Recent advances in catalytic decomposition of ozone

Ozone (O₃), as a harmful air pollutant, has been of wide concern. Safe, efficient, and economical O₃ removal methods urgently need to be developed. Catalytic decomposition is the most promising method for O₃ removal, especially at room temperature or even subzero temperatures. Great efforts have been made to develop high-efficiency catalysts for O₃ decomposition that can operate at low temperatures, high space velocity and high humidity. First, this review describes the general reaction mechanism of O₃ decomposition on noble metal and transition metal oxide catalysts. Then, progress on the O₃ decomposition performance of various catalysts in the past 30 years is summarized in detail. The main focus is the O₃ decomposition performance of manganese oxides, which are divided into supported manganese oxides and non-supported manganese oxides. Methods to improve the activity, stability, and humidity resistance of manganese oxide catalysts for O₃ decomposition are also summarized. The deactivation mechanisms of manganese oxides under dry and humid conditions are discussed. The O₃ decomposition performance of monolithic catalysts is also summarized from the perspective of industrial applications. Finally, the future development directions and prospects of O₃ catalytic decomposition technology are put forward.     

Pollution prevention at ports: clearing the air

Seaports are major hubs of economic activity and of environmental pollution in coastal urban areas. Due to increasing global trade, transport of goods through ports has been steadily increasing and will likely continue to increase in the future. Evaluating air pollution impacts of ports requires consideration of numerous sources, including marine vessels, trucks, locomotives, and off-road equipment used for moving cargo. The air quality impacts of ports are significant, with particularly large emissions of diesel exhaust, particulate matter, and nitrogen oxides. The health effects of these air pollutants to residents of local communities include asthma, other respiratory diseases, cardiovascular disease, lung cancer, and premature mortality. In children, there are links with asthma, bronchitis, missed school days, and emergency room visits. The significance of these environmental health impacts requires aggressive efforts to mitigate the problem. Approaches to mitigation encompass a range of possibilities from currently available, low-cost approaches, to more significant investments for cleaner air. Examples of the former include restrictions on truck idling and the use of low-sulfur diesel fuel; the latter includes shore-side power for docked ships, and alternative fuels. A precautionary approach to port-related air pollution would encourage local production of goods in order to reduce marine traffic, greener design for new terminals, and state-of-the art approaches to emissions-control that have been successfully demonstrated at ports throughout the world.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

重庆近11年大气混合层厚度研究

根据新闻颁国家标准ＧＢ／Ｔ１３２０１－９１的规定，计算了重庆地区近１１年大气混合厚度，分析结果表明，重庆地区大气混合层厚度有明显日变化和季节变化，大气稳定度是混合层厚度的主要决定因子。     

采用钙钛矿型催化剂(La0.8K0.2Cu0.05Mn0.95O3)同时催化去除NOx和碳烟的研究

将钙钛矿型催化剂与碳烟均匀混合后置于固定床连续流动反应体系中,利用程序升温反应技术,在模拟柴油机尾气的情况下对同时催化去除氮氧化物(NOx)和碳烟的反应进行了实验研究.通过改变含Cu原料的用量,得到不同Cu取代量的催化剂La0.8K0.2CuxMn1-xO3,性能评价结果表明,La0.8K0.2Cu0.05Mn0.95O3催化剂的综合性能较好,碳烟的起燃温度及NO向N2的最大转化率分别为280℃和58.0%.采用该催化剂,进一步考察了进气中NO浓度、O2浓度、进气总流量及催化剂与碳烟的接触状况对反应的影响.研究结果表明,进气中NO浓度、O2浓度、气体总流量和催化剂与碳烟之间的接触状况对NO的去除率的影响比较明显,而对碳烟起燃温度的影响较小.O2浓度从5%变为7.5%时,碳烟的起燃温度及最大NO转化率分别从280℃和53.8%变为270℃和96.7%.碳烟与催化剂松散接触时,碳烟的起燃温度及最大NO转化率分别为290℃和48.4%,紧密接触时分别为275℃和70.4%.而进气中NO浓度、气体总流量的变化对碳烟的燃烧基本上没有影响,虽然NO的转化率有明显变化,但生成的N2总量基本不变.     

