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Article

Determination of Nonylphenol in Crude Oils and Petroleum Products by Liquid Chromatography–Mass Spectrometry: Implications for Sustainable Petroleum Refining

by
Limin Wang
1,2,†,
Shijie Zhang
1,2,†,
Zi Long
1,
Feng Ju
3,
Huajun Zhen
2,4,5,*,
Hui Luan
1,
Guangli Xiu
2,4,5 and
Zhihe Tang
1,*
1
Research Institute of Safety and Environment Technology, China National Petroleum Corporation, Beijing 102206, China
2
School of Resources and Environmental Engineering, East China University of Science and Technology, Shanghai 200237, China
3
School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China
4
Shanghai Environmental Protection Key Laboratory on Environmental Standard and Risk Management of Chemical Pollutants, Shanghai 200237, China
5
State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, Shanghai 200237, China
*
Authors to whom correspondence should be addressed.
†
These authors have contributed equally to this work.
Sustainability 2025, 17(18), 8485; https://doi.org/10.3390/su17188485
Submission received: 25 August 2025 / Revised: 15 September 2025 / Accepted: 17 September 2025 / Published: 22 September 2025
(This article belongs to the Special Issue Advancing Sustainability in the Upstream Oil and Gas Industry: Waste Valorization, Emission Control, and Environmental Management)
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Versions Notes

Abstract

Nonylphenols (NPs), widely used as emulsifiers in petroleum production and refining, are compounds of environmental concern, with endocrine-disrupting effects. They can be released during oil extraction and processing, carried into petroleum products, and subsequently emitted during downstream applications such as combustion. Despite these potential pathways, information on their occurrence in petroleum streams remains limited, partly due to the lack of reliable methods for measuring NPs in complex petroleum matrices. In this study, we developed an analytical method combining normal-phase chromatography (NPC), solid-phase extraction (SPE), and liquid chromatography–Orbitrap high-resolution mass spectrometry (LC–Orbitrap-HRMS) for NP determination in crude oils and petroleum products. NPC was performed using alumina (5% water deactivation) as the stationary phase. The column was eluted sequentially with n-hexane, n-hexane/dichloromethane (4:1 and 1:1, v/v), dichloromethane, and dichloromethane/methanol (2:1, v/v). The first three fractions were discarded, and the remaining two fractions were combined and further purified using a C18 SPE cartridge to analysis. The method showed high recovery (82.8 ± 2.6%) and a low detection limit (1.0 ng/g) in crude oil. Application revealed widespread occurrence of NPs, with concentrations up to 784.4 ng/g in crude oils and up to 439.1 ng/g in refined fuels, indicating that these compounds can persist through refining and may be released during downstream use. These results demonstrate that the method is suitable for the routine monitoring of NPs in petroleum-related samples and provide a practical tool for supporting sustainable refining practices and improved environmental management in the upstream oil and gas sector.

1. Introduction

Petroleum has long been essential to human civilization, functioning as a critical energy source and primary industrial feedstock [1,2]. Petroleum-derived products, including plastics, polymers, and transportation fuels, are ubiquitous in contemporary society. In 2024, global consumption of petroleum reached 101 million barrels per day [3], highlighting its profound socioeconomic significance. Nevertheless, concerns regarding the environmental impact of petroleum and its originated products have persisted for a long time, primarily due to its inherent geochemical properties and associated industrial processing impacts [4]. Historically, environmental research and regulation have primarily focused on conventional pollutants from refinery processes, such as wastewaters, solids, and volatile organic compounds (VOCs), which are characterized by high organic content, high salinity, and oily constituents. Beyond these well-established concerns, emerging contaminants (ECs) originating from petroleum industry activities have increasingly garnered scientific attention [5,6].
Nonylphenols (NPs) constitute prevalent synthetic intermediates in petroleum industry, primarily serving as key precursors for synthesizing nonylphenol polyethoxylated (NPEOs) nonionic surfactants, alkylphenolic resins, and nonylphenol salts [7,8]. These compounds function as extensively utilized industrial additives, including surfactants, emulsifiers, demulsifiers, detergents, and dispersants, across critical petroleum operations, with predominant applications in upstream production and lubricant manufacturing [7,8]. Despite their pervasive deployment, NPs are established as prototypical endocrine disrupting chemicals (EDCs) and ECs with documented ecotoxicological and human health risks [9,10]. Consequently, the industrial utilization of NPs derivatives has been subjected to extensive regulation. For instance, in the European Union (EU), raw materials containing greater than 0.1% NP/NPEOs are not allowed for processing uses for textiles and leather processing; finished textile articles placed on the EU market must be less than 0.01% NPEOs (component-wise), NP/NPEOs mixtures greater than 0.1% cannot be placed on the market or used for domestic and industrial and institutional cleaning, and NP/NPEOs mixtures greater than 0.1% cannot be used for metalworking fluids, pulp and paper auxiliaries, and other industrial auxiliaries [9].
Previously, numerous studies have investigated the occurrence of NP across diverse environmental media [11,12], foodstuffs [13,14], food packaging materials [15], and textiles [16]. However, the presence of NPs in petroleum industries, e.g., crude oils and petroleum products, has received much less attention. A major obstacle is the lack of an analytical method due to the complex nature of petroleum and related products. Specifically, conventional single-step pretreatment methods, such as liquid–liquid extraction (LLE) [17], pressurized liquid extraction (PLE) [18], and solid-phase extraction (SPE) [19], exhibit limited efficacy for extremely complex organic matrices. These single methods were not only insufficient in reducing matrix effects, but also generally resulted in poor analyte recovery. Therefore, there is great need to develop an efficient method, possibly by combining multiple pretreatment methods, for the efficient analysis and determination of NPs in crude oils and petroleum products.
In summary, this study aims to establish an efficient and sensitive method for the determination of NPs by combining normal-phase chromatography (NPC)-SPE sample pretreatment with LC–Orbitrap-HRMS. The approach leverages the distinct chemical properties of NPs relative to the petroleum matrix, enabling accurate quantification in diverse crude oils sourced from various oil fields and refineries. The results of this study provide valuable insights for future monitoring and source tracking of NPs, thereby supporting efforts to assess and mitigate their potential environmental and human health risks.

