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Article

Simulated Ageing of Crude Oil and Advanced Oxidation Processes for Water Remediation since Crude Oil Pollution

1
Department of Sciences, University of Basilicata, Via dell’Ateneo Lucano 10, 85100 Potenza, Italy
2
Department of Geography, Environmental Management & Energy Studies, University of Johannesburg, Johannesburg 2092, South Africa
3
Department of European Cultures (DICEM), University of Basilicata, 75100 Matera, Italy
*
Author to whom correspondence should be addressed.
Catalysts 2021, 11(8), 954; https://doi.org/10.3390/catal11080954
Submission received: 13 July 2021 / Revised: 30 July 2021 / Accepted: 4 August 2021 / Published: 10 August 2021

Abstract

:
Crude oil can undergo biotic and abiotic transformation processes in the environment. This article deals with the fate of an Italian crude oil under simulated solar irradiation to understand (i) the modification induced on its composition by artificial ageing and (ii) the transformations arising from different advanced oxidation processes (AOPs) applied as oil-polluted water remediation methods. The AOPs adopted were photocatalysis, sonolysis and, simultaneously, photocatalysis and sonolysis (sonophotocatalysis). Crude oil and its water-soluble fractions underwent analysis using GC-MS, liquid-state 1H-NMR, Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS), and fluorescence. The crude oil after light irradiation showed (i) significant modifications induced by the artificial ageing on its composition and (ii) the formation of potentially toxic substances. The treatment produced oil oxidation with a particular effect of double bonds oxygenation. Non-polar compounds present in the water-soluble oil fraction showed a strong presence of branched alkanes and a good amount of linear and aromatic alkanes. All remediation methods utilised generated an increase of C5 class and a decrease of C6–C9 types of compounds. The analysis of polar molecules elucidated that oxygenated compounds underwent a slight reduction after photocatalysis and a sharp decline after sonophotocatalytic degradation. Significant modifications did not occur by sonolysis.

1. Introduction

The composition of petroleum crude oil varies widely depending on the source and processing. Oil is a complex organic mixture counting for a high number of chemically distinct components, including unsaturated and saturated hydrocarbons, hetero-atoms (such as N, S, and O) and a minor percentage of metals predominantly vanadium, nickel, iron, and copper. Many oil constituents can be carcinogens, neurotoxins, respiratory irritants, hepatotoxins, nephrotoxins, and mutagens. Their toxic effects can be acute and chronic, causing many direct symptoms and major long-term injuries, including reproductive problems and cancer [1].
The hydrocarbon fraction can be as high as 90% by weight in light oils, compared to about 70% in heavy crude oil. A majority of the heteroatomic free constituents are side-by-side paraffinic chains, naphthalene rings, and aromatic rings. Heteroatomic compounds constitute a relatively small portion of crude oils, less than 15%. However, they have significant implications since their presence, composition, and solubility, which depend on the origin of the crude oil, can cause either positive or negative effects in the transformation processes and are of environmental concern [2,3].
A significant consideration of the several processes affecting the crude oil spilt into the environment is needed to clarify the effects of increasingly widespread harmful events and predict the future fate of the oil. For this reason, the awareness of such phenomena will prove to be a valuable resource in the effort to develop innovative remediation technologies. The ecological impact of oil contamination in different environmental sections (marine, terrestrial and atmospheric) is a source of severe concern. Extraction techniques, transportation and refinery treatments of crude oil can originate pollution phenomena due to the dispersion of these compounds everywhere. These problems have attracted significant attention to understanding the fate of oil in the environment and the natural mechanisms of oil degradation and transformation to suggest a method to reduce the damages caused by original and derivative products [4,5,6].
As all xenobiotic substances, crude oil undergoes biotic (biotransformation by aquatic organisms such as algae, bacteria) and abiotic (hydrolysis, oxidation, photodegradation) processes, giving rise to many derivatives. In the same way as their parent molecules, these transformation products can lead to the contamination of terrestrial and aquatic environments due to oil deposition on soil and into the surface- and ground-water. Nevertheless, they can be more persistent and toxic than the parent compounds [1,2,3].
Extensive literature is already available on the microbiological degradation of crude oil, which received considerable attention from researchers. For example, since 1975, the biodegradability of crude oils has been studied and found to be highly dependent on their composition and incubation temperature [5]. Researchers also examined the ability of microorganisms to degrade a high number of hydrocarbons of a different structure in petroleum [6]. Furthermore, many authors have elucidated that the lighter fractions can undergo degradation more rapidly than the heavier ones, e.g., n-alkanes degraded more quickly than branched alkanes, and aromatics with two to three rings readily biodegraded through several pathways [4,5,6,7,8].
Photochemical processes are also essential contributors to pollutants’ degradation and the removal of exogenous substances from the environment [9,10], especially in tropical and sub-tropical climates. In those areas, solar irradiation intensity is high, and the lack of nutrients hinders biological processes. Moreover, photochemical reactions are the primary cause of the compositional change of crude oil spilt in a marine environment [11,12,13]. Photolysis plays an essential role in the mousse formation that begins a few moments after an oil spill [12]. Due to sunlight, the interfacial tension of a crude oil film rapidly decreases, and chocolate mousse starts to form, which leads to the stabilisation of the water-in-oil emulsions [13,14]. The formation of emulsions seems to depend on the amount of asphaltene present in the oil film, and researchers reported that this amount increases upon irradiation [13]. Moreover, an increase in emulsion viscosity occurs due to the structural organisation of the asphaltenes [14].
The oxidised products resulting from the photochemical transformation significantly affect the viscosity, mousse formation, and weathered petroleum’s physical properties. Moreover, photo-oxidation can lead to the destruction of existing toxic components, the generation of new toxic constituents and the formation of water-soluble products [10,11,12,13,14].
Since crude oil settles on the surface of water and soil, it undergoes solar irradiation. Solar degradation is a natural way for petroleum decontamination, also suggesting that techniques based on light irradiation could be helpful to the petroleum degradation processes. Light irradiation-based technologies have been improved using catalysts, the most effective and cheapest water purification tool being titanium dioxide (TiO2) [15,16]. Researchers have exploited combinations of different advanced oxidation processes (AOPs) for environmental detoxification in the last years, especially for wastewater treatment. The so-called sonophotocatalysis (SPC), the simultaneous use of ultrasound (US) and photocatalysis (PC) by semiconductors to degrade organic pollutants in water (e.g., the effluent of dye works) has been investigated, but combined AOPs methods were not applied to oil-polluted water remediation to our knowledge [17,18,19,20,21,22].
Among the analytical techniques available for structurally determining crude oil components or metabolites, gas chromatography combined with mass spectrometry (GC-MS) has been the best choice so far and most widely used [23,24]. The fractionation of crude oil and subsequent GC-MS analysis has characterised nearly 300 components comprising aliphatic, aromatic, and biomarker compounds [25,26,27,28]. However, most crude oil fractions remain unidentified since many components cannot be resolved and appear as “hump” or “unresolved complex mixture (UCM)” in GC chromatograms [29,30].
Compositions of the saturated hydrocarbons have been better characterised by two-dimensional gas chromatography coupled to mass spectrometry [29] and liquid chromatography-mass spectrometry [31]. However, polar species appear poorly resolved due to their compositional complexity far exceeding the peak capacity of typical analytical techniques. High mass resolving power is necessary for the resolution of many compounds present in crude oil.
The development of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) had provided the needed ultra-high resolving power (m/∆m50% > 100,000, in which ∆m50% is peak width at half peak height), and the use of electrospray ionization (ESI) mass spectrometry had made possible to detect most polar species. Thus, the coupling of these two techniques, ESI and FT-ICR mass spectrometry, produces a powerful analytical tool for analysing these polar species without a preliminary chromatographic separation [32,33].
This work investigates the modifications that the artificial ageing induced on the composition of the polar fraction of an Italian crude oil (Basilicata region—Southern Italy, Val D’Agri countryside) under solar irradiation. Moreover, it explores the possibility of oil-polluted water remediation using AOPs, such as photocatalysis (UV + TiO2), sonolysis (US, ultrasound irradiation) and the simultaneous use of photocatalysis and sonolysis, i.e., sonophotocatalysis (UV + TiO2 + US).

