Environ Geochem Health (2015) 37:587–601
DOI 10.1007/s10653-014-9675-7
ORIGINAL PAPER
Multi-pathway assessment of human health risk posed
by polycyclic aromatic hydrocarbons
Changsheng Qu • Bing Li • Haisuo Wu
Shui Wang • John P. Giesy
•
Received: 8 November 2014 / Accepted: 30 December 2014 / Published online: 9 January 2015
Ó Springer Science+Business Media Dordrecht 2015
Abstract To assess aggregate exposure to polycyclic
aromatic hydrocarbons (PAHs) via several environmental media and pathways, a probabilistic framework
for multi-pathway health risk assessment that integrates PAHs potency equivalence factors, risk estimation modeling, and Monte Carlo simulation was
applied to a case study in Nanjing, which is an
important industrial city in China. Incremental lifetime
risk of additional cancers posed by exposure to 16
USEPA priority PAHs in air, water, soil, and fish was
assessed. Risks to three age groups, infants, children,
and adults, through various exposure pathways,
including oral ingestion, dermal absorption, and inhalation, were estimated. Results of the analysis of risk
indicated that B[a]P, B[b]F, and BA were the predominant PAHs pollutants in Nanjing. Risk of additional
cancer for local adults was on average 2.62 9 10-5.
The risks were primarily due to ingestion of fish and
inhalation, which contributed 99 % of the total risks.
By contrast, risk to infants was essentially negligible.
Results of a sensitivity analysis indicated that the input
variables of concentration of PAHs in fish (Cf), the
body weight (BW), and the ingestion rate of fish (IRf)
were the major influences on estimates of risks.
C. Qu (&) B. Li H. Wu S. Wang
Key Laboratory of Environmental Engineering, Jiangsu
Academy of Environmental Science, Nanjing 210036,
China
e-mail: 031202026@163.com
J. P. Giesy
Department of Zoology, Center for Integrative
Toxicology, Michigan State University, East Lansing,
MI, USA
J. P. Giesy
State Key Laboratory of Pollution Control and Resource
Reuse, School of the Environment, Nanjing University,
Nanjing 210023, China
J. P. Giesy
Department of Veterinary Biomedical Sciences,
Toxicology Centre, University of Saskatchewan,
Saskatoon, SK, Canada
Keywords PAHs Environmental exposure Multipathway Monte Carlo simulation Asia Cancer
Introduction
Polycyclic aromatic hydrocarbons (PAHs) are a group
of organic compounds containing two or more fused
J. P. Giesy
Department of Biology and Chemistry and State Key
Laboratory in Marine Pollution, City University of Hong
Kong, Kowloon, Hong Kong, SAR, China
J. P. Giesy
School of Biological Sciences, University of Hong Kong,
Hong Kong, SAR, China
123
588
aromatic rings. They can enter into and spread through
the environment via various routes, including domestic and industrial wastewater discharges, oil spills, tire
wear debris, asphalt particles, atmospheric transport,
dispersion and deposition of industrial stack emission,
and vehicle exhaust (Binet et al. 2002; Srogi 2007;
Feng et al. 2009). Because of their potential to
bioaccumulate, persistence, and carcinogenic and
mutagenic potencies, PAHs have been of scientific
interest for many years (Orecchio and Papuzza 2009).
Hundreds of these compounds exist in the environment, 16 of which with greater toxicities have been
selected by the US Environmental Protection Agency
(USEPA) as priority pollutants to be controlled and
have, therefore, been routinely analyzed (Sun et al.
1998) (Table 1).
In China, since the 1970s, rapid development of
industry, agriculture, and municipalities has resulted in
greater loads of PAHs being distributed in the atmosphere, water, and soil (Xu et al. 2006; Shi et al. 2011;
Zhang et al. 2014). In the past few decades, previous
studies have focused on the occurrence, sources, and
spatial distribution of PAHs (Feng et al. 2009; Wang
et al. 2011a, b; Cao et al. 2010; Lin et al. 2012; Zhang
et al. 2011). It was found that Chinese PAH emissions
contributed over 20 % to the total global PAH emissions
(Zhang and Tao 2009). As a result, PAH emissions in
excess of 116,000 tons/year have resulted in the
contamination of various environmental media in China
(Zhang et al. 2007). For instance, on the whole, ranking
concentration levels of PAHs in rivers of the world,
PAHs level in water-dissolved phase in Chinese rivers
was a little higher than that in other countries (Feng et al.