2. Materials and Methods

2.1. Chemicals and Materials

Acetonitrile, methanol, n-hexane, and dichloromethane (all HPLC analytical grade) were purchased from Thermo Fisher Scientific (Waltham, MA, USA). Anhydrous sodium sulfate (Na2SO4), quartz sand (SiO2), ammonia (NH3·H2O), alumina (Al2O3), and amino-functionalized silica gel were purchased from Shanghai Titan Scientific Co., Ltd., Shanghai, Shanghai, China. NPs standards (≥98%) were obtained from J&K Scientific Co., Ltd., China, including the following isomers: nonylphenol (NP), hydrogen isotope labeled nonylphenol (NP-d4), hydrogen isotope labeled bisphenol A (BPA-d16). Four types of SPE columns (silica, florisil, neutral alumina, C18) were purchased from Shanghai Titan Scientific Co., Ltd., Shanghai, China. All water employed in the experimental procedures was of ultrapure grade. All glassware used in the experiments was cleaned by placing it in a muffle furnace and calcining at 450 °C for 5 h prior to use.

2.2. Preparation of Calibration Standards

Stock solutions of all technical standards were prepared at 1000 mg/L in methanol and stored in the dark at −20 °C. Mixed standard solutions containing NPs were prepared from combinations of these stock solutions. Working standard solutions were freshly prepared in methanol prior to calibration curve construction.

2.3. Sample Collection

A total of eleven petroleum samples (five crude oil and six petroleum products) were collected from three oil refineries between 2023 and 2025. Detailed information on the general location, collection date, and crude oil sources is listed in Table 1. Specifically, crude oil samples were collected from the outlet of the transfer pump, located downstream of the storage tank pipeline. Petroleum products from two of three investigated refineries, including gasoline, diesel oil, and aviation kerosene, were collected from the refined oil storage tank pipeline. After collection, petroleum samples were stored in 500 mL brown glass bottles and wrapped in aluminum foil and stored at −20 °C. Before each experiment, the packaged samples were heated to 40 °C in order to restore their fluidity. Then portions of petroleum samples were placed in 40 mL brown glass bottles, mixed evenly by vortex mixing, and subjected to following pretreatment steps.

2.4. Sample Pretreatment

2.4.1. Primary Purification by NPC

Considering the significant polarity difference between NPs and the non-polar matrix of petroleum, NPC was employed for initial sample cleanup [20]. NPC utilizes polar stationary phases (e.g., alumina, amino-functionalized silica-based packing) in combination with non-polar mobile phases (e.g., n-hexane, dichloromethane), enabling preliminary separation of NPs from petroleum-based interferents.
Since large-scale NPC columns (>10 g stationary phase) are not commercially available, a self-packed NPC column was prepared in a chemical safety fume hood by suspending 20 g of alumina (5% water-deactivated) in n-hexane and thoroughly mixing it to obtain a homogeneous slurry. The slurry was then transferred stepwise into a chromatography column (17 mm × 203 mm). After packing, a 1 cm layer of quartz sand was evenly applied on top of the stationary phase. During the packing process, the column was tapped continuously with a rubber bulb to eliminate air bubbles and ensure uniform packing density. A schematic of the setup is illustrated in Figure 1. To prepare the 5% water deactivated alumina that was used as stationary phase in NPC column, 20 g of alumina was weighed and placed into a tightly sealed vessel, followed by the addition of 1 mL of Milli-Q water; the mixture was shaken vigorously until all lumps disappeared and then allowed to cool overnight while kept tightly closed to maintain the activity level for subsequent use.
To carry out sample pretreatment, an aliquot of 0.02~0.1 g of the petroleum-based sample was accurately weighed and spiked with 100 ng of the surrogate NP-d4. The mixture was diluted with n-hexane and adjusted to a final volume of 0.5 mL, followed by vortex mixing for 20~60 s to homogenize the solution for purification. The sample was applied dropwise onto the quartz sand layer atop the alumina column. The stopcock was opened to allow the liquid level to descend to the sand surface, then closed. The column was held for 15 min to facilitate uniform dispersion of the sample within the stationary phase. The column was first rinsed sequentially with 30 mL of n-hexane, 30 mL of n-hexane and dichloromethane (4:1, v/v), and 30 mL of n-hexane and dichloromethane (1:1, v/v). All rinsed solvent was discarded. Subsequently, elution was performed with 30 mL of dichloromethane followed by 30 mL of dichloromethane and methanol (2:1, v/v). Both eluates were collected in a 250 mL round-bottom flask. After single use, each self-packed alumina column was emptied, cleaned, and baked, and the stationary filling materials were properly disposed of.

2.4.2. Further Enrichment by SPE

Subsequently, SPE, the most common method for NPs enrichment, was applied to further purify the isolates. This two-step process (a combination of NPC and SPE) significantly enhances purification efficacy, ultimately yielding extracts suitable for instrumental analysis.
Anhydrous sodium sulfate (1.0 g) was added to the flask from Section 2.4.1 to remove residual water. The solution was concentrated to near-dryness using a rotary evaporator at 50 °C and reconstituted in 1 mL of methanol. Further purification was carried out using a C18 SPE cartridge. The cartridge was fixed on an SPE manifold, conditioned with 6 mL of methanol, and kept moist throughout the process. The reconstituted sample was loaded onto the cartridge, which was then washed with 6 mL of methanol. The eluate was collected and evaporated to dryness under a gentle stream of high-purity nitrogen. The residue was spiked with 100 ng of the internal standard BPA-d16, reconstituted in 500 µL of methanol, and passed through a 0.22 μm PTFE membrane filter to obtain the final extract for nonylphenol analysis.

2.5. Instrumental Analysis

Chromatography–mass spectrometry technologies provide strong separation capabilities and high selectivity, making liquid chromatography–mass spectrometry (LC–MS) and gas chromatography–mass spectrometry (GC–MS) well-established techniques for the analysis of nonylphenols (NPs) [21,22,23]. To further improve the identification of trace-level compounds, high-resolution mass spectrometry (HRMS) is increasingly being adopted [24,25]. Among HRMS systems, Orbitrap mass spectrometry—a type of electrostatic orbital trap instrument—delivers high resolution, exceptional mass accuracy, high sensitivity, and a relatively compact design. Its application significantly enhances the ability to identify target compounds in complex matrices and to separate and characterize different structural isomers of NPs. Based on these advantages, the use of LC–Orbitrap-HRMS enables more accurate and reliable identification of NPs in petroleum samples [26,27].
LC–Orbitrap-HRMS analysis was carried out using an Orbitrap Exploris 240 system, purchased from Thermo Fisher Scientific, USA. Chromatographic separation was performed on a Waters ACQUITY C18 column (100 mm × 2.1 mm, 1.7 μm) maintained at 40 °C. The binary mobile phase consisted of 0.35% ammonia solution (A) and methanol (B) at a flow rate of 0.4 mL/min. The gradient setting of the mobile phase is shown in Table 2.
The mass spectrometer was equipped with an ESI source operating in negative ionization mode. Ionization was achieved with a spray voltage of 2500 V, sheath gas at 50 arb, auxiliary gas at 10 arb, and purge gas at 1 arb. The temperatures of the ion transport tube and evaporator were set at 325 °C and 350 °C, respectively. Parallel reaction monitoring (PRM) mode was used for quantitation with scan range at 50~750 m/z and an MS2 resolution at 30,000. MS parameters are listed in Table 3. Collision energy was optimized by varying it from 10% to 80% in 5% increments and comparing the resulting ion intensities of each analyte. The energy level that yielded the highest ion intensity (Table 3) was selected for subsequent instrumental analysis.

