Characteristics of Oil Droplets Stabilized by Mineral Particles: Effects of Oil Type and Temperature

Spill Science & Technology Bulletin, Vol. 8, No. 1, pp 19–30, 2002 Ó 2003 Elsevier Science Ltd. All rights reserved Printed in Great Britain 1353-2561/03 $ - see front matter

doi:10.1016/S1353-2561(02)00117-2

Characteristics of Oil Droplets Stabilized by Mineral Particles: Effects of Oil Type and Temperature ALI KHELIFA *, PATRICIA STOFFYN-EGLIà,1, PAUL S. HILL ,2 & KENNETH LEE  ,3  Department of Oceanography, Dalhousie University, Halifax, NS, Canada B3H 4J1 àBDR Research Limited, P.O. Box 652, Halifax, NS, Canada B3J 2T3   Marine Environmental Sciences Division, Bedford Institute of Oceanography, P.O. Box 1006, Dartmouth, NS, Canada B2Y 4A2

The relative influence of oil type and temperature on the characteristics of oil droplets stabilized by mineral particles (oil–mineral aggregates––OMA) was studied in the laboratory. OMA were generated by shaking eight different oils under two temperatures with natural mineral fines in seawater at a pre-defined energy level. Shape, mean and maximum sizes, size distribution and concentration of oil droplets forming negatively buoyant OMA were measured by image analysis using epi-fluorescence microscopy. Results showed that oil droplets are, on average, spherical regardless of oil composition and temperature. Non-spherical ‘‘elongated’’ oil droplets form more at 20 °C than at 0 °C. Droplet shape and size were not correlated to oil viscosity. The concentration of oil droplets decreased rapidly with oil viscosity, temperature and asphaltenes–resins content (ARC). When normalized with ARC, mass concentration of oil droplets correlates well with oil viscosity, regardless of experimental temperature. A model was proposed to calculate mass of oil dispersed by OMA as a function of oil viscosity and ARC. Size distributions of oil droplets follow similar trends, but their magnitudes depend on oil type and temperature. A function was derived that describes all the data when size distributions were presented in a normalized form N=Nt ¼ f ðD=D50 Þ, where N is number of droplets of diameter D, Nt is the total number of droplets and D50 the mean size of the droplets. Ó 2003 Elsevier Science Ltd. All rights reserved. Keywords: Oil droplet, oil dispersion, oil–mineral interaction, oil–mineral aggregate, clay–oil flocculation, oil spill

Introduction Oil spilled in aquatic environments is subjected to complex transformations immediately after it enters

*Corresponding author. Tel.: +1-902-494-2747; fax: +1-902-4943877. E-mail addresses: [email protected] (A. Khelifa), stoff[email protected] (P. Stoffyn-Egli), [email protected] (P.S. Hill), [email protected] (K. Lee). 1 Tel.: +1-902-456-7360; fax: +1-902-845-2153. 2 Tel.: +1-902-494-2266; fax: +1-902-494-3877. 3 Tel./fax: +1-902-4267344.

the water. The progression, duration, and result of these transformations depend on the properties and composition of the oil, spill conditions, as well as environmental parameters. For instance, oil dispersion, induced by local flow and turbulence conditions, is a natural process by which oil slicks are transformed into small droplets. Overall, these small oil droplets are less harmful to aquatic environments as they are more easily biodegraded than oil slicks (see for example Bragg et al., 1994; Weise et al., 1999). Therefore, it is fundamental to understand how this breakup process (transformation of oil slicks into small droplets) affects the dispersion of oil slicks, at least in 19

A. KHELIFA et al.

terms of size and concentration of dispersed droplets. Information on droplet size distribution is also of particular interest as it is directly related to transport and stability of OMA in the aquatic environment. A further reason why it is fundamental to understand how oil slicks transform into small droplets is that the development of numerical models, a powerful tool that helps to predict the fate and transport of oil spills in aquatic environments, requires a good understanding of oil droplet formation from oil slicks. Robust oil-spill numerical models should be developed using accurate behavior models, which describe, among others, the mechanism of oil droplet formation. In the majority of experimental studies on oil–mineral aggregates (OMA) formation, test flasks containing water and oil are subjected to mechanical agitation. From the oil spill perspective, relatively few studies have been focused on the size and concentration of oil droplets formed under turbulent motion. One of the most comprehensive laboratory studies investigating oil dispersion was conducted by Delvigne and his co-workers (Delvigne et al., 1987; Delvigne, 1987; Delvigne and Sweeney, 1988). They showed that the size of oil droplets generated under turbulent motion was influenced by oil viscosity and the level of turbulence. Measured size distributions of dispersed droplets were shown to follow a similar curve in a plot of number concentration versus droplet diameter. The trend of this curve has the form N  D2:3 , where N is the number of droplets of size D. According to Delvigne (1993), it is justified to apply the empirical relationships he obtained for oil dispersion due to breaking waves to cases where dispersion sources include a short-duration plunging phase. Examples of such dispersion sources are flow over a dam, cataract with a hydraulic jump, fast flow around an obstacle, and a ship crossing an oil slick. Furthermore, pouring experiments conducted by Delvigne and Hulsen (1994) showed that the oil dispersion coefficient was not affected by oil viscosity when the oil viscosity was <1 cm2 /s. In contrast, at higher oil viscosities the dispersion decreases considerably with viscosity. Lunel (1993) used laser phase Doppler particle analysis to measure the size distribution of naturally and chemically dispersed oil slicks. The results of laboratory studies and field trials at sea with a variety of oils and oil/dispersant combinations showed similarity in droplet size distributions with a median value of 20 lm. Lunel estimated that 90% of the oil droplets (50% of the oil volume) were <45 lm in diameter, and that 99% of the oil droplets (80%–90% of the oil volume) were <70 lm. Fraser and Wicks (1995) have discussed how the concept of critical Weber number (Hinze, 1955) may be used to estimate the maximum size of stable oil droplets dispersed in sea. The corre20

