Canfield, 2008). Full-scale IQ was also significantly associated with
blood Pb at age seven and a half in a subset analysis (n=200) in the
Detroit inner-city study for which the population mean blood Pb level
was 4.1 [mu]g/dL, as well as the other subgroup with higher blood Pb
levels (mean=4.6 [mu]g/dL, n=224) and in the full study group (mean=5.4
[mu]g/dL, n=246); additionally, performance IQ was significantly
associated with blood Pb in those analyses as well as in the subset
analysis (n=120) for which the population mean blood Pb level was 3
[mu]g/dL (although full-scale IQ was not significantly associated with
blood Pb in this lowest blood Pb subgroup) (Chiodo et al., 2004,
Chiodo, 2008). Vocabulary, one of ten subtests of the full-scale IQ,
was significantly associated with blood

Pb at age six in the German three-city study (n=384) in which the mean
blood Pb level was 4.2 [mu]g/dL (Walkowiak et al., 1998). In a Mexico
City cohort of infants age two, the mental development index (MDI) and
psychomotor development index (PDI) were significantly associated with
blood Pb in the full study group (mean=4.28 [mu]g/dL, n=294); further,
the MDI (but not the PDI) was significantly associated with blood Pb in
the subset analysis (n=193) for which the population mean blood Pb
level was 2.9 [mu]g/dL, and PDI (but not the MDI) was significantly
associated with blood Pb in the subset analysis (n=101) for which the
population mean blood Pb was 6.9 [mu]g/dL (Tellez-Rojo et al., 2006;
Tellez-Rojo, 2008). Scores on academic achievement tests for reading
and math were significantly associated with blood Pb at age six through
sixteen in a subgroup analysis (n=4043) of the NHANES III data for
which the population mean blood Pb level was 1.7 [mu]g/dL, as discussed
below (Lanphear et al. 2000; Auinger, 2008).
---------------------------------------------------------------------------

    \45\ The NHANES III survey was conducted in 1988-1994.
    \46\ Some studies also employed exclusion criteria which limited
variation in socioeconomic status across the study population.
Further, with regard to adjustment for potential confounders in the
large pooled international analysis (Lanphear et al. 2005),
discussed below, the authors adjusted for HOME score, birth weight,
maternal IQ and maternal education. Canfield et al. (2003) adjusted
for maternal IQ, maternal education, HOME score, birth weight, race,
tobacco use during pregnancy, household income, gender, and iron
status. Bellinger and Needleman (2003) adjusted for maternal IQ,
HOME score, SES, child stress, maternal age, race, gender, birth
order, marital status. Chiodo et al. (2004) adjusted for primary
care-giver education and vocabulary, HOME score, family environment
scale, SES, gender, number of children under 18, birth order.
Tellez-Rojo et al. (2006) adjusted for maternal IQ, birth weight and
gender; the authors also state that other potentially confounding
variables that were not found to be significant at p<.10 were not
adjusted for. Walkoviak et al. (1998) adjusted for parental
education, breastfeeding, nationality and gender. In Lanphear et al.
(2000), the authors adjusted for race/ethnicity and poverty index
ratio, as surrogates for HOME score/SES status, and adjusted for the
parental education level as a surrogate for maternal IQ; they also
adjusted for gender, serum ferritin level and serum cotinine level.
    \47\ The Criteria Document notes that a ``major challenge to
observational studies examining the impact of Pb on parameters of
child development has been the assessment and control for
confounding factors'' (CD, p. 6-73). However, the Criteria Document
further recognizes that ``[m]ost of the important confounding
factors in Pb studies have been identified, and efforts have been
made to control them in studies conducted since the 1990
Supplement'' (CD, p. 6-75). On this subject, the Criteria Document
further concludes the following: ``Invocation of the poorly measured
confounder as an explanation for positive findings is not
substantiated in the database as a whole when evaluating the impact
of Pb on the health of U.S. children (Needleman, 1995). Of course,
it is often the case that following adjustment for factors such as
social class, parental neurocognitive function, and child rearing
environment using covariates such as parental education, income, and
occupation, parental IQ, and HOME scores, the Pb coefficients are
substantially reduced in size and statistical significance (Dietrich
et al., 1991). This has sometimes led investigators to be quite
cautious in interpreting their study results as being positive
(Wasserman et al., 1997). This is a reasonable way of appraising any
single study, and such extreme caution would certainly be warranted
if forced to rely on a single study to confirm the Pb effects
hypothesis. Fortunately, there exists a large database of high
quality studies on which to base inferences regarding the
relationship between Pb exposure and neurodevelopment. In addition,
Pb has been extensively studied in animal models at doses that
closely approximate the human situation. Experimental animal studies
are not compromised by the possibility of confounding by such
factors as social class and correlated environmental factors. The
enormous experimental animal literature that proves that Pb at low
levels causes neurobehavioral deficits and provides insights into
mechanisms must be considered when drawing causal inferences
(Bellinger, 2004; Davis et al., 1990; U.S. Environmental Protection
Agency, 1986a, 1990).'' (CD, p. 6-75)
    \48\ The tests for cognitive function in these studies include
age-appropriate Wechsler intelligence tests (Lanphear et al., 2005),
the Stanford-Binet intelligence test (Canfield et al., 2003a), and
the Bayley Scales of Infant Development (Tellez-Rojo et al., 2006).
In some cases, individual subtests of the Wechsler intelligence
tests (Lanphear et al., 2000; Walkowiak et al., 1998), and
individual subtests of the Wide Range Achievement Test (Lanphear et
al., 2000) were used. The Wechsler and Stanford-Binet tests are
widely used to assess neurocognitive function in children and
adults, however, these tests are not appropriate for children under
age three. For such children, studies generally use the age-
appropriate Bayley Scales of Infant Development as a measure of
cognitive development. See footnote 63 for further information.
---------------------------------------------------------------------------

    The study by Lanphear et al. (2000) is a large cross-sectional
study using NHANES III dataset, with 4853 subjects in the full study
and more than 4000 in the subgroup analyses, that reports statistically
significant \49\ associations of concurrent blood Pb levels \50\ with
neurocognitive decrements in the full study population and in subgroup
analyses down to and including the subgroup with individual blood Pb
levels below 5 [mu]g/dL (CD, pp. 6-31 to 6-32; Lanphear et al., 2000).
Specifically the study by Lanphear et al. (2000) reported a
statistically significant association between math (p<0.001), reading
(p<0.001), block design (p=0.009), and digit span (p=0.04) scores and
blood Pb levels in the analysis that included all study subjects.
Additionally, the study reports statistically significant associations
for block design and digit span scores down to and including the
subgroup with individual blood Pb levels below 7.5 [mu]g/dL and 10
[mu]g/dL, respectively.\51\ Further, statistically significant
associations were observed for reading and math scores down to and
including the subgroup with individual blood Pb levels below 5 [mu]g/
dL, which included 4043 of the 4853 children.\52\ A similar pattern in
the magnitude of the effect estimates was observed across all the
subgroup analyses and for all four tests, including the subgroup with
individual blood Pb levels less than 2.5 [mu]g/dL, although not all the
effect estimates were statistically significant (Lanphear et al.,
2000).\53\ In particular, the lack of statistical significance in the
subset of individuals with blood Pb levels less than 2.5 [mu]g/dL may
be attributable to the smaller sample size (2467 children) and reduced
variability of blood Pb levels.\54\ Blood Pb levels in the full study
population ranged from below detection to above 10 [mu]g/dL, with a
population geometric mean of 1.9 [mu]g/dL, and the subgroups were
composed of children with blood Pb levels less than 10 [mu]g/dL
(geometric mean of 1.8 [mu]g/dL), less than 7.5 [mu]g/dL (geometric
mean of 1.8 [mu]g/dL), less than 5 [mu]g/dL (geometric mean of 1.7
[mu]g/dL), and less than 2.5 [mu]g/dL (geometric mean of 1.2 [mu]g/dL),
respectively (Lanphear et al., 2000; Auinger, 2008).\55\
---------------------------------------------------------------------------

    \49\ The statistical significance refers to the effect estimate
of the linear relationship across the range of data, as presented in
Table 4 of Lanphear et al. (2000).
    \50\ A limitation noted for this study is with regard to the use
of concurrent blood Pb levels in children of this age. The authors
state that ``it is not clear whether the cognitive and academic
deficits observed in the present analysis are due to lead exposure
that occurred during early childhood or due to concurrent
exposure'', however, they further note that ``concurrent blood lead
concentration was the best predictor of adverse neurobehavioral
effects of lead exposure in all but one of the published prospective
studies''. The average blood Pb level for 1-5 year olds was
approximately 15 [mu]g/dL in the 1976-1980 NHANES. When in that age
range, some of the children included in the NHANES III dataset may
have had blood Pb levels comparable to those of the earlier NHANES.
The general issue regarding blood Pb metrics is further discussed in
subsequent text.
    \51\ The associations with block design score were not
statistically significant for subgroups limited to blood Pb of <5
and <2.5 [mu]g/dL. The associations with digit span score were not
statistically significant for the blood Pb subgroups of <7.5 and
lower.
    \52\ The associations with math and reading scores were not
statistically significant for the subgroup limited to blood Pb <2.5
[mu]/dL.
    \53\ For example, for reading scores, effect estimates were -
0.99, -1.44, -1.53, -1.66, and -1.71 points per [mu]g/dL for all
children, the subgroup with blood Pb <10 [mu]g/dL, the subgroup with
blood Pb <7.5, the subgroup with blood Pb <5 and the subgroup with
blood Pb<2.5, respectively (Lanphear et al., 2000, Table 4).
    \54\ The authors state ``Indeed, while the average effects of
lead exposure on reading scores were not significant for blood lead
concentrations less that 2.5 [mu]g/dL, the size of the effect and
the borderline significance level ([beta] = -1.71, p=0.07) suggests
that the smaller sample size and the imprecision of the relationship
of blood Pb concentration with performance on the reading subtest--
as indicated by the large standard error--may be the reason we did
not find a statistically significant association for children in
that range.''
    \55\ We note that the datasets for each subgroup include
children for the lower blood Pb subgroups (in Table 4 of Lanphear et
al., 2000). For example, the dataset of children with blood Pb
levels <2.5 is a component of the dataset of children with blood Pb
levels <5 (Lanphear et al., 2000).
---------------------------------------------------------------------------

    The epidemiological studies that have investigated blood Pb effects
on IQ (as discussed in the CD, Section 6.2.3) have considered a variety
of specific blood Pb metrics, including: (1) Blood concentration
``concurrent'' with the response assessment (e.g., at the time of IQ
testing), (2) average blood concentration over the ``lifetime'' of the
child at the time of response assessment (e.g., average of measurements
taken over child's first 6 or 7 years), (3) peak blood concentration
during a particular age range, and (4) early childhood blood
concentration (e.g., the mean of measurements between 6 and 24 months
age). With regard to the latter two, the Criteria Document (e.g., CD,
chapters 3 and 6) has noted that age has been observed to strongly
predict the period of peak exposure (around 18-27 months when there is
maximum hand-to-mouth activity). The CD further notes, this maximum
exposure period coincides with a period of time in which major events
are occurring in central nervous system (CNS) development (CD, p. 6-
60). Accordingly, the belief that the first few years of life are a
critical window of vulnerability is evident particularly in the earlier
literature (CD, p. 6-60). However, more recent analyses have found even
stronger associations between blood Pb at school age and IQ at school
age (i.e., concurrent blood Pb), indicating the important role that is
continued to be played by Pb exposures later in life. In fact,
concurrent and lifetime averaged measurements were stronger predictors
of adverse neurobehavioral effects (better than the peak or 24 month
metrics) in all but one of the prospective cohort studies (CD, pp. 6-61
to 6-62). While all four specific blood Pb metrics were correlated with
IQ in the international pooled analysis by Lanphear and others (2005),
the concurrent blood Pb level exhibited the strongest relationship with
intellectual deficits (CD, p. 6-29).
    The Criteria Document presentation on toxicological evidence also
recognizes neurological effects elicited by exposures subsequent to
earliest childhood (CD, sections 5.3.5 and 5.3.7). For example,
research with monkeys has indicated that while exposure only during
infancy may elicit a response, exposures (with similar blood Pb levels)
that only occurred post-infancy also elicit responses. Further, in the
monkey research, exposures limited to post-infancy resulted in a
greater response than exposures limited to infancy (Rice and Gilbert,
1990; Rice, 1992).
    A study by Chen and others (2005) involving 622 children has
attempted to directly address the question regarding periods of
enhanced susceptibility to Pb effects (CD, pp. 6-62 to 6-64).\56\ The
authors found that the concurrent blood

Pb association with IQ was always stronger than that for 24-month blood
Pb. As children aged, the relationship with concurrent blood Pb grew
stronger while that with 24-month blood Pb grew weaker. Further, in
models including both prior blood Pb (at 24-months age) and concurrent
blood Pb (at 7-years age), concurrent blood Pb was always more
predictive of IQ. In fact, concurrent blood Pb explained most of Pb-
related variation in IQ such that prior blood Pb (at 24-months age) was
rendered nonsignificant and nearly null.\57\ The effect estimate for
concurrent blood Pb was robust and remained significant, little changed
from its value without adjustment for 24-month blood Pb level. The
Criteria Document concluded the following regarding the results of this
study (CD, pp. 6-63 to 6-64).
---------------------------------------------------------------------------

    \56\ In the children in this study, the mean blood Pb
concentration was 26.2 [mu]g/dL at age 2, 12.0 [mu]g/dL at age 5 and
8.0 [mu]g/dL at age 7 (Chen et al. 2005).
    \57\ We note that blood Pb levels at any point in time are
influenced by current as well as past exposures, e.g., through
exchanges between blood and bone (as summarized in section II.B.1
above and discussed in more detail in the Criteria Document).

