赭石对模拟重金属废水的吸附效果研究

采用模拟重金属废水的正交试验设计,进行赭石对模拟重金属废水的吸附效果研究,探讨pH、赭石加入量和振荡时间等影响因素对吸附效果的影响。结果表明,在一定pH、赭石加入量和振荡时间条件下,赭石对6种重金属（Pb、Cd、Mn、Zn、Cr和Ni）均有较好吸附效果,对Pb、Cd、Mn、Zn和Cr的最大吸附率可达100%,对Ni的吸附率达8963%。处理后废水中重金属达到污水排放标准。各影响因素对Mn、Zn和Cr吸附效率的影响大小表现为：pH＞赭石加入量＞振荡时间,Ni和Cd表现为：赭石加入量＞pH＞振荡时间,Pb表现为：pH＞振荡时间＞赭石加入量。赭石对废水中重金属吸附的最佳条件为赭石加入量40 g/L,pH 10～10.5,振荡时间2 h。     

利用UVC去除低浓度苯的实验研究

探讨了不同实验参数对苯的UVC去除效果的影响,获得了苯的去除率与苯的初始浓度、气体流量、相对湿度和氧气含量等参数之间的关系。数据表明,在实验条件范围内,苯的去除率的倒数与苯初始浓度、气体流量之间为线性关系;苯的去除率随相对湿度的增加呈现先升高后缓慢降低的关系,最佳相对湿度值在30%～50%之间;苯的去除率随氧气量的增加而缓慢增加;波长为185+254 nm的UV与254 nm的UV相比净化效果更为理想。还分析了苯降解产生的中间产物,探讨了苯的降解机理。     

湖岸缓冲带反硝化作用的研究进展

反硝化作用是湖岸缓冲带去除硝酸盐的重要途径。湖岸缓冲带是联系陆地与湖泊生态系的纽带,不仅为许多动植物提供适宜生境,而且通过反硝化作用能去除地下水中的硝酸盐,提高湖泊水质。概述不同检测反硝化速率的方法,并对比各种方法的优点与缺点。阐述反硝化作用的影响因素：厌氧环境、有机碳、湖岸坡度、缓冲带坡度、pH与温度、硝酸盐浓度。介绍反硝化速率模型的研究开发状况。最后,提出了目前国内外反硝化研究中存在的不足及发展方向。     

固定化假单胞菌降解油烟废气的研究

将从受油烟废气污染严重的土壤中分离筛选的具有较强降解油烟能力的假单胞菌利用活性炭为填料吸附固定后制成填料床生物反应器。实验考察了进气浓度、气体流量、气体停留时间、容积负荷等对油烟去除率的影响,初步研究了生物反应器的抗冲击能力。结果表明,活性炭填料对菌体具有良好的吸附能力,当油烟进气浓度小于100 mg/L,气体流速小于8 L/h,停留时间大于30 s,容积负荷为2.6～18.9 g油烟废气/(m³·h),生物反应器的降解效率可达到95%以上,且活性炭填料床反应器具有较强的抗冲击能力。     

微电解-催化氧化法处理高浓度甲醇废水

采用微电解一催化氧化法处理某化工厂的高浓度甲醇生产废水。实验结果表明：在进水pH为2．0、铁炭质量比为2、微电解时间为14h、空气流量为500mL／min的条件下,废水经微电解处理后,出水COD由原来的约7000mg/L降至约1000mg／L,COD去除率达85％以上;在过滤后微电解出水COD约为950mg／L、微电解出水pH为6．5、空气流量为300mL／min、催化氧化时间为3h时的条件下,经催化氧化处理后,出水COD降至100mg/L以下,出水水质达到GB8978--1996《污水综合排放标准》的二级标准。     

安全社区建设过程中的科学方法研究

随着安全社区在我国推广工作的不断深入开展,与之相适应的科学方法的运用水平与有效性已经显得相对不足。由于安全社区建设和伤害预防工作涉及社会学、管理学、预防医学、安全科学、心理学等多个学科,其学科跨度及巨大复杂性,使得没有任何一个学科可以单独地应用完成,并且它具有许多不同于其他学科的特殊性,因此,关于安全社区建设过程中的科学方法研究十分必要。     

