Journal of Environmental Protection, 2011, 2, 1192-1206
doi:10.4236/jep.2011.29137 Published Online November 2011 (http://www.scirp.org/journal/jep)
The Volatilization of Pollutants from Soil and
Groundwater: Its Importance in Assessing Risk for
Human Health for a Real Contaminated Site
Pamela Morra, Laura Leonardelli, Gigliola Spadoni
Department of Chemical, Mining & Environmental Engineering, Alma Mater Studiorum, University of Bologna, Bologna, Italy.
Received July 25th, 2011; revised August 29th, 2011; accepted October 4th, 2011.
ABSTRACT
Pollution of different elements (air, water, soil and subsoil) resulting both from accidental events and from ordinary
industrial and civil activities causes negative effects on the human health and on the environment. The present paper
examines the analysis of a contaminated site, focusing the attention on the negative effects for receptors exposed to soil
and groundwater contamination caused by industrial activities. The case study investigated is a contaminated area lo-
cated in the industrial district of Trento North once occupied by the Italian Carbochimica plant. Pollution in that area
is mainly due to contamination of soil and groundwater with polycyclic aromatic hydrocarbons. The methodology ap-
plied is the risk evaluation for human health, in terms of individual cancer risk and hazard index. In particular the at-
tention has been focused on a specific migration way: if pollutants in the soil or in the groundwater undergo a phase
change, they spread and get to the soil surface, causing a dispersion of vapors in the atmosphere. In this case risk as-
sessment calls for the evaluation of volatilization factor. Among the different models dealing with the estimation of
volatilization factor, those mostly known and used in the national and international field of Human Health Risk As-
sessment were chosen: Jury’s and Farmer’s models. A sensitivity analysis of models was performed, in order to identify
the most significant parameters to estimate the volatilization factors among the wide range of input parameters for the
application of models. Performing an accurate selection and data processing of the contaminated site, models for the
volatilization factors calculation are applied, thus evaluating air concentrations and Human Health Risk. The analysis
of the resulting estimates is an excellent aid to draw interesting conclusions and to verify if the soil and groundwater
pollutants volatilization affects the human health considerably.
Keywords: Human Health Risk Assessment, Volatilization Models, Soil Contamination, Groundwater Contamination,
Cancer Risk, Hazard Index
1. Introduction
Pollution of different elements (air, water, soil and sub-
soil) resulting both from accidental events and from daily
industrial and civil activities, implies effects on the hu-
man health and on the environment. Through the appli-
cation of the Human Health Risk Assessment methodo-
logy in a specific contaminated site, it is possible to eva-
luate the magnitude and probability of negative effects
posed to human beings caused by exposure to contami-
nation in various media [1]. The consolidated procedure
concerning the risk analysis applies the RBCA approach
[2], which refers to a step method based on three levels
of assessment. In the following we refer to a tier 2 risk
assessment, involving site-specific data collection and
analytical modeling of the fate and transport of contami-
nants across the environmental media involved (in par-
ticular unsaturated soil, groundwater and outdoor air).
Receptors exposures typically are described as contact
between the chemicals of concern (COCs) and the body’s
exchange boundaries (skin, lung and gastrointestinal tract)
across which the chemicals can be absorbed [3]. Expo-
sure assessment also includes the identification and quan-
tification of the multiple pathways and multiple routes
that characterize the movement of a chemical from its
source to an exposed individual. Frequently, in a site-
specific human health risk analysis, among all the poten-
tial pathways (inhalation, ingestion and dermal exposure)
and migration routes, it is possible to identify a few ones
that have a predominant influence on the evaluation of

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1193
Human Health for a Real Contaminated Site
final individual cancer risk and hazard index for a recep-
tors group.
In the present paper the attention has been focused on
the pathway of volatilization of hazardous vapors coming
from contaminated soil and groundwater into open air
and consequent exposure of receptors to COCs. The aims
of this study are to: 1) identify the parameters that more
affect the estimate of the volatilization factors and their
uncertainty, 2) evaluate the importance of volatilization
of pollutants from soil and groundwater in the risk as-
sessment for human health through the application of the
models to a real contaminated site case-study.
In order to reach the first objective, a selection of sim-
ple and diffusely used models for the estimation of vola-
tilization factor in risk analysis was performed thus op-
erating a sensitivity analysis on input parameters for the
application of models; the second objective has been
approached through the investigation of a case-study
concerning a contaminated area located in northern Italy,
where contamination of soil and groundwater is mainly
due to polycyclic aromatic hydrocarbons deriving from
the productive cycles in remote industrial activities.
2. Vapors Migration modeling
2.1. Volatilization Factors
In the assessment of human health risk, the estimation of
transport factors is necessary, thus considering the mi-
gration of pollutants from the contamination source to
the targets. When the volatilization is regarded, the trans-
port factor is called volatilization factor (VF) and con-
siders the attenuation phenomena occurring during mi-
gration. VF represents the ratio between the pollutants
concentration in the exposure site (cpoe, expressed for
example in mg/m3) and the concentration at the contami-
nation source (cs expressed for example in mg/kg), as
resulting from soil samples or calculated applying mo-
dels:
p
oe s
cVFc

 (1)
Detailed models of contaminant transport in soil and
groundwater include processes such as diffusion, disper-
sion and convection phenomena for each of the phases
present in the soil. Obviously, such models include a
large number of contaminated site parameters and soil-
specific parameters that are often not available or not
very accurate. Therefore, in most volatilization pheno-
mena estimates, predictive models are simplified in order
to allow the application of models even in situations
where a few site specific parameters are available [4].
For every soil layer a different volatilization factor is
identified: VFss (volatilization of outdoor vapors from
surface soil), VFds (volatilization factor of outdoor vapors
from deep soil), VFgw (volatilization factor of outdoor
vapors from groundwater). These factors are used to es-
timate outdoor air concentration of volatiles by using the
known chemical concentration in the groundwater and
soil.
Among the volatilization models from subsurface sou-
rces into outdoor air available in literature, two models
were selected, widely applied in the Risk Assessment for
Human Health and Environment and suggested by EPA
[1,5,6], ISPRA [7] and ASTM standard [2,8].
In detail the volatilization models selected are:
- Jury’s model [9,10], assuming a contamination source
with semi-infinite dimensions and time-varying concen-
trations (estimation of VFss,J1 and VFss,J2 for surface soil
and VFds,J for deep soil),
- Farmer’s model [11], with steady-state assumption
(estimation of VFss,F for surface soil, VFds,F1, VFds,F2 for
deep soil and VFgw for groundwater).
These models make the following common assump-
tions when calculating volatilization factors: uniform and
isotropic soil (fissuring-porous soil is not considered);
the chemicals do not biodegrade in soil, in water solu-
tions or in vapor phase; no transport within water, no
absorption or production of the gases; the partitioning
between the chemicals in the groundwater/soil matrix
and vapors is linear; chemical losses by biodegradation
do not occur between the groundwater/soil and the sur-
face; for outdoor emissions, steady-state atmospheric dis-
persion of vapors occurs within the breathing zone.
The calculation of VF, hence the concentration of vo-
latiles outdoors, is based on the movement of volatiles
from the soil and groundwater up through the capillary
zone, through the unsaturated zone, and emission into the
breathing zone in outdoor air (Figure 1).
The models relationships are derived from simple one-
dimensional or integral mass balances, based on the dif-
Ground water
Contaminated
groundwater
Capillary zone
Deep soil
Surface soil
Vadose zone
Contaminated
sub-soil
Contaminated
surface-soil
Air Mixing Height
Wind direction
Figure 1. Conceptual model of vapors migration to outdoor
air.