2009). These researches currently serve many compliance monitoring needs. However, PAHs can pose risk to
the public through inhalation of dust and from soil and
water by direct ingestion and dermal contact. Because of
the rapid increase in automobile and industrial production, the general Chinese population has more opportunities to be exposed to PAHs from multiple sources and
routes than do people in most other places in the world (Ji
et al. 2010). It was reported by 1.6 % of the lung cancer
morbidity in China was due to inhalation exposure to
ambient air PAHs (Zhang et al. 2009). Therefore, to
protect public health, besides environmental monitoring
studies, potential exposures to these PAHs and their
associated health risks deserve more attention.
Assessment of risks to human health, formalized in
1983 by the US National Research Council, is a process
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Environ Geochem Health (2015) 37:587–601
for estimating potential adverse health effects to humans
from exposure to chemicals in environmental media
(NRC 1983a). Several studies have been conducted to
evaluate risks posed by exposure to PAHs through
different environmental media or exposure pathways.
According to the risk assessment results, the occupational
risk to traffic policemen in Tianjin fell within the range
from 10-6 to 10-3 through inhalation (Hu et al. 2007), the
cancer risk levels via dermal contact and ingestion of soil
ranged from 10-7 to 10-6 in Guangzhou (Wang et al.
2011a, b), and the average cancer risk caused by dietary
exposure fell within the range from 10-6 to 10-5 in
Taiyuan (Xia et al. 2010). It can be found that oral
ingestion and dermal contact of soil and food, as well as
inhalation, may all pose potential risk to the public.
However, most of previous reports focused on exposure
to PAHs through certain environmental media or exposure pathways. Studies concerning multi-pathway assessment of human health risk are quite limited. A media- or
pathway-specific assessment approach might not guarantee public safety, for the public expose to PAHs
through various environmental media or exposure pathways. It is difficult to derive the overall health risk and
identify the key exposure route without multi-pathway
risk analysis. Therefore, it is vital to assess aggregate
exposure to PAHs via multiple media and pathways (Qu
et al. 2012a; Marin et al. 2003).
In this study, an integrated, multi-pathway assessment to estimate the lifetime risk of additional cancers
due to exposure to PAHs through multiple pathways,
including oral ingestion, dermal contact, and inhalation,
was conducted in Nanjing. As an extension of previous
efforts, the published literature on concentrations of the
16 EPA priority PAHs in air, water, soil, and food in
Nanjing was reviewed. Next, a multi-pathway assessment of risks of additional cancers was conducted to fill
the gap between routine environmental monitoring data
and the decision making support for protecting populations from exposure to PAHs. Detailed sensitivity and
uncertainty analyses were conducted to identify the
critical input variables that require further study.
Materials and methods
Study area
Nanjing, a typical megacity in eastern China (31° and
32°N, 118° and 119°E) with more than 8.1 million
2.1–6.7
1.8–11
0.5–2.0
1.0–9.4
Benzo[a]pyrene (B[a]P)
Indeno[1,2,3-c,d]pyrene (InP)
Dibenz[a,h]anthracene (DBA)
Benzo[g,h,i]perylene (BghiP)
ND not detected
14–43
ND
Benzo[b]fluoranthene (BbF)
Benzo[k]fluoranthene (BkF)
3.3–8.9
Chrysene (Chr)
5.7 ± 2.4
1.5–9.1
ND–13
0.3 ± 0.7
2.1 ± 2.6
ND–1.9
0.8–7.9
Anthracene (Ant)
Fluoranthene (Flt)
Pyrene (Pyr)
ND
0.3 ± 0.7
ND
ND–1.8
Fluorene (Flu)
Phenanthrene (Phe)
Benz[a]anthracene (BA)
ND
ND
Acenaphthene (Ace)
4.0 ± 2.7
0.9 ± 0.5
4.4 ± 1.6
5.5 ± 3.1
ND
29 ± 11
6.7 ± 1.9
4.0 ± 4.2
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
0.06–2.11
0.05–0.73
0.06–2.61
ND–1.33
ND–0.58
ND–0.99
ND
ND
ND
ND
Range
Mean
Range
Naphthalene (Nap)
Water (ng/L)
Air (ng/m3)
Acenaphthylene (Ac)
Compounds
Table 1 Concentrations of PAHs in air, water, and soil in Nanjing
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
0.19 ± 0.88
0.13 ± 0.28
0.22 ± 1.08
0.44 ± 0.53
0.19 ± 0.23
0.28 ± 0.41
Mean
ND–11.67
1.32–8.89
0.70–5.26
ND–20.08
0.79–5.87
1.57–51.67
0.67–47.58
0.92–7.64
0.90–10.77
3.56–78.60
1.03–7.07
2.61–54.46
ND–22.23
ND
ND
ND–89.90
Range
Soil (ng/g)
3.43 ± 3.17
3.34 ± 2.50
2.00 ± 1.45
3.33 ± 5.68
1.90 ± 1.50
19.85 ± 14.60
13.00 ± 12.02
3.72 ± 3.46
2.61 ± 2.80
24.55 ± 21.96
2.70 ± 2.14
24.08 ± 17.06
8.68 ± 7.34
ND
ND
32.92 ± 27.46
Mean
0.1–15.6
0.1–1.5
0.3–17.4
0.1–9.3
0.1–9.1
0.2–13.5
