Environmental and biological monitoring of exposures to PAHs and ETS in the
Noel J. Aquilinaa, Juana Mari Delgado-Saborita, Claire Meddingsa, Stephen Bakera, Roy M. Harrisona,⁎,
Peyton Jacob IIIb, Margaret Wilsonb, Lisa Yub, Minjiang Duanb, Neal L. Benowitzb
aDivision of Environmental Health & Risk Management, School of Geography, Earth & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT,
bDivision of Clinical Pharmacology and Experimental Therapeutics, Departments of Medicine, Psychiatry, and Biopharmaceutical Sciences, San Francisco General Hospital Medical Center,
University of California, San Francisco, UCSF Box 1220, San Francisco, CA 94143-1220, USA
a b s t r a c ta r t i c l ei n f o
Received 7 October 2009
Accepted 30 May 2010
Available online 29 June 2010
PAH monophenolic metabolites
The objective of this study was to analyse environmental tobacco smoke (ETS) and PAH metabolites in urine
samples of non-occupationally exposed non-smoker adult subjects and to establish relationships between
airborne exposures and urinary concentrations in order to (a) assess the suitability of the studied
metabolites as biomarkers of PAH and ETS, (b) study the use of 3-ethenypyridine as ETS tracer and (c) link
ETS scenarios with exposures to carcinogenic PAH and VOC. Urine samples from 100 subjects were collected
and concentrations of monophenolic metabolites of naphthalene, fluorene, phenanthrene, and pyrene and
the nicotine metabolites cotinine and trans-3′-hydroxycotinine were measured using liquid chromato-
graphy–tandem mass spectrometry (LC-MS/MS) to assess PAH and ETS exposures. Airborne exposures were
measured using personal exposure samplers and analysed using GC–MS. These included 1,3-butadiene
(BUT), 3-ethenylpyridine (3-EP) (a tobacco-specific tracer derived from nicotine pyrolysis) and PAHs. ETS
was reported by the subjects in 30-min time–activity questionnaires and specific comments were collected
in an ETS questionnaire each time ETS exposure occurred. The values of 3-EP (N0.25 μg/m3for ETS) were
used to confirm the ETS exposure status of the subject. Concentrations as geometric mean, GM, and standard
deviation (GSD) of personal exposures were 0.16 (5.50)μg/m3for 3-EP, 0.22 (4.28)μg/m3for BUT and 0.09
(3.03)ng/m3for benzo(a)pyrene. Concentrations of urinary metabolites were 0.44 (1.70)ng/mL for 1-
hydroxypyrene and 0.88 (5.28)ng/mL for cotinine. Concentrations of urinary metabolites of nicotine were
lower than in most previous studies, suggesting very low exposures in the ETS-exposed group. Nonetheless,
concentrations were higher in the ETS population for cotinine, trans-3′hydroxycotinine, 3-EP, BUT and
most high molecular weight PAH, whilst 2-hydroxyphenanthrene, 3+4-hydroxyphenanthrene and 1-
hydroxyphenanthrene were only higher in the high-ETS subpopulation. There were not many significant
correlations between either personal exposures to PAH and their urinary metabolites, or of the latter with
ETS markers. However, it was found that the urinary log cotinine concentration showed significant
correlation with log concentrations of 3-EP (R=0.75), BUT (R=0.47), and high molecular weight PAHs
(MWN200), especially chrysene (R=0.55) at the p=0.01 level. On the other hand, low correlation was
observed between the PAH metabolite 2-naphthol and the parent PAH, gas-phase naphthalene. These
results suggest that (1) ETS is a significant source of inhalation exposure to the carcinogen 1,3-butadiene
and high molecular weight PAHs, many of which are carcinogenic, and (2) that for lower molecular weight
PAHs such as naphthalene, exposure by routes other than inhalation predominate, since metabolite levels
correlated poorly with personal exposure air sampling.
© 2010 Elsevier Ltd. All rights reserved.
Polycyclic aromatic hydrocarbons (PAH) and volatile organic
compounds (VOC) are ubiquitous in outdoor and indoor air, and
therefore of public health concern. PAH are formed and emitted into
the environment as a result of incomplete combustion of organic
materials from natural and human activities. VOC sources are mainly
industrial processes, fossil fuel combustion in transportation and
heating, solvent use, building materials and environmental tobacco
smoke (ETS), also known as second-hand smoke (Harrison et al.,
2009). Due to their adverse health effects, including carcinogenicity
(IARC, 2006), it is important to assess their concentrations in both
occupational and environmental settings (Han et al., 2008).
Environment International 36 (2010) 763–771
⁎ Corresponding author. Tel.: +44 121 414 3494; fax: +44 121 414 3709.
E-mail address: email@example.com (R.M. Harrison).
0160-4120/$ – see front matter © 2010 Elsevier Ltd. All rights reserved.
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/envint
PAH absorbed into the human body are metabolized to their
monohydroxylated PAHs and finally to glucuronides and sulfates,
which are excreted in urine and bile (Chetiyanukornkul et al., 2006).
As regards nicotine, most is converted in the liver to cotinine which is
further metabolized to trans-3′-hydroxycotinine. Nicotine, cotinine
and hydroxycotinine are conjugated to form nicotine-N-glucuronide,
cotinine-N-glucuronide and hydroxycotinine-O-glucuronide.
Demethylation of nicotine and cotinine are minor metabolic path-
ways. Nicotine, cotinine, hydroxycotinine, nornicotine and respective
glucuronides account for 74–99% of a nicotine dose excreted in an
adult smoker's urine (Hukkanen et al., 2005).
