HIPS and FTIR Instrument Comparison - ahzs645/aethdata-analysis GitHub Wiki

1. Purpose

HIPS	FTIR
Measure light absorption (Fabs) at 633 nm to determine black carbon via mass absorption cross-section (MAC)	Predict TOR-equivalent elemental carbon (EC) and identify functional groups using infrared spectroscopy and multivariate regression

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2. Instrument Quick Specifications

Parameter	HIPS	FTIR
Light Source	632.8 nm He-Ne laser (1.5 mW)	Broadband IR (4000-420 cm⁻¹)
Detection System	Integrating sphere + plate (dual detector)	Mercury-cadmium-telluride detector
Sample Area	~1 cm diameter beam	6 mm aperture diameter
Filter Type	25 mm PTFE membrane	47 mm PTFE membrane
Analysis Mode	Transmission + backscatter	Transmission only
Resolution	Single wavelength	4 cm⁻¹ nominal

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3. Parallel Workflow Comparison

flowchart TD
    A[PM2.5 Sample Collection] --> B[PTFE Filter Collection]
    
    B --> C[Light Source]
    
    subgraph Light ["Light Source"]
        C --> D[633 nm He-Ne Laser]
        C --> E[FT-IR Spectroscopy 4000-420 cm⁻¹]
    end
    
    subgraph Measurement ["Measurement Approach"]
        D --> F[Integrating Sphere + Plate System]
        E --> G[Transmission Mode FT-IR]
        F --> H[Transmitted Light t]
        F --> I[Backscattered Light r]
        G --> J[Absorption Spectra]
    end
    
    subgraph Processing ["Data Processing"]
        H --> K[Calculate Absorptance A = 1-t/1-r]
        I --> K
        J --> L[Baseline Correction Smoothing Splines]
        L --> M[PLS Regression Analysis]
    end
    
    subgraph Analysis ["Analysis Methods"]
        K --> N[Light Absorption Coefficient Fabs]
        M --> O[Predict TOR-Equivalent EC]
        M --> P[Functional Group Identification]
    end
    
    subgraph Calibration ["Calibration & Validation"]
        N --> Q[Registration Filter Consistency Check]
        O --> R[TOR EC Reference Calibration]
        Q --> S[Field Blanks Quality Control]
        R --> S
        S --> T[Collocated Sampling Validation]
        T --> U_CAL[Performance Metrics R² MAD Bias]
    end
    
    subgraph Outputs ["Carbon Measurements"]
        N --> BC[Black Carbon BC = Fabs/MAC]
        O --> EC[Elemental Carbon EC]
        P --> SC[Source Classification Typical/Atypical]
    end
    
    %% Cross-method comparison
    BC --> X[Carbon Measurement Comparison]
    EC --> X
    
    %% Style classes
    classDef hips fill:#fff3e0,stroke:#ef6c00,stroke-width:2px
    classDef ftir fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
    classDef shared fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px
    classDef overlap fill:#e1f5fe,stroke:#01579b,stroke-width:2px
    
    class D,F,H,I,K,N,Q,BC hips
    class E,G,J,L,M,O,P,R,EC,SC ftir
    class A,B,C,X shared
    class S,T,U_CAL overlap

Color Legend:

• 🟠 Orange: HIPS-specific steps
• 🟣 Purple: FTIR-specific steps
• 🟢 Green: Shared infrastructure
• 🔵 Blue: Overlapping validation procedures

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4. Key Equations

HIPS:

• Absorptance: $A = 1 - \frac{t}{1-r}$

  where $r$ = sphere signal, $t$ = plate signal

• Absorption Coefficient: $F_{abs} = \frac{f}{V} \ln\left(\frac{1-r}{t}\right) \quad [\text{Mm}^{-1}]$

  where $f$ = filter area, $V$ = air volume sampled

• Black Carbon: $BC = \frac{F_{abs}}{MAC} \quad [\mu\text{g/m}^3]$

FTIR:

• PLS Prediction: $\hat{y}_{EC} = \mathbf{X} {\hat{\beta}}$

  where $\mathbf{X}$ = spectra matrix, ${\hat{\beta}}$ = regression coefficients

• Mass Concentration: $EC = \frac{\hat{y}{EC} \times A{filter}}{V_{air}} \quad [\mu\text{g/m}^3]$

  where $A_{filter}$ = filter area factor, $V_{air}$ = air volume sampled

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5. Calibration Approach

HIPS	FTIR
• Registration filter for session consistency	• TOR EC measurements as reference values
• Field blanks (r + t = 1 for clean PTFE)	• PLS regression calibrated to collocated samples
• No external reference needed	• Cross-validation with thermal-optical analysis
• MAC values: 8-18 m²/g (season-dependent)	• Multilevel modeling for atypical/typical samples

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6. Measurement Uncertainties

HIPS	FTIR
• Precision: σ = 0.17 Mm⁻¹ (11% relative)	• CSN Performance: R² = 0.886, MAD = 19.8%
• MAC variability: dominates uncertainty	• IMPROVE Performance: R² = 0.956, MAD = 19.5%
• Filter heterogeneity: ±10% (field blanks)	• Classification accuracy: 84-100% specificity

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7. Strengths & Limitations

HIPS	FTIR
✅ Strengths	✅ Strengths
Non-destructive single-filter analysis	Chemical specificity via functional group identification
Direct absorption measurement at climate-relevant wavelength	Source apportionment through multilevel modeling
Real-time results with established protocols	Multiple analytes (EC, OC, functional groups) from one spectrum
Self-calibrating using filter optical properties	Adaptable calibrations for different aerosol types
❌ Limitations	❌ Limitations
Single wavelength limits source discrimination	Requires reference data (TOR) for calibration
MAC variability introduces seasonal uncertainty	Computational complexity in data processing
Iron dust interference affects absorption estimates	Lower performance on low-mass samples (vs IMPROVE)

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8. Cross-Method Validation Potential

Complementary Measurements:

• HIPS BC vs FTIR EC: Both measure refractory carbon but via different physical principles
• Seasonal trends: HIPS MAC variability vs FTIR source classification
• Quality assurance: Independent validation of carbonaceous aerosol measurements

Validation Approach:

1. Collocated sampling on same filter type (PTFE)
2. Time-series comparison for trend analysis
3. Source-specific correlation using FTIR classification
4. Uncertainty quantification through dual-method approach

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