4.4–132
1.2–55.6
22.4–267
43.4–509
9.5–611
161–794
28–320
5.2–207
3.5–30.7
–
Range
Fish (ng/g)
0.87 ± 3.01
0.17 ± 0.30
1.04 ± 3.36
0.57 ± 1.81
1.18 ± 2.00
2.00 ± 3.02
26.50 ± 26.74
4.70 ± 10.73
101.46 ± 68.02
204.97 ± 122.63
39.84 ± 116.71
422.67 ± 179.77
92.40 ± 71.45
19.60 ± 40.77
9.67 ± 6.06
–
Mean
Environ Geochem Health (2015) 37:587–601
589
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Environ Geochem Health (2015) 37:587–601
Fig. 1 Location of the
study area
residents, is the capital of Jiangsu Province and
located in the lower Yangtze River drainage basin
(Fig. 1). As one of the most rapidly developing
megalopolises of China, Nanjing has experienced
accelerated industrialization and urbanization in
recent years. At the same time, PAHs are being
emitted to the environment, where they might pose a
threat to the public. Because contamination by the
PAHs is an increasing environmental concern, the
comprehensive study of human exposure to the PAHs
pollutants in Nanjing deserves much more attention.
performance liquid chromatography (HPLC) (Yin
et al. 2008). Little information on concentrations of
PAHs in food of Nanjing was available. Since fish
protein features prominently in the diet of people in
Nanjing, the concentration data of PAHs in fish were
used to assess this risk posed by ingestion of food. A
total of 193 samples of fishes, including 24 species
from Tai Lake, a main source of fish in Nanjing
market, were examined for PAHs (Wang et al. 2012)
(Table 1).
Potency equivalence factors (PEFs)
Environmental data
Drinking water of families in Nanjing (n = 25) was
collected in December 2013. The water samples
covered five major water treatment plants in Nanjing.
The 16 PAHs that have been identified as priority
pollutants by the USEPA were examined. Standard
target organic constituents were obtained from Supelco (Bellefont, PA, USA). A solid-phase extraction
(SPE) method was used to extract the target contaminants in water samples (Shi et al. 2012). Quality
assurance analyses were conducted according to
previous studies (Hu et al. 2013). Concentration of
PAHs in ambient air, soil, and food of Nanjing was
available from previous monitoring and investigations, which have been published in the peer-reviewed
literature. PAHs in air were quantified by use of a
week-long period (n = 28) on a day/night basis in the
summer and winter of 2004. Samples were collected
by the use of PM2.5 high-volume air samplers (Wang
et al. 2007). In 2007, 126 samples of soil were
collected from five districts of Nanjing and concentrations of PAHs were determined by the use of high-
123
Information on relative potencies was not available for
all of the PAHs. The carcinogenic risk posed by a multicomponent PAHs mixture can be estimated by conversion of the carcinogenic potency of each individual
PAH relative to that of B[a]P, which is considered to be
the most potent carcinogen among the PAHs. Carcinogenic potency of mixtures of PAHs (B[a]Peq) can be
calculated as the sum of the products of B[a]P
equivalents (PEF) and concentrations of individual
PAHs. This process can simplify and increase accuracy
of risk assessments (Chowdhury et al. 2009). There are
several sets of PEFs that have been developed by
various agencies and scientists. Among these, the PEFs
proposed by Nisbet and LaGoy have been demonstrated
to be among the most predictive PEFs and have been
commonly used (Petry et al. 1996; Wang et al. 2011a, b;
Peng et al. 2011) (Table 2).
Multi-pathway exposure modeling
PAHs exist in various environmental media, such as
air, water, and soil, and can enter human body via
Environ Geochem Health (2015) 37:587–601
591
Table 2 Potency equivalence factors (PEFs) for individual PAHs relative to B[a]P (Nisbet and Lagoy 1992)
Compound
PEF
Compound
PEF
Naphthalene (Nap)
0.001
Benz[a]anthracene (BA)
0.1
Acenaphthylene (Ac)
0.001
Chrysene (Chr)
0.01
Acenaphthene (Ace)
Fluorene (Flu)
0.001
0.001
Benzo[b]fluoranthene (BbF)
Benzo[k]fluoranthene (BkF)
0.1
0.1
Phenanthrene (Phe)
0.001
Benzo[a]pyrene (B[a]P)
1
Anthracene (Ant)
0.01
Indeno[1,2,3-c,d]pyrene (InP)
0.1
Fluoranthene (Flt)
0.001
Dibenz[a,h]anthracene (DBA)
1
Pyrene (Pyr)
0.001
Benzo[g,h,i]perylene (BghiP)
0.01
Fig. 2 Human exposure to
PAHs through multipathways
different routes, including ingestion, inhalation, or
dermal contact (Fig. 2). Assessments of cumulative
exposure estimate intensity, frequency, and duration
of exposures to agents, such as PAHs present in the
environment (NRC 1983b). Time-averaged dose can
be linked to the exposure medium concentration and is
used here for the exposure analysis [Eq. 1, adapted
from (USEPA 2004)].
