危化品海水快速分离工艺探究

目前国内外均无成熟的危化品海水分离装置,急需探索出可以有效进行危化品海水原位快速分离的工艺,解决海上危化品泄漏后危化品污染海水原位分离困难的问题,提高海上应急水平。用二甲苯作为海上运输常见危化品的代表,选择几种典型的污染物水分离工艺(重力分离、膜分离、吸附分离),分别在海水条件下进行了效果测试,并对3种工艺进行了串联组合和效果验证。结果表明:重力分离能够在10 min内将二甲苯海水高比例混合物快速分离,并将二甲苯质量浓度降至160～200 mg/L;膜分离能够耐冲击地完成对大质量浓度(如20 000 mg/L)二甲苯海水混合物的分离,将二甲苯质量浓度降至60 mg/L左右,但处理后的污染海水再过膜没有进一步的分离效果;吸附分离根据前期的柱试验结果选择了吸附容量较大且适宜填罐的活性炭种类IPG1240;重力分离-膜分离-吸附分离的组合能够实现危化品与海水的快速分离。     

混凝-Fenton工艺处理垃圾渗滤液膜滤浓缩液的中试研究

采用混凝-Fenton组合工艺对漳州九龙岭垃圾填埋场的渗滤液经NF+RO处理后膜滤浓缩液进行中试试验,探讨了PAC、PAM、FeSO4·7H2 O和H2 O2的投加量对处理效果的影响及反应机理,并设计各工艺单元参数.结果表明:混凝工艺药剂最佳投加量为PAC 2000 mg/L、PAM 9 mg/L;Fenton工艺的氧化剂最佳投加量为FeSO4·7H2 O 1.6 g/L、H2 O28 mL/L.膜滤浓缩液经处理后,出水COD约300 mg/L,色度约30,平均去除率分别达76.8%和95.4%,处理费35.52元/t,试验结果为同类膜滤浓缩液提供了经济可行的处理方法和工艺设计依据.     

膜参数对膜吸收法天然气脱硫传质性能的影响研究

以N-甲基二乙醇胺(MDEA)溶液为吸收液,采用膜吸收法进行了模拟天然气脱硫试验,考察了不同膜参数对MDEA溶液脱硫过程中传质性能的影响。结果表明:在较为理想的稳态膜吸收过程中,多孔膜孔径大小、膜厚度以及膜孔形态等因素对稳态膜吸收过程中的传质效果影响不大;在其他条件不变的情况下,多孔膜的传质性能随着孔隙率的增大而提高;同时传质效果还受到膜润湿现象的影响。这说明在较为理想的稳态膜吸收过程中孔隙率是对传质效果产生影响的主要因素,为膜吸收过程传质的影响因素探究及多孔膜选择提供了依据。     

两种粉尘收集系统在环境治理中的应用和对比

针对粉尘治理工程设计中经常混淆的设计理念,介绍了两种粉尘收集系统在环境治理中的各自应用特点,通过对两个工程实例的系统分析和经验总结,得出以下结论:脉冲袋式除尘系统和真空负压吸尘系统是两种不同的粉尘收集系统,脉冲袋式除尘系统是以控制粉尘逸散为原则,在尘源点密闭的基础上形成一定的负压,须合理确定系统的设计风量和吸尘罩的设置;真空负压吸尘系统则是以尽可能多收集粉尘减少人工清扫强度为原则,须优化设计吸尘管网,保证最远处吸尘点能有效吸力。     

水体中硼的去除方法研究进展

硼是人体与动、植物必需的一种微量元素。然而,当水中硼浓度超过最大允许值,将对人体和部分动、植物产生严重的负面影响。硼独特的物化性质导致常规水处理方法对硼的去除效果较差。论述了各种水处理除硼方法,包括化学沉淀、吸附、离子交换、液液萃取、纳滤、反渗透、正渗透、膜蒸馏、组合工艺和其他方法;分析了各种除硼方法的分离过程、影响因素和优缺点等;展望了水处理除硼方法发展趋势,认为开发出能在中性p H条件下快速高效除硼的膜,以及具有高硼吸附量、易再生和回收硼的特效硼吸附剂是除硼水处理技术的发展方向。     

强化除磷曝气生物滤池反冲洗优化及其污泥特性

为探讨BAF(曝气生物滤池)最佳反冲洗强度及其选择依据,以某处理石化二级出水的强化除磷BAF为研究对象,采取不同的反冲洗强度进行气-水联合反冲洗,探讨反冲洗过程中出水污泥量峰值出现时间、污泥的SOUR(比好氧呼吸速率)变化、反冲洗前后微生物量和微生物脱氢酶活性(DHA)的变化以及反冲洗后的恢复效果,并对反冲洗强度参数的选择进行了优化. 结果表明:在该研究条件下,采用气洗〔强度为12 L/(m2·s)〕4 min,气-水联合洗〔气洗强度为12 L/(m2·s),水洗强度为6 L/(m2·s)〕5 min,最后用清水漂洗9 min的反冲洗方式,排水中污泥的ρ(SS)可在最短时间(3 min)达到峰值;反冲洗排水中污泥的SOUR较低,平均值为0.5 mg/(mg·h);距离底端进水口1.3和2.2 m处的滤料层微生物的量损失较小,分别为4.4%和5.3%,其相应微生物的活性有所增加. 研究显示,该条件下反冲洗可有效清除滤料颗粒间所截留及滤料表面脱落的老化生物膜,并可保留适量活性较高的生物膜,强化了传质条件,反冲洗后对污染物的处理能力能恢复迅速.      

