双波长标准加入法同时测定水中硝酸盐和亚硝酸盐

本文应用双波长标准加入法同时测定了硝酸盐和亚硝酸盐，在研究硝酸盐和亚硝酸盐紫外光谱的基础上，精确选择亚硝酸盐等吸收点波长２０２．５ｎｍ，２１６．５ｎｍ为测定波长。亚硝酸盐含量回归方程经推导得Ｃ＝－３．８４１＋１５６．６Ａ，相关系Ｒ＝１．０００。将该法用于合成样品及实际水样分析，所得结果较满意。     

酸化—吹气—吸收法测定水及废水中的硫化物

本文设计了硫化物测定的酸化－吹气－吸收装置，验证了装置对硫化的回收效果，对硫化物标准溶液的配制及其稳定性进行了研究，对分析条件进行了最佳选择，建立了亚甲基监光度法测定硫化物的分析方法，并对实际样品进行了测定。本方法的检出限为０．００５ｍｇＳ＾２－／ｌ，线性范围为０．００５－０．７００ｍｇＳ＾２－／ｌ，可应用于水和废水样品中微量硫化物的测定。     

快速PFU微型生物群落毒性试验法对铜、铅、砷联合毒性的研究

采用快速PFU微型生物群落毒性试验法对铜、铅、砷的联合毒性进行了研究 ,并用相加指数法评价其联合效应 .结果表明 ,Cu(Ⅱ )与Pb (Ⅱ ) ,Cu(Ⅱ )与As(Ⅴ )的联合毒性为协同作用 ;Pb(Ⅱ )与As(Ⅴ )的联合毒性为相加作用     

Bayesian analysis under ordered functions of parameters

Ordered parameter problems arise in a wide variety of real world situations and are dealt with extensively in the literature. Traditional frequentist methods for dealing with these problems are rather complicated theoretically, especially when sample sizes are small. Bayesian methods are not widely used because high dimensional numerical integration is often required. However, Markov chain Monte Carlo methods provide alternatives to such numerical integration and also deal with ordered parameter problems in a straightforward manner. Little is known about the situation where functions of parameters are ordered. Such problems may seem to be of little practical concern initially, but one can readily see their importance in situations where ordering is placed on the means and variances of several normal or Gamma populations. For the Gamma distribution we will present real examples where we will analyze monthly precipitation data from San Francisco, California and Oakland Mills, Iowa. For the San Francisco data we will simultaneously order both monthly precipitation means and variances. For the Iowa data we will place ordering on seasonal average while still estimating monthly means. Our results show that we would obtain sharper, more accurate inference when order restrictions are employed.     

Neighborhood Level Spatial Analysis of the Relationship Between Alcohol Outlet Density and Criminal Violence

Misuse of alcohol is a significant public health problem, potentially resulting in unintentional injuries, motor vehicle crashes, drownings, and, perhaps of greatest concern, serious acts of violence, including assaults, rapes, suicides, and homicides. Although previous research establishes a link between alcohol consumption increased levels of violence, studies relating the density of alcohol outlets (e.g., restaurants, bars, liquor stores) and the likelihood of violent crime have been less common. In this paper we test for such a relationship at the small area level, using data from 79 neighborhoods in the city of Minneapolis, Minnesota. We adopt a fully Bayesian point of view using Markov chain Monte Carlo (MCMC) computational methods as available in the popular and freely available WinBUGS language. Our models control for important covariates (e.g., neighborhood racial heterogeneity, age heterogeneity) and also account for spatial association in unexplained variability using conditionally autoregressive (CAR) random effects. Our results indicate a significant positive relationship between alcohol outlet density and violent crime, while also permitting easy mapping of neighborhood-level predicted and residual values, the former useful for intervention in the most at-risk neighborhoods and the latter potentially useful in identifying covariates still missing from the fixed effects portion of the model.     

Cluster detection using Bayes factors from overparameterized cluster models

In this paper, we consider the use of a partition model to estimate regional disease rates and to detect spatial clusters. Formal inference regarding the number of partitions (or clusters) can be obtained with a reversible jump Markov chain Monte Carlo algorithm. As an alternative, we consider the ability of models with a fixed, but overly large, number of partitions to estimate regional disease rates and to provide informal inferences about the number and locations of clusters using local Bayes factors. We illustrate and compare these two approaches using data on leukemia incidence in upstate New York and data on breast cancer incidence in Wisconsin.     

