Clam shell catalyst for continuous production of biodiesel

Continuous flow transesterification of waste frying oil (WFO) with methanol for the biodiesel production was tested in a laboratory scale jacketed reactive distillation (RD) unit packed with clam shell based CaO as solid catalyst. The physiochemical properties of the clam shell catalysts were characterized by X-ray Diffraction (XRD), Brunauer–Emmett–Teller (BET), Scanning Electron Microscopy (SEM), and Energy Dispersive Atomic X-ray Spectrometry (EDAX). The effects of the reactant flow rate, methanol-to-oil ratio, and catalyst bed height were studied to obtain the maximum methyl ester conversion. Reboiler temperature of 65°C was maintained throughout the process for product purification and the system reached the steady state at 7 hr. The experimental results revealed that the jacketed RD system packed with clam shell based CaO showed high catalytic activity for continuous production of biodiesel and a maximum methyl ester conversion of 94.41% was obtained at a reactant flow rate of 0.2 mL/min, methanol/oil ratio of 6:1, and catalyst bed height of 180 mm.     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

固体废物全过程管理中固体废物鉴别研究

对固体废物应进行全过程管理,固体废物鉴别是固体废物全过程管理的基础和关键,包括依据产生来源鉴别和过程鉴别两种方法,依据产生来源鉴别包括丧失原有利用价值的物质、在生产过程中产生的副产物、环境治理和污染控制过程中产生的物质、其他物质四类,在每一类中详细地列举了属于该产生来源的具体固体废物种类名称,便于理解和增强可操作性。过程鉴别包括在固体废物再生利用过程和处置过程中的固体废物鉴别两类,其中在再生利用过程的固体废物鉴别中明确指出了固体废物再生利用产物只有同时满足产品质量标准要求、国家污染控制标准要求以及有实际市场需求、固定用户等条件时,才不作为固体废物管理,在处置过程的固体废物鉴别中具体地列出了处置固体废物全过程中仍然作为固体废物管理的国际惯用处置方式。同时,给出了清晰的"原料—产品—固体废物—处置或产品"全过程中固体废物的产生节点和相应的固体废物类别图,为固体废物鉴别工作提供参考,使固体废物全过程管理有的放矢,有效防止固体废物对环境和人体健康造成的危害。     

Landfill site selection using spatial information technologies and AHP: A case study in Beijing,China

Site selection is an important and necessary issue for waste management in fast-growing regions. Because of the complexity of waste management systems, the selection of the appropriate solid waste landfill site requires consideration of multiple alternative solutions and evaluation criteria. Based on actual conditions of the study area, we considered economic factors, calculated criteria weights using the analytical hierarchy process (AHP), and built a hierarchy model for solving the solid waste landfill site-selection problem in Beijing, China. A geographic information system (GIS) was used to manipulate and present spatial data. All maps are graded from 1 (lowest suitability) to 5 (highest suitability) using spatial information technologies. The candidate sites were determined by aggregation based on the criteria weights. The candidate sites are divided by ‘best’, ‘good’ and ‘unsuitable’ landfill areas. Best landfill areas represent optimal sites; good landfill areas can be used as back-up candidate sites. Our work offers a siting methodology and provides essential support for decision-makers in the assessment of waste management problems in Beijing and other rapidly developing cities in developing countries.     

废弃印刷线路板碘化法浸金研究

针对碘化法从废弃印刷线路板中提取金的工艺设计,分别考察了碘的质量分数、n(I₂)/n(I^-)比值、固液比、双氧水的质量分数、pH值、浸出时间和浸出温度对金浸出率的影响。结合正交设计优化实验方法,提出了从废弃印刷线路板中碘化法浸取金的最佳工艺条件：碘的质量分数为1.1％,n(I₂)∶n(I^-)=1∶10,双氧水的质量分数为1.5％,浸出时间4 h,固液比为1∶10,浸出温度为常温（25℃）,溶液pH值为中性,此时金浸出率可达97.5％。     