2. Results and Discussion

The crude oil sample, collected from the Oil Centre sited in Val D’Agri (Basilicata), underwent simulated solar treatment. Information on the composition of the oil water-soluble fraction obtained through GC-MS, liquid state 1H NMR and FT-ICR-MS was the basis for this investigation. Liquid state 1H NMR spectroscopy accomplished helpful information on the oil composition. This technique recognised amounts of 59%, 19%, and 20% of total hydrocarbons as linear, cyclic (or branched), and aromatic compounds. NMR spectroscopy cannot discriminate branched from cyclic alkanes because both compounds have the same intramolecular environment. Figure S1 compares data obtained by NMR and GC-MS.
The use of real standards introduced by an electrospray ion source allowed the calibration of mass spectra. Recalibration was necessary for the identified homologous series in each sample [34]. A troubling complication in structural studies of crude oil has been its enormous complexity on a molecular scale. The ultrahigh-resolution of FT-ICR spectra can be highly complex: these spectra typically comprise many peaks at each “Nominal mass” and thousands of peaks in a whole spectrum. Each peak could represent a chemically diverse compound. This complexity poses an investigative challenge to the study of spectra for structural interpretation.
The univocal assignment of elementary composition, merely based on the high resolution and accuracy of the instrument, is not possible for all mass values. For values higher than 400–500 Da, it is necessary to validate the result differently. The Kendrick plot (Kendrick mass defect vs Kendrick Nominal mass or KMD vs KNM) offers an outstanding vehicle to visualise and categorise all of the peaks in a mass spectrum. Kendrick mass defect (KMD) breakdown has been effectively applied to ultra-high resolution mass spectra, consenting to categorise peaks into complex spectra based on their homologous similarities across a selected type of masses [35]. Bi-dimensional plots can discern compounds differing by masses associated with a structural unit (e.g., CH2, COOH, CH2O, etc.). In this drawing, the signals of structurally related moieties all lie on horizontal or diagonal straight lines. Such a method permits the extraction of peaks that are homogeneously associated. The method can effectively recognise groups of associated compounds in FT-ICR-MS of petroleum samples [36]. The compounds of the same homologous series (having a different number of groups CH2) will fall in a single horizontal line of the diagram (KNM), with peaks separated from 14 Da and no difference of KMD.
Similarly, the signals relating to compounds of the same class but of different types will occupy points on a vertical line of the diagram, separated by a difference of 0.013 in the Kendrick mass defect. The conversion of mass spectra from the IUPAC mass scale (based on the 12C atomic mass as exactly 12 Da) to the Kendrick mass scale is the first step. The Kendrick mass scale poses CH2 = 14.0000 Da rather than 14.01565 Da. The Kendrick mass comes from the IUPAC mass, as shown in Equation (1) [35,36]:
Kendrick mass = IUPAC mass × (14.00000/14.01565)
Members of a homologous series (specifically, compounds that comprehend the same heteroatom and number of rings plus double bonds, but a different number of CH2 groups) have the same KMDs. They are thus quickly organised and selected from a list of all detected ion masses, as shown in Equation (2):
KMD = KNM − KEM
where KEM is the Kendrick exact mass.
By rounding the Kendrick mass up to the nearest whole number, the nominal Kendrick mass conveniently arises. Next, homologous series are parted based on even and odd Kendrick Nominal mass and KMD, as described elsewhere [36,37]. Finally, the Kendrick masses are sorted based on Kendrick mass defect and nominal-Z value and exported into an Excel spreadsheet in the second step. Then, a molecular formula calculator programme, limited to molecular formulas consisting of up to 12C 0–80 and 16O 0–10, assigns elemental compositions. Since members of a homologous series diverge only by integer multiples of CH2, the assignment of a single unit of such a series typically suffices to identify all higher-mass members of that series [36].
We also used the van Krevelen diagram for examining ultra-high resolution mass spectra. This kind of layout is used broadly in the geochemistry literature to study the evolution of coals or oil samples [38,39,40]. The molar hydrogen-to-carbon ratios (H/C) constitute the ordinate, and the molar oxygen-to-carbon ratio (O/C), the abscissa. As a result, each class of compounds plots in a specific location on the diagram. Researchers well recognised that they can identify the type of compounds from the position of their representative points in the van Krevelen plot [41,42,43].
In general, the chemical formula CcH2c(Ζ)NnOoSs can identify the crude oil composition. That is because the hydrogen deficiency index <Ζ> of the molecule is the same for all members of a homologous “type” series (i.e., the fixed number of rings plus double bonds). Every two-units decrease in <Ζ> value represents the addition of one ring or a double bond. Therefore, number-average molecular weight, Mn, and weight-average molecular weight Mw have a synthetic definition as:
Mn = ΣiMi/ΣNi
and
Mw = ΣNiMi2/ΣNiMi
where Ni is the relative abundance of ions of mass Mi [34].
The <Z> number plays an essential role for the general molecular formula CcH2c(Z)X of the corresponding neutral species, in which X denotes the constituent heteroatom (Nn, Oo, and Ss).

