Chemical transformations can take place in the environment (e.g. photo-or biological degradation) or within human-made infrastructures, such as wastewater treatment plants. Depending on the type of reactions and the structure of the parent compound, there may be more than 100 new chemicals formed at even the first level of the transformation tree. Considering the costs and complexity associated with performing transformation experiments, the expansion of such methods to the exposome chemical space is impossible, Figure . An alternative to this experimentally driven approach has been the predictive models where a combination of machine learning and heuristic methods are used. However, these methods are very uncertain, opaque, and are limited to a few reaction pathways while stopping at shallow levels (e.g. first or second levels) in the transformation tree. This implies that our current estimates of the coverage of the exposome chemical space are orders of magnitude smaller than its true size, given the number of possible reactions. unknown chemical space (gray), exposome chemical space (yellow), measurable chemical space (blue), measured chemical space (magenta), and identified/characterized chemical space (green) whereas b) shows the chemicals in US-EPA CompTox with 800 k unique structures. The Principal Component plot was generated using six elemental mass defects and monoisotopic mass of the chemicals in US-EPA CompTox (details of these calculations are provided elsewhere ). It should be noted that the size of subspaces are meant only for visualization purposes and are not representative of the true size of these spaces.