Sampling and Surveying Radiological Environments

By: Mark E. Byrnes

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Paperback | 2 December 2019 | Edition Number 1

At a Glance

Paperback
436 Pages

Dimensions(cm)
23.4 x 15.6 x 2.26

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Private landowners or Federal Agencies responsible for cleaning up radiological environments are faced with the challenge of clearly defining the nature and extent of radiological contamination, implementing remedial alternatives, then statistically verifying that cleanup objectives have been met. Sampling and Surveying Radiological Environments provides the how-tos for designing and implementing cost effective and defensible sampling programs in radiological environments, such as those found in the vicinity of uranium mine sites, nuclear weapons production facilities, nuclear reactors, radioactive waste storage and disposal facilities, and nuclear accidents. It includes downloadable resources that walk you through the EPA's Data Quality Objectives(DQO) procedures and provides electronic templates you can complete and print.
Sampling and Surveying Radiological Environments addresses all of the major topics that will assist you in designing and implementing statistically defensible sampling programs in radiological environments, including:

Summary of the major environmental laws and regulations that apply to radiological sites, and advice on regulatory interfacing
? Internet addresses where you can find regulations pertaining to each States

Theory of radiation detection and definitions of common radiological terminology

Statistics and statistical software that apply to the environmental industry

Details on commercially available radiological instrumentation and detection systems

Building decontamination and decommissioning, radiological and chemical equipment decontamination procedures, and tank/drum/remote characterization

Standard operating procedures for collecting environmental media samples

Guidance on sample preparation, documentation, and shipment

Guidance on data verification/validation, radiological data management, data quality assessment (DQA)

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