    These results support the idea that Pb exposure continues to be
toxic to children as they reach school age, and do not lend support
to the interpretation that all the damage is done by the time the
child reaches 2 to 3 years of age. These findings also imply that
cross-sectional associations seen in children, such as the study
recently conducted by Lanphear et al. (2000) using data from NHANES
III, should not be dismissed. Chen et al. (2005) concluded that if
concurrent blood Pb remains important until school age for optimum
cognitive development, and if 6- and 7-year-olds are as or more
sensitive to Pb effects than 2-year-olds, then the difficulties in
preventing Pb exposure are magnified but the potential benefits of
---------------------------------------------------------------------------
prevention are greater.

    In addition to findings of association with neurocognitive
decrement (including IQ) at study group mean blood Pb levels well below
10 [mu]g/dL, the evidence indicates that the slope for Pb effects on IQ
is steeper at lower blood Pb levels (CD, section 6.2.13). As stated in
the CD, ``the most compelling evidence for effects at blood Pb levels
<10 [mu]g/dL, as well as a nonlinear relationship between blood Pb
levels and IQ, comes from the international pooled analysis of seven
prospective cohort studies (n=1,333) by Lanphear et al. (2005)'' (CD,
pp. 6-67 and 8-37 and section <IP_ADDRESS>.11).\58\ Using the full pooled
dataset with concurrent blood Pb level as the exposure metric and IQ as
the response from the pooled dataset of seven international studies,
Lanphear and others (2005) employed mathematical models of various
forms, including linear, cubic spline, log-linear, and piece-wise
linear, in their investigation of the blood Pb concentration-response
relationship (CD, p. 6-29; Lanphear et al., 2005). They observed that
the shape of the concentration-response relationship is nonlinear and
the log-linear model provides a better fit over the full range of blood
Pb measurements \59\ than a linear one (CD, p. 6-29 and pp. 6-67 to 6-
70; Lanphear et al., 2005). In addition, they found that no individual
study among the seven was responsible for the estimated nonlinear
relationship between Pb and deficits in IQ (CD p. 6-30). Others have
also analyzed the same dataset and similarly concluded that, across the
range of the dataset's blood Pb levels, a log-linear relationship was a
significantly better fit than the linear relationship (p=0.009) with
little evidence of residual confounding from included model variables
(CD, Section 6.2.13; Rothenberg and Rothenberg, 2005).
---------------------------------------------------------------------------

    \58\ We note that a public comment submitted on March 19, 2008
on behalf of the Association of Battery Recyclers described concerns
the commenter had with the conclusion by Lanphear et al. (2005) of a
nonlinear relationship of blood Pb with IQ, citing a publication by
Surkan et al. (2007), a study published since the completion of the
Criteria Document, and the Tellez-Rojo et al. (2006) finding,
discussed in the Criteria Document, of two different slopes for
their study subgroups of young children with blood Pb levels below 5
[mu]g/d (n=193, for which the slope of -1.7 was statistically
significant, p=0.01) and those with blood Pb levels between 5 and 10
[mu]g/dL (n=101, for which the slope of -0.94 was not statistically
significant, p=0.12). The commenter also cites another publication
published since the completion of the Criteria Document, Jusko et
al. (2007) related to this issue. EPA notes that it is not basing
its proposed decisions on studies that are not included in the
Criteria Document.
    \59\ The geometric mean of the concurrent blood Pb levels
modeled was 9.7 [mu]g/dL; the 5th and 95th percentile values were
2.5 and 33.2 [mu]g/dL, respectively (Lanphear et al., 2005).
---------------------------------------------------------------------------

    The impact of the nonlinear slope is illustrated by the log-linear
model-based estimates of IQ decrements for similar changes in blood Pb
level at different absolute values of blood Pb level (Lanphear et al.,
2005). These estimates of IQ decrement are 3.9 (with 95% confidence
interval, CI, of 2.4-5.3), 1.9 (95% CI, 1.2-2.6) and 1.1 IQ points per
[mu]g/dL blood Pb (95% CI, 0.7-1.5), for increases in concurrent blood
Pb from 2.4 to 10 [mu]g/dL, 10 to 20 [mu]g/dL, and 20 to 30 [mu]g/dL,
respectively (Lanphear et al., 2005). For an increase in concurrent
blood Pb levels from <1 to 10 [mu]g/dL, the log-linear model estimates
a decline of 6.2 points in full scale IQ which is comparable to the 7.4
point decrement in IQ for an increase in lifetime mean blood Pb levels
up to 10 [mu]g/dL observed in the Rochester study (CD, pp. 6-30 to 6-
31).
    A nonlinear blood Pb concentration-response relationship is also
suggested by several other analyses that have observed that each [mu]g/
dL increase in blood Pb may have a greater effect on IQ at lower blood
Pb levels (e.g., below 10 [mu]g/dL) than at higher levels (CD, pp. 8-63
to 8-64; Figure 8-7). As noted in the Criteria Document, while this may
at first seem at odds with certain fundamental toxicological concepts,
a number of examples of non- or supralinear dose-response relationships
exist in toxicology (CD, pp. 6-76 and 8-38 to 8-39). With regard to the
effects of Pb on neurodevelopmental outcome such as IQ, the CD suggests
that initial neurodevelopmental effects at lower Pb levels may be
disrupting very different biological mechanisms (e.g., early
developmental processes in the central nervous system) than more severe
effects of high exposures that result in symptomatic Pb poisoning and
frank mental retardation (CD, p. 6-76).
    The Criteria Document describes this issue with regard to Pb as
follows (CD, p. 8-39).

    In the case of Pb, this nonlinear dose-effect relationship
occurs in the pattern of glutamate release (Section 5.3.2), in the
capacity for long term potentiation (LTP; Section 5.3.3), and in
conditioned operant responses (Section 5.3.5). The 1986 Lead AQCD
also reported U-shaped dose-effect relationships for maze
performance, discrimination learning, auditory evoked potential, and
locomotor activity. Davis and Svendsgaard (1990) reviewed U-shaped
dose-response curves and their implications for Pb risk assessment.
An important implication is the uncertainty created in
identification of thresholds and ``no-observed-effect-levels''
(NOELS). As a nonlinear relationship is observed between IQ and low
blood Pb levels in humans, as well as in new toxicologic studies
wherein neurotransmitter release and LTP show this same
relationship, it is plausible that these nonlinear cognitive
outcomes may be due, in part, to nonlinear mechanisms underlying
these observed Pb neurotoxic effects.

    More specifically, various findings within the toxicological
evidence presented in the Criteria Document provides biologic
plausibility for a steeper IQ loss at low blood levels, with a
potential explanation being that the predominant mechanism at very low
blood-Pb levels is rapidly saturated and that a different, less-
rapidly-saturated process, becomes predominant at blood-Pb levels
greater than 10 [mu]g/dL.\60\
---------------------------------------------------------------------------

    \60\ The toxicological evidence presented in the Criteria
Document of biphasic dose-effect relationships includes: Suppression
of stimulated hippocampal glutamate release at low exposure levels
and induction of glutamate exocytosis at higher exposure levels (CD,
Section 5.3.2); downregulation of NMDA receptors at low blood Pb
levels and upregulation at higher levels (CD, section 5.3.2); Pb
causes elevated induction threshold and diminished magnitude of
long-term potentiation at low exposures, but not at higher exposures
(CD, section 5.3.3); and low-level Pb exposures increase fixed-
interval response rates and high-level Pb exposures decrease fixed
interval response rates in learning deficit testing in rats (CD,
section 5.3.5). Additional in vitro evidence includes Pb stimulation
of PKC activity at picomolar concentrations and inhibition of PKC
activity at nano- and micro-molar concentrations (CD, section
5.3.2).

---------------------------------------------------------------------------

    In addition to the observed associations between neurocognitive
decrement (including IQ) and blood Pb at study group mean levels well
below 10 [mu]g/dL (described above), the current evidence includes
multiple studies that have examined the quantitative relationship
between IQ and blood Pb level in analyses of children with individual
blood Pb concentrations below 10 [mu]g/dL. In comparing across the
individual epidemiological studies and the international pooled
analysis, the Criteria Document observed that at higher blood Pb levels
(e.g., above 10 [mu]g/dL), the slopes (for change in IQ with blood Pb)
derived for log-linear and linear models are almost identical, and for
studies with lower blood Pb levels, the slopes appear to be steeper
than those observed in studies involving higher blood Pb levels (CD, p.
8-78, Figure 8-7). In making these observations, the Criteria Document
focused on the curves from the models from the 10th percentile to the
90th percentile saying that the ``curves are restricted to that range
because log-linear curves become very steep at the lower end of the
blood Pb levels, and this may be an artifact of the model chosen.''
    The quantitative relationship between IQ and blood Pb level has
been examined in the Criteria Document using studies where all or the
majority of study subjects had blood Pb levels below 10 [mu]g/dL and
also where an analysis was performed on a subset of children whose
blood Pb levels have never exceeded 10 [mu]g/dL (CD, Table 6-1). The
datasets for three of these studies included concurrent blood Pb levels
above 10 [mu]g/dL; the C-R relationship reported for one of the three
was linear while it was log-linear for the other two. For the one of
these three studies with the linear C-R relationship, the highest blood
Pb level was just below 12 [mu]g/dL (Kordas et al., 2006). Of the two
studies with log-linear functions, one reported 69% of the children
with blood Pb levels below 10 [mu]g/dL and a population mean blood Pb
level of 7.44 [mu]g/dL (Al-Saleh et al., 2001), and the second reported
a population median blood Pb level of 9.7 [mu]g/dL and a 95th
percentile of 33.2 [mu]g/dL (Lanphear et al., 2005). In order to
compare slopes across all of these studies (linear and log-linear), EPA
estimated, for each, the average slope of change in IQ with change in
blood Pb between the 10th percentile \61\ blood Pb level and 10 [mu]g/
dL (CD, Table 6-1). The resultant group of reported and estimated
average linear slopes for IQ change with blood Pb levels up to 10
[mu]g/dL range from -0.4 to -1.8 IQ points per [mu]g/dL blood Pb (CD,
Tables 6-1 and 8-7), with a median of -0.9 IQ points per [mu]g/dL blood
Pb (CD, pp. 8-80).\62\
---------------------------------------------------------------------------

    \61\ In the Criteria Document analysis, the 10th percentile was
chosen as a common point of comparison for the loglinear (and
linear) models at a point prior to the lowest end of the blood Pb
levels.
    \62\ Among this group of slopes (CD, Table 6-1) is that from the
analysis of the IQ-blood Pb (concurrent) relationship for children
whose peak blood Pb levels are below 10 [mu]g/dL in the
international pooled dataset studied by Lanphear and others (2005);
these authors reported this slope along with the companion slope for
blood Pb levels for the remaining children with peak blood Pb level
equal to or above 10 [mu]g/dL (Lanphear et al., 2005). In the
economic analysis for EPA's recent Lead Renovation, Repair and
Painting (RRP) Program rule (described above in section I.C),
changes in IQ loss as a function of changes in lifetime average
blood Pb level were estimated using the corresponding piecewise
model for lifetime average blood Pb derived from the pooled dataset
(USEPA, 2008; USEPA, 2007e). Selection of this model for the RRP
economic analysis reflects consideration of the distribution of
blood Pb levels in that analysis, those for children living in
houses with Pb-based paint. With consideration of these blood Pb
levels, the economic analysis document states that ``[s]electing a
model with a node, or changing one segment to the other, at a
lifetime average blood Pb concentration of 10 [mu]g/dL rather than
at 7.5 [mu]g/dL, is a small protection against applying an
incorrectly rapid change (steep slope with increasingly smaller
effect as concentrations lower) to the calculation''. We note that
the slope for the less-than-10-[mu]g/dL portion of the model used in
the RRP analysis (-0.88) is similar to the median for the slopes
included in the Criteria Document analysis of quantitative
relationships for distributions of blood Pb levels extending from
just below 10 [mu]g/dL and lower.
---------------------------------------------------------------------------

