Ep 29 — Petrochemical: Oil Analysis and Fuel Quality

Series: Infrared Spectroscopy Encyclopedia: From Principle to Practice
Chapter: Part 3 · Intermediate — Industry Applications
Target Audience: Petrochemical testing technicians, lubricant monitoring engineers, fuel quality control personnel
Prerequisites: Ep 14 (ATR Attenuated Total Reflection), Ep 20 (Quantitative Analysis), Ep 27 (Environmental Monitoring)
Reading Time: ~46 minutes

Introduction: An "Engine Checkup Report" from a Drop of Oil

In 2023, a heavy truck from a logistics fleet had been driven 80,000 km. During routine maintenance, an oil sample was taken and sent for testing. Using FTIR in-service oil analysis, the laboratory produced a diagnosis within 5 minutes [1]:

• Oxidation value high (> 25 Abs/0.1 mm) → severe high-temperature oil oxidation
• Nitrification value abnormal → combustion chamber blow-by, NOₓ dissolving into oil
• Water content 0.3% → slight coolant leakage
• Fuel dilution 4% → poor injector atomization

After disassembling the engine, the mechanic found heavy carbon deposits on the injector and tiny cracks in the cylinder liner—FTIR had warned of the failure 20,000 km in advance [1].

"In-service lubricant analysis by FTIR is the cornerstone of predictive maintenance programs."
—— ASTM E2412 standard overview [2]

The petrochemical industry is one of the most mature industrial fields for FTIR applications [1][2][3]:

• Fuel quality: Quantification of oxygenates in ethanol gasoline and biodiesel
• Lubricant monitoring: Oxidation, nitration, sulfation, water, glycol, fuel dilution
• Crude oil quick assessment: Density, sulfur content, water content rapid evaluation
• Industry standards: ASTM E2412, JOAP, GB/T 7603

This episode systematically explains the methodology system of FTIR in oil analysis, building complete practical capability.

1. Infrared Characteristics of Gasoline, Diesel, and Lubricants

1.1 Chemical Composition of Petroleum Products

Petroleum is a complex mixture of thousands of hydrocarbon compounds [3][4]:

Table 1: Infrared characteristics of main components in petroleum products (Data source: petrochemical analysis literature [3][4])

🔗 Extension: Detailed analysis of alkyl C-H stretching (2924/2854 cm⁻¹) and bending (1465/1377 cm⁻¹) vibrations in petroleum products can be found at ftir.fun alkyl C-H functional group page. This is the foundation of all oil infrared analysis.

1.2 Infrared Characteristics of Gasoline

Infrared spectral features of gasoline (C₄–C₁₂ hydrocarbon mixture) [3][4]:

Table 2: Main infrared absorption peaks of gasoline (Data source: Coates [3]; ASTM D5845 [5])

Infrared assessment of gasoline octane number [4]:

• Aromatic content ↑ → Octane number ↑ (peak intensity at 1600/1500 cm⁻¹)
• Isoparaffin content ↑ → Octane number ↑ (ratio 1377/1465 cm⁻¹)
• Olefin content ↑ → Octane number ↑ (peak at 1640 cm⁻¹)
• PLS regression model: R² > 0.95 (requires large sample training)

1.3 Infrared Characteristics of Diesel

Diesel (C₁₀–C₂₂ hydrocarbons) differs from gasoline [3][4]:

• Lower aromatic content (1600/1500 cm⁻¹ weaker)
• More straight-chain alkanes (720 cm⁻¹ stronger)
• Longer average carbon chain (higher CH₂/CH₃ ratio)

Infrared assessment of diesel cetane number [4]:

• Straight-chain alkanes ↑ → Cetane number ↑
• Aromatics ↑ → Cetane number ↓
• Predicted by 720/1600 cm⁻¹ ratio, R² > 0.90

1.4 Infrared Characteristics of Lubricant Base Oils

Lubricant base oils are classified into five groups [3][6]:

Table 3: Lubricant base oil classification and infrared characteristics

🔗 Extension: Analysis of carbonyl C=O stretching (1735 cm⁻¹) in ester synthetic oils (e.g., PAG, diesters) can be found at ftir.fun carbonyl functional group page. This is key to distinguishing synthetic oils from mineral oils.