2.1. Ageing Study of Crude Oil by FT-ICR-MS

A solar simulator (Suntest®), equipped with a xenon lamp as the light source used for the ageing treatment, provided information about the crude oil’s photochemical behaviour.
GC-MS spectra showed that the fraction present in the highest percentage shifted from the C8–C11 fractions to the C13 (Figure S2) in the irradiated sample. We observe an increased amount of the C13–C23 and a decreased amount of the C7–C12 fractions. In the natural (not irradiated) oil, the C8–C11 fractions represented 54.8% of all the compounds detected. Figure S2B depicts the distribution of the compounds as a function of their chemical type. The GC-MS analysis of the mixture deriving from solar simulator irradiation showed an increase in the relative amounts of both linear alkanes and aromatic compounds. At the same time, we observed a sharp decrease in the relative amounts of branched chains. After irradiation, we did not find cyclic alkanes and alkenes.
After the irradiation, the compositional analysis of the linear alkanes highlighted several changes (Figure S2C) compared to the not irradiated sample. Undecane was the hydrocarbon found in the highest percentage in the crude oil, while pentadecane was in the irradiated oil. A decrease in the C7–C12 and an increase in C13–C25 fractions is evident. All our analytical determinations agree with reducing the numberof branched alkanes in crude oil after irradiation. Figure S2D illustrates the modifications of the composition of this fraction. After the irradiation, branched alkanes underwent a sharp reduction and only C8, C9, C11, C12, and C13 fractions were present. Cyclic alkanes were not present after the solar simulator experiment (Figure S2E).
The percentage area of the aromatic compounds did not vary with solar irradiation (Figure S2B). However, a sharp decrease in benzene-like structures and an increase in naphthalenic ones have been observed (Figure S2F).
Figure 1a,b show the FT ICR-MS spectra of untreated and treated crude oil, respectively. The spectra show the distribution of multiple ions with a single charge comprised between m/z 150 and m/z 1400. Figure 1(c1–c3) show the scale-expanded segment of the mass spectrum in Figure 1a, revealing an average period of nominal 14 mass units. The signal intensities increased after light irradiation. The shift of maximum apex was not negligible in the treated crude oil sample, which was also more viscous. Thanks to the high accuracy of mass and the excellent resolution power of FT-ICR-MS, it was possible to carry out the non-ambiguous determination of the elementary composition of multiple isobaric picks.
The chemical formula CcH2c(Z)X generally expresses the composition of a hydrocarbon molecule; where, <c> is the number of carbon atoms, <Z> is the hydrogen deficiency (a measure of aromatic character), and X represents the constituent heteroatom (N, S, O) in the molecule. The heteroatom of interest is oxygen in this study. For simplification, Kendrick and van Krevelen diagrams of natural and irradiated crude oil shown in the figures report only the O3 class, which contains the most numerous groups of detected ions. Table 1 illustrates an example of homologous series extracted by the mass spectrum of the untreated sample, with a degree of unsaturation Z = −20 and class of oxygen O3, containing the most numerous groups of detected ions.
The compounds of the same homologous series, having a different number of CH2 groups, fall in a single horizontal line of the Kendrick plot with peaks separated from 14 Da and no difference in the Kendrick mass defect (Table 1, Figure 2). The compounds of the same class but different typology settle down on a vertical line of the diagram separated from a difference of 0.0134 in the value of KMD. Figure 2 compares Kendrick plots for positive-ion ESI FT-ICR mass spectra of natural (■) and irradiated (X) crude oil samples. Due to the high number of signals, the figure reports only the O3 class, containing the most numerous group of detected ions. Kendrick plot of crude oil sample for O3 class shows many compounds with a high degree of unsaturation (high value of KMD). In the low values of KMD, the highest percentage of compounds has a small alkylation series (limited number of -CH2– moieties).
This plot can visually sort up to thousands of compounds horizontally according to the number of CH2 groups and vertically according to class (heteroatom composition) and type (rings plus double bonds). Since these two classes have the same number of oxygen atoms, they have identical O/C ratios but distinguish themselves by different H/C ratios.
The attained results elucidate the transformation of oil components following irradiation. After irradiation with the xenon lamp (Suntest®), a slight shift of the peak to the higher masses appears in the recorded mass spectra, according to Griffiths et al. findings [31]. Therefore, it seems that a phenomenon of molecular polymerisation prevails on the destruction of the tri-, tetra- and penta-aromatic groups. Furthermore, since the increase in unsaturation correlates with the higher toxicity [44], our results could indicate higher toxicity for the oil after irradiation.
The plot of Figure 2 highlights the increase in the number of double bonds’ rings as the KMD increases (y-axis) and the alkylation series along the x-axis. The solar irradiation causes a diminution of rings or double bonds (picks rarefaction in samples irradiated), a consequent Kendrick Nominal mass raising of 2 Da, and the Kendrick mass defect diminution. The irradiated crude oil sample shows an expansion of alkylation in compounds with a high degree of unsaturation and a reduced unsaturation number for molecules with a low alkylation degree.
Figure 3 shows the van Krevelen plot for the class of O3 compounds found in the natural crude oil. The compounds in homologous series, corresponding to varying degrees of alkylation, appear along lines that intersect the value of 2 on the H/C axis. Similarly, a vertical line connects homologous series differing in degree of unsaturation. In agreement with the results in the Kendrick plot, most compounds have a low number of oxygen atoms and a high degree of unsaturation.
As the H/C ratio increases, the number of rings plus double bonds decreases. Thus, a slight shift to a lower H/C ratio (i.e., a higher number of rings plus double bonds) occurred. Figure 3 shows a minor shift of the data to the right due to increased oxidation and slight dehydration (the picks shift to the lower left) of hydrocarbons. Kendrick mass defect analysis has dramatically facilitated the interpretation of mass spectra, but it is still challenging to derive details for molecules that contribute to complex ultrahigh-resolution mass spectra.
Figure 4 shows the distribution of compounds associated with their number of oxygen atoms in natural and irradiated samples. In both samples, the number of total oxygenated compounds increases. The augmentation of oxygenated compounds should mainly refer to the O3 and O4 types present in the investigated model. The irradiation of crude oil in the solar simulator produces oil oxidation with a particular effect of double bonds oxygenation.
Figure 5 shows oxygen class Z-distributions for natural and irradiated samples, confirming a diminution of hydrogen deficiency index (~15–30% less) and augmentation of oxygen number after the light irradiation. Therefore, the light irradiation induces a manifest photo-oxidation of the crude oil composition. These results highlight toxicity as most of the new oxidised compounds are water-soluble, available in higher concentrations to the living organisms and probably more reactive and biologically active than their parent compounds [43,44].

