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。     

工业园区环境风险源识别与分级研究

以多年来中国各行业突发环境事故统计数据为基础,选取了对于企业突发环境事件有重大影响的7个因子以及17个指标,采用指标因子分析法对其进行定量,应用层次分析法确定各因子的权重,从而确定企业环境风险水平值。基于"危险物质水平—企业环境风险水平—周边环境受体状况"体系,构建了环境风险源分级矩阵,形成了包括"环境风险源初筛","环境风险源分级"的两步工业园区环境风险源识别与分级方法。该方法提出的工业园区环境风险源识别与分级体系具有科学性和可行性,能为工业园区环境风险管理提供依据。     

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.     

Microbial degradation of poly(3-hydroxybutyrate) and poly(3-hydroxybutyrate-co-3-hydroxyvalerate) in compost

The microbial degradation of tensile test pieces made of poly(3-hydroxybutyrate) [P(3HB)] or copolymers with 10% [P(3HB-co-10%3HV)] and 20% [P(3HB-co-20%3HV)] 3-hydroxyvaleric acid was studied in small household compost heaps. Degradation was measured through loss of weight (surface erosion) and changes in molecular weight and mechanical strength. It was concluded, on the basis of weight loss and loss of mechanical properties, that P(3HB) and P(3HB-co-3HV) plastics were degraded in compost by the action of microorganisms. No decrease inM _w could be detected during the degradation process. The P(3HB-co-20%3HV) copolymer was degraded much faster than the homopolymer and P(3HB-co-10%3HV). One hundred nine microbial strains capable of degrading the polymersin vitro were isolated from the samples used in the biodegradation studies, as well as from two other composts, and identified. They consisted of 61 Gram-negative bacteria (e.g.,Acidovorax facilis), 10 Gram-positive bacteria (mainlyBacillus megaterium), 35Streptomyces strains, and 3 molds.     

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.     

IDENTIFICATION OF AQUIFER DISPERSIVITIES: METHODS OF ANALYSIS AND PARAMETER UNCERTAINTY1

ABSTRACT: This paper presents a method for estimating aquifer dispersivities in solute transport models. Sensitivity equations are derived for the calculation of sensitivity coefficients. A modified Gauss-Newton algorithm is used to perform the least-squares minimization. A statistical procedure is outlined to assess reliability of the estimated parameters. The solute transport model is solved by the upstream weighted, multiple cell balance method which combines the concepts of local mass balance and finite element approximations. A one-dimensional solute transport problem in a vertical column system is first used to illustrate the inverse technique. A second example considers the parameter identification problem for three-dimensional solute transport with a unidirectional steady and uniform flow field. The third example solves the parameter identification problem in a three-dimensional, stream-aquifer, solute transport system with steady state flow. Numerical experiments are conducted to study data requirements for parameter identification.