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1194
Human Health for a Real Contaminated Site
ferent hypothesis of the considered volatilization models.
In particular VFss,J1 derives from Jury’s model, based
on the one-dimensional application of Fick’s laws con-
sidering the following assumptions and conditions: ab-
sence of boundary layer at the interface soil-air, thus
assuming a perfect mixing situation in air; no water flow
is considered through the soil (the pollutant’s loss due to
its transport into the groundwater is thus not considered
and lisciviation is therefore considered apart from vola-
tilization); the soil contaminated column of semi-infinite
depth has homogeneous physical characteristics; finally a
boundary condition considers that the soil concentration
at the ground level must be zero.
It’s worth noting that the condition of equilibrium par-
titioning is very rarely accomplished in the subsurface,
therefore calculated soil vapor values from soil-phase
data may clearly overestimate or underestimate actual
soil vapor concentration.
VFss,J2 and VFds,J are the upper limit of Jury’s model
and as a result are a conservative evaluation. Briefly,
they consider a mass balance in which the total value of
mass that can enter into the mixing volume (correspond-
ing to the total mass of pollutants in the surface soil) is
equal to the mass coming out of the mixing volume be-
cause of the aeolian transport during exposure time.
Therefore the applications of these relations do not take
into account the specific contaminant properties.
VFss,F, VFds,F1, VFds,F2, VFgw are obtained in Farmer’s
model. This model considers an initial uncontaminated
layer of soil (depth Ls) between the contamination source
top and the ground level. Vapors flux is calculated ap-
plying the Fick’s laws in steady-state conditions, so any
time reductions in source contamination due to the vola-
tilizing phenomena are not included. The equation VFss,F
is not considered since the outcome values of outdoor
volatilizing factors from surface soil result extremely
conservative for volatile compounds and not really con-
servative for the less volatile ones, when compared to the
results of the equation VFss,J1. Despite the fact that they
come from the same model, VFds,F1 is different from
VFds,F2, since they apply different hypothesis: the second
one considers the air flow from soil, while the first one
counts it as negligible. VFgw uses this last hypothesis, but
it is applied to the groundwater’s characteristics.
It’s worth noting that these models, though widely
used in risk assessment analysis, are based on simplify-
ing hypothesis that make them not always fitting the re-
ality of the case-studies. As an example, weaknesses and
critical aspects of the models are related to water soluble
compounds, contaminated source with non-homogenous
properties and time-variant volatilization quantities.
Equations of volatilization factors according to Jury
and Farmer are reported in the following (see Figure 2
for conceptual model used and Table 1 for parameters
included in the equations):
,1 3
2
π
s
ss J
air air
WDA kg
VF Um





(2)
,2 3
s
ss J
air air
Adkg
VF UL
m


 



(3)
,3
ss
ds J
air air
Wd kg
VF Um


 





(4)
,,
3
1
s
ss FAds F
air airs
kg
VFD AVF
ULL m





 
1
(5)
,2 3
sA
ds F
eff
s
air airs
Dkg
VF Lm
ULD
A









(6)
3
1
1
gw
air airGW
eff
ws
H
VF UL
m
DW





(7)
where the following parameters are included:
2
eff
As
wssa
H
m
DD kHs


 

(8)
3.333.33 2
22
eff aww
sa
ee
Dm
DD
H
s


 
 





(9)

12
cap
eff v
wscap veff eff
cap s
hhm
Dhh
s
DD



 





(10)
3.333.33 2
,,
22
a capwcap
eff w
cap a
ee
Dm
DD
H
s



 

(11)
In order to apply models for the volatilization factors
assessment a wide set of input parameters has to be con-
Wind direction
Groundwater
δair
Deep soil
Surface soil
LGW hv
hcap
Uair
A
LW
d
ds
LS
Figure 2. Representation of some geometrical parameters in
the scheme of conceptual model.
C opyright © 2011 SciRes. JEP

