溶藻细菌L8的溶藻活性代谢产物对水华鱼腥藻光合特性的影响研究

从广州城区某富营养化池塘筛选出1株溶藻细菌L8(简称L8菌),研究了L8菌的溶藻活性代谢产物(简称L8菌溶藻产物)对水华鱼腥藻(Anabaena flos-aquae)光合特性的影响。结果表明,L8菌溶藻产物能够使水华鱼腥藻中的类胡萝卜素、藻蓝蛋白和别藻蓝蛋白的含量显著升高,经L8菌溶藻产物作用7d后,3者分别升高了35.7%、63.2%和185.7%,而叶绿素a含量下降了51.3%;经L8菌溶藻产物作用7d后,水华鱼腥藻的光系统Ⅱ(PSⅡ)的光化学效率、潜在活性以及光合电子产量均明显降低。低温(77K)荧光发射光谱的变化表明,光合色素相对含量的变化导致光能在水华鱼腥藻2个光系统之间的分配发生了变化,影响了光能在光系统Ⅰ(PSⅠ)、PSⅡ中的分配,进而影响了水华鱼腥藻的光合作用效率。     

藻类膜对磷的吸附/吸收行为研究

在光照强度约4 000 lx及温度28℃条件下,将水华鱼腥藻(Anabaena flos-aquae)和斜生栅藻(Scenedesmus obliqnus)附着在弹性聚氯乙烯载体上形成藻类膜,研究藻细胞在富磷环境(约为2 mg/L)中对磷的短期吸收过程,分析基质中磷、藻细胞总磷及表面吸附磷的迁移变化特征。结果表明:水华鱼腥藻和斜生栅藻细胞总磷含量在稳定时分别为0.96和0.85 mg/mg(以chla计);藻细胞表面对磷的吸附在240 min时达到平衡,其中水华鱼腥藻吸附量占细胞总磷(包括表面吸附磷和细胞内磷)的28.1%,斜生栅藻则为23.5%。根据吸附模型拟合结果,藻细胞表面对磷的吸附符合Langmuir吸附等温式。     

包埋水华鱼腥藻和活性炭对污水中氮磷的净化

采用聚乙烯醇-海藻酸钠（PVA—SA）凝胶包埋水华鱼腥藻与活性炭混合物，对比水华鱼腥藻在包埋、吸附以及悬浮状态下对高浓度模拟废水中氨氮的去除效果，实验结果表明，水华鱼腥藻在包埋状态下对氨氮有更好的去除效果。通过正交实验研究SA、粉末活性炭（PAC）、水华鱼腥藻之间不同质量比的包埋混合物对去除污水中NH4＋-N、TP以及处理后废水中微囊藻毒素（MC）残留量的影响，结果表明，当PVA量为8％时，SA、PAC和藻含量分别在0．5％、0．5％和0．2％为NH4＋-N、TP的最佳去除组合，同时处理后污水中MC的含量也低于联合国标准1Iμg／L，避免了二次污染的同时为产毒素藻类的利用创造了条件。     

再生水补水景观湖浮游藻类群落结构特征及与环境因子的关系

在2014年6月至2015年5月,对以再生水为补水水源的天津临港生态湿地公园景观湖区的浮游藻类和水质指标进行逐月监测,应用典范对应分析(CCA)研究了浮游藻类与环境因子之间的关系,评价了湖区的水环境状况。结果表明:共鉴定出浮游藻类7门67属115种(包括变种),硅藻门种类最多,其次为绿藻门和蓝藻门,浮游藻类丰度范围为3.5×106~49×106cells·L~(-1),平均丰度为25.7×106cells·L~(-1),优势藻种主要为链状假鱼腥藻、梅尼小环藻、四尾栅藻、颤藻、项圈藻和卵形隐藻;多样性分析显示,藻类物种多样性一般,结合优势指示种评价水体为中污染富营养型水体;典范对应分析表明,水温、盐度、TN/TP等是影响临港再生水补水景观湖藻类群落结构的主要因素。     

铁对四尾栅藻生长的影响

采用实验室模拟培养的方法,分别测定了初始Fe3 摩尔浓度为0、10、100、1 000、10 000、30 000 nmol/L时的四尾栅藻生物量、叶绿素a浓度,同时利用扫描电镜观察了初始Fe3 摩尔浓度为0、10 000、30 000 nmol/L时的四尾栅藻细胞的表面结构.结果表明,初始Fe3 摩尔浓度在0、10 nmol/L时,四尾栅藻的生长受到抑制;初始Fe3 摩尔浓度超过10 000 nmol/L时,四尾栅藻生长受到的促进作用仍存在,但不显著;初始Fe3 摩尔浓度增加至30 000 nmol/L时,四尾栅藻生长未受到抑制;四尾栅藻叶绿素a浓度随时间的变化与四尾栅藻生长曲线相似,随初始Fe3 浓度的增加而增加;不同初始Fe3 浓度对四尾栅藻细胞表面结构影响不明显.     

