biostimulation and natural attenuation of oil spills in ...

nd

2 Mercosur Congress on Chemical Engineering 4 Mercosur Congress on Process Systems Engineering th

BIOSTIMULATION AND NATURAL ATTENUATION OF OIL SPILLS IN PATAGONIAN SOILS. CHARACTERIZATION BY CC, GC, AND UV-VISIBLE SPECTROSCOPY S. M. Ríos1, N. Nudelman2 * 1

Department of Chemistry. Universidad Nacional de la Patagonia San Juan Bosco Department of Organic Chemistry, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires .

2

Abstract. The degree of compositional changes in oil spills in Patagonian soils was determined by using column chromatography (CC), gas chromatography (GC), and UV-visible spectroscopy. Several compositional indexes were calculated. The index (Aliph+Aro)/Pol of the residues and crude oil were evaluated by means of CC data: residues with stimulated biodegradation showed lower indexes than the nonassisted residues. An increase in the index on aging was observed, the rate of the degradation decreases along the time, so the concentration of the aliphatic components tend to become constant while that of the polar ones decrease. A differentiated behavior of indexes such as: nC17/Pristane, nC18/Phytane, and others between biostimulated and no biostimulated residues were observed by GC, because they take into account some nalkanes which are the mainly biodegraded. On the other hand, the average retention time (ART) index shows that, from a global point of view, the residues increase their molecular weights mainly as a function of the exposure time, but not as a function of the biostimulation conditions. The ART index are between 21 minutes for the crude oil and 27 minutes for the older residue. The UV-visible spectra show that when the exposure time increases, the absorption moves progressively to longer wavelengths, probably by an increase in the number of condensed rings, this suggests an enrichment of polynuclear aromatic concentrations in the remaining residues. The chemical shifts of the maximum absorbance of the UV-Visible spectrum were λ= 1 220 nm for the crude oil and λ= 300 nm for the older residue. The application of H-nuclear magnetic resonance (NMR) spectroscopy as a non-conventional technique for the analysis of oil samples and some preliminary results are also briefly commented. Evaluation of the different indexes significance was carried out by the principal components analysis (PCA) methodology. The results indicate the usefulness of the determined parameters for quantifying the degree of transformations of the oil residues and for the modeling of their environmental impact on Patagonian soils.

Keywords: Petroleum residues, natural attenuation, biostimulation, Patagonian soils, modelling. 1. Introduction When petroleum is spilled in soil, its components undergo various physical and chemical modifications: evaporation, biodegradation and photooxidation are among the major factors contributing to the removal of the hydrocarbon molecules from the geosphere. Several models to predict compositional changes are currently been proposed, most of them use gas chromatography (GC) data, essentially based on the identification of chemical groups and the evaluation of their enhancing/retarding effects on degradability.

*

To whom all correspondence should be addressed. Address: Department of Organic Chemistry, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires. Pab II. Ciudad Universitaria.1428.Buenos Aires. Argentine. e-mail: [email protected]

1

nd


The hydrocarbons environmental fate determined by GC, show two types of group parameters. Ratios of compound concentration that decrease at the same rates retaining the initial oil signature until they can not longer be detected (Burg et al., 1995; Douglas et al., 1996). These ratios are termed “source” ratios (Garrett et al., 1998; Faure et al., 2000); and can be contrasted to ratios that change substantially with weathering and biodegradation, which are termed “weathering’ ratios (Stout et al., 2001; Barakat et al., 2001; Braddock et al., 2003). Two “weathering’ ratios are n-C17/Pristane concentration

