True and false positive rates in maximum contaminant level tests

The U.S. Environment Protection Agency (EPA) is promulgating a revised national primary drinking water regulation (NPDWR) which includes a monthly sample size and maximum contaminant level (MCL) for total coliform bacteria in public water systems. No previous quantification has been made of the coliform content that must be present in the sampled water in order for an MCL to be exceeded. This paper presents a method for evaluating the coliform level an MCL will detect with likelihood P.Our approach is to treat an MCL as a decision rule, with Type I (false positive) and Type II (false negative) error rates. The stringency of an MCL is quantified as the mean coliform level in the sampled system that it will detect with likelihood P. MCLs are contrasted on stringency by comparing the mean coliform level each targets for detection, with fixed error rates.Interim rules (NIPDWR), in effect since 1975, are shown to vary widely on the coliform content each targets for detection, that is, on stringency. Yes/no decisions on contamination have not been decided based on mean coliform content. Coliform levels permitted in monitored public water systems have been determined by the particular MCL used for testing. The same coliform level will test positively with one MCL 90 times in 100 yet be guaranteed 95% nondetection by a second MCL.EPA's reasonably safe standard for drinking water is reformulated on our stringency criteria. Its proposed monthly MCL is evaluated on its capability for maintaining this standard. Smaller systems will not provide its users this level of protection under the new rule.In addition, our evaluation of the safe water standard on stringency and the rationale for a monthly MCL require that coliform levels be identically distributed (i.d.) across month and sampled system. Empirical data strongly refute this model and question the utility of a monthly MCL.This work suggests an alternative, single sample MCL, with repeat sampling for verification, which can be configured to provide monitoring to discover mean coliform values at any level, in any size of system, at minimal extra cost.     

Joint versus separate estimation of state and change in category frequencies from repeat stratified two-phase sampling with a fallible classifier

Joint maximum likelihood estimates (JML) of category frequencies and change from repeat stratified two-phase samplingsurveys with a fallible classifier are often seriously biased andhave large root mean square errors when they are obtained for small populations (<5000) with three or more categories and amoderate to small phase II sample size (<1000). JML estimates of state also depend on antecedent or posterior data, a recipe for inconsistency. In these situations, a separate maximum likelihood estimation (SML) of category frequenciesat each survey date appears preferable. SML estimates of net change are obtained as the difference in states. SML standard errors of change are obtained via an estimate of the temporal correlation and variances of state. A bivariate binarylogistic model of change provided the estimate of temporal correlation. SML generally outperformed JMLsignificantly in terms of bias and root mean square errors in eight case studies.     

美国环境监测五大标准分析方法系列特点

着重介绍了美国环保局(EPA)开发的五套环境监测标准分析方法系列:EPA600,EPA500,CLP,EPASW-846,EPA200的要点,并简要评述了其特点,这些代表美国环境科学技术最新成就的方法系列应当为我们参考和借鉴.     

Measurements of stem diameter: implications for individual- and stand-level errors

Stem diameter is one of the most common measurements made to assess the growth of woody vegetation, and the commercial and environmental benefits that it provides (e.g. wood or biomass products, carbon sequestration, landscape remediation). Yet inconsistency in its measurement is a continuing source of error in estimates of stand-scale measures such as basal area, biomass, and volume. Here we assessed errors in stem diameter measurement through repeated measurements of individual trees and shrubs of varying size and form (i.e. single- and multi-stemmed) across a range of contrasting stands, from complex mixed-species plantings to commercial single-species plantations. We compared a standard diameter tape with a Stepped Diameter Gauge (SDG) for time efficiency and measurement error. Measurement errors in diameter were slightly (but significantly) influenced by size and form of the tree or shrub, and stem height at which the measurement was made. Compared to standard tape measurement, the mean systematic error with SDG measurement was only ?0.17 cm, but varied between ?0.10 and ?0.52 cm. Similarly, random error was relatively large, with standard deviations (and percentage coefficients of variation) averaging only 0.36 cm (and 3.8%), but varying between 0.14 and 0.61 cm (and 1.9 and 7.1%). However, at the stand scale, sampling errors (i.e. how well individual trees or shrubs selected for measurement of diameter represented the true stand population in terms of the average and distribution of diameter) generally had at least a tenfold greater influence on random errors in basal area estimates than errors in diameter measurements. This supports the use of diameter measurement tools that have high efficiency, such as the SDG. Use of the SDG almost halved the time required for measurements compared to the diameter tape. Based on these findings, recommendations include the following: (i) use of a tape to maximise accuracy when developing allometric models, or when monitoring relatively small changes in permanent sample plots (e.g. National Forest Inventories), noting that care is required in irregular-shaped, large-single-stemmed individuals, and (ii) use of a SDG to maximise efficiency when using inventory methods to assess basal area, and hence biomass or wood volume, at the stand scale (i.e. in studies of impacts of management or site quality) where there are budgetary constraints, noting the importance of sufficient sample sizes to ensure that the population sampled represents the true population.     