Biological monitoring has been increasingly viewed as a desirable
alternative to air sampling for characterizing environmental exposures,
not only because it accounts for all possible exposure routes but also
individual differences in uptake or genetic susceptibility (Lin et al.,
2005). The use of urinary biomarkers as a non-invasive means for
in occupational exposures (Rossbach et al., 2007; Forster et al., 2008).
1-Hydroxypyrene is widely considered as an appropriate biomarker
for exposures to PAH on the basis that pyrene is rapidly distributed,
metabolized and eliminated from the body; 1-hydroxypyrene in urine
represents a constant fraction (2%) of total pyrene intake (Bouchard et
from 4 to 35 h (Jongeneelen et al., 1990), declining to a baseline within
48-h (Buckley and Lioy, 1992). Whilst many studies have traditionally
reported 1-hydroxypyrene in urine (Pastorelli et al., 1999; Han et al.,
2008), only recently a few have reported concentrations of the other
PAH metabolites in occupationally exposed populations (Serdar et al.,
2003; Campoetal.,2006;Chetiyanukornkul et al.,2006;Rossbachetal.,
2007; Forster etal.,2008; Rossellaetal.,2009).However, veryfewhave
reported levels of urinary biomarkers concurrent with PAHs in ambient
air of a non-occupationally exposed population (Leroyer et al., 2010)
whilst no study has yet reported concurrent measurement of PAH
urinarybiomarkers and personal exposure levels of PAHs in the general
The MATCH (Measurement and Modelling of Air Toxic Concentra-
tions for Health Effect Studies) Project aimed to provide a significant
strengthening of the VOC and PAH personal exposure and microen-
vironment measurement database through generating new data via
direct measurements. The study sought to lead to advances in
understanding the causes and magnitude of exposures to VOC and
PAH (Delgado-Saborit et al., 2009a; Harrison et al., 2009) and to
establish whether collecting lifestyle information is sufficient to
model personal exposures reliably when compared with exposures
evaluated independently by personal samplers (Delgado-Saborit et
al., 2009b). The hypothesis tested in the work described in this paper
is that urinary metabolites of PAH and ETS are excreted as a
consequence of inhalation exposures to PAH and ETS-related VOCs
(e.g. 3-EP), and that subjects exposed to higher concentrations of PAH
and ETS-related VOCs will excrete higher levels of PAH and ETS
metabolites. If the hypothesis is valid, then ETS and PAH metabolites
might prove useful as biomarkers of inhalation exposure to carcino-
genic VOCs and PAHs, such as 1,3-butadiene and benzo(a)pyrene, and
therefore provide an alternative to costly personal exposure assess-
mentmeasurements. Thesecond hypothesis tested in thiswork is that
3-ethenylpyridine may serve as an ETS tracer in environmental
samples, which might be useful in those situations where urinary ETS
biomarkers (e.g. cotinine) cannot be collected.
2. Experimental section
2.1. Recruitment of subjects
The MATCH Project, recruited 100 healthy adult volunteer subjects
for personal exposure and indoor microenvironment (home and
office) measurements. Selection took no specific account of age,
gender or ethnic background. Potential subjects were excluded if they
were (a) smokers, (b) under 18 years old, (c) unhealthy, (d) unable to
carry personal sampler for any reason, (e) exposed to PAH/VOC at
work, or (f) travelled more than 2h/day professionally, (g) their
journey to work took more than 2 h travelling time for the return trip,
or (h) the distance from home to their workplace was more than
20mi. The self-reported non-smoking status of the subjects was
checked with the results of cotinine in the urine analyses, as discussed
in the Results and Discussion sections.
Subjects resided in three different areas of the United Kingdom
selected for their expected gradient in personal exposures concentra-
tions, namely London, West Midlands and rural South Wales. Subjects
were chosen to participate based upon four key determinants (i.e.
possible VOC/PAH sources), namely the location where they lived, if
they were exposed to ETS, if their house incorporated an integral
garage and by the proximity of the house to a major road. Subjects
were considered ETS exposed whenever they reported in the activity
diary to be in the company of a smoker (friend/relative) or to be in
places with smokers (e.g. pub) and this information was validated
with the airborne concentration of the ETS marker 3-ethenylpyridine
(Hyvarinen et al., 2000). Volunteers were asked to complete a
screening questionnaire containing information about personal
lifestyle, the study key factors and the exclusion criteria. The subjects
finally selected were briefed in the use of the equipment and form
filling one week prior to the sampling week.
Ethics Committee approval was secured for this study from the
South Birmingham Research Ethics Committee, Birmingham (REC Ref
2.2. Environmental monitoring and analysis
2.2.1. Personal exposure sampling
Collection of the samples was spread over two years, from May
2005 to May 2007, 44% of the subjects were sampled during warm
months (April–September) and 56% in cold months (October–March).
Each subject was sampled for a group of 14 VOCs and 1,3-
butadiene (separately) for a total of five consecutive 24-h periods
using one personal sampler pump (SKC model PCXR8), connected to
two different sorbent tubes (one for 14 VOCs and the other for 1,3-
butadiene), and during one concurrent day an additional pump
sampled PAH on 47-mm quartz filters. The active-sampling setup
was enclosed in a small aluminum briefcase and additional power
was supplied via camcorder batteries connected to the pumps. The
flow rates used were 40 mL min−1for VOC, 30 mL min−1for 1,3-
butadiene and 3 Lmin−1for PAH (Delgado-Saborit et al., 2009a). All
collected samples were kept in refrigerated conditions after sampling
and prior to analysis. Duplicates and blanks were taken from 3% of
the study population as described in detail in the Supporting
Researchers met the subjects daily early in the morning to collect
the sampler corresponding to the previous 24-h, to supply a new 24-
h sampler ready for the new day and to check that all the
questionnaires (as described below) were correctly completed.