    Among this group of quantitative IQ-blood Pb relationships examined
in the Criteria Document (CD, Tables 6-1 and 8-7), the steepest slopes
for change in IQ with change in blood Pb level are those derived for
the subsets of children in the Rochester and Boston cohorts for which
peak blood Pb levels were <10 [mu]g/dL; these slopes, in terms of IQ
points per [mu]g/dL blood Pb, are -1.8 (for concurrent blood Pb
influence on IQ) and -1.6 (for 24-month blood Pb influence on IQ),
respectively. The mean blood Pb levels for children in these subsets of
the Rochester and Boston cohorts are 3.32 and 3.8 [mu]g/dL,
respectively, which are the lowest population mean levels among the
datasets included in the table (Canfield, 2008; Bellinger, 2008). Other
studies with analyses involving similarly low blood Pb levels (e.g.,
mean levels below 4 [mu]g/dL) also had slopes steeper than -1.5 points
per [mu]g/dL blood Pb. These include the slope of -1.71 points per
[mu]g/dL blood Pb \63\ for the subset of 24-month-old children in the
Mexico City cohort with blood Pb levels less than 5 [mu]g/dL (n=193),
for which the mean concurrent blood Pb level was 2.9 [mu]g/dL (Tellez-
Rojo et al. 2006, 2008) \64\ and also the slope of -2.94 points per
[mu]g/dL blood Pb for the subset of 6-10-year-old children whose peak
blood Pb levels never exceeded 7.5 [mu]g/dL (n=112), and for which the
mean concurrent blood Pb level was 3.24 [mu]g/dL (Lanphear et al. 2005;
Hornung 2008). Thus, from these subset analyses, the slopes range from
-1.71 to -2.94 IQ points per [mu]g/dL of concurrent blood Pb. We also
note that the nonlinear C-R function in which greatest confidence is
placed in estimating IQ loss in the quantitative risk assessment
(described below in section II.C) has a slope that falls

intermediate between these two for blood Pb levels up to approximately
3.7 [mu]g/dL (USEPA, 2007b).
---------------------------------------------------------------------------

    \63\ This slope reflects effects on cognitive development in
this cohort of 24-month-old children based on the age-appropriate
test described earlier, and is similar in magnitude to slopes for
the cohorts of older children described here. The strengths and
limitations of this age-appropriate text, the Mental Development
Index (MDI) of the Bayley Scales of Infant Development (BSID), were
discussed in a letter to the editor by Black and Baqui (2005). The
authors state that ``the MDI is a well-standardized,
psychometrically strong measure of infant mental development.'' The
MDI represents a complex integration of empirically-derived
cognitive skills, for example, sensory/perceptual acuities,
discriminations, and response; acquisition of object constancy;
memory learning and problem solving; vocalization and beginning of
verbal communication; and basis of abstract thinking. Black and
Baqui state that although the MDI is one of the most well-
standardized, widely used assessment of infant mental development,
evidence indicates low predictive validity of the MDI for infants
younger than 24 months to subsequent measures of intelligence. They
explain that the lack of continuity may be partially explained by
``the multidimensional and rapidly changing aspects of infant mental
development and by variations in performance during infancy,
variations in tasks used to measure intellectual functioning
throughout childhood, and variations in environmental challenges and
opportunities that may influence development.'' Martin and Volkmar
(2007) also noted that correlations between BSID performance and
subsequent IQ assessments were variable, but they also reported high
test-retest reliability and validity, as indicated by the
correlation coefficients of 0.83 to 0.91, as well as high interrater
reliability, correlation coefficient of 0.96, for the MDI.
Therefore, the BSID has been found to be a reliable indicator of
current development and cognitive functioning of the infant. Martin
and Volkmar (2007) further note that ``for the most part,
performance on the BSID does not consistently predict later
cognitive measures, particularly when socioeconomic status and level
of functioning are controlled''.
    \64\ In this study, the slope for blood Pb levels between 5 and
10 [mu]g/dL (population mean blood Pb of 6.9 [mu]g/dL; n=101) was -
0.94 points per [mu]g/dL blood Pb but was not statistically
significant, with a P value of 0.12. The difference in the slope
between the <5 [mu]g/dL and the 5-10 [mu]g/dL groups was not
statistically significant (Tellez-Rojo et al., 2006; Tellez-Rojo,
2008).
---------------------------------------------------------------------------

    The C-R functions discussed above are presented in two sets in
Table 1 below.

                        Table 1. Summary of Quantitative Relationships of IQ and Blood Pb for Two Sets of Studies Discussed Above
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Form of model      Average
                                                                                Range BLL  ([mu]g/  Geometric mean BLL     from which      linear slope
        Study/Analysis             Study cohort     Analysis dataset      N         dL)  5th-95th         ([mu]g/dL)       average slope    \A\  (points
                                                                                percentile]                              derived      per [mu]g/dL)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                   Set of studies from which steeper slopes are drawn
--------------------------------------------------------------------------------------------------------------------------------------------------------
Tellez-Rojo <5 subgroup based   Mexico City, age   Children--BLL<5          193  0.8-4.9...........  2.9...............  Linear..........  -1.71
 on Lanphear et al. 2005,\B\     24 mo.             [mu]g/dL.
 Log-linear with low-exposure
 linearization (LLL) \B\.
                                   Dataset from which the log-linear function is derived is the pooled International     LLL\C\..........  -2.29 at 2
                                 dataset of 1333 children, age 6-10 yr, having median blood Pb of 9.7 [mu]g/dL and 5th-                     [mu]g/dL\C\
                                  95th percentile of 2.5-33.2 [mu]g/dL.Slope presented here is the slope at a blood Pb
                                                                 level of 2 [mu]g/dL.\C\
Lanphear et al. 2005,\B\ <7.5   Pooled             Children--peak           103  [1.3-6.0].........  3.24..............  Linear..........  -2.94
 peak subgroup.                  International,     BLL <7.5 [mu]g/
                                 age 6-10 yr.       dL.
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                         Set of studies with shallower slopes (Criteria Document, Table 6-1) \D\
--------------------------------------------------------------------------------------------------------------------------------------------------------
Canfield et al. 2003 \B\, <10   Rochester, age 5   Children--peak            71  Unspecified.......  3.32..............  Linear..........  -1.79
 peak subgroup.                  yr.                BLL <10 [mu]g/dL.
Bellinger and Needleman         Boston\A\ \E\....  Children--peak            48  1-9.3\E\..........  3.8\E\............  Linear..........  -1.56
 2003\B\.                                           BLL <10 [mu]g/dL.
Tellez-Rojo et al. 2006.......  Mexico City, age   Full dataset.....        294  0.8-<10...........  4.28..............  Linear..........  -1.04
                                 24 mo.
Tellez-Rojo et al. 2006 full--  Mexico City, age   Full dataset.....        294  0.8-<10...........  4.28..............  Log-linear......  -0.94
 loglinear.                      24 mo.
Lanphear et al. 2005,\B\ <10    Pooled             Children--peak           244  [1.4-8.0].........  4.30..............  Linear..........  -0.80
 peak\F\ subgroup.               International,     BLL <10 [mu]g/dL.
                                 age 6-10 yr.
Al-Saleh et al. 2001 full--     Saudi Arabia, age  Full dataset.....        533  2.3-27.36\G\......  7.44..............  Log-linear......  -0.76
 loglinear.                      6-12 yr.
Kordas et al. 2006, <12         Torreon, Mexico,   Children--BLL<12         377  2.3-<12...........  7.9...............  Linear..........  -0.40
 subgroup.                       age 7 yr.          [mu]g/dL.
Lanphear et al. 2005\B\ full--  Pooled             Full dataset.....       1333  [2.5-33.2]........  9.7 (median)......  Log-linear......  -0.41
 loglinear.                      International,
                                 age 6-10 yr.
                                                                                Median value....  -0.9 \D\
--------------------------------------------------------------------------------------------------------------------------------------------------------
\A\ Average slope for change in IQ from 10th percentile to 10 [mu]g/dL Slope estimates here are for relationship between IQ and concurrent blood Pb
  levels (BLL), except for Bellinger & Needleman which used 24 month BLLs with 10 year old IQ.
\B\ The Lanphear et al. 2005 pooled International study includes blood Pb data from the Rochester and Boston cohorts, although for different ages (6 and
  5 years, respectively) than the ages analyzed in Canfield et al. 2003 and Bellinger and Needleman 2003.
\C\ The LLL function (described in section II.C.2.b) was developed from Lanphear et al. 2005 loglinear model with a linearization of the slope at BLL
  below 1 [mu]g/dL. The slope shown is that at 2 [mu]g/dL. In estimating IQ loss with this function in the risk assessment (section II.C) and in the
  evidence-based considerations in section II.E.3, the nonlinear form of the model was used, with varying slope for all BLL above 1 [mu]g/dL.
\D\ These studies and quantitative relationships are discussed in the Criteria Document (CD, sections 6.2, <IP_ADDRESS> and 8.6.2).
\E\ The BLL for Bellinger and Needleman (2003) are for age 24 months.
\F\ As referenced above and in section II.C.2.b, the form of this function derived for lifetime average blood Pb was used in the economic analysis for
  the RRP rule. The slope for that function was -0.88 IQ points per [mu]g/dL lifetime averaged blood Pb.
\G\ 69% of children in Al-Saleh et al. (2001) study had BLL<10 [mu]g/dL.

3. Lead-Related Impacts on Public Health
    In addition to the advances in our knowledge and understanding of
Pb health effects at lower exposures (e.g., using blood Pb as the
index), there has been some change with regard to the U.S. population
Pb burden since the time of the last Pb NAAQS review. For example, the
geometric mean blood Pb level for U.S. children aged 1-5, as estimated
by the U.S. Centers for Disease Control, declined from 2.7 [mu]g/dL
(95% CI: 2.5-3.0) in the 1991-1994 survey period to 1.7 [mu]g/dL (95%
CI: 1.55-1.87) in the 2001-2002 survey period (CD, Section <IP_ADDRESS>) and
1.8 [mu]g/dL in the 2003-2004 survey period (Axelrad, 2008).\65\ Blood
Pb levels have also declined in the U.S. adult population over this
time period (CD, Section <IP_ADDRESS>).\66\ As noted in the Criteria
Document, ``blood-Pb levels have been declining at differential rates
for various general subpopulations, as a function of income, race, and
certain other demographic indicators such as age of housing'' (CD, pp.
8-21). For example, the geometric mean blood Pb level for children
(aged one to five) living in poverty in the 2003-2004 survey period is
2.4 [mu]g/dL. For black, non-Hispanic children, the geometric mean is
2.7 [mu]g/dL, and for the subset of this group that is living in
poverty, the geometric mean is 3.1 [mu]g/dL. Further, the 95th
percentile blood Pb level in the 2003-2004 NHANES for children aged 1-5
of all races and ethnic groups is 5.1 [mu]g/dL, while the corresponding
level for the subset of children living below the poverty level is 6.6
[mu]g/dL. The 95th percentile level for black, non-Hispanic children is
8.9 [mu]g/dL, and for the subset of that group living below the poverty
level, it is 10.5 [mu]g/dL (Axelrad, 2008).\67\
---------------------------------------------------------------------------

    \65\ These levels are in contrast to the geometric mean blood Pb
level of 14.9 [mu]g/dL reported for U.S. children (aged 6 months to
5 years) in 1976-1980 (CD, Section <IP_ADDRESS>).
    \66\ For example, NHANES data for older adults (60 years of age
and older) indicate a decline in overall population geometric mean
blood Pb level from 3.4 [mu]g/dL in 1991-1994 to 2.2 [mu]g/dL in
1999-2002; the trend for adults between 20 and 60 years of age is
similar to that for children 1 to 5 years of age (http://
www.cdc.gov/mmwr/preview/mmwrhtml/mm5420a5.htm).
    \67\ Although the 90th percentile statistic for these subgroups
is not currently available for the 2003-04 survey period, the 2001-
2004 90th percentile blood Pb level for children aged 1-5 of all
races and ethnic groups is 4.0 [mu]g/dL, while the corresponding
level for the subset of children living below the poverty level is
5.4 [mu]g/dL, and that level for black, non-Hispanic children living
below the poverty level is 7.7 [mu]g/dL (http://www.epa.gov/
envirohealth/children/body_burdens/b1-table.htm--then click on
``Download a universal spreadsheet file of the Body Burdens data
tables'').
---------------------------------------------------------------------------

a. At-Risk Subpopulations
    Potentially at-risk subpopulations include those with increased
susceptibility (i.e., physiological factors contributing to a greater
response for the same exposure) and those with increased exposure
(including that resulting from behavior leading to increased contact
with contaminated media) (USEPA 1986a, pp. 1-154). A behavioral factor
of great impact on Pb exposure is the incidence of hand-to-mouth
activity that is prevalent in very young children (CD, Section 4.4.3).
Physiological factors include both conditions contributing to a
subgroup's increased risk of effects at a given blood Pb level, and
those that contribute to blood Pb levels higher than those otherwise
associated with a given Pb exposure (CD, Section 8.5.3). These factors
include nutritional status (e.g., iron deficiency, calcium intake), as
well as genetic and other factors (CD, chapter 4 and sections 3.4,
5.3.7 and 8.5.3).
    We also considered evidence pertaining to vulnerability to
pollution-related effects which additionally encompasses situations of
elevated exposure, such as residing in older housing with Pb-containing
paint or near sources of ambient Pb, as well as socioeconomic factors,
such as reduced access to health care or low socioeconomic status (SES)
(USEPA, 2003, 2005c) that can contribute to increased risk of adverse
health effects from Pb. With regard to elevated exposures in particular
socioeconomic and minority subpopulations, we observe notably higher
blood Pb levels in children in poverty and in black, non-Hispanic
children compared to those for more economically well-off children and
white children, in general (as recognized in section II.B.1.b above).
    Three particular physiological factors contributing to increased
risk of Pb effects at a given blood Pb level are recognized in the
Criteria Document (e.g., CD, Section 8.5.3): age, health status, and
genetic composition. With regard to age, the susceptibility of young
children to the neurodevelopmental effects of Pb is well recognized
(e.g., CD, Sections 5.3, 6.2, 8.4, 8.5, 8.6.2), although the specific
ages of vulnerability have not been established (CD, pp. 6-60 to 6-64).
Early childhood may also be a time of increased susceptibility for Pb
immunotoxicity (CD, Sections 5.9.10, 6.8.3 and 8.4.6). Further early
life exposures have been associated with increased risk of
cardiovascular effects in humans later in life (CD, pp. 8-74). Early
life exposures have also been associated with increased risk, in
animals, of neurodegenerative effects later in life (CD, pp. 8-74).\68\
Health status is another physiological factor in that subpopulations
with pre-existing health conditions may be more susceptible (as
compared to the general population) for particular Pb-associated
effects, with this being most clear for renal and cardiovascular
outcomes. For example, African Americans as a group have a higher
frequency of hypertension than the general population or other ethnic
groups (NCHS, 2005), and as a result may face a greater risk of adverse
health impact from Pb-associated cardiovascular effects. A third
physiological factor relates to genetic polymorphisms. That is,
subpopulations defined by particular genetic polymorphisms (e.g.,
presence of the [delta]-aminolevulinic acid dehydratase-2 [ALAD-2]
allele) have also been recognized as sensitive to Pb toxicity, which
may be due to increased susceptibility to the same internal dose and/or
to increased internal dose associated with the same exposure (CD, pp.
8-71, Sections 6.3.5, <IP_ADDRESS> and 6.3.6).
---------------------------------------------------------------------------