Assessing soil lead contamination in Dallas Texas

During the summer of 1982, the U.S. Environmental Protection Agency conducted a comprehensive multimedia environmental monitoring program in the vicinity of two secondary lead smelters and at one reference site in Dallas, Texas. This monitoring program included a major soils investigation with the collection and analysis of over 2700 soil samples. In addition, approximately 1000 blood and 840 house dust samples were collected and analyzed for their lead content.Utilizing geostatistics and the data obtained from a portion of the soil samples, isopleths of constant soil lead concentrations within each of the three monitoring sites were identified. Presented are the soil monitoring strategy and the geostatistical techniques selected for identifying the distributions of soil lead patterns at each of the three monitoring sites. In addition, the soil sampling and analytical methods used, the sample handling and preparation procedures, and the geostatistical results obtained are identified.     

Development of the Coastal Intensive Site Network (CISNET)

The U.S. Environmental Protection Agency (EPA), National Oceanic and Atmospheric Administration (NOAA), and National Aeronautics and Space Administration (NASA) have formed a partnership to establish pilot sites for the development of a network known as the Coastal Intensive Site Network (CISNet). CISNet is composed of intensive, long-term monitoring and research sites around the U.S. marine and Great Lakes coasts. In this partnership, EPA and NOAA are funding research and monitoring programs at pilot sites that utilize ecological indicators and investigate the ecological effects of environmental stressors. NASA is funding research aimed at developing a remote sensing capability that will augment or enhance in situresearch and monitoring programs selected by EPA and NOAA. CISNet has three objectives: 1) to develop a sound scientific basis for understanding ecological responses to anthropogenic stresses in coastal environments, including the interaction of exposure, environment/climate, and biological/ecological factors in the response, and the spatial and temporal nature of these interactions, 2) to demonstrate the value of developing data from selected sites intensively monitored to examine the relationships between changes in environmental stressors, including anthropogenic and natural stresses, and ecological response, and 3) to provide intensively monitored sites for development and evaluation of indicators of change in coastal systems.     

我国环境监测方法标准体系的现状与发展构想

综述了我国环境监测方法标准体系的发展历程和现状,分析了环境监测方法标准在数量和内容及技术水平等方面不能满足环境管理需要、方法标准体系不健全、科学性有待提高等问题,提出加强环境监测方法标准的顶层设计、构建天地一体化的环境监测方法标准体系、实行动态管理并加强质控、加强监测科研借鉴国际经验等发展构想。     

汶川特大地震环境应急监测回顾与思考

以汶川特大地震后成都市环境应急监测为案例,在回顾历时近3个月的环境应急监测基础上,围绕应急监测组织体系、方案制定、能力建设等内容进行了分析并提出了建议,旨在对建立我国应对特大自然灾害或环境污染事故的环境应急监测预警体系进行初探。     

Sampling for landscape elements—a case study from Lower Saxony,Germany

The estimation of coverage, i.e., the proportion of the total area in a study region covered by a given target class, is essential to many aspects of environmental monitoring. We analyze and compare the efficiency of different sample-based approaches for the estimation of coverage of different land cover classes from aerial imagery in a case study in Lower Saxony, Germany on the basis of the estimated standard errors. A complete delineation of vegetation classes in n?=?279 aerial photo plots of 400 × 400 m thrown onto the study region of 1,117.7 km² in accordance with a systematic grid is compared to different configurations of line intercept sampling and clusters of points. The observation designs under study are characterized by different complexity and total size of the observation units and therefore also to the efforts related to yield a single observation. Especially for those classes that cover a relatively large proportion of the sampling frame, our results show that difference in performance between the different designs are negligible. A cluster of four transects of 200 m each allows estimating the area of land cover classes with high coverage with nearly similar precision as a complete mapping of fixed area plots of 16 ha each. Clusters of points show unexpected high precision for the estimated coverage of land cover classes with relatively high coverage.     

