The human genome is the counterpart to the human exposome with respect to the gene × environment interaction that describes health state and outcome. The genome has already been sequenced and is in the process of being assessed for specific functionality; to similarly decode the exposome will require the measurement and interpretation of suites of biomarker compounds in biological media such as blood, breath and urine. Of these, exhaled breath provides some important advantages for community or population-based studies in that the supply is essentially unlimited, the sampling procedures are non-invasive and can be self-administered, and there are little, if any, infectious wastes generated. The main concerns are to document a variety of compounds in breath, to assess what compounds and concentrations are considered statistically 'normal' in the healthy or unremarkably exposed population, and what graphic and mathematical approaches can be applied to assess outlier measurements as perturbations to the healthy exposome. In this paper, we explore a data set of exhaled breath measurements of exogenous exposures to jet fuel and develop summary statistics and variable clustering methods to establish between-group and intrinsic within-sample patterns that could be used to assess the status of random subjects.