18994
1971613
43980
64692
89185
4766
110198
Sewage volume Day 2
82600
20104
1978197
37500
55055
93456
7409
112925
Sewage volume Day 3
83300
19916
2457017
43180
57890
91559
8013
115085
Sewage volume Day 4
86500
19957
1935334
36360
58446
92588
7970
114330
Sewage volume Day 5
87100
19230
1940985
42460
150747
103689
9382
199395
Sewage volume Day 6
81400
19253
1918080
40750
109910
88046
7661
157839
Sewage volume Day 7
89500
20350
1932448
36880
75051
89820
7488
113819
Concentration Day 8
Sewage volume Day 8
Table S1. Continued.
City
Population served by
WWTP
sampling period
Munich
1000000
Berlin M
290000
Berlin R
1300000
Berlin S
750000
Berlin W
1500000
Copenhagen
531000
Barcelona
1150874
Castellon
180690
Concentration Day 1
12-18 Mar
2014
13.7
11-17 Mar
2014 (n = 5)
33.8
10-16 Mar
2014
28.0
11-17 Mar
2014
37.5
11-17 Mar
2014
26.7
11-17 Mar
2014
25.7
18-24 Mar
2014
14.0
11-17 Mar
2014
14.6
Concentration Day 2
27.8
38.7
26.1
36.6
19.9
26.4
14.1
12.1
Concentration Day 3
28.0
39.8
25.1
34.3
25.6
31.3
14.9
11.0
Concentration Day 4
40.0
63.8
25.5
36.7
21.6
37.8
15.9
22.2
Concentration Day 5
47.2
32.1
49.1
21.7
60.3
24.2
69.3
Concentration Day 6
43.7
38.1
50.0
28.6
38.8
17.9
33.8
Concentration Day 7
<LOQ
44.7
24.2
49.1
25.3
22.7
7.7
20.4
Sewage volume Day 1
276600
34077
201520
105752
179490
132022
231488
41561
Sewage volume Day 2
268670
34303
197660
104199
179136
131041
230245
45049
Sewage volume Day 3
274290
35097
198695
106191
179323
132962
242020
50158
Sewage volume Day 4
267090
34176
199740
105414
177885
150773
233484
42636
Sewage volume Day 5
260250
33609
205060
108258
191740
136217
217266
41606
Sewage volume Day 6
263130
37547
197834
145035
230170
262325
209872
39282
Sewage volume Day 7
266400
33829
278000
105641
186693
161058
222794
40267
Concentration Day 8
Sewage volume Day 8
Table S1. Continued.
City
Population served by
WWTP
sampling period
London
3400000
Milan
1122501
Amsterdam
769000
Eindhoven
450300
Utrecht
300000
Oslo
580639
Almada
138685
Concentration Day 1
11-17 Mar
2014
9.8
04-10 Feb
2015
4.1
12-18 Mar
2014
19.2
11-17 Mar
2014 (n = 6)
20.3
11-17 Mar
2014
25.0
10-17 Mar
2015 (n = 8)
4.2
11-17 Mar
2014
21.7
Concentration Day 2
9.8
3.1
30.9
21.5
5.1
30.7
Concentration Day 3
12.1
2.3
27.0
16.7
15.8
4.3
29.2
Concentration Day 4
23.6
5.0
40.6
16.0
22.5
9.1
63.3
Concentration Day 5
27.9
5.7
40.3
31.1
36.6
15.4
49.5
Concentration Day 6
17.3
3.9
21.4
36.9
20.3
32.0
42.8
Concentration Day 7
16.2
3.6
24.3
27.8
13.1
5.7
36.3
Concentration Day 8
4.0
Sewage volume Day 1
976028
403960
148310
Sewage volume Day 2
1088834
673970
147750
Sewage volume Day 3
1178888
660810
149870
Sewage volume Day 4
1184166
469900
Sewage volume Day 5
1138747
Sewage volume Day 6
Sewage volume Day 7
Sewage volume Day 8
118281
46680
392314
13900
46430
332093
14200
100504
46460
306596
13800
149770
100049
44110
275737
13700
395410
150400
97910
43960
255126
10600
1151415
423340
146400
96068
44410
248717
14400
1137846
424210
165240
105452
45600
252838
14300
251013
Table S2. Monte Carlo simulation for uncertainty assessment (Ort et al., 2014) with details of the distribution assumed for parametersa.
