部分取代苯类在江水中的生物降解与结构相关性研究

测定了２７种取代苯类化合物在松花江江水中的生物降解性．采用量子化学ＭＯＰＡＣ６．０－ＡＭ１法计算了化合物的分子量(ＭＷ)、生成热(Ｈｆ)、分子总表面积(ＴＳＡ)及最高占有轨道能(ＥＨＯＭＯ),结合辛醇/水分配系数ｌｇｐ及酸解离常数ｐＫａ对其中２２种化合物的ＢＯＤ值进行多元线性回归分析,得到如下模型:ＢＯＤ＝１０５．７３－０．４３９ＭＷ－０．０７６Ｈｆ－６．６６０ｌｇＰｎ＝２２,Ｒ２＝０．８２１,ＳＥ＝８．２５０,Ｆ＝２７．５６,Ｐ＝０．０００应用所得模型对其余５个化合物的生物降解性进行了预测．只有一个化合物的相对预测误差大于２０%,为２０．８%．平均预测误差为１２．４%．     

环境因素对原生动物群落特征的影响

1999年12月至2000年11月,对华中科技大学华瑜池的原生动物群落进行了研究,共检出原生动物125种,其中植鞭毛虫19种,动鞭毛虫28种,纤毛虫64种,肉足虫14种,对原生动物群落结构和功能的研究表明：1）自然条件下,PFU原生动物群落的种类组成数及原生动物群落的群集速度相对稳定;2）自然条件下,PFU原生动物群落结构和功能不受季节变化的影响;3）当PFU原和动物群落受到外界胁迫时,不管这种胁迫来自物化因素或是生物因素,其群落结构和功能都会发生破坏性变化;4）用PFU法进行原生动物群落生态学和毒理学研究,所得的结构参数及功能参数能反映客观状况,具有环境现实意义。     

热解焚烧技术处置医疗废物的影响因素与工况控制研究

针对热解焚烧技术处置医疗废物的特点,分析处置工艺运行参数对稳定工况的影响规律,确定医疗废物在热解焚烧技术炉内稳定焚烧的工艺参数,指出送风量与气化炉、燃烧炉的温度关系是焚烧系统控制的关键。通过对某型焚烧炉的测试,得到了送风量与气化炉和燃烧炉的温度关系曲线。测试结果表明,实时动态调控气化炉和燃烧炉的送风量,能够实现医疗废物的稳定焚烧。     

对地级市空气自动监测多参数站建设的思考

阐述了地级市空气自动监测多参数站(超级站)建设的必要性,提出了统筹考虑、分期实施与突出重点、兼顾一般的建设思路,介绍了站房选址原则。指出超级站建设应以常规监测、霾监测、光化学烟雾监测、空间立体监测和源解析监测为目标,实施质量控制和质量保证手段,设置数据采集和显示平台,满足对大气复合污染的监测需求。     

遗传和模拟退火算法在水质模型参数确定中的应用简介

水质模型参数的确定是构建水质模型的基础。相对于传统优化方法,现代优化算法的优势日趋明显。本文在基于现代优化算法的水质模型参数确定研究背景下,介绍了具有代表性的遗传算法和模拟退火算法,并对该两种算法的应用现状进行综述,旨在推进该领域的进一步探索。     

PARAMETER ESTIMATION OF THE NONLINEAR MUSKINGUM MODEL USING HARMONY SEARCH1

ABSTRACT: A newly developed heuristic algorithm, Harmony Search, is applied to the parameter estimation problem of the nonlinear Muskingum model. Harmony Search found better values of parameters in the nonlinear Muskingum model than five other methods including another heuristic method, genetic algorithm, in terms of SSQ (the sum of the square of the deviations between the observed and routed outflows), SAD (the sum of the absolute value of the deviations between the observed and routed outflows), DPO (deviations of peak of routed and actual flows), and DPOT (deviations of peak time of routed and actual outflow). Harmony Search also has the advantage that it does not require the process of assuming the initial values of design parameters. The sensitivity analysis of Harmony Memory Considering Rate showed that relatively large values of Harmony Memory Considering Rate makes the Harmony Search converge to a better solution.     

Hematology and Some Biochemical Parameters of Wild Rodents in Pistachio Gardens of Kerman Province, Southeast Iran

Wild rodents were collected using live snap traps in pistachio gardens of Kerman Province, Southeast Iran from 2007 to 2009, then some physiological parameters of them were measured. The samples were identified as follow: Nesokia indica, Meriones persicus, Meriones lybicus and Tatera indica. Blood samples were obtained from the heart, then the blood parameters (glucose, cholesterol, triglyceride, total protein, HDL, red and white blood cell number) in wild species of rodents and laboratory rat were compared. The results showed that there were no significant differences in serum glucose, triglyceride, HDL and total protein levels among different experimental groups. The concentration of cholesterol in T. indica was more than that in N. indica (P < 0.01). The total numbers of red blood cells also showed significant difference between wild garden rodent species and laboratory rat (P < 0.01), while the numbers of white blood cells showed no significant difference.     

A NEW LOOK AT FLOOD RISK DETERMINATION1

ABSTRACT: The probability distributions of annual peak flows used in flood risk analysis quantify the risk that a design flood will be exceeded. But the parameters of these distributions are themselves to a degree uncertain and this uncertainty increases the risk that the flood protection provided will in fact prove to be inadequate. The increase in flood risk due to parameter uncertainty is small when a fairly long record of data is available and the annual flood peaks are serially independent, which is the standard assumption in flood frequency analysis. But standard tests for serial independence are insensitive to the type of grouping of high and low values in a time series, which is measured by the Hurst coefficient. This grouping increases the parameter uncertainty considerably. A study of 49 annual peak flow series for Canadian rivers shows that many have a high Hurst coefficient. The corresponding increase in flood risk due to parameter uncertainty is shown to be substantial even for rivers with a long record, and therefore should not be neglected. The paper presents a method of rationally combining parameter uncertainty due to serial correlation, and the stochastic variability of peak flows in a single risk assessment. In addition, a relatively simple time series model that is capable of reproducing the observed serial correlation of flood peaks is presented.     

GEOLOGIC INFERENCE FROM “FLOW NET” TRANSMISSIVITY DETERMINATION: THREE CASE STUDIES1

A graphical inverse method for determining the regional transmissivity distribution was applied to three field problems. The study areas were the Hanford Site, Washington; the Rocky Mountain Arsenal, Colorado; and the Nevada Test Site, Nevada. This method can aid in flow system conceptualization by revealing the location of bedrock controls for groundwater flow. It is a valuable tool for aiding the hydrogeologist in asking questions about the nature of trends in the pattern of transmissivity values. Quantitative estimates of regional transmissivities can be used as starting points for further parameter refinement. Sensitivity analysis using Monte Carlo simulation shows that quantitative estimates of transmissivity can be obtained when measurement error in the hydraulic head does not cause a large error in the hydraulic gradient.     

PARAMETRIC ESTIMATION OF COVARIANCES OF REGIONALIZED VARIABLES1

ABSTRACT: The usefulness of stochastic models in describing the spatial variability of hydrogeologic quantities, such as permeability, storativity, piezometric head, seepage velocity, and solute concentrations is now widely recognized. In practice, these quantities are represented as the sum of a well-structured component, or drift, and a more erratic fluctuation component which is described statistically through its covariance function. This paper reviews some of the most recent and most promising methods for the estimation of parameters of these covariances from existing data. They are maximum likelihood, restricted maximum likelihood, minimum-variance unbiased quadratic estimation, and minimum-norm (weighted least squares) estimation. The applicability of such methods to conditional and unconditional probability problems is discussed.