3. Results and Discussion

3.1. Optimization of Sample Pretreatment

In order to mitigate matrix interference arising from the complex organic composition of petroleum samples and obtain purified extracts compatible with high-sensitivity instrumental analysis, a multistage clean-up pretreatment was developed. Primary purification was performed using normal-phase chromatography (NPC), which selectively separated target NPs through chromatographic fractionation. Subsequent enrichment and further purification were achieved by solid-phase extraction (SPE), thereby further concentrating analyte and reducing matrix-related ion suppression. This two-step pretreatment approach effectively isolated trace-level target analytes (NP) from complex organic interferents from crude oils and petroleum product.

3.1.1. Selection of NPC Packing Materials

As reported previously, crude oils contain not only non-polar substances such as paraffins and aromatic compounds, but also considerable amounts of polar impurities such as resins and asphaltenes [28]. To reduce matrix interference, appropriate packing materials can be used in NPC to take advantage of polarity differences, ideally removing impurities while limiting adsorption of the target analyte [29]. In this study, three commonly used normal-phase stationary phases—silica, florisil, and alumina—were tested in a preliminary way using commercially available SPE columns (6 cc, 1 g packing material). Columns were loaded with 100 ng NP-d4 and sequentially eluted with seven solvent mixtures of increasing strength (Table 4). The recovered NP-d4 was analyzed in each fraction to observe retention behavior. As shown in Table 4, NP-d4 generally eluted earlier from florisil, followed by silica and then alumina, which is consistent with trends reported in the literature [30]. On this basis, alumina was chosen for further optimization because of its relatively stronger retention and its suitability for separating non-polar impurities from crude oil and petroleum products.

3.1.2. Optimization of Alumina

Subsequent investigations focused on the selection and optimization of alumina. Alumina, particularly in its activated form, possesses a high specific surface area and abundant surface-active sites (primarily Lewis acid sites) [31], which contribute to distinct adsorption affinities toward compounds of varying polarity and chemical properties [29]. Upon loading of sample extracts—typically dissolved in non-polar or weakly polar solvents such as n-hexane or dichloromethane—alumina strongly retains polar interferents present in the matrix, including pigments, lipids, and other polar impurities [32,33,34]. Water molecules adsorb onto Lewis acid sites via hydrogen bonding, forming a hydration layer that facilitates the controlled modulation of alumina activity [35]. In general, neutral alumina separates molecules based on polarity differences and is widely used for cleaning up nonionic organic contaminants [36]. Acidic and basic alumina, on the other hand, selectively adsorb basic and acidic compounds, respectively, making them suitable for removing such interferents and isolating acidic or target analytes accordingly.
Based on these, we further investigated the impact of water content (5% vs. 0%) in alumina on its adsorption behaviors of crude oils samples using a self-packed chromatography column (17 mm × 203 mm, 20 g alumina or 5% water deactivated alumina). An aliquot of 100 μL NP-d4 standard solution (100 ng) was applied to the top of the prepared column. When deactivated, part of the adsorption sites from alumina column are occupied by water molecules, and thus will not be available for hydrocarbon retention, which reduces overall retention capacity of alumina column. Experimental results indicated that NP-d4 was predominantly eluted in fractions F4 (85%) and F5 (15%) from the 5% water-deactivated alumina, while mainly eluted in F5 (90%) from anhydrous alumina (Table 4). This result further proved the slightly decreased adsorption capacity for medium polar compound such as NP. However, some inconsistency was observed across repeated experiments with anhydrous alumina, where the majority of NPs occasionally eluted in F4 instead of F5. Moreover, a small fraction of NPs was eluted in later fractions (F6, methanol elution), which required extended evaporation times during concentration by rotary evaporator. Considering both reproducibility and operational efficiency, the 5% water-deactivated alumina column was ultimately selected.

3.1.3. Optimization of Elution Conditions

NPC separates target compounds based on differential interactions between the mobile phase and the stationary phase. Following the selection of packing materials, further optimization of the mobile phase composition is essential. Gradient elution represents a fundamental technique in chromatographic separation. In accordance with the principles of NPC, the polarity of the mobile phase is progressively increased—typically starting from a non-polar solvent such as petroleum ether and transitioning to a more polar solvent such as methanol. Elution was carried out sequentially using solvents designated as F1 through F6, with the gradient detailed in Table 5. Each fraction was collected in a separate clean 250 mL round-bottom flask, concentrated to near-dryness using a rotary evaporator, and then reconstituted in 100 μL of solvent for analysis by LC–Orbitrap-HRMS.
Experimental results indicated that NP-d4 was predominantly eluted in moderately polar solvents (fractions F4 and F5), consistent with theoretical predictions regarding its polarity-based chromatographic behavior. In summary, following elution procedure was established; fractions F1 to F3 were eluted and discarded, while F4 and F5 were collected, combined, and concentrated for subsequent analysis.

3.1.4. Selection of SPE Operations

Samples purified by NPC effectively removed the majority of non-polar interferents. However, certain moderately polar interfering compounds remained in the target eluate mixture. To achieve further purification, SPE was performed using a typical reversed-phase sorbent, specifically a C18 cartridge (1g 6 cc). The detailed experimental procedure is described in Section 2.4.2. Following SPE clean-up, the sample extract appeared clear and transparent, with no visible resinous or particulate aggregates, thereby meeting the requirements for subsequent instrumental analysis.