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for
Human Health for a Real Contaminated Site
1195
Table 1. List of parameters in volatilization factors models.
d Thickness of contamination source in the surface soil m
ds Thickness of contamination source in the deep soil m
hcap Height of capillary zone m
hv Height of unsaturated zone m
Ls Depth to subsurface soil contamination source m
LGW Depth to groundwater (= hcap + hv) m
L Extension of contamination source in across-wind direction m
W Width of contamination source area parallel to wind direction or groundwater flow direction m
A Contamination source area m2
ρs Soil bulk density kg/m3
θe Effective terrain porosity in unsaturated zone dimensionless
θw Volumetric water content dimensionless
θa Volumetric air content dimensionless
θw,cap Volumetric water content in the capillary zone dimensionless
θa,cap Volumetric air content in the capillary zone dimensionless
kS Soil-water sorption coefficient m3 H2O/kg soil
Dseff Effective diffusion coefficient in soil based on vapor-phase concentration m2/s
Dwseff Effective diffusion coefficient between the groundwater and soil surface m2/s
Dcapeff Effective diffusion coefficient through capillary zone m2/s
Da Diffusion coefficient of the substance in air m2/s
Dw Diffusion coefficient of the substance in water m2/s
H Henry’s Law constant dimensionless
δair Ambient air mixing zone height m
Uair Wind speed above the ground surface in the ambient mixing zone m/s
τ Average duration time of vapor flux s
sidered, characterizing geometry of contamination, the
contaminated soil’s and the above air’s characteristics,
and the physicochemical pollutants properties.
An analysis of the volatilization factors was carried
out in the open literature in order to establish the most
suitable transport factor for every environment section.
Both for the surface soil and the deep soil, the approach
proposed by standards ASTM 1739/95 [2], PS 104/98 [8]
and by Handbook Unichim 196/01 [12] was adopted.
Between the two evaluations VFss,J1 and VFss,J2, in par-
ticular the first equation is suggested for the less volatile
compounds while the second one is used for very volatile
compounds. The same choice is suggested also by the
software RBCA Tool Kit [13], BP-RISC [14] and GIU-
DITTA [15].
As regards the deep soil both the equation VFds,F1 and
the equation VFds,F2 gave nearly the same results. Fol-
lowing the approach suggested by Unichim Handbook
196/01 [12], the equations VFds,F2 and VFds,J were con-
sidered. In particular VFds,F2 was adopted for the less
volatile compounds while VFds,J for those very volatile. As
a matter of fact the values supplied by the equation VFds,F2
were too high and thus too conservative if applied to very
volatile compounds. This kind of approach is adopted by
software GIUDITTA [15] and RBCA Tool Kit [13].
It’s worth noting that the models analysis evidenced
that the incongruous situation may occur in which the VF
for surface soil value is lower than the VF value for deep
soil, but the reason of this lays obviously on the different
hypothesis at the basis of the two different model ty-
pologies.
Regarding saturated soil only a volatilizing factor VFgw
was considered. This equation is suggested by standards
ASTM 1739/95 [2], PS 104/98 [8], by Unichim Hand-
book 196/01 [12] and by all the software examined (BP-
RISC ver. 4.0, RBCA Toolkit ver. 1.2., GIUDITTA ver.
3.1 and ROME ver. 2.1).
2.2. Sensitivity Analysis of Volatilization Models
The sensitivity analysis is a common technique used in

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1196
Human Health for a Real Contaminated Site
the modeling issue to assess the effect of variability and
uncertainty of parameters on the results obtained from
the application of a specific mathematical model [16]. In
particular, in this section the aim is the sensitivity analy-
sis of the transport factors previously described, thus
identifying the variables that mostly affect these factors
and therefore the human health.
As explained in the previous section the selected vola-
tilization factors are: VFss,J1 and VFss,J2 for surface soil,
VFds,J and VFds,F2 for deep soil, VFgw for groundwater. In
the analysis, a typical volatile substance (benzene) and a
less volatile one (benzo(a)pyrene) are taken into account,
in order to consider both the expressions for surface soil
and deep soil. In particular VFss,J1 and VFds,F2 are applied
for benzo(a)pyrene, while VFss,J2 and VFds,J are applied
for benzene. VFgw is suitable for both compounds. A pre-
liminary analysis of which parameters are involved in the
various volatilization factors is specified in Table 2.
In the list, some parameters are not reported because
they are not independent, but are correlated as follows: A
and L (A/L = W); θa (θa = θe – θw); θacap (θacap = θe – θwcap);
hv (hv = LGW – hcap).
A brief remark has to be noted for the soil-water sorp-
tion coefficient ks: this parameter defines the substance
partitioning property between the solid phase (soil) and
the water phase. It is evaluated as the partition soil-water
coefficient (kd) that corresponds to (kOC·foc) for organic
compounds, where kOC is the carbon-water partition co-
efficient and foc represents the organic carbon fraction in
unsaturated soil. In this case, only foc is considered in the
variability analysis, whereas the carbon-water partition
coefficient is examined as a fixed parameter, as the other
specific compounds properties Da, Dw and H. Table 3
shows all the specific compound properties utilized in
the present sensitivity analysis (bold font) and in the case
study after described.
The application of the sensitivity analysis to the vola-
tilization factors attempts to provide a ranking of the mo-
del inputs based on their relative contributions to model
output variability and uncertainty. As sensitivity indica-
tors the Sensitivity Ratio (SR), also called elasticity and
the Sensitivity Score (SS) are taken into account [16].
The Sensitivity Ratio (SR) is the change in model out-
put per unit change in an input variable, as shown in the
following equation.
22
SR ref ref
ref ref
YYX X
YX









(12)
where Xref and Yref are the reference estimate for an input
variable and the corresponding value of the output vari-
able, while X2 and Y2 represent the value of the input
variable after changing and the corresponding value of
the output variable. The sensitivity ratio assumes diffe-
rent values if different reference values are taken into
account: for this reason estimation with minimum, maxi-
mum and mean values has been performed.
The Sensitivity Score (SS) is a variation of the sensi-
tivity ratio approach; it may provide more information,
but it requires additional information for the input vari-
ables.
This score is the SR weighted by a normalized meas-
ure of the variability in the input variable, as shown in
the following equation.



max min
SS SR
mean
XX
X

 (13)
where Xmax and Xmin are the maximum and minimum
values respectively, of an input variable, while Xmean is
the mean or reference value of an input variable.
The VF estimates are considered most sensitive to in-
put variables that yield the highest absolute value for SR
and SS.
In order to evaluate these preliminary sensitivity indi-
cators, the possible minimum, maximum and mean va-
lues assumed by the involved parameters have been ex-
amined and reported in Table 4. In particular the range
of values taken into consideration derives from an analy-
sis of all possible terrain typologies and environment
conditions and the less and most probable values as-
sumed by the parameters are the minimum and maxi-
mum values. For those parameters for which were not
possible the evaluation of a maximum value, the sensi-
tivity score has not been calculated.
The Sensitivity Ratio (SR, with a change of 10% in the
input parameters) and the Sensitivity Score (SS) near the
minimum value, mean value and maximum value has
been calculated for benzene and benzo(a)pyrene.
The evaluated SR and SS are utilized to rank the in-
volved parameter, according to ranking criteria derived
from national guidelines [7]. The sensitivity score is the
preferred indicator; for parameters without SS, the sensi-
tivity ratio is taken into account. Table 5 shows the level
of sensitivity of volatilization factor for each parameter,
considering an average situation among the sensitivity
ratio and score estimated near minimum, mean and maxi-
mum parameters values. Obviously for SR estimations
the same form of dependency of some parameters for di-
fferent volatilization factors, results in a similar behavior
of the sensitivity ranking.
It results that among the soil and groundwater para-
meters, volumetric water content (θw), volumetric water
content in the capillary zone (θw,cap) and organic carbon
fraction foc are relevant for the sensitivity of volatilize-
tion factors, besides those parameters easy predictable a
C opyright © 2011 SciRes. JEP