2.2. Remediation of Oil-Polluted Water

Since crude oil lies over the surface of water and soil, it suffers solar irradiation. Solar degradation is one of the natural ways for petroleum decontamination, and, as a consequence, techniques based on light irradiation could be advantageous in the petroleum degradation processes. Enhanced light irradiation-based technologies are available, adopting different approaches for the scope [10,11,12,45].
The accidental dispersion of crude oil in water bodies forms a characteristic thin layer of not water-miscible compounds and a deeper layer of solubilised substances, which cannot easily separate from the aqueous solvent. In this direction, our approach was to prepare a water/oil suspension and investigate the efficiency of different cleaning methods. The water-soluble fraction of crude oil was undergone degradation by photocatalysis, sonolysis, and sonophotocatalysis, i.e., the simultaneous use of UV, titanium dioxide, and ultrasound emitter (UV + TiO2 + US). GC-MS, liquid-state NMR, fluorescence, and high-resolution mass spectrometry (FT-ICR) analyses elucidated the chemical nature of water-soluble organic compounds after degradation processes and liquid-liquid extractions (LLEs). The results obtained in this study are concisely readable in Table 2.

2.2.1. Photocatalytic Degradation

In the photocatalytic process, the water/oil suspension was treated for 1 h with UV irradiation in the presence of titanium dioxide. GC-MS analysis of WSF (Figure S3) evidenced increased C5 compounds from 67% in not-treated WSF to 89% in the irradiated sample. Moreover, the amount of C6, C7, C8, and C9 compounds decreased. The analysis of chemical classes occurring in the irradiated WSF showed increased branched and cyclic alkanes, from 50% to 65% (branched) and from 4% to 7% (cyclic), respectively. On the other hand, the number of linear alkanes underwent a slight decrease (from 22% to 14%), and the aromatic compounds had a sharp decline (from 23% to 13%).
1H-NMR spectra (Figures S4 and S5) confirmed a slight increase of linear and cyclic alkanes, and a sharp decrease in aromatics, as evidenced in the chromatographic analysis.
FT-ICR MS analysis showed a minor decrease in the total number of oxygenated compounds. The O1 and O2 classes prevailed over the other types (Figure 6).
Comparison of Kendrick plots constructed for the untreated sample (Figure 7a) and the photodegraded model (Figure 7b) shows an increase in the number of compounds with low molecular weight and low degree of unsaturation. The formation of several homologous series, with KDM values of 0.124, 0.137, 0.150, and so on, is underlined in the Kendrick diagram plotted for the treated sample. The unsaturation degree of these homologous series falls in the range Z = −16 to Z = −20.
The van Krevelen diagram (Figure 8) shows an increase in O1 class, reduced O/C ratio, and decreased unsaturated compounds in the treated sample compared to the untreated one. After photocatalysis, the number of compounds with a low number of oxygen atoms increased. As shown in Figure 6, the O1 and O2 classes prevailed over the other types, resulting in a decrease in the O/C ratio.
From fluorescence spectra (Figure S6), it was possible to argue aromatic compounds’ decrease after 1-h photocatalytic treatment. Essentially, the absolute intensity of the peak at 347 nm decreases from 92.07 mAU for the natural sample to 49.50 mAU for the treated sample, with a reduction of 46%.

2.2.2. Ultrasonic Irradiation

In the sonolytic process, the water/oil suspension received 1-h ultrasound irradiation. GC-MS analysis (Figure S7) indicated that C5 compounds increased from 67% to 91% at the end of sonolysis, evidencing a behaviour analogous to photocatalysis. Furthermore, the C6, C7 and C8 compounds decreased, similarly to the photocatalytic process; otherwise, the C9 class disappeared. The analysis of functional groups evidenced that branched alkanes increased from 50% to 54% in the sonolysed WSF (from 50% to 65% in photocatalysis). Cyclic alkanes underwent a minor increase from 4% to 5% (like photocatalysis), but aromatic compounds slightly increased from 23% to 24% (decreased dramatically to 13% in photocatalysis). The number of linear alkanes decreased from 22% to 17% (22% to 14% in photocatalysis).
Liquid-state 1H-NMR spectra (Figures S8 and S9) evidenced a relatively equal amount of the three classes of compounds in the not-treated and sonolysed samples. In conclusion, no significant differences emerged in the composition of WSF before and after the processes of sonication and photocatalysis, with a unique exception for aromatic compounds, as mentioned above in the case of photocatalysis.
From FTICR MS analysis, the total number of oxygenated compounds registered a low increase in the sonicated sample. O1, O2 and O7 classes increased, but the other oxygenated types decreased (Figure 9).
Analysis of the Kendrick plot (Figure 10) after the degradation treatment shows a sharp increase in the number of compounds with low molecular weight. Seventy percent of compounds stay in the range m/z 159–597, and many homologous series with a high degree of unsaturation are visible.
The van Krevelen diagram (Figure 11) substantiates any differences between the natural and treated WSF samples.
The fluorescence study (Figure S10) confirms that the decrease of aromatic compounds is not so evident with US treatment. After 1-h of the sonolytic process, the absolute intensity of the maximum peak displays an insignificant drop from 99.96 mAU for the natural sample to 93.37 mAU for the treated one.