3.2. Method Validation

A five-point calibration curve was developed for NP and NP-d4, with concentration ranges of 125 ng/mL to 2000 ng/mL (dilution factor of 2) and 25 ng/mL to 400 ng/mL (dilution factor of 2), respectively. The correlation coefficients for NP and NP-d4 were 0.9988 and 0.9993, respectively, indicating excellent linearity of the calibration curves for quantitative analysis. In addition, the relative standard deviations (RSDs) of replicate injections at each concentration level were below 15%, confirming the precision and reliability of the instrumental method.
Solvent blanks and procedural blanks were measured to assess the possible background contamination of NP that does not originate from the sample. Specifically, solvent blanks were assessed by injection of optimal grade of methanol before, between, and after sample injections. Seven procedural blanks were prepared by analyzing NP content in 0.5 mL hexane that is used for dilution of petroleum-based sample prior to loading onto NPC column. This sample was brought through the entire measurement procedure and analyzed in the same manner as an actual petroleum sample, and thus could monitor the overall contamination throughout the entire sample-pretreatment process. The limit of detection (LOD) and limit of quantification (LOQ) were defined as the average blank concentration plus three and ten times the standard deviation. As a result, LOD and LOQ were determined to be 1.0 and 2.5 ng/g for NPs, respectively.
Standard addition and recovery experiments were conducted to evaluate the accuracy and precision of the method in crude oil matrices. Six aliquots of crude oil were processed, three of which were fortified with the surrogate NP-d4 (100 ng for each sample) prior to extraction to assess background levels of the target analyte. The remaining three samples were spiked with NPs and NP-d4 at known amounts of 1 μg and 100 ng, respectively. Results showed that method performance was satisfactory, yielding a mean recovery of 82.8 ± 2.6% (n = 6) for NPs and 80.1 ± 2.7% (n = 6) for NP-d4. Since it is well known that gasoline, diesel, and aviation kerosene are relatively less complex in composition and generally exhibit lower matrix interferences compared to crude oil [37], the method optimized and validated in crude oil is expected to be applicable to these refined products with reasonable confidence.
The inter-day and intra-day precision for the developed method was also evaluated. Specifically, NP and NP-d4 were spiked into six aliquots of crude oil samples (20 µg each) at known amounts of 1 μg and 100 ng, corresponding to final concentrations of 50 ng/g and 5 ng/g, respectively. Three aliquots were analyzed on day 0 to assess intra-day precision, while the remaining three were analyzed over the following three consecutive days to evaluate inter-day variation. The relative standard deviations (RSDs) of the measured concentrations were calculated to be 2.4% and 7.1%, respectively, demonstrating good intra- and inter-day precision.

3.3. Method Application

In this study, five crude oil samples and six petroleum products were collected from three representative refinery plants in China, following the procedure described in Section 2.4. The crude oils were sampled from the outlet of the transfer pump, located downstream of the storage tank pipeline and prior to entry into refining units. Among them, crude oils A2, B1, B2, and C were collected from distinct domestic oilfields, while crude oil A1 represented a blend of domestic and imported sources. Together, these samples reflect the diversity of crude oils processed in China, encompassing both geographically distinct domestic oilfields and overseas imports. The five crude oils also showed clear differences in physical properties. Crude oils A2 and B2 remained liquid at room temperature, indicating relatively high proportions of light hydrocarbon fractions. By contrast, crude oils A1, B1, and C exhibited a semi-solid consistency under the same conditions, largely attributable to their higher contents of paraffins and resins. These contrasting characteristics further emphasize the heterogeneous nature of crude oil sources included in this study. In addition, six petroleum products were sampled, consisting of one gasoline, one aviation kerosene, and one diesel oil from each of refinery plants A and B. These were sampled directly from the refined oil storage tanks of the respective facilities.
Using the optimized analytical method established in this study, NPs was detected in all five crude oil samples after subtracting the procedural blanks (n = 3), with concentrations ranging from 102.5 ng/g to 784.4 ng/g and an average value of 391.2 ± 258.4 ng/g. Taking crude oil A1 as an example (other crude oil samples displayed in Supplementary Figure S1) Figure 2a presents the total ion chromatogram (TIC), where the irregular baseline and high ion intensity implied the complex composition of the extracted crude oil sample. In contrast, the chromatograms of NPs, the surrogate, and the internal standard from crude oil A1 (Figure 2b) display low baselines and clean backgrounds, indicating that most interference compounds in crude oil were effectively removed. The detection of substantial NPs levels demonstrates its widespread occurrence in crude oils from different regions. Notably, the levels observed in crude oils were almost two orders of magnitude higher than those typically reported in other environmental matrix, such as surface water (0.13 ng/mL) [38].
In petroleum products, NPs were detected in three of six samples. Specifically, NPs were detected in two gasoline samples at concentrations of 53.8 and 439.1 ng/g, respectively. For diesel oil, NPs were only detected in refinery plant A (7.5 ng/g), but below the limit of detection (<1 ng/g) in refinery plant B. NPs were not detected in either of the aviation kerosene samples (<1 ng/g). To the best of our knowledge, this is the first report of NPs occurrence in crude oil and petroleum products. The detection of NPs in both crude oils and refined products suggests that these compounds may persist through refining and be released during subsequent petroleum use, thereby posing potential risks to human and ecological health. To the best of our knowledge, there is no regulation of NP presence or usage in raw materials and products from petroleum industry. The findings from the current study further highlights the need for the monitoring of NPs in oilfield chemicals and petroleum-derived products as part of environmental and safety assessments.
It should also be noted that the NP peak in crude oil samples (Figure 2b) was broader than that in mixed standards (Figure 2c), and exhibited multiple peak tips. This observation suggests that certain unknown NPs isomers may co-elute with those present in technical standard mixtures. Similarly, some NPs isomers absent from the technical standard mixtures were also detected in the other four crude oil samples as well as in selected petroleum products (two gasoline samples and one diesel oil sample from plant A, displayed n Supplementary Figure S2). Chemically, NPs are a mixture of para-, ortho-, and meta- isomers of substituted phenolic compounds with a straight or branched carbon chain, and para-NP (or 4-NP) comprises approximately 85.6~93.7% of the NPs mixture [39]. Indeed, there are 211 theoretical isomers of 4-NPs and 10 major isomers (4-NP35, 4-NP36, 4-NP37, 4-NP65, 4-NP110, 4-NP111, 4-NP112, 4-NP119, 4-NP193, 4-NP194) in various technical products [40]. Although individual standards for most NP isomers are not yet available, investigating their isomeric profiles in petroleum samples remains of great interest, as such analyses could provide valuable insights into the sources and transformation pathways of NPs across the petroleum production chain. Moreover, different NP isomers have been reported to exhibit varying degrees of endocrine-disrupting activity [39,41]; thus, characterizing the isomeric composition of NPs, particularly in petroleum products, may offer important information on potential health risks associated with petroleum combustion.