浅丘河道生态需水量计算方法对比研究——以鄂北地区水河为例

适宜的生态需水量是保障河道生态系统健康的重要因素,合理地计算生态需水量对河道生态系统评估具有现实意义。以鄂北地区典型浅丘河道——水河为例,基于Qp法(不同频率最枯月平均值法)、频率曲线法、最小月平均流量法、Tennant法及生物习性法5种方法的生态流量计算结果,探讨了各方法计算结果的合理性与适用性。结果表明:由于上下游河道水文条件差异性,上游断面采用生物习性法能较好地拟合河道水文节律变化和水质波动;同理,下游断面采用频率曲线法更加匹配下游河道水文、水质情况。因此,在河道上、下游断面分别采用生物习性法、频率曲线法计算得到适宜生态需水量为0.21 m^3/s、2.02 m^3/s。     

河流营养物参照状态的建立方法研究进展

建立营养物参照状态是河流水污染控制的关键问题之一。系统论述了参照状态的各种内涵,重点分析了国外建立河流营养物参照状态的各种方法及优缺点,并分析了其在中国的适用性。最后,提出了河流营养物参照状态的进一步研究的重点。参照状态根据允许人类活动影响的程度可有多种含义:最小干扰状态、历史状态、最少干扰状态和最佳可达成状态。其中,最少干扰状态和最佳可达成状态在现实管理中具有一定程度的可操作性。参照河流百分比法是建立营养物参照状态的首选方法,但中国水环境污染形势严峻,参照点变得越来越少。当参照点不存在时,一般河流百分比法是参照河流百分比法的替代方法,然而一般河流百分比法和参照河流百分比法的匹配性关系并不完全保持一致。由于栖息地退化等因素对生物完整性的影响程度可能比营养物浓度更大,生物响应法在实际应用中是非常困难的。流域模型法虽然有众多优点,但是数据要求较高,并且常用流域模型的机理与中国有较大差距,在中国应用的结果具有较大的不确定性。综合考虑中国水环境污染现状和数据要求,以多元线性回归模型为代表的简易模型方法在中国应有最大的适用性。然而,环境因素与营养物质间的关系往往都是非线性的,今后应着重研究建立河流营养物参照状态的多元非线性回归模型方法。此外,还应加强季风河流营养物参照状态的季节性差异与年际差异研究,并在全国层面上根据自然因素划分适当规模的生态区,分区确定各生态区的河流营养物参照状态。     

南京地区农业资源的综合评价研究

客观、准确地评价地区农业资源,对于农业资源的开发和利用具有重要意义。本文从系统论观点出发,将地区农业资源分成自然资源和社会资源,在能够较好地反映系统结构特征、不同样点差异及满足易于收集、便于数量表示和定量处理等基本要求的基础上,选择了若干评价指标。利用综合指数法、区位商法等评价方法,对南京地区的主要农业资源（土地资源、气候资源与社会资源）进行了定量分析,并在此基础上,利用资源优势度分析法进行了综合评价。结果表明,南部小区的农业资源具有整体优势,南部和中部的资源利用较为合理,北部小区则具有较为丰富的后备资源。最后,根据各地资源要素的不同组合,简要给出了较适宜的开发途径,为该地农业资源的进一步开发与利用提供了依据。     

油田开发项目中大气环境影响预测方法研究

针对油田开发过程中大气污染源点多面广的特点,选用适当的大气环境预测方法已成为问题关键,使用网格处理,分别计算点源（高斯模式）和面源（Ｈ－Ｇ模式）的污染贡献量,得到预测结果,并佐以百色油田的应用实例,得出：多源扩散模式（Ｈ－Ｇ模式）可以反映油田开发多源污染的叠加效果;Ｈ－Ｇ模式计算简便,要求参数少且容易获得,与复杂模式的计算结果相一致,能满足油田开发项目大气环境影响评价的要求。