Catalytic oxidation is widely used in pollution control technology to remove volatile organic compounds. In this study, Pd/ZSM-5 catalysts with different Pd contents and acidic sites were prepared via the impregnation method. All the catalysts were characterized by means of N2 adsorption- desorption, X-ray fluorescence (XRF), HE temperature programmed reduction (H2-TPR), and NH3 temperature programmed desorption (NH3-TPD). Their catalytic performance was investigated in the oxidation of butyl acetate experiments. The by-products of the reaction were collected in thermal desorption tubes and identified by gas chromatography/mass spectrometry. It was found that the increase of Pd content slightly changed the catalytic activity of butyl acetate oxidation according to the yield of CO2 achieved at 90%, but decreased the cracking by-products, whereas the enhancement of strong acidity over Pd-based catalysts enriched the by-product species. The butyl acetate oxidation process involves a series of reaction steps including protolysis, dehydrogenation, dehydration, cracking, and isomerization. Generally, butyl acetate was cracked to acetic acid and 2- methylpropene and the latter was an intermediate of the other by-products, and the oxidation routes of typical by-products were proposed. Trace amounts of 3-methylpentane, hexane, 2-methylpentane, pentane, and 2-methylbutane originated from iso4merization and protolysis reactions. 相似文献
Papillary thyroid cancer (PTC) has inflicted huge threats to the health of mankind. Metal pollution could be a potential risk factor of PTC occurrence, but existing relevant epidemiological researches are limited. The current case-control study was designed to evaluate the relationships between exposure to multiple metals and the risk of PTC. A total of 262 histologically confirmed PTC cases were recruited. Age- and gender-matched controls were enrolled at the same time. Urine samples were used as biomarkers to reflect the levels of environmental exposure to 13 metals. Conditional logistic regression models were adopted to assess the potential association. Single-metal and multi-metal models were separately conducted to evaluate the impacts of single and co-exposure to 13 metals. The increased concentration of urinary Cd, Cu, Fe, and Pb quartiles was found significant correlated with PTC risk. We also found the decreased trends of urinary Se, Zn, and Mn quartiles with the ORs for PTC. These dose-response associations between Pb and PTC were observed in the single-metal model and remained significant in the multi-metal model (OR25-50th=1.39, OR50-75th=3.32, OR>75th=7.62, p for trend <0.001). Our study suggested that PTC was positively associated with urinary levels of Cd, Cu, Fe, Pb, and inversely associated with Se, Zn, and Mn. Targeted public health policies should be made to improve the environment and the recognition of potential risk factors. These findings need additional studies to confirm in other population.
With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance. 相似文献
The aerobic riboflavin (Rf)-sensitized photodegradation of the endocrine disruptor 4,4'-isopropylidenebisphenol (bisphenol A, BPA), and of the related compounds 4,4'-isopropylidenebis(2,6-dibromophenol) and 4,4'-isopropylidenebis(2,6-dimethylphenol) has been studied in water and water-methanol mixtures through visible-light continuous photolysis, polarographic detection of oxygen uptake, stationary and time-resolved fluorescence spectroscopy, time-resolved near-IR phosphorescence detection and laser flash photolysis techniques. Bisphenols (BPs) quench excited singlet and triplet states of Rf, with rate constants close to the diffusion limit. BPs and dissolved molecular oxygen, employed in similar concentrations, competitively quench triplet excited Rf. As a consequence, superoxide radical anion and singlet molecular oxygen (O(2)((1)Delta(g))) are produced by electron- and energy-transfer processes, respectively, as demonstrated by auxiliary experiments employing selective quenchers of both oxidative species and the exclusive O(2)((1)Delta(g)) generator Rose Bengal. As a global result, the photodegradation of Rf is retarded, whereas BPs are degraded, mainly by an O(2)((1)Delta(g))-mediated mechanism, which constitutes a relatively efficient process in the case of BPA. Oxidation, dimerization and fragmentation products have been identified in the photooxidation of BPA. Results indicate that BPs in natural waters can undergo spontaneous photodegradation under environmental conditions in the presence of adequate photosensitizers. 相似文献