Preparation, characterization and performance of poly(m-phenylene isophthalamide)/organically modified montmorillonite nanocomposite membranes in removal of perfluorooctane sulfonate

Nanocomposite membranes containing poly(m-phenylene isophthalamide) (PMIA) and organically modified montmorillonite (OMMT) were prepared by a combination of solution dispersion and wet-phase inversion methods, and the effects of OMMT addition on the properties and performance of fabricated nanofiltration membranes were investigated. The membranes were characterized by contact angle measurements, scanning electron microscopy (SEM), atomic force microscopy (AFM), thermogravimetric analysis, and zeta potential. The performance of the membranes was elucidated by the removal of perfluorooctane sulfonate (PFOS) at neutral pH. Increasing OMMT concentration improved the thermal stability and hydrophilicity of the membranes. The permeation and rejection of PFOS were significantly improved. The performance of fabricated nanofiltration membranes in removal of PFOS varied depending on the solute and membrane properties as well as solution conditions. Finally, a comparison between fabricated membranes and a commercial NF membrane (ESNA1-K1, Hydecanme) proved that the OMMT addition is a convenient procedure for producing nanocomposite membranes with superior properties and performance.     

计算流体力学技术在膜分离过程中的应用与进展

计算流体力学（ComputationalFluidDynamics，CFD）技术近年被广泛地应用于膜分离过程模拟中。本文评述了CFD研究膜分离过程中流体力学、膜污染机理和浓差极化等现象，以及CFD技术在微滤、超滤、反渗透中的研究进展及待解决问题等。     

Life cycle assessment of spray dried soluble coffee and comparison with alternatives (drip filter and capsule espresso)

This paper aims to evaluate the environmental burdens associated with spray dried soluble coffee over its entire life cycle and compare it with drip filter coffee and capsule espresso coffee. It particularly aims to identify critical environmental issues and responsibilities along the whole life cycle chain of spray dried coffee. This life cycle assessment (LCA) specifically uses foreground data obtained directly from coffee manufacturers and suppliers. Aside from energy consumption and greenhouse gases emissions, water footprint is also studied in detail, including regionalization of water impacts based on the ecological scarcity method 2006. Other impact categories are screened using the IMPACT 2002+ impact assessment method.The overall LCA results for a 1 dl cup of spray dried soluble coffee amounts approximately to 1 MJ of primary non-renewable energy consumption, to emissions of 0.07 kg of CO_2-eq, and between 3 and 10 l of non-turbined water use, depending on whether or not the coffee cultivation is irrigated and wet treated. When considering turbined water, use can be up to 400 l of water per cup. Pouch – and to a lesser extent metal can packaging alternatives – show lower environmental burdens than glass or sticks.On average, about one half of the environmental footprint occurs at a life cycle stage under the control of the coffee producer or its suppliers (i.e., during cultivation, treatment, processing, packaging up to distribution, along with advertising) and the other half at a stage controlled by the user (shopping, appliances manufacturing, use and waste disposal). Key environmental parameters of spray dried soluble coffee are the amount of extra water boiled and the efficiency of cup cleaning during use phase, whether the coffee is irrigated or not, as well as the type and amount of fertilizer used in the coffee field. The packaging contributes to 10% of the overall life cycle impacts.Compared to other coffee alternatives, spray dried soluble coffee uses less energy and has a lower environmental footprint than capsule espresso coffee or drip filter coffee, the latter having the highest environmental impacts on a per cup basis. This study shows that a broad LCA approach is needed to help industry to minimize the environmental burdens directly related to their products. Including all processes of the entire system is necessary i) to get a comprehensive environmental footprint of the product system with respect to sustainable production and consumption, ii) to share stakeholders responsibility along the entire product life cycle, and iii) to avoid problem shifting between different life cycle stages.     

Data fusion modeling for groundwater systems

Engineering projects involving hydrogeology are faced with uncertainties because the earth is heterogeneous, and typical data sets are fragmented and disparate. In theory, predictions provided by computer simulations using calibrated models constrained by geological boundaries provide answers to support management decisions, and geostatistical methods quantify safety margins. In practice, current methods are limited by the data types and models that can be included, computational demands, or simplifying assumptions. Data Fusion Modeling (DFM) removes many of the limitations and is capable of providing data integration and model calibration with quantified uncertainty for a variety of hydrological, geological, and geophysical data types and models. The benefits of DFM for waste management, water supply, and geotechnical applications are savings in time and cost through the ability to produce visual models that fill in missing data and predictive numerical models to aid management optimization. DFM has the ability to update field-scale models in real time using PC or workstation systems and is ideally suited for parallel processing implementation. DFM is a spatial state estimation and system identification methodology that uses three sources of information: measured data, physical laws, and statistical models for uncertainty in spatial heterogeneities. What is new in DFM is the solution of the causality problem in the data assimilation Kalman filter methods to achieve computational practicality. The Kalman filter is generalized by introducing information filter methods due to Bierman coupled with a Markov random field representation for spatial variation. A Bayesian penalty function is implemented with Gauss–Newton methods. This leads to a computational problem similar to numerical simulation of the partial differential equations (PDEs) of groundwater. In fact, extensions of PDE solver ideas to break down computations over space form the computational heart of DFM. State estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. Further, a system identification theory has been derived based on statistical likelihood principles. A maximum likelihood theory is provided to estimate statistical parameters such as Markov model parameters that determine the geostatistical variogram. Field-scale application of DFM at the DOE Savannah River Site is presented and compared with manual calibration. DFM calibration runs converge in less than 1 h on a Pentium Pro PC for a 3D model with more than 15,000 nodes. Run time is approximately linear with the number of nodes. Furthermore, conditional simulation is used to quantify the statistical variability in model predictions such as contaminant breakthrough curves.