In this study, PM10 samples at four locations of Loudi, China were collected from January 2017 to March 2017 and December 2017 to February 2018 at first. Then, a new analytical strategy of second-order calibration based on the alternating trilinear decomposition (ATLD) coupled with gas chromatography-mass spectrometry (GC-MS) was firstly developed for quantitative analysis of seven polycyclic aromatic hydrocarbons (PAHs) in these samples. This strategy is more sensitive and efficient than traditional chromatography not only, but also it can resolve the problems of baseline drift and peaks overlapping in chromatographic analysis. Without the need for intricate pretreatment process and any derivation reactions, useful qualitative and quantitative information of seven PAHs was quickly extracted from the GC-MS-Sample data array by replacing chemical or physical separation with mathematical separation. In validation samples, the average recoveries of seven PAHs ranged from (96.7 ± 4.8) % to (107.9 ± 4.2) %, and the root-mean-square errors of prediction (RMSEPs) were within the range of 0.03–0.35 μg mL⁻¹. The highest concentrations of individual PAHs in these samples were for phenanthrene (1.34 μg mL⁻¹ in monitoring station), acenaphthylene (0.79 μg mL⁻¹ in municipal government) and chrysene (0.53 μg mL⁻¹ in monitoring station). Identified by component analysis, coal combustion and vehicle exhaust were the most possible sources of Loudi, China. These results demonstrated that the proposed method is characterised as a more precise, simple and promising analytical strategy to identify and quantify PAHs in actual aerosol.

Human activity today produces a large number of pollutants that end up in the environment, such as soil, water, and airborne particles. The first objective of this work is to introduce a new third-order multivariate calibration approach called self-weighted alternating quadrilinear decomposition (SWAQLD) for the analysis of organic pollutant of fluorene (FLU) in different water systems. One simulated and two real four-way data sets are used to study the potential of the proposed approach in comparison with two classical algorithms, namely alternating quadrilinear decomposition (AQLD) and parallel factor analysis (PARAFAC). The results of simulated data show that SWAQLD inherits the advantages of PARAFAC in terms of not only tolerance to experimental noise but also a fast convergence and a certain robustness to overestimation of the rank of the models from AQLD. The second objective of this work is to propose a new way of generating third-order data using excitation–emission matrix phosphorescence (EEMP) at room temperature for the study of the kinetic process of oxidation of FLU in complex chemical systems. The obtained rate constant and half-life of the FLU oxidation, on average, are 0.015 min⁻¹ and 45.5 min for free-interference water and 0.017 min⁻¹ and 40.0 min for wastewater, respectively. Research results show that SWAQLD coupled with EEMP allows the quantification and kinetic monitoring of FLU in analytical conditions of different complexities with excellent robustness to the choice of the number of model components.

Polycyclic aromatic hydrocarbons (PAHs) are a group of organic compounds that are both toxic and hazardous to human health and ecological systems. In recent work, a novel analytical strategy based on the chemometric-assisted HPLC-DAD method was proposed for the quantification and source apportionment of eight PAHs in PM10 samples. Compared to traditional chromatographic methods, this approach does not require the purification of complex PM10 samples. Instead, it utilizes a mathematical separation method to extract analytes’ profiles from overlapping chromatographic peaks, enabling precise quantification of PAHs in PM10. Firstly, 40 PM10 samples collected in Loudi city during two sampling periods were used for analysis. Subsequently, the second-order calibration method based on alternating trilinear decomposition (ATLD) was employed to handle the three-way HPLC-DAD data. Finally, the pollution sources of PAHs were analyzed by the feature component analysis method according to the obtained relative concentration matrix. For the validation model, the average recoveries of eight PAHs were between (88.8 ± 7.6)% and (105.6 ± 7.5)%, and the root-mean-square errors of prediction ranged from 0.03 μg mL⁻¹ to 0.47 μg mL⁻¹. The obtained limits of quantification for eight PAHs were in the range of 0.0050 μg mL⁻¹ to 0.079 μg mL⁻¹. For actual PM10 samples, results of the feature component analysis indicated that the main source of PAHs in PM10 may be traffic emissions and coal combustion. In summary, the proposed method provided a new and rapid analysis method for the accurate determination and source apportionment of PAHs in atmospheric aerosols.