C IR EF ED
ADI ¼
BW AT
year); ED is duration of exposure (years); BW is body
weight (kg); and AT is duration over which the dose is
averaged (days).
Contaminants in water and soil can adhere to
exposed skin and enter the human body through dermal
absorption. Average daily intakes of the PAHs through
dermal contact of water can be estimated using Eq. 2.
ADIderw ¼
ð1Þ
where ADI is the average daily exposure dose (mg/kg/
day); C is the B[a]P equivalent concentration in the
exposure medium, expressed as mg/L, mg/kg, or mg/
m3; IR is the rate of ingestion, expressed as L/day, kg/
day, or m3/day; EF is the exposure frequency (days/
Cw Abath Kp t EF ED
BW AT
ð2Þ
where Cw is the concentration of B[a]P equivalents in
water, Abath is the total skin surface area (cm2), Kp is
the dermal permeability coefficient of the PAHs in
water (cm/h), and t is the time for shower (min/day).
Average daily intakes of the PAHs through dermal
contact of soil can be estimated using Eq. 3.
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592
ADIders ¼
Environ Geochem Health (2015) 37:587–601
Cs As AF ABS EF ED
BW AT
ð3Þ
where Cs is the B[a]P equivalent concentration in soil,
As is the dermal surface area exposed (cm2), AF is the
soil-to-skin adherence factor (mg/cm2/day), and ABS
is the dermal absorption fraction (dimensionless).
Incremental lifetime cancer risk (ILCR) model
Risks of additional cancers in adults, children, and
infants were evaluated by applying the incremental
lifetime cancer risk (ILCR) model (USEPA 2004).
The model assumes that exposure to any amount of a
carcinogen will increase the risk of cancer, that is,
there is no safe or threshold dosage. A slope factor
multiplied by the average daily intake gives a maximum probability that a receptor will develop cancer
from exposure to a chemical over lifetime (USEPA
2004). And risks are assumed to be additive from
multiple chemicals and routes (Eq. 4).
Risk ¼ ADI SF
ð4Þ
where risk is the incremental cancer risk to an
individual over a lifetime, which is accumulative
across dermal, oral, and inhalation exposure; SF is the
carcinogenicity slope factor (mg/kg/day)-1, which
represents an upper bound estimate of the probability
of individual’s carcinogenic response per unit intake
dose of chemical over lifetime. SFs of B[a]P for each
exposure pathway are obtained from open databases or
the literature and are presented in Table 3.
Monte Carlo simulation
Uncertainties arising from data scarcity, parameter
variability, and model limitations can affect defining,
evaluating, and choosing various options for management of risks (Chen et al. 2011; Qu et al. 2012a, b;
Chen et al. 2015). Integration of variability and
uncertainty into risk estimation can lead to a more
Table 3 Carcinogenic slope factors of PAHs utilized in the
human health risk calculations
SF (mg/kg/day)-1
References
Inhalation
3.9
OEHHA (2011)
Oral
7.3
USEPA (2012)
Dermal
25
Knafla et al. (2006)
123
realistic understanding of risk (Chen and Chen 2012;
Chen et al. 2013). Monte Carlo simulation techniques,
which are often used to address uncertainty in
assessments of risks to humans (Mari et al. 2009),
provide quantitative estimates of probabilities of
exposure and adverse outcomes (Thompson et al.
1992). Repeated sampling based on probability distributions of exposure variables results in a frequency
distribution of risk. Variables used in the simulation
include parameters describing demographics of the
population, rates of inhalation, ingestion, dermal
absorption, and risk factors. In March 2014, a dietary
survey was conducted for the general population of
Nanjing by the use of a questionnaire given to 127
randomly selected individuals. The rate of ingestion of
fish, expressed as grams per day (g/day), was obtained,
while values for other parameters were taken from the
open published literature (Table 4).