    \68\ Specifically, among young adults who lived as children in
an area heavily polluted by a smelter and whose current Pb exposure
was low, higher bone Pb levels were associated with higher systolic
and diastolic blood pressure (CD, pp. 8-74). In adult rats, greater
early exposures to Pb are associated with increased levels of
amyloid protein precursor, a marker of risk for neurodegenerative
disease (CD, pp. 8-74).
---------------------------------------------------------------------------

    Childhood is well recognized as a time of increased susceptibility,
and as summarized in section II.B.2.b above and described in more
detail in the Criteria Document, a large body of epidemiological
evidence describes neurological effects on children at low blood Pb
levels. The toxicological evidence further helps inform an
understanding of specific periods of development with increased
vulnerability to specific types of neurological effect (CD, Section
5.3). Additionally, the toxicological evidence of a differing
sensitivity of the immune system to Pb across and within different
periods of life stages indicates the potential importance of exposures
of duration as short as weeks to months. For example, the animal
studies suggest that, for immune effects, the gestation period is the
most sensitive life stage followed by early neonatal stage, and that
within these life stages, critical windows of vulnerability are likely
to exist (CD, Section 5.9 and p. 5-245).
    In summary, there are a variety of ways in which Pb exposed
populations might be characterized and stratified for consideration of
public health impacts. Age or lifestage was used to distinguish

potential groups on which to focus the quantitative risk assessment
because of its influence on exposure and susceptibility. Young children
were selected as the priority population for the risk assessment in
consideration of the health effects evidence regarding endpoints of
greatest public health concern. The Criteria Document recognizes,
however, other population subgroups as described above may also be at
risk of Pb-related health effects of public health concern.
b. Potential Public Health Impacts
    As discussed in the Criteria Document, there are potential public
health implications of low-level Pb exposure, indexed by blood Pb
levels, associated with several health endpoints identified in the
Criteria Document (CD, Section 8.6).\69\ These include potential
impacts on population IQ, which is the focus of the quantitative risk
assessment conducted for this review, as well as heart disease and
chronic kidney disease, which are not included in the quantitative risk
assessment (CD, Sections 8.6, 8.6.2, 8.6.3 and 8.6.4). It is noted that
there is greater uncertainty associated with effects at the lower
levels of blood Pb, and that there are differing weights of evidence
across the effects observed.\70\ With regard to potential implications
of Pb effects on IQ, the Criteria Document recognizes the ``critical''
distinction between population and individual risk, noting that a
``point estimate indicating a modest mean change on a health index at
the individual level can have substantial implications at the
population level'' (CD, p. 8-77).\71\ A downward shift in the mean IQ
value is associated with both substantial decreases in percentages
achieving very high scores and substantial increases in the percentage
of individuals achieving very low scores (CD, p. 8-81).\72\ For an
individual functioning in the low IQ range due to the influence of
developmental risk factors other than Pb, a Pb-associated IQ decline of
several points might be sufficient to drop that individual into the
range associated with increased risk of educational, vocational, and
social handicap (CD, p. 8-77).
---------------------------------------------------------------------------

    \69\ The differing evidence and associated strength of the
evidence for these different effects is described in detail in the
Criteria Document.
    \70\ As is described in Section II.C.2.a, CASAC, in their
comments on the analysis plan for the risk assessment described in
this notice, placed higher priority on modeling the child IQ metric
than the adult endpoints (e.g., cardiovascular effects).
    \71\ Similarly, ``although an increase of a few mmHg in blood
pressure might not be of concern for an individual's well-being, the
same increase in the population mean might be associated with
substantial increases in the percentages of individuals with values
that are sufficiently extreme that they exceed the criteria used to
diagnose hypertension'' (CD, p. 8-77).
    \72\ For example, for a population mean IQ of 100 (and standard
deviation of 15), 2.3% of the population would score above 130, but
a shift of the population to a mean of 95 results in only 0.99% of
the population scoring above 130 (CD, pp. 8-81 to 8-82).
---------------------------------------------------------------------------

    The magnitude of a public health impact is dependent upon the size
of population affected and type or severity of the effect. As
summarized above, there are several population groups that may be
susceptible or vulnerable to effects associated with exposure to Pb,
including young children, particularly those in families of low SES
(CD, p. E-15), as well as individuals with hypertension, diabetes, and
chronic renal insufficiency (CD, p. 8-72). Although comprehensive
estimates of the size of these groups residing in proximity to sources
of ambient Pb have not been developed, total estimates of these
population subpopulations within the U.S. are substantial (as noted in
Table 3-3 of the Staff Paper).\73\
---------------------------------------------------------------------------

    \73\ For example, approximately 4.8 million children live in
poverty, while the estimates of numbers of adults with hypertension,
diabetes or chronic kidney disease are on the order of 20 to 50
million (see Table 3-3 of Staff Paper).
---------------------------------------------------------------------------

    With regard to estimates of the size of potentially vulnerable
subpopulations living in areas of increased exposure related to ambient
Pb, the information is still more limited. The limited information
available on air and surface soil concentrations of Pb indicates
elevated concentrations near stationary sources as compared with areas
remote from such sources (CD, Sections 3.2.2 and 3.8). Air quality
analyses (presented in Chapter 2 of the Staff Paper) indicate
dramatically higher Pb concentrations at monitors near sources as
compared with those more remote. As described in Section <IP_ADDRESS> of the
Staff Paper, however, since the 1980s the number of Pb monitors has
been significantly reduced by states (with EPA guidance that monitors
well below the current NAAQS could be shut down) and a lack of monitors
near some large sources may lead to underestimates of the extent of
occurrences of relatively higher Pb concentrations. The significant
limitations of our monitoring and emissions information constrain our
efforts to characterize the size of at-risk populations in areas
influenced by sources of ambient Pb. For example, the limited size and
spatial coverage of the current Pb monitoring network constrains our
ability to characterize current levels of airborne Pb in the U.S.
Further, as noted above in section II.A.1, the Staff Paper review of
the available information on emissions and locations of sources (as
described in section <IP_ADDRESS> of the Staff Paper) indicates that the
network is inconsistent in its coverage of the largest sources
identified in the 2002 National Emissions Inventory (NEI). The most
recent analysis of monitors near sources greater than 1 ton per year
(tpy) indicates that less than 15% of stationary sources with emissions
greater than or equal to 1 tpy have a monitor within one mile.
Additionally, there are various uncertainties and limitations
associated with source information in the NEI (as described in section
2.2.5 of the Staff Paper; USEPA, 2007c).
    In recognition of the significant limitations associated with the
currently available information on Pb emissions and airborne
concentrations in the U.S. and the associated exposure of potentially
at-risk populations, Chapter 2 of the Staff Paper summarizes the
information in several different ways. For example, analyses of the
current monitoring network indicated the numbers of monitoring sites
that would exceed alternate standard levels, taking into consideration
different statistical forms. These analyses are also summarized with
regard to population size in counties home to those monitoring sites
(as presented in Appendix 5.A of the Staff Paper). Information for the
monitors and from the NEI indicates a range of source sizes in
proximity to monitors at which various levels of Pb are reported.
Together this information suggests that there is variety in the
magnitude of Pb emissions from sources that could influence air Pb
concentrations. Identifying specific emissions levels of sources
expected to result in air Pb concentrations of interest, however, would
be informed by a comprehensive analysis using detailed source
characterization information, which was not feasible within the time
and data constraints of this review. Instead, we have developed a
summary of the emissions and demographic information for Pb sources
that includes estimates of the numbers of people residing in counties
in which the aggregate Pb emissions from NEI sources is greater than or
equal to 0.1 tpy or in counties in which the aggregate Pb emissions is
greater than or equal to 0.1 tpy per 1000 square miles (as presented in
Tables 3-4 and 3-5, respectively, in the Staff Paper).
    Additionally, the potential for resuspension of recently and
historically deposited Pb near roadways to contribute to increased
risks of Pb exposure to populations residing nearby is suggested in the
Criteria Document (e.g., CD, pp. 2-62 and 3-32).

4. Key Observations
    The following key observations are based on the available health
effects evidence and the evaluation and interpretation of that evidence
in the Criteria Document.
     Lead exposures occur both by inhalation and by ingestion
(CD, Chapter 3). As stated in the Criteria Document, ``given the large
amount of time people spend indoors, exposure to Pb in dusts and indoor
air can be significant'' (CD, p. 3-27).
     Children, in general and especially those of low SES, are
at increased risk for Pb exposure and Pb-induced adverse health
effects. This is due to several factors, including enhanced exposure to
Pb via ingestion of soil Pb and/or dust Pb due to normal childhood
hand-to-mouth activity (CD, p. E-15, Chapter 3 and Section 6.2.1).
     Once inhaled or ingested, Pb is distributed by the blood,
with long-term storage accumulation in the bone. Bone Pb levels provide
a strong measure of cumulative exposure which has been associated with
many of the effects summarized below, although difficulty of sample
collection has precluded widespread use in epidemiological studies to
date (CD, Chapter 4).
     Blood levels of Pb are well accepted as an index of
exposure (or exposure metric) for which associations with the key
effects (see below) have been observed. In general, associations with
blood Pb are most robust for those effects for which past exposure
history poses less of a complicating factor, i.e., for effects during
childhood (CD, Section 4.3).
     Both epidemiological and toxicologic studies have shown
that environmentally relevant levels of Pb affect many different organ
systems (CD, p. E-8). With regard to the most important such effects
observed in children and adults, the Criteria Document states (CD, p.
8-60) that ``neurotoxic effects in children and cardiovascular effects
in adults are among those best substantiated as occurring at blood-Pb
concentrations as low as 5 to 10 [mu]g/dL (or possibly lower); and
these categories of effects are currently clearly of greatest public
health concern. Other newly demonstrated immune and renal system
effects among general population groups are also emerging as low-level
Pb-exposure effects of potential public health concern.''
     Many associations of health effects with Pb exposure have
been found at levels of blood Pb that are currently relevant for the
U.S. population, with individual children having blood Pb levels of 5-
10 [mu]g/dL and lower, being at risk for neurological effects (as
described in the subsequent bullet). Supportive evidence from
toxicological studies provides biological plausibility for the observed
effects. (CD, Chapters 5, 6 and 8)
     Pb exposure is associated with a variety of neurological
effects in children, notably intellectual attainment and school
performance. Both qualitative and quantitative evidence, with further
support from animal research, indicates a robust and consistent effect
of Pb exposure on neurocognitive ability at mean concurrent blood Pb
levels in the range of 5 to 10 [mu]g/dL. Specific epidemiological
analyses have further indicated association with neurocognitive effects
in analyses restricted to children with individual blood Pb levels
below 5-10 [mu]g/dL, and for which group mean levels are lower.
Further, ``[s]ome newly available analyses appear to show Pb effects on
the intellectual attainment of preschool and school age children at
population mean concurrent blood-Pb levels ranging down to as low as 2
to 8 [mu]g/dL'' (CD, p. E-9; Sections 5.3, 6.2, 8.4.2 and 6.10).
     Deficits in cognitive skills may have long-term
consequences over a lifetime. Poor academic skills and achievement can
have enduring and important effects on objective parameters of success
in life as well as increased risk of antisocial and delinquent
behavior. (CD, Sections 6.1 and 8.4.2)
     The current epidemiological evidence indicates a steeper
slope of the blood Pb concentration-response relationship at lower
blood Pb levels, particularly those below 10 [mu]g/dL (CD, Sections
6.2.13 and 8.6).
     At mean blood Pb levels, in children, on the order of 10
[mu]g/dL, and somewhat lower, associations have been found with effects
to the immune system, including altered macrophage activation,
increased IgE levels and associated increased risk for autoimmunity and
asthma (CD, Sections 5.9, 6.8, and 8.4.6).
     In adults, with regard to cardiovascular outcomes, the
Criteria Document included the following summary (CD, p. E-10).

