Assessing Spatial, Temporal, and Analytical Variation of Groundwater Chemistry in a Large Nuclear Complex, USA

Statistical analyses were applied at the Hanford Site, USA, to assess groundwater contamination problems that included (1) determining local backgrounds to ascertain whether a facility is affecting the groundwater quality and (2) determining a ‘pre-Hanford' groundwater background to allow formulation of background-based cleanup standards. The primary purpose of this paper is to extend the random effects models for (1) assessing the spatial, temporal, and analytical variability of groundwater background measurements; (2) demonstrating that the usual variance estimate s ², which ignores the variance components, is a biased estimator; (3) providing formulas for calculating the amount of bias; and (4) recommending monitoring strategies to reduce the uncertainty in estimating the average background concentrations. A case study is provided. Results indicate that (1) without considering spatial and temporal variability, there is a high probability of false positives, resulting in unnecessary remediation and/or monitoring expenses; (2) the most effective way to reduce the uncertainty in estimating the average background, and enhance the power of the statistical tests in general, is to increase the number of background wells; and (3) background for a specific constituent should be considered as a statistical distribution, not as a single value or threshold. The methods and the related analysis of variance tables discussed in this paper can be used as diagnostic tools in documenting the extent of inherent spatial and/or temporal variation and to help select an appropriate statistical method for testing purposes.     

A Variance Estimator for Constrained Estimates of Change in Relative Categorical Frequencies

Consistent estimators of change and state becomes an issue when sample data come from a mix of permanent and temporary observation units. A joint maximum likelihood estimator of state and change creates estimates of state that depend on antecedent viz. posterior survey results and may differ from estimates of state derived from a single-date analysis of the sample data. A constrained estimator of change in relative categorical frequencies that eliminates this potential inconsistency is proposed and a model based estimator of their sampling variance is developed. The performance of the constrained estimator is quantified against six criteria and a joint maximum likelihood estimator in simulated sampling from 15 populations with three combinations of permanent and temporary samples, four to six categorical class attributes, and constant size between sampling dates. Bias of the constrained estimators was negligible but larger than for joint maximum likelihood estimators. Mean absolute deviations and variances of constrained estimators were generally at par with the joint estimators. Constrained estimators of root mean square errors and achieved coverage of nominal confidence intervals of constrained estimators were occasionally better. A generalized variance function for the constrained estimates of change is provided as a computational shortcut.     

The Variability of Estimates of Variance, and Its Effect on Power Analysis in Monitoring Design

Power analysis can be a valuable aid in the design of monitoringprograms. It requires an estimate of variance, which may come from a pilot study or an existing study in a similar habitat. For marine benthic infauna, natural variation in abundances canbe considerable, raising the question of reliability of varianceestimates. We used two existing monitoring programs to generatemultiple estimates of variance. These estimates were found to differ from nominated best estimates by 50% or more in 43% of cases, in turn leading to under or over-estimation of samplesize in the design of a notional monitoring program. The twostudies, from the same general area, using the same samplingmethods and spanning a similar time scale, gave estimatesvarying by more than an order of magnitude for 25% of taxa.We suggest that pilot studies for ecological monitoring programsof marine infauna should include at least two sampling times.     

红壤中结合态磷在酸化条件下的变化及其相互关系

以浙江沿海地区的红壤为研究对象，通过浸滤过程，研究了在酸化条件下，红壤中可溶笥结合态磷的变化和它们之间的相关关系，结果显示，红壤中可溶性Fe-P比Ca－P、Al－P对酸度的变化更为敏感；当红壤中可溶性磷的原始含量较高时，随酸度的增强从固相中释出的趋势更明显；在酸化过程中、红壤中不同可溶性结合态磷之间呈现出不同的相关关系，这归因子它们对酸化敏感性的差异。     

1420Al-Li合金特深模锻件偏心问题分析及对策

对 14 2 0Al Li合金特深模锻件在实际生产 (反挤压 )过程中所产生的偏心问题进行了分析 ,分析表明 ,在上下的方向上 ,润滑不均将使冲头产生弯曲变形和使挤压筒上抬 ,致使锻件产生明显的偏心 ;在左右方向上 ,冲头的轴线相对于挤压筒轴线左偏 ,是产生偏心的主要原因。文中还提出了纠偏的措施。     

Comparative analysis of data reduction techniques for questionnaire validation using self-reported driver behaviors

Introduction: Exploratory data reduction techniques, such as Factor Analysis (FA) and Principal Component Analysis (PCA), are widely used in questionnaire validation with ordinal data, such as Likert Scale data, even though both techniques are indicated to metric measures. In this context, this study presents an e-survey, conducted to obtain self-reported behaviors between Brazilian drivers (N = 1,354, 55.2% of males) and Portuguese drivers (N = 348, 46.6% of males) based on 20 items from the Driver Behavior Questionnaire (DBQ) on a five-point Likert Scale. This paper aimed to examine DBQ validation using FA and PCA compared to Categorical Principal Component Analysis (CATPCA) which is more indicative to use with Likert Scale data. Results: The results from all techniques confirmed the most replicated factor structure of DBQ, distinguishing behaviors as errors, ordinary violations, and aggressive violation. However, after Varimax rotation, CATPCA explained 11% more variance compared to FA and 2% more than PCA. We identified cross-loadings among the component of the techniques. An item changed its dimension in the CATPCA results but did not change the structural interpretability. Individual scores from dimension 1 of CATPCA were significantly different from FA and PCA. Individual scores from factor 1 of CATPCA were significantly different from FA and PCA. Practical applications: The CATPCA seems to be more advantageous in order to represent the original data and considering data constrains. In addition to finding an interpretable factorial structure, the representation of the original data is regarded as relevant since the factor scores could be used for crash prediction in future analyses.     

