Quantitative Analysis of lead (Pb) in Soil Using Laser-Induced Breakdown Spectroscopy Based on Signal Enhancement of Conductive Materials

Overview

Li and colleagues at Wuhan Polytechnic University investigate how adding conductive materials (sodium chloride and graphite) to soil tablets prior to laser-induced breakdown spectroscopy (LIBS) analysis improves the sensitivity and accuracy of quantitative lead (Pb) detection. The paper evaluates three univariate and three multivariate chemometric models (partial least-squares regression [PLSR], least-squares support vector machine [LS-SVM], and extreme learning machine [ELM]) against a 10-level spiked-soil calibration series. The best-performing configuration was a PLSR model on graphite-amended samples, achieving a prediction correlation coefficient (Rp) of 0.994 with a limit of detection (LOD) of 26.142 mg Pb/kg soil by the univariate Pb I 405.78 nm line. The work is a methodological study; it does not measure Pb in food matrices.

Study design

This is a laboratory methods-development study. The authors prepared a Pb-contaminated soil calibration set by spiking the certified reference material (CRM) agricultural soil GBW070046 (National Institute of Metrology, China) with Pb(NO3)2 solutions to reach 10 concentration levels: 276, 552, 828, 1104, 1380, 1656, 1932, 2208, 2484, and 2760 mg Pb/kg. Each concentration was pressed into 12 mm diameter, 2 mm thick tablets (0.3 g at 10 MPa, 30 s). Three tablets were prepared per concentration level.

For each additive condition, 50 soil tablets (30 for calibration, 20 for prediction) were used. The additive concentrations studied were 10%, 15%, 20%, 25%, and 30% by mass for both NaCl and graphite, with no-additive controls.

LIBS spectra were acquired over 230.55 to 883.77 nm (22,036 spectral variables). Sixteen spots per tablet were sampled in a 4x4 grid with 1 mm steps; five spectra per spot were averaged, giving 80 spectra per tablet. The mean of these 80 spectra was the representative spectrum for each tablet. Data preprocessing used wavelet transform (Daubechies 5, decomposition scale 3), area normalization, and median absolute deviation (MAD) outlier rejection.

Instrument

LIBS system components (Section 3.2):

• Pulsed laser: Q-switched Nd:YAG (Vlite-200, Beamtech Optronics, Beijing), 532 nm, up to 200 mJ pulse energy, 8 ns pulse duration, 1 to 10 Hz repetition rate; experimental energy set to 110 mJ
• Spectrometer: Echelle grating (SR-500i-A-R, Andor Technology, Belfast)
• Detector: intensified charge-coupled device (ICCD) camera (iStar DH340T, Andor Technology)
• Delay generator: DG645, Stanford Research Systems
• 3D crater profiler: VK-X-1000 confocal scanner (Keyence, Osaka)
• Delay time: 4 microseconds; lens-to-sample distance: 98 mm (focal length 100 mm); ICCD gain: 2000
• Wavelength calibration: Hg-Ar lamp (HG-1, Ocean Optics); intensity calibration: deuterium-halogen lamp (DH-2000-BAL-CAL, Ocean Optics)
• Software: Andor SOLIS v4.26 (acquisition); Unscrambler X 10.1 and MATLAB R2009a (data processing); Design Expert v8.05 (parameter optimization)

Samples

The Pb concentration range (276 to 2760 mg/kg) represents moderately to highly contaminated agricultural soil in a Chinese industrial context. These concentrations are well above typical background (usually below 50 mg/kg) and serve as a calibration series rather than a survey of environmental occurrence.

Results values

Optimal additive concentrations

Based on spectral intensity, signal-to-background ratio (SBR), signal-to-noise ratio (SNR), and relative standard deviation (RSD) of three Pb emission lines (Pb I 283.31 nm, Pb I 368.35 nm, Pb I 405.78 nm):

• Optimal NaCl addition: 10% (highest or near-highest intensity for all three Pb lines; lowest RSD; Pb I 405.78 nm showed the largest SBR)
• Optimal graphite addition: 20% (best overall spectral parameters across the three Pb lines)
• Pb I 405.78 nm consistently showed the highest SBR and SNR across both additive conditions and was selected as the primary line for univariate modeling

Plasma parameters with optimal additives (Section 2.2)

Ablation crater dimensions with optimal additives (inverted conical craters observed with additives; borehole without):

Univariate model performance (Section 2.3.1)

With 10% NaCl (Figure 6):

With 20% graphite (Figure 7):

Without additives (Figure 8), best-performing line only:

The lowest overall LOD was 26.142 mg/kg, obtained with the Pb I 405.78 nm line and 20% graphite.

Multivariate model performance (Table 2)

With 10% NaCl:

With 20% graphite:

Without additives:

The PLSR model with 20% graphite yielded the best prediction accuracy overall (Rp = 0.993; RMSEP = 108.609 mg/kg). The LS-SVM model achieved Rc = 1.000 in all additive conditions, indicating overfitting on the calibration set; its prediction RMSEP values (359 to 447 mg/kg) were substantially higher than those of PLSR and ELM.

LOD/LOQ

The LOD was computed per IUPAC convention from the calibration models. No LOQ values are reported by the paper. LOD values by condition are tabulated in the Results values section above. The lowest LOD across all conditions was 26.142 mg/kg (Pb I 405.78 nm, 20% graphite). The paper does not report blank-based or noise-based LOD calculations; the stated LOD derives from the calibration regression model.