3.4. Potential Source of NPs in Crude Oil and Petrolium Products

Nonionic surfactant ethers, particularly octylphenol ethoxylates (OPEOs) and nonylphenol ethoxylates (NPEOs), are widely used as surfactants, emulsifiers, and wetting agents in industrial and commercial applications. In the petroleum industry, emulsifiers are employed at multiple stages of production, from extraction and transportation to refining. For example, in hydraulic fracturing, NPEOs with 3 to 17 EOs units are typically applied at 5~10 mg/L to reduce water–oil interfacial tension, thereby facilitating fluid penetration into rock formations [42]. In transportation, emulsification is also used to reduce the viscosity of extra-heavy crude oil by forming immiscible oil–water mixtures, particularly when diluents are unavailable [43]. Because nonylphenol is the precursor for NPEOs synthesis, commercial products inevitably contain residual nonylphenol. Accordingly, the elevated nonylphenol concentrations observed in two crude oils suggest that NPEOs may still be widely used during extraction and transportation. Although nonylphenol levels may vary with extraction technologies and transportation methods (e.g., pipeline vs. ocean shipping), in this study, crude oils were sampled directly from refinery storage tanks where imports from multiple extraction sites and suppliers had already been mixed. Consequently, the specific sources could not be identified. Future studies should therefore investigate the influence of extraction practices and transportation methods on nonylphenol levels in crude oil.
In this study, NPs were detected in two of the three petroleum products analyzed (gasoline and diesel), but not in aviation kerosene. This suggests that NPs introduced during crude oil extraction and transportation may be partially carried into final petroleum products through the refining process. Moreover, it should be noted that long-chain nonionic surfactant ethers such as NPEOs may undergo decomposition, cleavage, or catalytic reforming under the high-temperature, high-pressure, and catalytic conditions of refining, potentially leading to the formation of NPs [44,45]. To further investigate this hypothesis, future studies could adopt two complementary approaches. Firstly, NP and NPEO concentrations could be quantified in different process streams throughout the refinery to trace NP fate and identify major contributing stages; secondly, laboratory-scale simulations under refinery-relevant conditions (e.g., temperature, pressure, catalytic environments) could be performed to examine the degradation pathways of NPEOs to NP and assess key influencing factors. Such studies would provide critical insights into the transformation mechanisms and operational conditions that promote NP formation during petroleum refining. In addition, petroleum products commonly contain chemical additives that are intentionally added at controlled concentrations to enhance performance or impart new functionalities. For example, alkylphenols have been used as pour point depressants in lubricating oils and as detergent–dispersant fuel additives [46]. Thus, considering these multiple potential sources of NPs in petroleum product as listed above, there is a strong need to investigate the pathways of NPs introduction and transformation along refining chains. Such efforts are of great importance for reducing the release of NPs into the environment during petroleum product consumption and for promoting sustainable development by minimizing emerging contaminants in the petroleum industry. Furthermore, the analytical method developed in this study offers a relatively low-cost and time-efficient approach, which may serve as a practical option for routine monitoring of NP levels in refinery operations.

4. Conclusions

This study focuses on developing a reliable analytical method for the determination of NPs in petroleum matrices, addressing a significant gap in current research. A multistage sample pretreatment method was established to effectively remove complex organic interferences from crude oils and petroleum products. Alumina deactivated with 5% water was selected as the stationary phase for normal-phase chromatography, and a polarity-based gradient elution was optimized to isolate and enrich NPs within key fractions. Subsequently, solid-phase extraction was employed to further concentrate the extracts and eliminate residual impurities, thereby meeting the stringent requirements of trace analysis. Finally, NPs were successfully detected and quantified using LC–Orbitrap-HRMS. Under the optimized parameters, all target compounds were analyzed within 20 min, exhibiting satisfactory linearity, LODs, and recovery. Furthermore, the method’s practical applicability was confirmed through the analysis of practical samples, proving it to be an effective tool for NPs monitoring. The results also revealed the widespread occurrence of NPs in petroleum, highlighting the need for increased attention to its potential environmental release and health implications.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/su17188485/s1: Figure S1: he MS/MS chromatograms of NPs in extracted crude oil A2 (a), B1 (b), B2 (c), and C (d). Target analytes were identified by comparing the retention time of MS2 product ion peak (setting mass error tolerance to 10 ppm) with that in reference standard (within 2%). The MS parameter for detection of NPs were listed in Table 2; Figure S2: The MS/MS chromatograms of NPs in gasoline A (a), diesel oil A (b) and gasoline B (c). Target analytes were identified by comparing the retention time of MS2 product ion peak (setting mass error tolerance to 10 ppm) with that in reference standard (within 2%). The MS parameter for detection of NPs were listed in Table 2.

Author Contributions

Conceptualization, Z.L. and Z.T.; methodology, H.Z. and F.J.; validation, L.W. and S.Z.; formal analysis, H.Z.; investigation, S.Z. and H.Z.; resources, Z.L.; writing—original draft preparation, L.W. and H.Z.; writing—review and editing, F.J. and H.Z.; visualization, H.L.; supervision, H.Z. and G.X.; project administration, Z.T.; funding acquisition, G.X. All authors have read and agreed to the published version of the manuscript.

Funding

The authors declare that this study received funding from Prospective Fundamental Technology Research Projects of China National Petroleum Corporation (2023DJ6907). The funder was not involved in the study design; collection, analysis, or interpretation of data; the writing of this article; or the decision to submit it for publication.

Institutional Review Board Statement

Not Applicable.

Informed Consent Statement

Not Applicable.

Data Availability Statement

Data sharing is available by emailing the corresponding author.

Conflicts of Interest

Authors Zi Long, Hui Luan, and Zhihe Tang are employed by the company China National Petroleum Corporation. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