of

the

aliphatic

compounds

and

n-C18/Phytane, where Pristane and Phytane are the

2,6,10,14-tetrametylpentadecane,

C19H40,

and

2,6,10,14-

tetrametylhexadecane, C20H42, respectively (De Jonge et al., 1997). These indices evaluate the relative biodegradation of n-alkanes, it is know that n-alkanes are degraded more rapidly than branched alkanes (Dutta and Harayama, 2001). Low values for n-C17/Pristane and n-C18/Phytane indices suggest high degradation. In addition, saturated pentacyclic triterpane biomarker compound C30-17α(H),21β(H)-hopane is an internal reference marker, too, because it is a natural petroleum component and it remains unchanged during environmental exposure.(Douglas et al., 1996; Bragg et al., 1992). Another index is the Total Resolvable Hydrocarbons (TRHC), that is the sum of nC10-nC35 alkanes plus Phytane and Pristane that are resolved as specific peaks. The ratio between TRHC and the Total Extractable Hydrocarbon (TEH) is a measure of the increase of the unresolved complex mixture (UCM). Changes in global residues volatility and molecular weight may be also estimated by the Average Retention Time (ART), that is calculated by average of the retention times in the GC chromatogram. The UV-visible spectrum of the residues, that depends on the electronic structure of the molecules, is also an additional useful technique. In practice, UV spectrometry is normally limited to conjugated systems. There is, however, an advantage to the selectivity of UV absorption: a large portion of a relatively complex mixture of molecules may be transparent in the UV-visible region so that it may obtain a spectrum similar to that of a much simpler molecules (Silverstein et al., 1991). It is know that the main conjugated systems in crude oil and its residues are aromatic compounds. Polynuclear aromatics might well be treated as individual chromophores and a correlation between the bands of benzene originated from π→ π* transitions (E2 band: λmax = 204 nm, εmax = 7900) and others, such as naphthalene (λmax = 221 nm, εmax = 133000; λmax = 286 nm, εmax = 9300) or anthracene (λmax = 256 nm, εmax = 180000; λmax = 375 nm, εmax = 9000) can be made. Nuclear magnetic resonance (NMR) spectroscopy is one of the more powerful spectroscopic analytical techniques for the characterization of organic compounds complex mixtures; it can be applied to high molecular weight fractions and to hydrocarbon mixtures. (Dutta and Harayama, 2001; Hairber and Buddrus, 2002). We have recently started the application of 1 H NMR spectroscopy to the study of hydrocarbons in crude oil and in oil residues in soils, the preliminary results indicate that this is a very promising tool for the characterization of the attenuation of oil spills in the environment. (Ríos and Nudelman, 2005) The goal of this study was to evaluate the natural attenuation of contaminated oil spills soils by the use of parameters that quantify the degree of compositional change and compare these results with assisted (fertilized or stimulated) degradation oil spilled soils in the Patagonian environment. Several parameters, mainly determined

2

nd


by column chromatography (CC), gas chromatography (GC) and UV-visible spectroscopy were used to determine the compositional indexes.

2. Experimental 2.1. Crude Oil Characteristics Lacustrine shales of the Pozo D-129 Formation, are the oil bearing sandstone of the middle to late Cretaceous of the Golfo San Jorge Basin. The crude oil was analyzed by silica gel column chromatography to separate group components (i.e. aromatic, aliphatic and polar compounds). Three fractions of different chemical nature were separated: aliphatic (41%), aromatic (35%) and polar (17%) fractions. The numbers in brackets give the percent composition by weight of the crude oil. The portion remaining in the column contains the asphaltene fractions (Nudelman et al., 2000). 2.2. Sample Characteristics In the present work, soil samples contaminated by oil spills in eleven different locations in the surroundings of Comodoro Rivadavia's city, were analyzed. Some properties of the samples are summarized in Table 1. The oil spills were of different ages, crude oil sources and environmental exposure conditions. In all cases, except for the samples 1 and 6-11, fertilization and/or mechanical mixed of the affected areas was carried out to improve the general conditions of the land, and to favor reforestation of species adapted to the zone. This process is known as biostimulation. Table 1. Characteristic of the Residue Samples

N°

1 2 3 4 5 6 7 8 9 10 11

Place

CS CR PT CO CO BV DA DA DA DA DA

a

Bios

No Yes Yes Yes Yes No No No No No No

b

Age (years)

