Thirty-three bituminous coal samples were utilized to test the application of laser-induced breakdown spectroscopy technique for coal elemental concentration measurement in the air. The heterogeneity of the samples and the pyrolysis or combustion of coal during the laser–sample interaction processes were analyzed to be the main reason for large fluctuation of detected spectra and low calibration quality. Compared with the generally applied normalization with the whole spectral area, normalization with segmental spectral area was found to largely improve the measurement precision and accuracy. The concentrations of major element C in coal were determined by a novel partial least squares (PLS) model based on dominant factor. Dominant C concentration information was taken from the carbon characteristic line intensity since it contains the most-related information, even if not accurately. This dominant factor model was further improved by inducting non-linear relation by partially modeling the inter-element interference effect. The residuals were further corrected by PLS with the full spectrum information. With the physical-principle-based dominant factor to calculate the main quantitative information and to partially explicitly include the non-linear relation, the proposed PLS model avoids the overuse of unrelated noise to some extent and becomes more robust over a wider C concentration range. Results show that RMSEP in the proposed PLS model decreased to 4.47% from 5.52% for the conventional PLS with full spectrum input, while R2 remained as high as 0.999, and RMSEC&P was reduced from 3.60% to 2.92%, showing the overall improvement of the proposed PLS model.

Using standard brass alloy samples, an approach to reduce the laser-induced breakdown spectroscopy measurement uncertainty was tested and proved. Two important parameters for plasma characterization, the plasma temperature and the electron density, were applied to minimize the signal uncertainties due to uncontrollable experimental parameter variations. Results show that for the pulse-to-pulse analysis, the signal fluctuations can be significantly reduced by utilizing the plasma characteristic information. The major source for the single pulse fluctuations is the redistribution of the characteristic line at different temperatures according to the Boltzmann distribution under LTE. The change of the degree of ionization also contributes to the signal fluctuations. For the multi-pulse analysis, due to the nonlinear relationship between the plasma temperature and the line intensity, it is not applicable to utilize the Boltzmann distribution to reduce the influences of the plasma properties. However, normalization with the combination of the whole spectrum area and the ratio between the ion and atom number density of the same element can further increase the measurement accuracy.