(213e) Chemical Release During Dredging of Contaminated Sediment | AIChE

(213e) Chemical Release During Dredging of Contaminated Sediment

Authors 

Ravikrishna, R. - Presenter, Indian Institute of Technology-Madras
Ekawde, P. - Presenter, Indian Institute of Technology-Madras
Mahesh, K. - Presenter, Indian Institute of Technology-Madras


One of the options for
the remediation of contaminated sediments in rivers, lakes or coastal bay areas
is dredging and subsequent relocation of the dredged material for storage
and/or disposal. Dredging induces resuspension of bed
sediment, the extent of which depends on the type of dredging as well as the
efficiency of execution. One of the concerns from a risk assessment perspective
is the release of chemicals into water and possibly to air as a result of desorption of the hazardous chemicals from the contaminated
solids, which are resuspended [1]. From a risk
assessment perspective, it is necessary to evaluate the chemical release during
dredging since this affects water quality and potentially the air quality as
well.

The primary point of
concern is the rate of chemical release from the resuspended
solids during dredging by desorption to the water
layer, where it can become ?bioavailable' or
evaporate. Traditionally, the prediction of the magnitude of chemical release
is based on mass balance measurements of suspended solids concentrations and
the bed sediment chemical concentration assuming .uniform chemical loading in
the undisturbed bed sediment with respect to particle sizes.  Previous experiments in laboratory
simulations suggested that the chemical concentration associated with the
solids may be particle size dependent. Since at different times, the suspended
solids concentration and particle size distribution vary, a model that predicts
the aqueous phase concentration must incorporate the dynamic behaviour of the solids. Correspondingly, the measurement
of chemical concentration as a function of particle size must be made for the
model to be useful.

The model to describe
the unsteady state change in aqueous phase chemical concentration in the absence
of evaporation, assuming the aqueous phase to be well mixed is shown in
equations 1a and 1b(1) ? 1b(n). Equation 1a represents the change in aqueous
phase concentration, which is the sum of contributions of desorption
of chemical from each discrete particle size. Equations 1b(1-n) represent
chemical balance on each of the ?n' particle fractions of size dpi .
The desorption kinetics are dependent on the
solid-water mass transfer coefficient, k2A3.   The driving force is the concentration
difference between the aqueous concentration and the concentration in
equilibrium with the chemical present on the solids, where KA32 is
the solid-water partition constant. The second term in equation 1a represents
the rate of evaporation.


          (1a)


                                               (1b-1
to 1b-n)

The quantity ρss,iis the suspended solid
concentration that is dependent on the particle size and changes with time. In
the model, it is assumed that the suspended solids concentration changes as a
result of the settling.  The equations
were solved using Matlab® along with the estimate of ρss,iat each time step. This
model is based on an earlier version of the model which did not consider the
time-dependency of suspended solids concentrations or the particle size
dependent loading [2].

            One of the primary inputs to the model described above is
the particle size dependent distribution of contaminant concentration (loading)
in the solids. An experimental technique based on the separation of different
fractions based on settling is also described here. Tests were conducted to
evaluate the efficiency of separation and the different fractions. In these
tests, the solids, chemical and organic carbon balance was measured to validate
the separation process. The separation of solids using the settling method is
reasonably effective with a solids balance that is satisfactory. Relative
loading of different size fractions were collected and were different. The
model was tested for conditions and the performance was evaluated with
reference to the previous model as well as experimental data obtained for
chemical desorption.