Conductivity b,c µmhos/cm

20 10 6 3 3 2 57 37 22 10 7

9364 1633 646 618 387 426 610 230 700 530 1500

pH

c,d

7.6 7.4 8.0 7.4 7.6 6.8 6.9 6.8 7.4 7.4 7.2

Clay e s % p/p 33 22 9 8 12 16 13 6 8 11 24

Total 25.8 16.6 8.7 8.6 9.3 16.1 11.4 9.0 6.5 8.6 10.0

Petroleum % p/p f f f f Alif Aro Pol Asph 32.2 33.1 35.0 21.0 25.0 28.2 35.1 40.2 37.3 46.0 35.0

31.1 39.0 35.0 19.7 28.0 27.8 32.3 32.7 29.5 29.0 33.0

36.7 28.0 29.0 58.7 39.0 43.0 32.5 27.1 25.8 19.0 28.0

0.0 0.0 1.0 0.6 8.0 1.0 0.1 0.1 7.4 5.0 4.0

a

BV Bella Vista, CR Comodoro Rivadavia, CS Cañadón Seco, PT Pico Truncado, CO Caleta Olivia, DA b c d e f Diadema Argentina biostimulation, extract 1/5 wt/wt, 25°C, soil without petroleum , Alif: aliphatic, Aro: aromatic, Pol: polar and Asph: asphaltenes.

3

nd


All samples were extracted from the surface, except in the case of sample 1 that was extracted to a depth of 20 cm to evaluate the most aged residuals. The contamination reached until that depth, since more recent oil residuals were overturned on the same land. Therefore, the estimation of the age of the sample is approximate (INTA, 1998). 2.3. Column Chromatography The total hydrocarbon determination in each sample was carried out by Soxhlet continuous extraction with methylene chloride. A glass column was filled with a slurry of activated silica gel suspended in n-hexane. The crude oil and each residue samples was loaded and the column was successively eluted with n-hexane, benzene and chloroform:metanol (1:1). The fractions eluted with these solvents are called aliphatic, aromatic and polar respectively (Nudelman, 2002). Each fraction was evaporated, and the residual oil was determined by gravimetric measurement (Table 1). The portion remaining in the column contains the asphaltene fraction. 2.4. Gas Chromatography . Samples of crude oil and of residues 1, 2, 4, 7, 9, 10 were selected for GC analysis. Samples 1 and 9 are of the same age, the sample 9 was taken from the surface. Residues 2 and 10 are also of the same age but only residue 2 undergone assisted degradation; samples 4 and 7 are residues of different ages. Gas chromatography (GC) was determined on a Konic 3000 gas chromatograph, equipped with a J & W DB1 fused silica column (30 m X 0.25 mm i.d.), split/splitless capillary injection system, and a flame ionization detector (FID). The samples were analyzed in the splitless mode using nitrogen as carrier gas. The injector and detector temperature were maintained at 250 ºC and 320 ºC, respectively. The oven temperature was programmed from 60 ºC (2 min hold), 135 ºC (2 min hold), and 185 ºC (2 min hold) at a rate of 5 ºC/min, to a final temperature of 290 ºC at rate of 5 ºC/min. The identification of resolved aliphatic hydrocarbons was made by comparing retention times with the corresponding standards (Chem Service). Resolved aliphatic hydrocarbons and unresolved complex mixtures (UCM) were calculated using the mean response factors of n-alkanes. For each sample, the individual n-alkane concentration from n-C9 to n-C30, the isoprenoid pristane and phytane concentration and the total resolved n-alkanes, were calculated (Commendatore et al., 2000). Prior to GC analysis, the separation of the asphaltene fraction of each residue was achieved with n-pentane (Speight, 1991).

2.5. UV-Visible Spectrometry UV-Visible spectra, using hexane as the solvent, were recorder by a HP-845 1A double arrangement diode spectrophotometer with automatic scan between 190-800 nm.

3. Results and Discussion 3.1. CC Parameters 4

nd


Figure 1 shows the index (Aliph+Aro)/Pol of the residues and crude oil. As it is exposed to the environment, the aliphatic fraction decrease due to the loss by volatilization and biodegradation while the polar fraction decreases, mainly due to lost by solubilization (Sugiura, 1997; Garrett, 1998).

