Environmental Engineering Reference
In-Depth Information
Table 7.6
Contingency table for assessing impacts of contaminated sediments on aquatic life based on three separate indicators of
sediment quality.
Possible
outcome
Sediment
chemistry
Toxicity
test
Benthic
community
Possible conclusions
1
+
+
+
Impact highly likely: contaminant-induced degradation of
sediment-dwelling organisms evident.
2
−
−
−
Impact highly unlikely: contaminant-induced degradation
of sediment dwelling organisms not evident.
3
+
−
−
Impact unlikely: contaminants unavailable to sediment-
dwelling organisms.
4
−
+
−
Impacts possible: unmeasured contaminants or conditions
exist that have the potential to cause degradation.
5
−
−
+
Impacts unlikely: no degradation of sediment-dwelling
organisms in the fi eld apparent relative to sediment
contamination; physical factors may be infl uencing
benthic community.
6
+
+
−
Impact likely: toxic chemicals probably stressing the system.
7
−
+
+
Impact likely: unmeasured toxic chemicals are probably
contributing to the toxicity.
8
+
−
+
Impact likely: sediment-dwelling organisms degraded by
toxic chemicals, but toxicity tests not sensitive to
chemicals present.
+, Indicator classifi ed as affected; as determined based on comparison to the established target.
−
, Indicator not classifi ed as affected; as determined based on comparison to the established target.
Adapted from Chapman (1992) and Canfi eld
et al.
(1996).
of indicators and associated metrics. For example,
Fig. 7.4 illustrates the relation between sediment
chemistry (as a function of mean PEC quotients) and
sediment toxicity (as a function of toxicity to
H.
azteca
in 10-day sediment tests). Similarly, relations
between metrics for a particular indicator can also
be evaluated using scatter plots. Figure 7.8 illustrates
the relation between two metrics for sediment chem-
istry: SEM normalized to AVS (i.e., SEM-AVS) and
toxic units of metals measured in pore water from
these same samples. The results of these types of
analysis can be used to establish concordance among
various indicators (i.e., high chemistry and toxic, low
chemistry and not toxic). Additionally, these analyses
can help to establish the rate of false positives (i.e.,
high chemistry and not toxic) or false negatives (i.e.,
low chemistry and toxic) among various indicators.
An expanded version of the sediment-quality triad
approach has been developed to incorporate meas-
ures of bioaccumulation with the traditional meas-
ures of sediment quality (MacDonald 1998).
Specifi cally, integration of data from sediment chem-
10
3
Toxic to amphipods
Non-toxic to amphipods
10
2
10
1
10
0
10
-1
10
-2
10
-3
-160
-120
-80
-40
0
40
80
400 480
SEM-AVS (
μ
mole/g)
Fig. 7.8
Relation between the molar concentration of
simultaneously extracted metals to acid volatile sulfi de
(SEM-AVS) and toxic units of metals in the sediment samples.
Toxicity of samples was determined using 10-day whole-
sediment tests with
Hyalella azteca
.
From Ingersoll
et al.
(2002).