sponding wind speed is then considered as a critical condition below which the use of chemical dispersant is necessary to form stable dispersions of oil in water. More recently, Li and Garrett (1998) have investigated theoretically the effect of oil viscosity on the size of droplets, assuming that viscous shear is the mechanism for droplet break-up. They showed that the maximum size of droplets is proportional to the ratio n ðld =lc Þ , where ld is the viscosity of the droplet, lc the viscosity of continuous phase and the superscript n equals to 3/8 if the size of the droplet is larger than half the Kolmogorov length (Hinze, 1975) and 1/8 otherwise. In summary, it is now acknowledged that characteristics of oil droplets generated by turbulent flows are affected by the physical properties of the oil, the intensity of the energy dissipation rate due to turbulence, and the hydrodynamic processes responsible for the production of turbulent fluctuations. The process of droplet break-up is one of the key mechanisms which dictate characteristics of oil droplets formed in turbulent flows. Mechanism of droplet break-up In light of its potential application to industrial processes, the mechanism of droplet break-up has been addressed in several studies. Hinze (1955) showed that the mechanism of droplet break-up could be described by the following two dimensionless variables: Nwe ¼

qc u2 D ; r

and

ld Nca ¼ pffiffiffiffiffiffiffiffiffiffiffi qd rD

ð1Þ

where qc and qd represent densities of continuous and droplet phases, respectively, u is the velocity difference in the flow over a distance of droplet diameter D, r is the oil–water interfacial tension. Nwe is called the Weber number, and Nca is referred to as the ‘‘viscosity group’’ by Hinze, but is commonly called the Capillary number. Both of these variables reflect the ratio between an external disturbing force, induced by the flow conditions, and an internal resisting force due to the interfacial tension. The disturbing forces are the dynamic pressure in the case of the Weber number, and the viscous shear in the case of the Capillary number. Hinze related the maximum size of droplets Dmax to a minimum value of Nwe . This value is defined as the critical Weber number, which is given by: ðNwe Þcrit ¼

qc u2 Dmax r

ð2Þ

Hinze postulates that ðNwe Þcrit is related to Nca by the equation: ðNwe Þcrit ¼ vð1 þ uðNca ÞÞ

ð3Þ

Spill Science & Technology Bulletin 8(1)

CHARACTERISTICS OF OIL DROPLETS STABILIZED BY MINERAL PARTICLES

where v and u are two functions of external conditions such as turbulence intensity and viscosity of the continuous phase. The function u decreases to zero when Nca goes to zero. Sleicher (1962) has shown that, in the case of flow in a pipe, the functions v and u may be approximated by the same simple functional form aðlV =rÞb , in which a and b are two constants, V is the average flow velocity in the pipe, and l ¼ lc for v and l ¼ ld for u. Subsequent studies used the concept of critical Weber number to investigate maximum size of droplets under various flow conditions (Calabrese et al., 1986; Fraser & Wicks, 1995; Li & Garrett, 1998; van der Zande & van den Broek, 1998). Delvigne (1991) has used this concept to show variations with oil viscosity of the critical velocity for droplet entrainment from a boomed oil slick. Considering that the mechanism of droplet breakup is controlled by oil and continuous phase properties and the energy dissipation rate e by turbulence, one may write the following functional relationship for the droplet size: D ¼ f ðe; lc ; qc ; ld ; qd ; rÞ

ð4Þ

It follows from dimensional analysis that a possible dimensionless relationship is:   D ld qd r ¼f ; ; ð5Þ g lc qc lc v where g and v represent the Kolmogorov microscales of length and velocity (Hinze, 1975), respectively. Eq. (5) proposes that, in the case of crude oil dispersed in water, the dimensionless size of oil droplets is essentially a function of the ratios of their viscosity and of their density normalized to those of the ambient water, (viscosity and density ratio, respectively) and the variable Nr ¼ r=lc v. Density ratio is expected to have small effect on crude oil droplet size because the range of its variation is narrow. The effects of viscosity ratio have been reported by many studies, as discussed in the previous sections. The relevance of the dimensionless variable Nr is much less discussed in the literature. One notes however that Sleicher (1962) has shown that the concept of critical Weber number as proposed by Hinze (1955) is not sufficient to explain experimental data published by Clay (1940) when the viscosity effect is negligible. Sleicher showed that the maximum size of droplets of low viscosity oil is a function of both the critical Weber number and a dimensionless variable similar to Nr . According to SleicherÕs suggestions and to Eq. (5), the concept of critical Weber number could be modified as follows: ðNwe Þcrit Nr0:5 ¼ vð1 þ uðNca ÞÞ Spill Science & Technology Bulletin 8(1)

ð6Þ

As our experiments were conducted under constant shaking energy, effects of variables g and v on characteristics of oil droplets, and consequently variations of D=g with Nr , cannot be addressed in the present study. The effects of viscosity ratio and interfacial tension on characteristics of oil droplets are discussed in this paper. Further experiments where agitation energy is varied are needed to validate Eq. (6).

