通过监测西安可口可乐饮料有限公司污水处理站的上流式厌氧污泥床(UASB)反应器,探讨饮料废水厌氧处理过程中COD去除率、沼气组分、氢分压、出水挥发性脂肪酸、产甲烷活性以及污泥形态。结果表明,UASB反应器对饮料废水中的COD去除率达到84.55%,产生的沼气中甲烷组分含量高达74.5%。反应器内的氢分压仅2.5 Pa,为水解发酵和产氢产乙酸过程创造了良好的条件。UASB反应器中污泥具有较高的产甲烷活性,以乙酸、丙酸和丁酸为基质时,最大比产甲烷活性分别为407.14、331.74和241.27 m L CH4/(g VSS·d)。UASB反应器中的污泥形态主要为絮状,甲烷菌中的优势菌为甲烷丝菌,同时存在少量甲烷杆菌。针对该厂UASB反应器中污泥的现状,提出了影响颗粒化的因素和控制措施,为后期的运行和管理提供了参考依据。 相似文献
The Ti-modified sepiolite (Ti-Sep)-supported Mn-Cu mixed oxide (yMn5Cu/Ti-Sep) catalysts were synthesized using the co-precipitation method. The materials were characterized by the X-ray diffraction scanning electron microscope, N2 adsorption-desorption, H2-TPR, O2-TPD, and XPS techniques, and their catalytic activities for CO oxidation were evaluated. It was found that the catalytic activities of yMn5Cu/Ti-Sep were higher than those of 5Cu/Ti-Sep and 30Mn/Ti-Sep, and the Mn/Cu molar ratio had a distinct influence on catalytic activity of the sample. Among the yMn5Cu/Ti- Sep samples, the 30Mn5Cu/Ti-Sep catalyst showed the best activity (which also outperformed the 30Mn5Cu/Sep catalyst), giving the highest reaction rate of 0.875 × 10–3 mmol·g–1·s–1 and the lowest T50% and T100% of 56°C and 86°C, respectively. Moreover, the 30Mn5Cu/Ti-Sep possessed the best low-temperature reducibility, the lowest O2 desorption temperature, and the highest surface Mn3+/Mn4+ atomic ratio. It is concluded that factors, such as the strong interaction between the copper or manganese oxides and the Ti-Sep support, good low-temperature reducibility, and good mobility of chemisorbed oxygen species, were responsible for the excellent catalytic activity of 30Mn5Cu/Ti-Sep.
Effects of physical/environmental factors on fine particle (PM2.5) exposure, outdoor-to-indoor transport and air exchange rate (AER) were examined. The fraction of ambient PM2.5 found indoors (FINF) and the fraction to which people are exposed (α) modify personal exposure to ambient PM2.5. Because FINF, α, and AER are infrequently measured, some have used air conditioning (AC) as a modifier of ambient PM2.5 exposure. We found no single variable that was a good predictor of AER. About 50% and 40% of the variation in FINF and α, respectively, was explained by AER and other activity variables. AER alone explained 36% and 24% of the variations in FINF and α, respectively. Each other predictor, including Central AC Operation, accounted for less than 4% of the variation. This highlights the importance of AER measurements to predict FINF and α. Evidence presented suggests that outdoor temperature and home ventilation features affect particle losses as well as AER, and the effects differ.Total personal exposures to PM2.5 mass/species were reconstructed using personal activity and microenvironmental methods, and compared to direct personal measurement. Outdoor concentration was the dominant predictor of (partial R2 = 30–70%) and the largest contributor to (20–90%) indoor and personal exposures for PM2.5 mass and most species. Several activities had a dramatic impact on personal PM2.5 mass/species exposures for the few study participants exposed to or engaged in them, including smoking and woodworking. Incorporating personal activities (in addition to outdoor PM2.5) improved the predictive power of the personal activity model for PM2.5 mass/species; more detailed information about personal activities and indoor sources is needed for further improvement (especially for Ca, K, OC). Adequate accounting for particle penetration and persistence indoors and for exposure to non-ambient sources could potentially increase the power of epidemiological analyses linking health effects to particulate exposures. 相似文献