微波强化CWPO工艺CuO_x-CeO_2/GAC催化剂的制备及其对二甲亚砜的降解

以颗粒活性炭(GAC)为载体、铜为活性组分、铈为助剂组分、草酸钠为沉淀剂,采用浸渍焙烧法制得CuO_x-CeO_2/GAC催化剂。以H_2O_2为氧化剂,微波强化催化湿式过氧化氢氧化(CWPO)处理二甲亚砜(DMSO)初始质量浓度为1 000 mg/L的废水,处理3 min后DMSO去除率达93.8%。催化剂第7次使用时DMSO去除率仍保持在75%以上。初始废水pH在3~9范围内,DMSO去除率均在85%以上。助剂Ce的加入提高了催化剂表面活性组分的分散性和稳定性,使催化剂的活性稳定性和使用寿命显著提高。     

Sb release characteristics of the solid waste produced in antimony mining smelting process

Sb release characteristics of blast furnace slag, mining waste rock and tailing sand were investigated in static immersion and dynamic leaching test. These three kinds of waste samples were collected from the antimony mine in Lengshuijiang, China, produced in mining smelting process. Effects of solid/liquid ratio, sample size and pH of leaching solution on Sb release characteristics were inspected based on the analysis of scanning electron microscope, pH and EC of leachate. The optimal parameters for Sb leaching of each sample were analyzed. For blast furnace slag and mining waste rock, Sb release contents increased along with the decline of solid/liquid ratio. The maximum accumulative release contents were 42.13, 34.26 mg/kg at the solid/liquid ratio of 1:20. While Sb release content for tailing sand decreased first and then increased with the reduction of solid/liquid ratio. When the solid/liquid ratio was 1:5, the accumulative Sb release content reached the most (24.30 mg/kg). Sb release content of mining waste rock increased with the drop of leaching solution pH, with the highest accumulative release content of 26.01 mg/kg at pH 2.0. Sb release contents of blast furnace slag and tailing sand showed positive correlation with the variation of leaching solution pH. The maximum accumulative release contents of these two samples were 215.91 and 147.83 mg/kg, respectively, when leaching solution pH was 7.0. In summary, Sb release capacity of the three samples in descending order was tailing sand, blast furnace slag and mining waste rock. pH and EC of the leachate in dynamic test varied independently with the initial pH of leaching solution while showing close relationship with mineral hydrolysis in the waste.     

Deep learning architecture for air quality predictions

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.     

Plasticity in metamorphic traits of <Emphasis Type="Italic">Rana kukunoris</Emphasis> tadpoles: The interactive effects of food level and rearing temperature

Larval amphibians are particularly likely to encounter variation in rearing temperature and resource availability due to variation in aquatic breeding habitats. In this study, plasticity in growth rates, larval mass, larval period, and size at metamorphosis were examined in Rana kukunoris Nikolskii, 1918 under different combinations of temperature and food level. Larval period and larval body mass was sensitive to food level, and varied with temperature. Tadpoles metamorphosed at an older age at low temperature than those reared at warm temperature. Food level was a significant affect on larval period at low temperature, but not at warm temperature. Mass was heavier for tadpoles reared at low temperatures than those reared at warm temperatures. The effect of food level depended on temperature, because larvae reared at low temperature that were offered a high food level achieved a larger size than larvae offered a low food level, but this did not occur at warm temperature. Therefore, we suggest that high food availability at low temperature prolonged developmental periods, thus larvae are larger as metamorphs than those reared at warm temperatures.     

电化学氧化法处理垃圾渗滤液纳滤浓缩液

实验利用电化学氧化法处理垃圾渗滤液纳滤浓缩液,以提高废水的可生化性。研究考察了水力停留时间、进水流量、循环流量、电流强度和原水氯离子浓度对有机物去除的影响。研究结果表明,电化学氧化法的最佳运行条件如下:水力停留时间为3 h,进水流量为1 m3/h,循环流量为15 m3/h,电流强度为420 A。在上述条件下,原水COD浓度从3 100mg/L降到1 311.3 mg/L,去除率达到57.7%,BOD/COD值由0.03提升至0.31。氯离子对电解有促进作用,但原水氯离子浓度超过5 000 mg/L,不需要外加工业盐。     

MnO_2/Al_2O_3吸附草甘膦及微波紫外耦合降解再生工艺

以掺混煅烧法制备Mn O2/Al2O3,并对草甘膦进行吸附,将吸附态草甘膦置于微波紫外耦合系统中进行降解和再生。研究并给出了Mn O2/Al2O3的最佳制备条件、最佳吸附条件和微波紫外耦合降解再生的最佳工艺参数。Mn O2/Al2O3最佳制备条件为Mn O2质量分数15%,煅烧温度500℃,煅烧时间2 h。在常温下,Mn O2/Al2O3对草甘膦的最大吸附量为75 mg/g。微波紫外耦合系统最佳工艺参数为功率500 W,时间25 min,空气量0.06 m3/h。在此操作条件下,Mn O2/Al2O3的再生率达到85%,并且可以多次再生利用,草甘膦最终降解产物为二氧化碳、氮氧化物、磷酸和水,矿化率为65%。     

助剂作用下超声浸取电解锰渣

用8-羟基喹啉、黄原酸钾、十六烷基三甲基溴化铵、磷酸三丁酯、柠檬酸5种物质作浸取助剂,考察了助剂作用下超声辅助浸取法从电解锰渣中提取锰的工艺条件。实验结果表明：用1%（质量分数）柠檬酸作浸取助剂,在固液比（g/mL）为1∶4、酸矿比（mL/g）为0.3∶1、浸取温度为70℃的条件下,超声浸取15min,锰浸出率平均可达57.28%,是加热酸浸法锰浸出率的2.72倍,是无助剂超声辅助浸取法锰浸出率的1.52倍。     

复合式静电除尘器脱除电厂排放PM2.5研究

控制燃煤电厂的小颗粒PM2.5排放是控制大气可吸人颗粒物污染的重要途径之一.传统静电除尘器对亚微米级颗粒脱除效率较低,为提高脱除效率,建立了一种脉冲预荷电直流收尘的复合式除尘系统,采用较低能耗的高压窄脉冲放电对颗粒物预荷电,大大提高了亚微米级颗粒的荷电量.结合传统的直流静电除尘器可以大幅提高对亚微米级颗粒的脱除效率,对小于1μm的颗粒脱除效率可以达到90%以上.并分析了脉冲荷电的电源形式和电压等因素对脱除效率的影响,为改造传统静电除尘器提供了理论支持.