The document summarizes a study that investigated using Hibiscus cannabinus L. (Kenaf) core as a natural sorbent to clean up oil spills. A mathematical model was developed using response surface methodology to describe the sorption behavior of kenaf core in simulated bunker oil C and seawater mixtures. The model showed sorption quantity increased with higher oil concentration and longer exposure time. Testing found kenaf core effectively sorbed oil due to its lignocellulosic composition and properties, making it a potential alternative for oil spill response. However, its sorption capacity was lower than activated carbon due to having a smaller pore volume and surface area.

1. SORPTION BEHAVIOR OF HIBISCUS CANNABINUS L.
CORE IN SIMULATED
BUNKER OIL C – SEAWATER MIXTURE
Lea C. Tan, Trina G. Napasindayao, Florinda T. Bacani
Chemical Engineering Department, De La Salle University-Manila, Philippines
2401 Taft Avenue, Malate, Manila, Philppines, 1004
Keywords: Kenaf; mathematical equation; quantifying sorbent capacity; oil spill;
sorbent; sorption
ABSTRACT
Sorption using natural sorbents is an alternative method of oil spill treatment. This
research proposed a polynomial equation that described the sorption behavior of
Hibiscus cannabinus L. core in Bunker Oil C-seawater mixtures. This equation may
be applied for oil concentrations of 0.001 to 0.003 mL oil/mL mixture and for a
contact time of 15.00 to 120.00 min. The sorption behavior was characterized using
specialized parameter define as Sorption Quantity (SQ) (g oil sorbed/g sorbent). The
amount of oil sorbed by the Kenaf core was measured at different oil concentrations
and contact times using mass balances. Design Experts, a computer software, was
utilized in formulating the central composite design and in the statistical analysis
which made use of the response surface method. Results show that the sorption
behavior is best at high oil concentration and longer duration of exposure. Based on
the sorption parameter, the most recommended time of contact is in the range of
65.00 to 95.00 min. The quadratic model was selected among other polynomial
equations based on its R2
value of 0.9495 and p-value which is less than 0.0001 at a
0.05 confidence level.

2. INTRODUCTION
The availability of liquid petroleum in the form of crude oil and its refined products
is a key driver in modern society, but its widespread use results in accidental and
intentional releases resulting to oil spills. These oil spills have created large damages,
casualties and losses on both marine and land resources. In addition, oil spills
generally take about two to three years to clean up, some for even longer. Within
such time periods considerable damage will have occurred at the site of the spill.
Many methods have been proposed in an effort to clean up oil spills, among which
involve the use of chemical dispersants, microorganisms, and bioremediation agents.
However, these processes alone have not solved the oil pollution problem
particularly in the Philippines. It is therefore necessary to find an alternative and
immediate means to clean up oil pollution.
The advantage of sorption over conventional oil spill treatment is that it does not
alter the make-up of the environment. Sorption usually employs oleophilic, synthetic
sorbents. However, these fibers degrade slowly. Lignocellulosic fibers are renewable
and biodegradable natural sorbents with good sorptive properties but are oleophobic
and cannot be used for oil spills prior to treatment. Hibiscus cannabinus L., or Kenaf
is a lignocellulosic fiber that may be used because it is oleophilic. Kenaf can grow
under any wide range of weather conditions. This plant specie is native to tropical
countries and is harder, stronger and more lustrous than jute based fibers. However,
no prior research has been done to mathematically describe the ability of Philippine-
grown Kenaf to sorb oil in an aqueous mixture.
The viability of using Philippine-grown Kenaf core as a sorbent of Bunker Oil C
in seawater and the effect of contact time and oil concentration on the sorption
behavior was investigated. A mathematical equation of the mass transfer of the oil
into the Kenaf was generated to predict the SQ given the time and oil concentration.
THEORETICAL FRAMEWORK
Sorption
Sorption is the process where a material moves across a boundary to move from one
phase to another where sorption is generally an equilibrium process and is a result of
the interaction between three molecules: the sorbent, sorbate, and the solvent
(LaGrega et al., 2001).

3. Viscosity, surface tension and wettability are certain sorbate characteristics that
affect its sorptive capacity. Another important characteristic is the high surface area
which will results in longer contact with the sorbate. Other factors that aid in the
sorption of the sorbent include the amount of wax in the surface, the hollowed
surface, and the noncollapsing lumen of the fiber. The chemical composition as well
as the structure of the sorbent also affects its sorptive capacity. The structure, on the
other hand, affects the ability of the liquid to penetrate the solid as well as the
tendency of the sorbent to swell. Swelling occurs when the solid expands upon
sorbing the liquid thus increasing the space that may be occupied by the liquid.
Response Surface Methodology
Response surface methodology (RSM) is a technique that combines statistical
and mathematical means in order to develop, improve, or optimize a given process. It
is also useful for processes in which the underlying mechanism is not fully
understood.
In order to fit a second-order response surface, a minimum of three levels for
each design variable is required. The number of distinct design points have to be
greater than or equal to 1+2n+n(n+1)/2 where n is the number of levels in the
experimental design (Myers and Montgomery, 1995).
Central composite design (CCD) is the most common experimental design for
fitting second order models in sequential experimentation. It makes use of a two-
level factorial or fraction (resolution V) along with 2n axial or star points. There are
then F factorial points, 2n axial points, and nc center runs. Generally an empirical
model is based on observed data and general polynomial models are linear functions
with unknown coefficients which are solved using linear regression analysis. The
RSM determines the number of replications needed, location of the optimum region,
the most appropriate function required, the proper experimental design as well as the
extent of transformation needed (Myers and Montgomery, 1995).
MATERIALS AND METHODS
Bunker Oil C was added to water with 0.5 M NaCl concentrations to prepare
mixtures of the following concentrations: 0.001, 0.002 and 0.003 mL oil/mL mixture.

