SiO2掺杂对Ru-TiO2催化剂的结构及其对丁二酸湿式氧化活性的影响

在TiO2粉末中掺杂SiO2,制备0—20%的SiO2TiO2载体.利用浸渍法在载体上负载Ru,制备Ru/SiO2TiO2催化剂.结果表明,催化剂的晶相以锐钛矿为主,晶粒尺寸为30—50nm.掺杂的SiO2主要为无定型,以5—15nm分散于催化剂中,比表面积随SiO2掺杂量的增加显著增大,但对TiO2的晶体结构无明显影响,也未形成Si—O—Ti键.Ru因粒径细化及含量过低未产生衍射峰.在300ml间歇式反应釜中,反应温度210—270℃,初始氧分压085MPa条件下,对丁二酸(74g·l-1,COD=7000mg·l-1)的催化湿式氧化结果表明,SiO2掺杂量对COD的去除率有显著影响,掺杂10%SiO2的催化剂对COD的去除率最高.在连续十次运行中,COD的去除率保持在85%左右,活性未见降低.     

TiO2/H2O2/UV和TiO2/O3/UV降解对氯苯甲酸和喹啉的试验研究

主要叙述TiO2/H2O2/UV和TiO2/O3/UV体系降解对氯苯甲酸（4-CBA）和喹啉的试验研究.研究表明,（1）在TiO2/H2O2/UV体系里目标物降解速度先随过氧化氢投加量的增加而提高,但超过一定浓度之后便开始下降;（2）在TiO2/O3/UV体系中,目标降解物的反应速度都非常快,且臭氧浓度高的时候降解速度更快;（3）二氧化钛催化剂在TiO2/O3/UV体系中作为积极因素有助于提高反应速率,而在TiO2/H2O2/UV体系是消极因素,会降低反应速率.     

有机物好氧生物降解性的综合测试评价方法

综合考虑有机物好氧生物降解过程中的耗氧量,最终产物量和微生物活性３个影响生物降解性的因素,以ＢＯＤ５／ＣＯＤ作为耗氧指标,以ＣＯ２作为降解产物量指标,以ＡＴＰ作为微生物活性指标,根据这３个指标提出模糊聚类综合 加权综合评估２种综合评价有机物生物降解性的方法,综合评价了２２种有机化合物和有机废水的生物降解性,并比较了这２种综合评价方法的优劣,同时也提出了采用这２种综合评价方法所需进行了具体步骤。     

从长江洪水看土壤环境保护的重要性

从１９９８ 年长江流域发生的特大洪水说起,分析从汉代到清末２０００ 年间及近４０ 年来长江流域水旱灾害的变化趋势,认为造成长江洪水灾害的原因主要是气候异常,但也与生态环境遭到破坏有关,其中土壤侵蚀、水土流失是最重要的因素。探讨了防治长江水患的对策;基于对土壤的吸水和贮水功能主要靠地被层和土壤有机质层,而水土流失是从植被破坏、地被层消失开始的,以及对古今治水、治土正反两个方面的认识,提出了治水的同时应治土的观点及５ 条有效的途径。     

Effects of climate and land-cover change on the conservation status of gibbons

Species shift their distribution in response to climate and land-cover change, which may result in a spatial mismatch between currently protected areas (PAs) and priority conservation areas (PCAs). We examined the effects of climate and land-cover change on potential range of gibbons and sought to identify PCAs that would conserve them effectively. We collected global gibbon occurrence points and modeled (ecological niche model) their current and potential 2050s ranges under climate-change and different land-cover-change scenarios. We examined change in range and PA coverage between the current and future ranges of each gibbon species. We applied spatial conservation prioritization to identify the top 30% PCAs for each species. We then determined how much of the PCAs are conserved in each country within the global range of gibbons. On average, 31% (SD 22) of each species’ current range was covered in PAs. PA coverage of the current range of 9 species was <30%. Nine species lost on average 46% (SD 29) of their potential range due to climate change. Under climate-change with an optimistic land-cover-change scenario (B1), 12 species lost 39% (SD 28) of their range. In a pessimistic land-cover-change scenario (A2), 15 species lost 36% (SD 28) of their range. Five species lost significantly more range under the A2 scenario than the B1 scenario (p = 0.01, SD 0.01), suggesting that gibbons will benefit from effective management of land cover. PA coverage of future range was <30% for 11 species. On average, 32% (SD 25) of PCAs were covered by PAs. Indonesia contained more species and PCAs and thus has the greatest responsibility for gibbon conservation. Indonesia, India, and Myanmar need to expand their PAs to fulfill their responsibility to gibbon conservation. Our results provide a baseline for global gibbon conservation, particularly for countries lacking gibbon research capacity.     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