    Epidemiological studies have consistently demonstrated
associations between Pb exposure and enhanced risk of deleterious
cardiovascular outcomes, including increased blood pressure and
incidence of hypertension.\74\ A meta-analysis of numerous studies
estimates that a doubling of blood-Pb level (e.g., from 5 to 10
[mu]g/dL) is associated with ~1.0 mm Hg increase in systolic blood
pressure and ~0.6 mm Hg increase in diastolic pressure. Studies have
also found that cumulative past Pb exposure ( e.g., bone Pb) may be
as important, if not more, than present Pb exposure in assessing
cardiovascular effects. The evidence for an association of Pb with
cardiovascular morbidity and mortality is limited but supportive.
---------------------------------------------------------------------------

    \74\ The Criteria Document states that ``While several studies
have demonstrated a positive correlation between blood pressure and
blood Pb concentration, others have failed to show such association
when controlling for confounding factors such as tobacco smoking,
exercise, body weight, alcohol consumption, and socioeconomic
status. Thus, the studies that have employed blood Pb level as an
index of exposure have shown a relatively weak association with
blood pressure. In contrast, the majority of the more recent studies
employing bone Pb level have found a strong association between
long-term Pb exposure and arterial pressure (Chapter 6). Since the
residence time of Pb in the blood is relatively short but very long
in the bone, the latter observations have provided rather compelling
evidence for a positive relationship between Pb exposure and a
subsequent rise in arterial pressure'' (CD, pp. 5-102 to 5-103).
Further, in consideration of the meta-analysis also described here,
the Criteria Document stated that ``The meta-analysis provides
strong evidence for an association between increased blood Pb and
increased blood pressure over a wide range of populations'' (CD, p.
6-130) and ``the meta-analyses results suggest that studies not
detecting an effect may be due to small sample sizes or other
factors affecting precision of estimation of the exposure effect
relationship'' (CD, p. 6-133).

Studies of nationally representative U.S. samples observed associations
between blood Pb levels and increased systolic blood pressure at
population mean blood Pb levels less than 5 [mu]g/dL, particularly
among African Americans (CD, Section 6.5.2). With regard to gender
---------------------------------------------------------------------------
differences, the Criteria Document states the following (CD, p. 6-154).

    Although females often show lower Pb coefficients than males,
and Blacks higher Pb coefficients than Whites, where these
differences have been formally tested, they are usually not
statistically significant. The tendencies may well arise in the
differential Pb exposure in these strata, lower in women than in
men, higher in Blacks than in Whites. The same sex and race
differential is found with blood pressure.

Animal evidence provides confirmation of Pb effects on cardiovascular
functions (CD, Sections 5.5, 6.5, 8.4.3 and 8.6.3).

     Renal effects, evidenced by reduced renal filtration, have
also been associated with Pb exposures indexed by bone Pb levels and
also with mean blood Pb levels in the range of 5 to 10 [mu]g/dL in the
general adult population, with the potential adverse impact of such
effects being enhanced for susceptible subpopulations including those
with diabetes, hypertension, and chronic renal insufficiency (CD,
Sections 6.4, 8.4.5, and 8.6.4). The full significance of this effect
is unclear,

given that other evidence of more marked signs of renal dysfunction
have not been detected at blood Pb levels below 30-40 [mu]g/dL in large
studies of occupationally exposed Pb workers (CD, pp. 6-270 and 8-
50).\75\
---------------------------------------------------------------------------

    \75\ In the general population, both cumulative and circulating
Pb has been found to be associated with longitudinal decline in
renal functions. In the large NHANES III study, alterations in
urinary creatinine excretion rate (one indicator of possible renal
dysfunction) were observed in hypertensives at a mean blood Pb of
only 4.2 [mu]g/dL. These results provide suggestive evidence that
the kidney may well be a target organ for effects from Pb in adults
at current U.S. environmental exposure levels. The magnitude of the
effect of Pb on renal function ranged from 0.2 to -1.8 mL/min change
in creatinine clearance per 1.0 [mu]g/dL increase in blood Pb in
general population studies. However, the full significance of this
effect is unclear, given that other evidence of more marked signs of
renal dysfunction have not been detected at blood Pb levels below
30-40 [mu]g/dL among thousands of occupationally exposed Pb workers
that have been studied (CD, p. 6-270).
---------------------------------------------------------------------------

     Other Pb associated effects in adults occurring at or just
above 10 [mu]g/dL include hematological (e.g., impact on heme synthesis
pathway) and neurological effects, with animal evidence providing
support of Pb effects on these systems and evidence regarding mechanism
of action (CD, Sections 5.2, 5.3, 6.3 and 6.9.2).

C. Human Exposure and Health Risk Assessments

    This section presents a brief summary of the human exposure and
health risk assessments conducted by EPA for this review. The complete
full-scale assessment, which includes specific analyses conducted to
address CASAC comments and advice on an earlier draft assessment, is
presented in the final Risk Assessment Report (USEPA, 2007b).
    The focus of this Pb NAAQS risk assessment is on characterizing
risk resulting from exposure to policy-relevant Pb (i.e., exposure to
Pb that has passed through ambient air on its path from source to human
exposure--as described in section II.A.2). The design and
implementation of this assessment needed to address significant
limitations and complexity that go far beyond the situation for similar
assessments typically performed for other criteria pollutants. Not only
was the risk assessment constrained by the timeframe allowed for this
review in the context of breadth of information to address, it was also
constrained by significant limitations in data and modeling tools for
the assessment, as discussed further in section II.C.2.h below.
Furthermore, the multimedia and persistent nature of Pb, and the role
of multiple exposure pathways (discussed in section II.A), add
significant complexity to the assessment as compared to other
assessments that focus only on the inhalation pathway. The impact of
this on our estimates for air-related exposure pathways is discussed in
section II.C.2.e.
    The remainder of this overview of the human health risk assessment
is organized as follows. An overview of the human health risk
assessment completed in the last review of the Pb NAAQS in 1990 (USEPA,
1990a) is presented first. Next, design aspects of the current risk
assessment are presented, including: (a) CASAC advice regarding the
design of the risk assessment, (b) description of health endpoints and
associated risk metrics modeled, including the concentration-response
functions used, (c) overview of the case study approach employed, (d)
description of air quality scenarios modeled, (e) explanation of air-
related versus background classification of risk results in the context
of this analysis, (f) overview of analytical (modeling) steps completed
for the risk assessment and (g) description of the multiple sets of
risk results generated for the analysis. Then, key sources of
uncertainty associated with the analysis are presented. And finally, a
summary of exposure and risk estimates and key observations is
presented.
1. Overview of Risk Assessment From Last Review
    The risk assessment conducted in support of the last review used a
case study approach to compare air quality scenarios in terms of their
impact on the percentage of modeled populations that exceeded specific
blood Pb levels chosen with consideration of the health effects
evidence at that time (USEPA, 1990b; USEPA, 1989). The case studies in
that analysis, however, focused exclusively on Pb smelters including
two secondary and one primary smelter and did not consider exposures in
a more general urban context. The analysis focused on children (birth
through 7 years of age) and middle-aged men. The assessment evaluated
impacts of alternate NAAQS on numbers of children and men with blood Pb
levels above levels of concern based on health effects evidence at that
time. The primary difference between the risk assessment approach used
in the current analysis and the assessment completed in 1990 involves
the risk metric employed. Rather than estimating the percentage of
study populations with exposures above blood Pb levels of interest as
was done in the last review (i.e., 10, 12 and 15 [mu]g/dL), the current
analysis estimates changes in health risk, specifically IQ loss,
associated with Pb exposure for child populations at each of the case
study locations with that estimated IQ loss further differentiated
between air-related and background Pb exposure categories.
2. Design Aspects of Exposure and Risk Assessments
    This section provides an overview of key elements of the assessment
design, inputs, and methods, and includes identification of key
uncertainties and limitations.
a. CASAC Advice
    The CASAC conducted a consultation on the draft analysis plan for
the risk assessment (USEPA, 2006c) in June, 2006 (Henderson, 2006).
Some key comments provided by CASAC members on the plan included: (1)
Placing a higher priority on modeling the child IQ metric than the
adult endpoints (e.g., cardiovascular effects), (2) recognizing the
importance of indoor dust loading by Pb contained in outdoor air as a
factor in Pb-related exposure and risk for sources considered in this
analysis, and (3) concurring with use of the IEUBK biokinetic blood Pb
model. Taking these comments into account, a pilot phase assessment was
conducted to test the risk assessment methodology being developed for
the subsequent full-scale assessment. The pilot phase assessment is
described in the first draft Staff Paper and accompanying technical
report (ICF 2006), which was discussed by the CASAC Pb panel on
February 6-7 (Henderson, 2007a).
    Results from the pilot assessment, together with comments received
from CASAC and the public, informed the design of the full-scale
analysis. The full-scale analysis included a substitution of a more
generalized urban case study for the location-specific near-roadway
case study evaluated in the pilot. In addition, a number of changes
were made in the exposure and risk assessment approaches, including the
development of a new indoor dust Pb model focused specifically on urban
residential locations and specification of additional IQ loss
concentration-response (C-R) functions to provide greater coverage for
potential impacts at lower exposure levels.
    The draft full-scale assessment was presented in the July 2007
draft risk assessment report (USEPA, 2007a) that was released for
public comment and provided to CASAC for review. In their review of the
July draft risk assessment report, the CASAC Pb Panel made several
recommendations for additional exposure and health risk analyses
(Henderson, 2007b). These included a recommendation that the general
urban

case study be augmented by the inclusion of risk analyses in specific
urban areas of the U.S. In this regard, they specifically stated the
following (Henderson, 2007b, p. 3)

    * * * the CASAC strongly believes that it is important that EPA
staff make estimates of exposure that will have national
implications for, and relevance to, urban areas; and that,
significantly, the case studies of both primary lead (Pb) smelter
sites as well as secondary smelter sites, while relevant to a few
atypical locations, do not meet the needs of supporting a Lead
NAAQS. The Agency should also undertake case studies of several
urban areas with varying lead exposure concentrations, based on the
prototypic urban risk assessment that OAQPS produced in the 2nd
Draft Lead Human Exposure and Health Risk Assessments. In order to
estimate the magnitude of risk, the Agency should estimate exposures
and convert these exposures to estimates of blood levels and IQ loss
for children living in specific urban areas.

    Hence, EPA included additional case studies in the risk assessment
focused on characterizing risk for residential populations in three
specific urban locations. Further, CASAC recommended using a
concentration-response function with a change in slope near 7.5 [mu]g/
dL. Accordingly, EPA included such an additional concentration-response
function in the risk assessment. Results from the initial full-scale
analyses, along with comments from CASAC, such as those described here,
and the public resulted in a final version of the full-scale
assessments which is briefly summarized here and presented in greater
detail in the Risk Assessment Report and associated appendices (USEPA,
2007b).
    In their review of the final risk assessment, CASAC expressed
strong support, stating as follows (Henderson, 2008a, p. 4):

    The Final Risk Assessment report captures the breadth of issues
related to assessing the potential public health risk associated
with lead exposures; it competently documents the universe of
knowledge and interpretations of the literature on lead toxicity,
exposures, blood lead modeling and approaches for conducting risk
assessments for lead.