References

  1. Kapustin, N.O.; Grushevenko, D.A. Analysis of the “Circular Plastics Economy” Phenomena and Its Long-Term Implications for Demand for Petroleum Market. Environ. Sci. Pollut. Res. 2023, 30, 85889–85902. [Google Scholar] [CrossRef]
  2. Wang, H.; Liu, D.; Lv, Y.; Wang, W.; Wu, Q.; Huang, L.; Zhu, L. Ecological and Health Risk Assessments of Polycyclic Aromatic Hydrocarbons (PAHs) in Soils around a Petroleum Refining Plant in China: A Quantitative Method Based on the Improved Hybrid Model. J. Hazard. Mater. 2024, 461, 132476. [Google Scholar] [CrossRef] [PubMed]
  3. Energy Institute. Statistical Review of World Energy 2025; Energy Institute: London, UK, 2025. [Google Scholar]
  4. Chen, J.; Di, Z.; Shi, J.; Shu, Y.; Wan, Z.; Song, L.; Zhang, W. Marine Oil Spill Pollution Causes and Governance: A Case Study of Sanchi Tanker Collision and Explosion. J. Clean. Prod. 2020, 273, 122978. [Google Scholar] [CrossRef]
  5. Yao, Y.; Meng, Y.; Chen, H.; Zhu, L.; Sun, H. Non-Target Discovery of Emerging PFAS Homologues in Dagang Oilfield: Multimedia Distribution and Profiles in Crude Oil. J. Hazard. Mater. 2022, 437, 129300. [Google Scholar] [CrossRef] [PubMed]
  6. Zhao, M.; Yao, Y.; Dong, X.; Baqar, M.; Fang, B.; Chen, H.; Sun, H. Nontarget Identification of Novel Per- and Polyfluoroalkyl Substances (PFAS) in Soils from an Oil Refinery in Southwestern China: A Combined Approach with TOP Assay. Environ. Sci. Technol. 2023, 57, 20194–20205. [Google Scholar] [CrossRef]
  7. Cattelaens, F.; Myrdek, T. Study of the Efficiency of Technical Grade Nonionic Surfactants. J. Surfactants Deterg. 2023, 26, 53–60. [Google Scholar] [CrossRef]
  8. Nassar, A.M.; Ahmed, N.S.; Abdel-Hameed, H.S.; El-Kafrawy, A.F. Synthesis and Utilization of Non-Metallic Detergent/Dispersant and Antioxidant Additives for Lubricating Engine Oil. Tribol. Int. 2016, 93, 297–305. [Google Scholar] [CrossRef]
  9. Zhao, Y.; Ji, J.; Wu, Y.; Chen, S.; Xu, M.; Cao, X.; Liu, H.; Wang, Z.; Bi, H.; Guan, G.; et al. Nonylphenol and Its Derivatives: Environmental Distribution, Treatment Strategy, Management and Future Perspectives. Chemosphere 2024, 352, 141377. [Google Scholar] [CrossRef]
  10. Diehl, J.; Johnson, S.E.; Xia, K.; West, A.; Tomanek, L. The Distribution of 4-Nonylphenol in Marine Organisms of North American Pacific Coast Estuaries. Chemosphere 2012, 87, 490–497. [Google Scholar] [CrossRef]
  11. Deng, Z.-H.; Li, N.; Jiang, H.-L.; Lin, J.-M.; Zhao, R.-S. Pretreatment Techniques and Analytical Methods for Phenolic Endocrine Disrupting Chemicals in Food and Environmental Samples. TrAC Trends Anal. Chem. 2019, 119, 115592. [Google Scholar] [CrossRef]
  12. Hermabessiere, L.; Dehaut, A.; Paul-Pont, I.; Lacroix, C.; Jezequel, R.; Soudant, P.; Duflos, G. Occurrence and Effects of Plastic Additives on Marine Environments and Organisms: A Review. Chemosphere 2017, 182, 781–793. [Google Scholar] [CrossRef]
  13. Careghini, A.; Mastorgio, A.F.; Saponaro, S.; Sezenna, E. Bisphenol A, Nonylphenols, Benzophenones, and Benzotriazoles in Soils, Groundwater, Surface Water, Sediments, and Food: A Review. Environ. Sci. Pollut. Res. 2015, 22, 5711–5741. [Google Scholar] [CrossRef]
  14. Castellani, F.; Vitali, M.; Antonucci, A.; Del Morrone, G.; Cofone, L.; D’Ancona, G.; Pindinello, I.; Mattiucci, S.; Protano, C. Optimization of a Fast and Sensitive Method Based on Matrix Solid-Phase Dispersion-LC-Ms/Ms for Simultaneous Determination of Phthalates and Bisphenols in Mussel Samples. Food Addit. Contam. Part A Chem. Anal. Control Expo. Risk Assess. 2024, 41, 537–549. [Google Scholar] [CrossRef]
  15. Mottier, P.; Frank, N.; Dubois, M.; Tarres, A.; Bessaire, T.; Romero, R.; Delatour, T. LC-MS/MS Analytical Procedure to Quantify Tris(Nonylphenyl)Phosphite, as a Source of the Endocrine Disruptors 4-Nonylphenols, in Food Packaging Materials. Food Addit. Contam. Part A Chem. Anal. Control Expo. Risk Assess. 2014, 31, 962–972. [Google Scholar] [CrossRef] [PubMed]
  16. Gao, H.; Ge, Y.; Tong, L.; Yin, L.; Ma, Q. Quantitative Analysis of Nonylphenol Ethoxylates in Textiles Using Ultrasonic/Microwave-Assisted Extraction Coupled with Ultra-High-Performance Supercritical Fluid Chromatography-Photodiode Array-Tandem Mass Spectrometry. J. Chromatogr. A 2025, 1753, 465985. [Google Scholar] [CrossRef] [PubMed]
  17. Luo, X.; Hong, J.; Zheng, H.; Qin, J.; Wang, M.; Yang, B. A Rapid Synergistic Cloud Point Extraction for Nine Alkylphenols in Water Using High Performance Liquid Chromatography and Fluorescence Detection. J. Chromatogr. A 2020, 1611, 460606. [Google Scholar] [CrossRef] [PubMed]
  18. Andreu, V.; Ferrer, E.; Rubio, J.L.; Font, G.; Picó, Y. Quantitative Determination of Octylphenol, Nonylphenol, Alkylphenol Ethoxylates and Alcohol Ethoxylates by Pressurized Liquid Extraction and Liquid Chromatography–Mass Spectrometry in Soils Treated with Sewage Sludges. Sci. Total Environ. 2007, 378, 124–129. [Google Scholar] [CrossRef]
  19. Yang, Y.; Lu, L.; Zhang, J.; Yang, Y.; Wu, Y.; Shao, B. Simultaneous Determination of Seven Bisphenols in Environmental Water and Solid Samples by Liquid Chromatography–Electrospray Tandem Mass Spectrometry. J. Chromatogr. A 2014, 1328, 26–34. [Google Scholar] [CrossRef]
  20. Salthammer, T.; Uhde, E.; Omelan, A.; Morrison, G.C. Sorption of Semi-Volatile Organic Compounds to Clothing Textiles. Sci. Total Environ. 2025, 981, 179578. [Google Scholar] [CrossRef]
  21. Omar, T.F.T.; Aris, A.Z.; Yusoff, F.M.; Mustafa, S. An Improved SPE-LC-MS/MS Method for Multiclass Endocrine Disrupting Compound Determination in Tropical Estuarine Sediments. Talanta 2017, 173, 51–59. [Google Scholar] [CrossRef]
  22. Erarpat, S.; Bodur, S.; Chormey, D.S.; Öz, E.; Bakirdere, S. Sensitive Determination of 4-n-Nonylphenol in Domestic Wastewater and Liquid Detergent by Binary Solvent Microextraction (BSME) and Gas Chromatography-Mass Spectrometry (GC-MS) with Matrix Matching Calibration. Anal. Lett. 2022, 55, 1080–1092. [Google Scholar] [CrossRef]
  23. Cai, C.; Ying, Y.; Wu, P.; Tang, J.; Wang, L.; Ying, T. Survey of Octylphenol, Nonylphenol, and Bisphenol A in Infant Milk Powders by Solid-Phase Extraction Combined GC/MS Method. J. Food Qual. 2018, 2018, 2848627. [Google Scholar] [CrossRef]
  24. Cserbik, D.; Redondo-Hasselerharm, P.E.; Farre, M.J.J.; Sanchis, J.; Bartolome, A.; Paraian, A.; Herrera, E.M.; Caixach, J.; Villanueva, C.M.M.; Flores, C. Human Exposure to Per- and Polyfluoroalkyl Substances and Other Emerging Contaminants in Drinking Water. npj Clean Water 2023, 6, 16. [Google Scholar] [CrossRef]
  25. Lee, K.; Alava, J.J.; Cottrell, P.; Cottrell, L.; Grace, R.; Zysk, I.; Raverty, S. Emerging Contaminants and New POPs (PFAS and HBCDD) in Endangered Southern Resident and Bigg’s (Transient) Killer Whales (Orcinus Orca): In Utero Maternal Transfer and Pollution Management Implications. Environ. Sci. Technol. 2023, 57, 360–374. [Google Scholar] [CrossRef]
  26. Boti, V.; Kobothekra, V.; Albanis, T.; Konstantinou, I. QuEChERS-Based Methodology for the Screening of Alkylphenols and Bisphenol A in Dairy Products Using LC-LTQ/Orbitrap MS. Appl. Sci. 2021, 11, 9358. [Google Scholar] [CrossRef]
  27. Luo, X.; Zhang, L.; Niu, Z.; Ye, X.; Tang, Z.; Xia, S. Liquid Chromatography Coupled to Quadrupole-Orbitrap High Resolution Mass Spectrometry Based Method for Target Analysis and Suspect Screening of Non-Ionic Surfactants in Textiles. J. Chromatogr. A 2017, 1530, 80–89. [Google Scholar] [CrossRef]
  28. Xie, W.; Zhao, J.; Zhang, Q.; Ye, C.; Zheng, G.; Shan, Q.; Li, L.; Shao, X. Occurrence, Distribution and Bioaccumulation of Alkylphenols in the Pearl River Networks, South China. Ecol. Indic. 2020, 110, 105847. [Google Scholar] [CrossRef]
  29. Faramawy, S.; El-Naggar, A.Y.; El-Fadly, A.M.; El-Sabagh, S.M.; Ibrahim, A.A. Silica, Alumina and Aluminosilicates as Solid Stationary Phases in Gas Chromatography. Arab. J. Chem. 2016, 9, S765–S775. [Google Scholar] [CrossRef]
