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BACKGROUND Keemun black tea (KBT) is one of the most popular tea beverages in China as a result of its unique flavor and potential health benefits. The geographical origin of KBT influences its quality and price. The present study aimed to apply a head‐space solid phase microextraction approach and gas chromatography–mass spectrometry combined with chemometric analysis to profile the volatile compounds of KBT collected from five production areas. RESULTS: Thirty‐one peaks were detected in 61 KBT samples. Hierarchical cluster analysis, principal component analysis (PCA), k‐nearest neighbor (k‐NN) and stepwise linear discriminant analysis (SLDA) were employed to visualize the volatile fractions. The results of unsupervised statistical tools were compared using a test for similarities and distinctions, which showed that different sources may be associated. A satisfying combination of average recognition (91.7%) and cross‐validation prediction abilities (84.6%) was obtained for the PCA–k‐NN. Among all of the statistical tools, SLDA provided promising results, with 100% recognition and 96.4% prediction ability. CONCLUSION: The results obtained in the present study indicate that the volatile compounds can be used as indicators to identify the geographical origin of KBT. © 2019 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

More accurate source analysis of potentially toxic elements (PTEs) in atmospheric fallout that endanger biodiversity and human health remains needed. This study determined the concentrations of seven PTEs, including Pb, Cd, As, Cu, Zn, Ni, and Cr, by inductively coupled plasma mass spectrometry (ICP-MS), and the sources of PTE pollution were quantified using multivariate statistical analysis, including principal component analysis (PCA), cluster analysis (CA), and Pearson correlation analysis, and Moran index was applied for mutual verification and supplementation. PCA and CA revealed that the same mixed sources of Pb, Cd, As, Cu, and Zn were found in the atmospheric dust fall in the study area, while Ni and Cr had the same source of pollution. Pearson correlation analysis provided that there were strong correlations between Pb–Cd, Pb-As, Pb-Cu, Cd-As, Cd-Cu, As-Cu, and Ni–Cr, indicating commonality between the two sources of heavy metal pollution. Additionally, the Moran index showed that strong spatial correlations were observed between Pb, Cd, As, Cu, and Zn, whose sources were mainly related to non-ferrous metal processing smelter smelting slag sites and an environmental company in the study area. However, no spatial correlation was found between Ni and Cr, which mainly originated from the local geological background. [ABSTRACT FROM AUTHOR]