废水采样位置对污染源监测结果的影响

近年来,我国经济技术快速发展,但是环保问题也越来越突出。工业生产和人们的日常生活都会产生废水,废水采样是对废水源进行监测和管理的重要环节,废水监测的影响因素较多。本文主要分析了废水采样位置对监测结果的精确性造成的影响,以期为相关技术人员提供一定参考。     

一种新型水质自动采样仪的研制

将计算机技术应用于采样仪中,实现人－机对话,同时配以运行可靠,成本较低的水样采集,贮存和转换等部件,实现自动采样,达到智能化的目的。采样仪的控制采用单片机技术,以８０３１芯片作为微处理器,配以外围接口电路和功能键盘,体积小,成本低。采集贮存系统由蠕动泵,电磁铁及配套的机械传动装置,水样贮存盘和容器等组成,结构简单,运行平稳。采样有连续采样和间歇采样２种功能,并可按需要任意调节采样时间,采样周期,切     

Influence of Riffle and Snag Habitat Specific Sampling on Stream Macroinvertebrate Assemblage Measures in Bioassessment

Stream macroinvertebrate communities vary naturally among types of habitats where they are sampled, which affects the results of environmental assessment. We analyzed macroinvertebrates collected from riffle and snag habitats to evaluate influences of habitat-specific sampling on taxon occurrence, assemblage measures, and biotic indices. We found considerably more macroinvertebrate taxa unique to snags (143 taxa) than to riffles (75 taxa), and the numbers of taxa found in both riffles and snags (149 taxa) were similar to that found in snags. About 64% of the 47 macroinvertebrate measures we tested differed significantly between riffles and snags. Eighty percent intercepts of regressions between biotic indices and urban or agricultural land uses differed significantly between riffles and snags. The Hilsenhoff biotic index calculated from snag samples explained 69% of the variance of riffle samples and classified 66% of the sites into the same stream health group as the riffle samples. However, four multimetric indices for snag samples explained less than 50% of the variance of riffle samples and classified less than 50% of the sites into the same health group as the riffle samples. We concluded that macroinvertebrate indices developed for riffle/run habitat should not be used for snag samples to assess stream impairment. We recommend developing an index of biotic integrity specifically for snags and using snags as an alternate sampling substrate for streams that naturally lack riffles.     

Patchy Distribution Fields: Sampling Distance Unit of an Interleaved Survey and Reconstruction Adequacy

A mathematical model was used to examine the effects of choosing various units of sampling distance of an interleaved (two-pass) acoustic survey on the adequacy of reconstructing patchy distribution fields. The model simulates fish or plankton patches (or gaps) of different shapes and spatial orientations, and an interleaved survey by parallel or zigzag transects, along which a unit of sampling distance is set. The efficiency of a survey is determined by the adequacy of a reconstructed field to that originally generated, which is evaluated by calculating their correlations (r). Regarding immovable fields, the experiments conducted indicate that a patchy field can be reconstructed properly (r ² > 0.70) if the distance between transects D < (1.5–2.0)R and the unit of sampling distance d < (1.5– 2.0)R _p. As, for regular surveys d < (1.0–1.5)R _p, it may be concluded that interleaved surveys are more efficient than regular ones because of the factor studied. In regard to movable fields, a comparison of the results of interleaved surveys with those of regular surveys directly indicates that the former may ensure a more adequate field reconstruction than the latter do. This fact confirms the previous conclusion that an interleaved survey is expedient in cases where there is no preference regarding the position of a vessel for further work.     

Estimating upper percentiles of surface water monitoring data with sparse samples

The estimation of upper percentiles of chemical concentrations in surface water systems within sites and regions may be necessary for the assessment of potential risk to ecosystems and human health. Limited sample sizes at monitoring sites often limit the use of direct methods to estimate upper percentiles. In such cases, upper percentiles within regions within a time frame may be estimated by pooling data across sites and years, and then deriving percentile estimates from the pooled dataset. The method uses the observations resulting from either a known probability-sampling design or a sampling design treated like one because its observations come close to matching that of a probability-sample. These observations are then weighted to ensure that estimates are representative of a target population across all the sites within the region and the range of years in the time frame. This method of estimating upper percentiles of annual site concentration profiles is demonstrated using atrazine and validated using the monitoring data from both sparsely sampled and high-frequency water monitoring programs, where point and interval estimates of the 90th, 95th, and 99th pooled population percentiles are provided. This method shows that the pooled data from multiple sparse datasets can be used to provide estimates of near-peak concentrations with greater certainty, which are consistent with those generated by high-frequency sampling monitoring programs.     