Prediction models of CO, SPM and SO2 concentrations in the Campo de Gibraltar Region, Spain: a multiple comparison strategy

The 'Campo de Gibraltar' region is a very industrialized area where very few air pollution studies have been carried out. Up to date, no model has been developed in order to predict air pollutant levels in the different towns spread in the region. Carbon monoxide (CO), Sulphur dioxide (SO(2)) and suspended particulate matter (SPM) series have been investigated (years 1999-2000-2001). Multilayer perceptron models (MLPs) with backpropagation learning rule have been used. A resampling strategy with two-fold crossvalidation allowed the statistical comparison of the different models considered in this study. Artificial neural networks (ANN) models were compared with Persistence and ARIMA models and also with models based on standard Multiple Linear Regression (MLR) over test sets with data that had not been used in the training stage. The models based on ANNs showed better capability of generalization than those based on MLR. The designed procedure of random resampling permits an adequate and robust multiple comparison of the tested models. Principal component analysis (PCA) is used to reduce the dimensionality of data and to transform exogenous variables into significant and independent components. Short-term predictions were better than medium-term predictions in the case of CO and SO(2) series. Conversely, medium-term predictions were better in the case of SPM concentrations. The predictions are significantly promising (e.g., d (SPM 24-ahead) = 0.906, d (CO 1-ahead) = 0.891, d (SO2 1-ahead) = 0.851).     

Occurrence of phenols in leachates from municipal solid waste landfill sites in Japan

The concentrations of 41 phenols in leachates from 38 municipal solid waste (MSW) landfill sites in Japan were measured. The main phenols detected in leachates were phenol, three cresols, 4-tert-butylphenol, 4-tertoctylphenol, 4-nonylphenol, bisphenol A, and some chlorophenols. The concentration levels of phenols were affected by the pH values of the leachates and the different types of landfill waste. The origins of phenol and p-cresol were considered to be incineration residues, and the major origin of 4-tert-butylphenol, bisphenol A, and 2,4,6-trichlorophenol was considered to be solidified fly ash. In contrast, the major origins of 4-tert-octylphenol and 4-nonylphenol were considered to be incombustibles. The discharge of leachates to the environment around MSW landfill sites without water treatment facilities can cause environmental pollution by phenols. In particular, the disposal of incineration residues including solidified fly ash and the codisposal of solidified fly ash and incombustibles might raise the possibility of environmental pollution. Moreover, the discharge of leachates at pH values of 9.8 or more could pollute the water environment with phenol. However, phenol, 4-nonylphenol, and bisphenol A can be removed to below the con centration levels that impact the environment around landfill sites by a series of conventional water treatment processes.     

Assessment of heavy metal enrichment in the offshore fine-grained sediments of the Caspian Sea

Sampling of the offshore seabed sediments of southwestern part of the Caspian Sea was carried out by gravity corer in order to study heavy metal concentration and the physicochemical factors controlling their distribution in the fine-grained fraction. The grain size distribution, amount, and type of clay minerals, total organic carbon (TOC) content, and Eh–pH of the sediments were determined. The average concentrations of the heavy metals in ppm are Mn (563), Cu (207.5), Sr (187), Zn (94), Pb (26.3), Ni (14.5), Co (11.5), Cd (2.56), and Ag (1.04) in their order of abundances. Co and Zn mostly indicate increase in silt-size fraction of the sediments suggesting their probable detrital provenance but the Mn, Ni, Cu, Sr, Pb, Cd, and Ag concentrations show a similar trend to distribution of the clay-size fraction. The concentrations of Mn, Co, and Cd increase with increase in the TOC content but the Cu, Pb, Ni, Ag, and Sr concentrations decrease with increase of the TOC content. The amounts of Zn, Cu, Sr, Pb, Cd, and Ag increase with increase in the CaCO₃ content. The calculated enrichment factor indicates that the sediments are very strong to extremely enriched in Ag, significantly enriched in Cu and Cd, and depleted to mineral for Pb, Sr, Co, Ni, and Zn. Variations of the Cu, Sr, Cd, Ag, and Pb concentrations are similar to the clay and CaCO₃ distributions.