b. Health Endpoint, Risk Metric and Concentration-Response Functions
    The health endpoint on which the quantitative health risk
assessment focuses is developmental neurotoxicity in children, with IQ
decrement (or loss) as the risk metric. Among the wide variety of
health endpoints associated with Pb exposures, there is general
consensus that the developing nervous system in young children is the
most sensitive and that neurobehavioral effects (specifically
neurocognitive deficits), including IQ decrements, appear to occur at
lower blood levels than previously believed (i.e., at levels <10 [mu]g/
dL). The selection of children's IQ for the quantitative risk
assessment reflects consideration of the evidence presented in the
Criteria Document as well as advice received from CASAC (Henderson,
2006, 2007a).
    Given the evidence described in detail in the Criteria Document
(Chapters 6 and 8), and in consideration of CASAC recommendations
(Henderson, 2006, 2007a, 2007b), the risk assessment for this review
relies on the functions presented by Lanphear and others (2005) that
relate absolute IQ as a function of concurrent blood Pb or of the log
of concurrent blood Pb, and lifetime average blood Pb, respectively. As
discussed in the Criteria Document (CD, p. 8-63 to 8-64), the slope of
the concentration-response relationship described by these functions is
greater at the lower blood Pb levels (e.g., less than 10 [mu]g/dL). As
discussed in the Criteria Document and summarized in section II.B.2,
threshold blood Pb levels for these effects cannot be discerned from
the currently available epidemiological studies, and the evidence in
the animal Pb neurotoxicity literature does not define a threshold for
any of the toxic mechanisms of Pb (CD, Sections 5.3.7 and 6.2).
    In applying relationships observed with the international pooled
analysis by Lanphear and others (2005) to the risk assessment, which
includes blood Pb levels below the range represented by the pooled
analysis, several alternative blood Pb concentration-response models
were considered in recognition of a reduced confidence in our ability
to characterize the quantitative blood Pb concentration-response
relationship at the lowest blood Pb levels represented in the recent
epidemiological studies. The functions considered and employed in the
initial risk analyses for this review include the following.
     Log-linear function with low-exposure linearization, for
both concurrent and lifetime average blood metrics, applies the
nonlinear relationship down to the blood Pb concentration representing
the lower bound of blood Pb levels for that blood metric in the pooled
analysis and applies the slope of the tangent at that point to blood Pb
concentrations estimated in the risk assessment to fall below that
level.
     Log-linear function with cutpoint, for both concurrent and
lifetime average blood metrics, also applies the nonlinear relationship
at blood Pb concentrations above the lower bound of blood Pb
concentrations in the pooled analysis dataset for that blood metric,
but then applies zero risk to all lower blood Pb concentrations
estimated in the risk assessment (this cutpoint is 1 [mu]g/dL for the
concurrent blood Pb).
    In the additional risk analyses performed subsequent to the August
2007 CASAC public meeting, the two functions listed above and the
following two functions were employed (details on the forms of these
functions as applied in this risk assessment are described in Section
5.3.1 of the Risk Assessment Report).
     Population stratified dual linear function for concurrent
blood Pb, derived from the pooled dataset stratified at peak blood Pb
of 10 [mu]g/dL \76\ and
---------------------------------------------------------------------------

    \76\ As mentioned above (section II.B.2.b), this function
(derived for lifetime average blood Pb), was used in the economic
analysis for the RRP rule. This model was selected for the RRP
economic analysis with consideration of advice from CASAC and of the
distribution of blood Pb levels being considered in that analysis,
which focused on children living in houses with lead-based paint
(USEPA, 2008). With consideration of these blood Pb levels, the
economic analysis document states that ``[s]electing a model with a
node, or changing one segment to the other, at a lifetime average
blood Pb concentration of 10 [mu]g/dL rather than at 7.5 [mu]g/dL,
is a small protection against applying an incorrectly rapid change
(steep slope with increasingly smaller effect as concentrations
lower) to the calculation'' (USEPA, 2008).
---------------------------------------------------------------------------

     Population stratified dual linear function for concurrent
blood Pb, derived from the pooled dataset stratified at 7.5 [mu]g/dL
peak blood Pb.
    In interpreting risk estimates derived using the various functions,
consideration should be given to the uncertainties with regard to the
precision of the coefficients used for each analysis. The coefficients
for the log-linear model from Lanphear et al. (2005) had undergone a
careful development process, including sensitivity analyses, using all
available data from 1,333 children. The shape of the exposure-response
relationship was first assessed through tests of linearity, then by
evaluating the restricted cubic spline model. After determining that
the log-linear model provided a good fit to the data, covariates to
adjust for potential confounding were included in the log-linear model
with careful consideration of the stability of the parameter estimates.
After the multiple regression models were developed, regression
diagnostics were employed to ascertain whether the Pb coefficients were
affected by collinearity or influential observations. To further
investigate the stability of the model, a random-effects model (with
sites

random) was applied to evaluate the results and also the effect of
omitting one of the seven cohorts on the Pb coefficient. In the various
sensitivity analyses performed, the coefficient from the log-linear
model was found to be robust and stable. The log-linear model, however,
is not biologically plausible at the very lowest blood Pb
concentrations as they approach zero; therefore, in the first two
functions the log-linear model is applied down to a cutpoint (of 1
[mu]g/dL for the concurrent blood Pb metric), selected based on the low
end of the blood Pb levels in the pooled dataset, followed by a
linearization or an assumption of zero risk at levels below that point.
    In contrast, the coefficients from the two analyses using the
population stratified dual linear function with stratification at 7.5
[mu]g/dL and 10 [mu]g/dL,\77\ peak blood Pb, have not undergone as
careful development. These analyses were primarily done to compare the
lead-associated decrement at lower blood Pb concentrations and higher
blood Pb concentrations. For these analyses, the study population was
stratified at the specified peak blood Pb level and separate linear
models were fitted to the concurrent blood Pb data for the children in
the two study population subgroups.\78\ While these analyses are quite
suitable for the purpose of investigating whether the slope at lower
concentration levels is greater compared to higher concentration
levels, use of such coefficients as the primary C-R function in a risk
analysis such as this may be inappropriate. Further, only 103 children
had maximal blood Pb levels less than 7.5 [mu]g/dL and 244 children had
maximal blood Pb levels less than 10 [mu]g/dL. While these children may
better represent current blood Pb levels, not fitting a single model
using all available data may lead to bias. Slob et al. (2005) noted
that the usual argument for not considering data from the high dose
range is that different biological mechanisms may play a role at higher
doses compared to lower doses. However, this does not mean a single
curve across the entire exposure range cannot describe the
relationship. The fitted curve merely assumes that the underlying dose-
response follows a smooth curve over the whole dose range. If
biological mechanisms change when going from lower to higher doses,
this change will result in a gradually changing slope of the dose-
response. The major strength of the Lanphear et al. (2005) study was
the large sample size and the pooled analysis of data from seven
different cohorts. In the case of the study population subgroup with
peak blood Pb below 7.5 [mu]g/dL, less than 10% of the available data
is used in the analysis (103 of the 1333 subjects in the pooled
dataset), with more than half of the data coming from one cohort
(Rochester) and the six other cohorts contributing zero to 13 children
to the analysis. Such an analysis consequently does not make full use
of the strength of the pooled study by Lanphear and others (2005).
---------------------------------------------------------------------------

    \77\ See previous footnote.
    \78\ Neither fit of the model nor other sensitivity analyses
were conducted (or reported) for these coefficients.
---------------------------------------------------------------------------

    In consideration of the preceding discussion and the range of blood
Pb levels assessed in this analysis,\79\ greater confidence is placed
in the log-linear model form compared to the dual-linear stratified
models for purposes of the risk assessment described in this notice.
Further, in considering risk estimates derived from the four core
functions (log-linear function with low-exposure linearization, log-
linear function with cutpoint, dual linear function, stratified at 7.5
[mu]g/dL peak blood Pb, and dual linear function, stratified at 10
[mu]g/dL peak blood Pb), greatest confidence is assigned to risk
estimates derived using the log-linear function with low-exposure
linearization since this function (a) is a nonlinear function that
describes greater response per unit blood Pb at lower blood Pb levels
consistent with multiple studies identified in the discussion above,
(b) is based on fitting a function to the entire pooled dataset (and
hence uses all of the data in describing response across the range of
exposures), (c) is supported by sensitivity analyses showing the model
coefficients to be robust, and (d) provides an approach for predicting
IQ loss at the lowest exposures simulated in the assessment (consistent
with the lack of evidence for a threshold). Note, however, that risk
estimates generated using the other three concentration-response
functions are also presented to provide perspective on the impact of
uncertainty in this key modeling step. We additionally note that the
CASAC Pb Panel recommended that C-R function derived from the pooled
dataset stratified at 7.5 [mu]g/dL, peak blood Pb, be given weight in
this analysis (Henderson, 2008).
---------------------------------------------------------------------------

    \79\ The median concurrent values in all case studies and air
quality scenarios are below 5 [mu]g/dL and those for air quality
scenarios within the range of standard levels proposed in this
notice are below 3 [mu]g/dL (as shown in Table 1).
---------------------------------------------------------------------------

c. Case Study Approach
    For the risk assessment described in this notice, a case study
approach was employed as described in Sections 2.2 (and subsections)
and 5.1.3 of the Risk Assessment Report (USEPA, 2007b). In summarizing
the assessment in this proposal, we have focused on five \80\ case
studies that generally represent two types of population exposures: (1)
More highly air-pathway exposed children (as described below) residing
in small neighborhoods or localized residential areas with air
concentrations somewhat near the standard level being evaluated, and
(2) urban populations with a broader range of air-related exposures.
These five case studies are:
---------------------------------------------------------------------------

    \80\ A sixth case study (the secondary Pb smelter case study) is
also described in the Risk Assessment Report. However, as discussed
in Section 4.3.1 of that document (USEPA, 2007b), significant
limitations in the approaches employed for this case study have
contributed to large uncertainties in the corresponding estimates.
---------------------------------------------------------------------------

     A general urban case study: This case study is not based
on a specific geographic location and reflects several simplifying
assumptions used in representing exposure including uniform ambient air
Pb levels associated with the standard of interest across the
hypothetical study area and a uniform study population. This case study
characterizes risk for a localized part of an urban area at different
standard levels, but based on national average estimates of the
relationships between the different standard form assessed and ambient
air exposure concentrations. Thus, while this provides characterization
of risk to children that are relatively more highly air pathway exposed
(as compared to the location-specific case studies), this case study is
not considered to represent a high-end scenario with regard to the
characterization of ambient air Pb levels and associated risk.\81\
---------------------------------------------------------------------------

    \81\ In representing the different forms of each standard level
assessed (maximum monthly or maximum quarterly) as annual air
concentrations for input to the blood Pb model for this case study,
however, we relied on averages of these relationships for large
urban areas nationally. As the averages are higher than the medians,
localized areas near more than half the urban monitoring locations
would have higher exposures and associated risks than those reported
for this case study. Further, we note that exposure concentrations
would be twice those used here if the 25th percentile values for
these relationships had been used in place of the averages. For this
reason, this case study should not be interpreted as representing a
high-end scenario with regard to the characterization of ambient air
Pb levels and associated risk.
---------------------------------------------------------------------------

     A primary Pb smelter case study: \82\ This case study
estimates risk for children living in an area currently not in
attainment with the current NAAQS that is impacted by Pb emissions from
a primary Pb smelter. Results described

here are those for the area within 1.5 km of the facility (the
``subarea'') where airborne Pb concentrations are closest to the
current standard. As such, this case study characterizes risk for a
specific more highly exposed population and also provides insights on
risk to child populations living in areas near large sources of Pb
emissions.\83\
---------------------------------------------------------------------------

    \82\ See Section II.C.2.a for a summary of CASAC's comment with
regard to the primary and secondary Pb smelter case studies.
    \83\ Result for the full study area, which extends 10 km out
from the facility, are presented in the Risk Assessment Report
(USEPA, 2007a), but are not presented here. Exposures in the full
study area were dominated by modeled children farther from the
facility where, as discussed in the ANPR (section III.B.2.h), there
is likely underestimation of ambient air-related Pb exposure due to
increasing influence of other sources relative to that of the
facility, which were not included in the dispersion modeling
performed to estimate air concentrations for this case study.
---------------------------------------------------------------------------

     Three location-specific urban case studies: These urban
case studies focus on specific urban areas (Cleveland, Chicago and Los
Angeles) to provide representations of the distribution of ambient air-
related risk in specific densely populated urban locations. These case
studies represent areas with specific population distributions and that
experience a broader range of air-related exposures due both to
potential spatial gradients in ambient air Pb levels and population
density. A large majority of the population in these case studies
resides in areas with much lower air concentrations than those in the
very small subareas of these case studies with the highest
concentrations. Ambient air Pb concentrations are characterized using
source-oriented and other Pb-TSP monitors in these cities, while
location-specific U.S. Census demographic data are used to characterize
the spatial distribution of residential child populations in these
study areas.
    These different case studies generally represent two types of
population exposures. The general urban and primary Pb smelter subarea
provide estimates of risk for more highly air-pathway exposed children
residing in small neighborhoods or localized residential areas with air
concentrations somewhat near the standard level being evaluated. By
contrast, the three location-specific urban case studies included in
the analysis provide risk estimates for an urban population with a
broader range of air-related exposures. In fact, for the location-
specific urban case studies, the majority of the modeled populations
experience ambient air Pb levels significantly lower than the standard
level being evaluated, with only a small population experiencing
ambient air Pb levels at or near the standard.\84\
---------------------------------------------------------------------------

    \84\ Based on the nature of the population exposures represented
by the two categories of case study, the first category (the general
urban and primary Pb smelter case studies) relates more closely to
the second evidence-based framework (see Sections II.D.2.a and
II.E.3.a) with regard to estimates of air-related IQ loss. As
mentioned above these case studies, as compared to the other
category of case studies, include populations that are relatively
more highly air pathway exposed to air Pb concentrations somewhat
near the standard level evaluated.
---------------------------------------------------------------------------

    In considering risk results generated for the location-specific
urban case studies, we note that, given the wide range of monitored Pb
levels in urban areas, combined with the relatively limited monitoring
network characterizing ambient levels in the urban setting, it is not
possible to determine where these case studies fall within the
distribution of ambient air-related risk in U.S. cities.
d. Air Quality Scenarios
    Air quality scenarios assessed include (a) a current conditions
scenario for the location-specific urban case studies and the general
urban case study, (b) a current NAAQS scenario for the location-
specific urban case studies, the general urban case study and the
primary Pb smelter case study, and (c) a range of alternative NAAQS
scenarios for all case studies. The alternative NAAQS scenarios include
levels of 0.5, 0.2, 0.05, and 0.02 [mu]g/m\3\, with a monthly averaging
time, as well as a level of 0.2 [mu]g/m\3\ scenario using a quarterly
averaging time.\85\
---------------------------------------------------------------------------