2.2.2. Subject related information
The atmospheric sampling was backed up with information
related to the subjects. Several questionnaires, completed daily
included 30-min activity diaries, travel description sheets, location
description sheet and activity questionnaires. Information about the
subject's demographics, home and products stored within the
house were collected once per subject. An ETS questionnaire was
filled out when the subjects were exposed to ETS (once per event).
Further details of the questionnaires can be found in Harrison et al.
N.J. Aquilina et al. / Environment International 36 (2010) 763–771
2.2.3. Analysis of environmental samples
Three methods were employed for analysing 1,3-butadiene, the
rest of the VOC and all the PAHs as described in detail in Delgado-
Saborit et al. (2009a).
In this study, only a selected group of VOC compounds mainly
related to ETS is presented jointly with the urinary biomarker data,
which included 3-ethenylpyridine (3-EP), 1,3-butadiene (BUT) and
naphthalene (Naph) in the gas phase. The measured particulate-
phase PAH were acenaphthylene (Ac), acenaphthene (Ace), fluorene
(Fl), phenanthrene (Phe), anthracene (Ant), fluoranthene (Fluo),
pyrene (Pyr), benzo(a)anthracene (BaA), chrysene (Chry), benzo(b)
fluouranthene (BbF), benzo(k)fluoranthene (BkF), benzo(a)pyrene
(BaP), indeno(1,2,3-cd) pyrene (Ind), benzo(ghi)perylene (BghiP),
dibenzo(ah)anthracene (DahA) and coronene (Cor).
2.3. Biological monitoring
2.3.1. Urine collection and storage
As part of the sampling protocol, the subjects provided a urine
sample with the purpose of performing urinary biomarker analyses
related to the air toxics under study. The first, mid-stream urine
sample done in the morning – corresponding to the previous 24-
h personal exposure sample – was collected every day in a 100 mL
polypropylene bottle from each volunteer in order to analyse a set of
biomarkers present in the urine. Urine samples were collected by the
researcher during the daily visit to the subjects' house, were then
transferred to the laboratory in refrigerated conditions prior to
storage in a −80 °C freezer.
2.3.2. Selection of urine samples for analysis
A total of 500 urine samples were collected. Among those samples,
a subset of 100 urine samples were chosen for analysis balancing the
following criteria: (a) prioritise the analysis of at least one urine
sample from each subject; (b) maximise the number of urine samples
related to the day where VOC and PAH were sampled concurrently;
(c) select wherever possible urine samples representative of days
with reported ETS exposure, which was verified with the levels of 3-
ethenylpyridine in personal exposure. Six subjects did not give their
consent for analysing their urinary biomarkers and four PAH personal
samples were not collected due to faulty pumps. From the 100
selected samples, eight samples from five subjects were not
considered in the data analysis, as from the high cotinine values
(N50 ng/mL), it is highly likely that these subjects smoked at some
point prior to the urine collection (Jarvis et al., 1987) as confirmed
later. This subset of 92 samples (excluding the 8 samples from
smokers) contained samples from two different days for six subjects.
To avoid a within-subject effect upon between-subject relationships,
the 2-day mean values have been considered in the analysis for each
of those six subjects instead of the individual 1-day data. Therefore,
the final number of samples in the analysed subset is 86 urine/VOC
data. This subset consists of 62 urine–VOC/PAH data and 24 pairs of
urine–VOC data (See Table S2 in Supporting Information). As regards
ETS exposure, 55 urine samples were from No ETS subjects and 31
were from ETS-exposed subjects, which includes 19 samples from
subjects with low ETS exposures and 12 samples from subjects with
high ETS exposures. The criteria to classify subjects as No-, low- and
high ETS exposure are described in detail in the Results section.
2.3.3. Analysis of urinary biomarkers
About15 mL ofurinefromeachoftheselected100sampleswassent
in dry ice to the Division of Clinical Pharmacology at the University of
California San Francisco. The urine samples were analysed for the
nicotine metabolites cotinine (Cot) and trans-3′-hydroxycotinine
(T3HCot) and the PAH metabolites 2-naphthol (2-Nap), 1-hydroxy-
fluorene (1-HFl), 2-hydroxyfluorene (2-HFl), 3-hydroxyfluorene (3-
HFl), 1-hydroxyphenanthrene (1-HPhe), 2-hydroxyphenanthrene (2-
Monohydroxy metabolites of naphthalene, fluorene, phenan-
threne, and pyrene were determined by the method of Jacob et al.,
(2007). Concentrations of cotinine and trans-3′-hydroxycotinine in
urine were determined using liquid chromatography–tandem mass
spectrometry (LC-MS/MS). The method (Jacob et al., in preparation) is
similar to a published method for determining cotinine concentra-
tions in plasma of non-smokers (Bernert et al., 1997) (Supporting
Information contains a detailed description).
The methods have been fully validated, using the criteria of Shah et
al. (2000), for precision, accuracy,and to determine the lowerlimits of
detection. These are precision (CV) of ±15% and accuracy within ±
15% of the expected amount, except at the lower limit of quantitation,
for which ±20% is considered acceptable. These criteria are widely
used in drug development studies and are acceptable to the US Food
and Drug Administration (Shah et al., 2000).
