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Significance and Use
5.1 Studies of indoor air problems are often iterative in nature. A thorough engineering evaluation of a building () is sometimes sufficient to identify likely causes of indoor air problems. When these investigations and subsequent remedial measures are not sufficient to solve a problem, more intensive investigations may be necessary.
5.2 This guide provides the basis for determining when probability sampling methods are needed to achieve statistically defensible inferences regarding the goals of a study of indoor air quality. The need for probability sampling methods in a study of indoor air quality depends on the specific objectives of the study. Such methods may be needed to select a sample of people to be asked questions, examined medically, or monitored for personal exposures. They may also be needed to select a sample of locations in space and time to be monitored for environmental contaminants.
5.3 This guide identifies several potential obstacles to proper implementation of probability sampling methods in studies of indoor air quality in buildings and presents procedures that overcome those obstacles or at least minimize their impact.
5.4 Although this guide specifically addresses sampling people or locations across time within a building, it also provides important guidance for studying populations of buildings. The guidance in this document is fully applicable to sampling locations to determine environmental quality or sampling people to determine environmental effects within each building in the sample selected from a larger population of buildings.
1.1 This guide covers criteria for determining when probability sampling methods should be used to select locations for placement of environmental monitoring equipment in a building or to select a sample of building occupants for questionnaire administration for a study of indoor air quality. Some of the basic probability sampling methods that are applicable for these types of studies are introduced.
1.2 Probability sampling refers to statistical sampling methods that select units for observation with known probabilities (including probabilities equal to one for a census) so that statistically defensible inferences are supported from the sample to the entire population of units that had a positive probability of being selected into the sample.
1.3 This guide describes those situations in which probability sampling methods are needed for a scientific study of the indoor air quality in a building. For those situations for which probability sampling methods are recommended, guidance is provided on how to implement probability sampling methods, including obstacles that may arise. Examples of their application are provided for selected situations. Because some indoor air quality investigations may require application of complex, multistage, survey sampling procedures and because this standard is a guide rather than a practice, the references in are recommended for guidance on appropriate probability sampling methods, rather than including expositions of such methods in this guide.
1.4 Units—The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.
1.5 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
2. Referenced Documents (purchase separately) The documents listed below are referenced within the subject standard but are not provided as part of the standard.
D1356 Terminology Relating to Sampling and Analysis of Atmospheres
ICS Number Code 13.040.01 (Air quality in general)
|Link to Active (This link will always route to the current Active version of the standard.)|
ASTM D5791-95(2017), Standard Guide for Using Probability Sampling Methods in Studies of Indoor Air Quality in Buildings, ASTM International, West Conshohocken, PA, 2017, www.astm.orgBack to Top