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for
Human Health for a Real Contaminated Site
1197
Table 2. Dependency of parameters in the volatilization factors.
Source and site
specific parameters Soil specific parameters Outdoor parameters Compound specific parameters
d ds L
s L gw W ρs h ca θeθw θw,ca foc δaiUair τ D Dw Hk d/koc
VFss,J1           
VFss,J2      
VFds,J      
VFds,F2
          
VFgw
        
Table 3. Compound-specific parameters [1].
Compound Da (cm2/s) Dw (cm2/s) H KOC (cm3/g) Carcinogenic/Toxic
properties Volatility
Acenaphthene 1 × 10–2 1 × 10–5 6.34 × 10–3 4.9 × 103 T +/-
Anthracene 1 × 10–2 1 × 10–5 2.6 × 10–3 2.35 × 104 T +/-
Benzene 8.8 × 10–2 9.8 × 10–6 2.28 × 10–1 62 C/T +
Benz(a)anthracene 5.1 × 10–2 9 × 10–6 1.37 × 10–4 3.58 × 105 C/T -
Benzo(a)pyrene 4.3 × 10–2 9 × 10–6 4.63 × 10–5 9.69 × 105 C/T -
Benzo(b)fluoranthene 2.3 × 10–2 5.56 × 10–6 4.55 × 10–3 1.23 × 106 C/T +/-
Benzo(g,h,i)perylene 4.9 × 10–2 5.65 × 10–5 3 × 10–5 1.6 × 106 T -
Benzo(k)fluoranthene 2.62 × 10–2 5.56 × 10–6 3.45 × 10–5 1.23 × 106 C/T -
Chrysene 2.48 × 10–2 6.21 × 10–6 3.88 × 10–3 3.98 × 105 C/T +/-
Dibenz(a,h)anthracene 2.02 × 10–2 5.18 × 10–6 6.03 × 10–7 1.79 × 106 C -
Ethylbenzene 7.5 × 10–2 7.8 × 10–6 3.23 × 10–1 204 T +
Fluoranthene 1 × 10–2 1 × 10–5 6.58 × 10–4 4.91 × 104 T -
Fluorene 1 × 10–2 1 × 10–5 2.6 × 10–3 7.71 × 103 T +/-
Indeno(1,2,3–c,d)pyrene 1.9 × 10–2 5.66 × 10–6 6.56 × 10–5 3.47 × 106 C/T -
Naphthalene 5.9 × 10–2 7.5 × 10–6 1.97 × 10–2 1.19 × 103 C/T +
Pyrene 2.72 × 10–2 7.2 × 10–6 4.51 × 10–4 6.8 × 104 T -
Toluene 8.7 × 10–2 8.6 × 10–6 2.72 × 10–1 140 T +
Xylenes 8.7 × 10–2 7.8 × 10–6 3.14 × 10–1 196 T +
Table 4. Range of values for parameters taken into account in the sensitivity analysis.
Minimum value Maximum value Mean/Default value Measure unit
d 0 1 0.5 m
ds 0 n.a. (LGW -1) 2 m
hcap 0.1 1.92 1 m
Ls 1 n.a. (LGW - ds) 2 m
LGW 1 n.a. 3 m
W 0 n.a. 30 m
ρs 1600 1750 1700 kg/m3
θe 0.28 0.426 0.353 dimensionless
θw 0.04 0.38 0.21 dimensionless
θw,cap 0.248 0.383 0.31 dimensionless
foc 0.001 0.03 0.01 dimensionless
δair 1 5 2 m
Uair 0.5 4 2.25 m/s
τ 15 40 30 (residential); 25 (industrial)years

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1198
Human Health for a Real Contaminated Site
Table 5. Sensitivity ranking of parameters for the volatilization from soil and groundwater of benzene and benzo(a)pyrene.
Volatilization factors as described in 2.1.
VFss,J1 VFss,J2 VFds,J VFds,F2 VFgw
Sost. B Sost. A Sost. A Sost. B Sost. A Sost. B
d M/H
ds H
hcap M/H M/L
Ls H
LGW L H
W H H H H H H
ρs L L L L
θe L M/L M M
θw H H M/L M
θw,cap
H L
foc M H
δair M/H M/H M/H M/H M/H M/H
Uair M M M M M M
τ L M/L M/L
Substance A: benzene; Substance B: benzo(a)pyrene;
SS sensitivity criteria:
0 < |SS| ≤ 0.5 Low (L); 0.5 < |SS| ≤1 Middle/Low (M/L); 1 < |SS| ≤ 1.5 Middle (M); 1.5 < |SS| ≤ 2 Middle/High (M/H); |SS|> 2 High (H)
SR sensitivity criteria:
0 < |SR| ≤ 0.33 Low (L); 0.33 <|SR| ≤0.66 Middle (M); |SR| > 0.66 High (H).
priori as the contamination source geometry (W, d, ds, Ls)
and the ambient air mixing zone heigth (δair).
As a final step of the sensitivity analysis, a Monte
Carlo Simulation has been performed, assuming a Gaus-
sian probability distribution for the variability of input
parameters to derive a probability distribution of out-
comes. This approach allows multiple input variables to
vary simultaneously in order to rank ordering the input
variables contribution to variability in the outcome esti-
mate. The graphs (Figure 3) extracted by the application
of the Crystal Ball software [17] show both the relative
magnitude and direction of influence (positive or nega-
tive) for each variable in the calculation of Volatilization
Factors (Contribution to Variance). The simulation was
performed with 100,000 trails and correlated assump-
tions have been applied. The Gaussian probability dis-
tributions of each input parameters are set up fitting
minimum, mean and maximum values or fitting values
for different soil typologies [18-21]. In particular in order
to build the Gaussian distribution, it has been assumed
the mean of the distribution as the mean/default values as
indentified before and the standard deviation as about
one third of the distance between the mean and the
minimum or the maximum value.
The software Crystal Ball calculates sensitivity by
computing Spearman’s rank correlation coefficients [22],
which measure the strength and direction of association
between input variables and output estimates while the
simulation is running. Correlation coefficients provide a
meaningful measure of the degree to which outputs and
inputs change together.
If an input and an output have a high correlation coef-
ficient, it means that the input has a significant impact on
the output; positive coefficients indicate that an increase
in the input is associated with an increase in the output
while negative coefficients imply the opposite situation.
The larger the absolute value of the correlation coeffi-
cient, the stronger the relationship. In addition, to help
interpret the rank correlations, Crystal Ball computes the
Contribution to Variance (as represented in the above
cited graphs) that designates what percentage of the vari-
ance in the target output is due to the specific input; it is
calculated by squaring the rank correlation coefficients
and normalizing them to 100%.
The analysis of contribution to variance in sensitivity
charts almost confirms the results obtained in the estima-
tion of the simplified analysis with SR and SS estimation:
in the case of less volatile compounds, the volumetric
water content (θw) has a predominant role among pa-
rameters in volatilization factors from soil and ground-
water, followed by foc in the volatilization from soil and
LGW in the volatilization from groundwater; in the case
C opyright © 2011 SciRes. JEP