光照度对蓝藻垂直迁移特性影响研究

通过水柱和摇瓶试验研究了蓝藻细胞胞内碳水化合物含量及蓝藻细胞在水体中的垂直分布对光照度变化的响应。结果表明,水柱试验中,在无光照和光照度为5000lx的条件下,铜绿微囊藻出现明显的表面浮聚现象,经过24h后,表层的藻细胞数分别占总藻细胞数的47%和26%;水柱试验中,在不同光照条件下,铜绿微囊藻胞内碳水化合物含量都呈现出表层低、底层高的现象;摇瓶试验中,水华鱼腥藻和铜绿微囊藻胞内碳水化合物含量对光照度的变化有很好的响应,光照度适量时,胞内碳水化合物含量上升,光照度不足或者过高时,胞内碳水化合物含量下降;光照度的变化能够在短时间内引起蓝藻细胞胞内碳水化合物含量变化,改变蓝藻细胞密度,从而影响到蓝藻细胞在水体中的垂直分布。     

四步盐析提取巢湖新鲜蓝藻中藻蓝蛋白及其稳定性

实验采用四步盐析法提取巢湖水华蓝藻中的藻蓝蛋白并对其稳定性进行研究。以藻蓝蛋白纯度和得率为指标,采用3次冻融破壁后蓝藻,运用黄金分割法在饱和度为0%~70%的范围内选取合适的硫酸铵用量。并考察了光照、时间、环境温度、p H、乙醇及常见食品添加剂对藻蓝蛋白稳定性的影响。结果表明,常温下四步盐析法采用硫酸铵的饱和度分别为21%、30.4%、26.28%和47.76%,藻蓝蛋白纯度和得率分别为3.157和1.664%。藻蓝蛋白在避光和常温中性条件下保持稳定,超出此范围稳定性下降。添加乙醇和柠檬酸将导致藻蓝蛋白稳定性下降,氯化钠和苯甲酸钠对藻蓝蛋白稳定性影响较小。     

脉冲变频电磁场对水华鱼腥藻生长的效应

对脉冲变频电磁场作用下，扫描频率和磁感应强度的变化对水华鱼腥藻细胞活性和生长的影响进行了研究。结果显示，扫描频率从25~27 Hz增大到1~60 kHz时，磁场对藻细胞活性的抑制作用减小，但增大到60 kHz以上，磁场对藻细胞产生强烈抑制作用，累积水力停留时间4 min的藻样在48 h培养时间内已失去活性停止生长。扫描频率为50~100 Hz和1~60 kHz时，累积水力停留时间2 min的藻样，细胞受到磁场刺激生长加快；只有累积水力停留时间＞6 min，才表现出对藻活性的抑制作用。磁感应强度增大至120 G，磁场对细胞活性产生明显抑制作用，增大磁感应强度有利于对细胞活性和生长的抑制。     

南海湖非冰封期浮游植物群落生态特征及其与环境因子关系

分别于2017、2018年的非冰封期(5—10月)对南海湖的浮游植物群落和环境因子进行了调查。共发现浮游植物7门80属157种(含变种),其中绿藻门种数最多,其次是硅藻门和蓝藻门,时间上7月最多、10月最少,空间上呈东高西低、南高北低的趋势。浮游植物密度为23.35×10~6～126.00×10~6个/L,平均值为66.78×10~6个/L。主要优势种有微小平裂藻(Merismopedia tenuissima)、水华束丝藻(Aphanizomenon flosaquae)和螺旋弓形藻(Schroederia spiralis)。南海湖水质总体处于中污染状态。冗余分析表明,TN、TP、pH和温度是影响浮游植物分布的主要环境因子,绿藻门与TN关系密切,蓝藻门与TP、温度关系密切,硅藻门与pH关系密切。     

