Recycling sewage sludge into ceramic materials: A review

Environmental Chemistry Letters - Huge amounts of unwanted sewage sludge are generated in the process of wastewater treatment, calling for methods to recycle sewage sludges into value-added...     

垃圾场渗出污水厌氧处理的可行性研究

采用血清瓶静态试验法研究了垃圾渗出污水的厌氧处理的可行性。试验表明:垃圾渗出污水对厌氧发酵微生物无抑制作用,有良好的厌氧降解性,产气率为0.321/g·COD,污水中的大部份有机物都能被厌氧消化,COD_cr去除率为78.2%,发酵过程中还能获得能源——沼气。具有良好的应用前景。     

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.     

活性炭纤维吸附／热解吸／毛细管气相色谱法测定低浓度VOCs的方法

本文以活性炭纤维为吸附材料,建立了活性炭纤维吸附／二次热解吸 缩／毛细管气相色谱法测定空气中ＶＯＣＳ的方法,讨论了吸附剂的安全采样体积,湿度控制及分析方法的精密度,检出限和回收率。本法对苯,甲苯,四氯乙烯,对－二甲苯和苯乙类的最低可测浓度分别为０．１３,０．０２,０．１２,０．０５和０．０５μｇ．ｍ＾－３,适用于低浓度ＶＯＣＳ样品的测定。     

震后灾害链生机制及其对汶川地震城镇重建的影响

汶川8级大地震对地表产生强烈扰动,导致次生山地灾害极度发育,影响到震后灾害的活动特征及其相应的减灾对策。震后松散固体物质急剧增加、流域微地貌变化明显(沟道堵塞严重)、水文变化利于侵蚀和洪峰,使得灾害群发链生:崩塌、滑坡→泥石流→堰塞湖→溃决洪水(泥石流),8月中旬灾区各地因强降雨而大规模爆发泥石流堵塞河道,洪水冲毁掩埋重建城镇,给地震重灾区造成巨大损失。从以汶川县映秀镇为例,在阐述灾害链研究成果的基础上,分析震后灾害链的形成条件、成灾过程以及对城镇重建居民点的危害特点,进而提出灾害防治措施,为灾后城镇建设防灾减灾提供参考建议。     

铁催化聚丙烯腈脱氮的研究

应用热天平研究了载铁聚丙烯腈的脱氮碳化行为，负载铁对ＰＡＮ的稳定化和脱氮碳化均具有显著的催化作用，并在５８０－７６０℃范围内明显增加了Ｎ２形成速率。ＸＰＳ和ＸＲＤ对碳化过程中铁和氮化学形态变化的研究结果表明，铁催化反应机理可能是负载铁与吡啶氮作用形成中间体铁氮化物，后者进而分解释放出Ｎ２。     

Does green credit policy affect corporate debt financing? Evidence from China

Environmental Science and Pollution Research - Green finance is one of the most important ways to help companies achieve green transformation and development. We construct a quasi-natural...     

Arsenic sorption by red mud-modified biochar produced from rice straw

Red mud-modified biochar (RM-BC) has been produced to be utilized as a novel adsorbent to remove As because it can effectively combine the beneficial features of red mud (rich metal oxide composition and porous structure) and biochar (large surface area and porous structure properties). SEM-EDS and XRD analyses demonstrated that red mud had loaded successfully on the surface of biochar. With the increasing of pH in solution, arsenate (As(V)) adsorption on RM-BC decreased while arsenite (As(III)) increased. Arsenate adsorption kinetics process on RM-BC fitted the pseudo-second-order model, while that of As(III) favored the Elovich model. All sorption isotherms produced superior fits with the Langmuir model. RM-BC exhibited improved As removal capabilities, with a maximum adsorption capacity (Q_max) for As(V) of 5923 μg g^?1, approximately ten times greater than that of the untreated BC (552.0 μg g^?1). Furthermore, it has been indicated that the adsorption of As(V) on RM-BC may be strongly associated with iron oxides (hematite and magnetite) and aluminum oxides (gibbsite) by X-ray absorption near-edge spectroscopy (XANES), which was possibly because of surface complexation and electrostatic interactions. RM-BC may be used as a valuable adsorbent for removing As in the environment due to the waste materials being relatively abundant.     

类-Fenton体系对水中17β-雌二醇的光降解

以250W照明金属卤化物灯为光源研究了水中17β雌二醇(E2)在类Fenton体系中的光降解。结果表明,Fe(Ⅲ)/H2O2体系能有效地光降解E2。pH3～6范围内,E2光降解率及反应初始速率随酸度的增大而增大;H2O2初始浓度越大,E2降解率及反应初始速率越大;E2初始浓度越低,E2降解率越高,反应初始速率越低。     

高效生物处理技术在炼油厂碱渣废水处理中的应用

结合大港石化实际情况,在详细介绍柴油碱渣应用QBR高效生物处理技术取得成功的基础上,提出酸化回收粗酚或环烷酸并配套QBR、QBF等高效生物处理技术处理各种碱渣的新型工艺路线。经QBR处理后,出水COD去除率可达97%以上,石油类和挥发酚的去除率可达98%以上,硫化物去除率在99%以上。该技术的成功应用解决了困扰石化公司多年的碱渣废水处理的老大难问题,为炼厂碱渣废水乃至高浓度有机废水的处理开辟了一条新的途径。