影响富营养化水体沉水植物修复的生态因子探讨

日益严重的水体富营养化现象，不仅降低了它的使用功能，也使水生态系统日趋退化，从而制约了当地社会经济的可持续发展。利用组建或重建沉水植物技术净化水质或进行水体生态修复是一种有效的生态工程措施。本文综述了光照、pH、营养盐、重金属、悬浮颗粒物及着生藻类等生态因子对沉水植物修复的影响和修复时应注意的问题。     

春夏两季四种植物净化生活污水的静态试验研究

在春夏两季，分别开展为期30天的静态试验，以研究芦苇、黄菖蒲、美人蕉、香蒲四种湿地植物对富营养化生活污水的净化效果。试验结果表明：通过纵向比较，夏季时植物对TN、TP的净化效果优于春季。通过横向比较，春季时黄菖蒲和香蒲的净化能力较强；夏季时美人蕉的净化能力较强。在时间上，可将喜温植物与耐寒植物结合，以保证湿地系统的长年运行；在空间上，可将挺水植物与沉水植物结合，以保证湿地系统的处理效果。     

小议火电厂总量减排核查要点

从资料核查、在线监测设备核查、集控系统核查及现场核查4个环节详细介绍了火电厂总量减排现场核查的要点。对核查中出现的问题进行总结及分析,为同类环境管理工作提供参考。     

植物对潜流人工湿地净化微污染水效果的影响研究

以4种湿地植物为实验对象,在野外构建中试潜流人工湿地,研究了不同植物及植物连根收割对湿地运行效果的影响。结果显示,植物明显提升了湿地的去污效果;其中美人蕉湿地的TP和NH4+-N去除率最高,达到55.6%和78%;空心菜湿地的TN去除率最高,达到80.5%;芦竹湿地的COD去除率最高,为26.6%;植物连根收割后,湿地运行效果下降;其中TN去除率降至空白水平之下,而其他污染指标下降至略高于空白的水平。     

Comparative Evaluation of Biomonitoring Techniques of Tropospheric Ozone

During a survey of tropospheric ozone pollution carried out using tobacco plants (Nicotiana tabacum L.) cv. Bel-W3, ozone- supersensitive, and cv. Bel-B, ozone-resistant, as bioindicators, the effectiveness of the traditional biomonitoring method, based on the use of adult plants, was compared with an innovative miniaturized kit of seedlings. The ratio of foliar and cotyledonar necrosis, respectively, was estimated as ozone injury rate. The miniaturized kit proved to be advantageous, since seedlings need only easy growth procedures and a large number of individuals can be placed in a small space, supplying good data amounts for statistical elaboration. Moreover, correlation studies among cotyledonar and foliar injury index and ozone levels monitored through physico-chemical measurements and results of analysis of variance tests highlighted the high sensitivity of the innovative methodology.     

水生植物对污染物的清除及其应用

综述了水生植物对氮、磷、重金属及有毒有机物等各类污染物的清除作用及其在污染治理中的应用实践,同时对水生植物在废水处理和湖泊治理方面的应用提出了相应的建议。     

The use of physiological characteristics for comparison of organic compounds phytotoxicity

The influence of intact (FLT) and photomodified (phFLT) fluoranthene (0.05, 0.5 and 5 μmol l⁻¹) and herbicide Basagran (5, 20, 35 and 50 nmol l⁻¹) on the germination, growth of seedlings and photosynthetic processes in pea plants (Pisum sativum L., cv. Garde) was investigated. The germination was significantly inhibited already by the lowest concentration (0.05 μmol l⁻¹) of FLT and phFLT, while Basagran caused inhibition only in higher concentrations (35 and 50 nmol l⁻¹). The growth of roots was significantly inhibited by higher concentration 5 μmol l⁻¹ of both FLT and phFLT and the shoot of seedlings was significantly influenced only by photomodified form. The length of root and shoot was inhibited already by concentration 5 nmol l⁻¹ of Basagran. Organic compounds applied on chloroplasts suspension influenced primary photochemical processes of photosynthesis. In chlorophyll fluorescence parameters, the significant increase of F₀ values and the decrease of F_V/F_M and Φ_II values by application of FLT (0.5 and 5 μmol l⁻¹) and phFLT (0.05, 0.5 and 5 μmol l⁻¹) was recorded. The maximum capacity of PSII (F_V/F_M) was influenced by the highest (50 nmol l⁻¹) and the effective quantum yield of PSII (Φ_II) already by the lowest (5 nmol l⁻¹) concentration of Basagran. Hill reaction activity decreased and was significantly inhibited by higher concentration (0.5 and 5 μmol l⁻¹) of FLT and phFLT and already by the lowest concentration (5 nmol l⁻¹) of Basagran.     

