应用生物强化技术处理焦化废水难降解有机物

通过驯化富集培养,从处理 经废水的活性污泥中分离出2株萘降解菌WN1、WN2和1株吡啶降解菌WB1,研究了投加高效菌种及微生物共代谢对 经废水生物处理的增强作用,同时研究了高效菌种和共代谢初级基质组合协同作用的效果。结果表明,投加共代谢初级基质、Fe^3 和高效菌种均能促进难降解有机物的降解,提高焦化废水COD去除率,当3者协同作用时,效果最好。     

磁絮凝法处理DZA有机废水的研究

本文介绍了磁絮新颖产分离技术,应用该技术能有效处理水中ＤＺＡ有机物,实现数秒内的快速分离污泥,污泥含水率低。     

含酚废水高温生物处理效果的研究

本试验模拟焦化废水部分水质,进水酚约１０００ｍｇ／Ｌ,ＣＯＤｃｒ约２０００ｍｇ／Ｌ,水温维持在６０℃￣６８℃,从焦化废水生物处理厂的活性污泥中分离得到的１２株高温菌用于高温处理试验,结果酚的去除率在１２％￣１００％,ＣＯＤｃｒ的去除率在１３％￣９８％,两者的去除率变化如此之大,在于高温菌大多数为芽孢杆菌,是由于它们生活史中的营养细胞和芽胞不断交替演变所致。     

苯酚的超临界水氧化试验

以自建的一套连续式超临界水氧化装置的温度，压力，溶氧量和流量等参数的可控性进行了实验，并在此基础上进行了苯酚的超临界水氧化研究。结果表明：所建立的装置能比较精确控制各种条件参数，是可靠的超临界水氧化试验研究装置。在氧气过量的条件下，停留时间是影响苯酚在超临界水中氧化分解的主要因素，反应的温度和压力升高导致苯致苯酚去除率的增大，只要有足够的氧气，苯酚起始浓度的增加对苯酚的转化率影响不明显，在实验条件下，溶液中苯酚的去除动力学对苯酚是一级，氧气是零级。     

焦化废水处理利用的复合生态工程系统实验

生态工程系统(EES)处理焦化废水是实现低成本废水资源化的有效手段。该EES由UASB ABS IWBE组成。结果表明：在HRT为30h时，该系统对废水COD去除率的均值是91．1％，对NH4-N去除率平均为99．5％，对酚去除率平均为99．8％。废水可达标排放或循环利用。     

三种生物除磷工艺的比较

比较了Ａ／Ｏ法、Ａ＾２／Ｏ法和ＳＢＲ法生物除磷工艺。结果表明，它们的除磷效果好；污染含磷量达６％以上、除磷系数达０．０４左右，是常规好氧生物处理的３倍。在系统除磷系数相同的条件下，Ａ＾２／Ｏ法取好，是常规好氧法的３倍；ＳＢＲ法次之，高速率Ａ／Ｏ法因不能经反硝化作用脱氮，去氮效果与常规好氧法相同。     

二段生物接触氧化法处理含硫废水的中试研究

用二段生物接触氧化法探索炼油过程中所产生的含硫废水的处理新方法． 结果表明：经此工艺处理后的出水 Ｃ Ｏ Ｄ、氨氮、硫化物和酚的质量浓度ρ分别为２６６ ．９ ｍｇ／ Ｌ、８２ ．８５ ｍｇ／ Ｌ、１ ．１８ ｍｇ／ Ｌ 和１ ．４３ ｍｇ／ Ｌ,相应的去除率分别为８６ ．３ ％ 、４０ ％ 、９２ ．７ ％ 和９９ ．３ ％ ,出水水质达到国家三级排放标准． 进出水水质的变化曲线表明,生物接触氧化法处理含硫废水对进水水质变化的适应能力比较强,出水水质比较稳定,显示了二段接触氧化法处理含硫废水的可行性     

两相厌氧消化工艺处理有机废水的进展和应用

两相厌氧消化工艺是近年来发展很快的一种处理有机废水的新技术.本文介绍了该技术的微生物学原理和基本特点,总结了国内外的研究和应用现状,简要分析了该技术的研究动态.     

