黄连根茎浸提物对绿藻的毒理作用

黄连根茎和制剂具有抗菌等作用,广泛用于水产养殖,所造成水生态风险需要评估.试验设置总生物碱为0(CK),0.088(T1)、0.44(T2)和1.76 mg·L-1(T3)的黄连根茎浸提液(CRE)4种处理,研究了对斜生栅藻和蛋白核小球藻的毒理作用.结果表明,T1抑制绿藻生长,T2和T3使绿藻生长和繁殖停止;它们均显著降低绿藻叶绿素和蛋白质含量,说明CRE抑制光合作用和蛋白质合成是绿藻生长繁殖速率降低和死亡的直接原因.CRE使氢离子和胞内物质外流,导致藻液p H值显著降低和电导率提高.在T1和T2处理中,绿藻细胞SOD活性先升后降;在T3处理中,SOD活性显著降低.说明在CRE暴露初期,低中浓度的CRE诱导绿藻细胞产生抗性,随暴露时间增长或直接暴露在高浓度的CRE下,抗氧化酶系统被破坏.同样,随着CRE浓度增大,丙二醛含量增加,意味着绿藻细胞膜结构破坏,透性增加.CRE总体上对蛋白核小球藻的危害作用大于斜生栅藻.在水产养殖中,滥用黄连根茎或制剂,以及大规模集约化种植黄连对水体初级生产力具有潜在的生态风险.     

G20峰会期间杭州地区空气质量特征及气象条件分析

利用空气质量和气象要素的监测资料与再分析资料,分析了2016年G20峰会期间(2016年8月10日—9月20日)杭州及周边地区空气质量演变及区域特征,探讨了气象条件对G20峰会期间杭州空气质量的影响.结果表明:G20峰会管控期间,由于机动车排放大幅度降低,杭州NO_2浓度较管控前有所下降,对比周边城市降幅居于首位;而由于不利气象条件的影响,PM_(2.5)、PM_(10)、SO_2、CO和O_3浓度比管控前有不同程度的增长,但增幅相比周边城市较小,说明管控措施对杭州空气质量有一定的改善效果.9月7日管控措施结束后污染反弹现象明显.气象条件对杭州的空气质量有重要影响:在管控前,杭州晴热高温天气有利于O3的生成,偏东风相对洁净,污染传输较少;在管控期,杭州虽受到静稳天气和外来污染传输的影响,但得益于减排应急管控措施的有效实施,NO_2浓度下降幅度最大,其他污染物的增幅也较周边城市偏小;在管控后,气象条件不利于污染物的垂直扩散,受静稳天气和污染源恢复常态的影响,PM_(2.5)、PM_(10)、NO_2、SO_2和CO出现了整个研究时段的最大值,而台风"莫兰蒂"使得杭州PM_(2.5)、PM_(10)和O_3浓度出现了整个研究时段的最低值.     

细水雾灭火剂在商用厨房中的应用研究

商用厨房火灾的最主要原因是油锅的持续高温引发食用油自燃起火,食用油极易复燃的火灾行为大大增加了其扑救难度,通过实验表明,细水雾灭火剂极强的冷却作用能够有效扑救食用油火灾.     

矿山企业清洁生产审核实践及研究

结合清洁生产审核的政策和工作原理,将北京某铁矿公司的生产指标与国家采选行业清洁生产标准进行对比,确定审核目标,通过加权法从技术、环境、经济方面分析比较得出审核方案和审核结论. 对该企业实施清洁生产审核工作所取得的经验和存在问题进行总结和分析,不仅为矿山企业今后的清洁生产审核积累了丰富的实践经验,而且对我国当前正在开展的循环经济试点工作起到了很好的借鉴和推动作用.     

河流型饮用水水源保护区划分比较

比较分析了国内外河流型水源保护区划分的原则、方法和标准,例证了我国不同省份的划分实践。指出,我国各省多采用经验值划分水源保护区范围,部分省份划分方案久未更新,没有充分发挥保护区的作用。提出,应进一步细化水源保护区划分规范指导要求,及时修订省级水源保护区划分方案,并借鉴国外水源保护区划分经验,通过调整水质标准、重视公众参与、利用地理信息系统等方式划分水源保护区,从源头上预防水源污染,降低饮用水公共风险,保障饮用水安全。     

Preparation and Characterization of Xylan Derivatives and Their Blends

Although hemicellulose is found widely in nature, it is currently under-utilized as a raw material for commercial applications. It would be desirable to find new uses for hemicellulose in order to add value to this agro-based material. A common type of hemicellulose is xylan, which is found in a number of wood species and in cotton. In this work we prepared cationic and anionic xylan derivatives and characterized them by ¹³C NMR, FT-IR, size exclusion chromatography (SEC), thermal analysis, and rheology. In particular, the ¹³C NMR spectra of carboxymethyl xylan (CMX) and quaternary ammonium-adducted xylan (QAX) were fully assigned with the help of samples with different degrees of substitution. SEC indicated that the beechwood xylan showed a bimodal molecular weight distribution, but with derivatization the distribution tended to become unimodal. Thermal analysis and rheology studies did not uncover any surprises; the solution of xylan and its derivatives exhibited mostly Newtonian behavior. The blends of CMX and QAX produced a precipitate at almost all ratios, indicating the formation of a polyelectrolyte complex. When cationic and anionic xylan samples were added together to paper, the paper dry strength increased. Thus, the combination of cationic/anionic xylan may be of interest in selected applications.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Toxicity of sediment cores from Yangtze River estuary to zebrafish (<Emphasis Type="Italic">Danio rerio</Emphasis>) embryos

Toxicity evaluation is an important segment in sediment quality monitoring in order to protect aquatic organisms and human health. The purpose of this study is to assess the toxicity of sediments from three sediment cores in Yangtze River Estuary, China, using the zebrafish (Danio rerio) embryo tests. Fertilized zebrafish eggs were exposed to both whole sediments and sediment organic extracts prepared from collected sediments, in order to provide a comprehensive and realistic insight into the bioavailable toxicity potential of the sediments. As end points, development parameters (mortality, hatching rate, and abnormality) in the developing embryos were recorded during the 96-h exposure. The results showed that some samples increased mortality, inhibited the hatching of embryos, and induced morphological abnormalities. The embryonic toxicities presented serrated changes and irregular distribution with depth, which may be related to hydrodynamic effect and unstable environmental input. However, lethal and sub-lethal effects were more significant at the sub-surface sediments (10～40 cm), which indicated that the pollution is more serious in recent decades.     

响应面法优化黄粉虫幼虫处理餐厨垃圾饲养条件的研究

研究了黄粉虫幼虫处理餐厨垃圾的方法.首先在饲养温度、饲料含水量和饲养密度等条件下进行单因素实验,然后,以利用率为指标,运用响应面法优化了黄粉虫幼虫处理餐厨垃圾的饲养条件,结果表明,最佳饲养条件为饲养温度26.7℃、饲料含水量14.5％、饲养密度4.1头/cm2.在此饲养条件下,黄粉虫对餐厨垃圾利用率理论值为38.72％,实际餐厨垃圾利用率为38.88％,相对误差为0.41％,说明利用黄粉虫幼虫处理餐厨垃圾具有较好的效果.