2.2.3. Sonophotocatalytic Degradation

The contemporary use of UV irradiation, titanium dioxide and ultrasound irradiation to treat the oil aqueous suspension shows results mainly similar to those obtained with sonolysis or photocatalysis.
GC-MS analysis (Figure S11) demonstrated that after 1-h of treatment, C5 compounds increased from 67% in not-treated WSF to 91% in the treated sample, while C6, C7 and C8 compounds decreased; C9 compounds were not detected (like the simple US). The analysis of functional groups in the sonophotocatalytic degradation evidenced an increase from 50% to 64% of branched alkanes (similar to photocatalysis) and from 4% to 9% of cyclic alkanes (higher than the other technologies). The number of linear alkanes underwent a slight decrease (from 22% to 19%, similar to the other technologies). In comparison, aromatic compounds showed the sharpest decline (from 23% to 7%), also proved by integrating NMR spectra (Figures S12 and S13). In the natural WSF, the aromatics alkanes occupied 19% of the whole spectral area, whilst in the treated sample, this amount decreases up to 3.3%. On the other hand, the amount of linear and cyclic alkanes increases by about 7–8%.
Figure 12 shows the trend of oxygenated compounds after sonophotocatalytic treatment. In this case, the total number of oxygenated compounds decreased from 1203 (not treated WSF) to 993 (treated WSF).
Comparison of Kendrick plots (Figure 13) obtained for the not-treated and treated samples showed an increased number of compounds with low molecular weight, especially in the range m/z 169–369, and compounds with a low unsaturation degree.
The van Krevelen diagram (Figure 14) let us see an intensification of signals relative to oxygenated compounds with an O/C ratio in the range 0.10–0.25.
Fluorescence spectra (Figure S14) substantiated the decreasing of aromatic compounds after 1-h sonophotocatalytic treatment. The absolute intensity of the peak at 347 nm decreased from 89.92 mAU for the natural sample to 47.95 mAU for the treated sample, reducing by 48%.

3. Materials and Methods

3.1. Crude Oil and Chemicals

The director of the Eni-Cova Oil Plant in Val d’Agri (Basilicata Region, Southern Italy) kindly provided the oil sample taken from the first step of oil purification after extraction, including dehydration and degasification. Table 3 accounts for the elemental composition reported in the label accompanying the sample delivered for this research.
All chemicals used were of analytical grade. TiO2 Degussa P-25, obtained as a gift from Evonik (Hanau, Germany), was the catalyst adopted. Table 4 reports a summary scheme of the investigation executed.

3.2. Photodegradation Apparatus

The Suntest CPS+ (Heraeus Industrietechnik GmbH, Hanau, Germany), equipped with a xenon lamp of 1.1 kW, protected employing a quartz plate (total passing wavelength: 300 nm < λ< 800 nm), was the solar simulator adopted for photochemical reactions. The temperature of the irradiation chamber was 25 °C, maintained through both a thermostatic bath and a conditioned airflow. During the experiments, the crude oil samples were kept up in the horizontal position, creating a homogeneous film of 0.5 cm thickness.

3.3. Photodegradation Process and Sample Preparation for ESI FT-ICR MS

The protocol used for oil ageing experiments was: (i) the irradiation of the natural crude oil (10 mL) for a week in the borosilicate planar reactor; (ii) crude oil samples preparation by dissolving ~30 mg of material in 30 mL of toluene; (iii) withdrawal of 1 mL solution and its dilution with 0.5 mL methanol; addition of either 10 µL acetic acid (for positive ion ESI) or 10 µL ammonium hydroxide (for negative ion ESI) to facilitate protonation or deprotonation in the electrospray ionisation process, respectively.

3.4. Ultrasonic Irradiation of WSF Samples

A crude oil/water suspension was arranged in a borosilicate decanter (5 L) equipped with a Teflon tap at the bottom. The decanter was filled with 3.5 L of ultrapure water; the crude oil was added at the ratio of 1/20 (oil/water), and the suspension was magnetically stirred and then kept in the dark for 30 days at constant temperature (25 °C) to reach equilibrium and the separation of oil phase on the surface of the aqueous phase. Aqueous samples were drawn off through the Teflon tap without disturbing the oil/water separation surface. The collected aqueous sample (500 mL) underwent cotton filtration, to avoid the formation of an emulsion in the solution. The ultrasonic degradation tool was the immersible ultrasonic emitter Sinaptec Nexus P198-R (Sinaptec, Lezennes, France), an ultrasonic module furnished with a titanium sonotrode (S23-10-1/2, Sinaptec), an electrical signal of frequency close to 20 kHz, and a voltage of about 1 kV. In this configuration, the electric power provided by the generator (Nexus P198-R, same manufacturer) is adjustable between 7 W and 100 W, as indicated on a digital display panel. However, this electrical measurement does not determine with high precision the acoustic power dissipated in the liquid. The experimental temperature was fixed to 25 °C.

3.5. Photocatalytic and Sonophotocatalytic Degradation of WSF Samples

The photocatalytic method to degrade the water-soluble fraction of crude oil utilises a 125 W high-pressure mercury lamp (Philips-HPK, Philips, Turnhout, Belgium) that provides its maximum energy at 365 nm, with a range of emission from 195 to 580 nm. The catalyst was TiO2 (80% anatase–20% rutile). The simultaneous use of the mercury lamp, titanium dioxide and the ultrasound emitter (UV + TiO2 + US) permitted the sonophotocatalytic degradation. The experimental temperature was 25 °C for photocatalysis and sonophotocatalysis trials.

3.6. Liquid–Liquid Extraction (LLE)

The experimental protocol was (i) to collect samples of the oil WSF after 15, 30, 45, and 60 min of treatment; (ii) to extract in triplicate 30 mL of each sample in a separatory funnel (50 mL) with 3 mL dichloromethane for GC-MS analysis and (iii) another 30 mL with the same solvent for 1H-NMR spectroscopy; (iv) to perform fluorescence analysis using 5 mL of the aqueous solution without extraction.
The internal standard used for assessing the reproducibility of WSF extraction was 1 mL of 1,3-dibromopropane (26.7 mg L−1) added to the volume of dichloromethane needed for each liquid–liquid extraction. In addition, it was necessary to add 1.0 mL of 1-bromododecane (29.0 mg L−1) to evaluate the GC-MS analysis reproducibility at the end of each extraction. Thus, the injection volume was 1 µL extract for each GC-MS run.

3.7. Analysis of Fluorescence

A research-grade spectrofluorometer FP-6500 Jasco (Jasco Corporation, Cremella, Italy) was available for fluorescence analysis. This analysis was necessary to appreciate the aromatic compounds remaining in the water-soluble fraction of crude oil. The spectrofluorometer FP-6500 Jasco, adopting as emitting source a DC-powered 150 W xenon lamp (in a sealed housing), employs a photometric rationing system, which utilises a second photomultiplier tube to monitor and compensate for any variations in the intensity of the xenon source, thus ensuring maximum analytical stability. Furthermore, a concave holographic grating monochromator with optimised blaze angles provides maximum sensitivity over the entire wavelength range; (220–750 nm; 1 nm resolution).
The fluorescence optical path adopted was 1 cm in quartz cells (volume ca 5 cm3) at 237 and 320 nm excitation and 347 and 360 nm emission.