  30. Neugebauer, F.; Dreyer, A.; Lohmann, N.; Koschorreck, J. Determination of Halogenated Flame Retardants by GC-API-MS/MS and GC-EI-MS: A Multi-Compound Multi-Matrix Method. Anal. Bioanal. Chem. 2018, 410, 1375–1387. [Google Scholar] [CrossRef]
  31. Seok, J.; Phan, N.T.Y.; Kim, J.-C.; Shin, H.; Choi, M. Catalytic Synergy between Lewis Acidic Alumina and Pt in Hydrodechlorination for Plastic Chemical Recycling. J. Am. Chem. Soc. 2024, 146, 23881–23890. [Google Scholar] [CrossRef]
  32. Hu, Y.; Xi, C.; Cao, S.; Wang, G.; Li, X.; Zhang, L.; Zhang, Y. Simultaneous determination of 16 organophosphorous pesticides in vegetables, fruits and tea by gas chromatography coupled with clean-up by mesoporous alumina as solid-phase extraction adsorbent. Se Pu Chin. J. Chromatogr. 2014, 32, 784–788. [Google Scholar] [CrossRef] [PubMed]
  33. Xin, L.; Chen, Y.; Li, M.; Liang, F.; Xia, N.; Wang, L. Determination of Sedative and Anesthetic Drug Residues in Aquatic Food Products Using Solid Phase Extraction (SPE) and Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). Anal. Lett. 2025, 58, 1182–1203. [Google Scholar] [CrossRef]
  34. Cardona, Y.; Korili, S.A.; Gil, A. Use of Response Surface Methodology to Optimize Triclosan Adsorption on Alumina Pillared Clays in a Fixed-Bed Column for Applications in Solid-Phase Extraction. Appl. Clay Sci. 2023, 235, 106879. [Google Scholar] [CrossRef]
  35. Pesek, J.J.; Matyska, M.T. Modified Aluminas as Chromatographic Supports for High-Performance Liquid Chromatography. J. Chromatogr. A 2002, 952, 1–11. [Google Scholar] [CrossRef]
  36. Cui, K.; Wen, J.; Zeng, F.; Zhou, X.; Li, S.; Zeng, Z. Determination of Organophosphate Ester Flame Retardants and Plasticizers in Soil Samples by Microwave-Assisted Extraction Coupled with Silica Gel/Alumina Multilayer Solid-Phase Extraction and Gas Chromatography-Mass Spectrometry. Anal. Methods 2017, 9, 986–993. [Google Scholar] [CrossRef]
  37. Coker, A.K. Characterization of Petroleum and Petroleum Fractions. In Petroleum Refining Design and Applications Handbook; John Wiley & Sons, Ltd.: Hoboken, NJ, USA; Scrivener Publishing LLC.: Beverly, MA, USA, 2018; pp. 31–62. ISBN 978-1-119-25711-0. [Google Scholar]
  38. Wu, M.; Wang, L.; Xu, G.; Liu, N.; Tang, L.; Zheng, J.; Bu, T.; Lei, B. Seasonal and Spatial Distribution of 4-Tert-Octylphenol, 4-Nonylphenol and Bisphenol A in the Huangpu River and Its Tributaries, Shanghai, China. Environ. Monit. Assess. 2013, 185, 3149–3161. [Google Scholar] [CrossRef] [PubMed]
  39. Rashidian, A.; Dušek, J.; Drastik, M.; Smutná, L.; Fritsche, K.; Braeuning, A.; Pijnenburg, D.; van Beuningen, R.; Honkakoski, P.; Poso, A.; et al. Filling the Blank Space: Branched 4-Nonylphenol Isomers Are Responsible for Robust Constitutive Androstane Receptor (CAR) Activation by Nonylphenol. Environ. Sci. Technol. 2024, 58, 6913–6923. [Google Scholar] [CrossRef]
  40. Bhandari, G.; Bagheri, A.R.; Bhatt, P.; Bilal, M. Occurrence, Potential Ecological Risks, and Degradation of Endocrine Disrupter, Nonylphenol, from the Aqueous Environment. Chemosphere 2021, 275, 130013. [Google Scholar] [CrossRef]
  41. Guenther, K.; Kleist, E.; Thiele, B. Estrogen-Active Nonylphenols from an Isomer-Specific Viewpoint: A Systematic Numbering System and Future Trends. Anal. Bioanal. Chem. 2006, 384, 542–546. [Google Scholar] [CrossRef]
  42. Pawar, R.; Vidic, R.D. Impact of Surfactants Used in Oil and Gas Extraction on Produced Water Treatment by Membrane Distillation. Desalination 2024, 586, 117906. [Google Scholar] [CrossRef]
  43. Ratnakar, R.K.; Pandian, S.; Mary, H.; Choksi, H. Flow Assurance Methods for Transporting Heavy and Waxy Crude Oils via Pipelines without Chemical Additive Intervention. Pet. Res. 2025, 10, 204–215. [Google Scholar] [CrossRef]
  44. Ying, G.-G.; Kookana, R.S. Degradation of Five Selected Endocrine-Disrupting Chemicals in Seawater and Marine Sediment. Environ. Sci. Technol. 2003, 37, 1256–1260. [Google Scholar] [CrossRef]
  45. Micić, V.; Kruge, M.A.; Hofmann, T. Variations of Common Riverine Contaminants in Reservoir Sediments. Sci. Total Environ. 2013, 458–460, 90–100. [Google Scholar] [CrossRef]
  46. Zainal, N.A.; Zulkifli, N.W.M.; Gulzar, M.; Masjuki, H.H. A Review on the Chemistry, Production, and Technological Potential of Bio-Based Lubricants. Renew. Sustain. Energy Rev. 2018, 82, 80–102. [Google Scholar] [CrossRef]
Sustainability 17 08485 g001
Figure 1. Schematic diagram of normal-phase chromatographic separation device.
Figure 1. Schematic diagram of normal-phase chromatographic separation device.
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Figure 2. The TICs of extracted crude oil A1 (a) and the MS/MS chromatograms of NPs, NP-d4, and BPA-d16 in extracted crude oil A1 (b) and mixed standard (c). The m/z range for TIC acquisition was 50–750 in ESI negative mode. Target analytes were identified by comparing the retention time of MS2 product ion peak (setting mass error tolerance to 10 ppm) with that in reference standard (within 2%). The MS parameters for detection of NPs, NP-d4, and BPA-d16 are listed in Table 2.
Figure 2. The TICs of extracted crude oil A1 (a) and the MS/MS chromatograms of NPs, NP-d4, and BPA-d16 in extracted crude oil A1 (b) and mixed standard (c). The m/z range for TIC acquisition was 50–750 in ESI negative mode. Target analytes were identified by comparing the retention time of MS2 product ion peak (setting mass error tolerance to 10 ppm) with that in reference standard (within 2%). The MS parameters for detection of NPs, NP-d4, and BPA-d16 are listed in Table 2.
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Table 1. Information on collection of petroleum samples from three refineries in China.
Table 1. Information on collection of petroleum samples from three refineries in China.
Refinery PlantsCollection DateLocationSample TypeSample NameSource
A17 January 2025Northwestern Chinacrude oilcrude oil A1Imported and Domestic
crude oil A2Domestic
petroleum productsgasoline A/
diesel oil A/
aviation kerosene A/
B22 May 2025North Chinacrude oilcrude oil B1Domestic
crude oil B2Domestic
petroleum productsGasoline B/
diesel oil B/
aviation kerosene B/
C25 October 2023Northeastern Chinacrude oilcrude oil CDomestic
Table 2. Liquid chromatographic mobile phase gradient for NPs detection method.
Table 2. Liquid chromatographic mobile phase gradient for NPs detection method.
TimeA (0.35% Ammonia in Water, %)B (Methanol, %)
0.0095.05.0
1.0095.05.0
5.001.099.0
7.001.099.0
7.1095.05.0
9.0095.05.0
Table 3. Mass spectrometry information of NP, surrogate, and internal standard.
Table 3. Mass spectrometry information of NP, surrogate, and internal standard.
NumberSubstanceRetention Time
(min)		Precursor Ion
(m/z)		Product Ion
(m/z)		Collision Energy
(%)		Remarks
1NP6.37219.1754133.065850Target
2NP-d46.54223.2005110.067550Surrogate
3BPA-d165.24231.1329216.109145Internal standard
Table 4. Adsorption effect of different packing materials.
Table 4. Adsorption effect of different packing materials.
Fractionation NumberElution SolventRelative Fraction
FlorisilSilicaAlumina
F1n-hexaneNDND *ND *
F2n-hexane/dichloromethane (4:1, v/v)NDNDND
F3n-hexane/dichloromethane (1:1, v/v)20.8%NDND
F4dichloromethane79.2%98.8%ND
F5dichloromethane/methanol (3:1, v/v)ND1.2%71.6%
F6dichloromethane/methanol (1:1, v/v)NDND23.7%
F7methanolNDND4.7%
* ND represents not detected.
Table 5. Impact of water content on alumina column.
Table 5. Impact of water content on alumina column.
Fractionation NumberSolventsRelative Fraction
Alumina5% Deactivated Alumina
F1n-hexaneNDND *
F2n-hexane/dichloromethane (4:1, v/v)NDND
F3n-hexane/dichloromethane (1:1, v/v)NDND
F4dichloromethane2%85%
F5dichloromethane/methanol (2:1, v/v)90%15%
F6methanol8%ND
* ND represents not detected.
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MDPI and ACS Style