(Alif + Aro) / Pol

5

0 age (years)

0

60

Fig. 1. Index (Alif+Aro)/ Pol as a function of the exposure time, samples: 1, and 6-11 (circles), samples 2-5 (white triangles) and crude oil (black square).

But, polar compounds could, additionally be formed through to aliphatic biodegradation and photooxidative processes of aromatics (Maki, 2001). This is consistent with the ratio (Aliph+Aro)/Pol observed for the youngest degraded environmental samples. Residues with biostimulation (samples 2-5) showed lower indexes than the other residues (samples 1 and 6-11). Since the degradation rate decreases along the time the concentration of the aliphatic components tends to become constant while the polar ones decrease due to their higher solubility. Therefore, an increase of the ratio (Aliph+Aro)/Pol is expected with age and the ratio (Aliph+Aro)/Pol tends to be come constant as it is observed. This result could be interpreted as a likely indication of the compositional stabilization. 3.2 GC Parameters Figure 2 (a) shows the gas chromatogram (fingerprint) of the crude oil. The higher intensities correspond to nalkanes (n-C9 to n-C30), prystane, and phytane. The hump is caused by the overlapping of components peaks with low individual concentrations and similar volatility, we called it “unresolved complex mixture’ ( UCM). The chromatogram shows, mainly, low molecular weight components with unimodal UCM, below of the full resolved compounds with a declination starting in n-C26. Volatilization, biodegradation, partitionining into water, and photodegradation alter the component profile of crude oil exposed to the environment (Short, 1997). N-alkanes are considerably more biodegradable than branched alkanes and alkyl aromatics, their peaks in the profile quickly attenuate. Lower boiling components are more biodegradable, more water-soluble, and more volatile than higher weight components, therefore they are moved from the mixture sooner. The effect of this “weathering” process is that the component profile shifts to

5

nd


the higher boiling range and loses the regularly spaced n-alkanes peaks (Douglas et al., 1996; De Jones et al., 1997).

(b )

250 0

Int.

C 10

C 12

C2 C2

C 14

200 0

C2

3

C2

4

C2 5 C2

1

0

6

C2

C 16

Fit a no Pr i st a no

C 18

7

C2

9

C3

0

M C NR

C 20

0

5

10

15

20

25

30

35

40 t ie m po d e re4t5en c ió n5 0

C 22

150 0

Phytane Fita no

Prista no Pristane

C 24

100 0

C 26 C 28

50 0

C 30

(a )

M C NR UCM 0 0

10

20

t, m in

30

time em po d e r ete nc ión 4 0tiretention 50

Fig. 2. (a) Gas chromatogram of crude oil. Insert (b) GC of an oil residue in soil of 57 years of exposure. UCM means Unresolved Complex Mixture.

Then, UCM mass tends to increase during the environmental exposure due to the formation of products of the degradable original components. The insert in Figure 2 shows a gas chromatogram of the sample 7 (57 years) . Note the exaggerated hump in the weathered residue. This becomes a predominant feature as the n-alkanes are selectively removed from the mixture. The chromatogram shows, mainly, high molecular weight components with unimodal UCM, the declination starts at n-C15, and a maximum between n-C21 y n-C25.. Indexes n-C17/Prystane and n-C18/Phytane for crude oil and residues as a function of the environmental exposure time are showed in Figure 3. It can be observed that all of them decrease, compared with crude oil (time = 0, y axis). Residues with stimulated biostimulation (samples 7, 9 and 10) show lower indexes than the noassisted residues (samples 2 and 4). The gas chromatogram for sample 1 shows no defined peaks for n-C17, n-C18, pristane, and phytane, and similar degradation rates for n-alkanes and branched alkanes. This is in disagreement with the global tendency of the superficial samples, it may be due to the different exposure conditions.

C 17/Pris C18/Phy

10

1

0,1

0,01 0

Aged, years

60

Fig. 3. n-C17/Pristane (black) and n-C18/Phytane (white), samples 7, 9 and 10 (circle), sample 1 (triangle), samples 2 and 4 (square) and crude oil (triangle on y axis).