兼性生化处理生活污水最佳工况研究

在常温条件下进行兼性生化处理生活污水试验,研究COD去除率与HRT、MLSS、进水有机物浓度和混合液水温的关系。在试验中最佳的水平搭配为MLSS=5500mg/L,进水有机物浓度=180mg/L,HRT=8h和混合液水温=20℃,与回归分析所得出MLSS=5881mg/L,进水有机物浓度=192.7mg/L,HRT=8.9063h和混合液水温=21.3790℃的最佳工艺条件相吻合。最后通过等高线分析得出常温下生活污水兼性生化的适宜范围。     

Synergistic effect of F and triggered oxygen vacancies over F-TiO2 on enhancing NO ozonation

Oxidation-absorption technology is a key step for NO_x removal from low-temperature gas. Under the condition of low O₃ concentration (O₃/NO molar ratio = 0.6), F-TiO₂ (F-TiO₂), which is cheap and environmentally friendly, has been prepared as ozonation catalysts for NO oxidation. Catalytic activity tests performed at 120°C showed that the NO oxidation efficiency of F-TiO₂ samples was higher than that of TiO₂ (about 43.7%), and the NO oxidation efficiency of F-TiO₂-0.15 was the highest, which was 65.3%. Combined with physicochemical characteristics of catalysts and the analysis of active species, it was found that there was a synergistic effect between F sites and oxygen vacancies on F-TiO₂, which could accelerate the transformation of monomolecular O₃ into multi-molecule singlet oxygen (¹O₂), thus promoting the selective oxidation of NO to NO₂. The oxidation reaction of NO on F-TiO₂-0.15 follows the Eley-Rideal mechanism, that is, gaseous NO reacts with adsorbed O₃ and finally form NO₂.     

复合氧化物汽车尾气净化催化剂抗SO2中毒机理研究

复合氧化物催化剂(ASC)具有较高的活性和良好的抗SO_2中毒性能.用IR、XPS、TPD等技术研究了该催化剂抗SO_2中毒机理,结果表明,与易失活催化剂相比,ASC经500h反应(反应气含SO_2约20ppm),其活性组分价态无显著变化,仅表面发生SO_2的化学吸附,经与约500ppm的SO_2作用20h后,发现仅有少量SO_4~(2-)形成.这是由于在ASC催化剂中添加了特殊助剂,而使催化剂活性组分得到保护的缘故.     

宿迁3次突发性空气重污染过程对比分析

利用空气质量资料、常规观测资料、NCEP1.0°×1.0°再分析资料，应用数理统计、天气学等方法对宿迁市3次突发性重污染天气进行对比分析.结果表明：①宿迁"突发"空气重污染时，AQI级别由前一日的一、二级至第2日转为五级以上，AQI值迅速上升.②3次空气重污染过程天气背景相似，高层为宽广平直的偏西气流，地面受高压控制，中低层风向和温度平流突然转变，且都有深厚的逆温层结；持续变化较小的气压梯度、较低风速、温度日较差及相对湿度的增大（150328过程（即2015年3月28日—4月1日污染过程）除外）为颗粒物浓度迅速增长提供了条件.③大气稳定度级别迅速变高和混合层高度迅速降低并维持，对污染物快速聚集有显著影响.④物理量诊断表明，污染发生前期上空为弱上升运动，随后迅速转为下沉运动，或气流下沉运动区域迅速扩大、升高，是空气质量迅速转差的重要动力因素.⑤内蒙古地区的沙尘远距离输送形成的污染，是造成150328过程与另外两次过程明显不同的主要原因.     

氢氧化钠吸收—盐酸萘乙二胺分光光度法测定污染源废气中的氮氧化物

对非稳态工艺废气中氮氧化物的监测 ,目前的监测方法无法获得准确满意的结果 .氢氧化钠吸收—盐酸萘乙二胺分光光度法监测 ,可以延长采样时间 ,扩大测定范围 ,消除了推荐、试行方法中的有关缺陷