Mechanism of oil–mineral aggregation OMA formation occurs naturally when oil and mineral particles are present in a turbulent aqueous medium. The most common form of OMA consists of an oil droplet with solid particles attached on its surface. These solid particles prevent recoalescence of oil droplets. Several recent studies have significantly advanced the understanding of the formation and characteristics of OMA (e.g. Lee et al., 1998; Guyomarch et al., 1999; Lee & Stoffyn-Egli, 2001; Stoffyn-Egli & Lee, 2002). It is general knowledge within the oil production community that solid particles are capable of stabilizing the droplets of one fluid in another. Indeed, Ramsden (1903) first observed emulsions stabilized by the presence of solid or highly viscous matter at the interface of two liquids. Pickering (1907) discovered that finely divided solid particles wetted more by water than oil could act as an emulsifying agent for oil-inwater emulsions. Since then, numerous investigations have been focused on the stability of solids-stabilized emulsions (see Menon & Wasan, 1988; Yan & Masliyah, 1995; Binks & Lumsdon, 2000a,b, for a review). Subsequent investigations on the environmental fate of oil spills reported that dispersed oil droplets can aggregate with clay particles (Poirier & Thiel, 1941; Huang & Elliot, 1977; Bassin & Ichiye, 1977; Zurcher & Thuer, 1977). Most recently, it has been suggested that OMA formation may play a major role in the natural cleaning of oiled shorelines and may be the basis for the development of an active oil spill countermeasure technology. However, the recognition that OMA formation plays a major role in the natural cleaning of oiled shorelines is very recent (Owens et al., 1994; Lee et al., 1997; Owens, 1999; Sergy et al., 1999). To date, both experimental and theoretical evidence show that oil–mineral aggregation is a process that occurs naturally after oil spills or during oil production. Among the various factors affecting OMA formation are the physical properties of mineral particles such as size, density, composition and concentration, oil properties such as viscosity, droplet size, composition, density and concentration, and environmental conditions such as temperature, pH, salinity, and hydrodynamic conditions. 21

A. KHELIFA et al.

Objectives The principal aim of this study is to obtain quantitative information on the characteristics of oil droplets stabilized with mineral particles at an early stage of their formation. In the experimental procedure, OMA are formed in shaker-flasks with eight different test oils, at two temperatures under a pre-determined energy level. Epi-fluorescence microscopy and image analysis are then used to count and measure oil droplets. The specific objectives of the study are to: 1. Investigate how shape, size, and concentration of mineral-stabilized droplets are affected by oil composition. 2. Investigate self-similarity in size distributions of mineral-stabilized droplets for different crude oils. 3. Investigate the influence of temperature on the characteristics of oil droplets associated with OMA. 4. Compare the results with those of previous studies of oil droplets generated in the absence of mineral particles.

Experiments Experimental procedure OMA were generated using a reciprocating shaker/ water bath at a constant shaking energy. Erlenmeyer flasks (250 ml nominal capacity) with silicone stoppers covered in aluminium foil were used as reaction chambers. Each test chamber contained seawater (125 ml) and the mineral phase added as a concentrated suspension. This concentrated mineral suspension was stirred with a magnetic stir bar while the appropriate volume was withdrawn with an Eppendorfâ volumetric pipette and dispensed in the Erlenmeyer flasks. The flasks were then shaken for 5 min before the addition of the oil phase. The test oil was added at the surface of the water using a hypodermic syringe weighed before and after dispensing the oil. This weight was used to calculate the exact amount of oil added to each watermineral mixture. The Erlenmeyer flasks were shaken for 4 h in a reciprocating shaker, after which the content was poured into a 250-ml separatory funnel. The funnels were left to settle overnight in the refrigerator. A 50-ml sample containing the settled phase was then transferred to 60-ml plastic sample cups. These samples, containing all the negatively buoyant OMA formed, were fixed with mercuric chloride (200 ppm) and stored in the refrigerator until analysis. Experimental conditions Weise et al. (1999) have shown that a reciprocating shaker is more efficient in producing OMA as com22