Sensitivity analyses were conducted to identify the
most significant parameters that were included in the
risk estimation. Spearman’s rank order correlation
coefficients between inputs and outputs were calculated. The Monte Carlo simulation and sensitivity
analysis were performed using @Risk software (version 5.5; Palisade Corporation; Ithaca, NY, USA). To
ensure the stability of results, simulations were run for
5,000 iterations with each parameter sampled independently. Concentrations of B[a]Peq were estimated
by the multiplication of the individual PAH concentration by its PEF on the basis of the Monte Carlo
simulation. The probability density functions were
fitted to the observed concentration data values using
the @Risk Best Fit function. The goodness of fit was
determined using the Chi-squared statistic, the Kolmogorov–Smirnov statistic, and the Anderson–Darling statistic.
Results and discussion
B[a]P equivalent concentration (B[a]Peq)
Lognormal curves were found to be the distributions
that best fit the distribution of concentrations of
B[a]Peq in various environmental media (Fig. 3).
Firstly, the mean concentration of B[a]Peq in air was
estimated to be 8.74 ng/m3. It is much lower than that
in occupational environments, like in carbon black
manufacturing industry in southern Taiwan (308 ng/
Environ Geochem Health (2015) 37:587–601
593
Table 4 Risk parameters used for the Monte Carlo simulation
Parameter
Symbol
Units
Infants
Children
Adults
References
Age
–
Year
0–1
2–18
19–70
Body weight
BW
kg
6.79 ± 1.27
37.3 ± 9.1
58.7 ± 12.0
Chen and Liao (2006),
Xiao et al. (2005)
IRa
m3/day
5.05 ± 0.49
9.67 ± 2.39
12.44 ± 1.27
Wang et al. (2009)
Population parameter
Inhalation parameter
Inhalation rate
Ingestion parameter
Ingestion rate of water
IRw
mL/day
283.25 ± 91.48
497.35 ± 138.28
1,366 ± 728
USEPA (1997, 2008)
Ingestion rate of soil
IRs
mg/day
0–30
24 ± 4
25 (0.1–50)
Stanek et al. (2001),
USEPA (2008),
LaGoy (1987)
Ingestion rate of fish
IRf
mg/day
4.16 ± 2.37
27.45 ± 5.52
61.25 ± 13.86
Abath
m2
0.39 ± 0.05
1.09 ± 0.37
1.67 ± 0.10
Wang et al. (2008)
719 ± 1.19
860 (430–2,160)
1,530
(760–4,220)
Wang et al. (2008),
Chen and Liao (2006)
0.04
0.65 ± 1.2
0.49 ± 0.54
Dermal parameter
Total skin surface area
2
Exposed skin surface
area
As
cm
Soil-to-skin adherence
factor
Time for shower
AF
mg/cm2-day
t
min/day
15
18.41 ± 1.32
10.4 (3–61)
USEPA (2004),
Finley et al. (1994)
USEPA (1997, 2008)
Dermal absorption
factor
ABS
Unitless
0.13
0.13
0.13
USEPA (2004)
Dermal permeability
coefficient
Kp
cm/h
0.7
0.7
0.7
USEPA (2004)
Exposure frequency
EF
Days/year
345 (180–365)
345 (180–365)
345 (180–365)
Smith (1994)
Averaging time
AT
Days
25,550
25,550
25,550
USEPA (1997)
Exposure duration
ED
Year
1
17
52
USEPA (1997, 2008)
Risk model parameter
The mean and standard deviation were used for lognormal distributions; minimum and maximum for uniform distributions; and
mean, minimum, and maximum for triangular distributions
m3) and at road intersections in the city of Tianjin
(82.4 ng/m3), but higher than that on campus in
Tianjin (2.4 ng/m3) (Tsai et al. 2001; Hu et al. 2007).
Mean concentration of B[a]Peq in air in Nanjing was
close to the current annual limit on concentration of
B[a]P in China (10 ng/m3). However, beginning in
2016, the newly recommended air quality standard of
B[a]P annual limit will be reduced to 1 ng/m3 (MEP
2012). Secondly, the concentration of B[a]Peq in
drinking water in Nanjing was 0.004 ng/L on average
and far less than the national standard limit of 10 ng/L
(MOH 2006). Thirdly, the mean concentration of
B[a]Peq in soil in Nanjing was 8.19 ng/g, which is
much less than the proposed national limit value of
100 ng/g, dm for farmland (MEP 2008). Compared to
the concentration of B[a]Peq in road dust in polluted
industrial areas in Ulsan, Korea (0.93–16.74 lg/g)
(Dong and Lee 2009), mean concentration of B[a]Peq
in soil in Nanjing was relatively low. Furthermore, this
value was also similar to the background concentrations of B[a]P in uncontaminated soils in Poland that
ranged from 1.5 to 78 ng/g (Wcisło 1998), but a little
higher than that in Tarragona, Spain (\2 ng/g) (Nadal
et al. 2004). Finally, contamination by PAHs might
occur during processing of food or through environmental pollution, especially in fish. The mean concentration of B[a]Peq in fish used in this study was
4.58 ng/g. This concentration is slightly less than the
national limit of B[a]P in aquatic products in China
(5 ng/g) (MOH 2012), but exceeded the European
limit of B[a]P in muscle meat of fish (2 ng/g) (CEC
2006). Compared to previous studies, B[a]Peq in fish in
Nanjing was less than that in Taiyuan (5.71 ng/g) (Xia
et al. 2010), but greater than that in Tianjin, northern
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Environ Geochem Health (2015) 37:587–601
Fig. 3 B[a]Peq concentrations of each environmental media
China (1.52 ng/g), and Seoul, South Korea
(0.15–0.52 ng/g) (Li 2007; Yoon et al. 2007).
