Journal Critique MIKE

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USE OF FLOATING BEAD FILTERS TO RECONDITION CIRCULATING WATERS

IN WARMWATER AQUACULTURE PRODUCTION SYSTEM

Ronald F. Malone;Lance E. Beecher

Published in Journal of Aquacultural Engineering © / 2000

A CRITIQUE

Submitted to

AILEEN D. NIEVEA, Ph.D.

For

RES298 COM / RESEARCH SEMINARSchool of Graduate Studies

Mapua Institute of Technology

On

05 OCTOBER 2010

By

NAPOLEON MICHAEL B. ORIGENES

MSST - 1989131132





2. Theory of Operation

It is clear that the author works on the function of floating bead filters and

states vividly the process involved. The author describes the advantages of such

use of the FBF in the production system so as mentioning its involvement in the

simplification of the most important water reconditioning performance.

CLARIFICATION PERFORMANCE

Clarification is the process of removing suspended solids from water .

Specifically, the study did not nebtion specific amount of physical straining it can

provide. Its only a belief that bioabsorption, the capture of particles by the

bacterial biofilter is the dominant removal process for such fine particles, that’s why

clarification efficiency is rarely an issue for a recirculating bioclarifier application,

allowing focus on another important water reconditioning process, biofiltration.

BIOFILTRATION PERFORMANCE

Biofiltration depends on the formation of a filter bead through the attachment and

growth of beneficial bacteria that extracts and dissolves chemicals from the water

and convert them to biomass or harmless dissolved compounds. The study clearly

states the importance of the process involved whereas conversions of toxic

components of water into relatively safe form. The study of the bacteria which are

responsible to these conversions are only limited to the toxic nitrogen forms,



ammonia and nitrate. The study does not affirm if any other harmful variety of

toxic forms other than nitrogen passes through the biofiltration process.

not exclusively specified or identified but it is quite clear that the authors generally

worked on only one hypothesis during the entire duration of the study, which is:

The presence of oil in the sediments will affect the partitioning of PCB during land

biotreatment of impacted sediment . Proving this hypothesis, however, is not

straightforward or simple since it entails a lot of required routine tasks which would

include, at least for this particular study, mechanism by which the presence oil

affects the PCB partitioning and/or degradation, coming up with an appropriate

equilibrium partitioning model in the presence of a third phase (oil phase), and

predicting equilibrium partitioning in the presence of oil phase using these models.

Further, it was postulated that, as a consequence of PCB oil-phase

partitioning, biotreatment would lead to higher PCB concentrations in the oily

matter and thus increased PCB partitioning to the aqueous phase if the degradation

of oily matter proceeded faster compared to PCBs. This postulate appeared in the

abstract although it can also appear as a conclusion.

3. Experimental approach

3.1 Experimental set-up and data gathering



The data used by the authors were based on the study of Alcoa (1995). This

long-term field study of the biodegradation of PCB-contaminated sediments and

sludge in pilot-scale engineered land-treatment units (LTUs) in Massena, N. Y.

made use of three of the four LTUs (labeled LTU1, LTU2 and LTU4) in the facility. A

schematic of the cross-section of the 1.2-m wide and 9.1-m long pilot-scale LTUs is

shown in Figure 1.

The sediments originated from on-site settling and treatment lagoons with

varying levels of PCBs, polycyclic aromatic hydrocarbons (PAHs), oil, cyanide,

fluoride and heavy metals (Alcoa 1995); Smith et al. 1999).

Figure 1. Schematic of pilot-scale land biotreatment unit.



The design of the pilot-scale land treatment seems to be a very good

approximation of what the full-scale biotreatment facility would look like. In

addition, the processes (partitioning, degradation, etc.) and effects of other

components that may be present, which were not quantified in this research, in the

pilot scale could well represent the processes that would be occurring in the full

scale facility.

For experimental purposes, it is quite rational to premix lagoon sediments

and mix them with sand to homogeneity by repeated tilling and shoveling.

However, there was no indicated means to determine the degree of homogeneity

the sand-sediment mixture attained. While it is true that mixing the sediment with

sand would increase the porosity of the treatment zone matrix (to promote aerobic

condition for microbial degradation), some degrees of heterogeneity (uneven

distribution of sand in sediment or of sediment in sand) would greatly affect the

sampling. It should be noted that sand adsorbs neither the aqueous phase nor

organic carbons (oil included). A sample taken from a specific point could not have

represented the entire system. Average of the values from multiple sampling (i.e.

sampling from different points), however, could lessen the uncertainty. Even the

basis or reason for the choice of sediment-to-clean sand amendment ratio (1:11 for

LTU1, 1:14 for LTU2, and 1:1 for LTU4) was not clearly established.