pared to an orbital shaker or a magnetic stirrer as it provided the most effective means to disrupt the liquid/air interface. In this study, OMA were generated with a temperature-controlled (water-bath) reciprocating shaker set at the minimum speed capable of continuously disrupting the layer of surface oil (160 cycles/min; 22 mm stroke length). The experiments were run at temperatures of 20 °C (room temperature) and 0 °C. Each test consisted of 125 ml of seawater, 12.5 mg of mineral (100 mg/l) and approximately 31 mg of oil (250 mg/l). The natural seawater used, filtered on layered gravel beds, had a salinity of 34 1 g/l (from Bedford Basin, Dartmouth, Nova Scotia, Canada). The mineral used was a natural sediment sample from the St.-Lawrence Estuary (Canada), sizefractionated by settling to retain the <2 lm fraction, and with a median grain size of 0.9 lm. This mineral phase consists mostly of quartz, feldspars, illite, chlorite and amphiboles (Weise et al., 1999). The eight different oils considered in this study were selected to span a wide range of viscosity values. Table 1 summarizes some of their physical properties. Data acquisition UV Epi-fluorescence microscopy is particularly sensitive for the detection of crude oil because aromatic hydrocarbons have a strong natural fluorescence. The analytical procedure used in this study is described in detail by Stoffyn-Egli and Lee (2002). In summary, an heamocytometer slide of known sample volume was used for quantitative microscopic analysis using a Leitz TASþ image analysis system coupled to an Orthoplan UV epi-fluorescence microscope with a computer controlled motorized stage (band pass excitation filter: 450–490 nm; reflection short pass filter: 510 nm; suppression filter: 515 nm). A 40 objective was used to image 99 sequential fields of view in three to six counting chambers (0.2 ll for each replicate analysis). Data analysis Data were processed using image analysis. In each microscope field of view, the area A, the perimeter P , and the maximum length Lmax of each fluorescent area were measured. Fluorescent areas will be called droplets hereafter although they are not always circular and may sometimes represent aggregates comprised of two or more droplets. A theoretical detection limit of 2.0 lm for the smallest particle dimension was obtained with the particular system used based on magnification, pixel resolution and noise reduction techniques applied. The equivalent diameter D of affi pffiffiffiffiffiffiffiffi droplet was calculated using the expression 2 A=p. Spill Science & Technology Bulletin 8(1)

CHARACTERISTICS OF OIL DROPLETS STABILIZED BY MINERAL PARTICLES

Table 1 References and properties of oils used in this study (Environment Canada, 2001) Oil reference

Federated (Alberta, 1994) Brent Blend (U.K.) Gulfaks (Norway) Prudhoe Bay (Alaska, 1995) Arabian Medium IF 30 (Svalbard) Maya (Mexico), weathered 9% IF 300

Dynamic viscosity (Pa s)

Interfacial tension (N/m)

Quantity of oil added (mg)

Resins and asphaltenes (wt.%)

0 °C

20 °C

0 °C

20 °C

0 °C

20 °C

0 °C

20 °C

FED BB GF PB ARAB IF30 MAYA

841 847 881 895 890 955 963

825 831 866 880 876 – 948

0.018 0.025 0.023 0.014 0.019 0.030 0.030

0.016 0.022 0.027 0.008 0.022 – 0.025

0.018 0.025 0.023 0.014 0.019 0.030 0.030

0.016 0.022 0.027 0.008 0.022 – 0.025

33.3 29.4 30.4 36.1 33.9 28.2 32.8

31.3 32.1 31.0 31.8 31.9 – 32.3

4 5 6 14 13 – 26

IF300

996

982

0.078

0.024

0.078

0.024

31.0

31.7

28

Most of data at 20 °C were obtained by extrapolation of available data at 0 and 15 °C.

Variable parameters like mean area, mean perimeter, mean and maximum diameters, maximum length, mean and minimum shape factors, as well as the total number and volume of droplets present in each replicate were calculated. Size distributions were also calculated for each replicate using the equivalent diameter D. The size classes chosen are bound by the values of 3, 6, 10, 15, 21, 28, 36, and 45 lm. Size distributions were plotted using the central values of each size class. The <3 lm particles were plotted at 2 lm. No droplet of size larger than 45 lm was observed. Average data values are presented for each individual test, based on the analysis of three to six replicates counting chambers.

Results and Discussion Microscopy observations revealed a variety of OMA structures in the negatively buoyant OMA formed in the laboratory tests. The majority were droplet aggregates, defined in Lee and Stoffyn-Egli (2001) and Stoffyn-Egli and Lee (2002) as individual oil droplets surrounded by mineral particles. However multiple droplet aggregates, where more than one droplet is present in a single OMA, and solid aggregates, elongated oil particles containing some mineral particles within the oil phase as well as on its periphery were also present in the samples. Further details regarding OMA characterization and illustration are presented in Lee and Stoffyn-Egli (2001) and StoffynEgli and Lee (2002). Solid aggregates will be measured as elongated (non-circular) fluorescent areas. In the following discussion ‘‘droplet’’ will refer to any distinct fluorescent particle in two dimensions, regardless of OMA type.