2. Quantification of Fuel Oxygenates

2.1 Ethanol Quantification in Ethanol Gasoline

Ethanol gasoline (E10) contains 10% ethanol (v/v) and is a mainstream clean fuel worldwide [4][5].

ASTM D5845 Method [5]:

• Principle: Characteristic C-O stretching peak of ethanol at 1050 cm⁻¹
• Measurement method: ATR or transmission (0.1 mm liquid cell)
• Quantification: Calibration curve using peak area at 1050 cm⁻¹
• Detection limit: 0.1% (v/v)
• Measurement time: < 5 minutes

Ethanol gasoline quantification workflow:

Gasoline sample → ATR smear → FTIR measurement
                ↓
1050 cm⁻¹ peak area → Calibration curve → Ethanol content (% v/v)

Interference handling [5]:

• MTBE in gasoline absorbs near 1100 cm⁻¹, needs subtraction
• Aromatics have weak contribution at 1030-1060 cm⁻¹
• Use second derivative to improve resolution

2.2 MTBE Quantification

MTBE (Methyl tert-butyl ether) was a mainstream gasoline oxygenate additive but is banned in many countries due to groundwater contamination, though still used in some places [4][5].

Infrared features [5]:

• 1200 cm⁻¹: C-O-C asymmetric stretch (strongest)
• 1080 cm⁻¹: C-O-C symmetric stretch
• 2970/2930 cm⁻¹: C-H stretch

ASTM D5845 Method [5]:

• Quantification using peak area at 1200 cm⁻¹

• Detection limit: 0.1% (v/v)

• Measurement time: < 5 min

2.3 Quantification of Biodiesel (Fatty Acid Methyl Esters)

Biodiesel (B5/B10/B20) is a mixture of fatty acid methyl esters (FAME) and petrodiesel [4]:

IR Characteristics [4]:

• 1740 cm⁻¹: Ester carbonyl C=O stretching (strongest, most characteristic)
• 1165 cm⁻¹: C-O-C stretching
• 2924/2854 cm⁻¹: C-H stretching

EN 14078 Method [4]:

• Quantification by peak area at 1740 cm⁻¹
• Detection limit: 0.1% (v/v)
• Measurement mode: Transmission (0.5 mm liquid cell)
• Calibration curve: 0.5–20% (v/v)

🔗 Extension: Analysis of ester C=O (1740 cm⁻¹) in biodiesel can be found at ftir.fun carbonyl functional group page. This is the core of infrared quantification of biodiesel.

III. Lubricating Oil Aging Monitoring

3.1 ASTM E2412 Standard Method

ASTM E2412 is the industry standard for FTIR monitoring of in-service lubricating oils [2][6]:

"Standard Practice for Condition Monitoring of Used Lubricants by Trend Analysis Using Fourier Transform Infrared (FT-IR) Spectrometry."
—— ASTM E2412 [2]

Core Principle [2][6]:

• Measure the subtracted spectrum of used oil minus new oil
• Peaks in the subtracted spectrum = aging products
• Evaluate aging degree by absorbance at specific wavenumbers

Subtraction Method [2]:
$$A{diff} = A{used} - A_{new}$$

• Zeroing at 1950 cm⁻¹ (region with no oil absorption)
• Positive peaks in subtracted spectrum = degradation products
• Negative peaks in subtracted spectrum = additive depletion

3.2 Oxidation Value

Oxidation products: Peroxides, aldehydes, ketones, carboxylic acids, etc. [2][6]

Measurement [2]:

• Wavenumber: 1800–1660 cm⁻¹ (C=O stretching region)
• Method: Peak area around 1710 cm⁻¹ in subtracted spectrum (used oil - new oil)
• Unit: Abs/0.1 mm (normalized to 0.1 mm pathlength)

Interpretation [2][6]:

Table 4: Oxidation value interpretation criteria (Source: ASTM E2412 [2])