The relative proportions of B[a]Peq varied among
matrices and media. The concentration of B[a]Peq in
air was primarily contributed by B[a]P and B[b]F,
which accounted for 46 and 30 % of the total PAHs,
respectively. Anthracene contributed the greatest
proportion (71 %) to the concentration of B[a]Peq in
water, followed by Acenaphthene and Fluorene with
contributions of 8.3 and 7.9 %, respectively. In soil,
DBA, B[a]P, and B[b]F were the predominant
contributors to the concentration of B[a]Peq, providing
41, 24, and 21 %, respectively. In fish, B[a]P, BA, and
Anthracene contributed 36, 14, and 12 %, respectively, to the B[a]Peq.
For infants, inhalation and ingestion of fish were the
dominant pathways of exposure, whose median
B[a]Peq exposure doses were 8.25 9 10-8 and
3.02 9 10-8 mg/kg, bm/day, respectively. The
B[a]Peq daily exposure dose from other pathways
ranged from 2.03 9 10-12 to 2.17 9 10-10 mg/kg,
bm/day. In children and adults, dose of B[a]Peq was
greater than that of infants. Moreover, ingestion of fish
was the main pathway of exposure with B[a]Peq mean
daily exposure doses of 7.04 9 10-7 and 2.91 9 10-6
mg/kg, bw/day for children and adults, respectively.
Following ingestion of fish, inhalation exposure doses
were 4.71 9 10-7 and 1.43 9 10-6 mg/kg, bm/day,
respectively. Similarly, the contribution from other
exposure pathways was relatively slight.
Analysis of exposure
Estimation of risk
Probability functions of concentrations of B[a]Peq in
air, water, soil, and fish were used in Monte Carlo
simulations to estimate exposure to B[a]Peq (Fig. 4).
From daily exposures via different exposure pathways, the incremental lifetime cancer risks were
estimated using Eq. 4, and Monte Carlo simulation
123
B[a]Peq daily exposure doses of adults (mg kg-1 d-1)
B[a]Peq daily exposure doses of children (mg kg-1 d-1)
B[a]Peq daily exposure doses of infants (mg kg-1 d-1)
Environ Geochem Health (2015) 37:587–601
595
95th
75th
mean
25th
5th
1.4E-07
1.2E-07
6.0E-10
1.0E-07
5.0E-10
4.0E-10
8.0E-08
3.0E-10
6.0E-08
2.0E-10
1.0E-10
4.0E-08
1.0E-12
Water ingestion Soil ingestion
Dermal contact Dermal contact
of water
of soil
Water ingestion Soil ingestion
Dermal contact Dermal contact
of water
of soil
2.0E-08
0.0E+00
Inhalation
Fish ingestion
1.6E-06
1.4E-06
1.2E-08
1.2E-06
1.0E-08
1.0E-06
8.0E-09
8.0E-07
6.0E-09
4.0E-09
6.0E-07
2.0E-09
4.0E-07
0.0E+00
2.0E-07
0.0E+00
Inhalation
Fish ingestion
7.0E-06
6.0E-06
4.0E-08
5.0E-06
3.0E-08
4.0E-06
2.0E-08
3.0E-06
1.0E-08
2.0E-06
0.0E+00
Water ingestion Soil ingestion Dermal contact Dermal contact
of water
of soil
1.0E-06
0.0E+00
Inhalation
Fish ingestion
Fig. 4 Box and whisker plots of B[a]Peq daily exposure doses for three age groups
123
596
Fig. 5 Total incremental lifetime cancer risk to different age
groups
was used to calculate cumulative probability of the
total risks of different age groups (Fig. 5). Overall, the
incremental lifetime cancer risks posed by exposure to
PAHs through different exposure pathways were in the
order of adults [ children [ infants. The total risk to
adults was 2.62 9 10-5 on average (i.e., 26 in a
million). For children, the mean risk was 7.08 9 10-6,
which was much less than that of the adults. Because
of physiological and behavioral differences, the
exposures of infants were expected to differ from
those of adults and children. The average risk to
infants for that portion of their lives was estimated to
5.31 9 10-7, which was less than those of adults and
children.