Assessing temporal representativeness of water quality monitoring data

The effectiveness of different monitoring methods in detecting temporal changes in water quality depends on the achievable sampling intervals, and how these relate to the extent of temporal variation. However, water quality sampling frequencies are rarely adjusted to the actual variation of the monitoring area. Manual sampling, for example, is often limited by the level of funding and not by the optimal timing to take samples. Restrictions in monitoring methods therefore often determine their ability to estimate the true mean and variance values for a certain time period or season. Consequently, we estimated how different sampling intervals determine the mean and standard deviation in a specific monitoring area by using high frequency data from in situ automated monitoring stations. Raw fluorescence measurements of chlorophyll a for three automated monitoring stations were calibrated by using phycocyanin fluorescence measurements and chlorophyll a analyzed from manual water samples in a laboratory. A moving block bootstrap simulation was then used to estimate the standard errors of the mean and standard deviations for different sample sizes. Our results showed that in a temperate, meso-eutrophic lake, relatively high errors in seasonal statistics can be expected from monthly sampling. Moreover, weekly sampling yielded relatively small accuracy benefits compared to a fortnightly sampling. The presented method for temporal representation analysis can be used as a tool in sampling design by adjusting the sampling interval to suit the actual temporal variation in the monitoring area, in addition to being used for estimating the usefulness of previously collected data.     

Detecting change in advance tree regeneration using forest inventory data: the implications of type II error

Achieving adequate and desirable forest regeneration is necessary for maintaining native tree species and forest composition. Advance tree seedling and sapling regeneration is the basis of the next stand and serves as an indicator of future composition. The Pennsylvania Regeneration Study was implemented statewide to monitor regeneration on a subset of Forest Inventory and Analysis plots measured by the U.S. Forest Service. As management techniques are implemented to improve advance regeneration, assessments of the change in the forest resource are needed. When the primary focus is on detecting change, hypothesis tests should have small type II (β) error rates. However, most analyses are based on minimizing type I (α) error rates and type II error rates can be quite large. When type II error rates are high, actual improvements in regeneration can remain undetected and the methods that brought these improvements may be deemed ineffective. The difficulty in detecting significant change in advance regeneration when small type I error rates are given priority is illustrated. For statewide assessments, power (1-β) to detect changes in proportion of area having adequate advance regeneration is relatively weak (≤0.5) when the change is smaller than 0.05. For evaluations conducted at smaller spatial scales, such as wildlife management units, the reduced sample size results in only marginal power even when relatively large changes (≥0.20) in area proportion occur. For fixed sample sizes, analysts can consider accepting larger type I error rates to increase the probability of detecting change (smaller type II error rates) when it occurs, such that management methods that positively affect regeneration can be identified.     

应用统计分析方法优化布点监测区域环境噪声

应用统计分析方法,对湖南省湘潭市2001年城区环境噪声网格布点及其监测结果总体进行了区域环境噪声监测点的最优集合,并通过网格布点法与优化布点法对该市2002年和2003年环境噪声监测结果进行了对比检验,结果表明,两种方法监测的等效声级和标准差平均值均<1dB(A),监测结果之间无显著性差异。     

火电厂石灰石-石膏脱硫设施环保验收监测若干问题的探讨

以"十一五"期间较为常见的火电厂石灰石-石膏脱硫设施竣工环保验收监测为例,着重就验收过程监测布点、设施处理效率计算、污染物总量核算、减排项目标准执行以及环境管理检查中存在的问题进行探讨,提出解决问题的方法与思路,为今后火电厂竣工环保验收监测工作提供借鉴。     

Patchy distributions: Optimising sample size

A method for estimating sample size which does not require an a priori definition of desired precision, or the assumption that the population is normally distributed with constant variance, has recently been proposed. This paper discusses this method and presents five modifications which make the method easier to use and reduce the probability of estimating a larger sample size than is actually required. The method is extended and used to estimate the mean abundance of patchily distributed benthic organisms. The technique can be used to guide the design of any environmental sampling programme, be it physical, chemical or biological, where comparisons between times and/or locations are required. Trade-offs between numbers of replicates and numbers of levels/sites are discussed.     

Pollutant monitoring in the Olympic National Park Biosphere Reserve

Interest in global contamination has been instrumental in the establishment of over 33 Biosphere Reserves in the United States. These reserves include pristine areas that have been protected from industrial development. They serve as areas in which present and future environmental pollution can be assessed.Pollutant monitoring studies are being conducted in the Olympic National Park Biosphere Reserve by the U.S. Park Service and the U.S. Environmental Protection Agency. Studies are designed to identify levels of trace element and organic contaminants in physical and biological media. Ten remote sites were selected for intensive sampling. These areas were located in the Hoh, Quinault, and Dosewallips River drainages; at Anderson and Grand Pass; near Ozette Lake and, at the northern edge of Blue Glacier. Their proximity to vehicle-traveled roads varied from 3 to 20 kilometers.Samples were taken in air, water, soil, litter and vegetation. Samples will be analyzed for organic and heavy metal contaminants. Airborne particulate size and chemical characterization is being investigated.     

