Temporal and spatial distribution of novel brominated flame retardants in atmosphere of the Beijing-Tianjin-Hebei region, China.

The occurrence and spatio-temporal distribution of atmospheric novel brominated flame retardants (NBFRs) were studied across five sampling sites in the Beijing-Tianjin-Hebei (BTH) region over a whole year. By collecting samples (gas and particle) with a high-volume active air sampler (HV-AAS), nine NBFRs were analyzed and the sum concentrations ranged from 1.65 to 344 pg/m3, with the highest value found in the urban sampling site in Shijiazhuang City. Decabromodiphenylethane (DBDPE) was the predominant congener, which accounted for 60% of ∑9NBFRs on average, while it was 90% of ∑9NBFRs in the rural site and significantly higher than those observed in the urban sites (one-way ANOVA, p < 0.05). The levels of particle-bound NBFRs were significantly correlated with the variation of total suspended particulates (TSP) and temperature (p < 0.01), indicating their evident impact on the spatio-temporal distribution of NBFRs. Moreover, a significantly positive correlation was observed between the concentrations of 2-ethylhexyl-2,3,4,5-tetrabromobenzoate (EH-TBB) and bis (2-ethyl-1-hexyl) tetrabromophthalate (BEH-TEBP) (p < 0.01). Monocyclic brominated flame retardants (including PBBz, PBT, PBEB, HBB and TBP-DBPE) were correlated with each other (p < 0.01) in both gas and particle phase, suggesting their co-occurrence and the similar source in the environment. The gas-particle partitioning behavior was well predicted by the Li-Jia Empirical Model, and the results indicated that the target NBFRs did not reach the equilibrium state in air. This is one of very few studies revealed the spatio-temporal distribution of atmospheric NBFRs in the BTH region.

Nondestructive identification and classification of starch types based on multispectral techniques coupled with chemometrics.

Starch is the main source of energy and nutrition. Therefore, some merchants often illegally add cheaper starches to other types of starches or package cheaper starches as higher priced starches to raise the price. In this study, 159 samples of commercially available wheat starch, potato starch, corn starch and sweet potato starch were selected for the identification and classification based on multispectral techniques, including near-infrared (NIR), mid-infrared (MIR) and Raman spectroscopy combined with chemometrics, including pretreatment methods, characteristic wavelength selection methods and classification algorithms. The results indicate that all three spectral techniques can be used to discriminate starch types. The Raman spectroscopy demonstrated superior performance compared to that of NIR and MIR spectroscopy. The accuracy of the models after characteristic wavelength selection is generally superior to that of the full spectrum, and two-dimensional correlation spectroscopy (2D-COS) achieves better model performance than other wavelength selection methods. Among the four classification methods, convolutional neural network (CNN) exhibited the best prediction performance, achieving accuracies of 99.74 %, 97.57 % and 98.65 % in NIR, MIR and Raman spectra, respectively, without pretreatment or characteristic wavelength selection.

Perfluoroalkyl acids (PFAAs) in urban surface water of Shijiazhuang, China: Occurrence, distribution, sources and ecological risks.

It is extremely important to analyze the contaminative behaviors of Perfluoroalkyl acids (PFAAs) due to their serious threats to urban environments which are closely related to humans. Current study aimed to explore the distribution, source apportionment and ecological risk assessment of PFAAs in surface water from Shijiazhuang, China. The concentrations of ∑PFAAs ranged from 19.5 to 125.9 ng/L in the investigation area. Perfluorobutanesulfonic acid (PFBS) and perfluoropentanoic acid (PFPeA) were the predominant contaminants (mean value: 14.3 ng/L and 16.6 ng/L, respectively). The distribution of PFAAs according to geospatial analysis and hierarchical clustering analysis (HCA) showed that higher levels of ∑PFAAs were detected in the southern surface water of Shijiazhuang and there was a stepwise decrease from the wet season to the dry season. Furthermore, based on source apportionment, the dominant potential sources were found to be wastewater treatment plant (WWTP) effluents and industrial discharge. The risk quotients (RQs) revealed low ecological risks of all PFAAs for aquatic organisms in Shijiazhuang surface water. Collectively, this study provided basic data for regulatory strategies for controlling PFAA pollutions in urban surface water.

Lactic acid bacteria isolated from Kazakh traditional fermented milk products affect the fermentation characteristics and sensory qualities of yogurt.

Lactic acid bacteria (LAB) play a crucial role in the development of the taste, texture, and aroma of traditional fermented milk products. Five LABs from Kazakh traditionally prepared dairy products showed continuous subculture stability, as well as proper acidification and coagulation ability. They were identified as Pediococcus pentosaceus (1-5, 1-7), Enterococcus faecium (1-19), and Lactobacillus plantarum (1-12, 1-15). Their coagulation time and acidity values ranged from 5.97 to 12.78 h and 76.47 to 89.39°T. Yogurts prepared with L. plantarum were more condensed and textural integrity than those with P. pentosaceus and E. faecium. Determination of the volatile compound profiles suggested a higher diversity of volatile compounds than the control. The sensory evaluation presented positive overall sensory quality scores for the yogurts prepared with 1-12 and 1-15. The results provide additional information regarding the contributions of native LABs to the unique flavor and sensory qualities of traditionally prepared milk products. They may help to select starters or adjunct starters for developing distinctive, traditional nomadic fermented milk to satisfy consumer demand and increase market acceptability.