催化臭氧氧化—生物活性炭吸附组合工艺处理反渗透浓水

采用催化臭氧氧化—生物活性炭吸附组合工艺处理反渗透(RO)浓水,比较了4种催化剂催化臭氧氧化的性能,优化了初始RO浓水pH、臭氧氧化时间、生物活性炭柱空床停留时间(EBRT)等工艺条件。实验结果表明:以WP-01为催化剂催化臭氧氧化RO浓水时无需调节废水pH;臭氧氧化反应5 min时RO浓水的BOD5/COD达0.28,可生化性得到显著改善;WP-01催化剂重复使用30次其催化活性没有明显下降;生物活性炭吸附单元的EBRT控制在30 min左右,可确保出水COD稳定在50 mg/L以下,符合GB 18918—2002《城镇污水处理厂污染物排放标准》的一级A标准;催化臭氧单元处理每吨RO浓水的电费约为1.22元。     

海水淡化超滤-反渗透工艺沿程溴代消毒副产物变化规律

研究了海水淡化超滤-反渗透(UF-RO)工艺沿程有机物和溴代消毒副产物(Br-DBPs)变化特征.该海水中含有较高浓度的Br-(45.6~50.9 mg·L-1)和较多的芳香类化合物[比紫外吸收值SUVA为3.6~6.0 L·(mg·m)-1];色氨酸类芳香族蛋白质、富里酸类有机物和溶解性微生物代谢产物是海水中主要的荧光特征有机物.UF-RO工艺进水海水经Na Cl O消毒后,DBPs的种类和浓度显著增加,且增加的主要为Br-DBPs,其中三溴甲烷(CHBr3)占总三卤甲烷(THMs)的70.48%~91.50%,二溴乙酸(Br2CHCO2H)占总卤乙酸(HAAs)的81.14%~100%,二溴乙腈(C2HBr2N)占总卤乙腈(HANs)的83.77%~87.45%.UF膜对THMs、HAAs和HANs的去除率分别为36.63%~40.39%、73.83%~95.38%和100%.RO膜可以完全去除HAAs,但是对THMs不能完全去除.进水海水的抗雌激素活性为0.35~0.44 mg·L-1,氯消毒后增加了32%~69%.海水淡化UF-RO系统生成的DBPs和其他生物毒性物质最终被截留到了UF浓水和RO浓水中.     

液体零排放技术在工业水处理领域的应用

介绍了最新的、已实现工业应用的液体零排放技术,概括了该技术的常规系统组成,描述了液体零排放技术的预处理、热处理、最终废弃物处理以及高效反渗透预浓缩的液体零排放技术的特点,总结了该技术在电力、炼油及石化、煤化工和采油等工业水处理领域的应用,指出了该技术存在的问题,展望了该技术的发展前景。     

袋式除尘器用滤布粉尘层剥离性能实验研究

通过对袋式除尘器用滤布反吹风清灰效果以及惯性力甩脱清灰效果的研究,实验表明,反吹风清灰时,在一定反吹风速下,滤布上粉尘负荷越大,清灰效果越好;在一定粉尘负荷下,粉尘剥离率随反吹风风速的增加而提高,当反吹风速增加到0.07 m/s时,剥离率趋于平缓;惯性力清灰时,在一定转速下,粉尘剥离率随粉尘负荷的增加而提高;在一定粉尘负荷下,粉尘剥离率随着惯性力的增加而提高,当惯性力达到200 Pa时,剥离率基本稳定;剥离力与剥离率具有良好的相关性,符合准=F/(a+bF)形式。研究结果有助于深化袋式除尘器清灰机理的认识,同时为袋式除尘器清灰方式和运行参数的选取提供科学依据。     

NF和低压RO工艺处理锅炉补给水的研究

以自来水为原水,采用纳滤(NF)与低压反渗透(RO)工艺进行锅炉补给水处理研究。考察了一级NF及RO工艺、二级NF及RO工艺、NF-RO串联和RO-NF串联工艺对锅炉补给水的软化除盐效果。结果表明,NF和RO分别在0.75MPa和1.0Mpa压力下,回收率20%时处理效果最好。一级NF和一级RO可满足中低压热水锅炉补给水的水质要求;二级NF和二级RO、NF-RO和RO-NF工艺均可满足中低压蒸汽锅炉补给水的水质要求;串联工艺处理效果优于二级NF,且比二级RO节能;RO-NF和二级RO工艺可满足高压锅炉补给水的水质要求。     

B2C服饰类电商企业逆向物流网络联建研究

在电子商务环境下,由于网络购物的兴起,导致大量退货逆向物流和回收逆向物流.鉴于国内多数电商企业没有完善的逆向物流系统,相关学术研究和出版物较少,网购产品中81.8％是服装鞋帽类产品,故提出一种基于电商环境下服饰类行业联合构建逆向物流网络.该网络模型旨在降低两大逆向物流的回收成本,形成规模效应和溢出效应.因此,构建了0-1MILP数学模型和模拟数据,借助Lingo9.0计算软件找出模型的最佳运营状态,为服饰类电商企业高效完成逆向物流活动、提高服务质量、增强行业竞争力提供思路.     

Comparing Contaminant Removal Costs for Aquifer Recharge with Wastewater with Water Supply Benefits

The use of waters of impaired quality has been suggested as a means to expand available water resources supply for water‐limited communities. An ongoing concern is the safety of supplies that use wastewater because of the potential for introduction of emerging contaminants such as pharmaceuticals into drinking water supplies. Prior research into contaminants of emerging concerns (CECs) have included a variety of methods, but the only consistent removal is with reverse osmosis (RO) membranes, ultraviolet light (UV), and advanced oxidation processes (AOP). However, few of these prior studies have measurable quantities of these contaminants in the influent wastewater, so determining actual removal percentages is difficult. This project was designed to evaluate the removal of CECs to verify that a 3‐log removal of common constituents was realized. Spike testing was used to compare to prior research and to evaluate whether the project costs were competitive with other forms of reuse or other water supplies. The combination of RO/UV/AOP was effective at obtaining a 3‐log removal of CECs, but the RO and UV/AOP processes alone were not capable of removing all substances. However, despite the extensive treatment, the proposed process was both competitive cost‐wise and met the water quality goals.     

沸石负载型TiO2处理炼化反渗透浓缩水的研究

利用沸石负载型二氧化钛对炼化企业的反渗透浓缩水进行研究,考察了催化剂对浓缩水的处理效果及影响降解的因素。由实验结果可知:沸石负载型二氧化钛对反渗透浓缩水TOC降解率达到67.4%,降解浓缩水的最佳条件为:pH值为4～6,温度30～40℃,光照时间2.5h,催化剂投加量为1.5g/L。实验为浓缩水处理技术的发展提供了新的依据。     

Modelling and optimisation of a product recovery network

An appropriate logistics network is an important element of the infrastructure of any product recovery company. Small and medium enterprises (SMEs) constitute a major fraction of the product recovery industry with a different business objective and scale of operation from those of original equipment manufacturers. This paper addresses the network design issues for SMEs involved in product recovery activities. A mathematical formulation is presented in an SME context and a subsequent simulation model is developed. A genetic algorithm approach is presented for optimising the network for a single product scenario.