3.8. 1H-NMR Analysis

A Varian Oxford AS400 spectrometer (Palo Alto, CA, USA), operating at 400 MHz, was enough for the 1H-NMR spectra recording. The set temperature for the used 5 mm non-gradient broadband inverse (BBI) probe was 25 °C.
All the 1H-NMR spectra have tetramethylsilane (TMS) as reference under the acquisition parameters shown in Table 5.
In degradation experiments, liquid–liquid extraction with chloroform permitted to isolate the water-soluble fraction of crude oil. After the complete evaporation of the solvent in a rotary evaporator, the addition of 500 μL deuterated chloroform (CDCl3) permitted to recuperate the residual organic mixture.

3.9. Mass Spectrometry of Polar Components

The instrument available to determine polar components was the micro ESI/FT-ICR/MS 7 T Thermo Electron (Waltham, MA, USA).
The method used for the routine analyses permitted a mass accuracy better than 2 ppm by external calibration, using the mixture of caffeine, MRFA, and Ultramark. The technique separated more than 6000 ion signals belonging to chemically different elemental compositions with a 200,000 resolving power (m/Δm50% at m/z 400) in positive electrospray mode. The robustness of this equipment, combined with unprecedented ease of use, ultra-high mass accuracy, high sensitivity, and excellent resolving power, make it an ideal instrument for analysis. The infusion of the samples at a flow rate of 5 μL/min permitted the best result in terms of spectrum resolution. ESI conditions were: needle voltage, +4.5 kV; heated capillary current 4 A; tube lens voltage 135.12; temperature 300 °C; N2 speed 2.33 u.a.; aux gas flow rate 0.73; scansions per second 1000.

4. Conclusions

In this study, we tried to characterise the ageing process of crude oil simulating solar irradiation on a thin layer of an oil sample. As a result, FT-ICR MS evidenced an augmentation of compounds with low molecular weight and a slight increase of the number of oxygen atoms in the oxygenated species, as depicted in Kendrick and van Krevelen diagrams. Furthermore, the simulated ageing produced the oxidation of crude oil with a particular effect on double bonds’ oxygenation, as confirmed by the disappearance of alkenes in gas chromatographic analysis. The observed results seem to be recognisable because the energy irradiated with the xenon lamp could be enough for catalysing the reaction of olefins with the atmospheric oxygen following a bridge mechanism.
We experimented with different solutions for the cleaning treatment of oil-polluted water (photocatalysis, sonolysis, and sonophotocatalysis). GC-MS analyses of the water-soluble fraction of crude oil for both natural and treated samples discovered that only a few compounds are detectable in the aqueous solution, principally C5–organic chains (~50%). Low amounts of C6, C7, C8 and C9 chains were also present. Both GC-MS and liquid state 1H-NMR signals showed that the branched alkanes were the principal chemical class in the soluble fraction of oil, followed by a small amount of linear and aromatic alkanes.
With all the degradation methods utilised, an increase of the C5–class and a decrease of C6–C9 types of compounds was evident. Furthermore, the FT-ICR comparative analyses of oxygenated species elucidated that the total number of O-compounds in the treated WSF samples is different for all of the degradation methods experimented. The number of the oxygenated compounds slightly decreased with photocatalysis compared to the non-treated sample. An opposite trend appeared with the sonolysis treatment. The sonophotocatalytic method showed a sharp reduction in the number of oxygenated compounds, probably due to the volatilisation of small molecules formed during the oxidation process. It is conceivable that ultrasound can promote this volatilisation. The degradation of the water-soluble fraction of crude oil performed with photocatalysis and sonophotocatalysis led to an apparent decrease of aromatic compounds of 46% and 48%, respectively, for the two techniques, as also confirmed by the fluorescence analysis. With the use of sonolysis, there was no effect on the number of aromatic compounds. Nevertheless, all the degradation methods applied were capable of increasing the number of cyclic alkanes. Therefore, we could speculate that ultrasound in sonophotocatalytic technology can affect the rate of the photocatalytic degradation of the organic pollutants due to a synergistic effect typically observed with an increase of the degradation process efficiency.
In conclusion, our results confirm the photo-oxidation effect caused by light irradiation either on crude oil (simulated ageing) or on the soluble oil fraction. Naturally, the behaviour of each oil type could be different, and then it is not possible to generalise our findings to all cases of oil spilling and environmental remediation. Therefore, it is necessary to check case by case before reaching specific solutions for more efficient remediation processes to avoid making the situation worse.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/catal11080954/s1 Figure S1: Percentage of compounds in crude oil as recognized by GC-MS (blue column) and 1H-NMR (red column). Figure S2: GC-MS compositional analysis of crude oil (blue column) and solar simulator irradiated crude oil (red column), as a function of the number of carbon atoms (A); composition of crude oil as a function of the type of compounds, LH: linear aliphatic hydrocarbons; BH: branched aliphatic hydrocarbons; CH: cyclic aliphatic hydrocarbons; AH: aromatic hydrocarbons; AL: alkenes (B); composition of the linear aliphatic hydrocarbons as a function of the number of carbon atoms (C); composition of the branched aliphatic hydrocarbons fraction as a function of the number of carbon atoms (D); composition of the cyclic hydrocarbons as a function of the number of carbon atoms (E); composition of the aromatic hydrocarbons fraction as a function of the number of carbon atoms (F). Figure S3: GC-MS compositional analysis of WSF crude oil before (red column) and after (blue column) photocatalysis: distribution of hydrocarbons as a function of the number of carbon atoms (A) and distribution of the compounds as a function of chemical species (B). Figure S4: 1H-NMR spectra of WSF crude oil before (A) and after (B) photocatalysis. Figure S5: 1H-NMR compositional analysis of WSF crude oil before (red column) and after (blue column) photocatalysis: distribution of the compounds as a function of chemical species. Figure S6: Fluorescence spectra of WSF crude oil before (blu line) and after (red line) photocatalysis. Figure S7: GC-MS compositional analysis of WSF crude oil before (red column) and after (blue column) sonolysis: distribution of hydrocarbons as a function of the number of carbon atoms (A) and distribution of the compounds as a function of chemical species (B). Figure S8: 1H-NMR spectra of WSF crude oil before (A) and after (B) sonolysis. Figure S9: 1H-NMR compositional analysis of WSF crude oil before (red column) and after (blue column) sonolysis: distribution of the compounds as a function of chemical species. Figure S10: Fluorescence spectra of WSF crude oil before (blu line) and after (red line) sonolysis. Figure S11: GC-MS compositional analysis of WSF crude oil before (red column) and after (blue column) sonophotocatalysis: distribution of hydrocarbons as a function of the number of carbon atoms (A) and distribution of the compounds as a function of chemical species (B). Figure S12: 1H-NMR spectra of WSF crude oil before (A) and after (B) sonophotocatalysis. Figure S13: 1H-NMR compositional analysis of WSF crude oil before (red column) and after (blue column) sonophotocatalysis: distribution of the compounds as a function of chemical species. Figure S14: Fluorescence spectra of WSF crude oil before (blu line) and after (red line) sonophotocatalysis.