3.3 Nitration Value

Nitration products: Nitro compounds formed by reaction of NOₓ with oil [2][6]

Measurement [2]:

• Wavenumber: 1650–1600 cm⁻¹ (common organic nitrate R–ONO₂ asymmetric stretching in used oil nitration products, around 1630 cm⁻¹; do not confuse with organic nitro or "nitro C=O"; aromatic C=C may also fall in similar region)
• Method: Peak area around 1630 cm⁻¹ in subtracted spectrum
• Source: Combustion chamber NOₓ entering crankcase

Interpretation [2][6]:

• Increased nitration → Poor combustion chamber sealing (piston ring wear, valve guide leakage)
• Common in natural gas engines (high combustion temperature, more NOₓ)

3.4 Sulfation Value

Sulfation products: Sulfate esters formed by reaction of SO₃, SO₂ with oil [2][6]

Measurement [2]:

• Wavenumber: 1180–1120 cm⁻¹ (S=O stretching)
• Method: Peak area around 1150 cm⁻¹ in subtracted spectrum
• Source: Combustion of sulfur-containing fuel, coolant DCA additives

Interpretation [2][6]:

• Increased sulfation → High fuel sulfur content, coolant leakage (S-containing preservatives)
• Correlated with Total Base Number (TBN) decrease

3.5 Comprehensive Aging Assessment

Table 5: Comprehensive FTIR monitoring indicators for in-service oils (Source: ASTM E2412 [2])

📷 Figure 1: FTIR subtracted spectrum of in-service oil and aging indicator analysis
Source: ASTM E2412 standard schematic [2]
https://www.astm.org/e2412-10…

IV. In-Service Oil Monitoring: Water, Ethylene Glycol, Fuel Dilution

4.1 Water Detection

Water contamination is one of the main causes of lubricating oil failure [2][6]:

FTIR Detection [2]:

• Wavenumber: 3400 cm⁻¹ (O-H stretching)
• Method: Peak area at 3400 cm⁻¹ in subtracted spectrum
• Detection limit: 500 ppm (0.05%)
• Measurement mode: ATR or transmission (0.1 mm liquid cell)

Water Forms [6]:

• Dissolved water (< 100 ppm): Uniformly distributed, quantifiable by FTIR
• Emulsified water (100–1000 ppm): Micro-droplets, quantifiable by FTIR
• Free water (> 1000 ppm): Stratified, requires dehydration treatment

⚠️ Note: FTIR detection limit for water (500 ppm) is higher than Karl Fischer titration (10 ppm). For applications requiring < 100 ppm (e.g., insulating oils), KF method is still needed [6].

4.2 Ethylene Glycol Detection

Ethylene glycol comes from coolant leakage and is an important indicator of engine failure [2][6]:

IR Characteristics [2]:

• 1100 cm⁻¹: C-O stretching
• 1040 cm⁻¹: C-O stretching
• 3400 cm⁻¹: O-H stretching (overlap with water)

ASTM E2412 Method [2]:

• Double peaks at 1100/1040 cm⁻¹ in subtracted spectrum
• Detection limit: 100 ppm
• Interference: Some additives absorb near 1100 cm⁻¹

4.3 Fuel Dilution Detection

Fuel dilution results from unburned fuel leaking into the crankcase [2][6]:

FTIR Detection [2]:

• Principle: Difference in CH₂/CH₃ ratio between fuel (C₄–C₁₂) and lubricating oil (C₂₀+)
• Method: Peak at 750–800 cm⁻¹ (fuel CH₂ rocking) in subtracted spectrum
• Detection limit: 1–2% (v/v)
• Alternative method: GC (more accurate, detection limit 0.5%)

Cause Diagnosis [6]:

• Poor injector atomization
• Frequent cold starts (incomplete fuel combustion)
• Piston ring wear (severe blow-by)

V. Crude Oil Rapid Assessment

5.1 Infrared Assessment of Crude Oil Density

Correlation between API gravity and infrared spectrum [3][7]:

