Volatile organic compound identification and characterization by PCA and mapping at a high-technology science park

Emission profiles, source identifications, and health risk of polycyclic aromatic hydrocarbons (PAHs) in a road tunnel located in Xi'an, China

Understanding the sources and characteristics of PM2.5-bound PAHs from traffic-related pollution can provide valuable data for mitigating air contamination from traffic in local urban regions. However, little information on PAHs is available regarding the typical arterial highway-Qinling Mountains No.1 tunnel in Xi'an. We estimated the profiles, sources, and emission factors of PM2.5-bound PAHs in this tunnel. The total PAH concentrations were 22.78 ng·m-3 and 52.80 ng·m-3 at the tunnel middle and exit, which were 1.09 and 3.84 times higher than that at the tunnel entrance. Pyr, Flt, Phe, Chr, BaP, and BbF were the dominant PAH species (representing approximately 78.01% of total PAHs). The four rings PAHs were dominant (58%) among the total PAH concentrations in PM2.5. The results demonstrated that diesel and gasoline vehicles exhaust emissions contributed 56.81% and 22.60% to the PAHs, respectively, while the corresponding value for together brakes, tyre wear, and road dust was 20.59%. The emission factors of total PAHs were 29.35 μg·veh-1·km-1, and emission factors of 4 rings PAHs were significantly higher than those of the other PAHs. The sum of ILCR was estimated to be 1.41×10-4, which accorded with acceptable level of cancer risk (10-6-10-4), PAHs should not ignored as they still affect the public health of inhabitants. This study shed light on PAH profiles and traffic-related sources in the tunnel, thereby facilitating the assessment of control measures targeting PAHs in local areas.

Occurrence and distribution of antimicrobial resistance genes in the soil of an industrial park in China: A metagenomics survey

As zoned areas of industries, industrial parks have great impacts on the environment. Several studies have demonstrated that chemical compounds and heavy metals released from industrial parks can contaminate soil, water, and air. However, as an emerging pollutant, antimicrobial resistance genes (ARGs) in industrial parks have not yet been investigated. Here, we collected soil samples from 35 sites in an industrial park in China and applied a metagenomics strategy to profile the ARGs and virulence factors (VFs). We further compared the relative abundance of ARGs between the sites (TZ_31-35) located in a beta-lactam antimicrobial-producing factory and other sites (TZ_1-30) in this industrial park. Metagenomic sequencing and assembly generated 14, 383, 065 contigs and 17, 631, 051 open reading frames (ORFs). Taxonomy annotation revealed Proteobacteria and Actinobacteria as the most abundant phylum and class, respectively. The 32 pathogenic bacterial genera listed in the virulence factor database (VFDB) were all identified from the soil metagenomes in this industrial park. In total, 685,354 ARGs (3.89% of the ORFs) and 272,694 virulence factors (VFs) (1.55% of the ORFs) were annotated. These ARGs exhibited resistance to several critically important antimicrobials, such as rifampins, fluroquinolones, and beta-lactams. In addition, no significant difference in the relative abundance of ARGs was observed between sites TZ_31-35 and TZ_1-30, indicating that ARGs have already disseminated widely in this industrial park. The present study gave us a better understanding of the whole picture of the resistome and virulome in the soil of the industrial park and suggested that we should treat the industrial park as a whole in the surveillance and maintenance of ARGs.

Pitavastatin slows tumor progression and alters urine-derived volatile organic compounds through the mevalonate pathway

Bone is a frequent site of metastasis from breast cancer, and a desirable drug could suppress tumor growth as well as metastasis-linked bone loss. Currently, no drug is able to cure breast cancer-associated bone metastasis. In this study, we focused on statins that are known to inhibit cholesterol production and act as antitumor agents. After an initial potency screening of 7 U.S. Food and Drug Administration-approved statins, we examined pitavastatin as a drug candidate for inhibiting tumor and tumor-induced bone loss. In vitro analysis revealed that pitavastatin acted as an inhibitor of tumor progression by altering stress to the endoplasmic reticulum, down-regulating peroxisome proliferator-activated receptor γ, and reducing Snail and matrix metalloproteinase 9. In bone homeostasis, it blocked osteoclast development by suppressing transcription factors c-Fos and JunB, but stimulated osteoblast mineralization by regulating bone morphogenetic protein 2 and p53. In a mouse model, pitavastatin presented a dual role in tumor inhibition in the mammary fat pad, as well as in bone protection in the osteolytic tibia. In mass spectrometry-based analysis, volatile organic compounds (VOCs) that were linked to lipid metabolism and cholesterol synthesis were elevated in mice from the tumor-grown placebo group. Notably, pitavastatin-treated mice reduced specific VOCs that are linked to lipid metabolites in the mevalonate pathway. Collectively, the results lay a foundation for further investigation of pitavastatin's therapeutic efficacy in tumor-induced bone loss, as well as VOC-based diagnosis of tumor progression and treatment efficacy.-Wang, L., Wang, Y., Chen, A., Teli, M., Kondo, R., Jalali, A., Fan, Y., Liu, S., Zhao, X., Siegel, A., Minami, K., Agarwal, M., Li, B.-Y., Yokota, H. Pitavastatin slows tumor progression and alters urine-derived volatile organic compounds through the mevalonate pathway.