2.4. Statistical analysis
Data were analysed using SPSS 15.0 for Windows (SPSS Inc.1989–
2006), Excel 2002 (Microsoft Corporation, 1985–2001) and Access
2007 (Microsoft Corporation, 2006). Data below the detection limit
(See Table S3, supporting information for LOD) were replaced with
half the value of the detection limit for the purpose of statistical
analysis. When urinary data was available for a subject for more than
one day, the arithmetic mean of both measurements was used for the
data analysis. Low-, Medium- and High-molecular weight (MW) PAH
were calculated adding the concentrations of Naph to An, Fluo to Chry
and B(b)F to Cor, generating new variables labelled as SumMW120-
180, SumMW200-250 and SumMW250-300 respectively. The sum of
the first 16 PAH was also calculated adding the concentrations from
Naph to B(ghi)P (Sum16PAH). These newly calculated values were
considered as independent variables in the data analysis.
Personal exposures and microenvironment concentrations were
tested for normality using the skewness statistic. All the VOC
concentrations, including 1,3-butadiene, PAH and urinary biomarker
(ETS and PAH metabolites) concentrations were found to have right-
skewed distributions. For this reason geometric means and geometric
standard deviations are reported and all the environmental and
biological concentrations were logged (log10). The datasets were
normally distributed after log transformation. Measures of the
association between PAH and VOC in environmental samples and
ETS and PAH metabolites in biological samples were characterised by
Pearson correlation coefficients (R) for logged data. Statistical
differences between two strata (i.e. ETS vs. No ETS concentrations)
were tested in the logged database with a t-test for equality of means
and Kolmogorov–Smirnov in those cases where the variance was
heterogeneous. General Linear Models were used to search for
interaction between different subject characteristics (e.g. gender,
age) and excretion of creatinine levels. Results were considered
significant with p values less than 0.05. Variance was considered
homogeneous provided that pN0.05 in Levene's test.
3.1. Description of subjects
The main sources of exposure that were examined in this study were inhalation
exposures.Thereforeinformationregarding activities and characteristics that mightaffect
the airborne concentrations relating to personal exposure was collected. This information
consisted of subjects' demographics (e.g. age, gender, occupation), time spent in different
microenvironments, activities that may affect the PAH and/or VOC personal exposures
(e.g. fireplace use, candle burning), home characteristics and ETS exposure characteriza-
tion. This information collected through questionnaires is summarized in Table S4 for the
subjects that participated in the study as well as for the sub-sample of subjects whose
urinary samples were analysed. As dietary exposures were not in the scope of this study,
N.J. Aquilina et al. / Environment International 36 (2010) 763–771
information about diet lifestyles (e.g. vegetarianism), cooking styles or duplicate food
samples was not collected.
3.2. ETS classification criteria
The ETS status self-reported in the initial screening questionnaire was confirmed
with information reported in the questionnaires daily and with the personal exposures
to 3-ethenylpyridine, an ETS tracer.
No ETS subjects were those who declared his/her No ETS status in the screening
questionnaire and no ETS events were registered in the time–activity diaries. This
information was later confirmed with the levels of 3-ethenylpyridine (3-EP) in air
samples. Those subjects whose 3-EP was b0.25 μg/m3(maximum 3-EP concentration
measured in the No ETS subpopulation) were classified as No ETS. In fact the 3-EP value
in the No ETS population was 0.07±0.06 μg/m3.
ETS subjects were those who reported ETS events in the time–activity diary on the
day preceding urine collection. This information was confirmed with the levels of 3-
ethenylpyridine (3-EP) in air samples. Those subjects whose 3-EP was 0.25b3-
EPb1.4 μg/m3were classified as low ETS. Those subjects whose 3-EP was N1.4 μg/m3
were classified as high ETS. The value of 1.4 μg/m3was selected from the frequency
distribution of 3-ethenylpyridine in the ETS population (Fig. 1). In Fig. 1 the distribution
of ETS subjects appears to be bimodal, with the value of 1.4 μg/m3as the cutpoint
between both modes.
3.3. Levels of ETS and PAH metabolites in urine and personal exposures to PAH and selected
Table 1 presents the geometric means (GM) and geometric standard deviation
(GSD) of the urinary ETS biomarker and PAH metabolite concentrations, with the
corresponding personal exposure concentrations to selected VOCs (i.e. 3-EP, BUT,
Naph), corresponding parent PAH (i.e. Fl, Phe, Pyr) and non-parent PAH compound for
the analysed samples excluding those from subjects which had extremely high cotinine
concentrations (i.e. smokers). Arithmetic values, minima and maxima as well as the
creatinine corrected concentrations are available in Table S5, supporting information.
3.4. Effect of ETS on nicotine- and PAH metabolites in urine
The samples have been subdivided as ETS and non-ETS exposed based on the
threshold personal exposure to 3-EP of 0.25 μg/m3. This cut-off concentration was
determined from the comparison of high 3-EP concentrations with the activities noted
in the time–activity diaries, indicating exposure to ETS, as described above.
The urinary biomarkers of nicotine exposure (cotinine and trans-3′-hydroxycoti-
nine) and the personal exposure concentrations of selected VOC (3-EP and BUT) and
some non-parent PAH compounds were higher in the ETS-exposed sub-sample
compared with the non-ETS at the pb0.05 level. On the other hand, for the PAH
metabolite biomarkers and the respective PAH parent compounds, there is no
statistically significant distinction between the ETS and non-ETS-exposed groups.
