Assessing background particulate contamination in an historic building – surface lead loading and contamination

ABSTRACT

Investigation of suspect surface contamination in a building may require comparative sampling across different zones to provide meaningful information with regard to contaminant sources, pathways and/or extent of dispersal. However, evaluation of the data using traditional null hypothesis significance testing (NHST) based upon the mean may result in misleading inference when encountering erratic distributions typical of environmental contaminant data. Sampling data (n = 90) for lead content in surface dust collected throughout a historic building with suspect contamination from uncontrolled disturbance to lead coatings were evaluated using traditional NHST and randomization/permutation inference; the latter metric was the maximum difference in frequency of detection (Δfd _max), to directly calculate the probability of the observed differences. In the examples for lead in surface dust presented herein, areas with “lower” mean concentration and/or no significant difference via NHST actually represented “greater contamination,” as Δfd _max indicated a greater probability of encountering lead at higher concentrations. Resulting conclusions with regard to sources and pathways contradicted those generated from traditional NHST, and underscore the need to recognize differences in applicability of different inference approaches, depending upon the distribution of the data and the particular problem. This is particularly relevant for forensic purposes.

Implications

The use of permutation/randomization inference to gain insight into sources and pathways of contamination may be more appropriate than the conventional Neyman/Pearson (N/P) logic in negative hypothesis significance testing (NHST). This suggests a broader understanding by environmental professionals of the assumptions and limitations of NHST and alternative inference such as through permutation/randomization is warranted.

Disclosure statement

No potential conflict of interest was reported by the author.

Additional information

Notes on contributors

R. Christopher Spicer

R. Christopher Spicer is Director of Industrial Hygiene for Gallagher Bassett Technical Services, and is a Certified Industrial Hygienist (CIH) and a Certified Hazardous Materials Manager (CHMM). He has more than thirty five years of experience in environmental consulting involving a variety of general and indoor environmental issues facing the construction, real estate and insurance communities. He currently is a member of ASTM committees on mold and asbestos and has previously published several peer reviewed technical articles on environmental data assessment.