4. Kenaf core (20.00 g) was introduced into the mixtures for exposure times of 15.00,
67.5 and 120.00 min. The wet core is then distilled using 20% toluene-xylene solvent
to separate the water sorbed by the Kenaf. The oil sorbed by the Kenaf was
determined by mass balance and used to solve for the experimental response. The
dependent variables were then plotted against time and concentration to determine
their respective behavior. Central Composite Design was applied to determine the
values of the independent variables for the runs while Response Surface Method was
used to generate the mathematical equation and perform statistical analysis. The
physical and chemical properties of the sorbent and sorbate were also correlated to
the analysis of the data. The experimental set-up is shown in figure 1.
FIGURE 1. Experimental Set-up
RESULTS AND DISCUSSION
The sequential model sum of squares, lack of fit tests and model summary statistics
revealed that the quadratic equation is the most appropriate polynomial equation for
the sorption process. A quadratic polynomial equation was generated to determine
the SQ where t is time in minutes and C is concentration in mL oil/mL mixture:
2470.01714.21057.22381.231056.5 253
+⋅⋅+⋅×+⋅−⋅×−= −−
CttCtSQ
Eq. 1
at time range of: 12000.15 ≤≤t
at concentration range of: 003.0001.0 ≤≤C

5. Element%
0
10
20
30
40
C 27.51 N 31.48 O 34.17 Mg 0.07 K 0.23 Nb 6.54
Analysis of variance was applied to reduce the quadratic model by determining
the respective terms that had an effect on the equation. The square of the regression
coefficient for Equation 1 has a value of 0.9495. Since this is close to unity, it
indicates that the generated equation has predicted values that are close to the
response.
The large amount of carbon in the Kenaf (27.51%) explains why it sorbs oil
instead of water since it is composed of the same organic material as shown by the
lignin content and elemental percent of Carbon as shown in figure 2A with figure 2B
showing the SEM result.
FIGURE 2. (A) Elemental Composition of the Kenaf Core ; (B) SEM of Kenaf
Core at 10 micrometers
Sorption Quantity, SQ, shown in Figure 3, is based on the oil sorbed per gram of
Kenaf core. The behavior observed follows the general sorption kinetics of organic
pollutants using natural sorbents which is characterized by a rapid initial uptake and
then a slow approach to equilibrium.
Sorption Rate is affected by the pore volume of the Kenaf core which dictates
how much Bunker Oil C can be accommodated by vacant spaces within the Kenaf
core. The BET pore volume (8.519E-04 cc/g) of the Kenaf is small; therefore not
much oil can be accommodated in its interior. The high kinematic viscosity
(241.9mm2
/s) of Bunker Oil C also contributes to the small SQ value since its
molecules are larger. This makes it more difficult to sorb and penetrate the inner
portion of the Kenaf core.
(A)
(B)

6. FIGURE 3. Sorption Quantity Interaction Profile
CONCLUSION AND RECOMMENDATION
Among the mathematical models, the quadratic model was chosen based on
statistical tests. Results show that the sorption behavior is best at high oil
concentration and longer duration of exposure. However, contact time was observed
to have greater effect on the sorption properties compared to the oil concentration.
In the graphs generated, there is a difference in the SQ with respect to time. The
common trend when all the response parameters are plotted against time is an
increase in the response at the start followed by a gradual decrease until change in
the response is no longer evident. The sorption of organic pollutants involves two
mechanisms which results in an initial surge in the sorption which is then followed
by a retarded increase. Various models have been proposed to explain this behavior.
Philippine Kenaf core is not as good a sorbent compared to activated carbon due
to its low pore volume and surface area but the sorption performance of the core is
the best among the other parts of the Kenaf plant. This makes the Kenaf core a good

7. sorbent along with the pore diameter which falls under the range of good sorbent. Its
natural properties such as biodegradability and oleophilic nature make it useful as an
alternative response for oil spills unlike most substances which require processing
before application.
For further investigation of the sorption capacity of Kenaf core in simulated oil
spill, it is suggested to apply the method of steepest ascent to optimize the response.
This may be used to obtain the values of the independent variables to derive the
conditions to maximize the sorption quantity. This is done by determining the
principal axes of the contour lines generated in the initial experiment and then
drawing a perpendicular line from it. The direction to be followed is obtained from
the behavior of the contour plot as to whether it is increasing or decreasing. Other
parts of Kenaf may also be used as sorbent, particularly the pitch which has a large
sorption capacity. Lastly, other investigations may also be conducted on different oils
used as the sorbate to determine how the different oil properties affect the sorption
behavior. Properties of the sorbent (pore volume, pore size, surface area of the pore)
and sorbate (viscosity, surface tension, density) which affect the sorption behavior
may also be included among the independent variables in other studies to formulate a
more general equation.
REFERENCE
Bedient, P.B.; Rifai, H.S.; Newell, C.J. Groundwater contamination: Transport and
remediation. NJ; PTR Prentice Hall, 1994.
LaGrega, M.; Buckingham, P.; Evans, J. Hazardous waste management. New York;
McGraw-Hill Co. Inc, 2001.
Lee, B.; Han, J.; Rowell, R. Lignocellulosic Fibers. 1999, 35: 423-433.
Myers, R.; Montgomery, D. Response surface methodology: process and product
optimization using design of experiments. New York:Wiley Series in Probability and
Statistics, 1995.
Zaveri, M. Thesis, North Carolina State University, May 2004.