6

nd


The difference in both indexes increases when the exposure time increases, suggesting than C17 degradation rate is greater than C18 rate, if Pristane/Phytane (Pri/Phy) ratios are constant during the time period evaluated (Pri/Phy, 0.810 ± 0.320). Pri/Phy values close to 1.0 indicate petroleum-derived hydrocarbons and values from 1.4 to 6.7 indicate biogenic hydrocarbons (Commendatore et al., 2000). Figure 4 shows the indexes TRHC/TEH for crude oil and residues, where TRHC is total resolvable hydrocarbons and TEH is total extractable hydrocarbons, as a function of the environmental exposure time. The indexes decrease, suggesting an increase in the UCM during the exposure time. This decrease is similar to the decrease in n-C17/Pristane and n-C18/Phytane, but three important differences exist. First, the y axis in Figure 3 is logarithmic, this may be indicative of a probable first order kinetics, that is one of the kinetics proposed for the interpretation of the biodegradation data (Dragun, 1998); while y axis in Figure 4 is linear, suggesting a constant preference of n-alkanes degradation compared with other crude oil components. Secondly, the slopes of the Figure 2 are different for assisted degradation residues than for non-assisted degradation residues, showing differences in velocity rates. While in Figure 3 the slopes are similar, suggesting a constant preference of nalkanes degradation in both type of residues. And third, sample 1 shows an anomalous behavior in Figure 3, but not in Figure 4, this suggest that the global degradation of the n-alkanes is a general tendency, although, the degradation rates of n-C17, n-C18, pristane and phytane are different for superficial and not superficial samples. 28

ART, minutes

1,5

(b)

TRHC/TEH

20 0

Aged, years

60

(a)

0 0

Aged, years

60

Fig. 4. TRHC/TEH (a) and ART (b) as a function of the exposure time, samples 7, 9 and 10 (black circle), samples 1, 2 and 4 (white triangle) and crude oil (black square)

The average retention time (ART) as a function of the environmental exposure time is shown in Figure 4 (b). The average retention times are between 21 and 27 minutes and the increase in ART with exposure time is in agreement with loss of the lower boiling range hydrocarbons. The nC17/Pristane, nC18/Phytane, and TRHC/TEH indexes take into account volatile n-alkane, which are those more easily biodegraded; therefore, the naturally 7

nd


attenuated residues exhibit a different behavior from those that have been biostimulated. On the other hand, the ART index considers all compounds detected by GC, the plot in Fig. 4b shows only one line suggesting that, from a global point of view, the molecular weight of the residues increases mostly as a function of the exposure time, being apparently independent of the biostimulation conditions. 3.3. UV-visible spectrum Figure 5 shows the UV-Visible spectrum of the samples 1-6 and of the crude oil. When the exposure time increases, the absorption moves to progressively longer wavelengths, probably by an increase in the number of condensed rings, this suggests an enrichment of polynuclear aromatic concentration in the remaining residues. 3

Ab so rb ance

Absorbance

(a )

(c and d )

(e )

(b )

(f)

(g )

0 20 0

w a ve len g th , n m

35 0

Fig 5. UV-Visible spectra of the crude oil (a), sample 1 (g), 2 (f), 3 (e), 4 (d), 5 (c), and 6 (b), in hexane.

In crude oil (a), aromatics with few benzene rings may be the main components, but when the exposure time increases due to the recalcitrant characteristics of the polynuclear aromatics they are not altered and remain in the residue. Note that samples 4 (d) and 5 (c) have the same spectra, both have three years of exposure and biostimulation conditions. 3.4. Principal component analysis, PCA The following determinations: i) the percentage of fractions (Ali %, Aro %, Pol %) shown in Table 1 and ii) the GC indexes were used in the principal component analysis (PCA). In its basic form, PCA is a transformation of a set of variables into a new set of variables which are uncorrelated with each other. Thus, a large number of correlated variables are transformed into a small number of uncorrelated variables, that describe the most important trends. These new variables are called “principal components” (PC) and often account for a large number of the total variance in the original data material (Brandyik and Daling, 1998). Each parameter was previously normalized to eliminate the influence of their varying magnitudes on the analysis. The first two principal components (PC1 and PC2, respectively) accounted for more than 99 % of 8

nd


variance, and they were used to generate the factor score plot shown in Figure 6. No pre-classification of the residues was performed; thus oils exhibiting similar parameters become plotted near one to the other. PC1 and PC2 components represented 77% and 22%, respectively, of the total variance among the residue samples; they are expressed in this two-dimensional plot. 10*