Sampling uncertainty
(Us)
Per capita
Concentration (C)
Daily flow (F)
Excretion rate (E)
Population (P)
consumption
(L)
Total uncertainty
(Ut)
Australia
Normal (1,
0.05
)
√7
Normal (1, 0.037)
0.32
Lugano
Normal (1,
0.05
)
√7
Normal (1, 0.110)
0.34
Barcelona
Normal (1,
0.05
)
√7
Normal (1, 0.023)
Eindhoven
Normal (1,
0.05
)
√6
Normal (1, 0.046)
Oslo
Normal (1,
0.05
)
√8
Normal (1, 0.046)
0.32
The rest
Normal (1,
0.05
)
√7
Normal (1, 0.046)
0.32
a
Normal (1, 0.2)
Beta (426.804,
35140.196)
Normal (1, 0.2)
C∙F
Us ∙
E∙P
0.32
0.33
Normal (mean, SD) specifies a normal distribution with the entered mean and standard deviation, Beta (a,b) specifies a beta distribution with the entered a
and b values, a = ((1 — mean) / standard error2 — 1 / mean) × mean2 and b = a × (1 / mean — 1) (Jones et al., 2014).
Table S3. Detailed parameters for probabilistic comparative risk assessment of alcohol (Lachenmeier and Rehm, 2015)a.
LD50 (mg/kg body
weight)b
MOE for city
Normal (5593, 1346)
with truncation (3450,
7060)
BMDL10
(mg/kg body
weight)c
Per capita consumption
(L/day/1000 inhabitants)
Normal (mean, SD) with
truncation (min, max)e
Exposure (mg/day/person)
Body weight (kg)d
MOE
BMDL10
Per capita consumption × 0.789
LD50
Normal (73.9, 12)
MOE for
Exposure
(
)
× 1000
10.2
Bodyweight
whole
Uniform (6.3982, 44.2856)
population
a
Normal (mean, SD) with truncation (min, max) specifies a normal distribution with the entered mean and standard deviation truncating the input
distribution by minimum-maximum range, Uniform (min, max) specifies a uniform probability distribution with the entered minimum and maximum values.
b
Median lethal dose derived from guinea pig, mouse, rabbit and rat. The values were taken from ChemIDplus Advanced (United States National Library of
Medicine; http://chem.sis.nlm.nih.gov/chemidplus) (Lachenmeier and Rehm, 2015).
c
Lower one-sided confidence limit of benchmark dose for a 10% incidence of health effect, estimated from LD50 using the method by Gold et al. (2003).
d
Values for bodyweight were assessed according to EFSA Scientific Committee (2012), Lachenmeier and Rehm (2015).
e
See Table S4.
Table S4. Per capita consumption (L/day/1000inhabitants) of alcohol in each city.
City
mean
SD
min
max
Canberra
Toowoomba
Montreal
Granby
Lugano
Dortmund
Dülmen
Dresden
Munich
Berlin
Copenhagen
Barcelona
Castellon
London
Milan
Amsterdam
Eindhoven
Utrecht
Oslo
Almada
14.6
9.7
29.2
44.3
6.5
23.6
20.3
29.4
29.5
16.9
40.2
11.7
23.4
21.5
6.4
22.0
21.7
12.9
19.2
14.6
4.6
2.5
5.7
9.7
1.4
5.6
12.0
27.7
17.0
2.9
19.5
3.5
17.8
9.5
1.3
6.4
6.7
4.2
16.1
5.1
9.3
6.9
21.8
27.3
4.5
18.1
5.5
15.1
0.5
13.8
24.6
5.7
11.6
10.9
5.1
14.3
13.7
7.7
8.8
8.4
22.3
14.5
38.8
59.3
8.4
34.0
40.0
91.7
47.4
22.3
74.0
17.6
61.6
36.0
8.1
30.5
30.4
20.7
52.9
24.1
Table S5. Per capita daily load data for the cocaine (COC), amphetamine (AMP), methamphetamine
(METH), MDMA and Cannabis (mg/day/1000inhabitants) not available on EMCDDA (European
Monitoring Centre for Drugs and Drug Addiction, 2015).
COC Day 1
COC Day 2
COC Day 3
COC Day 4
COC Day 5
COC Day 6
COC Day 7
AMP Day 1
AMP Day 2
AMP Day 3
AMP Day 4
AMP Day 5
AMP Day 6
AMP Day 7
METH Day 1
METH Day 2
METH Day 3
METH Day 4
METH Day 5
METH Day 6
METH Day 7
MDMA Day 1
MDMA Day 2
MDMA Day 3
MDMA Day 4
MDMA Day 5
MDMA Day 6
MDMA Day 7
Cannabis Day 1
Cannabis Day 2
Cannabis Day 3
Cannabis Day 4
Cannabis Day 5
Cannabis Day 6
Cannabis Day 7
a
No data reported.
