1.1 本指南的范围和目的是为评估、合规和纠正措施环境监测计划提供各种统计方法。虽然本文提供的方法适用于许多环境监测问题，并且通常是最佳的，但它们并不排除使用其他统计方法，这些方法可能对某些特定地点的应用同样有用，甚至更有用。 1.2 以下各节详细介绍了环境监测（土壤、地下水、空气、地表水和废物流）评估和纠正措施计划中使用的选定统计程序。 1.3 以下章节中描述的统计方法应作为指导。其他方法也可能适用于现场特定条件，或用于监测本文件中未介绍的情况或媒体。 1.4 这种做法提供了有组织的信息收集或一系列选择，并不建议采取具体行动。 本文件不能取代教育、经验和专业判断。并非本惯例的所有方面都适用于所有情况。本ASTM标准不代表或取代在不考虑项目的许多独特方面的情况下判断给定专业服务是否充分的谨慎标准。本文件标题中的“标准”一词仅表示该文件已通过ASTM共识程序获得批准。 1.5 本标准并非旨在解决与其使用相关的所有安全问题（如有）。本标准的用户有责任在使用前制定适当的安全和健康实践，并确定监管要求的适用性。 ====意义和用途====== 5.1 本标准主要用于评估、合规和纠正措施环境监测计划（例如，可能污染地下水的设施）。 该指南的意义在于，它提出了一种统计方法，允许将地下水数据与监管和/或基于健康的限制进行比较。 5.2 当然，可以应用于环境现场的检测、评估和纠正措施监测计划的统计方法得到了大量支持。 注1: 例如，在美国，90 % 美国环保局的SW846（第9章）中使用了平均值的置信上限（UCL）来确定废物是否有害。如果UCL小于特定危险废物代码的标准，则即使某些单个测量值超过标准，该废物也不是危险废物。同样，在美国环保局对RCRA设施地下水监测数据的统计分析中，临时最终指南的附录（1992年） ( 2. ) ，建议使用分布的平均值和各种上百分位的置信区间进行评估和纠正措施。 有趣的是，1989年和1992年美国环保局的指导文件 ( 2. , 3. ) 建议使用较低的95 % 置信限（LCL）作为确定评估监测中是否超过标准的工具。 该领域的最新指南要求在评估监测中使用LCL，在纠正措施中使用UCL。这样，只有当真实浓度超过标准或标准的置信度很高时，才会触发纠正措施，而纠正措施会一直持续到真实浓度低于标准或标准的置信度很高时。这也是本指南中采用的一般方法。 5.3 评估和纠正措施监测计划中需要统计方法的原因有几个。首先，一次测量几乎没有显示出感兴趣采样位置的真实浓度，并且只有一个样本无法确定测量的浓度是典型值还是极值。 目的是将真实浓度（或包含真实浓度的某个区间）与相关标准或标准进行比较。其次，在许多情况下，感兴趣的成分是自然存在的（例如金属），自然存在的浓度可能超过相关标准。在这种情况下，相关的比较是背景（例如，场外土壤或上梯度地下水），而不是固定的标准。因此，背景数据应具有统计特征，以获得自然发生浓度上限的统计估计，从而可以放心地确定现场浓度是否高于背景水平。第三，通常需要在多个采样点将多个潜在的关注成分与标准或背景进行比较。随着比较的数量越来越多，仅仅是偶然就会出现超越。这个问题的统计方法可以减少假阳性结果的可能性。 5.4 近年来，检测监测的统计方法得到了很好的研究（见Gibbons，1994a，1996，美国环保局1992） ( 2. , 4. , 5. ) 和实践 D6312 ，原为PS 64-96，由Gibbons、Brown和Cameron撰写，1996年）。虽然同样重要，但评估监测、第一阶段和第二阶段调查、持续监测和纠正措施监测的统计方法受到的关注较少（Gibbons和Coleman，2001） ( 6. ) . 5.5 本指南总结于 图1 ，它提供了一个流程图，说明了为评估和纠正措施计划开发统计评估方法的步骤。 图1 说明了选择一般比较策略的各种决策点，以及如何根据现场具体情况选择统计方法。

1.1 The scope and purpose of this guidance is to present a variety of statistical approaches for assessment, compliance and corrective action environmental monitoring programs. Although the methods provided here are appropriate and often optimal for many environmental monitoring problems, they do not preclude use of other statistical approaches that may be equally or even more useful for certain site-specific applications. 1.2 In the following sections, the details of select statistical procedures used in assessment and corrective action programs for environmental monitoring (soil, groundwater, air, surface water, and waste streams) are presented. 1.3 The statistical methodology described in the following sections should be used as guidance. Other methods may also be appropriate based on site-specific conditions or for monitoring situations or media that are not presented in this document. 1.4 This practice offers an organized collection of information or a series of options and does not recommend a specific course of action. This document cannot replace education, experience and professional judgements. Not all aspects of this practice may be applicable in all circumstances. This ASTM standard is not intended to represent or replace the standard of care by which the adequacy of a given professional service must be judged without consideration of a project's many unique aspects. The word Standard in the title of this document only means that the document has been approved through the ASTM consensus process. 1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory requirements prior to use. ====== Significance And Use ====== 5.1 The principal use of this standard is in assessment, compliance and corrective action environmental monitoring programs (for example, for a facility that could potentially contaminate groundwater). The significance of the guidance is that it presents a statistical method that allows comparison of groundwater data to regulatory and/or health based limits. 