Author Contributions

Conceptualisation, F.L., S.A.B. and L.S.; Data curation, F.L., G.B. and S.A.B.; Formal analysis, L.S.; Investigation, L.S.; Methodology, G.B.; Resources, S.A.B.; Writing—original draft, F.L. and L.S.; Writing—review and editing, S.A.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data supporting results reported in this paper can be found at the Department of Sciences, University of Basilicata, Via dell’Ateneo Lucano 10, 85100, Potenza, Italy. Due to the multitude of files produced for this investigation, a link will be provided under specific requests.

Acknowledgments

We acknowledge the Director of ENI-COVA Oil Plant in Val d’Agri (Basilicata Region, Southern Italy), who kindly provided the oil sample. Special thanks go to Mauro Tummolo, and to Jean-Marc Chovelon, University Claud Bernard Lyon 1, for the sonolysis and sonophotocatalysis data.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. (a) FT ICR-MS spectrum of the untreated oil sample; (b) FT ICR-MS spectrum of the same sample irradiated by xenon-lamp. The spectrum shows the distribution of multiple ions with a single charge comprised between m/z 150 and 1400; c1, c2, c3 insets = mass scale-expanded segments of the full range crude oil mass spectrum in Figure 1a, revealing periodicities of 14.016 Da from compound series differing in the number of CH2 groups and 2.016 Da from compound series differing in the number of rings plus double bonds.
Figure 1. (a) FT ICR-MS spectrum of the untreated oil sample; (b) FT ICR-MS spectrum of the same sample irradiated by xenon-lamp. The spectrum shows the distribution of multiple ions with a single charge comprised between m/z 150 and 1400; c1, c2, c3 insets = mass scale-expanded segments of the full range crude oil mass spectrum in Figure 1a, revealing periodicities of 14.016 Da from compound series differing in the number of CH2 groups and 2.016 Da from compound series differing in the number of rings plus double bonds.
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Figure 2. Kendrick mass plot of the O3 species found in natural (■) and irradiated oil (X). This plot illustrates the increase in the number of rings plus double bonds as the KMD increases (y-axis) and the alkylation series along the x-axis.
Figure 2. Kendrick mass plot of the O3 species found in natural (■) and irradiated oil (X). This plot illustrates the increase in the number of rings plus double bonds as the KMD increases (y-axis) and the alkylation series along the x-axis.
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Figure 3. van Krevelen plot of the O3 species found in natural (■) and irradiated oil (X). The compounds in homologous series, corresponding to varying degrees of alkylation, appear along lines that intersect the value of 2 on the H/C axis. Similarly, a vertical line connects homologous series differing in degree of unsaturation.
Figure 3. van Krevelen plot of the O3 species found in natural (■) and irradiated oil (X). The compounds in homologous series, corresponding to varying degrees of alkylation, appear along lines that intersect the value of 2 on the H/C axis. Similarly, a vertical line connects homologous series differing in degree of unsaturation.
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Figure 4. FT-ICR compositional analysis of natural and irradiated crude oil samples as a function of the number of oxygen atoms.
Figure 4. FT-ICR compositional analysis of natural and irradiated crude oil samples as a function of the number of oxygen atoms.
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Figure 5. Oxygen class <Z>-distributions for natural and irradiated samples.
Figure 5. Oxygen class <Z>-distributions for natural and irradiated samples.
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Figure 6. FT-ICR MS analysis of natural and 1-h photocatalysed WSF of crude oil as a function of the number of oxygen atoms.
Figure 6. FT-ICR MS analysis of natural and 1-h photocatalysed WSF of crude oil as a function of the number of oxygen atoms.
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Figure 7. Kendrick mass plots of the O1–O10 species found in the untreated crude oil WSF (a) and the 1-h photocatalysed sample (b).
Figure 7. Kendrick mass plots of the O1–O10 species found in the untreated crude oil WSF (a) and the 1-h photocatalysed sample (b).
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Figure 8. The van Krevelen plots of the O1–O10 species found in the untreated crude oil WSF (a) and the 1-h photocatalysed sample (b).
Figure 8. The van Krevelen plots of the O1–O10 species found in the untreated crude oil WSF (a) and the 1-h photocatalysed sample (b).
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Figure 9. FT-ICR analysis of natural and 1-h sonicated WSF of crude oil samples asa function of the number of oxygen atoms.
Figure 9. FT-ICR analysis of natural and 1-h sonicated WSF of crude oil samples asa function of the number of oxygen atoms.
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Figure 10. Kendrick mass plot of the O1–O10 species found in the not-treated WSF of crude oil (a) and after 1-h of US treatment (b).
Figure 10. Kendrick mass plot of the O1–O10 species found in the not-treated WSF of crude oil (a) and after 1-h of US treatment (b).
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Figure 11. The van Krevelen plots of the O1–O10 species found in the not-treated WSF of crude oil (a) and after 1-h US treatment (b).
Figure 11. The van Krevelen plots of the O1–O10 species found in the not-treated WSF of crude oil (a) and after 1-h US treatment (b).
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Figure 12. FT-ICR MS analysis of natural and 1-h sonophotocatalysed WSF sample of crude oil as a function of the number of oxygen atoms.
Figure 12. FT-ICR MS analysis of natural and 1-h sonophotocatalysed WSF sample of crude oil as a function of the number of oxygen atoms.
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Figure 13. Kendrick mass plots of the O1–O10 species found in the not-treated WSF of crude oil (a) and after 1-h of sonophotocatalytic treatment (b).
Figure 13. Kendrick mass plots of the O1–O10 species found in the not-treated WSF of crude oil (a) and after 1-h of sonophotocatalytic treatment (b).