巢湖蓝藻的机械清除工艺以及藻水分离实验研究

对巢湖蓝藻进行机械清除以及藻水分离实验研究，实验采用的浮式围栏引导一机械清除．投加剥离液辅助机械清除工艺处理量大，除藻效率高，筛网过滤-浓缩-卧螺离心机脱水成藻泥的藻水分离工艺较为理想，藻泥含水率仅为89％。2011年5-10月在巢湖运用上述方法清除湖面水华蓝藻，共处理富藻水1．6万m3，得到藻泥970t，累计清除蓝藻106．7t（干重）。按照所清除蓝藻的总氮、总磷的平均含量计算，相当于从湖中移除了氮6．25t，磷2．1t。表明在富营养湖泊中水华蓝藻大量暴发时，采用上述方法除藻，对控制蓝藻水华污染，有效降低内源氮、磷等污染物负荷具有十分重要的作用。     

次氯酸钠发生器的研制

介绍了电解法生产次氯酸钠的原理 ,并在原有生产工艺的基础上进行了重新设计和对设备的重新选择、改造 ,得出了各个工艺参数的最佳值 ,生产出高品质的次氯酸钠     

Estimation of uncertainty of sampling for analysis of pesticide residues

Abstract

A computer model was used to take random samples from primary sample populations obtained from field trials to simulate the uncertainty of sampling for residue analysis of plant commodities and soil. The results indicate about 40%, 30% and 20% relative uncertainty when random samples of size 5, 10 and 25 are taken respectively, from a single lot. Therefore the sample size should be the same for establishing and enforcing legal limits.     

An application of the theory of kinematics of mixing to the study of tropospheric dispersion

The most common technique used for numerical simulations of tracer mixing is that of the numerical solution of the advection–diffusion equation with the unresolved fluxes parameterized using the similarity theory. Despite correct predictions of the overall directions of transport, models based on a numerical solution of the advection–diffusion equation lack sufficient accuracy to correctly reproduce the coupling of mixing with small scale processes which are sensitive to the microstructure of the tracer distribution. The objective of this paper is to revisit the basic formalism employed in numerical models used to investigate atmospheric tracers. The main mathematical method proposed here is the theory of kinematics of mixing which could be applied effectively for simulations of atmospheric transport processes. At the beginning of the paper, we introduce simple mathematical transformations in order to demonstrate how complex topological structures are created by mixing processes. These idealistic flow systems are essential to explain transport properties of much more complex three-dimensional geophysical flows. An example of the application of the kinematics of mixing to the analysis of tracer transport on a planetary scale is presented in the following sections. The complex filamentary structures simulated in the numerical experiment are evaluated using some commonly applied statistical measures in order to compare the results with the data published in the literature. The results of the experiment are also analysed with the help of simple conceptual models of fluid filaments. The microstructure of the tracer distribution introduced in the paper is essential to increase our understanding of atmospheric transport and to develop more realistic parameterizations of small-scale mixing. The presented results could also be used to improve calculations of the coupling between microphysical processes and tracer mixing.     

不同泥源对厌氧氨氧化反应器启动的影响

采用2套上流式生物膜反应器,分别接种少量厌氧氨氧化污泥和大量硝化污泥,考察其对厌氧氨氧化反应器启动的影响。污泥接种入反应器后,测得接种厌氧氨氧化污泥的反应器(R1)内MLSS为0.22 g/L,另一个反应器(R2)MLSS为2.7 g/L。与直接接种厌氧氨氧化污泥相比,R1经过72 d的运行才显现出厌氧氨氧化特性。经过114 d的培养,前者氮去除速率由0.23 kg/(m3.d)提升到5.29 kg/(m3.d),总氮去除率大于89%;R2的氮去除速率由0.01 kg/(m3.d)提升到1.1 kg/(m3.d),总氮去除率大于84.6%。说明普通污泥启动需要一个较长的筛选过程,直接接种少量的厌氧氨氧化污泥比接种普通的污泥能够更快启动厌氧氨氧化反应器。     