3.2 Conceptual models for equilibrium partitioning

The following were three conceptual models evaluated to compare the

predicted and the measured PCB partitioning between sediments-phase and

aqueous phase:

3.2.1 Model 1

PCB distributes between two phases: aqueous phase and organic-carbon

phase in the sediment . In this case, the PCB partitioning to the aqueous phase was

calculated with the following equation:

W OC OC S C K f C = (1)

where KOC values were estimated using the following equations by Chiou et al.

(1983) and Oliver (1985), respectively:

log KOC = 0.904 log KOW – 0.543 (2a)

log KOC = 0.41 log KOW + 3.42 (2c)

These equations had been developed on experimental measurements of PCB

partitioning between sediments and water. Equation 2a was derived from on

investigation of the sorption relationships for PCBs and chlorinated benzenes on

various soils and sediments and the equation was proposed for compounds with log

KOW ranging from 2.11 to 5.62 (R2 = 0.96) (Chiou et al. 1983). Equation 2c was



based on PCB determination in suspended sediments from Lake Ontario (Oliver

1985).

The incorporation of the equations 2a and 2c are justified only on the basis

that the model assumes partitioning only between the aqueous phase and the

sediment phase containing the organic carbon. These are similar systems utilized

to come up with equations.

3.2.2 Model 2

PCB partitions or distributes among three phases: organic-carbon phase in

the sediment , the oil , and the aqueous phase. It was assumed that the oil had

characteristics similar to Fyrquel 220 (f OC = 0.75), a hydraulic fluid used at the site

where sediment samples were taken. Luthy et al. (1997) investigated the

dissolution of PCB congeners from Arochlor 1242 and mixture of Arochlor 1242 with

Fyrquel 220 and found an equilibrium partitioning consistent with Raoult’s law of

liquid solubilities:

iiiiS X C γ = (3)

It was reported that the apparent the average activity coefficients of prominent

congeners for which corresponding solubility existed (Luthy et al. 1997). Equations

1 and 2a were used to calculate sediment-water partitioning while equation 3 was

used to calculate oil-water partitioning.



It should be noted that the distribution or partitioning of PCB in the three

phases at equilibrium were not clearly presented. Material balances could make this

possible. It can be suggested that maybe, in a separate paper, a thermodynamic

model for the liquid-liquid-equilibrium involving the PCB distributed into the three

different phases. In addition, it would help if the distribution of the PCB were

presented in a ternary diagram.

3.2.3 Model 3

This model assumes that the PCBs distribute into aqueous phase and oil-

phase, which means that the PCBs in the sediment-phase is solely associated with

the oil in it. This model also uses the same activity coefficients specified in model

2.

At this particular point it would be expected that Models 2 and 3 would be

useful in explaining the effect of oil in the partitioning of PCB in impacted sediment

during land biotreatment.

3.3 Relative rate of oil and PCB degradation

Based on a two-box modeling approach, the effects of differential rates of oil

degradation were analyzed to determine the fraction of fast- and slow-degrading oil

components and their respective degradation constants (Ghosh 1998):

( ) t k t k t s f e f feC

C −− −+= 10

(4)



and PCB on equilibrium partitioning relationships during the time course of land

biotreatment operations.

After evaluating the constants from the fitted model for oil and PCB

degradation, profiles of the PCB homologs within the sediment carbon, the oil, and

the aqueous phase were simulated and compared with the measured concentrations

in the corresponding phases. The simplified relative model used for the partitioning

of PCB from the oil to the aqueous phase is given in equation 5, and equation 6

results when equation 5 is combined with equation 4.

( )

( ) t k

oil

oil

o

ioil

t k

i

i

o

i s

oil

iS

it

oil s

i s

e f MW

C

e f MW

C

t C

C X

,

,

1

1

)(,

,

,

−

−

−

−

≅= (5)

( )

( )

t k k

ooil

o

i s

oil i

ioil iiiw

i soil seC

C

f MW

f MW S t C

)(,

,,,

1

1)(

−

−

−≅ γ (6)

These equations would suggest that the mole fraction of PCB in the oil phase is

small; further, they predict the concentration of PCBs in the aqueous phase will

increase if the slow rate constant for oil is greater than the slow rate constant for

PCB degradation. The aqueous concentration would be constrained by the limits of

pure-phase PCB solubilities, partitioning onto sediment organic carbon, and the

general recalcitrance of heavier oil compounds.