However, when comparing the high-ETS subgroup with the other two (i.e. non- and
low ETS) there are statistically significant differences at the pb0.05 level for 2-
hydroxyphenanthrene, 3+4-hydroxyphenanthrene and 1-hydroxypyrene. Within-
subject cross-correlations between PAH were calculated using the log database. For all
compounds except the most volatile (acenaphthene, acenaphthylene and fluorene),
cross-correlations were significant at pb0.01, giving correlation coefficients typically
between 0.35 and 0.95. This is not surprising as PAH exposure is typically to a mixture
3.5. Effect of sources other than ETS in urinary PAH metabolites
As outlined above, the subjects participating in this study came from three distinct
geographic areas of the United Kingdom (Birmingham, London and South Wales),
including urban, suburban and rural dwellers. Additionally, subject selection explicitly
took account of whether the subject's home had an integral garage and whether it
fronted onto a major highway. When the personal exposures to different levels of PAH
and VOC and urinary metabolites of PAH were analysed in relation to these potential
influences on exposure, no significant differences were found. We attribute this to the
importance of ETS exposure which was not appreciably influenced by the other factors
and for some of the compounds, the importance of non-respiratory exposures.
3.6. Correlations between personal exposure levels and biological concentrations in urine
Correlations of the logged concentrations of urinary biomarkers with selected VOC,
respective PAH parent compounds and non-parent PAH compounds in personal
exposures are shown in Table 2. Normalising with creatinine is a common practice used
to correct for differences in urinary flow. Correlations between environmental
concentrations and creatinine-normalised logged concentrations of urinary biomarkers
(i.e. corrected with creatinine) are shown in Table S6, supporting information.
Correlations nominally significant at the pb0.05 level (2-tailed) are highlighted in
bold type. The scatter plots corresponding to some of the compounds that correlate
(pb0.05) with urinary biomarkers are presented in Fig. 2. Suprisingly, in the case of the
ETS biomarkers, the correlation of the biomarker concentrations with selected VOC and
some non-parent PAH personal exposures is significantly higher in the un-normalised
data (Table 2) than in the normalised data (Table S6). Table 2 shows that log cotinine
un-normalised has a significant correlation with log 3-EP (R=0.75), with log BUT
(R=0.47) and with log Chry (R=0.55), which are all higher than for the respective
creatinine-normalised correlations (R=0.74/0.43/0.44 respectively) (Table S6). PAH
metabolites do not correlate with the parent or non-parent PAH compounds. However,
when data from only high-ETS subjects is correlated, 2-naphthol correlates at the 0.05
level with Ph, Pyr, Chry, SumMW120-180, SumMW200-250 and Sum16PAH.
4.1. Environmental levels of PAH and selected VOCs in
The levels of VOC and PAH concentrations in personal exposure
observed in this study (Table 1) are substantially lower than those
Fig. 1. Cumulative frequency distribution of 3-ethenypyridine (μg/m3) in ETS and No ETS subjects.
N.J. Aquilina et al. / Environment International 36 (2010) 763–771
found in similar studies, conducted in different locations in the United
States and Europe and at earlier times as discussed in detail in
Delgado-Saborit et al. (2009a).
4.2. Biological levels of PAH and ETS biomarkers in urine
Nicotine and PAH urinary metabolites from 100 first morning
urine samples of non-occupationally exposed subjects have been
analysed (Table 1). Cotinine and trans-3′hydroxycotinine levels in
non-ETS samples are similar than those reported by Lazcano-Ponce et
al. (2007) and Jacob et al. (2007) whilst much lower than those
reported by Simoni et al. (2006), Heinrich et al. (2005) and Wall et al.
(1988), however cotinine and trans-3′hydroxycotinine levels for ETS
subjects are substantially lower than previously reported (Wall et al.,
1988; Heinrich-Ramm et al., 2002; Heinrich et al., 2005; Jacob et al.,
2005; Simoni et al., 2006; Lazcano-Ponce et al., 2007; Matt et al.,
2007). Chetiyanukornkul et al. (2006) reported levels in Thailand of
PAH biomarkers for taxi drivers and traffic wardens, where both
groups were occupationally exposed to VOCs and PAHs, to be in the
range of those found in this study, whilst the levels found in Thai rural
villagers working in farms were considerably higher. As regards 1-
hydroxypyrene levels, our results are in line with results reported in
several studies performed in Germany, Italy and France (Merlo et al.,
1998; Pastorelli et al., 1999; Heudorf and Angerer, 2001; Leroyer et al.,
2010), whilst data reported from Thai rural villagers (in 2006), Dutch
adults (in 1994), Polish children (in 1994) and adults in Rome (Italy,
in 2001), spanning from the mid 1990s to the mid 2000s, are
substantially higher than our 1-HPyr data (Jongeneelen, 1994; Tomei
et al., 2001; Chetiyanukornkul et al., 2006). Several extreme cases of
urinary biomarkers were identified in our study (Table S5). The
information provided in the subjects' activity diaries allowed it to be
identified that all the cotinine and tran-3′hydroxycotinine extreme
cases were related to higher exposures to ETS, whilst PAH urinary
biomarker extremes were related to use of a fireplace (i.e. wood and
gas), use of a photocopier and commuting through heavily trafficked
4.3. ETS metabolites as biomarkers of ETS exposure
Previous studies have indicated that the levels of urinary cotinine
in non-smokers were usually less than 20 μg/L and the discrim-
ination threshold between active and passive smokers was from 50 to
100 μg/L (Jarvis et al., 1987). In this project the arithmetic mean
urinary cotinine level is 3.33±6.39 μg/L and the geometric mean and
standard deviation is 0.88 (5.28)μg/L, which shows that our non-
smoking subjects are towards the lower end of the range of ETS
exposure. However, eight samples from five volunteers were
excluded from the analysis as they were well above 50 μg/L of
Concentrations of urinary biomarkers (ng mL−1), selected VOC (μg m−3), parent PAH (ng m−3) and non-parent PAH (ng m−3) personal exposure concentrations by key
% CasesbLOD All subjects (ETS+No ETS)No ETS subjectsETS subjects
No casesGMGSDNo cases GMGSDNo cases GMGSD
Urinary biomarker concentrations
Selected VOC personal exposure concentrations
Parent PAH personal exposure concentrations
Non-parent PAH personal exposure concentrations
Σ Low MW [Naph-An]
Σ Medium MW [Fluo-Chry]
Σ High MW [B(b)F-Cor]
Σ 16 [Naph-B(ghi)P]
aThe concentrations in ETS subset are significantly different than the non-ETS subset at the 0.05 level.