一种基于Logistic回归的全损飞行事故分析与预测

运用Logistic回归方法分析全损飞行事故的影响因素,并构建预测模型,然后利用飞行事故案例进行了实证检验。通过对样本数据过离散、空单元、多元共线性和特异值、特殊影响案例的诊断,以及对模型的拟合程度和预测效果的检验,表明所构建的模型比较符合现实情况,而且具有较好的拟合程度和预测效果。模型指出航班类型和机龄因素具有统计学意义,国内航班比国际航班的全损概率要高;机龄越老,全损概率越高。     

Comparison of Three Pebble Count Protocols (EMAP,PIBO, and SFT) in Two Mountain Gravel‐Bed Streams1

Abstract: Although the term ``pebble count'' is in widespread use, there is no standardized methodology used for the field application of this procedure. Each pebble count analysis is the product of several methodological choices, any of which are capable of influencing the final result. Because there are virtually countless variations on pebble count protocols, the question of how their results differ when applied to the same study reach is becoming increasingly important. This study compared three pebble count protocols: the reach‐averaged Environmental Monitoring and Assessment Program (EMAP) protocol named after the EMAP developed by the Environmental Protection Agency, the habitat‐unit specific U.S. Forest Service’s PACFISH/INFISH Biological Opinion (PIBO) Effectiveness Monitoring Program protocol, and a data‐intensive method developed by the authors named Sampling Frame and Template (SFT). When applied to the same study reaches, particle‐size distributions varied among the three pebble count protocols because of differences in sample locations within a stream reach and along a transect, in particle selection, and particle‐size determination. The EMAP protocol yielded considerably finer, and the PIBO protocol considerably coarser distributions than the SFT protocol in the pool‐riffle study streams, suggesting that the data cannot be used interchangeably. Approximately half of the difference was due to sampling at different areas within the study reach (i.e., wetted width, riffles, and bankfull width) and at different locations within a transect. The other half was attributed to using different methods for particle selection from the bed, particle‐size determination, and the use of wide, nonstandard size classes. Most of the differences in sampling outcomes could be eliminated by using simple field tools, by collecting a larger sample size, and by systematically sampling the entire bankfull channel and all geomorphic units within the reach.     

Estimating prevalence using composites

We are interested in estimating the fraction of a population that possesses a certain trait, such as the presence of a chemical contaminant in a lake. A composite sample drawn from a population has the trait in question whenever one or more of the individual samples making up the composite has the trait. Let the true fraction of the population that is contaminated be p. Classical estimators of p, such as the MLE and the jackknife, have been shown to be biased. In this study, we introduce a new shrinking estimator which can be used when doing composite sampling. The properties of this estimator are investigated and compared with those of the MLE and the jackknife.     

Analysis of composite sampling data using the principle of maximum entropy

A new tool is presented based on the principle of maximum entropy for enhanced hot spot detection based on composite sampling with no (or minimal) requirement for composite breakdown. The methodology presented here is easy to implement and facilitates the use of multiple criteria for evaluating attainment of site remediation objectives. The new methodology provides very simple decision rules that can easily be used by non-statisticians and complements the use of composites for control of residual mean concentrations.     

Estimation of the mean in line intercept sampling

Ratio estimation of the parametric mean for a characteristic measured on plants sampled by a line intercept method is presented and evaluated via simulation using different plant dispersion patterns (Poisson, regular cluster, and Poisson cluster), plant width variances, and numbers of lines. The results indicate that on average the estimates are close to the parametric mean under all three dispersion patterns. Given a fixed number of lines, variability of the estimates is similar across dispersion patterns with variability under the Poisson pattern slightly smaller than varia-bility under the cluster patterns. No variance estimates were negative under the Poisson pattern, but some estimates were negative under the cluster patterns for smaller numbers of lines. Variance estimates become closer to zero similarly for all spatial patterns as the number of lines increases. Ratio estimation of the parametric mean in line intercept sampling works better, from the viewpoint of approximate unbiasedness and variability of estimates, under the Poisson pattern with larger numbers of lines than other combinations of spatial patterns, plant width variances and numbers of lines.