measurement of the shape factor variable U ¼ 4pA=P 2 , where A and P are the measured area and perimeter of the droplet (two-dimensional fluorescent area), respectively. This variable gives an indication of the droplet shape. A circular form is characterized by U ¼ 1. Variations of mean and minimum values of U with viscosity ratio (viscosity of the oil over that of the seawater) are presented in Fig. 1 for all test oils at both 0 and 20 °C. This figure shows that, on average, oil droplets are circular, regardless of the oil viscosity or experimental temperature. However, it is interesting to note that the presence of elongated oil droplets for which U takes minimum values (Umin ) much smaller than 1, is greater at 20 °C than at 0 °C. The reason for such influence of temperature on the shape of oil droplets is not clear, as there is no correlation of U with the viscosity ratio (Fig. 1), nor with the oil/water interfacial tension values (data not shown). To further investigate this behavior, the distributions of the variable U were calculated for different oils at 0 °C (Fig. 2a) and 20 °C (Fig. 2b). Fig. 2 shows the

1.2

1.0

Φ mean , Φ min



Symbol Density (kg/m3 )

0.8

0.6

0.4

0.2 Minimum at 0°C

Minimum at 20 °C

Mean at 0 °C

Mean at 20 °C

0.0

Shape of oil droplets The shape of oil droplets stabilized by mineral particles was investigated in this study through the Spill Science & Technology Bulletin 8(1)

0.1

1

10

100

µd /µc

1000

10000

100000

Fig. 1 Shape factor of oil droplets stabilized by mineral particles: variations of minimum and mean values with viscosity ratio. 23

A. KHELIFA et al.

100

1.E+07

Droplet size D 50 and Dmax (µm)

Cumulative number of oil droplets per ml

a 1.E+06

1.E+05

1.E+04

1.E+03

1.E+02

1.E+01

FED

BB

GF

PB

ARAB IF30

MAYA IF300

1.E+00

Dmax at 0°C D50 at 0°C

Dmax at 20°C D50 at 20°C

10

1 0.0

0.2

0.4

0.6

0.8

1.0

1.2

Φ

0.1

1

10

100

1000

10000

100000

µd / µ c

Cumulative number of oil droplets per ml

1.E+07

b

Fig. 3 Variations of mean and maximum droplet sizes with viscosity ratio at 0 and 20 °C.

1.E+06

1.E+05 1.E+04

1.E+03

1.E+02

1.E+01

1.E+00 0.0

0.2

0.4

0.6

FED

BB

GF

PB

ARAB IF300

MAYA

0.8

1.0

1.2

Φ

Fig. 2 Shape factor distributions of oil droplets stabilized by mineral particles at 0 °C (a) and 20 °C (b).

existence of large numbers of non-spherical oil droplets stabilized by mineral particles at both temperatures. The elongation and the number of these nonspherical droplets are larger at 20 °C than at 0 °C. One notes also the similarity of the curves shown in Fig. 2a and b. The shape of these curves is preserved and is independent of oil type. It is not clear if such behavior is the consequence of the solid-stabilization process, or if it reflects a characteristic of dispersed droplets. Mean and maximum sizes of oil droplets Variations of mean and maximum sizes (equivalent diameter) of mineral-stabilized oil droplets with viscosity ratio are shown in Fig. 3 for all test oils at both operating temperatures. Fig. 3 shows that the oil viscosity has negligible effect on both maximum and mean sizes of oil droplets. This observation is in disagreement with those of Delvigne et al. (1987) and Delvigne and Sweeney (1988). Delvigne and coworkers found that minimum, mean and maximum sizes of oil droplets are proportional to m0:34 d , where md is the kinematic viscosity of the oil used. However, they used in their experiment a grid column to generate turbulent energy responsible for oil droplet for24

mation. Oil droplets were generated without any mineral phase. It is evident that these experimental conditions may have certain effects on the size of oil droplets. Furthermore, their sampling device for oil droplets (16 cm high and 2.3 cm wide) was kept vertical in a stationary position for 20 h after sampling and prior measurement of oil droplet size. This procedure may have had significant effects on the size distribution of oil droplets, by allowing coalescence of oil droplets during their migration to the surface. It is important to note that van der Zande and van den Broek (1998) have found a negligible effect of oil viscosity on maximum size of droplet formed in an orifice. They related this behavior to the rapidity of the break-up mechanism in the orifice. Hinze (1955) has in fact showed theoretically that when the Capillary number (Eq. (1)) is very small, the maximum droplet size does not depend on oil viscosity. The maximum size of oil droplet is then described by the density of the continuous phase, the interfacial tension and the rate of dissipation of turbulent energy (Hinze, 1955). The issue of viscosity influence on oil droplet size warrants further investigation, with particular attention paid to the agitation method. Temperature affects the mean size of oil droplets slightly (Fig. 3). The mean size at 0 °C is larger than mean oil droplet size observed at 20 °C. As variations in mean size and shape factor (Figs. 1 and 2) of droplets with temperatures are not correlated to variations in oil viscosity induced by temperature changes, it becomes evident that temperature affects oil droplet size through other mechanism than viscosity.

Concentrations of oil droplets The concentration of oil droplets stabilized by clay particles has been plotted versus viscosity ratio in Spill Science & Technology Bulletin 8(1)

CHARACTERISTICS OF OIL DROPLETS STABILIZED BY MINERAL PARTICLES

0°C

7

Number Nt of oil droplets (10 /ml)

1

20°C

C1

0.1

C2

0.01 0.1

1

10

100

1000

10000

100000

µd / µc Fig. 4 Variations of number concentration of oil droplets with viscosity ratio at 0 and 20 °C.