Wang, L.; Zhang, S.; Long, Z.; Ju, F.; Zhen, H.; Luan, H.; Xiu, G.; Tang, Z. Determination of Nonylphenol in Crude Oils and Petroleum Products by Liquid Chromatography–Mass Spectrometry: Implications for Sustainable Petroleum Refining. Sustainability 2025, 17, 8485. https://doi.org/10.3390/su17188485

AMA Style

Wang L, Zhang S, Long Z, Ju F, Zhen H, Luan H, Xiu G, Tang Z. Determination of Nonylphenol in Crude Oils and Petroleum Products by Liquid Chromatography–Mass Spectrometry: Implications for Sustainable Petroleum Refining. Sustainability. 2025; 17(18):8485. https://doi.org/10.3390/su17188485

Chicago/Turabian Style

Wang, Limin, Shijie Zhang, Zi Long, Feng Ju, Huajun Zhen, Hui Luan, Guangli Xiu, and Zhihe Tang. 2025. "Determination of Nonylphenol in Crude Oils and Petroleum Products by Liquid Chromatography–Mass Spectrometry: Implications for Sustainable Petroleum Refining" Sustainability 17, no. 18: 8485. https://doi.org/10.3390/su17188485

APA Style

Wang, L., Zhang, S., Long, Z., Ju, F., Zhen, H., Luan, H., Xiu, G., & Tang, Z. (2025). Determination of Nonylphenol in Crude Oils and Petroleum Products by Liquid Chromatography–Mass Spectrometry: Implications for Sustainable Petroleum Refining. Sustainability, 17(18), 8485. https://doi.org/10.3390/su17188485

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