Canberra
Toowoomba
Montreal
Granby
58.4
37.1
35.2
51.0
80.7
97.9
67.2
23.2
24.8
20.2
24.6
27.4
24.2
27.3
100.3
99.5
101.0
117.7
120.5
115.9
108.8
59.8
24.9
22.2
90.9
65.1
85.3
50.0
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
0.8
1.0
0.6
2.0
8.2
1.8
1.8
16.5
17.3
16.8
16.8
21.6
16.7
17.4
76.4
80.3
94.1
104.4
124.3
105.3
102.7
3.1
4.2
1.9
8.1
17.1
3.4
3.4
5.1
2.0
2.0
2.0
1.9
1.9
2.0
115.8
125.3
177.8
165.0
158.6
163.6
145.1
7.0
8.8
12.5
10.3
9.1
9.5
10.1
NAa
NAa
NAa
NAa
NAa
NAa
NAa
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
50.7
36.4
47.7
53.4
60.5
48.0
44.4
74.0
82.8
104.7
93.4
137.2
104.7
64.7
23.1
24.4
25.8
23.7
27.7
20.6
14.8
NAa
NAa
NAa
NAa
NAa
NAa
NAa
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
< LOQ
25
20
15
10
5
0
30
c
25
Per capita alcohol consumption
(L/day/1000inhabitants)
b
Per capita alcohol consumption
(L/day/1000inhabitants)
Per capita alcohol consumption
(L/day/1000inhabitants)
a
30
20
15
10
5
0
2009a
2015b
Oslo
30
25
20

15

10
5
0
2013c
2014b
Barcelona
2012d
2013d
2014d
2015b
Milan
Figure S1. Intra-city comparisons of alcohol consumption in Oslo (a), Barcelona (b) and Milan (c). Error bar and asterisk indicate standard deviation and p <
0.05, respectively. aReid et al., 2011. bPresent study. cMastroianni et al., 2014. dRodríguez-Álvarez et al., 2015.
Proportion of weekly alcohol consumption (%)
50
40
30
weekday
weekend
20
10
0
Figure S2. Average weekday and weekend alcohol consumptions as proportions of the weekly total. The error bars indicate SDs.
difference
References
EFSA Scientific Committee, 2012. Guidance on selected default values to be used by the EFSA
Scientific Committee, Scientific Panels and Units in the absence of actual measured data.
EFSA Journal 10, 2579. doi:10.2903/j.efsa.2012.2579
European Monitoring Centre for Drugs and Drug Addiction, 2015. Wastewater analysis and drugs — a
European multi-city study [WWW Document]. URL (accessed 8.12.15).
Gold, L.S., Gaylor, D.W., Slone, T.H., 2003. Comparison of cancer risk estimates based on a variety of
risk assessment methodologies. Regul. Toxicol. Pharmacol. 37, 45–53. doi:10.1016/S02732300(02)00026-0
Jones, H.E., Hickman, M., Kasprzyk-Hordern, B., Welton, N.J., Baker, D.R., Ades, A.E., 2014. Illicit and
pharmaceutical drug consumption estimated via wastewater analysis. Part B: Placing backcalculations in a formal statistical framework. Sci. Total Environ. 487, 642–650.
doi:10.1016/j.scitotenv.2014.02.101
Lachenmeier, D.W., Rehm, J., 2015. Comparative risk assessment of alcohol, tobacco, cannabis and
other illicit drugs using the margin of exposure approach. Sci. Rep. 5, 8126.
doi:10.1038/srep08126
Mastroianni, N., Lopez de Alda, M., Barcelo, D., 2014. Analysis of ethyl sulfate in raw wastewater for
estimation of alcohol consumption and its correlation with drugs of abuse in the city of
Barcelona. J. Chromatogr. A 1360, 93–99. doi:10.1016/j.chroma.2014.07.051
Ort, C., van Nuijs, A.L.N., Berset, J.-D., Bijlsma, L., Castiglioni, S., Covaci, A., de Voogt, P., Emke, E.,
Fatta-Kassinos, D., Griffiths, P., Hernández, F., González-Mariño, I., Grabic, R., KasprzykHordern, B., Mastroianni, N., Meierjohann, A., Nefau, T., Östman, M., Pico, Y., Racamonde, I.,
Reid, M., Slobodnik, J., Terzic, S., Thomaidis, N., Thomas, K.V., 2014. Spatial differences and
temporal changes in illicit drug use in Europe quantified by wastewater analysis. Addiction
109, 1338–1352. doi:10.1111/add.12570
Reid, M.J., Langford, K.H., Mørland, J., Thomas, K.V., 2011. Analysis and Interpretation of Specific
Ethanol Metabolites, Ethyl Sulfate, and Ethyl Glucuronide in Sewage Effluent for the
Quantitative Measurement of Regional Alcohol Consumption. Alcohol. Clin. Exp. Res. 35,
1593–1599. doi:10.1111/j.1530-0277.2011.01505.x
Rodríguez-Álvarez, T., Racamonde, I., González-Mariño, I., Borsotti, A., Rodil, R., Rodríguez, I., Zuccato,
E., Quintana, J.B., Castiglioni, S., 2015. Alcohol and cocaine co-consumption in two European
cities assessed by wastewater analysis. Sci. Total Environ. 536, 91–98.
doi:10.1016/j.scitotenv.2015.07.016