Fig. 5 Variations of number concentration of oil droplets with asphaltenes þ resins content (ARC).

Fig. 4 for both experimental temperatures. The concentration of droplets decreases rapidly when oil viscosity increases. It should be noted that the decrease in droplet number is not continuous for the entire range of oil viscosity ratio (Fig. 4). The gradient is more pronounced at low values than at high values of viscosity ratio. As shown in Fig. 4, experimental data may be represented by two separate curves C1 and C2. Both of these curves are described by the power law of b the form aðld =lc Þ . For C1, a ¼ 0:26 and b ¼ 0:96, and for C2, a ¼ 0:90 and b ¼ 0:32. One possible reason for the different behaviors between low and high viscosity may be due to differences in the rheological properties of oil droplets at low and high viscosity ratios. Oils with high viscosities behave as non-Newtonian fluids, contrary to the ones having low viscosities. More data are needed to cover the intermediate viscosity ratio values between 5 and 300. Additional data are also needed to verify the proposed trend at high viscosity ratio. Volume concentration of oil droplets stabilized by clay particles was investigated to verify the trends shown in Fig. 4. The volume concentration is calculated from the sum of elementary volumes of oil droplets. The volume of each droplet is estimated considering its geometry. Droplets with form factor <0.7 were considered to have cylindrical shape. The height of the cylinder is approximated by the measured maximum length Lmax of the droplet, and the diameter of its base is calculated by A=Lmax . All other droplets were considered to have a spherical shape with a diameter equal to the equivalent diameter of the area of the droplet. Interestingly, the variations of volume concentration with viscosity follow a similar trend as number concentration, (data not plotted). Furthermore, the fact that no influence of viscosity on the mean size of oil droplets was observed (Fig. 3), it is

suggested that the changes in volume concentration with viscosity are related to changes in the number of oil droplets rather than to their sizes. Regarding temperature effects, it appears from data presented in Fig. 4 that the effect of temperature on the number of oil droplets stabilized by mineral particles is determined by the temperature influence on oil viscosity. However, when the effect of asphaltenes– resins content (ARC) (hereafter referred to as ARC) of the oil is considered, the influence of temperature on the number of droplets becomes clearer (Fig. 5). The droplet concentration correlates with the ARC of the oil. It decreases rapidly with increasing ARC concentration. The trends in the data at the two operating temperatures are similar. Curves C3 and C4 shown in Fig. 5 are represented by the same equation of the form:

Spill Science & Technology Bulletin 8(1)

Nt ¼ aðT ÞWar0:64

ð7Þ

where Nt is the total number of droplets in 107 /ml, War is the weight percent of asphaltenes and resins in the oil, and a is a function describing the effects of the temperature T . At temperature 0 and 20 °C, a equals 0.35 and 1.13, respectively. It is generally accepted that ARC have a large influence on viscosity of crude oils. This is clearly illustrated in Fig. 6, where the viscosity ratio is shown to increase exponentially with ARC. The effect of temperature is once again evident. Curves C5 and C6 are described with the same exponential function: ld ¼ bðT ÞecðT ÞWar lc

ð8Þ

where b and c are functions dependent on the temperature T . For T equals 0 and 20 °C, their numerical 25

A. KHELIFA et al.

lated using the procedure discussed previously, and oil density. The data shown in Fig. 7 were fitted using least squares method. The best fitting is shown by the solid line, which is represented by the following equation: ld 0:22 Wo ¼ 0:3e3:23ð lc Þ War

Fig. 6 Variations of viscosity ratio with asphaltenes þ resins content (ARC).

values are b ¼ 0:168 and c ¼ 0:35, and b ¼ 0:085 and c ¼ 0:29, respectively. Results presented in Figs. 4–6 show how concentration of oil droplets, viscosity ratio and ARC are interrelated, and how temperature affects their relationships. The break in the correlation shown in Fig. 4 between low and high viscosity conditions is not observed in Figs. 5 and 6 at the corresponding conditions of low and high ARC, suggesting that a unique correlation function should represent the entire range of data shown in Fig. 4. Such a function is depicted in Fig. 7 where the dimensionless mass concentration of oil droplets Wo normalized with ARC (War ) of the oil is shown to correlate well with the viscosity ratio regardless of temperature. Dimensionless mass concentration Wo is a ratio between the mass of oil stabilized by OMA and the initial mass of oil introduced in the system. The mass of oil stabilized by OMA is a product of volume concentration of droplets, calcu-