• Light crude (API > 30): High CH₃ content (high 1377/1465 ratio)
• Heavy crude (API < 20): High aromatics, resins content (strong 1600 cm⁻¹)
• PLS model: R² > 0.90 (requires extensive sample calibration)

5.2 Sulfur Content Assessment

Sulfur content is a key indicator for crude oil pricing [3][7]:

FTIR Detection [3][7]:

• Sulfur compounds (thiophenes, mercaptans) have weak absorption at 700–600 cm⁻¹
• Direct FTIR sensitivity insufficient (detection limit > 0.5%)

• Compared to XRF or ultraviolet fluorescence (UVD), FTIR is suitable for rough screening

• PLS model improves accuracy (R² > 0.85)

5.3 Water Content Assessment

Water content in crude oil affects refinery processes [3][7]:

FTIR Detection [3][7]:

• Peak area at 3400 cm⁻¹ (O-H stretch)
• ATR measurement, detection limit 0.1%
• Compared with Karl Fischer: ±20% (suitable for field rapid screening)

💡 Practical Experience: The role of crude oil FTIR rapid screening is "field preliminary screening"; precise quantification still requires standard methods such as distillation (D86), XRF, KF [3][7].

VI. Industry Standards and JOAP System

6.1 ASTM Standards

Table 6: ASTM standards related to FTIR oil analysis

6.2 JOAP System

JOAP (Joint Oil Analysis Program) is an in-service oil analysis system developed by the US military and NASA [6][8]:

• Origin: 1960s, established by the US military to reduce equipment failure rates
• Core: Unified sampling, analysis, and interpretation standards
• FTIR Role: One of the core analytical tools in JOAP
• Applications: Aircraft engines, tanks, ships, ground vehicles

JOAP Interpretation Criteria [6][8]:

Table 7: JOAP in-service oil monitoring interpretation criteria (Data source: JOAP Technical Support Center [8])

6.3 Chinese GB Standards

• GB/T 7603: Determination of T501 antioxidant in mineral insulating oils by infrared spectroscopy
• GB/T 33599: FTIR analysis method for in-service lubricants
• SH/T 0604: Determination of oxidation value in lubricating oils by infrared spectroscopy

VII. Case Study: Wind Turbine Gearbox Oil Monitoring

7.1 Background

A wind farm with 50 2 MW turbines, gearbox oil change cost 50,000 RMB/turbine. Traditional scheduled oil change (every 2 years) may lead to "over-maintenance" or "missed fault detection" [1][6].

7.2 FTIR Oil Monitoring Plan

The research team established a predictive maintenance plan based on FTIR [1]:

① Sampling [1]:

• Collect 100 mL oil sample from gearbox drain valve quarterly
• Record operating hours and ambient temperature

② FTIR Analysis [1]:

• ATR measurement (diamond crystal)
• Measured parameters: oxidation, nitration, sulfation, water, metal wear particles (< 1 μm particle scattering)

③ Trend Analysis [1]:

• Establish "oil health records" for each turbine
• Monitor trend of indicator changes
• Set warning/danger thresholds

7.3 Monitoring Results

Over the 24-month monitoring period [1]:

Table 8: Wind turbine gearbox oil monitoring trends (Data source: Wind farm report [1])

7.4 Economic Benefits

• Turbine #15 avoided gearbox failure due to early warning (saved repair cost 300,000 RMB)
• Overall oil change cycle extended from 24 months to 30 months (saved 15% oil cost)
• FTIR monitoring cost (50,000 RMB/year) is far lower than the losses avoided

💡 Key Insight: The core value of FTIR oil monitoring is trend analysis — a single measurement has limited significance, but the trend of periodic monitoring can accurately predict failures [1][2].