57 P C2

10 0

22

3*

20# PC1

Fig 6. Principal components factor score plot (1st vs. 2nd PC). Labels show the age of the spill. The line shows the evolution with the time in natural attenuation. The points for biostimulated degradation and non-superficial sample are shown by * and #, respectively.

The Euclidean distances between the samples plotted in the score plot represent real and defensible differences in the parameters indexes among the residues. PC1 is largely influenced by TRHC/TEH, Pol % and nC18/Phytane in this order, while PC2 is influenced by nC17/Pristane, Aro %, nC18/Phytane and Alif %, respectively. The line shows the evolution with the time in natural attenuation. Note that samples with 3 and 10 years are placed outside of the time line, suggesting that bioestimulation altered the natural attenuation. This may involve that the increase in degradation, may be to accelerate the compositional global changes. The sample of 20 years shown in the Figure, corresponds to a non-superficial sample. It is worth to be mentioned that in the PCA including data determined by 1H NMR spectroscopy, the PC1 is mostly influenced by the NMR data, suggesting that this methodology could be successfully used for a more detailed characterization of the environmental attenuation of oil spills in soils. (Ríos and Nudelman, 2005)

4. Conclusions The oil spilled soils in Patagonian environment were evaluated during long time, mainly by using gas chromatography (GC) and or combined GC-mass spectrometry (GC-MS) for component analyses, The GCdetectable compounds in crude oil are generally the more susceptible to biodegradation, but the global alteration of the crude oil components that are resistant to biodegradation could not be characterized by GC techniques. Therefore, UV-Visible and CC data have been also employed in the present study, to evaluate the total alteration including the non-volatile fraction in crude oil and its residues. The results suggest that the combination of a set of indexes obtained by several techniques is a more realistic overview to evaluate the degree of the 9

nd


environmental transformations of crude oil spilled in soils. This methodology allowed to show that biostimulation can be highly significant in the total evolution of the residues. In the score plot of the PCA analysis, points for the youngest biostimulated samples are close to the older non-stimulated samples. This conclusion has been reached by the combination of the GC and the CC indexes. The presence of polar compounds in the first years of the exposition may increase during the stimulation process, the generation of a great concentration of them could be expected in a relatively short period of time (shorter than in natural attenuation). This could have an undesired effect on the possibility of subsoil migration due to the increase in the water-soluble fractions. The presence of a not superficial sample with anomalous behavior in relation with superficial samples suggested a different fate of the components and the need to evaluate the real consequences of the biostimulation process in superficial and in the subsoil environment.

References Barakat, A. O., Qian, Y., Kim, M., Kennicutt M. C. (2001). Chemical characterization of naturally weathered oil residues in arid terrestrial environment in Al-Alamein. Egypt. Environ. Intern, 27, 291. Braddock, J. F., Lindstrom, J. E., Prince, R. C. (2003). Weathering of a subartic oil spill over 25 years: the caribou-poker creeks research watershed experiment. Cold Regs. Sci. Tech., 36, 11. Bragg, J., Prince, R., Wilkinson, J., Atlas, R. (1992). Bioremediation for shoreline cleanup following, the 1989 Alaskan oil spill. Consultants Report. Brandyik J., Daling S. (1998). Optimising oil spill dispersants as a function of oil type and weathering degree:;a multivariate approach using partial least squares (PSL). Chemom. Intel. Lab. Sys., 42, 73. Burg, P. H., Selves, J. L., Colin, J. P. (1995). Numerical simulation of crude oil behavior from chromatographic data. Anal. Chim. Ac., 317, 107. Commendatore, M. G., Estevez, J. L., Colombos, J. C. (2000). Hydrocarbons in coastal sediments of Patagonia, Argentina: levels and probable sources. Mar. Poll. Bull., 11, 989. De Jonge, H., Freijer, J. I., Verstraten, J. M., y Westervels, J. (1997). Relation between bioavailability and fuel oil hydrocarbon composition in contaminated soils. Environ. Sci. Technol. 31, 771. Douglas, G. S., Bence, A. E., Prince, R. C., Mcmillen, S. J., Butler, E. L. (1996). Environmental Stability of selected petroleum hydrocarbon source and weathering ratios. Environ. Sci. Technol., 30, 2332. nd

