Using a novel adsorbent macrocyclic compound cucurbit[8]uril for Pb removal from aqueous solution

In this study, cucurbit[8]uril (CB[8]) was utilized as a kind of new adsorbent to remove Pb^2 + ions from aqueous solution. With the solution pH increased from 2 to 6, the removal efficiency of adsorption increased from 55.6% to 74.5%correspondingly. The uptake of Pb^2 + increased rapidly in the initial 30 min, and then the adsorption rate became slower. The Pseudo-second order model could be used to interpret the adsorption kinetics satisfactorily; and the rate determining step in Pb^2 + adsorption onto CB[8] was the external mass transfer step. Equilibrium isotherm study reveals that the Langmuir model gave a better fitting result than Freundlich model. The maximum adsorption capacity calculated by the Langmuir model was 152.67 mg/g for 298 K, 149.70 mg/g for 313 K and 136.42 mg/g for 323 K, respectively. The adsorption is a spontaneous process of exothermic nature. The effect of the adsorbent dosage and the influences of solution pH and co-existing cations were also investigated. The CB[8] was synthesized and characterized by ¹H NMR, IR, ESI-MS spectra, SEM-EDAX, Zeta-potential and BET-analysis. The adsorption mechanism was due to the coordination between CB[8] molecule and Pb^2 + ions.     

重大自然灾害后遗体处置应急预案研究

重大自然灾害发生后一般都会伴随着大量人员的遇难,及时妥善处置灾后众多遇难者遗体,是许多国家面临的棘手问题。借鉴我国唐山7.8级地震和汶川8.0级地震中遗体应急处置的经验与教训,从遗体的搜集、存放、运输、消毒、防腐、保存、火化、掩埋等方面,探索遗体处理应急预案的程序与内容,从而提高政府应对重大自然灾害后大量遗体的应急处置能力,全面保障灾区群众的身心健康。     

零价铁PRB技术在地下水原位修复中的研究进展

PRB(可渗透反应墙)是地下水治理中新型的原位修复技术,具有成本低、处理效果好、对环境干扰小等优点,已逐渐应用到实际. 原位修复技术中PRB根据结构的不同可分为单处理系统PRB和多单元处理系统PRB,单处理系统PRB适用于单一污染物、污染浓度较低、污染羽规模较小的场地,多单元系统用于污染场地较复杂、污染种类较多的场地. 零价铁PRB去除地下水中无机污染物及有机组分的反应机理主要是氧化还原反应和还原性脱卤反应. 实际场地PRB的运行中存在的主要问题是零价铁钝化及PRB堵塞,现阶段的解决方法主要包括超声、电化学等,但为了提高PRB技术的实用性,铁材料的解钝化技术、实际场地PRB的设计与安装、PRB体系的长期运行及服务期满后的处置均需进一步的研究探索.      

纳米零价铁对溶液中PCB77的降解及其影响因素

设计了以溶液初始pH值、3,3’,4,4’-四氯联苯(PCB77)初始浓度、纳米零价铁(Fe0)投加量、纳米零价硅(Si0)投加量、腐殖酸和环糊精浓度为影响因素的正交试验,研究纳米Fe0降解PCB77时各因素对反应体系中PCB77残留率、氢离子浓度及氧化还原电位变化的影响及其相互关系。结果表明,在溶液初始pH值为4.5,初始ρ(PCB77)为1 mg.L-1,纳米Fe0投加量为10 g.L-1,纳米Si0投加量为0,ρ(腐殖酸)为0.25 g.L-1,ρ(环糊精)为1 g.L-1时,反应2 h后,PCB77残留率最低,为35.2%。溶液初始pH值对反应体系中PCB77的残留率影响最大,纳米Fe0投加量次之;溶液初始pH值对反应体系中氢离子浓度变化影响最大,环糊精投加量次之;PCB77初始浓度对反应体系中氧化还原电位变化影响最大,纳米Fe0投加量次之。     

零价纳米铁对大肠杆菌的毒性效应

以大肠杆菌为研究对象,通过检测尺寸为20 nm的零价纳米铁暴露下大肠杆菌形貌、生长曲线和细胞内酶活性的变化,研究了零价纳米铁对大肠杆菌的毒性效应,并探讨了其可能的毒性机制.用透射电镜(TEM)观察零价纳米铁与大肠杆菌(JM109)接触后细胞的形态变化;用0、112、560和1 120 mg·L-1的零价纳米铁染毒大肠杆...     

