Environmental Health Criteria 214

HUMAN EXPOSURE ASSESSMENT
of samples to be obtained should be based on these considerations.
8.3.1 Concentration and loading
Almost all settled dust contains measurable levels of common
environmental contaminants such as heavy metals and pesticides, and
most residential surfaces, such as floors and windowsills, contain
settled dust (CDC, 1991). The actual concentration of a target analyte
in a sample of settled dust depends on the amount of dust collected
that does not contain the analyte and the amount of dust collected
that does contain the analyte.
The analyte concentration, sometimes called a mass
concentration, is usually expressed as micrograms of analyte per
gram of dust (µg/g). The amount of dust on a surface can be expressed
as grams of dust per unit area, such as per square metre, and is
usually called dust loading (g/m 2 ). The analyte concentration,
multiplied by the dust loading on a surface, gives a analyte
loading value and is commonly expressed as micrograms of analyte per
unit area (µg/m 2 ). The dust loading and analyte loading measurements
are both area concentrations, that is, the concentration of dust or
contaminant per unit area. In this report, "concentration" refers to
mass concentration and "loading" refers to area concentration.
The example of residential sampling for lead is used to simplify
the discussion. Common wipe sampling methods, such as the HUD method,
measure lead loading directly, without measuring lead concentration
and dust loading. Fig. 24 illustrates what common wipe samples can
measure, using realistic results collected from floors in a
hypothetical residence. Assume that each diagonal line in the figure
represents the lead loading results from one wipe sample. The diagonal
lead loading lines show the infinite number of lead concentration
( y axis) and dust loading ( x axis) combinations that might result
in the measured lead loading. As mentioned earlier, the product of the
two parameters is the lead loading (µg/g × g/m 2 = µg/m 2 ). Using a
log scale on the x and y axes ensures that the infinite number of
combinations that result in the same lead loading value fall on a
straight line. As noted in Chapter 4, the distribution of many
measures of environmental exposure is skewed right and may often be
approximated by a lognormal distribution. For lognormal distributions,
geometric relationships (e.g., factorial) exist among quantiles of the
distribution, in contrast to the linear relationships present in
measures that follow a normal distribution. As described in Chapter 4,
lognormal distributions can be "normalized" in a numerical sense by
expressing the data as the log-transformed values or in a graphical
sense by plotting data on log scales. This example assumes that lead
concentration and dust loading are lognormally distributed and
perfectly correlated with each other, i.e., lead loading in µg
lead/m 2 is assumed to be constant. A scatter plot of two perfectly
correlated and lognormally distributed measures depicted on a normal
scale would exhibit a curved relationship, but appears as a straight
line when depicted on a log scale.
Because common wipe sampling measures lead loading directly, but
does not measure lead concentration and dust loading, the results from
wipe sampling cannot be used to determine which combination of lead
concentration and dust loading is present. Similarly, Davies et al.
(1990) states that for a given contaminant loading value, the
contaminant concentration can range from high where there is little
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