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1199
Human Health for a Real Contaminated Site
Figure 3. Sensitivity charts for Volatilization Factors resulting from Monte Carlo Simulation (Contribution to Variance).
of very volatile compounds as benzene, thickness of
contamination source is the prevailing parameter in vola-
tilization from soil, while hcap in volatilization from
groundwater. In both cases the dimension of the conta-
mination source W has a medium weight in the contribu-
tion of variance differently from the high sensitivity
ranking evaluated by the SR and SS evaluation; other-
wise the wind velocity, which the SR and SS estimation
evaluated in all cases with a medium ranking, has in the
Monte Carlo analysis a medium contribute to variance
for volatilization of very volatile compounds and a lower
contribute for volatilization of less volatile compounds.
3. Case Study: “North Trento”
3.1. Site Description
A case study, regarding a contaminated area in Trentino
Alto Adige, is hereby analyzed. The area in exam is in
the self-governing province of Trento, in the abandoned
industrial area of north Trento, once occupied by the
“Carbochimica Italiana” plant (42,700 m2) which has
been the last owner of the site.
The plant activity was initially tar distillation for road
works and waterproofing and was then extended to the
production of naphthalene, oils for wood, pitch for elec-
trodes, phthalic anhydride and fumaric acid. In 1983,
after a declining of activity and the economic inability to
invest in process water depuration, the plant was closed.
In the middle of the 80s plants of Carbochimica Italiana
were demolished and the industrial site was dismissed.
The site is in the list of priority of the contaminated
sites of national interest.
In 2001 a barrier has been realized as environmental
contingency action for groundwater, in order to put a
hydraulic confine for the contamination dispersion. Since
September 2004 experimentations about reclamation on
demonstrative scale has begun, in order to test the results

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1200
Human Health for a Real Contaminated Site
,
of the chemical oxidation by means of ozone technology
[23].
The area is still characterized by soil and groundwater
pollution as a consequence of the productive activity that
took place in the area without a proper control of produc-
tive cycles. The site has been analyzed with a monitoring
campaign in which a large amount of data samples have
been produced: 219 surveys, 879 samples and 23,738
chemical analyses for about a hundred of chemical com-
pounds. Among these, eighteen substances have been
analyzed, extracting the ones with higher concentration,
worse toxicity properties and more extensive detection.
The list of site contamination substances is reported in
the Table 3, in which compound-specific parameters are
reported. For each analyzed substance carcinogenic and/
or toxic classification and volatility characteristics are
reported.
Most of the analyzed compounds exceed the limit
values of the contaminated sites established by national
regulation for soil and for some substances groundwater
limits, too.
3.2. Conceptual Model: Contaminated Site, Soil
and Groundwater Characterization
The stratigraphy of subsoil in the north Trento area is
characterized by a surface soil 1 meter depth of filling
terrain (SS in VF calculation), the beneath deep soil of
sandy loam texture and, at about 2.5 m (hv) from terrain
level, the saturated area. The piezometric oscillation of
groundwater level can be considered ± 1.5 m. The moni-
tored data samples have been set apart as contamination
in surface soil and in deep soil. The surface soil and the
deep soil have been considered conservatively as fully
contaminated (d = 1 m, ds = 1.5 m). Capillary height for
sandy loam texture is assumed as 0.25 m [24]. The con-
taminated area is schematized to a rectangle of dimen-
sions 140 m × 300 m (W parallel and L orthogonal to
wind direction). The groundwater direction is the same
as the wind one since both groundwater and wind direc-
tion follow the Adige Valley direction (from north-west
to south-east). Wind velocity Uair and direction are ob-
tained from the meteorological station of Trento-Ron-
cafort (194 m a.s.l.). A value of 1.37 m/s has been calcu-
lated as the mean wind velocity, measuring data of a re-
cent year with an anemometer localized at 10 m of height,
so for conservative approximation a mean value of about
1 m/s has been assumed at the ambient air mixing zone
height (2 m). Soil properties are assumed as those typical
of sandy loam texture. As suggested in the national gui-
delines [7], the mean duration time of vapor flux is posed
coinciding with the exposure duration of receptors. For
industrial/commercial areas the considered value is 25
years.
The contamination distribution mapping has been re-
alized arranging a georeferenced database with the con-
centration mean values of the different pollutants in the
surface soil and in the deep soil in 171 sampling points.
As regards the groundwater concentration values, a ho-
mogeneous mean distribution has been considered, tak-
ing into account a few available monitoring points in
proximity of the industrial area.
The analyzed site has been subdivided in a number of
cells with sides parallel and orthogonal to the wind di-
rection, which coincides with the groundwater flux di-
rection; the dimensions of the cells are W = 16 m parallel
and L = 15 m orthogonal to wind direction. An estima-
tion of surface soil, deep soil and groundwater contami-
nation has been possible for each identified cell of the
site, in this way allowing the calculation of the volatili-
zation factors in the entire area. Since the soil properties
are considered uniform in the analyzed contaminated site,
as described above, the calculation of the volatilization
factor results in a constant VF for each substance, evalu-
ated for each cell of the site.
3.3. Volatilization and Human Health Risk
Results
Volatilization factors for surface soil, deep soil and ground-
water have been calculated from the conceptual model
built up on the basis of the available information about
the contaminated site.
The concentration of each contaminant i in air cair,i is
conservatively calculated by summing the contribution
of the volatilization from surface soil, deep soil and
groundwater:
,,,,, ,air iss iss ids ids igw igwi
cVFcVFcVFc