基于最佳范化能力的BP网络隐节点数反比关系式的环境预测模型

网络结构和样本集复杂性是影响BP网络泛化能力的两个最重要因素.对一个给定的训练样本集,为了构造一个与样本集复杂性相匹配的网络结构,使BP网络具有最佳泛化能力,在分析BP网络的泛化能力（用检测误差E₂表示）与网络结构和样本集复杂性之间关系的基础上,建立了含参数的BP网络检测误差E₂与网络隐节点数H、样本的因子数n、样本数N和样本集的复相关系数R之间的一般关系表达式,并提出了用于定量描述样本集复杂性的"广义"复相关系数R_n的新概念.借助于222个复杂函数的模拟仿真实验,应用免疫进化算法,对表达式中的参数进行优化,得到参数优化后的网络检测误差E₂的定量解析表达式;依据误差理论和灵敏度概念,对优化得到的最小检测误差E₂₀的表达式进行了可靠性论证.在此基础上导出了具有最佳泛化能力的BP网络隐节点数H₀与"广义"复相关系数R_n之间满足的H₀-R_n反比关系式.分别用满足H₀-R_n反比关系式的隐节点数和6个经验公式的隐节点数构造的BP网络用于100个模拟检测函数进行仿真实验,发现前者构造的BP网络具有最佳泛化能力（即最小检测误差）的函数个数达到76个,远远多于后者构造的BP网络具有最佳泛化能力的函数个数;还将二者构造的BP网络用于环境预测的7个具体实例,进行预测效果比较,结果表明,前者预测的相对误差绝对值的平均值和最大值小于或远小于后者的相应值.从而验证了由H₀-R_n反比关系式得出的BP网络隐节点数计算公式的可行性和实用性,为具有最佳泛化能力的BP网络的结构设计指出了新途径.     

用经济手段管理森林防火的尝试

实践证明,在市场经济条件下,运用经济手段管理森林防火工作,是使森林防火工作由单一行政命令的传统模式向经济、法律、行政相结合的新的森防管理模式转变的有效途径。     

Effects of nitrate concentration in interstitial water on the bioremediation of simulated oil-polluted shorelines

Nutrient addition has been proved to be an effective strategy to enhance oil biodegradation in marine shorelines.To determine the optimal range of nutrient concentrations in the bioremediation of oil-polluted beaches,nitrate was added to the simulated shoreline models in the initial concentration of 1,5 and 10 mg/L.Whenever the NO3-N concentration declined to 70% of its original value, additional nutrients were supplemented to maintain a certain range.Results showed adding nutrients increased the oil biodegradation level,the counts of petroleum degrading bacteria(PDB)and heterotrophic bacteria (HB),and the promoted efficiency varied depending on the concentration of nitrate.Oil degradation level in 5 mg/L(NO_3-N)group reached as much as 84.3% accompanied with the consistently highest counts of PDB;while in 1 mg/L group oil removal efficiency was only 35.2%,and the numbers of PDB and HB were relatively low compared to the other groups supplemented with nutrients.Although counts of HB in the 10 mg/L group were remarkable,lower counts of PDB resulted in poorer oil removal efficiency (70.5%) compared to 5 mg/L group.Furthermore,it would need more NO_3-N(0.371 mg)to degrade 1 mg diesel oil in the 10 mg/L group than in the 5 mg/L group(0.197 mg).In conclusion, Nitrate concentration in 5 mg/L is superior to 1 and 10 mg/L in the enhancement of diesel oil biodegradation in simulated shorelines.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.