    \85\ For further discussion of the air quality scenarios and
averaging times included in the risk assessment, see section 2.3.1
of the Risk Assessment Report (USEPA, 2007b).
---------------------------------------------------------------------------

    The current NAAQS scenario for the urban case studies assumes
ambient air Pb concentrations higher than those currently occurring in
nearly all urban areas nationally.\86\ While it is extremely unlikely
that Pb concentrations in urban areas would rise to meet the current
NAAQS and there are limitations and uncertainties associated with the
roll-up procedure used for the location-specific urban case studies (as
described in Section III.B.2.h below), this scenario was included for
those case studies to provide perspective on potential risks associated
with raising levels to the point that the highest level across the
study area just meets the current NAAQS. When evaluating these results
it is important to keep these limitations and uncertainties in mind.
---------------------------------------------------------------------------

    \86\ This scenario was simulated for the location-specific urban
case studies using a proportional roll-up procedure. For the general
urban case study, the maximum quarterly average ambient air
concentration was set equal to the current NAAQS.
---------------------------------------------------------------------------

    Current conditions for the three location-specific urban case
studies in terms of maximum quarterly average air Pb concentrations are
0.09, 0.14 and 0.36 [mu]g/m\3\ for the study areas in Los Angeles,
Chicago and Cleveland, respectively. In terms of maximum monthly
average the values are 0.17 [mu]g/m\3\, 0.31 [mu]g/m\3\ and 0.56 [mu]g/
m\3\ for the study areas in Los Angeles, Chicago and Cleveland,
respectively.
    Details of the assessment scenarios, including a description of the
derivation of Pb concentrations for air and other media are presented
in Sections 2.3 (and subsections) and Section 5.1.1 of the Risk
Assessment Report (USEPA, 2007b).
e. Categorization of Policy-Relevant Exposure Pathways
    As discussed in Section IIA, this review focuses on air-related
exposure pathways (i.e., those pathways where Pb passes through ambient
air on its path from source to human exposure). These include both
inhalation of ambient air Pb (including both Pb emitted directly into
ambient air as well as resuspended Pb); and ingestion of Pb that, once
airborne, has made its way into indoor dust, outdoor dust or soil,
dietary items (e.g., crops and livestock), and drinking water. Because
of the nonlinear response of blood Pb to exposure (simulated in the
IEUBK blood Pb model) and also the nonlinearity reflected in the C-R
functions for estimation of IQ loss, this assessment first estimates
total blood Pb and risk (air- and nonair-related), and then separates
out those estimates of blood Pb and associated risk associated with the
pathways of interest in this review.
    To separate out risk for the pathways of interest in this review,
we split the estimates of total (all-pathway) blood Pb and IQ loss into
background and two air-related categories (referred to as ``recent
air'' and ``past air''). However, significant limitations in our
modeling tools and data resulted in an inability to parse specific risk
estimates into specific pathways, such that we have approximated
estimates for the air-related and background categories.
    Those Pb exposure pathways identified in section II.A.2 as being
tied most directly to ambient air, which consequently have the
potential to respond relatively more quickly to changes in air Pb
(inhalation and ingestion of indoor dust loaded directly from ambient
air Pb) were placed into the ``recent air'' category. The other air-
related Pb exposure pathways, associated with atmospheric deposition,
were placed into the ``past air'' category. These include ingestion of
Pb in

outdoor dust/soil and ingestion of the portion of Pb in indoor dust
that after deposition from ambient air outdoors is carried indoors with
humans (as described in section II.A.2 above).\87\
---------------------------------------------------------------------------

    \87\ As discussed below, due to technical limitations related to
indoor dust Pb modeling, dust from Pb paint may be included to some
extent in the ``past air'' category of exposure pathways.
---------------------------------------------------------------------------

    Thus, total blood Pb and IQ loss estimates were apportioned into
the following pathways or pathway combinations:
     Inhalation of ambient air Pb (i.e., ``recent air'' Pb):
This is derived using the blood Pb estimate resulting from Pb exposure
limited to the inhalation pathway (and includes inhalation of Pb in
ambient air from all sources contributing to the ambient air
concentration estimate, including potentially resuspension).
     Ingestion of ``recent air'' indoor dust Pb: This is
derived using the blood Pb estimate resulting from Pb exposure limited
to ingestion of the Pb in indoor dust that is predicted in this
assessment from infiltration of ambient air indoors and subsequent
deposition.\88\
---------------------------------------------------------------------------

    \88\ Recent air indoor dust Pb was estimated using the
mechanistic component of the hybrid blood Pb model (see Section
3.1.4 of the Risk Assessment Report). For the primary Pb smelter
case study, estimates for this pathway are not separated from
estimates for the pathway described in the subsequent bullet due to
uncertainty regarding this categorization with the model used for
this case study (Section <IP_ADDRESS> of the Risk Assessment Report).
---------------------------------------------------------------------------

     Ingestion of ``other'' indoor dust Pb (considered part of
``past air'' exposure): This is derived using the blood Pb estimate
resulting from Pb exposure limited to ingestion of the Pb in indoor
dust that is not predicted from infiltration of ambient air indoors and
subsequent deposition.\89\ This is interpreted to represent indoor
paint, outdoor soil/dust, and additional sources of Pb to indoor dust
including historical air (as discussed in the Risk Assessment Report,
Section 2.4.3). As the intercept in regression dust models will be
inclusive of error associated with the model coefficients, this
category also includes some representation of dust Pb associated with
current ambient air concentrations (described in previous bullet). For
the primary Pb smelter case study, estimates for this pathway are not
separated from estimates for the pathway described above due to
uncertainty regarding this categorization with the model used for this
case study (Risk Assessment Report, Section <IP_ADDRESS>). This pathway is
included in the ``past air'' category.
---------------------------------------------------------------------------

    \89\ ``Other'' indoor dust Pb is estimated using the intercept
in the dust models plus that predicted by the outdoor soil
concentration coefficient (for models that include soil Pb as a
predictor of indoor dust Pb) (Section 3.1.4 of the Risk Assessment
Report).
---------------------------------------------------------------------------

     Ingestion of outdoor soil/dust Pb: This is derived using
the blood Pb estimate resulting from Pb exposure limited to ingestion
of outdoor soil/dust Pb. This pathway is included in the ``past air''
category (and could include contamination from historic Pb emissions
from automobiles and Pb paint).
     Ingestion of drinking water Pb: This is derived using the
blood Pb estimate resulting from Pb exposure limited to ingestion of
drinking water Pb. This pathway is included in the policy-relevant
background category.
     Ingestion of dietary Pb: This is derived using the blood
Pb estimate resulting from Pb exposure limited to ingestion of dietary
Pb. This pathway is included in the policy-relevant background
category.
    As noted above, significant limitations in our modeling tools and
data resulted in an inability to parse risk estimates for specific
pathways, such that we approximated estimates for the air-related and
background categories. Of note in this regard is the apportionment of
background (nonair) pathways. For example, while conceptually indoor Pb
paint contributions to indoor dust Pb would be considered background
and included in the ``background'' category for this assessment, due to
technical limitations related to indoor dust Pb modeling, ultimately,
dust from Pb paint was included as part of ``other'' indoor dust Pb
(i.e., as part of past air exposure). The inclusion of indoor lead Pb
as a component of ``other'' indoor air (and consequently as a component
of the ``past air'' category) represents a source of potential high
bias in our prediction of exposure and risk associated with the ``past
air'' category because conceptually, exposure to indoor paint Pb is
considered part of background exposure. Further, Pb in ambient air does
contribute to the exposure pathways included in the ``background''
category (drinking water and diet), and is likely a substantial
contribution to diet (CD, p. 3-48). But we could not separate the air
contribution from the nonair contributions, and the total contribution
from both the drinking water and diet pathways are categorized as
``background'' in this assessment. As a result, our ``background'' risk
estimate includes some air-related risk.
    Further, we note that in simulating reductions in exposure
associated with reducing ambient air Pb levels through alternative
NAAQS (and increases in exposure if the current NAAQS was reached in
certain case studies) only the exposure pathways categorized as
``recent air'' (inhalation and ingestion of that portion of indoor dust
associated with outdoor ambient air) were varied with changes in air
concentration. The assessment did not simulate decreases in ``past
air'' exposure pathways (e.g., reductions in outdoor soil Pb levels
following reduction in ambient air Pb levels and a subsequent decrease
in exposure through incidental soil ingestion and the contribution of
outdoor soil to indoor dust). These exposures were held constant across
all air quality scenarios. In comparing total risk estimates between
alternate NAAQS scenarios, this aspect of the analysis will tend to
underestimate the reductions in risk associated with alternative NAAQS.
However, this does not mean that overall risk has been underestimated.
The net effect of all sources of uncertainty or bias in the analysis,
which may also tend to under- or overestimate risk, could not be
quantified. Interpretation of risk estimates is discussed more fully in
section II.C.3.b.
    In summary, because of limitations in the assessment design, data
and modeling tools, our risk estimates for the ``past air'' category
include both risks that are truly air-related and potentially, some
background risk. Because we could not sharply separate Pb linked to
ambient air from Pb that is background, some of the three categories of
risk are underestimated and others overestimated. On balance, we
believe this limitation leads to a slight overestimate of the risks in
the ``past air'' category. At the same time, as discussed above, the
``recent air'' category does not fully represent the risk associated
with all air-related pathways. Thus, we consider the risk attributable
to air-related exposure pathways to be bounded on the low end by the
risk estimated for the ``recent air'' category and on the upper end by
the risk estimated for the ``recent air'' plus ``past air'' categories.
f. Analytical Steps
    The risk assessment includes four analytical steps, briefly
described below and presented in detail in Sections 2.4.4, 3.1, 3.2,
4.1, and 5.1 of the Risk Assessment Report (USEPA, 2007b).
     Characterization of Pb in ambient air: The
characterization of outdoor ambient air Pb levels uses different
approaches depending on the case study (as explained in more detail
below): (a) source-oriented and non-source oriented monitors are
assumed to represent different exposure zones in the city-specific case
studies, (b) a single exposure level is assumed for the entire

population in the general urban case study, and (c) ambient levels are
estimated using air dispersion modeling based on Pb emissions from a
particular facility in the primary Pb smelter case study.
     Characterization of outdoor soil/dust and indoor dust Pb
concentrations: Outdoor soil Pb levels are estimated using empirical
data and fate and transport modeling. Indoor dust Pb levels are
predicted using a combination of (a) regression-based models that
relate indoor dust to ambient air Pb and outdoor soil Pb, and (b)
mechanistic models.\90\
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    \90\ Indoor dust Pb modeling for the urban case studies is based
on a hybrid mechanistic-empirical model which considers the direct
impact of Pb in ambient air on indoor dust Pb (i.e., which models
the infiltration of ambient air indoors and subsequent deposition of
Pb to indoor surfaces). This modeling does not consider other
ambient air-related contributions to indoor dust, such as ``tracking
in'' of outdoor soil Pb. By contrast, indoor dust Pb modeling for
the primary Pb smelter case study subarea uses a site-specific
regression model which relates average dust Pb values (based on a
recent multi-year dataset) to annual average air Pb concentrations
(based on air dispersion modeling). In this way, modeling for the
primary Pb smelter subarea may reflect some contributions to indoor
dust Pb that relate to longer term impacts of ambient air (e.g.,
``tracking in'' of outdoor soil), as well as contributions from
infiltration of ambient air. Additional detail on the methods used
in characterizing Pb concentrations in outdoor soil and indoor dust
are presented in Sections 3.1.3 and 3.1.4 of the Risk Assessment,
respectively. Data, methods and assumptions here used in
characterizing Pb concentrations in these exposure media may differ
from those in other analyses that serve different purposes.
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     Characterization of blood Pb levels: Blood Pb levels for
each exposure zone are derived from central-tendency blood Pb
concentrations estimated using the Integrated Exposure and Uptake
Biokinetic (IEUBK) model, and concurrent or lifetime average blood Pb
is estimated from these outputs as described in Section <IP_ADDRESS> of the
Risk Assessment Report (USEPA, 2007b). For the point source and
location-specific urban case studies, a probabilistic exposure model is
used to generate population distributions of blood Pb concentrations
based on: (a) The central tendency blood Pb levels for each exposure
zone, (b) demographic data for the distribution of children (less than
7 years of age) across exposure zones in a study area, and (c) a
geometric standard deviation (GSD) intended to characterize
interindividual variability in blood Pb (e.g., reflecting differences
in behavior and biokinetics related to Pb). For the general urban case
study, as demographic data for a specific location are not considered,
the GSD is applied directly to the central tendency blood Pb level to
estimate a population distribution of blood Pb levels. Additional
detail on the methods used to model population blood Pb levels is
presented in Sections 3.2.2 and <IP_ADDRESS> of the Risk Assessment Report
(USEPA, 2007b).
     Risk characterization (estimating IQ loss): Concurrent or
lifetime average blood Pb estimates for each simulated child in each
case study population are converted into total Pb-related IQ loss
estimates using the concentration-response functions described above in
section II.C.2.b.\91\
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    \91\ The four C-R functions applied in the risk assessment,
which are based on analyses presented in Lanphear et al. (2005)
include a log-linear function with low-exposure linearization, a
log-linear function with a cutpoint, and two dual linear functions
(based on population stratification at peak blood Pb levels of 7.5
and 10 [mu]g/dL) (see section II.C.2.b).
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    We have also used the results of exposure modeling to estimate air-
to-blood ratios for two of the case studies (the general urban and
primary Pb smelter case studies). Specifically, we compared the change
in ambient air Pb between adjacent NAAQS levels with the associated
reduction in concurrent blood Pb levels (for the median population
percentile) to derive air-to-blood ratios. As they relate air
concentrations \92\ input to the first analytical step to blood Pb
estimates output from the third analytical step, they may be viewed as
a collapsed alternate to the three steps for the exposure pathways
directly linked to air concentrations in this assessment. The values
for these ratios are affected by design aspects of the risk assessment,
most notably those identified here:
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    \92\ Because the IEUBK blood Pb model runs with an annual time
step, the air concentrations input to the ``recent air'' pathways
modeling steps were in terms of annual average air concentration.
---------------------------------------------------------------------------