°C °C

Fig. 7 Variations of the ratio Wo =War with viscosity ratio. 26

ð9Þ

This equation shows how viscosity ratio and ARC affect the amount of oil stabilized by minerals. For a given viscosity ratio, oils with high ARC are trapped more efficiently in OMA than those containing less ARC. This is in agreement with what many investigators have observed under various conditions of oil– mineral interaction (Menon & Wasan, 1986; Bragg & Owens, 1994; Owens et al., 1994; Bragg & Yang, 1995; Guyomarch et al., 1999; Owens, 1999). However, it is worthwhile to note that oils with high ARC also have high viscosities (Eq. (8)). These viscous oils necessitate more energy to break into small droplets than oils with low viscosity. It is evident that, under low agitation energy, the viscosity of the more viscous oils is the dominant factor controlling the rate of OMA formation and the effect of oil chemistry can be neglected, as Wood et al. (1998) have reported, because this rate is essentially dictated by the rate of droplet formation. However, under high agitation energy, as in many nearshore environments, once the droplets are formed, the chemistry of oil becomes a key factor that controls the rate of OMA formation, as shown in Eq. (9). It is important to note that concentration of minerals is also a dominant factor controlling the rate of OMA formation. Its effect is not shown in Eq. (9) because the concentration of minerals was not varied in this study. Thus, effects of agitation energy (turbulence) and mineral concentration on the rate of OMA formation are controlling factors that need to be integrated in Eq. (9). This is beyond the scope of the present work and it calls, perhaps, for further experimental investigations. In summary, the experimental data presented here indicate that the concentration of oil droplets is affected essentially by viscosity ratio, ARC (Eq. (7)) and temperature. Temperature affects viscosity ratio as shown by Eq. (8), and the ARC-normalized concentration of mineral-stabilized oil droplets as a function of viscosity ratio is expressed by Eq. (9). Further investigations are needed to show how the functions a, b and c in the above equations are related to temperature. Variations of number concentration of oil droplets with oil–water interfacial tension (r) show no obvious trend when r varies between 8 103 and 30 103 N/m (Fig. 8). Nevertheless, a point with high value of Spill Science & Technology Bulletin 8(1)

CHARACTERISTICS OF OIL DROPLETS STABILIZED BY MINERAL PARTICLES

°C °C

Fig. 8 Variations of number concentration of oil droplets with interfacial tension at 0 and 20 °C.

r (about 78 103 N/m) shows a strong decrease of droplet concentration. Further data are needed to fill the gap shown in Fig. 8 and establish possible correlation between droplet concentration and r. We believe that droplet concentration decreases with oil– water interfacial tension. Size distributions of oil droplets Measured size distributions of oil droplet stabilized by mineral particles at temperatures 0 and 20 °C are shown in Fig. 9a and b, respectively. The trend, N  D2:3 , found by Delvigne et al. (1987) and reported in Delvigne and Sweeney (1988), as well as the trend of the envelope curve, N  D3 , observed by Muzzio et al. (1991) are also plotted in these figures. The measured curves with different types of oil at the two temperatures show evidence of self-preserving size distributions of oil droplets. The envelope curve observed by Muzzio et al. fits better the present data for droplets with equivalent diameter above 8 lm than the trend found by Delvigne and Sweeney. However, both trends appear inadequate to describe the measured data at smaller diameters. Further analysis of measured oil droplet size distributions using dimensionless variables leads to the recognition of N =Nt and D=D50 , where D50 is the mean diameter of the droplets, as the key dimensionless variables to describe the self-similarity in droplet size distributions. The curve fitting the size distribution data, expressed in term of these dimensionless variables as shown in Fig. 11, is described by the following equation:     N D D log ¼ 0:76 log3  2:9 log2 Nt D50 D50   D  0:51 log  0:35 ð10Þ D50 Spill Science & Technology Bulletin 8(1)

Fig. 9 Size distributions of oil droplets stabilized by mineral particles at 0 °C (a) and 20 °C (b).

°C °C

Fig. 10 Self-similar size distributions for oil droplets stabilized by mineral particles at 0 and 20 °C.

It must be noted that this equation fits the data obtained with all the oils tested and at the two operating temperatures 0 and 20 °C. The data shown in Fig. 10 were also fitted to lognormal distribution using least 27

A. KHELIFA et al.

Conclusion

°C °C

Fig. 11 Cumulative size distributions of oil droplets stabilized by mineral particles at 0 and 20 °C: comparison with published data.

squares method. The best fitting shown by the dashed line was obtained with mean and standard deviation of the size ratio (D=D50 ) of 0.43 and 0.78, respectively. This finding shows that, besides the shape of the similarity curve shown by Eq. (9), Nt and D50 are the only oil droplet characteristics that are affected by the dimensional variables (Eq. (4)) controlling the formation of the droplets. However, the phenomenological behavior shown by the above equation was investigated under constant shaking energy. Turbulence may have important effects on Nt and D50 , as shown by Delvigne et al. (1987) and Delvigne and Sweeney (1988). For comparison purposes, the measured cumulative size distributions of oil droplets stabilized by clay particles are plotted in a dimensionless form in Fig. 11, along with data reported by Delvigne and Sweeney (1988), and Lunel (1993). The distributions measured by Delvigne and colleagues were obtained without sediment during their breaking-wave experiment in a small-scale wave flume (15 m long, 0.5 m wide, water depth of 0.43 m). Lunel has studied size distributions of oil droplets in the laboratory and at sea. Most of his observations were made for chemically dispersed oil slicks. He showed that the droplet size distributions measured with and without dispersant were very similar. Two of his data sets were obtained during sea trials using Slickgone NS as the oil dispersant and either Forties crude oil or medium fuel oil (MFO). The third data set (ST Final), was produced using the Swirling Flask test in the laboratory. All the data presented in Fig. 11 plot along similar curves, regardless of the different conditions of oil droplets formation. This observation confirms the relevance of the dimensionless variables N =Nt and D=D50 to describe droplet size distributions. 28

