[en] In recent years, environmental impact assessment of nuclear facilities has become synonymous with the accumulation and interpretation of near-background environmental radiation surveillance data. However, data interpretation techniques have not completed the transition from dealing with readily detectable atomospheric radioactivity contamination to the very low levels of radiation now present. Regulatory requirements for collection and interpretation of low-level environmental surveillance data necessitate the development of more effective data interpretation techniques. The application of distribution analysis techniques to interpretation of near-background data is presented as it applies to several important problem areas. Specifically treated are (1) the quantification of typical background environmental levels and expected maximum variability of these levels, (2) systemization of seasonal or yearly variations in background, (3) identification and differentiation of plant contributions to environmental contamination inventories from naturally occurring contamination, and (4) derivation of annual average concentration numbers from data including less-than-detectable values. Present methodology being applied to these problem areas is discussed and compared with capabilities and mechanics of distribution analysis techniques. The mechanics of applying distribution analysis methodology are illustrated by organizing authentic environmental surveillance data and analysing several of the example problem areas by these techniques. The objective of this discussion is to present the mechanics of application in a format for easy and direct application to problems related to the interpretation of near-background environmental surveillance data. (author)