Evaluation of the presence of drugs of abuse in tap waters

A total of seventy samples of drinking water were tested for non-controlled and illicit drugs. Of these, 43 were from Spanish cities, 15 from seven other European countries, three from Japan and nine from seven different Latin American countries. The most frequently detected compounds were caffeine, nicotine, cotinine, cocaine and its metabolite benzoylecgonine, methadone and its metabolite EDDP. The mean concentrations of non-controlled drugs were: for caffeine 50 and 19 ng L⁻¹, in Spanish and worldwide drinking water respectively and for nicotine 13 and 19 ng L⁻¹. Illicit drugs were sparsely present and usually at ultratrace level (<1 ng L⁻¹). For example, cocaine has mean values of 0.4 (Spain) and 0.3 ng L⁻¹ (worldwide), whereas for benzoylecgonine, these mean values were 0.4 and 1.8 ng L⁻¹, respectively. Higher concentrations of benzoylecgonine were found in Latin American samples (up to 15 ng L⁻¹). No opiates were identified in any sample but the presence of methadone and EDDP was frequently detected. Total mean values for EDDP were 0.4 ng L⁻¹ (Spain) and 0.3 ng L⁻¹ (worldwide). Very few samples tested positive for amphetamines, in line with the reactivity of chlorine with these compounds. No cannabinoids, LSD, ketamine, fentanyl and PCP were detected.     

Mechanisms of biodegradation of dibenzoate plasticizers

Biodegradation mechanisms were elucidated for three dibenzoate plasticizers: diethylene glycol dibenzoate (D(EG)DB), dipropylene glycol dibenzoate (D(PG)DB), both of which are commercially available, and 1,6-hexanediol dibenzoate, a potential green plasticizer. Degradation studies were done using Rhodococcus rhodochrous in the presence of pure alkanes as a co-substrate. As expected, the first degradation step for all of these systems was the hydrolysis of one ester bond with the release of benzoic acid and a monoester. Subsequent biodegradation of the monobenzoates of diethylene glycol (D(EG)MB) and dipropylene glycol (D(PG)MB) was very slow, leading to significant accumulation of these monoesters. In contrast, 1,6-hexanediol monobenzoate was quickly degraded and characterization of the metabolites indicated that the biodegradation proceeded by way of the oxidation of the alcohol group to generate 6-(benzoyloxy) hexanoic acid followed by β-oxidation steps. This pathway was blocked for D(EG)MB and D(PG)MB by the presence of an ether function.The use of a pure hydrocarbon as a co-substrate resulted in the formation of another class of metabolites; namely the esters of the alcohols formed by the oxidation of the alkanes and the benzoic acid released by hydrolysis of the original diesters. These metabolites were biodegraded without the accumulation of any intermediates.     

混凝试验搅拌器的研制

影响混凝效果的因素众多,混凝沉淀烧杯试验是进行水的混合、絮凝、沉淀工艺研究、设计和生产指导的最有效方法之一,阐述了智能型混凝试验搅拌器的设计原理和技术性能.     

生物质快速热裂解主要参数对生物油产率的影响

以松木木屑为原料,在自制的小型流化床上,开展了生物质热裂解温度、生物质粒径和进料速率对生物油产率的影响实验研究.结果表明,在热裂解温度分别为450、475、500、525和550℃条件下,当热裂解温度为500℃时,生物油产率最高,平均产率达到53.33%（质量百分比）.反应温度越高,炭产量越低,不可冷凝气体产量越高,气体发热值越高;粒径＜1 mm的生物质其粒径对生物油产率影响不大;生物质进料速率增加时,生物油产率增加.本研究为生物能的利用提供了新的途径.     

生物质快速热裂解主要参数对生物油产率的影响

以松木木屑为原料,在自制的小型流化床上,开展了生物质热裂解温度、生物质粒径和进料速率对生物油产率的影响实验研究.结果表明,在热裂解温度分别为450、475、500、525和550℃条件下,当热裂解温度为500℃时,生物油产率最高,平均产率达到53.33%(质量百分比).反应温度越高,炭产量越低,不可冷凝气体产量越高,气体发热值越高;粒径＜1 mm的生物质其粒径对生物油产率影响不大;生物质进料速率增加时,生物油产率增加.本研究为生物能的利用提供了新的途径.     

Visualisation of the complexity of EUSES

The interdependencies of parameters applied in the models of EUSES are visualised in a directed connectivity graph. The parameters (inputs, defaults, state variables, outputs) are represented by boxes (nodes) and their relations by lines (edges). The visualisation, on the one hand, clarifies the complexity of the models in EUSES and, on the other hand, creates an overview and transparency. The parameters’ relations to each other can be recognised faster, and the models can be better understood. The complexity was quantified by the number (variety), kind (substance parameter, physico-chemical parameter, concentration, other parameters), and depth (dimension) of the parameter and the number of relations (connectivity). The variety of EUSES (without the modelsSimple Treat andSimple Box whose interior structure is not documented and without the effect and risk characterisation) amounts to 466, the connectivity to 961, and the maximal dimension is 21.