Characteristics, sources and potential ecological risk of atmospheric microplastics in Lhasa city.

Atmospheric microplastics are important contributors to environmental contamination in aquatic and terrestrial systems and pose potential ecological risks. However, studies on atmospheric microplastics are still limited in urban regions of the Tibetan Plateau, a sentinel region for climate and environmental change under a warming climate. In this study, the occurrence and potential ecological risk of atmospheric microplastics were investigated in samples of suspended atmospheric microplastics collected in Lhasa city during the Tibetan New Year in February 2023. The results show that the average abundance of atmospheric microplastics in Lhasa was 7.15 ± 2.46 MPs m-3. The sizes of the detected microplastics ranged from 20.34 to 297.18 µm, approximately 87% of which were smaller than 100 µm. Fragmented microplastics (95.76%) were the dominant shape, followed by fibres (3.75%) and pellets (0.49%). The primary polymer chemical components identified were polyamide (68.73%) and polystyrene (16.61%). The analysis of meteorological data and the backwards trajectory model indicated the air mass in Lhasa mainly controlled by westwards, and the atmospheric microplastics mainly originated from long-distance atmospheric transport. The potential ecological risk index assessment revealed that the atmospheric microplastic pollution in Lhasa was relatively low. This study provides valuable insights and a scientific foundation for future research on the prevention and control of atmospheric microplastic pollution in Lhasa and other ecologically sensitive cities.

Rapid quantitative analysis of adulterated rice with partial least squares regression using hyperspectral imaging system.

BACKGROUND: Rice adulteration in the food industry that infringes on the interests of consumers is considered very serious. To realize the rapid and precise quantitation of adulterated rice, a visible near infrared (VNIR) hyperspectral imaging system (380-1000 nm) was developed in the present study. A Savitsky-Golay first derivative (SG1) transform was utilized to eliminate the constant spectral baseline offset. Then, the adulterated levels of rice samples were quantified by partial least squares regression (PLSR). RESULTS: A SG1-PLSR model based on full-wavelength was attained with a coefficient of determination of prediction set (RP ) of 0.9909, root-mean-square error of prediction set (RMSEP ) of 0.0447 g kg-1 and residual predictive deviation (RPDP ) of 11.28. Furthermore, fifteen important wavelengths were selected based on the weighted regression coefficients (BW ) and a simplified model (PLSR-15) was established with RP of 0.9769, RMSEP of 0.0708 g kg-1 and RPDP of 3.49. Finally, two visualization maps produced by applying the optimal models (SG1-PLSR and PLSR-15) were used to visualize the adulterated levels of rice. CONCLUSION: These results demonstrate that VNIR hyperspectral imaging system is an effective tool for rapidly quantifying and visualizing the adulterated levels of rice. © 2019 Society of Chemical Industry.

Accuracy improvement of quantitative analysis for major elements in laser-induced breakdown spectroscopy using single-sample calibration.

Accurate determination of major elements using limited standard samples is always a big challenge in laser-induced breakdown spectroscopy (LIBS). Based on a simple calculation process, we propose a new one-point calibration method called single-sample calibration LIBS (SSC-LIBS) to build the calibration and improve the accuracy of determination of major elements. In this work, several major elements (Fe, Cu, Zn, Ni, Cr, Nb, and Mo) in three sets of matrix-matched certified samples were determined without sample preparation. The results showed that compared with multipoint calibration LIBS (MPC-LIBS), the R2, RMSECV, and ARE of Cu elements were improved from 0.40 to 0.97, 3.55 wt% to 0.76 wt%, and 5.19% to 1.05%, respectively, while the ARSD decreased from 16.22% to 1.15%. Furthermore, the AREs in the concentration ranges of 1-10, 10-20, 30-40, 50-60, 60-70, and 80-100 wt% were 5.16%, 2.55%, 1.75%, 1.69%, 1.05%, and 0.44%, respectively, with almost all less than 5%, as calculated by SSC-LIBS. These results demonstrated that SSC-LIBS can improve the accuracy and stability of detecting major elements using only one standard sample, which can greatly promote the application of LIBS.