 (14)
where css,i, cds,i and cgw,i are respectively the concen-
tration of the compound i in the surface soil, deep soil
and groundwater, while VFss,i, VFds,i, VFgw,i are the
corresponding volatilization factors.
Among the VF relations, as explained before, the sele-
ction is as follows: VFss,J1 for the less volatile com-
pounds and VFss,J2 for very volatile compounds about the
surface soil, VFds,F2 for the less volatile compounds and
VFds,J for those very volatile as regards the deep soil,
VFgw for groundwater. The application of Jury and Far-
mer’s models results in VFss that ranges from 1.06 × 10–8
kg/m3 (calculated for indeno(1,2,3-c,d)pyrene) to 1.73 ×
10–5 kg/m3 for very volatile compounds; VFds ranges from
5.10 × 10–12 kg/m3 (calculated for indeno(1,2,3-c,d)pyrene)
to the maximum value of 2.59 × 10–5 kg/m3 for very vo-
latile compounds; finally VFgw ranges from 5.77 × 10–8
l/m3 (calculated for dibenz(a,h)anthracene) to 3.97 × 10–5
C opyright © 2011 SciRes. JEP

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for
Human Health for a Real Contaminated Site
1201
l/m3 estimated for xylenes. The transfer factors for less
volatile compounds result several orders of magnitude
lower than those for very volatile ones, but the relative
concentrations in air obviously depend also by the conta-
mination levels in soil and groundwater.
As the distribution of pollutants in groundwater is con-
sidered uniform in the contaminated site, the term related
to the groundwater, i.e. concentration in air due to vola-
tilization from groundwater, is constant. The contribute
of the polluted groundwater to the total value of air con-
centration is null or limited (up to 3%) for a dozen of
substances, medium-level for acenapthene and pyrene
(up to 11%) and naphthalene (up to 41%), and high/
prevailing for those substances for which the cont-
mination of surface and deep soil is localized in only a
few monitoring points (benzene, benzo(k)fluoranthene,
ethylbenzene, toluene and xylenes). Using the poten-
tiality of the map calculation in Gis systems, the total
concentration in air is calculated and mapped for each of
the eighteen considered substances.
As an example in Figure 4 Benzo(a)pyrene concen-
tration (in µg/m3) distribution in air due to the contri-
bution of surface soil, deep soil and groundwater volati-
lization is represented, as calculated from the available
data in monitored points samples.
In order to calculate the human health risk caused by
the analyzed contaminated site, among all the possible
exposure scenarios, the ingestion, dermal contact and
outdoor inhalation scenarios are taken into account, as
schematized in the conceptual model in Figure 5. In
performing the human health risk analysis, the receptors
considered as potential targets of the contamination are
industrial workers localized on the dismissed area. This
choice was dictated by considerations about the actual
utilization of the site: since the dismissing of the plant,
the ex-industrial area was abandoned, but periodically
supervised and subjected to maintenance and numerous
monitoring campaigns.
In order to calculate the exposure intakes for the iden-
tified receptors, the standard procedures in human
health risk assessment have been utilized [5,16]. The
exposure intakes are expressed as mass of substance in
contact with the organism, normalized by time unit and
body weight (mg/(kg·d)); a summary of the relations
used in the procedure can be found in [25].
Human health risk assessment consists in the quanti-
fication of Individual Cancer Risk and Hazard Quotient
for the exposed population, i.e. the computation of the
upperbound excess lifetime cancer risk and noncarci-
nogenic hazards for each of the pathways and receptors
identified in the area of interest. Cancer risk is defined as
the probability that a receptor will develop cancer in his
lifetime, assuming a unique set of exposure, model, and
toxicity properties. In contrast, hazard is quantified as the
potential for developing noncarcinogenic health effects
as a result of exposure to COCs, averaged over an expo-
sure period. It is worth noting that hazard is not a proba-
bility but, more exactly, a measure of the magnitude of a
receptor’s potential exposure relative to a standard ex-
posure level.
The individual cancer risk of a receptor j set by ex-
posure to multiple carcinogenic chemicals i, can be cal-
Figure 4. Benzo(a)pyrene concentration (in µg/m3) distribution in air due to the contribution of surface soil, deep soil and
groundwater volatilization.

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1202
Human Health for a Real Contaminated Site
Figure 5. Conceptual model of the human health risk as-
sessment: exposure scenarios.
culated, for low doses exposition hypothesis, through the
following equation:
,
_
j
ij i
i
I
ndividual CancerRiskLADDCSF
 (15)
where:
LADDij is Lifetime Average Daily Dose for a lifetime
exposure of 70 years (mg/kg day) through multiple ex-
posure pathways
CSFi is the Cancer Slope Factor for COC i (mg/kg
day)–1. Comparing an exposure estimate to a Reference
Dose (RfD), the potential for noncarcinogenic health
effects resulting from exposure to a chemical is evalu-
ated. A RfD is defined as a daily intake rate that is esti-
mated to cause no appreciable risk of adverse health effe-
cts, even to sensitive populations, over a specific expo-
sure duration [5]. Generally, the more the Hazard Quo-
tient value exceeds 1, the greater is the level of concern.
Based on similar COCs toxicological characteristics and
additive health effects, the Hazard Quotient (HQ) for
receptor j exposed to multiple chemicals i, is calculated
as:
,ij
j
ii
A
DD
HQ RfD  [16]
where ADDij is the Average Daily Dose averaged for the
exposure duration relative to the toxic i for the receptor j
(mg/kg day) through multiple exposure pathways RfDi is
the COC i Reference Dose (mg/kg day) below which
there are no adverse effects. The parameter values adopted
for the estimation of the exposure intakes are those typi-
cally utilized for the human health risk assessment in the
case of workers receptors [26]. The estimation of the
exposure time and exposure frequency results from the
consideration that the area is dismissed since years and
that maintenance works are not requested every day. As
a reasonable hypothesis, it has been considered a total
number of 1500 hours of exposure for workers receptors.
Table 6 shows the carcinogenicity and toxicity values
of the considered substances utilized for the estimation
of Individual Cancer Risk and Hazard Quotient, ex-
tracted from U.S. EPA IRIS Database. Summing the con-
tribution of all the carcinogenic substances and all the
toxic substances, the distribution of total individual can-
cer risk and total hazard quotient, respectively, has been
estimated on the considered zone, as represented in Fi-
gure 6(a) and Figure 7(a). As expected, for receptors
located and directly exposed on contaminated site, total
individual cancer risk has quite high values, especially in
the north side of the area. The hazard quotient appro-
aches the value of 1 only in a very limited spot of the
area.
It’s worth noting that the calculated cancer risk and
hazard quotient values don’t take into account any pro-
tection of the receptors, thus resulting excessively con-
servative and unrealistic. It is evident that workers us-
ually use Personal Protective Equipment (PPE) conform-
ing to the regulations in force for safety subject during
maintenance and monitoring activities in contaminated
sites. The use of PPE as gloves and masks can be taken
into account in the estimation of risks by considering a
reduction factor. As regards the inhalation exposure, if a
mask giving protection from dust and gas with mean
assigned protection factor is considered, a reduction fac-
tor of 1/30 can be supposed (EN 133, EN 529 standards).
For dermal contact exposure wearing gloves (EN 374 -
2004 standard) and for ingestion exposure wearing a
safety mask, a reduction factor of 1/100 can be conser-
vatively hypothesized.
The results consequently obtained adopting the pro-
tection reduction factors are represented in Figure 6(b)
and Figure 7(b), where it is evident an average decrease
of risks of about 2 orders of magnitude.
In particular for total individual cancer risk, values
above the limit typically considered as threshold accept-
ability, 10–5, are almost disappeared, while for hazard
quotient, values are all reduced under 0.01 estimates.
The analysis of the contribution of pathways to both
cancer risk and hazard quotient put in evidence that total
cancer risk is mainly due to the dermal contribution This
assessment can be used as a significant criterion to select
the more appropriate PPE in order to reduce risks of
exposed workers. In this specific case the inhalation
pathway contribution due to volatilization of COCs from
soil and groundwater does not constitute the prevailing
concern of the contaminated site, but a particular regard
has to be posed to dermal contact and therefore to a good
choice of safety gloves during maintenance and moni-
toring activities on the polluted area.
Finally the analysis of the contribution of the con-
sidered substances shows that in the estimation of cancer
C opyright © 2011 SciRes. JEP