     Because they are derived from differences in blood Pb
estimates between air quality scenarios and the only pathways varied
with air quality scenarios are ambient air and indoor dust (as
described in section II.C.2.e above), the exposure pathways reflected
in the ratios are generally the ``recent air'' pathways (described in
section II.C.2.e above), which include inhalation of ambient air and
ingestion of indoor dust loaded by infiltration of ambient air. Ratios
for the primary Pb smelter case study subarea may additionally reflect
some contributions to indoor dust from other ambient air-related
pathways (e.g., ``tracking in'' of soil containing ambient air Pb), yet
still not all air-related pathways. Thus, the air-to-blood ratios
derived for both case studies (described in section II.C.3.a) are lower
than they would be if they reflected all air-related pathways.
     The blood Pb estimates used in this calculation are for
the ``concurrent'' metric (i.e., concentrations during the 7th year of
life). Accordingly, the resultant air-to-blood ratios are lower than
they would be if based on blood Pb estimates for the 2nd year of life
(e.g., peak) or estimates averaged over the exposure period.
    Key limitations and uncertainties associated with the application
of these specific analytical steps are summarized in Section III.B.2.k
below.
g. Generating Multiple Sets of Risk Results
    In the initial analyses for the full-scale assessment (USEPA,
2007a), EPA implemented multiple modeling approaches for each case
study scenario in an effort to characterize the potential impact on
exposure and risk estimates of uncertainty associated with the
limitations in the tools, data and methods available for this risk
assessment and with key analytical steps in the modeling approach.
These multiple modeling approaches are described in Section <IP_ADDRESS> of
the final Risk Assessment Report (USEPA, 2007b). In consideration of
comments provided by CASAC (Henderson, 2007b) on these analyses
regarding which modeling approach they felt had greater scientific
support, a pared down set of modeling combinations was identified as
the core approach for the subsequent analyses. The core modeling
approach includes the following key elements:
     Ambient air Pb estimates (based on monitors or modeling
and proportional rollbacks, as described below),
     Background exposure from food and water (as described
above),
     The hybrid indoor dust model specifically developed for
urban residential applications (which predicts Pb in indoor dust as a
function of ambient air Pb and nonair contribution),
     The IEUBK blood Pb model (which predicts blood Pb in young
children exposed to Pb from multiple exposure pathways),
     The concurrent blood Pb metric,
     A GSD for concurrent blood Pb of 2.1 to characterize
interindividual variability in blood Pb levels for a given ambient
level for the urban case studies,\93\ and
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    \93\ In the economic analysis for the RRP rule, a GSD of 1.6 was
used in its probabilistic simulations, reflecting the fact that the
simulated exposures focus on a subset of Pb exposure pathways
(exposure to dust and airborne Pb resulting from renovation
activity) and a CASAC recommendation to use the IEUBK-recommended
GSD with the Leggett model, where no GSD is provided. In addition,
the accompanying sensitivity analysis used a GSD of 2.1 to consider
the impact on IQ change estiamtes of using a larger GSD, which would
reflect greater heterogeneity in the study population with regard to
Pb exposure and blood Pb response.

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     Four different functions relating concurrent blood Pb to
IQ loss (described in section II.C.2.b), including two log-linear
models (one with a cutpoint and one with low-exposure linearization)
and two dual-linear models with stratification, one stratified at 7.5
[mu]g/dL peak blood Pb and the other at 10 [mu]g/dL peak blood Pb.
    For each case study, the core modeling approach employs a single
set of modeling elements to estimate exposure and the four different
concentration-response functions referenced above to derive four sets
of risk results from the single set of exposure estimates. The spread
of estimates resulting from application of all four functions captures
much of the uncertainty associated model choice in this analytical
step. Among these four functions, EPA has greater confidence in
estimates derived using the log-linear with low-exposure linearization
concentration-response function as discussed above.
    In addition to employing multiple concentration-response functions,
the assessment includes various sensitivity analyses to characterize
the potential impact of uncertainty in other key analysis steps on
exposure and risk estimates. The sensitivity analyses and uncertainty
characterization completed for the risk analysis are described in
Sections 3.5, 4.3, 5.2.5 and 5.3.3 of the Risk Assessment Report
(USEPA, 2007b).
h. Key Limitations and Uncertainties
    As recognized above, EPA has made simplifying assumptions in
several areas of this assessment due to the limited data, models, and
time available. These assumptions and related limitations and
uncertainties are described in the Risk Assessment Report (USEPA,
2007b). Key assumptions, limitations and uncertainties are briefly
identified below, with emphasis on those sources of uncertainty
considered most critical in interpreting risk results. In the
presentation below, limitations (and associated uncertainty) are
listed, beginning with those regarding design of the assessment or case
studies, followed by those regarding estimation of Pb concentrations in
ambient air indoor dust, outdoor soil/dust, and blood, and lastly
regarding estimation of Pb-related IQ loss.
     Temporal aspects: Exposure modeling uses a 7 year exposure
period for each simulated child, during which time, media
concentrations remain fixed (at levels associated with the ambient air
Pb level being modeled) and the child remains at the same residence,
while exposure factors and physiological parameters are adjusted to
match the age of the child. These aspects are a simplification of
population exposures that contributes some uncertainty to our exposure
and risk estimates.
     General urban case study: As described in section
II.C.2.c, this case study is not based on a specific location and is
instead intended to represent a smaller neighborhood experiencing
ambient air Pb levels at or near the standard of interest.
Consequently, it assumes (a) a single exposure zone within which all
media concentrations of Pb are assumed to be spatially uniform and (b)
a uniformly distributed population of unspecified size. While these
assumptions are reasonable in the context of evaluating risk for a
smaller subpopulation located close to a monitor reporting values at or
near the standard of interest, there is significant uncertainty
associated with extrapolating these risks to a specific urban location,
particularly if that urban location is relatively large, given that
larger urban areas are expected to have increasingly varied patterns of
ambient air Pb levels and population density. The risk estimates for
this general urban case study, while generally representative of an
urban residential population exposed to the specified ambient air Pb
levels, cannot be readily related to a specific large urban population.
     Location-specific urban case studies: The Pb-TSP
monitoring network is currently quite limited and consequently, the
number of monitors available to represent air concentrations in these
case studies is limited, ranged from six for Cleveland to 11 for
Chicago. Accordingly, our estimates of the magnitude of and spatial
variation of air Pb concentrations are subject to uncertainty
associated with the limited monitoring data and method used in
extrapolating from those data to characterize an ambient air Pb level
surface for these modeled urban areas. Details on the approach used to
derive ambient air Pb surfaces for the urban case studies based on
monitoring data are presented in Section 5.1.3 of the Risk Assessment
Report (USEPA, 2007b). As recognized in Section, III.B.2.a, the
analyses for these case studies were developed in response to CASAC
recommendations on the July 2007 draft Risk Assessment (Henderson,
2007b). Subsequently, the CASAC has reviewed the approach used in
conducting the final draft of the full-scale risk assessment, including
the inclusion of the location-specific urban case studies and expressed
broad support for the technical approach used (Henderson, 2008).
     Current NAAQS air quality scenarios: For the location-
specific urban case studies, proportional roll-up procedures were used
to adjust ambient air Pb concentrations up to just meet the current
NAAQS (a detailed discussion is provided in Sections 2.3.1 and <IP_ADDRESS>
of the Risk Assessment Report, USEPA, 2007b). This procedure was used
to provide insights into the degree of risk which could be associated
with ambient air Pb levels at or near the current standard in urban
areas. EPA recognizes that it is extremely unlikely that Pb
concentrations would rise to just meet the current NAAQS in urban areas
nationwide and that there is substantial uncertainty with our
simulation of such conditions. For the primary Pb smelter case study,
where current conditions exceed the current NAAQS, attainment of the
current NAAQS was simulated using air quality modeling, emissions and
source parameters used in developing the 2007 proposed revision to the
State Implementation Plan for the area (described in Section <IP_ADDRESS> of
the Risk Assessment Report (USEPA, 2007b)).
     Alternative NAAQS air quality scenarios: In all case
studies, proportional roll-down procedures were used to adjust ambient
air Pb concentrations downward to attain alternative NAAQS (described
in Sections 2.3.1 and <IP_ADDRESS> of the Risk Assessment Report, USEPA,
2007b). There is significant uncertainty in simulating conditions
associated with the implementation of emissions reduction actions to
meet a lower standard.
     Estimates of outdoor soil/dust Pb concentrations: Outdoor
soil Pb concentration for both the urban case studies and the primary
Pb smelter case study are based on empirical data (as described in
Section 3.1.3 of the Risk Assessment). To the extent that these data
are from areas containing older structures, the impact of Pb paint
weathered from older structures on soil Pb levels will be reflected in
these empirical estimates. In the case of the urban case studies, a
mean value from a sample of houses built between 1940 and 1998 was used
to represent soil Pb levels (as described in Section <IP_ADDRESS> of the
Risk Assessment). In the case of the primary Pb smelter case study
subarea, site-specific data are used. As there has been remediation of
soil in this subarea, the measurements do not reflect historical air
quality. Additionally,

studies since remediation have reported increasing soil Pb levels
indicating that soil concentrations are still responding to current air
quality, and consequently underestimate eventual steady state
conditions for the current air quality. In all case studies, the same
outdoor soil/dust Pb concentrations (based on these datasets) are used
for all air quality scenarios (i.e., the potential longer-term impact
of reductions in ambient air Pb on outdoor soil/dust Pb levels and
associated impacts on indoor dust Pb have not be simulated). In areas
where air concentrations have been greater in the past, however,
implementation of a reduced NAAQS might be expected to yield reduced
soil Pb levels over the long term. As described in Section 2.3.3 of the
Risk Assessment Report (USEPA, 2007b), however, there is potentially
significant uncertainty associated with this conclusion, particularly
with regard to implications for areas in which a Pb source may locate
where one of comparable size had not been previously. Additionally, it
is possible that control measures implemented to meet alternative NAAQS
may result in changes to soil Pb concentrations; these are not
reflected in the assessment.
     Estimates of indoor dust Pb concentrations for the urban
case studies (application of the hybrid model): The hybrid mechanistic-
empirical model for estimating indoor dust Pb for the urban case
studies (as described in Section <IP_ADDRESS> of the Risk Assessment Report,
USEPA, 2007b) utilizes a mechanistic model to simulate the exchange of
outdoor ambient air Pb indoors and subsequent deposition (and buildup)
of Pb on indoor surfaces, which relies on a number of empirical
measurements for parameterization (e.g., infiltration rates, deposition
velocities, cleaning frequencies and efficiencies). There is
considerable uncertainty associated with these parameter estimates. In
addition, there is uncertainty associated with the partitioning of
total indoor dust Pb estimates between the infiltration-related
(``recent air'') component and other contributions (``other'' as
described in section II.C.2.e).
     Estimates of indoor dust Pb concentrations for the primary
Pb smelter case study (application of the site-specific regression
model): There is uncertainty associated with the site-specific
regression model applied in the remediation zone (as described in
Section <IP_ADDRESS> of the Risk Assessment Report), and relatively greater
uncertainty associated with its application to air quality scenarios
that simulate notably lower air Pb levels (as is typically the case
when applying regression-based models beyond the bounds of the datasets
used in their derivation). The log-log form of the regression model
prevents the ready identification of an intercept term handicapping us
in partitioning estimates of air-related indoor dust (and consequently
exposure and risk estimates) between ``recent air'' and ``other''
components. In addition, limitations in the model-derived air estimates
used in deriving the regression model prevented effective consideration
for the role of ambient air Pb related to resuspension in influencing
indoor dust Pb levels. A public commenter suggested that indoor dust Pb
levels using this model may be overestimated due to factors associated
with the model's derivation. Factors identified by the commenter,
however, may contribute to a potential for either over- or
underestimation, and as noted by the commenter, additional research
might reduce this uncertainty.
     Characterizing interindividual variability using a GSD:
There is uncertainty associated with the GSD specified for each case
study (as described in Sections 3.2.3 and <IP_ADDRESS> of the Risk