There are no absolute criteria for acceptable
number of additional cancers over a lifetime. In most
jurisdictions, the one-in-one-million (1 9 10-6)
chance of additional cancers proposed by the USEPA
is frequently used as a management goal for risks
posed by environmental contamination. However,
risks ranging from 1-in-10,000 (1 9 10-4) to 1-in1,000,000 (1 9 10-6) are generally considered
acceptable, depending on the situation and circumstances of exposure (HC 2004). Compared with this
risk range, the total risks combined from different
exposure pathways of infants (5.31 9 10-7 on average) were minimal. For children, the mean carcinogenic risk was 7.08 9 10-6, and the probabilities of
total risks exceeding 1 9 10-5 and 1 9 10-4 were
15 % and 0, respectively. For adults, the carcinogenic
risks were not significant from the mean obtained
based on point estimations (2.62 9 10-5). However,
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Environ Geochem Health (2015) 37:587–601
from the cumulative probability curve, it was found
that probabilities of total risks to adults exceeding
1 9 10-5 and 1 9 10-4 were as high as 97.6 and
0.5 %, respectively. That is, there was a potential
carcinogenic risk to local residents. Thus, it is
unilateral to judge the risk only by mean values or
point estimation. Probabilistic risk assessments, based
on Monte Carlo simulation, can provide more comprehensive information, which is crucially important
for decision making of risk control.
Multi-pathway assessment of exposure was conducted to determine relative contributions of each
exposure pathway (Table 5). For all age groups, the
incremental lifetime risks of additional cancers posed
by ingestion of fish and inhalation were the greatest
and together accounted for nearly 99 % of the total
risks. For adults, on average, ingestion of fish and
inhalation contributed 81.81 and 17.07 %, respectively, to the risk of additional cancers. Other
pathways of exposure contributed only 1 %. Ingestion
of fish and inhalation contributed 72.77 and 25.97 %,
respectively, to the total risk to children. For infants,
inhalation contributed most to the total risk, accounting for 57.56 %, whereas ingestion of fish contributed
41.86 %. The contribution of inhalation reflects the
increasingly grim situation of air pollution control in
the studied area, which is a microcosm of the
conditions prevalent in China. The source of fish in
this study was Tai Lake, a eutrophic shallow lake that
is surrounded by large industrial areas. The contribution of ingestion of fish to the overall risk shows that
food ingestion is the overwhelmingly dominant exposure pathway of environmental PAHs. Therefore,
assessments of risks to health of humans should be
conducted further for aquaculture and fisheries activities in Tai Lake to avoid health risk through aquatic
products consumption. Because of the small concentration of B[a]Peq in drinking water, the ILCRs from
ingestion and dermal contact of water were essentially
negligible. With regard to the ingestion and dermal
contact of soil, they contributed little to the total risks
and could be considered negligible for all three age
groups.
For substances deemed to be carcinogenic, the
estimated exposure is multiplied by the appropriate
slope factor to derive an estimate of the potential risk
associated with that exposure. However, this model
does not assume any threshold for effects. As such, it is
2.88E-07
2.70E-07
8.40E-07
8.88E-08
8.45E-07
6.90E-10
Dermal contact of soil
2.28E-09
1.35E-09
4.97E-10
8.81E-09
2.61E-07
3.71E-08
6.12E-09
1.35E-05
2.13E-05
5.39E-09
1.69E-08
4.63E-05
8.20E-06
8.00E-10
3.40E-06
1.29E-09
5.15E-06
1.33E-09
1.15E-05
3.84E-09
1.93E-06
3.10E-10
1.14E-10
1.72E-07
2.22E-07
6.10E-08
3.91E-11
Ingestion of fish
Dermal contact of
water
5.35E-07
1.27E-10
3.53E-09
8.04E-09
3.65E-09
1.14E-09
1.59E-09
3.72E-09
1.41 E-10
Ingestion of soil
3.50E-10
3.69E-10
8.93E-09
1.57E-08
3.24E-08
1.35E-06
1.47E-08
4.00E-09
3.85E-10
4.45E-06
6.90E-06
1.11E-09
9.01E-11
8.13E-11
8.57E-11
2.51E-06
7.70E-07
1.84E-06
2.49E-10
2.20E-11
1.42E-11
9.34E-8
3.05E-07
1.47E-11
4.10E-11
3.80E-12
Ingestion of water
4.77E-07
1.74E-07
Inhalation
Mean
95 %
8.70E-07
3.28E-06
5%
SD
Mean
95 %
5%
5%
SD
Children
Infants
Exposure pathway
Table 5 Incremental lifetime cancer risks of different exposure pathways
Adults
95 %
Mean
SD
Environ Geochem Health (2015) 37:587–601
597
believed (but not proved) that the slope factor for
carcinogenic substances will overestimate the actual
cancer incidence associated with low-dose exposure to
environmental pollutants (Kelly and Cardon 1991).