bThe concentrations in the high-ETS subset (3-EPN1.4 μg m−3) only are significantly higher than the non- and low-ETS subset at the 0.05 level.
N.J. Aquilina et al. / Environment International 36 (2010) 763–771
cotinine—the cut-off value suggested for smokers. In a subsequent
communication, the subjects thus identified admitted that they had
4.3.1. Cotinine vs. trans-3′-hydroxicotinine as ETS biomarker
The influence of exposure to ETS has been studied. Cotinine is the
primary metabolite coming from nicotine that is very stable in the
body (half life is approximately 18 h, CV 30%) and can be measured
reliably in blood, saliva and urine for monitoring nicotine exposure in
people (Benowitz and Jacob, 1994). However, Tuomi et al. (1999)
suggest that although cotinine has been used extensively as a nicotine
marker in the urine of both active and passive smokers, trans-3′-
to 40% of the total nicotine excretion and is better used alongside
cotinine when monitoring passive ETS exposure (Tuomi et al., 1999).
This is consistent with our results, where higher concentrations of
trans-3′-hydroxycotinine were measured compared with cotinine.
However from Table 2 it can be seen that Pearson correlations of 0.75
and 0.64 respectively are obtained when correlating cotinine and
trans-3′-hydroxycotinine with 3-EP respectively. Thus both nicotine
metabolites correlated extremely well, but cotinine correlates most
highly with our chemical marker of vapour phase ETS (3-EP),
supporting the hypothesis that 3-EP can be used as a chemical tracer
4.3.2. Normalising vs. non-normalising metabolite levels with creatinine
The correlations of cotinine and trans-3′-hydroxycotinine with 3-
EP, BUT and some non-parent PAH were higher when considering the
non-creatinine-normalised ETS metabolite data (Table 2 and Table S6
supporting information for creatinine-normalised data). This poses
the question of the appropriateness of normalising the ETS urinary
biomarkers with creatinine. Hinwood et al. (2002) argue that 24 h
composite or spot samples can be influenced by urine output rate or
dilution. Viau et al. (2004) advocate creatinine adjustment to correct
al. (2005) argue that creatinine excretion varies with meat intake,
Correlation of urinary biomarkers with selected ETS, VOC compounds, parent PAH and non-parent PAH personal exposures (Pearson R, logged database) (sample size VOC≤86,
VOC selected compounds
Naphthalene (gas phase)
PAH parent compounds
PAH non-parent compounds
Sum of low MW PAH [Naph-An]
Sum of medium MW PAH [Fluo-Chry]
Sum of high MW PAH [B(b)F-Cor]
Sum of 16PAH [Naph-B(ghi)P]
Bold Values represent correlations statistically significant at the 0.05 level (2-tailed).
aThe correlation between the variables is statistically significant in a 2-tailed test at the 0.05 level (*) or at the 0.01 level (**).
bThe correlation between the variables is statistically significant in a 2-tailed test at the 0.05 level only in the high-ETS subset (N=9).
Fig. 2. Scatter log plots of urinary cotinine (in ng/mL) and personal exposure to selected VOC (in μg/m3) and PAH (in ng/m3) where significant correlations have been identified.
N.J. Aquilina et al. / Environment International 36 (2010) 763–771
diurnal factors, age, gender and other factors. This suggests that the
creatinine adjustment method may not adequately reduce the
measurement variability due to urine dilution, as appears to occur
in our dataset (Supporting Information Table S6). Thompson et al.
(1990) adjusted cotinine levels based on the observed regression
relationship between urinary cotinine and urinary creatinine in a
group of smokers instead of the common method of expressing
urinary cotinine as a ratio to urinary creatinine (Thompson et al.,
1990). Along with the traditional method of normalising biomarker
data with creatinine (i.e. ratio of biomarker to creatinine concentra-
tion), we tested also the method proposed by Thompson et al. (1990).
In our study, however, the correlation between logged cotinine and
logged trans-3′-hydroxycotinine with logged creatinine is very low
(N=86; RCot=0.06; RT3HCot=0.26; pN0.10) suggesting that Thomp-
son's method is not valid in the case of non-smoker subjects. Further
investigation of the effect of season, age and gender on the levels of
creatinine, cotinine and trans-3′-hydroxycotinine by means of a
General Linear Model suggests a mild interaction of gender (males)
plus age and the interaction of gender (males) plus season (winter) as
factors affecting creatinine levels (pb0.10), whilst no effect was
flaggedfor cotinine ortrans-3′-hydroxycotinineconcentrations. These
results may indicate different excretion mechanisms for creatinine,
cotinine and trans-3′-hydroxycotinine, consistent with the arguments
provided by Boeniger et al. (1993) and Barr et al. (2005) which
suggest that the creatinine adjustment method may not adequately
reduce the measurement variability due to urine dilution for ETS
4.3.3. Correlation between exposures to PAH and ETS metabolites
Table 2 shows that not only is there a strong association (pb0.01)
between ETS metabolites and personal exposures to ETS VOC markers
(e.g. 3-EP, R=0.75 and BUT, R=0.47 with cotinine), but also with
most of the PAH found predominantly in the particulate phase (≥ 4-
rings), with Pearson coefficients ranging from 0.3 (BghiP/Cot) to 0.55
(Chry/Cot). The PAH compound that shows the strongest correlation
with the ETS urinary biomarkers cotinine (Pearson R=0.55, pb0.01)
and trans-3′-hydroxycotinine (Pearson R=0.52, pb0.01) is chrysene.