Characteristics of oil droplets stabilized by the process oil–mineral aggregation were investigated in the laboratory. OMA were formed in seawater with a mixture of natural mineral fines at a pre-defined energy level with eight different oils, and at two temperatures. For negatively buoyant OMA it was concluded that: 1. On average, oil droplets are spherical regardless of oil type and temperature. In term of distribution, their shapes follow a common trend. Large numbers of deformed (elongated) droplets were observed. The deformation is more pronounced at a temperature 20 °C than at 0 °C. 2. Mean and maximum sizes of oil droplets are not dependent on oil viscosity. 3. The number of oil droplets is strongly correlated with viscosity ratio, temperature, and ARC. Correlation between number concentration and viscosity ratio shows different trends for low and high viscosity ratio, possibly due to differences in rheological properties of the oil tested. Correlation between number concentration and ARC shows a single trend with a magnitude significantly affected by the temperature (Eq. (7)). Viscosity ratio increases exponentially with ARC (Eq. (8)). 4. Mass concentration of oil droplets normalized to ARC is represented by a single function of oil viscosity ratio (Eq. (9)) regardless of the operating temperature. 5. Self-similarity in size distributions of oil droplets is shown. A single function describes all the data when size distributions are presented in a dimensionless form N =Nt ¼ f ðD=D50 Þ. Experimental data are well represented by Eq. (10). 6. Comparison with published data showed that normalized cumulative size distributions of mineral-stabilized oil droplets are similar to those of mineral-free oil droplets formed under field and laboratory conditions. It is important to note that results presented in this paper where obtained under controlled laboratory conditions with a mixture of mineral fines at a constant specific energy level and test oil concentration. Further work is needed to quantify the effects of these factors on the size of mineral-stabilized oil droplets. In such investigation, it is suggested to consider Eq. (5) to clarify the role of the dimensionless variable Nr . The effects of these factors on Nt and D50 need also to be investigated to show how the results of this study apply to different mixing conditions. The viscosity effect on the mean and maximum sizes of oil droplets is not yet fully understood. It is not clear from this Spill Science & Technology Bulletin 8(1)

CHARACTERISTICS OF OIL DROPLETS STABILIZED BY MINERAL PARTICLES

study if the observed negligible effect of viscosity on these characteristics is just a consequence of the presence of the solid phase, or is related to the procedure used to agitate the samples, or to some other mechanisms. However, one should note the similarity in size distributions between the results of the present study and those obtained in previous field trials and laboratory investigations. Of particular importance, this study has shown that, even with the relatively low mineral concentration of 100 mg/l and a moderate shaking energy, OMA formed readily with various types of oils. The mass of oil dispersed by OMA can be quantified using Eq. (9), if the viscosity ratio, the asphaltenes þ resins content and the mass of spilled oil are known. With such empirical relationship, it becomes possible to integrate the contribution of OMA to oil dispersion in future generation of numerical models to simulate fate and transport of oil spills. Eq. (9) suggests that this contribution may not be negligible, as it can be calculated (Eq. (9)) that it represents about 80% of spilled oils of low viscosities, as Federated crude oil, and about 24% for more viscous oils, such as Maya weathered at 9%, for a temperature of 20 °C. Acknowledgements—This work is supported by the Atlantic Canada Petroleum Institute, the Research and Development Fund of the Canadian Coast Guard and the Panel of Energy Research and Development (PERD) of Canada. We thank Zhendi Wang, (Emergencies Science and Technology Division, Environment Canada) for providing the oil tested in this study and Jay Bugden and Jennifer Dixon (Marine Environmental Science Division, Fisheries and Oceans Canada) for technical support.

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Stoffyn-Egli, P., Lee, K., 2002. The observation and characterization of oil–mineral aggregates. Spill Science and Technology Bulletin, this issue. van der Zande, M.J., van den Broek, W.M.G.T., 1998. Break-up of Oil Droplets in the Production System. In: Proceedings of the 1998 ASME Energy Sources Technology Conference, Houston, USA. Weise, A.M., Nalewajko, C., Lee, K., 1999. Oil–mineral fine interactions facilitate oil biodegradation in seawater. Environmental Technology 20, 811–824. Wood, P.A., Lunel, T., Daniel, F., Swannell, R., Lee, K., StoffynEgli, P., 1998. Influence of Oil and Mineral Characteristics on Oil–Mineral Interaction. In: Proceedings of the 21st Arctic and Marine Oilspill Program (AMOP) Technical Seminar, Ottawa, Ont., pp. 51–77. Yan, N., Masliyah, J.H., 1995. Characterization and demulsification of solids-stabilized oil-in-water emulsions. Part 1. Partitioning of clay particles and preparation of emulsions. Colloids and Surfaces 96, 229–242. Zurcher, F., Thuer, M., 1977. Rapid weathering processes of fuel oil in natural waters: Analyses and Interpretations. Environmental Science and Technology 12 (7), 838–843.

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