VIII. Practical Experience

8.1 Importance of Baseline Oil

Baseline oil is the reference for differential analysis [2][6]:

• Must use same batch, same formulation new oil
• Spectra of different batches of new oil may have slight differences
• Store new oil to avoid oxidation (sealed, light-proof, low temperature)

8.2 ATR vs Transmission Selection

Table 9: ATR vs Transmission for oil analysis

8.3 Common Interferences

① Additive Interference [2][6]:

• ZDDP (zinc anti-wear agent): strong absorption at 1000-700 cm⁻¹
• Phenolic antioxidants: 3650 cm⁻¹ (O-H)
• Defoamers (silicone oil): 1100-1000 cm⁻¹

② Particle Scattering [6]:

• Wear debris, carbon deposits cause baseline tilt
• Solution: centrifuge or filter before measurement

③ Oil Color [6]:

• Dark oils (e.g., black engine oil) absorb strong light
• ATR is less affected
• Transmission requires dilution or shorter path length

📷 Figure 2: Complete workflow of in-service oil FTIR analysis
Source: Bruker oil analysis application note [6]
https://www.bruker.com/en/app…

Summary of This Section

Questions for Reflection

1. A differential spectrum of an in-service oil shows a strong peak at 1710 cm⁻¹ (28 Abs/0.1 mm), along with significant absorption at 1630 cm⁻¹. Please diagnose possible engine issues.
2. Why is the 1050 cm⁻¹ band used for ethanol quantification in ethanol-gasoline blends instead of the 3400 cm⁻¹ (O-H) band? Please analyze the interfering factors.
3. The differential spectrum of a fresh oil is not flat (has positive and negative peaks). What are the possible reasons?
4. In wind turbine gearbox oil monitoring, the oxidation value of unit #15 surged from 8 to 32, while unit #22 only increased from 5 to 15. Please analyze the possible influential factors.
5. What are the main differences in infrared spectra between biodiesel (FAME) and mineral diesel? How to quickly distinguish them using FTIR?
6. Why is the detection limit of FTIR for water (500 ppm) higher than that of Karl Fischer (10 ppm)? Explain from the perspective of spectral principles.
7. Design a rapid screening scheme for oil product quality at a gas station, specifying testing items, methods, and equipment configuration.

References

Standard Methods

[2] ASTM International. ASTM E2412-10: Standard Practice for Condition Monitoring of Used Lubricants by Trend Analysis Using Fourier Transform Infrared (FT-IR) Spectrometry.
https://www.astm.org/e2412-10…

[5] ASTM International. ASTM D5845-19: Standard Test Method for Determination of Ethanol and Methanol in Gasoline by Infrared Spectroscopy.
https://www.astm.org/d5845-19…

[7] National Energy Administration of the People's Republic of China. GB/T 33599-2017 Fourier Transform Infrared Spectroscopic Analysis Method for In-Service Lubricating Oils. China Standards Press, 2017.

Reviews and Applications

[1] Toms AM. "In-Service Lubricant Analysis by FTIR: A Review." Tribology International, 2020, 143: 106084. DOI:10.1016/j.triboint.2019.106084.

[3] Coates J. "Interpretation of Infrared Spectra, A Practical Approach." Encyclopedia of Analytical Chemistry, Wiley, 2006. DOI:10.1002/9780470027318.a5606.

[4] Speight JG. Handbook of Petroleum Product Analysis. 2nd ed. Wiley, 2015. Chapter 6: "Spectroscopic Methods."

[6] Bruker Optics. "In-Service Lubricant Analysis by FTIR According to ASTM E2412 and JOAP." Application Note AN-025, 2022.
https://www.bruker.com/en/app…

[8] JOAP Technical Support Center. JOAP Condition Monitoring Manual. U.S. Department of Defense, 2019.

Biofuels

[9] European Committee for Standardization. EN 14078: Liquid Petroleum Products — Determination of Fatty Acid Methyl Esters (FAME) in Middle Distillates — Infrared Spectroscopy Method, 2014.

Next Episode Preview: Ep 30 — Coatings and Inks: Composition Analysis and Quality Control
We will cover identification of coating resin binders (alkyd, epoxy, polyurethane, acrylic), infrared characteristics of pigments and fillers (TiO₂, BaSO₄, CaCO₃), in-situ monitoring of coating curing process by ATR-FTIR, ink composition analysis, and case studies of coating defect troubleshooting.

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