The existing literature on LIBS signal-enhancement methods reports LODs for Pb in soil of 0.132 to 40.6 mg/kg (reported in the Introduction, Table 2 reference range from cited comparator studies). The 26.142 mg/kg LOD obtained here falls within that range and is comparable to other published conductive-additive and confinement-enhancement methods.

CRM/recovery

The base matrix was CRM agricultural soil GBW070046. The paper does not report a separate certified reference validation (no analysis of the unmodified CRM at its certified Pb concentration, no recovery percentage, no comparison between LIBS-measured and ICP or AAS reference values). The CRM was used solely as a clean base soil matrix for spiking; it was not independently verified against its certified values.

Methods

The analytical method is LIBS with additive-based signal enhancement. The key steps are:

1. Soil spiking: Pb(NO3)2 dissolved in deionized water at target concentrations, mixed with CRM soil, dried at 60 degrees C for 8 hours, ground to uniform texture
2. Tablet preparation: 0.3 g soil-additive mixture pressed at 10 MPa for 30 seconds
3. Spectral acquisition: 532 nm Q-switched Nd:YAG laser at 110 mJ, 4 microsecond delay, 16 spots per tablet in a 4x4 grid, 5 accumulations per spot, 80 spectra averaged per tablet
4. Preprocessing: wavelet denoising (Daubechies 5, scale 3), area normalization, MAD outlier rejection
5. Modeling: univariate calibration curves on each Pb emission line; multivariate PLSR, LS-SVM, and ELM on full spectral range

LIBS provides total elemental Pb without speciation. The method does not distinguish Pb species. No wet digestion, acid extraction, or solvent preparation is required. Matrix-matched calibration is used (spiked soil rather than external standard solution).

Evidence fitness

Context only (EF-4). This paper is a methodological development study for environmental soil monitoring. It does not measure Pb in food ingredients, food products, or food-contact materials. The concentration range studied (276 to 2760 mg Pb/kg soil) is relevant to contaminated soil remediation assessment, not to dietary exposure assessment. The paper is useful as background for understanding rapid-analysis tools applicable to agricultural soil quality monitoring, which is a supply-chain upstream driver of crop Pb accumulation. It does not contribute direct occurrence data for any food matrix, and cannot populate or update contamination-profile estimates for any ingredient or product page.

Regulatory context

The paper does not analyze Pb against specific regulatory limits. It references the significance of Pb soil monitoring for food safety in the introduction, noting that “excessive Pb in soil can change its physicochemical properties, affect soil functions and the growth of animals and plants, and enter the human body through the food chain” (Introduction, p. 1). No comparison is made to Chinese, EU, or Codex maximum levels for Pb in soil or food. For food-related Pb regulatory context, see Lead and regulations/china-gb2762-food-contaminants.

Limitations

The paper acknowledges the following limitations and scope constraints:

• The calibration range (276 to 2760 mg Pb/kg) covers only highly contaminated soils. The lowest calibration point (276 mg/kg) is well above typical agricultural background and far above concentrations where food-chain Pb uptake risk would need to be assessed from soil data.
• The LOD of 26.142 mg/kg, while competitive for LIBS, is orders of magnitude above the sub-mg/kg Pb concentrations typically found in uncontaminated agricultural soils and in most food matrices.
• The soil tablets were laboratory-prepared from a single CRM base mixed with Pb(NO3)2. Real-world soil samples contain variable organic matter, moisture, particle size distribution, and co-contaminant mixtures that may affect LIBS signal behavior differently from the lab calibration matrix.
• No field validation was performed. All measurements were conducted in a controlled laboratory setting.
• The LS-SVM model achieved Rc = 1.000 (perfect calibration fit) with large prediction errors, a pattern indicative of overfitting. The authors note this result without further discussion.
• CRM recovery was not reported, so the absolute accuracy of the LIBS method relative to reference analytical methods (ICP-MS, AAS) is not established by this paper.

Implications

• Certification: Not applicable. This paper provides no occurrence data for any food ingredient or product. It does not inform any HMT&C limit or contamination-profile estimate.
• Courses: Demonstrates LIBS as a rapid, non-destructive alternative to conventional digestion-based methods (AAS, ICP-OES, ICP-MS) for Pb detection in soil. Useful for supply-chain context modules covering how agricultural soil Pb is monitored upstream of crop production. The additive enhancement approach (NaCl and graphite) illustrates a low-cost alternative to instrument modifications such as dual-pulse excitation or magnetic confinement.
• App: No change to any ingredient contamination_profile block. This paper provides no food-matrix Pb measurements.
• Microbiome: No relevance to metal-microbiome interactions.

Provenance notes

Open-access article, CC BY 4.0, published in Molecules (MDPI), 5 August 2024. PMCID PMC11314256; PMID 39125103. PDF SHA-256: 6fcf79ace14169d28715492b1699e360766017966e9c63b7b6b8d49a46b8c61d. Obtained from PMC OA S3 (pmc-oa-opendata.s3.amazonaws.com). Note that the first author listed on the paper is Shefeng Li (S.L.), not Sun; the cite-key sun2024-libs-pb-soil may reflect an earlier mis-attribution during page creation. The paper’s corresponding author is Xiaodan Liu (X.L., xiaodanliu@whpu.edu.cn). The cite-key is retained as-is to preserve cross-reference continuity.

Related evidence

• Lead

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