Dragun, J. (1998). The Soil Chemistry of Hazardous Materials, 2 Edition, Amhert Scientific Publishers, Massachusetts. Dutta, T. K., Harayama, S. (2001). Analysis of long-side-chain alkylaromatics in crude oil for evaluation of their fate in the environment. Environ. Sci. Technol., 35, 102. Faure, P., Landais, P., Schlepp, L., Michels R. (2000). Evidence for diffuse contamination of river sediments by road asphalt particles. Environ. Sci. Techonol., 34, 1174. Garrett, R. M., Pickering, I. J., Haith, C. E., Prince, R. C. (1998). Photooxidation of crude oils. Environ. Sci. Techonol., 32, 3719.

Hairber, S.; Buddrus, J. (2002). Isolated methyl groups as new structural parameters for Petroleum crudes. Fuel, 81, 981. 10

nd


INTA E.E.A. Chubut, E.E.A. (1998). Recuperación de Areas Disturbadas por la Actividad Petrolera en la Patagonia, Folleto de Jornadas de Campo. Maki, H., Sasaki, T., Harayama, S. (2001). Photo-oxidation of biodegraded crude oil and toxicity of the photo-oxidized products. Chemos., 44, 1145. Nudelman, N., Ríos, S.M., Katusich, O. (2000). Interactions between crude oil and Patagonian soil as a function of the soil clay-water contents. Environ. Technol., 21, 437-447. Nudelman, N., Ríos, S. M., Katusich, O. (2002). Organic cosolvent effect on the estimation of the equilibrium aqueous concentrations of the oil residuals in Patagonian Soils. Environ. Technol, 23, 9, 961 (a). Nudelman, N., Ríos, S. M., (2002). Interaction of oil residues in Patagonian Soil. In Interfacial Applications in Environmental Engineering, Ch. 10. Marcel Dekker Publication, U.S.A. (b). Ríos, S. M., Nudelman, N. (2005). Natural attenuation of oil spills in Patagonian soils. Characterization by

1

H NMR

Spectroscopy, Environ. Sci. & Technol., submitted. Short, J., Heintz, R. (1997). Identification of Exxon Valdez oil in sediments and tissues from Prince William Sound and the Northwestern Gulf of Alaska based on a PAH weathering model. Environ. Sci. Technol., 31, 2375. Silverstein, R. M., Bassier, G. C., Morrill, T. C. (1991). Spectrometric Identification of Organic Compounds. John Wiley and Sons, N.Y.. Speight, J. G. (1991). The Chemistry and Technology of Petroleum. Marcel Deccker, N. Y.. Stout, S. A., Uhler, A. D., McCarty, K. J. (2001). A strategy and methodology for defensibly correlating spilled oil to source candidates. Environ. Foren., 2, 87. Sugiura, K., Ishihara, M., Shimauchi, T., Harayama ,S. (1997). Physicochemical properties and biodegradability of crude oil. Environ. Sci. Technol., 31, 45.

Acknowledgements Thanks are given to O. Katusich (UNPSJB) for technical assistance, and to Mas Mirta (UNPSJB) for statistics help. Financial support from the University of Buenos Aires; the University of La Patagonia San Juan Bosco (UNPSJB) and from the National Research Council from Argentina (CONICET) is gratefully acknowledged.

11