焦化废水中有机物的识别、污染特性及其在废水处理过程中的降解

采用液-液萃取辅以硅胶、氧化铝净化的方法,并结合GC/MS分析技术,系统分析了焦化废水中有机物的组成.在焦化废水中检测到15类558种有机物.根据有机物的分子结构、废水中的含量、毒性及环境效应,筛选出焦化废水中的特征性有机污染物,以区别于其它工业废水,可作为追溯环境中污染物来源的依据.经物理、生物和化学处理后,焦化废水中大部分有机物被去除,其中,对去除率的主要贡献是生物处理阶段.为了更好地考察生物处理阶段对有机污染物的去除特征,选定酚类、多环芳烃和喹啉类物质作为研究对象,分析了3类特征性污染物在A/O2工艺各单元中的去除状况及组成变化特征.     

生物接触氧化处理微污染地面水的实验研究

生物接触氧化处理微污染地面水的实验结果表明,该方法处理效果显著、稳定性好、操作方便、容易实施,是解决污染给水处理问题的经济可行办法。     

Impact of hydraulic loading on removal of polycyclic aromatic hydrocarbons (PAHs) from vertical-flow wetland

The effects of polycyclic aromatic hydrocarbons (PAHs) removal on lab-simulated vertical wetland systems, each containing eight dominant species, under continuous- and intermittent-flow feeding modes, were determined. The main results were: (1) PAHs removal effect was greater in intermittent-flow system than in continuous-flow system, with the exception of the floating plant Hydrilla verticillata wetland. This may be due to pollutants remaining stable for longer duration under intermittent-flow mode, which is conducive to microbial, plant, and water absorption of PAHs, as well as to microbial decomposition and absorption by plant roots; (2) absorption and degradation rates of PAHs varied among wetland body plants in different periods with removal efficiencies of 30%–70% observed following the first and fifth cycles, and under high-performance degradation conditions; (3) mean removal rates of PAHs by hydrophytes under continuous-flow mode were as follows: H. verticillata (34.4%), Arundo donax (Gramineae) (33.2%), Phragmites australis (28.7%), Ipomoea aquatica Forsk (Convolvulaceae) (28.5%), Zizania aquatic (27.6%), Calla palustris (Araceae) (27.2%), Acorus calamus (26.8%), and Hardy canna (17.9%); (4) average rates of PAHs removal by hydrophyte under intermittent-flow mode were as follows: A. donax (40.5%), Z. aquatic (37.9%), A. calamus (37.0%), P. australis (36.9%), Hardy canna (34.6%), C. palustris (33.9%), I. aquatica (31.2%), and H. verticillata (29.3%).     

不同水力负荷下凤眼莲去除氮、磷效果比较

采用人工模拟方法,研究了不同水力负荷(0.14、0.20、0.33和1.00m3.m-2.d-1)对凤眼莲去除富营养化水体氮、磷效果的影响,试验期间进水TN、NH4+-N、NO3-N、TP平均质量浓度分别为4.85、1.33、2.92和0.50mg.L-1。结果表明,凤眼莲净化系统对富营养化水体具有较好的去除效果,低水力负荷(0.14、0.20m3.m-2.d-1)下,出水TN、NH4+-N和TP均达到了GB3838—2002《地表水环境质量标准》的Ⅳ类水质标准;当水力负荷提高到1.00m3.m-2.d-1后,出水TN、NH4+-N、NO3-N和TP质量浓度明显上升。4种水力负荷下,凤眼莲净化系统对TN和TP去除率分别为84.95%和80.65%、73.87%和73.04%、51.60%和64.05%、30.77%和47.79%,即随水力负荷的提高而降低;相应的TN、TP去除负荷分别为0.58和0.06、0.72和0.07、0.83和0.11、1.47和0.23g.m-2.d-1,即随水力负荷的提高而增加。综合考虑净化效果和污水处理能力,本试验条件下凤眼莲系统的水力负荷宜控制在0.33m3.m-2.d-1。     

Detection and delineation of critical areas using echelons and spatial scan statistics with synoptic cellular data

Geographical surveillance for hotspot detection and delineation has become an important area of investigation both in geospatial ecosystem health and in geospatial public health. In order to find critical areas based on synoptic cellular data, geospatial ecosystem health investigations apply recently discovered echelon tools. In order to find elevated rate areas based on synoptic cellular data, geospatial public health investigations apply recently discovered spatial scan statistic tools. The purpose of this paper is to conceptualize a joint role for these together in the spirit of a cross-disciplinary cross-fertilization to accomplish more effective and efficient geographical surveillance for hotspot detection and delineation, and early warning system.     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.