Monitoring air quality with lichens: a comparison between mapping in forest sites and in open areas

Four different methods of epiphytic lichen mapping were used for the assessment of air quality in the region under the influence of the Sostanj Thermal Power Plant (Salek Valley, Slovenia). Three methods were based on the presence of different lichen species (VDI, EU and ICP-Forest), the fourth on a frequency and coverage assessment of different growth forms of epiphytic lichens, e.g. crustose, foliose and fruticose (SI). A comparison of the results from the assessment of air quality between forest sites (ICP-Forest, SI) and open areas (VDI, EU and SI), obtained by the different methods of epiphytic lichen mapping, is presented in the contribution. Data showed that lichen species richness is worse in forest sites in comparison with open areas. From the data obtained it can be concluded that epiphytic lichen mapping in open areas is a better method for the assessment of air pollution in a given area than mapping in forest sites. The species-based methods in open areas are more powerful and useful for air quality assessment in polluted research areas than the SI and ICP-Forest methods.     

Database for accidents and incidents in the fuel ethanol industry

The purpose of the present research is to collect information about accidents and incidents that have occurred at fuel ethanol facilities from 1998 to October 2014, and to keep complete unified records of them in a database. The developed database contains general information about the accident or incident, its sequence, mitigation measures, its causes and consequences for humans, environment and for the plant. Until now, this information is not available. The work consisted in gathering information from different documental sources and subsequent organization in a database. It complements the previous work made for biodiesel industry and fills the existing gap in the field of ethanol. Knowledge about this information enables us to manage plant risks, since the accidents that are more likely to occur and the main sources of risk can be easily identified. Also, it makes it possible to exchange information with interested third parties. Statistical analysis shows that accident frequency has an oscillatory behavior, rising in the last year. Fire is the most common type of accident, while equipment mechanical failure is the main cause of accident. Partial material loss has been identified as the most common consequence. Finally, some conclusions are obtained concerning to the importance of having an updated and complete accident and incident database.     

基于神经网络分类器的城市污水处理厂水力冲击预警系统

提出了一套基于神经网络分类器的城市污水处理厂水力负荷冲击预警系统,以期对进水水量骤增现象进行提前1天的预报,使污水处理厂可根据预报结果提前采取水力冲击防护措施,从而保证各单元的平稳运行.根据进水水量的涨幅将某污水处理厂12年日进水水量监测数据分为"常规"和"冲击"两类,重点对"冲击"数据进行提前1天的预测,并采用冲击漏报率、冲击误报率和报准率对模型的预测精度进行评价;同时,基于同样的建模方法和不同的训练、验证样本建立了N(1)、N(2)和N(3)3个平行模型,以对模型的鲁棒性和建模方法的可重复性进行考察.结果显示,3个模型对2010年、2011年和2012年3年测试样本的预测效果良好,冲击漏报率和报准率两项指标数值均较为稳定,分别在0~0.167和0.981~0.995之间浮动,冲击误报率虽然在数值上的浮动较大,最低为0.143,最高为0.500,平均为0.310,但仍在工程上的可承受范围内.该结果表明,本研究基于神经网络分类器所建立的3个神经网络模型预测精度高、鲁棒性好,显示出良好的性能,有望为污水处理厂水力冲击防护工作提供有力参考.