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Figure 14. The van Krevelen plots of the O1–O10 species found in the not-treated WSF of crude oil (a) and after 1-h of sonophotocatalytic treatment (b).
Figure 14. The van Krevelen plots of the O1–O10 species found in the not-treated WSF of crude oil (a) and after 1-h of sonophotocatalytic treatment (b).
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Table 1. Homologous series of O3 class with <Z> = −20.
Table 1. Homologous series of O3 class with <Z> = −20.
m/zIntensityCompositionKNMKMD
337.18183941.7C22 H25 O347210.45494
351.19725150.2C23 H27 O349170.23920
365.21283112.4C24 H29 O351130.02038
379.22704609.2C25 H31 O353100.82256
393.24244252.4C26 H33 O355060.60640
407.25823311.8C27 H35 O357020.38464
421.27373427.8C28 H37 O358980.16848
435.28934966.3C29 H39 O360950.94924
449.30523587.2C30 H41 O362910.72748
463.32024252.1C31 H43 O364870.51692
477.33624772.3C32 H45 O366830.29390
505.36687455.6C34 H49 O370760.86536
533.39815506.9C36 H53 O374680.42618
547.41316265.8C37 H55 O376640.21674
561.42926183.2C38 H57 O378610.99120
575.44465847.4C39 H59 O380570.77504
589.46065685.7C40 H61 O382530.55118
603.47606234.8C41 H63 O384490.33586
617.49215529.1C42 H65 O386450.11018
631.50753522.3C43 H67 O388420.89486
645.52304399.5C44 H69 O390380.67870
659.53855131.9C45 H71 O392340.46086
673.55454308.2C46 H73 O394300.23700
687.57034191.7C47 H75 O396260.01566
701.58542133.1C48 H77 O398230.80454
715.60143178.9C49 H79 O310,0190.58068
729.61653507.6C50 H81 O310,2150.36872
743.63233063.6C51 H83 O310,4110.14836
Table 2. Synthetic results obtained from the different photodegradation processes of crude oil and oil water-soluble fraction (WSF) under investigation.
Table 2. Synthetic results obtained from the different photodegradation processes of crude oil and oil water-soluble fraction (WSF) under investigation.
Degradation Method/SystemGC-MS1H-NMRFT-ICR MSFluorescence
Photolysis (UV)/
Ageing of crude oil
-
increase of C13–C23 classes and a decrease of C7–C12 types of compounds
-
signal intensities increase-augmentation of compounds with a low molecular weight
-
a light increase of the number of oxygen atoms in the oxygenated species, in particular, O3 and O4 types
-
oxidation of crude oil with a particular effect on double bonds’ oxygenation
Photocatalysis (UV + TiO2)/
Oil Water-Soluble Fraction (WSF)
-
increase of C5 compounds from 67% to 89%
-
decrease of C6, C7, C8 and C9 compounds
-
increase of branched alkanes from 50% to 65%
-
increase of cyclic alkanes from 4% to 5%
-
decrease of aromatic compounds from 23% to 13%
-
decrease of linear alkanes from 22% to 14%
-
slight increase of linear and cyclic alkanes and a sharp decrease in aromatics
-
no other significant differences emerged in the composition of WSF before and after the processes
-
a slight decrease in the total number of oxygenated compounds
-
the O1 and O2 classes prevailed over the other types
-
aromatic compounds’ decrease (about 46% after 1 h of treatment)
Sonolysis (US)/
Oil Water-Soluble Fraction (WSF)
-
increase of C5 compounds from 67% to 91%
-
disappeared C9 class
-
increase of branched alkanes from 50% to 54%
-
increase of cyclic alkanes from 4% to 5%
-
increase of aromatic compounds from 23% to 24%
-
decrease of linear alkanes from 22% to 17%
-
no significant differences emerged in the composition of treated and not treated WSF
-
a low increase of oxygenated compounds: O1, O2 and O7 classes and decrease of the other oxygenated types
-
a sharp increase in the number of compounds with a low molecular weight
-
no significant differences emerged in the composition of aromatic compounds before and after the processes
Sonophotocatalysis
(UV + TiO2 + US)/
Oil Water-Soluble Fraction (WSF)
-
increase of C5 compounds from 67% to 91%
-
decrease C6, C7 and C8 compounds;
-
disappeared C9 class
-
increase of branched alkanes from 50% to 64%
-
increase of cyclic alkanes from 4% to 9%
-
significant decrease of aromatic compounds from 23% to 7%
-
decrease of linear alkanes from 22% to 19%
-
significant decrease of aromatic compounds from 23% to 7%
-
the total number of oxygenated compounds decreased from 1203 to 993
-
increase of compounds with low molecular weight and compounds with a low unsaturation degree
-
aromatic compounds’ decrease (about 48% after 1 h of treatment)
Table 3. Elemental composition (%) of the oil sample taken from the first step of oil purification after extraction, including dehydration and degasification a.
Table 3. Elemental composition (%) of the oil sample taken from the first step of oil purification after extraction, including dehydration and degasification a.
CHNO bS
85.4 ± 2.811.8 ± 1.40.3 ± 0.10.6 ± 0.41.9 ± 0.9
a Metals (Ni and V) < 1000 ppm. b Obtained as the complement to 100.
Table 4. Experiments performed and analytical methods used in this study.
Table 4. Experiments performed and analytical methods used in this study.
Experiments PerformedTreated SystemAnalytical Methods Applied
GC-MS1H-NMRFT-ICR MSFluorescence
Artificial ageing process by photolysis (UV)Crude oilX X
Remediation process by photocatalysis (UV + TiO2)Oil WSFXXXX
Remediation process by sonolysis (US)Oil WSFXXXX
Remediation process by sonophotocatalysis (UV + TiO2 + US)Oil WSFXXXX
Table 5. 1H-NMR acquisition parameters.
Table 5. 1H-NMR acquisition parameters.
InstrumentSolventAcquisition TimeSpectral WidthLine BroadeningNumber of Scans
Varian Oxford AS400CDCl32.049 s6410.3 Hz0.20 Hz512
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Lelario, F.; Bianco, G.; Bufo, S.A.; Scrano, L. Simulated Ageing of Crude Oil and Advanced Oxidation Processes for Water Remediation since Crude Oil Pollution. Catalysts 2021, 11, 954. https://doi.org/10.3390/catal11080954

AMA Style

Lelario F, Bianco G, Bufo SA, Scrano L. Simulated Ageing of Crude Oil and Advanced Oxidation Processes for Water Remediation since Crude Oil Pollution. Catalysts. 2021; 11(8):954. https://doi.org/10.3390/catal11080954

Chicago/Turabian Style

Lelario, Filomena, Giuliana Bianco, Sabino Aurelio Bufo, and Laura Scrano. 2021. "Simulated Ageing of Crude Oil and Advanced Oxidation Processes for Water Remediation since Crude Oil Pollution" Catalysts 11, no. 8: 954. https://doi.org/10.3390/catal11080954

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