These results suggest a direct relation between ETS exposures and
exposure to PAH compounds bound to particles. This is consistent
with an earlier work where chrysene was emphasized to be a main
constituent of sidestream smoke, the primary contributor to ETS
(Georgiadis et al., 2001). This suggests that the ETS urinary
biomarkers studied are good biological indicators of personal
exposure to high molecular weight polycyclic aromatic hydrocarbons,
including carcinogenic PAHs such as benzo(a)pyrene, in our study
population. This finding may not apply to other populations in which
non-ETS exposures to PAH are dominant. Further data obtained in
smoking environments during MATCH is being evaluated to identify if
Chry in conjuction with 3-EP data can be used as a PAH marker for ETS
in indoor environments.
4.4. PAH metabolites as biomarkers of inhaled PAH and ETS exposure
As regards the PAH urinary metabolites, Jacob et al. (2007)
reported that the hydroxyfluorenes, hydroxyphenanthrenes, 1-
hydroxypyrene and 2-naphthol were all significantly higher in
smokers compared to non-smokers (Jacob et al., 2007; Wilhelm et
al., 2007). Merlo et al. (1998) found that non-smoker subjects
exposed to ETS had higher levels of 1-HPyr than those non-ETS
exposed. However in our case, higher concentrations were not
observed in our ETS-exposed group (Table 1), either because the
ETS exposure was not high enough (dependent on number of
cigarettes smoked, time spent in the ETS, distance from smokers,
ventilation) to make such a distinction clear or else other sources of
PAH contributedto higherexposures in the non-exposed group. In the
high-ETS subgroup only, levels of 2-hydroxyphenanthrene, 3+4-
hydroxyphenanthrene and 1-hydroxypyrene were statistically signif-
icantly higher than the levels in the other groups. This suggests that it
is only in high ETS environments that ETS is a relevant source of total
exposure to PAH, compared with other PAH intake pathways such as
dietary sources (Ramesh et al., 2004).
4.4.1. Correlation between PAH and ETS exposures and PAH metabolites
It was also noted that there was no correlation between the PAH
metabolites and the ETS metabolites or the ETS VOC markers; nor was
there a correlation between the PAH metabolite biomarkers and the
respective PAH parent compounds (Table 2). This lack of correlation
may arise because the PAH parent compounds (i.e. Naph, Fl, Phe and
Pyr) come from a multitude of sources, including both inhalation and
the diet. It might also be a consequence of the very low levels of PAH
and VOC concentrations to which the subjects were exposed, even
those classified as ETS-exposed, compared withexposures in smokers,
the latter not having been considered in this project. This is consistent
with the fact that only in the high-ETS subset some correlations
appeared between 2-naphthol and some PAHs, but not with
naphthalene itself, whichsuggests thatit is only in high ETS exposures
that 2-naphthol might be an ETS biomarker and that Naph might have
additional intake sources. A further cause may be inter-subject
variability in host polymorphism in genes for PAH metabolism
(Brand and Watson, 2003). Hence, it appears that the metabolites of
the PAH compounds cannot be used with confidence to assess
personal exposures to PAHs, nor to distinguish between a low and a
non-ETS-exposed group. This finding is consistent with results
reported by Leroyer et al. (2010), which suggest that 1-hydroxypyr-
ene is not an unequivocal biomarker of exposure to atmospheric PAHs
in atmospheric scenarios relevant to the general population. On the
other hand, cotinine and trans-3′-hydroxycotinine show a significant
correlation (pb0.05) with the sum of 16 PAH, which include the low
molecular weight PAH group (Naph–An) containing the PAH parent
It is unfortunate that the PAH metabolites measured in urine
derive from the low molecular weight compounds (naphthalene,
fluorene, phenanthrene and pyrene), for which our data do not reflect
the entire airborne concentration, as the sampling technique collects
only the particle phase, which contains a minor proportion of the low
molecular weight PAHs. This may partly explain the low correlation of
PAHurinary metabolites andparent compounds (Table 2). However,a
recent study by Leroyer et al. (2010) also supports our findings
regarding the lack of correlation between pyrene (gas+particulate
phase) with the 1-hydroxypyrene metabolite in urine. The personal
exposure data for naphthalene (in the gas phase) should be reliable as
this was measured with the VOC methodology. The relatively weak
correlation between naphthalene exposures and urinary 2-naphthol
(in Table 2) is probably due to other non-respiratory sources of
naphthalene exposure, of which there are many (Price and Jayjock,
2008). It is also notable that while Fustinoni et al. (2010) found
positive correlations between respiratory exposure and urinary
concentrations of BTEX compounds, naphthalene did not show a
4.4.2. Importance of other routes of exposure to PAH in urinary
Dietary exposure to PAH might be a greater source of PAH intake
into the body than airborne PAHs as the estimated average adult
dietary intake of BaP and BaA was 1.6 and 0.8 ng/kg bodyweight/day
respectively in 2000 in the UK population (Food_Standards_Agency,
2002). In comparison, at the UK air quality standard for B(a)P of
0.25 ng/m3, assuming a 70 kg person inhaling 20 m3of air daily, B(a)
P intake from the atmosphere is much lower at 0.07 ng/kg
bodyweight/day. However, the relative absorption efficiencies via
the gastrointestinal and respiratory tracts are not known. Neverthe-
less, collecting information about dietary exposures was not included
N.J. Aquilina et al. / Environment International 36 (2010) 763–771
in the study design and therefore the interaction between diet, air
exposures and other subject characteristics (e.g. age, gender and/or
ethnicity) and urinary biomarker excretion would require further
4.5. Limitations and strengths
The authors have identified some limitations and strengths in this
study. The main limitation was that only particulate-phase PAHs were
collected in personal exposures. However, most of the parent
compounds of the urinary biomarkers measured are mainly found
in the gas phase. Therefore, correlations between PAH urinary
biomarkers and parent compounds in the gas phase could not be
assessed within this study. On the other hand, the strength of this
study is that for the first time, personal exposures to PAHs and VOC
compounds and a wide variety of PAH and ETS urinary biomarkers
have been measured simultaneously in the non-occupationally
exposed population. Only Pastorelli et al. (1999) and Leroyer et al.
