INSTRUCTOR MANUAL
HEAVY METALS IN LAKE NAKURU
INTRODUCTION
OVERVIEW ON THE USE OF THIS MODULE
This module is designed to guide students through a consideration of the role of heavy metals in
the water, sediments and suspended solids of Lake Nakuru in the deaths of the flamingoes
residing in this region of the African Rift Valley. This module relies heavily on a report by Nelson
et al. of measurements of the heavy metals chromium, copper, lead and zinc in Lake Nakuru
samples. Through this module, students are introduced to the analytical methods anodic
stripping voltammetry (ASV), Atomic Spectroscopy, and x-ray fluorescence (XRF) and their
application to measurements of heavy metal concentrations in Lake Nakuru samples. These
materials are designed to be modular in their format and used relatively independently. We
envision that instructors could use the materials in their entirety as a unit on elemental analysis,
for example in an instrumental analysis course or select one or two of the units to use in the
class as active learning exercises. Alternatively, these materials could find use as a supplement
to laboratory experiences, as a prelab for existing experiments or a drylab where the relevant
instrumentation is not available. Curricular materials to support inquiry-based laboratory
experiences related to the elemental analysis of Lake Nakuru samples are currently under
development.
INTRODUCTION – Answers to questions
Q1. What is the likely route of exposure (i.e. eating, drinking, or some other means)?
The most likely exposure route for the flamingoes is through eating. Flamingos are filter feeders
and likely ingest suspended sediments and other particulates that contain heavy metals in the
process of filtering algae from the water.
Q2. Why do you think the authors emphasize the importance of particulate bound metals rather
than metal ions dissolved in the water? Is part of the rationale specific to flamingos? If so,
why? Are there other reasons?
There are several reasons why particulate bound metals are most important for this problem.
The first is related to Q1. Since one of the largest exposure routes for the flamingos is by
ingestion, particulate-bound metals are an important source of these contaminants. These
metals may be released from the particulate matter in the gut and become bioavailable. Another
reason that particulate bound metals may be important is that the solubility of the metal ions can
be limited in these alkaline waters due to precipitation of the hydroxide complex.
Q3. Why do you think that [F-] is included in this calculation, while [Cl-] is not?
Alkalinity is a measure of a water sample's buffering capacity. Remember that HCl is a strong
acid, and dissociates completely. Since HF is a weak acid, F- acts as the conjugate base and
contributes to the sample's alkalinity.
Q4. Using the data in Table 1 (Nelson, 1998), calculate the total alkalinity of Lake Nakuru, in
mg/L CaCO3.
AT = [HCO3-] + 2 x [CO32-] + [SO42-] + 2 x [PO43-] + [F-] + [NH3] + [OH-] - [H+]
Species
Bicarbonate
Carbonate x 2
Phosphate x 2
Fluoride
Sulfate
Hydroxide
mg/L1
3200
8200
27.2
129
62
g/L
3.2
8.2
0.0272
0.129
0.062
AT(Molar)
AT(mg/L CaCO3)
Eq/L
0.0525
0.1367
0.0003
0.0068
0.0006
0.0001
0.197 moles/L
19700 mg/L CaCO3
To calculate the total alkalinity using the equation for AT, it is simplest to think about the
equivalents of each weak base. The concentrations given by Nelson et al. can be converted to
equivalents/L and the total amounts of the equivalents summed. In Lake Nakuru the
concentrations of NH3 and H+ can be neglected but for other waters that may not be the case.
This means that the sample has a buffering capacity of 0.197 M. Often AT is expressed in terms
of the mg/L of CaCO3 because carbonate is the most abundant ion, although this is not the case
in Lake Nakuru.
Q5. Why could it be important to filter suspended particles or sediment from the water sample
before acidification?
Acidification could release particulate bound metals into the water sample and elevate the
concentrations measured.
Q6. Assume that you collect and filter a 1 liter water sample from Lake Nakuru. Using the total
alkalinity you calculated in Q4, would addition of 5 mL of 10% nitric acid reduce the pH of your
water sample to < 2? If not, how do you suggest that this protocol should be altered?
EPA Method 1669 recommends addition of 5 mL of 10% HNO3. Concentrated HNO3 is 15.8 M
so 10% HNO3 would be 1.58 M. This amount into 1 L gives a concentration of H+ of 0.0079 M,
which would not be sufficient to properly neutralize the alkalinity and lower the pH the Lake
Nakuru samples for storage. To neutralize the alkalinity, 0.197 moles of H+ would need to be
added, which would correspond to 125 mL of 10% HNO3. Since the water sample is so well
buffered, it would likely be wise to use a glass electrode to measure the pH following addition
HNO3 to reach pH 2.
Q7. Examine the results presented in Figure 1 of the paper by Nelson et al. Why do you think
that the experimental results deviate most from the line at low concentrations of the dissolved
metal?
Although the data in Figure 1 showing the adsorption of metals from solution are fit by the
authors using linear least squares regression, at lower concentrations there appears to be less
adsorption of chromium, copper and zinc; the points lie systematically below the line. In the
Methods section the authors describe taking a number of actions to overcome matrix effects in
their measurements. It is difficult to say with certainty why these values are lower than predicted
from the regression, but one possibility is suppression of atomization due to matrix effects.
Matrix effects are a common problem in AAS and GFAAS measurements and would be
expected to be more pronounced for solutions containing low concentrations of the analyte.
Q8. For adsorption to algae (Figure 2 of Nelson et al.) the adsorption behavior is not linear. The
authors suggest that the results for Cr, Cu and Zn are consistent with that of a Langmuir
isotherm (click here for a tutorial on the Langmuir isotherm).
In a simple solution equilibrium model, a metal ion binds with a ligand, for example EDTA, with a
defined stoichiometry and it is relatively simple to write the expression for the equilibrium
constant. The Langmuir isotherm describes strong binding of an adsorbate to a surface that has
a limited number of sites for adsorption. The interaction between the adsorbate and the surface
is specific meaning that only a monolayer of adsorbate molecules, or in this case metal ions, is
formed. The shape of the binding curve for this process is different from equilibria that occur in
a homogeneous solution because the available surface binding sites are saturated at high
adsorbate concentrations. The functional form of Langmuir adsorption equilibrium is
K ads 

C (1   )
where C is the solution concentration of the adsorbate and the surface coverage  defines the
fraction of the adsorption sites occupied. Therefore, the fraction of sites available for binding can
be represented as 1-. Once all the available binding sites are occupied, no additional
adsorption occurs and the binding sites are said to be saturated.
In Figure 2 of Nelson et al. the authors have plotted the amount of adsorbed metal ion vs its
solution concentration. If we let  be the amount of metal adsorbed in g/g and max represent
the maximum amount of adsorbed metal ion when all the surface sites have been saturated,
then  would be equal to the ratio of /max. The Langmuir isotherm can be expressed as
defined below allowing for the calculation of Kd.
C
1
C


 K  max max
Rearrangement of this equation to solve for  gives the following equation quoted on page 2304
of Nelson et al.

max  K d  C
(1  K d  C )