基于生态安全的DAT-IAT城市污水处理工艺改进研究

通过正交试验,得到了DAT-IAT工艺和A/DAT-IAT工艺处理城市污水的常规指标去除和生态毒理指标削减的最优运行条件。结果表明,在正交试验的同一工艺中,COD去除最优运行条件的出水COD值优于生态毒性削减最优运行条件的出水COD值,但前者出水的生态毒性较大。由于厌氧池的水解酸化作用,A/DAT-IAT工艺对COD和生态毒性的处理效果均优于DAT-IAT工艺,并且回流总能耗低于DAT-IAT工艺,但是出水COD仍不达标。为了降低进入工艺的COD的总量,以絮凝沉淀做为预处理工艺,并采用Al残留量最小的絮凝剂投药量以降低出水中残留Al带来的生态风险。结果表明,在COD去除最优运行条件下,具有絮凝预处理的工艺对COD的去除效果优于没有絮凝预处理的工艺。絮凝-A/DAT-IAT工艺在COD去除最优运行条件下出水COD为104.46 mg/L,满足排放标准。在毒性削减最优运行条件下,具有絮凝预处理的工艺的出水生态毒性有所上升,但是污染物的总量得到了大幅削减。絮凝-A/DAT-IAT工艺与DAT-IAT工艺相比,在污染物去除效率得到大幅增加的同时,生态毒性得到有效控制,生态安全得到了有效的保障。     

微曝气Fenton氧化法处理模拟双酚A废水的效果及其生物验证

研究了微曝气Fenton氧化法关键工艺参数对模拟双酚A（BPA）废水处理效果的影响,并从活性污泥性质和污染物去除率两方面,采用膜生物反应器(membrane bioreactor, MBR)对微曝气Fenton氧化法的处理效果进行了实验验证,为实现BPA废水的生物处理奠定基础。结果表明,初始pH值、反应时间、H₂O₂/COD(质量浓度比)、H₂O₂/Fe²⁺ (摩尔浓度比)、反应温度及曝气量均对预处理效果有较大影响,在最佳条件下,COD去除率可达70%,BOD/COD值则由原废水的0.02提高到0.50以上。MBR处理上述出水的结果表明,经微曝气Fenton氧化处理BPA的废水,可较好地适应后续的生化处理。     

太阳光Fenton法处理垃圾渗滤液中有机污染物

研究利用太阳光Fenton法处理垃圾渗滤液。根据太阳光辐射强度随时间的变化规律,选择重庆7、8月份的晴天,在中午12：00到下午14：00时进行试验,研究太阳光辐射时间、pH值、Fenton试剂用量对垃圾渗滤液COD去除率的影响。研究结果表明：太阳光Fenton法对垃圾渗滤液的COD有较好的去除效果,COD去除率达86.2%。太阳光Fenton法处理垃圾渗滤液的优化条件是：日光辐射时间为120 min,pH值为2.5,Fe²⁺浓度为5 mmol/L,H₂O₂浓度为570 mmol/L。同时,论文还对太阳光Fenton法处理垃圾渗滤液的动力学进行分析。研究结果显示：太阳光Fenton法处理垃圾渗滤液,其表观动力学方程为-dC/dt=2.6×10^-8×P^1.92×F^1.79×E^1.67。     

基于超临界水氧化过程的能源环境系统设计

阐述了超临界水氧化过程的工艺路线,介绍了超临界水氧化过程的特点,提出了基于超临界水氧化过程的能源环境系统,设计了几种热量与能量回收系统程的耦合工艺,为提高超临界水氧化过程的经济性奠定了基础。     

阳离子染料废水治理技术

介绍了阳离子染料废水的特点,以及近年来阳离子染料废水的各种处理技术,并对阳离子染料废水处理技术的发展进行了展望,指出阳离子废水处理技术正朝着各种工艺优化组合的方向发展。