Profile and source apportionment of volatile organic compounds from a complex industrial park

Industrial emissions, mainly from industrial parks, are important sources of ambient volatile organic compounds (VOCs). Identification of the major sources of VOCs from industrial parks has practical significance in emission reduction. In this study, the major species of VOCs from a residential area located downwind of a complex industrial park were sampled with Tenax absorption tubes and analyzed by thermal desorption coupled with gas chromatography/mass spectrometry (TD-GC/MS). Receptor models of factor analysis with nonnegative constraints (FA-NNC) and positive matrix factorization (PMF) were employed to recognize the potential emission sources, which suggested an association with the production processes in the nearby industrial park. In order to validate the sources, the profiles of VOC emissions of related workshops under actual manufacturing processes were acquired. It was found that xylenes & amines, phenols and esters were the major species of VOCs for the workshops of foundry, refractory materials and printing, respectively. Similarity analysis indicated that the detected profiles of VOC emissions from the dominant industrial types had good correlations with the identified factors from receptor models. Source contributions to VOCs in the receptor region exhibited that foundry production was the primary contributor (56-64%), followed by refractory material production (22-26%) and printing (14-18%). This study provides a strategy for source apportionment of VOCs from a local complex industrial park, which is helpful in the development of targeted control strategies.

Fluorescence and photophysical properties of xylene isomers in water: with experimental and theoretical approaches

A thorough analysis of the photophysical properties involved in electronic transitions in excitation-emission spectra of xylene isomers has been carried out using the time-dependent density functional theory (PBEPBE/6-31 + G(d,p)) method. For the first time a structural and spectroscopic investigation to distinguish isomers of xylene, a widespread priority pollutant, was conducted experimentally and theoretically. The fluorescence properties of xylene isomers (sole and mixture (binary and ternary)) in water were studied. The fluorescence peak intensities of xylenes were linearly correlated to concentration, in the order of p-xylene > o-xylene > m-xylene at an excitation/emission wavelength (ex/em) of 260 nm/285 nm for o-, m-xylene and ex/em 265 nm/290 nm for p-xylene at the same concentration. The theoretical excitation/emission wavelengths were at ex/em 247 nm/267 nm, 248 nm/269 nm and 251 nm/307 nm for o-, m- and p-xylene, respectively. The vertical excitation and emission state energies of p-xylene (ex/em 4.94 eV/4.03 eV) were lower and the internal conversion energy difference (0.90 eV) was higher than those of m-xylene (ex/em 5.00 eV/4.60 eV) (0.4 eV) and o-xylene (ex/em 5.02 eV/4.64 eV) (0.377 eV). The order of theoretical emission and oscillator strength (0.0187 > 0.0175 > 0.0339) for p-xylene > o-xylene > m-xylene was observed to be in agreement with the experimental fluorescence intensities. These findings provide a novel fast method to distinguish isomers based on their photophysical properties.

E-nose based rapid prediction of early mouldy grain using probabilistic neural networks

In this paper, early mouldy grain rapid prediction method using probabilistic neural network (PNN) and electronic nose (e-nose) was studied. E-nose responses to rice, red bean, and oat samples with different qualities were measured and recorded. E-nose data was analyzed using principal component analysis (PCA), back propagation (BP) network, and PNN, respectively. Results indicated that PCA and BP network could not clearly discriminate grain samples with different mouldy status and showed poor predicting accuracy. PNN showed satisfying discriminating abilities to grain samples with an accuracy of 93.75%. E-nose combined with PNN is effective for early mouldy grain prediction.