The effect of the presence of oil could only be partly explained by kinetics as

described in this paper. However, a better understanding of the process or pre-









4.2 Organic carbon in sediment and changes during land biotreatment

It is evident in Figures 3(a-c) that there was a significant reduction in oil

levels during the active phase of remediation; further, the oil continued to deplete

even after the passive treatment phase. Nearly half of the carbon associated with

the sediment was also degraded in the first two years. The increase in biomass by

year 5 or 6 was attributed by the author to the introduction of biomass when



healthy vegetation on the topsoil geotextile was established. Another possible

reason to explain the decrease in organic-carbon to sediment ratio is the

degradation of oil, which is part of the organic carbons.

4.3 Prediction of equilibrium partitioning of PCB

As expected, Model 2 (sediment-oil-water) and Model 3 (oil-water) gave

close predictions of the observed (or measured) concentration of PCB homologs in

the aqueous phase. These are indistinguishable in Figure 4, which shows this

agreement. The graphical presentation (aqueous PCB concentration vs PCB

homolog) already speaks for the agreement between the model and the

experimental values; thus, no further statistical proof would be necessary. And,

while it is true, as suggested by the author, that the oil-water model (Model 3) is

adequate in itself for describing total aqueous-phase PCB partitioning in LTU

systems, an extensive study involving other initial oil-to-PCB ratios and effect of the

type of organic carbon (other than oil) in the impacted sediment be considered.

Further, Ghosh et al. (2000b) suggested that rather than the widely used f OC-KOC

relationships, oil measurements be combined with bulk PCB measurements to

provide far better predictions of sediment-water PCB partitioning for systems

similar to this.





4.4 Change in oil and effect on PCB partitioning

Used as a model for determining the rates of in oil and PCB degradation

(changes in PCB and oil concentration), equation 4 predicted, and closely

approached, the actual rate of degradation as measured. From this tow-box model,

the parameters were evaluated. Like in the previous part, the graphical

presentation in Figure 5 is probably the best possible way to report the data. As in

any other modeling studies, a parity plot may also be presented to show how the

predicted values agree with the measured values.

There is a discussion on the constants determined for different PCB

homologs; however, this is not presented.



Figure 6 shows the same results as Figure 5, only that the data for LTU4

were removed.

4.5 Prediction of changing PCB equilibrium with degradation of PCB and oily matter

Although presented for the di- and tetra- PCB homologs only, Figures (7a-b)

could very well suggest that the models described previously couldt not predict the

effects of changing PCB equilibrium on degradation of PCb and oily matter. Other

models should be proposed. As suggested, the models could be derived based on a

combination of equilibrium and mass transfer principles.



5. Conclusions

Most conclusions are solely based on the objectives and findings in this study

and, therefore, are sound. However, the way one conclusion was presented in the

abstract was quite confusing: As a consequence of PCB oil-phase partitioning,

biotreatment would lead to higher PCB concentrations in the oily matter and thus

increased PCB partitioning to the aqueous phase if the degradation of oily matter

proceeded faster compared to PCBs. This appeared in the abstract as postulate and

could be mistaken as a conclusion.



6. Nomenclature:

CS hydrophobic organic compounds (HOCs) concentration on the solid, mg/kg

Cs,io PCB homolog concentration in sediment at t = 0

CW aqueous concentration, mg/L

CWi aqueous concentration of component i at equilibrium, mg/L

C0 initial oil concentration at t = 0

f fraction of fast-degrading oil

f OC fraction of organic carbon

kf fast fraction rate constant, y-1

ks slow fraction rate constant, y-1

ks,oil slow pool rate constant for oil

KOC organic-carbon-normalized partition coefficient, L/kg

KOW octanol-water partition coefficient

MW molecular weight of homolog or oil

S compound solubility

Si subcooled liquid solubility of pure component i in water

Xi mole fraction of component i in the organic liquid

γ I activity coefficient of component i in the organic liquid

7. References (from the paper)

All the references used here are the actual references used by this paper. The

original paper follows this page.



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