(2010) report measurements of environmental and biological
exposures to PAHs made simultaneously. However, they only
reported values for 1-hydroxypyrene and 3-hydroxybenzo(a)pyrene,
compared with the wide range of urinary biomarkers that we have
reported, including those of ETS exposure (i.e. cotinine and trans-3′
hydoxycotinine). Therefore, the fact that we have measured simul-
taneously PAH and VOCs in personal exposures and PAH and ETS
urinary metabolites has allowed us to assess the correlation of
environmental concentrations with urinary metabolites for those
subjects in the general population, and in particular to those exposed
to second-hand smoke.
Our study has studied for the first time the relationship between
urinary PAH and ETS metabolites and PAH and VOC personal
exposures in the general population. The monophenolic metabolites
of low molecular weight PAH are not well correlated with the nicotine
metabolites or 3-ethenylpyridine, indicating that ETS is probably not
the main source of exposure to the parent low molecular weight
particle-phasePAHin thenon-smokingpopulation.The factthatsome
PAH metabolites are higher only in the high ETS, but not the low-ETS
subpopulation supports this finding. This is most likely because ETS is
not the main contributor to airborne concentrations for the non-
smoking population or because dietary sources dominate exposure to
these compounds. The fact that airborne gas-phase naphthalene
concentrations are not correlated with urinary 2-naphthol suggests
the latter is the case for this compound. For fluorene and phenan-
threne, our measurement data contain high uncertainties as we were
only able to measure the minority particle-associated phase of these
compounds. These results suggests that PAH metabolites cannot be
used as unequivocal biomarkers of airborne ETS and PAH exposures.
Our study also presents novel data showing significant relation-
ships between urinary excretion of the nicotine metabolites, cotinine
and trans-3′-hydroxycotinine and the gas-phase ETS marker, 3-
ethenylpyridine. This serves to confirm the value of 3-ethenylpyridine
as a chemical marker of ETS exposure which can be used in studies
where it is not practicable to take urine samples.
Furthermore we demonstrate significant associations between the
urinary nicotine metabolite concentrations and personal airborne
as a known human carcinogen. In the context of the measured
exposures, it appears that ETS is an important source of 1,3-butadiene
and benzo(a)pyrene exposure. In the case of the other higher
molecular weight PAH (benzo(a)anthracene, chrysene, benzo(b)
fluoranthene, benzo(k)fluoranthene and dibenzo(a,h)anthracene,
we found significant correlations between the atmospheric exposures
to these compounds and the concentrations of urinary nicotine
metabolites. Correlations of the sum of the medium molecular weight
PAH (fluoranthene to chrysene) and of the sum of high molecular
weight PAH (benzo(b)fluoranthene to coronene) with cotinine and
trans-3′-hydroxycotinine were statistically significant. These data
emphasize the importance of ETS as a medium for exposure of non-
smokers to polycyclic aromatic hydrocarbons and 1,3-butadiene.
These compounds are likely to play a major role in the elevated cancer
risk associated with ETS exposures.
Research described in this article was conducted under contract to
the Health Effects Institute (HEI), an organization jointly funded by
the United States Environmental Protection Agency (EPA) (Assistance
Award No. R-82811201) and certain motor vehicle and engine
manufacturers. The contents of this article do not necessarily reflect
the views of HEI, or its sponsors, nor do they necessarily reflect the
views and policies of the EPA or motor vehicle and engine
manufacturers. Analytical chemistry carried out at the University of
California, San Francisco was funded by the Flight Attendant Medical
Research Institute, the US National Institutes of Health (DA012393,
CA78603), and the California Tobacco Related Disease Research
The authors wish to thank all the 100 subjects who participated in
MATCH, and to acknowledge the support provided by agencies in
London (Environment Agency and DEFRA), Birmingham and Swansea
City Councils and the local media to recruit volunteers. Special thanks
go to Dr Ben Armstrong who advised over the statistical analysis and
the Biosciences Workshop for building and maintaining the atmo-
spheric samplers. The authors wish to thank the MSc and MPhil
students from the University of Birmingham who participated in the
sampling campaigns as well as acknowledge the support and help
provided by Dr. Colvile, Dr. Clemitshaw and the MSc students from
Imperial College during the sampling campaigns in London.
Appendix A. Supplementary data
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