Effects of geomorphology, habitat, and spatial location on fish assemblages in a watershed in Ohio, USA

In this paper, we evaluate relationships between in-stream habitat, water chemistry, spatial distribution within a predominantly agricultural Midwestern watershed and geomorphic features and fish assemblage attributes and abundances. Our specific objectives were to: (1) identify and quantify key environmental variables at reach and system wide (watershed) scales; and (2) evaluate the relative influence of those environmental factors in structuring and explaining fish assemblage attributes at reach scales to help prioritize stream monitoring efforts and better incorporate all factors that influence aquatic biology in watershed management programs. The original combined data set consisted of 31 variables measured at 32 sites, which was reduced to 9 variables through correlation and linear regression analysis: stream order, percent wooded riparian zone, drainage area, in-stream cover quality, substrate quality, gradient, cross-sectional area, width of the flood prone area, and average substrate size. Canonical correspondence analysis (CCA) and variance partitioning were used to relate environmental variables to fish species abundance and assemblage attributes. Fish assemblages and abundances were explained best by stream size, gradient, substrate size and quality, and percent wooded riparian zone. Further data are needed to investigate why water chemistry variables had insignificant relationships with IBI scores. Results suggest that more quantifiable variables and consideration of spatial location of a stream reach within a watershed system should be standard data incorporated into stream monitoring programs to identify impairments that, while biologically limiting, are not fully captured or elucidated using current bioassessment methods.     

农业面源污染对我国农村地表水的影响与对策研究

基于2015—2021年我国农村地表水环境质量监测数据,分析了农村地表水环境质量状况特征;选取农业农村社会经济活动相关参数,与农村地表水中主要超标因子的超标比例进行了相关性分析;以2020年为基准年,对全国31个行政区,涵盖农村地表水水质状况、农业农村活动水平和污染压力、环境容量3个方面的9个指标进行了聚类分析。结果表明,我国农村地表水的变化趋势、季节特点和主要超标因子等表现出明显的农业面源污染特征;乡村人口、农业投入品使用量和经济作物种植比例等参数与主要超标指标具有较强的相关性（R＞0.9）;聚类分析将全国31个行政区划分为7种不同的农业面源污染类型。提出,应根据不同地区农业面源污染特点,因地制宜地推进标准化规模养殖、畜禽粪污资源化利用、化肥减量行动、高效低风险农药推广等农业面源污染治理措施,进一步加大农村生活污水处理设施建设,同时,完善农村环境质量监测网络,加强农业面源污染监测和评估。     

BOD生物传感器快速测定方法应用与探讨

介绍了微生物传感器快速测定生化需氧量(BOD)的方法,通过对标准溶液、工业废水、地表水、污水处理厂废水的检测,分析其精密度和准确度,通过与BOD_5的比对,对方法的存在问题及适用性进行了探讨和研究,为该方法的发展及其在环境监测中的实际应用提供了技术依据。     

羽绒工业建设项目竣工环境保护验收监测实例

以某水洗羽毛绒企业为例,从监测依据、评价标准、污染源与防治措施、监测内容、监测结果评价等方面,对羽绒工业建设项目竣工环境保护验收监测作实例分析。针对监测过程中需要关注的如单位产品基准排水量、无规律间歇性排水的污染物总量核算,以及恶臭气体无组织排放监测布点等问题,提出了解决方案。     

Quality assurance and quality control data validation procedures used for the Love Canal and Dallas lead soil monitoring programs

Public awareness of soils contamination has increased in recent years due in part to the notoriety associated with the indiscriminate release, packaging, transporting and disposal of hazardous materials. In 1980, and again in 1982, the U.S. Environmental Protection Agency (EPA) was responsible for designing, implementing and conducting environmental monitoring programs at Love Canal in Niagara Falls, New York, and in Dallas, Texas, that dealt with suspected contaminated soils. Both of these monitoring programs were conducted over a relatively short time with the collection and analysis of over 4000 soil samples. The methods employed by the Environmental Protection Agency for providing soil data that was scientifically valid and of defensible quality for each of these monitoring programs are presented. Also, methods for identifying data bias, its precision and its uncertainty are identified.