5.2 Of course, there is considerable support for statistical methods applied to detection, assessment and corrective action monitoring programs that can be applied to environmental sites. Note 1: For example, in the United States, the 90 % upper confidence limit (UCL) of the mean is used in USEPA’s SW846 (Chapter 9) for determining if a waste is hazardous. If the UCL is less than the criterion for a particular hazardous waste code, then the waste is not a hazardous waste even if certain individual measurements exceed the criterion. Similarly, in the USEPA Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities Addendum to the Interim Final Guidance (1992) ( 2 ) , confidence intervals for the mean and various upper percentiles of the distribution are advocated for assessment and corrective action. Interestingly, both the 1989 and 1992 USEPA guidance documents ( 2 , 3 ) suggest use of the lower 95 % confidence limit (LCL) as a tool for determining whether a criterion has been exceeded in assessment monitoring. The latest guidance in this area calls for use of the LCL in assessment monitoring and the UCL in corrective action. In this way, corrective action is only triggered if there is a high degree of confidence that the true concentration has exceeded the criterion or standard, whereas corrective action continues until there is a high degree of confidence that the true concentration is below the criterion or standard. This is the general approach adopted in this guide, as well. 5.3 There are several reasons why statistical methods are needed in assessment and corrective action monitoring programs. First, a single measurement indicates very little about the true concentration in the sampling location of interest, and with only one sample it cannot be determined if the measured concentration is a typical or an extreme value. The objective is to compare the true concentration (or some interval that contains it) to the relevant criterion or standard. Second, in many cases the constituents of interest are naturally occurring (for example, metals) and the naturally existing concentrations may exceed the relevant criteria. In this case, the relevant comparison is to background (for example, off-site soil or upgradient groundwater) and not to a fixed criterion. As such, background data should be statistically characterized to obtain a statistical estimate of an upper bound for the naturally occurring concentrations so that it can be confidently determined if onsite concentrations are above background levels. Third, there is often a need to compare numerous potential constituents of concern to criteria or background, at numerous sampling locations. By chance alone there will be exceedances as the number of comparisons becomes large. The statistical approach to this problem can decrease the potential for false positive results. 5.4 Statistical methods for detection monitoring have been well studied in recent years (see Gibbons, 1994a, 1996, USEPA 1992 ( 2 , 4 , 5 ) and Practice D6312 , formerly PS 64-96 authored by Gibbons, Brown and Cameron, 1996). Although equally important, statistical methods for assessment monitoring, Phase I and II Investigations, on-going monitoring and corrective action monitoring have received less attention, (Gibbons and Coleman, 2001) ( 6 ) . 5.5 The guide is summarized in Fig. 1 , which provides a flow-chart illustrating the steps in developing a statistical evaluation method for assessment and corrective action programs. Fig. 1 illustrates the various decision points at which the general comparative strategy is selected, and how the statistical methods are to be selected based on site-specific considerations.