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1203
Human Health for a Real Contaminated Site
Table 6. Carcinogenicity and toxicity values for the considered substances.
inhalation ingestion dermal inhalation ingestion dermal
CSF
(mg/kg-d)–1
CSF
(mg/kg-d)–1
CSF
(mg/kg-d)–1
RfD
(mg/kg-d)
RfD
(mg/kg-d)
RfD
(mg/kg-d)
Acenaphtene n.a. n.a. n.a. 0 0.06 0.06
Anthracene n.a. n.a. n.a. 0 0.3 0.3
Benzene 0.0273 0.055 0.055 0.00855 0.004 0.004
Benz(a)anthracene 0.6 0.73 0.73 0.285 0 0
Benzo(a)pyrene 7.32 7.3 7.3 3.135 0 0
Benzo(b)fluoranthene 0.31 0.73 0.73 0.285 0 0
Benzo(g,h,i)perylene n.a. n.a. n.a. 0.03 0.03 0.03
Benzo(k)fluoranthene 0.031 0.073 0.073 0.0285 0 0
Chrysene 0.0031 0.007 0.007 0.03 0.03 0.03
Dibenz(a,h)anthracene 3.1 7.3 7.3 n.a. n.a. n.a.
Ethylbenzene n.a. n.a. n.a. 0.285 0.1 0.1
Fluoranthene n.a. n.a. n.a. 0 0.04 0.04
Indeno(1,2,3-c,d)pyrene 0.31 0.73 0.73 3.14 0.03 0.03
Naphthalene 0.00012 0 0 0.02 0.02 0.02
Pyrene n.a. n.a. n.a. 0.03 0.03 0.03
Toluene n.a. n.a. n.a. 1.43 0.08 0.08
Xylenes n.a. n.a. n.a. 0.2 0.2 0.2
Figure 6. Total Individual Cancer Risk for workers localized directly on the contaminated dismissed area, without PPE (a)
and with PPE (b).

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1204
Human Health for a Real Contaminated Site
Figure 7. Total Hazard Quotient for workers localized directly on the contaminated dismissed area, without PPE (a) and with
PPE (b).
risk benzo(a)pyrene is the main cause, while the hazard
quotient is mainly originated by naphthalene, followed
by pyrene and chrysene.
4. Conclusions
To quantify the negative effects to receptors exposed to
soil and groundwater contamination, human health risk
assessment methodology is usually applied, to evaluate
individual cancer risk and hazard index. The paper ex-
amined in particular the dispersion of contaminant va-
pors through volatilization from soil and groundwater in
the atmosphere. Volatilization factors have been esti-
mated applying Jury’s and Farmer’s models. The sensiti-
vity analysis of models, performed with the Sensitivity
Ratio, Sensitivity Score and Monte Carlo Simulation,
identified the most significant parameters: volumetric
water content, thickness of the contamination source and
height of capillary zone among the wide range of input
parameters for the application of models. Finally a case
study regarding a contaminated area located in the indus-
trial district of Trento North was investigated. A con-
ceptual model of the site was built up, processing the
available monitored data; the concentrations of several
contaminants in air were evaluated through the estima-
tion of volatilization factors. Individual Cancer Risk and
Hazard Quotient have been calculated for workers re-
ceptors localized on the contaminated site, analyzing the
inhalation, ingestion and dermal pathways. In the consi-
dered contaminated site, the volatilization of compounds
from contaminated soil and groundwater does not con-
stitute the main concern: the dermal contribution results
the prevailing pathway for risks and the obtained results
can advise the appropriate use of PPE that enable the
considerable decrease of the risks for the exposed recep-
tors. Adopting conservative reductive factors accounting
for the protection of PPE, the resulting individual cancer
risks and hazard quotients are clearly below the accept-
ability limits.
5. Acknowledgements
We would like to acknowledge the autonomous province
of Trento for the support during this study and for pro-
viding the monitoring data relative to the contaminated
site of Trento North.
REFERENCES
[1] U.S. EPA, “Soil Screening Guidance: Technical Back-
ground Document and User’s Guide,” Office of Solid
Waste and Emergency Response, Washington D.C.,
EPA/540/R-95/128, 1996.
[2] ASTM, “American Society for Testing and Materials
Standard Guide for Risk-Based Corrective Action Ap-
plied at Petroleum Release Sites, E1739-95,” West Con-
shohocken, PA, 1995.
[3] U.S. EPA, “Guidelines for Exposure Assessment,” Fed-
eral Register, Vol. 57, No. 104, 1992, pp. 22888-22938.
C opyright © 2011 SciRes. JEP

