Abstract: Fruit charcoal is a kind of common fuel, and the gases and aerosols produced in its combustion process can affect environmental air quality and harm human health. Therefore, it is of great significance to detect and identify the air composition during the combustion process of fruit charcoal. Laser-induced breakdown spectroscopy (LIBS) is used to detect the air and aerosol during the combustion of fruitcharcoal, and at the same time, fruit charcoal and its combustion ash are also detected as auxiliary analysis. The spectral lines of four samples are calibrated, and it is found that when the charcoal is burning, the carbon concentration in the air increases, and the generated aerosols contain Ca, Mg, K, Si and other elements. The elemental composition of fruit charcoal and ash is similar, both containing C, Fe, Mg, Ca, Sr, K, Na, Ba, and the intensity of C and H in fruit charcoal spectrum is higher than that in ash spectrum. Considering that the combustion of fruit charcoal produce more gas and less particulate matter, it is difficult to judge whether the fruit charcoal is burning or has burned in the room from the perspective of image recognition, so the air with and without combustion of fruit charcoal are further distinguished by principal component analysis (PCA) algorithm, and the bands where the characteristic spectral lines of C and CN are selected as the original features of cluster analysis. The results show that the two kinds of air with and without fruit charcoal combustion can be well distinguished, which proves that LIBS combined with PCA can effectively identify the combustion of fruit charcoal and can be used to detect the air pollution caused by the combustion of fruit charcoal. Furthermore, the composition of fruit charcoal and ash are also distinguished in the same way, and it is found that the distinction effect is good, which provides a reference for the recovery and utilization of fruit charcoal after combustion.

Key words: spectroscopy, laser-induced breakdown spectroscopy, fruit charcoal, air pollution, carbon emission, principal component analysis