Uncertainty characterization for emergy values

While statistical estimation of uncertainty has not typically accompanied published emergy values, as with any other quantitative model, uncertainty is embedded in these values, and lack of uncertainty characterization makes their accuracy not only opaque, it also prevents the use of emergy values in statistical tests of hypotheses. This paper first attempts to describe sources of uncertainty in unit emergy values (UEVs) and presents a framework for estimating this uncertainty with analytical and stochastic models, with model choices dependent upon on how the UEV is calculated and what kind of uncertainties are quantified. The analytical model can incorporate a broader spectrum of uncertainty types than the stochastic model, including model and scenario uncertainty, which may be significant in emergy models, but is only appropriate for the most basic of emergy calculations. Although less comprehensive in its incorporation of uncertainty, the proposed stochastic method is suitable for all types of UEVs. The distributions of unit emergy values approximate the lognormal distribution with variations depending on the types of uncertainty quantified as well as the way the UEVs are calculated. While both methods of estimating uncertainty in UEVs have their limitations in their presented stage of development, this paper provides methods for incorporating uncertainty into emergy, and demonstrates how this can be depicted and propagated so that it can be used in future emergy analyses and permit emergy to be more readily incorporated into other methods of environmental assessment, such as LCA.     

京杭大运河苏州高新区段水质污染状况研究

以2005—2010年京杭大运河苏州高新区段水质监测数据为基础,运用内梅罗综合污染指数法以及采取方差分析对京杭大运河苏州高新区段水质的主要污染因子及其变化趋势进行了研究,并对京杭大运河水质污染状况进行了综合评价。结果表明:京杭大运河苏州高新区段主要污染物为氨氮、总磷;氨氮浓度在2006—2010年间虽有明显下降,但仍超过《地表水环境质量标准》(GB3838—2002)IV类水质要求,为劣V类水,总磷亦有明显下降,但在2008—2010年3年间其浓度略有波动,在IV类和V类水质之间浮动;2005—2008年间其水质处于污染状态,2009—2010年水质较好,为轻污染。该研究结果可为苏州高新区河流水环境治理提供科学依据。     

基于REOF方法的辽宁气候舒适度区域特征分析

基于辽宁省50个气象站1964-2008年的气象资料,采用适应东北地区的人体舒适度计算公式及分级标准,得出辽宁省近45年历年人体各舒适度级别日数,使用旋转经验正交分解法(REOF),对辽宁省气候舒适度进行区域划分,并分析了各区域气候舒适度的空间分布特征和变化趋势.结果表明:(1)根据前4个旋转倚载向量场高载荷区分布,将...     

北京地区冬夏季持续性雾-霾发生的环境气象条件对比分析

在北京地区,除冬季供暖期外盛夏也是雾-霾天气的高发季节,与我国南方不同.使用微波辐射仪、风廓线和常规气象探测资料、NCEP再分析资料以及大气成分观测结果,通过对比分析揭示了冬、夏季持续6 d的2个雾-霾过程形成和维持机制的异同.冬季雾-霾过程出现在高空西北气流、低层多短波活动的背景下,其形成和维持的主要机制是边界层内始终有逆温层、地面弱风场、底层湿度逐渐增大.逆温层昼高夜低、湿度昼小夜大是影响PM2.5质量浓度和能见度日变化的重要环境因子.在雾-霾天气持续期间地面弱风场能够维持主要源于冷空气势力弱、常不能影响到地面.此外,入夜后地面迅速辐射降温、边界层上层有暖平流以及空气过山后下沉增温在逆温层的形成中起了关键作用.然而,对于夏季持续性雾-霾天气,气溶胶区域输送、环境大气保持对流性稳定、空气的高饱和度是其发生的重要条件.在副热带高压长时间控制下对流层低层盛行偏南风,北京的PM2.5质量浓度随着偏南风风速增大升高.对流层底层系统性偏南风与北京附近的山谷风共同构成了从北京以南气溶胶累积地向北输送的机制.夏季雾-霾过程低层没有逆温,但是北京上空一直维持超过200 J·kG-1的对流抑制能量,它同样限制了污染物的垂直扩散.夏季自由对流高度也存在昼夜变化,其对PM2.5浓度和能见度的作用与逆温层高度升降相同.因此,冬、夏个例分别代表了2种不同类型的持续性雾-霾过程,导致差异的根本原因在于大气环流型.