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1205
Human Health for a Real Contaminated Site
[4] J. Grifoll and Y. Cohen, “Chemical Volatilization from
the Soil Matrix: Transport through the Air and Water
Phases,” Journal of Hazardous Materials, Vol. 37, No. 3,
1994, pp. 445-457. doi:10.1016/0304-3894(93)E0100-G
[5] U.S. EPA, “Risk Assessment Guidance for Superfund,
Volume I: Human Health Evaluation Manual. Interim
Final,” Office of Emergency and Remedial Response,
Washington D.C., OSWER Directive 9285.7-0/a, 1989.
[6] U.S. EPA, “Soil Screening Guidance: Technical Back-
ground Document,” 1994.
[7] APAT, “Criteri Metodologici per l’Applicazione Dell’
Analisi Assoluta di Rischio ai Siti Contaminati. rev.2,”
Roma, 2008 (in Italian).
[8] ASTM, “American Society for Testing and Materials
Standard Provisional Guide for Risk-Based Corrective
Action,” Report PS104-98, 1998.
[9] W. A. Jury, W. F. Spencer and W. J. Farmer, “Behaviour
Assessment Model for Trace Organics in Soil: I. Model
Description,” Journal of Environmental Quality, Vol. 12,
No. 4, 1983, pp. 558-564.
doi:10.2134/jeq1983.00472425001200040025x
[10] W. A. Jury, D. Russo, G. Streile and H. E. Abd, “Evalua-
tion of Volatilization by Organic Chemicals Residing be-
low the Soil Surface,” Water Resources Research, Vol.
26, No. 1, 1990, pp. 13-20.
doi:10.1029/WR026i001p00013
[11] W. J. Farmer, M. S. Yang, J. Letey and W. F. Spencer,
“Hexachlorobenzene: Its Vapor Pressure and Vapor
Phase Diffusion in Soil,” Proceedings of Soil Science So-
ciety of America, Vol. 44, 1980, pp. 676-680.
doi:10.2136/sssaj1980.03615995004400040002x
[12] Unichim, “Manuale n.196/01 Suoli e Falde Contaminati,
Analisi di Rischio Sito-Specifica, Criteri e Parametri,”
2002 (in Italian).
[13] RBCA Tool Kit 1.2, “RBCA Tool Kit for Chemical Re-
leases,” Groundwater Services Inc., Texas, 1999.
[14] RISC 4.0, “Risk-Integrated Software for Clean-up –
User’s manual,” BP-Amoco Oil, Sunbury UK, 2001.
[15] GIUDITTA 3.1, “Manuale d’uso/Allegati,” Provincia di
Milano-URS Dames and Moore, 2006 (in Italian).
[16] U.S. EPA, “Risk Assessment Guidance for Superfund:
Volume III—Part A, Process for Conducting Probabilistic
Risk Assessment,” OSWER 9285, EPA 540-R-02-002,
2001, pp. 7-45.
[17] Decisioneering, Inc., “Crystal Ball ® User Manual,” 2005
[18] R. F. Carsel and R. S. Parrish, “Developing Joint Prob-
ability Distributions of Soil Water Retention Characteris-
tics,” Water Resources Research, Vol. 24, No. 5, 1988,
pp. 755-769. doi:10.1029/WR024i005p00755
[19] J. A. Connor, C. J. Newell and M. W. Malander, “Pa-
rameter Estimation Guidelines for Risk-Based Corrective
Action (RBCA) Modeling,” NGWA Petroleum Hydro-
carbons Conference, Houston, November 1996.
[20] M. Th. Van Genuchten and P. J. Wierenga, “Mass Trans-
fer Studies in Sorbing Porous Media: I. Analytical Solu-
tion,” Soil Science Society of America Journal, Vol. 40,
No. 4, 1976, pp. 473-480.
doi:10.2136/sssaj1976.03615995004000040011x
[21] M. Th. Van Genuchten, “A Closed-Form Equation for
Predicting the Hydraulic Conductivity of Unsaturated
Soils,” Soil Science Society of America Journal, Vol. 44,
No. 5, 1980, pp. 892-898.
doi:10.2136/sssaj1980.03615995004400050002x
[22] E. L. Lehmann, “Nonparametrics: Statistical Methods
Based on Ranks,” New York, Springer, 2006.
[23] G. Andreottola and C. Simonini, “Test di Ozonizzazione
in situ di Terreni Contaminati da IPA. Risultati
Preliminary,” Proceedings of Conference in “Nuovi
Indirizzi Nella Bonifica dei siti Contaminati - La Prassi,
la Normativa, le Nuove Tecnologie,” Provincia di Milano,
2004 (in Italian).
[24] C. W. Fetter, “Applied Hydrogeology,” 3rd Edition,
Prentice Hall, Engelwood Cliffs, 1994.
[25] P. Morra, S. Bagli and G. Spadoni, “The Analysis of
Human Health Risk with a Detailed Procedure Operating
in a Gis Environment,” Environment International, Vol.
32, No. 4, 2006, pp. 444-454.
doi:10.1016/j.envint.2005.10.003
[26] U.S. EPA, “Exposure Factors Handbook,” National Cen-
ter for Environmental Assessment, Washington D.C.,
EPA/600/R-09/052A, 2009

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for 1206
Human Health for a Real Contaminated Site
Notation
δair ambient air mixing zone height
ρs soil bulk density
θa volumetric air content
θa,cap volumetric air content in the capillary zone
θe effective terrain porosity in unsaturated zone
θw volumetric water content
θw,cap volumetric water content in the capillary zone
τ average duration time of vapor flux
A contamination source area
ADD Average Daily Dose averaged for the exposure duration
cpoe pollutant concentration in point of exposure
cs pollutant concentration at the contamination source
COC Chemical of Concern
CSF Cancer Slope Factor
d thickness of contamination source in the surface soil
ds thickness of contamination source in the deep soil
DA diffusivity
Da diffusion coefficient of the substance in air
Dcapeff effective diffusion coefficient through capillary zone
Dw diffusion coefficient of the substance in water
Dseff effective diffusion coefficient in soil based on vapor-phase
concentration
Dwseff effective diffusion coefficient between the groundwater
and soil surface
foc organic carbon fraction
H Henry’s law constant
hcap height of capillary zone
hv height of unsaturated zone
kd partition soil-water coefficient
kOC carbon-water partition coefficient
ks soil-water sorption coefficient
L extension of contamination source in across-wind direction
LGW depth to groundwater
Ls depth to subsurface soil contamination source
LADD Lifetime Average Daily Dose for a lifetime exposure of
70 years
RfD Reference Dose
Uair wind speed above the ground surface in the ambient mix-
ing zone
VFss volatilization factor of outdoor vapors from surface soil
VFds volatilization factor of outdoor vapors from deep soil
VFgw volatilization factor of outdoor vapors from groundwater
W width of contamination source area parallel to wind or
groundwater flow direction
C opyright © 2011 SciRes. JEP