Furthermore, the B[a]Peq-based approach is necessarily limited to 16 priority PAHs and does not account
for the toxicity of all PAHs to which the population is
generally exposed. It should also be pointed out that
this study presented modeled estimates of exposure
and modeled estimates of risk, but no evidence of
actual health effects was reported. More detailed and
in-depth health investigation is necessary in the future
to examine whether adverse health outcomes occur.
Despite these limitations, this study has the merit of
taking into account various exposure pathways and
estimating the potential risk from a probabilistic view
by applying Monte Carlo simulation approach to show
the actual PAHs profiles encountered in environmental
settings.
Sensitivity analysis
Uncertainties are inherent in quantitative risk assessment. For this reason, a quantitative sensitivity
analysis was conducted to further evaluate the variability and uncertainty of the parameters that contributed most significantly to the risk estimations. The
results of the sensitivity analysis for each exposure
pathway in the assessment model were shown in the
form of tornado plots illustrating the Spearman’s rank
order correlation coefficients (Fig. 6). The tornado
plot gave both the magnitude and direction (positive or
negative) of the correlation. The results of the analysis
indicated that the concentration of B[a]Peq in fish (Cf),
the body weight (BW), the ingestion rate of fish (IRf),
the exposure frequency (EF), and the B[a]Peq concentration in air (Ca) were the most influential variables
for all the three age groups. Therefore, in order to
increase accuracy of the risk estimation, efforts should
focus on more accurately and precisely defining the
probability distributions of the Cf, BW, IRf, EF, and Ca
parameters. For instance, more survey and examination of PAHs in different environmental media,
especially in meat, rice, vegetable, and air, is needed.
It is also necessary to conduct more surveys of diets of
local people and their cooking habits to illustrate the
importance of cooking, which might influence both
exposure parameters and concentration of PAHs in
food.
123
598
Fig. 6 Sensitivity analysis
for incremental lifetime
cancer risk models for three
age groups
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Environ Geochem Health (2015) 37:587–601
Environ Geochem Health (2015) 37:587–601
Conclusions
Aggregate probabilistic estimates of exposures of
humans to PAHs via various environmental media and
pathways were developed, and a multi-pathway framework for assessment of risks was proposed by integrating PAHs potency equivalence factors, risk estimation
modeling, and the Monte Carlo simulations. In the case
study of Nanjing, People’s Republic of China, incremental lifetime risks of additional cancers posed by 16
priority PAHs in air, water, soil, and fish through
multiple routes of exposure, including oral ingestion,
dermal absorption, and inhalation exposure, were
estimated for infants, children, and adults. Concentrations of PAHs in the environment of Nanjing represented a risk of 2.62 9 10-5 for additional cancers in
adults exposed via all pathways. Exposures to B[a]P,
B[b]F, and BA through ingestion of fish and inhalation
contributed 99 % to the total risks. Thus, the potential
health hazard from the PAHs deserves more attention in
the future. Results of this study imply that multipathway health risk assessment might be a useful tool to
estimate the health risk posed by environmental PAHs
pollution. Through identification of key exposure
pathways and the selection of groups at greater risk,
more practical control of pollution and thus more
effective measure to alleviate the risk can be formulated
to ensure the most effective and least costly methods of
minimizing risks of additional cancers to the public. It
may be helpful to the understanding of PAHs-triggered
environmental health problem and further benefit the
pollution control and risk alleviation for the counties
and regions those troubled with PAHs pollution.
However, this study still has uncertainties and limitations. Importantly, because of the absence of a local
dietary survey and of information concerning the PAH
concentrations in the local foods, only fish was included
in this study. More detailed information on the PAHs
concentrations of different media is required to reduce
the uncertainties and limit the variabilities. Moreover,
on the basis of sensitivity analysis results, further
research should be directed to better characterizing
those parameters that could most effectively improve
the estimation results.
Acknowledgments This work was supported by National
Natural Science Foundation (Grant No. 41201545), National
Meta-Program for Science and Technology of Water Pollution
Control (2012ZX07506-001), National 863 Project (2013AA
06A309), and Jiangsu Science Program for Environmental
599
Protection (2014038). Prof. Giesy was supported by the program
of 2012 ‘‘High Level Foreign Experts’’ (#GDW20123200120)
funded by the State Administration of Foreign Experts Affairs, the
P.R. China to Nanjing University and the Einstein Professor
Program of the Chinese Academy of Sciences. He was also
supported by the Canada Research Chair program, a Visiting
Distinguished Professorship in the Department of Biology and
Chemistry and State Key Laboratory in Marine Pollution, City
University of Hong Kong.
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