Discovery of emerging organic pollutants in the atmosphere through an omics approach

● We review the framework of discovering emerging pollutants through an omics approach. ● High-resolution MS can digitalize atmospheric samples to full-component data. ● Chemical features and databases can help to translate untargeted data to compounds. ● Biological effect-directed untargeted analyses consider both existence and toxicity. Ambient air pollution, containing numerous known and hitherto unknown compounds, is a major risk factor for public health. The discovery of harmful components is the prerequisite for pollution control; however, this raises a great challenge on recognizing previously unknown species. Here we systematically review the analytical techniques on air pollution in the framework of an omics approach, with a brief introduction on sample preparation and analysis, and in more detail, compounds prioritization and identification. Through high-resolution mass spectrometry (HRMS, typically coupled with chromatography), the complicated environmental matrix can be digitalized into “full-component” data. A key step to discover emerging compounds is the prioritization of compounds from massive data. Chemical fingerprints, suspect lists and biological effects are the most vital untargeted strategies for comprehensively screening critical and hazardous substances. Afterward, compressed data of compounds can be identified at various confidence levels according to exact mass and the derived molecular formula, MS libraries, and authentic standards. Such an omics approach on full-component data provides a paradigm for discovering emerging air pollutants; nonetheless, new technological advancements of instruments and databases are warranted for further tracking the environmental behaviors, hence to evaluate the health risk of key pollutants.     

Biological removal of air loaded with a hydrogen sulfide and ammonia mixture

The nuisance impact of air pollutant emissions from wastewater pumping stations is a major issue of concern to China. Hydrogen sulfide and ammonia are commonly the primary odor and are important targets for removal. An alternative control technology, biofiltration, was studied. The aim of this study is to investigate the potential of unit systems packed with compost in terms of ammonia and hydrogen sulfide emissions treatment, and to establish optimal operating conditions for a full-scale conceptual design. The laboratory scale biofilter packed with compost was continuously supplied with hydrogen sulfide and ammonia gas mixtures. A volumetric load of less than 150 gH2S/(m^3.d) and 230 gNH3/(m^3.d) was applied for about fifteen weeks. Hydrogen sulfide and ammonia elimination occurred in the biofilter simultaneously. The removal efficiency, removal capacity and removal kinetics in the biofilter were studied. The hydrogen sulfide removal efficiency reached was very high above 99%, and ammonia removal efficiency was about 80%. Hydrogen sulfide was oxidized into sulphate. The ammonia oxidation products were nitrite and nitrate. Ammonia in the biofilter was mainly removed by adsorption onto the carrier material and by absorption into the water fraction of the carrier material. High percentages of hydrogen sulfide or ammonia were oxidized in the first section of the column. Through kinetics analysis, the presence of ammonia did not hinder the hydrogen sulfide removal. According to the relationship between pressure drop and gas velocity for the biofilter and Reynolds number, non-Darcy flow can be assumed to represent the flow in the medium.     

Influence of osmotic distillation on membrane absorption for the treatment of high strength ammonia wastewater

Osmotic distillation (OD) was found to be a coupled process in membrane absorption (MA) for the treatment of high strength ammonia wastewater. As a result, ammonia could not be concentrated in absorption solution(AS) as expected. The inhibition of the coupled OD in MA process was investigated as well as various factors affecting the inhibition. The results indicated that the coupled OD can be effectively inhibited by heating concentrated solution and cooling dilute solution. It was also found that experimental minimum inhibition temperature difference(MITD) between concentrated and dilute solutions was different when using polyvinylidene fluoride(PVDF) and polypropylene(PP) membranes respectively, which could be ascribed to material properties, such as OD and membrane distillation (MD) coefficients of the membranes. Experimental MITDs were found to be higher than theoretical MITDs which were calculated using a simplified method.